Health GIS Conference Proceedings 2020

P a g e | 24 other areas. Mammogram and ultrasound services of these hospitals, mainly at Kota Bharu district. were offered in Hospital Universiti Sains Malaysia This means that majority of the patients live near (Hospital USM), Hospital Raja Perempuan Zainab health facilities and they have more tendency to II (HRPZ II), Kota Bharu Medical Centre and KPJ utilize these facilities than those living far away Perdana Specialist Hospital situated at Kota Bharu (Mizen et al., 2015). Our finding was supported by district. However, at other district, only Hospital previous study conducted in Pahang state. This Kuala Krai offered breast cancer screening services study found that 97.7% of the respondents live (Breast Cancer Foundation, n.d). Apart from that, within 20 km radius from the nearest hospital or high population density might contribute to high within 5 km radius from the nearest clinic (CRP cancer incidences detected where vast majority of Report, 2009). Hence, people living in the area with Kota Bharu’s population is ethnically Malay. As good geographical access were able to get early stated by Azizah et al., (2015), most of the patients diagnosis of breast cancer by medical professionals diagnosed with breast cancer in Kelantan were at the healthcare centres. However, the accessibility Malay populations (Azizah et al., 2015). Apart from to public hospitals remains poor in some districts, that, air pollution and more exposure to carcinogens especially rural districts in the state which imply (Mahdavifar et al., 2016) might contribute to higher that patients in this area must travel longer distance incidences observed in these high-risk areas. and duration to reach the nearest facilities. As a Meanwhile, cold spots were in the southwest areas result, they might not repeat the visit to healthcare of the state. Low incidences of breast cancer cases at facilities (Awoyemi et al., 2011). Studies have these areas might be due to lack of people were shown that women who live far away from facilities screened and low awareness among population were less likely to undergo mammogram screening living in these areas. than those who live nearby the facilities. An In addition, it was found that distribution of breast example is a local study that showed non-compliant cancer incidences was spatially clustered. The patients for mammogram lived far away from clustering incidence pattern were observed mainly at facilities (mean distance of 51.1 km) as compared to the northern part of the state. Among the factors that control group (26.5 km) (Mahmud et al., 2018). might contribute to this clustering pattern were With almost none breast cancer screening facilities presence of higher carcinogenic environmental offered in the rural area of the state, this can be a factors and other risk factors in the high-risk areas. major obstacle for communities to reach the Furthermore, registration of breast cancer cases facilities and can inhibit access (Graham et al., possibly more complete in these areas as compared 2010). In addition, travel burden also reported to to other part of the state and faster or more refined cause delay in receiving treatment (Awoke et al., diagnostic technique might also be one of the 2019) and associated with higher health risks or potential factors (Ahmadi et al., 2018). Invasive unfavourable outcomes (Becher et al., 2004). Hence, carcinoma of no special type was the most common patients were more likely to present at advanced histological subtypes of breast carcinoma observed stage of cancer. Finding from a local study at Sabah in this study, which accounted for 185 cases (90%) state showed that patients who presented with late out of total cases reported. Similarly, a local study stage of cancer were also poor, non-educated and conducted in Sabah state also reported the same from rural areas (Leong et al., 2007). Apart from pattern, whereby this histologic subtype makes up longer travel time, cost and stress might as well act 88.4% of the cases (Leong et al., 2007). Moreover, as a major barrier to access healthcare facilities it was found that most of the death occur from this especially in rural communities who are more histologic subtype, constituting for 78.6% of the familiar with traditional medicine (Buor, 2003). cases among breast cancer women in Kelantan Furthermore, the population living in this poor between 2007 to 2011 (Hanis et al., 2019). In this geographical access area may have poor awareness case, many factors might play roles in the regarding breast cancer risks and the importance to development of breast cancer. Nulliparity, seek for early medical attention (Ahmadi et al., overweight/obesity, family history of breast cancer 2018). Hence, this study helps to highlight areas that and the use of oral contraceptive were the need attention to improve the delivery of health care significant risk factors of breast cancer in Kelantan services to the population in Kelantan. population as reported by a local study (Norsa’adah et al., 2005). 5. CONCLUSION This study mapped the spatial distribution of breast The result of this study suggests that cancer incidences and evaluate the geographical accessibility to public hospitals appears good with accessibility to all public hospitals in Kelantan. It 60.19% of the cases located within 10 km distance International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

P a g e | 25 was found that the breast cancer cases were Buor, D., 2003, Analysing the Primacy of Distance clustered, and the highest incidences of breast in the Utilization of Health Services in the cancer occurred at the northern part of Kelantan, Ahafo-Ano South District, Ghana Int. J. Health where the state capital city, Kota Bharu was located. Plan. Manag., Vol. 18 (4), 293-311 Furthermore, the distribution of high-risk breast cancer areas was focused at the northwest and CRP Report, 2009, A Report on Community northeast areas of the state. Whereas, the cold-spot Survey. Department of Social and Preventive areas were found at the southwest areas of the state. Medicine, Faculty of Medicine, University of In addition, most of the cases were accessible to all Malaya. public hospitals in Kelantan state. The findings from this study are useful for public health authorities and Graham, J. E., Fisher, S. R., Berges, I. M., Kuo, Y. health practitioners in planning strategies and F. and Ostir, G., 2010, Walking Speed Threshold interventions by directing more efforts towards for Classifying Walking Independence in population in the hot-spot areas that will minimize Hospitalized Older Adults. Phys Ther., Vol. the breast cancer incidences in Kelantan. 90(11), 1591–1597. ACKNOWLEDGMENT Guajardo, O.A. and Oyana, T. J., 2009, A Critical Author would like to thank Hospital Universiti Assessment of Geographic Clusters of Breast Sains Malaysia and School of Medical Sciences, and Lung Cancer Incidences among Residents Universiti Sains Malaysia for the support given. Living Near the Tittabawassee and Saginaw Rivers, Michigan, USA. J Environ Public REFERENCES Health, 1-16, DOI:10.1155/2009/316249. Ahmadi, A., Ramazani, R., Rezagholi, T. and Ghoncheh, M., Momenimovahed, Z. and Salehiniya, Yavari, P., 2018, Incidence Pattern And Spatial H., 2016, Epidemiology, Incidence and Analysis of Breast Cancer in Iranian Women: Mortality of Breast Cancer in Asia. Asian Pac J Geographical Information System applications. Cancer Prev., Vol. 17: 47-52. East Mediterr Health J. Vol. 24(4):360–367. Hanis, T. M., Yaacob, N. M., Hairon, S. M., Awoyemi, T. T., Obayelu, O. A. and Opaluwa, H. I., Abdullah, S., Nordin, N., Hashimah Abdullah, 2011, Effect of Distance on Utilization of Health N. and Md Ariffin, M. F., 2019, Modelling Care Services in Nigeria Rural Kogi State. Hum Excess Mortality among Breast Cancer Patients Ecol., Vol. 35(1):1–9. in the North East Region of Peninsular Malaysia, 2007–2011: a population-based study. BMC Awoke, N., Dulo, B. and Wudneh, F., 2019, Total Public Health, Vol. 19(1). DOI:10.1186/s12889- Delay in Treatment of Tuberculosis and 019-8113-2. Associated Factors among New Pulmonary TB Patients in Selected Health Facilities of Gedeo Herrmann, C., Ess, S., Thürlimann, B., Probst- Zone, Southern Ethiopia, 2017/18. Hensch, N. and Vounatsou, P., 2015, 40 Years of Progress in Female Cancer Death Risk: A Interdisciplinary Perspectives on Infectious Bayesian Spatio-Temporal Mapping Analysis in Diseases, Vol. 3, 1-14. Switzerland. BMC Cancer, Vol. 15, 1-10. Azizah, A. M., Nor Saleha, I. T., Noor Hashimah, A., Asmah, Z.A. and Mastulu, W., 2015, International Agency of Research Cancer, World Malaysian National Cancer Registry Report Health Organization. GLOBOCAN 2020: 2007–2011. Ministry of Health. Available from https://gco.iarc.fr. Retrieved 26 Becher, H., Muller, O., Jahn, A., Gbangou, A., March 2021. Kynast-Wolf, G. and Kouyate, B., 2004, Risk Factors of Infant and Child Mortality in Rural Leong, B. D., Chuah, J. A., Kumar, V. M. and Yip, Burkina Faso. Bull World Health Organ, Vol. C. H., 2007, Breast Cancer in Sabah, Malaysia: a 82(4):265–73. Two Year Prospective Study. Asian Pacific Breast Cancer Foundation., n.d, Hospitals and Journal of Cancer Prevention:APJCP, Vol. 8(4), Clinics in Kelantan. Available from 525–529. https://www.breastcancerfoundation.org.my/hos pitals-and-clinics-in-kelantan (Retrieved 25 Madhu, B., Srinath, K. M., Rajendran, V., Devi, M. March 2021) P., Ashok, N. C. and Balasubramanian, S., 2016, Spatio-Temporal Pattern of Breast Cancer— Case Study of Southern Karnataka, India. Journal of Clinical and Diagnostic Research. Vol. 10(4), LC20–LC24. Mahdavifar, N., Pakzad, R., Ghoncheh, M., Pakzad, I., Moudi, A. and Salehiniya, H., 2016, Spatial Analysis of Breast Cancer Incidence in Iran. Asian Pacific Journal of Cancer Prevention, International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

Cancer Control in Western Asia Special Issue, P a g e | 26 Vol. 17:59-64. Mahmu, A. and Aljuni, S. M., 2018, Availability Rocha-Brischiliari S. C., Andrade, L., Nihei, O. K., and Accessibility of Subsidized Mammogram Brischiliri, A., Hortelan, M. S., Carvalho, Screening Program in Peninsular Malaysia: A M.D.B., et al., 2018, Spatial Distribution of Preliminary Study Using Travel Impedance Breast Cancer Mortality: Socioeconomic Approach. PLoS ONE, Vol. 13(2), e0191764. Disparities and Access to Treatment in the State Mehrabani, D., Tabei, S., Heydari, S. T., Shamsina, of Parana, Brazil. Plos One. Vol. 31, 1–15. S., Shokrpour, N., Amini, M., Masoumi, S. J., Julaee, H ., Farahmand, M. and Manafi, A., Samat, N., Shattar, A. K. A., Sulaiman, Y., Ab 2008, Cancer Occurrence in Fars Province, Manan, A. and Weng, C. N., 2013, Investigating Southern Iran. Iran Red Crescent Med J., Vol. Geographic Distribution of Colorectal Cancer 10(4)314-322. Cases: An Example from Penang State, Merletti, F., Galassi, C. and Spadea, T., 2011, The Malaysia. Asian Soc. Sci, Vol. 9, 38–46. Socioeconomic Determinants of Cancer. Environ Health. Vol. 10(l1):S7. Samat, N., Jambi, D., Musa, N. S., Shatar, A.K.A., Mizen, A., Fry, R., Grinnell, D. and Rodgers, S. E., Ab Manan, A. and Sulaiman, Y., 2010, Using A 2015, Quantifying the Error Associated with Geographic Information System (GIS) in Alternative GIS-based Techniques to Measure Evaluating the Accessibility of Health Facilities Access to Health Care Services. AIMS Public for Breast Cancer Patients in Penang State, Heal. Vol. 2(4):746–761. Malaysia. Kajian Malaysia. Vol. 28 (1), 103- Mohebbi, M., Mahmoodi, M., Wolfe, R., 122. Nourijelyani, K., Mohammad, K., Zeraati, H. and Fotouhi, A., 2008, Geographical Spread of Santos, R. S. and Melo, E. C. P., 2011, Mortalidade Gastrointestinal Tract Cancer Incidence in the e Assistência Oncológica no rio de janeiro: Caspian Sea region of Iran: Spatial Analysis of Câncer de Mama E Colo Uterino. Esc Anna Nery Cancer Registry Data. BMC Cancer. Vol. 8, 137. (impr.). Vol. 15 (2): 410–416. Norsa'adah, B., Rusli, B. N., Imran, A. K., Naing, I. and Winn, T., 2005, Risk Factors of Breast Unger-Saldaña, K., 2014, Challenges to the Early Cancer in Women in Kelantan, Malaysia. Diagnosis and Treatment of Breast Cancer in Singapore Medical Journal, Vol. 46(12), 698– Developing Countries. World J Clin Oncol. Vol. 705. 5(3): 465–477. Yomralioglu, T., Colak, E. H. and Aydinoglu, A. C., 2009, Geo-Relationship between Cancer Cases and the Environment by GIS: A Case Study of Trabzon in Turkey. Int J Environ Res Public Health. Vol. 6, 3190-204. Zhu, Q., Zhang, X., Zai, H. Y., Jiang, W., Zhang, K. J., He, Y. Q. and Hu, Y., 2021, CircSLC8A1 Sponges miR-671 to Regulate Breast Cancer Tumorigenesis via PTEN/PI3k/Akt Pathway. Genomics, Vol. 113(1), 398-410. International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

P a g e | 27 GEOGRAPHIC DISTRIBUTION OF THYROID CANCER INCIDENCE: A TERTIARY CENTRE EXPERIENCE Nur Fatihah Mohd Zuhdi,1 Wan Faiziah Wan Abdul Rahman,2* Tengku Ahmad Damitri Al Astani Tengku Din,3 Ahmad Filza Ismail4 and Rosline Hassan5 1Department of Pathology, School of Medical Sciences, Universiti Sains Malaysia, 16150, Kubang Kerian, Kelantan, Malaysia, E-mail: [email protected] 2Department of Pathology, School of Medical Sciences, Universiti Sains Malaysia, 16150, Kubang Kerian, Kelantan, Malaysia & Hospital Universiti Sains Malaysia, 16150, Kubang Kerian, Kelantan, Malaysia E-mail: [email protected] 3Department of Chemical Pathology, School of Medical Sciences, Universiti Sains Malaysia, 16150, Kubang Kerian, Kelantan, Malaysia, E-mail: [email protected] 4Department of Community Medicine, School of Medical Sciences, Universiti Sains Malaysia, 16150, Kubang Kerian, Kelantan, Malaysia, E-mail: [email protected] 5Department of Hematology, School of Medical Sciences, Universiti Sains Malaysia, 16150, Kubang Kerian, Kelantan, Malaysia, E-mail: [email protected] *Corresponding author ABSTRACT Kelantan state recorded an increasing trend of thyroid cancer incidence with approximately 2.7% annual increment rate between 2006 and 2015. Geographical Information System (GIS) has been widely used in evaluating health data. Yet, there is limited data on spatial distribution of cancer in Malaysia. Hence, we aim to map the incidence of thyroid cancer cases in Kelantan state and perform the spatial analysis to determine distribution and pattern of cases and measure the distance from the existing public hospitals. Registries of patients diagnosed with thyroid carcinoma from the year of 2013 to 2020 were retrieved from medical record office. The year of diagnosis, age, gender, residential addresses and histological subtypes were obtained. The latitudes and longitudes of patients’ residences and public hospitals were acquired using Global Positioning System (GPS) and all data were recorded in Microsoft Excel format prior to analysis. The radiuses of public hospitals were set within and beyond 10 km and spatial data analysis were carried out using ArcGIS 10.2 software. A total of 90 cases with thyroid carcinomas were recorded and mapped. The most common histological subtypes observed were papillary thyroid carcinoma (71%). The spatial distribution of thyroid cancer cases in Kelantan represented a clustered pattern (NNR: 0.549377, p-value <0.001) and most cases concentrated at northern part of Kelantan. Majority of the cases (60%, 54 cases) were located within 10 km radius from public hospitals. The remaining 36 cases (40%) were situated beyond 10 km radius from public hospitals. In conclusion, thyroid cancer cases in Hospital USM were clustered with most cases concentrated at northern part of Kelantan, where the state capital city, Kota Bharu was located. Whereas, majority of the cases have good geographical accessibility to public hospitals. These study findings provide useful information for health practitioners in planning public health intervention by targeting locations with good geographical access in order to improve overall health population in Kelantan. KEY WORDS: Thyroid Cancer, Geographic Information System, Disease Mapping, Kelantan State 1. INTRODUCTION Worldwide, 586,202 new cases were recorded with Thyroid cancer is one of the most common 43,646 mortality cases in 2020 (Globocan, 2020). endocrine malignancies (Horner et al., 2009), According to Malaysian National Cancer Registry representing 2% of all cancers with approximately 2 Report 2012-2016, thyroid cancer ranked eighth fold of incidence rate in the past 25 years (Goodarzi most frequent cancer among female in Malaysia et al., 2018). It is one of the rapid growing types with age standardized rate of 3.2 per 100,000 among all cancers worldwide (Jung et al., 2012). International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

P a g e | 28 population (Azizah et al., 2019). In Kelantan state, residential addresses were extracted. The registries thyroid cancer is the fourth common cancer and were carefully examined to ensure no duplicate recorded much higher age-standardized rate (5.1%) entry. The histological subtypes of thyroid cancers than the national average (Othman et al., 2008). and date of specimens taken were obtained from histopathological report acquired from Pathology Incorporating spatial information in cancer data Department. In addition, the addresses of all public can examine the occurrence of cancer incidence in hospitals in Kelantan were obtained from Kelantan relation to the geographic variation and Health Department. environmental parameters (Wang et al., 2008 and Levine et al., 2009). The spatial data can be A total of 9 public hospitals involved in this integrated into the existing tabular data by using study, which were Hospital Gua Musang, Hospital Global positioning system (GPS) to include the Kuala Krai, Hospital Tengku Anis, Hospital geographical location based on the addresses of Machang, Hospital Tanah Merah, Hospital Pasir patients (Wang et al., 2008) which will be mapped Mas, Hospital Universiti Sains Malaysia, Hospital using Geographical Information System (GIS) Raja Perempuan Zainab II and Hospital Tumpat. software. Spatial data analysis using Geographic The radiuses were set within and beyond 10 km Information System (GIS) is increasingly being used from these hospitals. The geographic coordinates of to determine the cluster of cases, identify disease residential addresses and public hospitals in pattern and evaluate the environmental factors and Kelantan were obtained using Global Positioning SES on the geographical distribution of disease System (GPS). All data were recorded in Microsoft Hanley et al., (2015). It is also used to analyse the Excel format. Then, the analysis of spatial data were accessibility to public health facilities (Kuupiel et performed using ArcGIS 10.2 software. Spatial al., (2019). Many studies have applied GIS global pattern analysis by average nearest neighbour technology and spatial data analysis in assessing ratio was carried out to determine the spatial health data (Levine et al., 2009 and Rushton et al., distribution of breast cancer cases in Hospital USM. 2006). However, there is limited data on spatial The spatial distribution of the values in the dataset distribution of cancer in Malaysia. Therefore, this were interpreted as clustered/random/dispersed. study aims to map the incidence of thyroid cancer cases in Kelantan state and perform the spatial 3. RESULTS analysis to determine distribution and pattern of cases, identify cluster of cases and measure the 3.1 Geographical Distribution of Thyroid Cancer distance from existing public hospitals. These information can effectively be used to create Cases awareness and reduce rate of mortality by targeting Figure 1 shows the geographical location mapping the effort at areas with significantly high number of of all thyroid cancer cases from 2013 to 2020 in cases for early detection. Hospital USM (n=90). Cases were distributed throughout the state with high concentration in the northern part of Kelantan. 2. MATERIALS AND METHODS Figure 1: Geographical distribution of thyroid This study was conducted in Hospital Universiti cancer cases in Hospital USM Sains Malaysia, Kelantan state which is situated in the northeast of Peninsular Malaysia. Hospital Universiti Sains Malaysia (USM) is a referral centre for thyroid cancer management. This study involved all thyroid cancer cases from Kelantan and nearby state, Terengganu that were registered in Hospital USM, covering 15 districts altogether. The districts involved in Kelantan were Kota Bharu, Bachok, Pasir Mas, Pasir Puteh, Machang, Tumpat, Tanah Merah, Kuala Krai and Gua Musang. Whereas, the districts from Terengganu were Besut, Kuala Terengganu, Kemaman, Setiu, Kuala Nerus and Marang. A total of 90 thyroid cancer cases were included in this study. Registries of patients who were diagnosed with thyroid cancers from 2013 to 2020 in Hospital USM were retrieved from medical record office, Hospital Universiti Sains Malaysia. From these data, year of diagnosis, age, gender, and International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

P a g e | 29 3.2 Spatial Distribution of Thyroid Cancer Cases Spatial analysis shows that thyroid cancer cases in Hospital USM represented a clustered pattern (NNR: 0.549377, Z-score: -8.18, p-value <0.001)(Figure 2). Figure 3: Geographical distribution of all thyroid cancer cases from public hospitals within and beyond 10 km radius from public hospitals Figure 2: Spatial distribution of thyroid cancer incidences 3.3 Geographical Accessibility of Thyroid Cancer Cases to Public Hospitals Figure 3 shows the mapping of geographical location for all thyroid cancer cases (n=90) within 10 km and beyond 10 km radius from all public hospitals (n=9). Whereas, figure 4 only mapped the cases within 10 km radius from public hospitals, which revealed majority of cases had good access to public hospitals (Figure 4). 3.4 Number of Thyroid Cancer Cases According Figure 4: Geographical distribution of thyroid cancer cases and their distances from public To Distances from Pubic Hospitals hospitals within 10 km radius Most of the cases (60%, 54 cases) were located within 10 km radius from public hospitals. Out of 54 cases, 31 cases were found to overlap between two hospitals and 1 case overlapped between three hospitals. The remaining 36 cases (40%) were situated beyond 10 km radius from public hospitals, as shown in Figure 5. International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

P a g e | 30 Figure 5: Number of thyroid cancer cases according to the distance with radius of ≤ 10 km and > 10 km from public hospitals Figure 6: Percentage of thyroid cancer cases according to tumour types in HUSM from year 2013 to 2020 3.5 Types of Thyroid Carcinoma This is probably due to the highest concentration of The most common histological subtypes observed Malay population in this area, which make up the were papillary (71%), followed by follicular (17%), largest ethnic group in Kelantan and large anaplastic (10%) and poorly differentiated population screening in this area as compared to carcinoma (2%), as illustrated in Figure 6. other part of the state. Generally, thyroid cancer incidence in Malaysia is predominant in Malay 3.6 Thyroid Cancer Cases According to Districts ethnic (Htwe, 2012). The number of cases were reported according to districts in both states. A total of 9 districts from Furthermore, it may be possible that population’s Kelantan state and 6 districts from Terengganu state ease of access to health facilities in this area were involved in this study, as shown in Table 1. contribute to the high number of cases detected. However, there was no statistically significant 4. DISCUSSION hotspot areas reported in this study. The most The spatial analysis showed that distribution of common histological subtype of thyroid carcinoma thyroid cancer cases in Hospital USM were observed was papillary, which accounted for 64 clustered. Most of the cases were concentrated at cases (71%) out of total cases. The similar pattern northern part of Kelantan, where the state capital were also reported in other studies (Htwe et al., city, Kota Bharu was located. Similarly, previous 2009 and Othman et al., 2018). Papillary thyroid local study also reported the same finding (Othman carcinomas were more frequent among other et al., 2018). cancers associated with iodine deficiency (Othman et al., 2018). International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

P a g e | 31 Table 1: Number of thyroid cancer cases according to all districts in Kelantan and few districts in Terengganu Mafauzy et al., (1995) reported that Kelantan to access healthcare facilities especially in rural population had chronic iodine deficiency (Mafauzy communities who are more familiar with traditional et al., 1995), which is one of the risk factors of medicine (Buor, 2003). Furthermore, those who thyroid carcinoma. lived in poor geographical access area might have poor awareness regarding the risks of cancer and the In this study, geographical accessibility was importance to seek early medical attention (Ahmadi measured as: 0-10 km = good geographical access; et al., 2018). Hence, this study helps to highlight and > 10 km = poor geographical access (Kuupiel et potential regions that require much attention from al., 2019). Majority of patients (60%) had good public health authorities to ensure the health care geographic access to the public hospitals as they services are effectively distributed to the population were located within 10 km of radius from hospitals. in this state. These cases were mostly from Kota Bharu district, an urban area of Kelantan state and it was found that 5. CONCLUSION 2 public hospitals were located in this district, which This study provided information on the spatial are Hospital Raja Perempuan Zainab II and Hospital distribution and pattern of thyroid cancer incidences USM. Hence, population who live within this as well as geographical accessibilities to public district and nearby areas have more privilege to hospitals within and beyond 10 km radius in access the health facilities and receive early Kelantan state. It was found that thyroid cancer screening for their diseases. Furthermore, greater cases in Hospital USM were clustered and most of availability of health facilities in this urban area of the cases were concentrated at the northern part of Kelantan might also contributed to the high number Kelantan, where the state capital city, Kota Bharu of cases registered in comparison to rural areas was located. Also, majority of the cases had good (Samat et al., 2010). geographical access to the public hospitals. These study findings provided useful informations for However, the accessibility to public hospitals health practitioners in planning public health was poor in some districts, especially rural districts interventions by targeting locations with good in the state. About 40% of patients lived beyond 10 geographical access to health facilities in order to km radius from public hospitals and hence, had poor improve overall health population in Kelantan. geographical access. These patients have to travel far and longer duration to reach the nearest public 6. LIMITATION OF STUDY hospitals. As a result of travel burden, they are less This study mapped the confirmed cases of thyroid likely to get early screening and presented with carcinomas in Hospital USM and evaluate their higher health risks or unfavourable outcomes spatial distribution. Hence, it could not properly (Becher et al., 2004). Apart from longer travel time, cost and stress might as well act as a major barrier International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

P a g e | 32 explain the spatial distribution of the disease in Htwe, T. T., 2012, Thyroid Malignancy among Kelantan state as a whole. Goitrous Thyroid Lesions: A Review of Hospital-Based Studies in Malaysia and ACKNOWLEDGMENT Myanmar. Singapore medical journal, Vol. Author would like to thank Hospital Universiti 53(3), 159–163. Sains Malaysia and School of Medical Sciences, Universiti Sains Malaysia for the support given. Htwe, T. T., Hamdi, M. M., Swethadri, G. K., Wong, J. O., Soe, M. M. and Abdullah, M. S., REFERENCES 2009, Incidence of Thyroid Malignancy among Goitrous Thyroid Lesions from the Sarawak Ahmadi, A., Ramazani, R., Rezagholi, T., Yavari, General Hospital 2000-2004. Singapore Med J, Vol. 50(7):724-728. P., 2018, Incidence pattern and spatial analysis Jung, K. W., Won, Y. J., Kong, H. J., Oh, C. M., of breast cancer in Iranian women: Geographical Cho, H., Lee, D. H. and Lee, K. H., 2015, Cancer Statistics in Korea: Incidence, Mortality, Information System applications. East Mediterr Survival, and Prevalence in 2012. Cancer Research and Treatment, Vol. 47(2):127-141. Health J. 24(4):360–367. Kuupiel, D., Adu, K. M., Apiribu, F., (Bawontuo, Azizah, A. M., Hashimah, B., Nirmal, K., Siti V., Adogboba, D. A., Ali, K. T., Mashamba- Thompson, T. P., 2019, Geographic Zubaidah, A. R., Puteri, N. A., Nabihah, A., Accessibility to Public Health Facilities Providing Tuberculosis Testing Services at Sukumaran, R., Balqis, B., Nadia, S. M. R., Point-Of-Care in the Upper East Region, Ghana. BMC Public Health, Vol. 19, 718 . Sharifah, S. S. S., Rahayu, O., Nur Alham, O. Levine, R. S., Yorita, K. L., Walsh, M. C. and and Azlina, A. A., 2019, Malaysian National Reynolds, M. G., 2009, A Method for Statistically Comparing Spatial Distribution Cancer Registry Report 2012-2016, National Maps. International Journal of Health Geographics. http://www.ijhealthgeographics- Cancer Registry, Vol. 5: 19. .com/content/8/1/7 (Retrieved 10 March 2021). Becher, H., Muller, O., Jahn, A., Gbangou, A., Lyons, M. A., 2004, Psychosocial Impact of Cancer In Low Income Rural/Urban Women: Phase 1. Kynast-Wolf, G. and Kouyate, B., 2004, Risk Online Journal of Rural Nursing and Health Care, Vol. 4(1). http://www.rno.org/journal- Factors of Infant and Child Mortality in Rural /issues/vol4/issue1/Lyons_article.htm (retrieved 10 March 2021). Burkina Faso. Bull World Health Organ, Vol. Mafauzy, M., Mohamad, W. B, Anum, M. Y. and 82(4):265–273. Musalmah, M., 1995, Urinary Iodine Excretion in the Northeast of Peninsular Malaysia. Buor, D., 2003, Analysing the Primacy of Distance Southeast Asian J Trop Med Public Health, Vol. 26(1):138-142. in the Utilization of Health Services in the Moore, D. A. and Carpenter, T. E., 1999, Spatial Ahafo-Ano South District, Ghana Int. J. Health Analytical Methods and Geographic Information Systems: Use in Health Research and Plan. Manag., Vol. 18 (4), 293-311 Epidemiology. Epidemiologic Review, Vol. 21(2): 143–161. Globocan, 2020, Available from: Othman, N. H., Nor, Z. M. and Biswal, B. M., 2008, https://gco.iarc.fr/today/data/factsheets/cancers/3 Is Kelantan Joining the Global Cancer Epidemic?—Experience from Hospital 2-Thyroid-fact-sheet.pdf. (Retrieved 10 March Universiti Sains Malaysia; 1987-2007. Asian Pac J Cancer Prev, Vol. 9(3):473-478. 2021) Othman, N. H., Ghani, N. N. A. and Mohd, N. Z., Goodarzi, E., Moslem, A., Feizhadad, H., Jarrahi, A. 2018, Clinico-pathological Characteristics and Survival Analysis of 300 Thyroid Cancer Cases M., Adineh, H. A., Sohrabivafa, M. and in One Referral Hospital in Kelantan, Malaysia: A 10-year Study. Asian Pacific Journal of Khazaei, Z., 2019, Epidemiology, Incidence and Cancer Care, Vol. 3(3), 53. the World: An Ecology Study in 2018. Adv Hum Biol, Vol. 9:162-167. Hanley, J. P., Jackson, E., Morrissey, L. A., Rizzo, D. M., Sprague, B. L., Sarkar, I. N. and Carr, F. E., 2015, Geospatial and Temporal Analysis of Thyroid Cancer Incidence in a Rural Population. Thyroid: official Journal of the American Thyroid Association, Vol. 25(7), 812–822. Horner, M.J., Ries, L.A.G., Krapcho, M., Neyman, N., Aminou, R., Howlader, N., Altekruse, S.F., Feuer, E.J., Huang, L., Mariotto, A., Miller, B.A., Lewis, D.R., Eisner, M.P., Stinchcomb, D.G., Edwards, B.K. (eds). Bethesda, MD: 2009. SEER Cancer Statistics Review, 1975-2006, National Cancer Institute. https://seer.cancer.- gov/csr/1975_2006/, based on November 2008 SEER data submission, posted to the SEER web site, 2009. International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

Rushton, G., Armstrong, M., Gittler, J., Greene, B., P a g e | 33 Pavlik, C., West, M. and Zimmerman, D., 2006, Geocoding in Cancer Research: A Review. Sprague, B.L., Warren Andersen, S. and Trentham- American Journal of Preventive Medicine, Vol. Dietz, A., 2008, Thyroid Cancer Incidence and 30(2S): S16–S24. Socioeconomic Indicators of Health Care Access. Cancer Causes Control, Vol. 19:585– Samat, N., Jambi, D., Musa, N. S., Shatar, A. K. A., 593. Ab Manan, A. and Sulaiman, Y., 2010, Using A Geographic Information System (GIS) in Wang, F., McLafferty, S., Escamilla, V. and Luo, Evaluating the Accessibility of Health Facilities L., 2008, Late-Stage Breast Cancer Diagnosis for Breast Cancer Patients in Penang State, and Health Care Access in Illinois. The Malaysia. Kajian Malaysia, Vol. 28(1): 103-122. Professional Geographer, Vol. 60(1): 54–69. International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

P a g e | 34 TEMPORAL AND SPATIAL COMPARISON OF ONLINE SEARCHES AND CONFIRMED CASES OF LISTERIOSIS OUTBREAK: AN EXPLORATORY STUDY OF GOOGLE TRENDS IN THE US Hung Nguyen Ngoc1 and Wantanee Kriengsinyos2 Institute of Nutrition, Mahidol University, Thailand E-mail: [email protected], [email protected] ABSTRACT Listeriosis or listeria infection is a rare, serious, and high mortality disease, which is the third leading cause of death from foodborne illness in the US. This disease is characterized by non-specific symptoms with a long incubation period ranging from one to four weeks, as late as 90 days after exposure. Traditional surveillance investigations of listeriosis' clusters and food sources remained limited due to a small number of geographically dispersed case-patients, long incubation period, and difficulties in patients’ recall of food exposures. Therefore, a timely and publicly accessible surveillance tool may allow better food safety advice and education campaigns. People with listeriosis may search online through Google Trends (GT), which appears to be a potential tool web-based for real-time surveillance of outbreaks. The present exploratory study compares the spatiotemporal dynamics of listeriosis searches on GT, in comparison with CDC’s surveillance data at state- and county-level within the state of Texas. The GT’s query volumes of disease terms, pathogen, and symptoms were extracted from 2005 and 2018. Results from spatial and temporal analyses manifest noticeably similar patterns between the search frequency and the actual listeriosis incidence. Time series analysis of the Google Trends showed a lag period of -1 months with the CDC reported data. This study contributed that the Google Trends search data hold a potential role in forecasting emerging rare infectious disease events, especially in resource-constrained areas. The competence to briskly gather and disseminate information about outbreaks is useful for food safety regulators in identifying the food sources and minimizing the contamination. KEY WORDS: Listeria, listeriosis, Google Trends, spatial, temporal, foodborne disease 1. INTRODUCTION pregnant women, the elderly, and people with Listeriosis or listeria infection is a rare, serious, and defected immune systems (Muñoz et al., 2012). high mortality disease that ranks the third leading Listeria infection is characterized by a long cause of death from foodborne illness in the US incubation period ranged from one to four weeks, as (Saleh et al., 2012). The fatality rate of this disease late as 90 days after exposure, causes various in the US is approximately 20%, whereas it doubled manifestations ranging from asymptomatic intestinal in developing countries, ranging from 40 to 58% carriage and gastroenteritis, to invasive and (Furyk et al., 2011). Since 2011, listeriosis has been disseminated severe illnesses such as septicemia, classified as an “emerging” nationally notifiable meningoencephalitis, and perinatal infection (Stavru disease that has become more involved in food- et al., 2011). In the US or other developed countries, borne outbreaks lately in the US. Most listeriosis outbreaks of Listeriosis are usually recorded, outbreak is associated with the consumption of whereas the documenting of this infection is barely various processed foods contaminated with the reported in the developing world. The reasons might pathogen, especially in ready-to-eat foods such as come from the delays in seeking medical services dairy-based food products (milk, cheeses), corn- upon sickness among the population (Rocourt et al., salad, meat, hot-dog (Makino et al., 2011). 2003). Although most listeria infection cases are sporadic, which are not associated with a recognized The dominant pathogenic species of this disease illness’s cluster, the outbreak inspection is a crucial is Listeria monocytogenes (L. monocytogenes), opportunity to prevent additional incidents by which geneses serve infections in immune- compromised individuals, particularly in newborns, International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

P a g e | 35 removing the contaminated vehicles and improving Surveillance Network (FoodNetFast) (CDC, 2008) food safety. Previous lately multistate outbreaks in and National Outbreak Reporting System (NORS) the US revealed that the traditional surveillance (NORS, 2021). FoodNetFast is a principal investigation of listeriosis' clusters and food sources foodborne disease CDC surveillance, that provides remained limited due to its scattered characteristics foodborne disease data in 10 states accounting for (i.e. small number of geographically dispersed case- 15% of the US population (CDC, 2008), whereas, patients, long incubation period, and difficulties in NORS is a web-based platform system that provides patients’ recall of contaminated food exposures) reports of all waterborne and foodborne disease (Olsen et al., 2005). Thus, prompt and real-time outbreaks and enteric disease outbreaks in the States detection is essential for improving the control and (NORS, 2021). In addition, data of listeriosis prevention of this infectious disease. confirmed-cases at the county-level in the state of Texas was collected from the Texas Department of In recent times, a novel Internet-based State Health Services (Texas Department of State surveillance system based on Internet search Health Services, 2021). Individual years were behavior has recently emerged as a promising aggregated to gather the overall statistic of technique to supplement the existing system confirmed cases through the examined period. (Milinovich et al., 2014). Amongst, Google Trends (GT) is affirmed as the primary sources of 2.3 Google Search Trends information for the population searches, particularly Google Search is one of the most popularly used in the US (Tonsaker et al., 2014). Information or search engines in the US, which market share was results generated from queries fed into search estimated at 88% among the existing system (Search engines can be used for monitoring and surveillance Engine Market Share United States of America, purposes. It can measure the outbreaks' magnitude 2021). The trend of searches is recorded and can be in the prodromal stages and produce timely accessed from Google Trends (GT). GT produces information (Milinovich et al., 2014). Recent studies outcomes with the sum of the search volumes of all attempt to explore the association between possible queries called relative search volume infectious diseases with GT searches, which (RSV). RSV is a normalized data series, ranging primarily for surveillance or descriptive purposes from 0 to 100 based on a topic proportion to all (Pelat et al., 2009 and Carneiro and Mylonakis, searches on all topics. The attributes of the value of 2009). However, GT additionally appears to be a 100 to the maximum number of monthly hits and novel tool to understand spatial or temporal patterns attributes to all other months their relative value as a of diseases and risks. It can track disease exploiting proportion of the maximum number of hits. In the not only for seasonal pattern analyses but also to be present study, RSV was individually extracted for a expanded to discover the geospatial or series of search terms in the US states from 2005 to spatiotemporal pattern. 2018. The keyword was applied includes (1) the disease's term: \"listeria\", (2) the disease's symptoms: In an effort to extend previous literature in \"listeriosis\", (3) the most common pathogen: evaluating Google Trends data's application to better \"listeria monocytogenes\". understand the dynamics of rare infectious disease, this study was conducted to better understand the 2.4 Temporal Analysis dynamics of listeriosis cases versus listeriosis For temporal analysis, each above keyword was concerns using a comprehensive search process. We obtained separately and the sum of these values for use GT query data, especially in symptoms and each month was calculated, which is considered the disease terms to track listeriosis outbreaks both monthly search frequency. These data were spatially and temporally and compare the patterns expressed in line-plot accordingly and were with confirmed listeriosis cases by the US Centers compared with monthly trends of the CDC- for Disease Control (CDC). confirmed cases. Spearman rank correlation, and cross-correlation time series analysis were tested to 2. MATERIALS AND METHODS assess the association between the two datasets. The time dependence between two variables or lag 2.1 Study Design and Setting values indicates the degree and direction of The cross-sectional study employed the database associations. A lag of –1 for assessing correlation from Google Trends and CDC. suggests that GT data has been shifted backward by one-month from the CDC data and the opposite is 2.2 CDC Database true for +1. The positive lag period may support the The number of confirmed listeriosis cases by States surveillance team to ensure that the outbreak is over. in the timeframe from 2005 through 2018 was obtained from the CDC web-accessible system includes the Foodborne Diseases Active International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

IBM-SPSS Statistic for Windows, v25.0 (IBM P a g e | 36 Corp., Armonk, NY, USA) was applied for all statistical analyses. A p-value less than 0.05 was spatial trends was based on central tendency (mean) considered statistically significant. with given legends (showing different class limits). 2.5 Spatial Analysis 3. RESULTS AND DISCUSSION Similar RSV of the above keywords were individually extracted. The highest number of 3.1 Temporal Trends searches overall for one term in one state is assigned Figure 1 compares the monthly trends of the CDC- the value of 100 and all other items are given a confirmed listeriosis cases with the GT search value to represent their relative frequency compared results for the period between 2005 and 2018. Both to the maximum. We take the sum of search graphs apparently describe the seasonality, peaked frequencies in all search items for each state and during summer and fall, usually between July to graph that data over a US map. The spatial trends September. However, it seems evident that the for the aggregated number of CDC-confirmed peaks for the search patterns precede to some extent listeriosis cases were also drawn at the state-level those for the actual cases. The linear association maps. between CDC disease surveillance and GT pattern was furtherly assessed using time-series cross- In addition, the state with the highest reported correlations (data was omitted). The results showed number of confirmed listeriosis cases - Texas-was that GT query data showed the highest correlation at furtherly selected and analyzed for the spatial a lag of –1 month (r =0.23) with the CDC data. Such variations within the state. Based on the availability time lag between predicted and confirmed results of the dataset, data was collected from the corresponds to the previous literature on Google timeframe from 2008 to 2017, and procedures were Trends (Araz et al., 2014 and Verma et al., 2018). similarly conducted with the state-level identical The negative lag period found in the present study steps. The GT outcomes provide the metro-scale will help to figure out the approximate time of aggregation, while CDC listeriosis confirmed-cases primary case incidence and further analysis to look were extracted by county-level. For all mapping for biologically plausible associations. However, schemes, the relative number of cases was this interrelationship alone should not be interpreted represented using a grayscale with a quantile break. as definitive evidence of approaching outbreaks or The darker the state or county, the higher number of epidemics as the analyses performed were univariate aggregated cases or searches. The comparison in and exploratory in nature. Therefore, the results of this study should be properly understood with caution in the biological plausibility and natural history of the disease concerned. Figure 1: Temporal comparison of (dark blue) Google Trends (light blue) CDC-confirmed listeriosis case during timeframe from 2005 to 2018 International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

P a g e | 37 Figure 2: State-level spatial distribution of CDC-confirmed listeriosis cases (left) and Google Trends’ relative search volumes (RSV) (right), aggregated from 2005 to 2018 Figure 3: County-level spatial distribution of CDC-confirmed listeriosis cases (left) and Google Trends’ relative search volumes (RSV) (right) in Texas, aggregated from 2008 to 2017 3.2 Spatial Trends distribution of confirmed listeriosis cases and GT's Figure 2 illustrates the state-level spatial variation of outcomes for listeriosis searches in the state of CDC-confirmed listeriosis cases and GT results. Texas. A direct comparison seems difficult due to There seems a divergence between the spatial the small sample size and different categories, pattern of the actual listeriosis cases and GT’s particularly, the metro-scale aggregation was searches. CDC-confirmed cases and GT outcomes extracted from GT's searches, while the county- distribution display the high closeness with low aggregation scale was quoted for actual confirmed concentration in the North, moderate to high cases. Nevertheless, it still can be considered as concentration in Midwest and Northwest US. A preliminary exploratory evidence of spatial similar pattern was also observed in Southeast US. comparison between two datasets at the state-level. However, some mismatch was conceded. In It seems that a moderate to high query volume of particular, the pattern extracted from GT’s search is searches for listeriosis were reported in Prairies and greatly focused on the high concentration in Lakes area, and Gulf Coast, associated with the high Southwest US, whereas the actual case is number of confirmed was accordingly reported in accordingly expressed in low level. those areas. Contrarily, a similar low concentration was found in Big Bend and Hill County, whereas The comparison at the county-level was also the medium level was recorded in South Texas. examined. There are marked discrepancies in Figure 3, which displays the county-level spatial International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

The comparison also explored some evidence of the P a g e | 38 mismatch in spatial comparison. Specifically, a huge population search for listeriosis in Panhandle Plains, Carneiro, H. A. and Mylonakis, E., 2009, Google while the rare case was confirmed in most of the Trends: A Web-Based Tool for Real-Time counties in this region. Surveillance of Disease Outbreaks. Clin Infect Dis Off Publ Infect Dis Soc Am., Vol. 49(10), 4. CONCLUSION 1557-1564. doi:10.1086/630200. The study's findings revealed that the GT-based prediction system has the capability to identify CDC, 2018, Foodborne Diseases Active infectious disease outbreaks with modest reliability. Surveillance Network (FoodNet). Centers for In this study, the lag period for listeriosis is reported Disease Control and Prevention. Published at -1 months, which supports the understanding of October 14. Accessed March 20, 2021. the average time of primary case occurrence and https://www.cdc.gov/FoodNetFast. further analysis to look for biologically plausible associations. This forecast correlation, which Furyk, J. S., Swann, O. and Molyneux, E., 2011, occurred before the actual outbreak provides Systematic Review: Neonatal Meningitis in the sufficient time to deploy responses for timely action. Developing World. Trop Med Int Health TM IH, Vol. 16(6), 672-679. doi:10.1111/j.1365- Several limitations should be acknowledged in 3156.2011.02750.x. the interpretation of the results in the present investigation. The study does not consider the Makino, S. I., Kawamoto, K., Takeshi K, Okadac, possibility that Google searches usually adjusted, Y., Yamasakic, M., Yamamotoc, S. and Igimic, especially, when issues are raised in the media, even S., 2005, An Outbreak of Food-Borne Listeriosis if people do not perceive actual risks and simply just Due to Cheese in Japan, During 2001. Int J Food want to know more about the issues. Additionally, Microbiol, Vol. 104(2),189-196. doi:10.1016- none of the powerful statistical analyses was /j.ijfoodmicro.2005.02.009. performed to comprehensively evaluate the temporal or spatial trend due to the inherent Milinovich, G. J, Williams, G. M., Clements, A. C. limitation of Google Trends data, which are A. and Hu, W., 2014, Internet-Based displayed as relative search frequencies compared to Surveillance Systems for Monitoring Emerging the maximum. Although many possible variations of Infectious Diseases. Lancet Infect Dis., Vol. search terms in Google Trends analysis were 14(2), 160-168. doi:10.1016/S14733099(13)- applied, including disease names, bacterium, and 70244-5. symptoms, to ensure the robustness of this study, our findings cannot be interpreted as confirmatory Muñoz, P., Rojas, L., Bunsow, E., Saez, E., but should be considered purely exploratory. Sánchez-Cambronero, L., Luis Alcalá, L., In conclusion, this study explores the potential use Rodríguez-Creixems, M., Bouza, E., 2012, of Google Trends in forecasting emerging rare Listeriosis: An Emerging Public Health Problem infectious disease events, especially in resource- Especially among the Elderly. J Infect. Vol. constrained areas. Despite the huge potential of this 64(1), 19-33. doi:10.1016/j.jinf.2011.10.006. approach, this tool cannot be used as a surrogate to traditional surveillance systems and can only be National Outbreak Reporting System (NORS), used to supplement the existing system. Future 2021, | CDC. Published March 11. Accessed studies should compare the search trends of multiple March 20, 2021. https://www.cdc.gov/nors/- diseases with similar symptoms with listeriosis to index.html. validate the finding of this study. Olsen, S. J., Patrick, M., Hunter, S. B., Reddy, V., REFERENCES Kornstein, L., MacKenzie, W. R., Lane, K., Bidol, S., Stoltman, G. A., Frye, D. M., Lee, I., Araz, O. M., Bentley, D. and Muelleman, R. L., Hurd, S., Jones, T. F., LaPorte, T. N., Dewitt, 2014, Using Google Flu Trends Data in W., Graves, L., Wiedmann, M., Schoonmaker- Forecasting Influenza-Like-Illness Related ED Bopp, D. J., Huang, A. J., Vincent, C., Visits in Omaha, Nebraska. Am J Emerg Med., Bugenhagen, A., Corby, J., Carloni, E. R., Vol. 32(9), 1016-1023. doi:10.1016/j.ajem- Holcomb, M. E., Woron, R. F., Zansky, S. M., .2014.05.052. Dowdle, G., Smith, F., Ahrabi-Fard, S., Ong, A. R., Tucker, N., Hynes, N. A. and Mead, P., 2005, Multistate outbreak of Listeria monocytogenes infection linked to delicatessen turkey meat. Clin Infect Dis Off Publ Infect Dis Soc Am., Vol. 40(7), 962-967. doi:10.1086/428575. Pelat,, C., Turbelin, C., Bar-Hen, A., Flahault, A. and Valleron, A. J., 2009, More Diseases Tracked by Using Google Trends. Emerg Infect International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

Dis., Vol. 15(8), 1327-1328. doi:10.3201- P a g e | 39 /eid1508.090299. Rocourt, J., BenEmbarek, P., Toyofuku, H. and Stavru, F., Archambaud, C. and Cossart, P., 2011, Schlundt, J., 2003, Quantitative Risk Assessment Cell Biology and Immunology of Listeria of Listeria Monocytogenes in Ready-to-Eat Monocytogenes Infections: Novel Insights. Foods: the FAO/WHO approach. FEMS Immunol Rev., Vol. 240(1),160-184. Immunol Med Microbiol., Vol. 35(3), 263-267. doi:10.1111/j.1600-065X.2010.00993.x. doi:10.1016/S0928-8244(02)00468-6. Saleh, I., Alwan, N., Barbour, E., Azhar, E. and Texas Department of State Health Services, 2021, Harakeh. S., 2012, Listeria Infections: Listeriosis. Accessed March 21. https://www.- Epidemiology, Pathogenesis and Treatment. dshs.state.tx.us/idcu/disease/listeriosis/. Listeria Infections: Epidemiology, Pathogenesis Tonsaker, T., Bartlett, G. and Trpkov, C., 2014, and Treatment. 155-166. Health Information on the Internet: Gold Mine Search Engine Market Share United States of or Minefield? Can Fam Physician Med Fam America, 2021, StatCounter Global Stats. Can., Vol. 60(5),407-408. Accessed March. https://gs.statcounter.com/- search-engine-market-share/all/united-states-of- Verma, M., Kishore, K., Kumar, M., Sondh, A. R., america Aggarwal, G. and Kathirvel, S., 2018, Google Search Trends Predicting Disease Outbreaks: An Analysis from India. Healthc Inform Res., Vol. 4(4), 300-308. doi:10.4258/hir.2018.24.4.300. International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

P a g e | 40 EFFECTS OF THE APPLICATION OF HEALTH PROMOTION MODEL WITH DHARMA WAY AND THAI WAY FOR PREVENTION OF COMPLICATIONS IN THE ELDERLY WITH CHRONIC NON-CONTAGIOUS DISEASES IN CHIANG RAK NOI SUB-DISTRICT, BANG PA-IN DISTRICT, PHRA NAKHON SI AYUTTHAYA PROVINCE Aree Sanguanchue,1* Thassaporn Chusak,1 Phannathat Tanthanapanyakorn,1 Jiaranai Pathomrotsakun1 and Klarnarong Wongpituk1 Faculty of Public Health, Valaya Alongkorn Rajabhat University under the Royal Patronage, Thailand *E-mail: [email protected] ABSTRACT The study's goal was to use health promotion initiatives based on Dharma and Thai principles to reduce problems from noncommunicable illnesses. Chiang Rak Noi Subdistrict, Bang Pa-in District, Phra Nakhon Si Ayutthaya Province was the subject of the research. Thirty-six diabetic and hypertensive patients were chosen as study subjects. G*Power was used to calculate sample proportions (Buchner, 2010). The following criteria were used to select the sample: being on medicine and not having any problems. Data was gathered using a structured interview schedule, which was validated by five specialists. The reliability was 0.70 and the content validity was 0.71. Percentage, mean, standard deviation, and paired sample t-test, as well as Independent Samples t – test, were utilized as statistics. The results showed that there was a statistically significant difference in blood glucose levels in the experimental group at 0.001. The experimental group's mean health promotion behavior scores were greater than the control group's (p < 0.01). The experimental group had the highest levels of pleasure while using the Dharma way and the Thai approach (X=44.41, S.D=10.25). This study suggests that a health promotion program based on Dharma and Thai principles be conducted on a continual basis for diabetic and hypertension patients. Furthermore, this type of advertising effort should be expanded to other towns. KEYWORDS: Mental Health, Older People, Social Support, Family Relationshi 1. INTRODUCTION goal is to be in good health, which includes Chronic diseases are produced by a variety of risk physical, mental, intellectual, and social well-being. behaviors, therefore prevention and treatment of It emphasizes morality, meditation, and wisdom, as these idiopathic diseases needs a wide range of well as living by sufficiency economy principles. A research and technology. As a result, various daily routine is a mixture of concepts of medicine domains of research and technology are required to and public health, as well as a lifestyle based on the link preventative behavior modification and principles of the life clock. This would be used to problem-solving with the concepts of medicine and prevent and alleviate social, economic, and public health. This has the potential to improve environmental problems, lowering the risk of health by allowing believers to be integrated with various illnesses. Chronic illnesses, in particular, on medicine, modern public health, Thai traditional an individual, family, community, and social level, a medicine, alternative medicine, and sufficiency study by Piyaset (2016). economy in patient prevention, treatment, and rehabilitation. Uthai Sudsuk created the concept of a The researcher is interested in establishing a sort health promotion model based on the Thai way of of health promotion based on Thai lifestyle life. Buddhist principles have been used to develop concepts. Prayer, meditation, conversation, dharma, the body and mind in preparation for wisdom. To food, emotional management, exercise, and a life establish a method for human life development. The clock are some of the strategies used to help the International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

elderly with chronic noncommunicable diseases. P a g e | 41 Applied to diabetic and hypertensive individuals. The incidence of diabetes and from the research at any time. The tools utilized in hypertension is increasing year by year. this investigation were of two types: an experimental model and a questionnaire designed 2. MATERIAL AND METHOD with expert assistance. This study was quasi-experimental. Figures 1 and 2 show the results of a study on the effect of utilizing 3. RESULT the Thai health promotion model in Chiang Rak Noi The results demonstrated a statistically significant Sub-district, Bang Pa-in District, Phra Nakhon Si difference in blood glucose levels between the Ayutthaya Province. The goals are as follows: 1. To control and experimental groups at 0.001, as compare the outcomes of blood sugar and blood indicated in Table 1. The results compared blood pressure levels before and after the model was pressure levels between the control and applied. 2. Assess the model's level of satisfaction experimental groups (Table 2). The results indicated with chronic disease patients. A program was used that the blood pressure levels in the control and to determine the sample size, which was 36 experimental groups were statistically significantly participants, 18 of whom had diabetes and 18 of different at 0.001. The mean and standard deviation whom had hypertension. The sample was chosen of satisfaction with the research model among using Purposive Sampling Theory and the Inclusion elderly people with noncommunicable diseases criteria that were established. People who can listen (Table 3). The findings revealed that the samples to, speak, read, and write Thai. To take part in this were extremely happy with health promotion study on a voluntary basis. Diabetes doesn't have patterns based on Dharma principles, the Thai way any side effects. There are no side effects from to prevent difficulties for the elderly with chronic hypertension. Patients have the option to withdraw non-contagious illnesses (average =44.41, S.D.= 10.25). Figure 1: Map of Phra Nakhon Si Ayutthaya province Table 1: Comparison of blood sugar levels between control and experimental groups Group category n S.D t df p-values -13.93 124.04 0.000* Control 36 120.02 9.52 Experimental 36 93.10 12.27 *p<0.001 International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

P a g e | 42 Figure 2: Map of Chiang Rak Noi sub-district, Bang Pa-in district Table 2: Comparison of blood pressure levels between the control group and the experimental group Group category n S.D. t df p-values Control 36 153.22 18.92 -7.10 35 0.000* 36 134.94 19.45 Experimental *p<0.001 Table 3: Mean and Standard Deviation of Research Model Satisfaction Satisfaction level Satisfaction 44.41 S.D level 10.25 highest Satisfaction of health promotion model with Thai way of life and Dharma way 4. CONCLUSION AND DISCUSSION address health problems and put them into effect in The outcomes of using a health promotion model in cooperation with medical and public health the Thai and Dharma ways. The goal is to avoid concepts. Furthermore, via counseling, exchange chronic illness problems in the elderly. Comparison experience. It is a two-way conversation between of blood pressure and blood glucose levels two or more individuals who are knowledgeable in following the adoption of a health promotion Buddhism, medicine, public health, and lifestyle. It approach. According to the hypothesis, the data might be a monk or another competent individual. demonstrate significant differences at the 0.001 The concepts of the Dharma and Thai ways were level. Explain that prayer is a sacred word that employed by the researchers in this study. This is necessitates prayer. This gives you the ability to simple to implement in the context of daily life. As prevent a variety of hazards. Prayer is a form of a consequence, the research participants can practice Buddhist dharma study. The mind is calmer after a according to the hypotheses on a regular basis. period of prayer, which is the goal of meditation. It relieves stress and improves one's life, resulting in The findings of a blood glucose level better health. They contribute to the body's chemical comparison between the control and experimental compounds, cause health and immunological groups. The difference in blood glucose levels illnesses, and cause a wide range of disorders. between the control and experimental groups was Dharma discussion entails knowing the Dharma that statistically significant at 0.001. According to the promotes the creation of health. Also, prevent and results of a randomized controlled trial on the International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

benefits of nursing case management on Buddhist P a g e | 43 monks at risk of type 2 diabetes. It was discovered that the experimental group demonstrated a ACKNOWLEDGEMENT statistically significant link with health behaviors The researchers would like to express their gratitude after following the model in the study by Chaimai et to Valaya Alongkorn Rajabhat University, under al., (2017). It was based on the benefits of Royal Patronage, as well as the Chiang Rak Noi mindfulness training on happiness and blood sugar Municipality and health volunteers. This facilitates levels in diabetes patients. Furthermore, as data collection and gives a location for research compared to the control group, the blood glucose endeavors. Thank you so much to all of the elderly level was considerably lower after the trial (p < for their assistance in making the research endeavor 0.01), as reported by Zarifsanaiey et al., (2020). The a success. comparison of blood pressure levels revealed that the control and experimental groups had statistically REFERENCES substantially different blood pressure values at 0.001. This might be due to a misunderstanding of Piyaseth, L., 2016, A Model Development to the research model. Exchanges among the elderly Enhance Buddhism-Oriented Health Conditions with chronic conditions are also possible. According for Preventing and Solving Chronic Illness in the to the study Association of blood pressure reduction Community: A Case Study of Ban Khui Parang, with incidence of dementia or cognitive impairment: Wang Kuang Sub-District, Prankratai District, a systematic review and meta-analysis, it wasn't. Kamphaeng Phet Province. Journal of Health There was no significant link between blood Education, Vol. 39(132), 23-34. pressure and intervention study change, as reported by Hughes et al., (2020). It was also not consistent Chaimai, A., Piaseu, N. and Mekwiwatanawong, C., with the impact of self-management education 2017, Effects of Nursing Case Management of tailored to health literacy on medication adherence Buddhist Monks at Risk for Type 2 Diabetes: A and blood pressure control in older adults with Randomized Controlled Trial. Pacific Rim primary hypertension: A randomized controlled International Journal of Nursing Research, Vol. experiment. This revealed that there was no 21(4), 305-316. difference in the proportion of regulated blood pressure readings across the groups (p > 0.05), as Zarifsanaiey, N., Jamalian, K., Bazrafcan, L., reported by Delavar et al., (2020). Keshavarzy, F. and Shahraki, H. R., 2020, The Effects of Mindfulness Training on the Level of However, according to the findings of this study, Happiness and Blood Sugar in Diabetes Patients. it should be used in the implementation of health Journal of Diabetes & Metabolic Disorders, Vol. promotion programs based on dharma principles and 19(1), 311-317. the Thai way of life to prevent problems in the elderly with chronic non-contagious illnesses. Hughes, D., Judge, C., Murphy, R., Loughlin, E., Integrating with other relevant and current sciences, Costello, M., Whiteley, W. and Canavan, M., as well as applying to develop contextually engaged 2020, Association of Blood Pressure Lowering health supplements. with Incident Dementia or Cognitive Impairment: A Systematic Review and Meta- Analysis. Jama, Vol. 323(19), 1934-1944. Delavar, F., Pashaeypoor, S. and Negarandeh, R., 2020, The Effects of Self-Management Education Tailored to Health Literacy on Medication Adherence and Blood Pressure Control among Elderly People with Primary Hypertension: A randomized Controlled Trial. Patient Education and Counseling, Vol. 103(2), 336-342. International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

P a g e | 44 THE PARTICIPATION OF VOLUNTEERS IN PROMOTING PUBLIC HEALTH, ELDERLY HEALTH, BANG KHONTHI DISTRICT, SAMUTSONGKHRAM PROVINCE Sureewan Siladlao1, Thanya Promsorn1, Tammasak Saykaew1, Wanwimon Mekwimon1 and Klarnarong Wongpituk2 1Public Health Program, College of Allied Health Sciences, Suan Sunandha Rajabhat University, Thailand E-mail: [email protected] 2 Faculty of public health, Valaya Alongkorn Rajabhat University under the Royal Patronage, Thailand ABSTRACT This research was a descriptive research to study the participation of health volunteers, health promotion of the elderly in Bang Khonthi District, Samut Songkhram Province. The samples used in the study were the public health volunteers in Bang Khonthi District, Samut Songkhram Province. The objectives of the study are: 1. To study the participation of public health volunteers in promoting elderly health in Bang Khonthi District, Samut Songkhram Province. 2. To compare the differences in participation of public health volunteers in promoting elderly health in the district. Bang Khonthi, Samut Songkhram Province Classified by personal factors. The samples used in the study were the public health volunteers in Bang Khonthi District, Samut Songkhram Province. The sample group of 242 people. The statistics used for data analysis were Percentage, Mean and Standard Deviation. The T-test was used to test the differences. One-way analysis of variance (One-Way ANOVA). The results of general data analysis of public health volunteers in Bang Khonthi District showed that most respondents were female 87.6%. Most health volunteers were between 51- 60 years old 35.1%. Most health volunteers had The level of education is at the primary elementary level 31.18%, most public health volunteers are Buddhists (98.18 percent. Most public health volunteers have marital status 43.0% Most public health volunteers are employed 41.7%. Most public health volunteers earn less than 5,000 baht 54.1%. Most public health volunteers have a period of 0 - 5 years 36.4% The results of the analysis of participation in promoting elderly health in general found that participation in the promotion of elderly health is at a moderate level. When considering each aspect, it was found that participation in decision making Participation is moderate. The participation in the operation Participation is moderate. Participation in receiving benefits Participation is moderate. Participation, evaluation Participation is moderate. The results of data analysis comparing the differences between personal factors and the participation of public health volunteers in promoting the elderly health of Bang Khonthi district, Samut Songkhram province found that gender, age, educational level, religion, status, occupation, income and duration of work were different. The participation of public health volunteers in promoting health among the elderly was significantly different at the level of 0.05. For a different gender. Participation in the promotion of health of the elderly is not different. KEYWORDS: Public health volunteers, The elderly, Samut Songkhram 1. INTRODUCTION over has increased from 611 million in 2007 to 962 Today, the world's population of all age groups is million in 2017, with an average annual rate of 5.8 growing at a slower rate. The aging population is percent. According to the health report statistics in increasing at a very high rate. In the ten years 2017, one in five NCDs that cause death are caused between 2007 and 2017, the world population has by stroke (rate 48.7 per hundred thousand increased from 6,609 million to 7,550 million, population), ischemic heart disease (rate 32.3 per equals to an increase with an average rate of 1.4 hundred thousand population), diabetes (rate 22.3 percent per year. But the aging population is per hundred thousand population), hypertension increasing at a rate that is four times higher than that (rate 12.2 per hundred thousand population), chronic of the total population. The population aged 60 and International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

P a g e | 45 obstructive airway disease (rate 11.4 per hundred in elderly health promotion in Bang Khonthi thousand population) (Division of Communicable District, Samut Songkhram Province. Diseases, 2017) From these data it shows that chronic diseases are all related to a person's 3. RESEARCH CONCEPTUAL FRAMEWORK behavior, and the increasing number of the elderly From literature review and related research, the population will have a direct impact on the country's study was summarized as the concept of the study as public health policies and programs. This is because shown in Chart as follows: the elderly will have many health problems as a result of the deterioration of the body, illnesses in Independent variable Dependent variable physical, mental, personality, as well as loss of roles and social status. Therefore, taking care of the General The participation of elderly is more about helping them reach their information public health volunteers fullest potential in their daily activities rather than - gender in promoting the health focusing on specific diseases treatment - age of the elderly. (Pongsaengpan and Rodjarkpai, 2014). - education level - involvement of public Samut Songkhram Province has an increasing - religion health volunteers in number of elderly people every year. Statistics show - status decision-making that the number of elderly in Samut Songkhram - occupation - involvement of public province is one in 10 of the elderly province. There health volunteers in are 3 districts in Samut Songkhram province as - income their operations follows: Mueang Samut Songkhram district, Bang - duration of - participation of public Khonthi district, and Amphawa district. According public health health volunteers to to the Samut Songkhram Provincial Statistics Office volunteer work receive benefits 2019, the proportion of the elderly population in - involvement of public each district is 19.44, 25.88 and 22.89 percent, health volunteers in the respectively. From the above data, it shows that in evaluation Bang Khonthi District has the highest elderly population in Samut Songkhram Province. Bang 4. RESEARCH METHODOLOGY Khonthi District is one of the areas that This is a descriptive research to study the continuously performs public health work by participation of public health volunteers in Bang allowing people to participate in the development Khonthi District, Samut Songkhram Province. The and self-reliance of public health operations, there sample in this study is public health volunteers. The are public health volunteers who work in providing tool is questionnaire of quantitative research for data services to people together with public health collection which is divided into 2 parts as follows: workers in planning and implementing community health problems, so it is imperative to develop Part 1: General information questionnaire of the effective participation in the practice of public respondents is gender, age, education level, religion, health volunteers. Therefore, the researcher is status, occupation and length of service. interested in further study how public health volunteers are involved in decision-making, Part 2: The participation questionnaire for public operational aspects, receiving benefits, and the health applicants to promote health of the elderly is evaluation of health care in the elderly in the divided into 4 areas as follows: participate in community at what level, and when compared by decisions, join in operation, participation in individual factors of public health volunteers, how receiving benefits, and participation in assessments. much health volunteers were involved in elderly Analysis of descriptive statistical data, including health care? The knowledge gained is information, frequency, percentage, mean and standard deviation, and as a guideline for organization to improve to t-test, one-way ANOVA analysis. enable public health volunteers to perform their duties appropriately and efficiently. 5. RESEARCH RESULTS This is descriptive research with the aim to study the 2. OBJECTIVES participation of public health volunteers in 1. To study the participation of public health promoting the health of the elderly in Bang Khonthi volunteers in promoting health of the elderly in District, Samut Songkhram Province, and to Bang Khonthi District, Samut Songkhram Province. investigate the participation of public health 2. To compare the differences between personal volunteers in promoting health of the elderly in factors of public health volunteers and participation International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

P a g e | 46 Bang Khonthi District, Samut Songkhram Province. participation in operations, participating in receiving The sample group from 242 public health volunteers benefits, and assessment participation were at a in promoting the health of the elderly in Bang moderate level with the mean equal to 3.27, 3.36, Khonthi District, Samut Songkhram Province. The 3.29, and 3.39, respectively, as shown in Table 1. researcher presented the results of the analysis of the From Table 1, it was found that participation of data as follows: public health volunteers in elderly health promotion was at a moderate level. 5.1 Results of Data Analysis on Personal 5.3 Analysis Results of Comparison Study of Character Factors Results of general data analysis of public health Differences between Factors volunteers were found that the majority of The results of data analysis were compared between respondents were 87.6% female and 12.4% male. personal factors with the participation of public Classified by age, it was found that most of them health volunteers in the promotion of elderly health, were between 51-60 years old, 35.1 percent, it was found that the age, education level, religion, followed by age 61 and over, 30.6 percent, and 41- occupational status, average monthly income, and 50 years, 27.7 percent. Classified by education length of work were different. The involvement of level, it was found that most of them had an public health volunteers in promoting the health of education level at the primary school, 31.8 percent, the elderly was significantly different at 0.05. followed by the lower secondary education level Participation in promoting health of the elderly was 30.2 percent. Classified by religion, it was found no different. that most of them were Buddhists, 98.8% and Christianity at 1.2 percent. Classified by status it 6. SUMMARIZE AND DISCUSS RESEARCH was found that the majority of them had marital status, 43.0 percent, followed by a single, 39.7 FINDINGS percent. Classified by occupation it was found that The results of the study were found that the the majority of workers engaged in employment, participation of public health volunteers in 41.7 percent, followed by agriculture, 23.6 percent. promoting overall elderly health was at a moderate Classified by monthly income it was found that level which was consistent with the study of most of them had income below 5,000 baht, 54.1 Khaopatumthip (2014), who conducted a research percent, followed by income between 5,001-10,000 study on the participation of public health baht, 38.0 percent. Classified by duration of work, volunteers in promoting health in Tambon Health it was found that most of them had a period of Promoting Hospital, Phutthamonthon District, working between 0-5 years, 36.4 percent, and Nakhon Pathom Province. The results of the study followed by a period of 11 years and more 33.1 showed that the overall participation was moderate. percent. A comparison of the differences between 5.2 Analysis Results of Participation in Elderly personal factors and the participation of public health volunteers in promoting elderly health was Health Promotion found that which consistent with the study of The analysis of information on participation in Khaopatumthip (2014) the results of the study elderly health promotion was found that the showed that the health volunteers with age, participation in health promotion of the elderly was education level, religion, occupational status, at a moderate level with the mean equal to 3.33 income, different years of public health volunteers (S.D. = 0.51). When considered individually, it was service were affects participation in promoting found that participation in decision-making, health of the elderly differently. Table 1: Mean and standard deviation of participation of public health volunteers in elderly health promotion Participation of public health volunteers 3.27 S.D. Participation level Participation in decision-making 3.36 0.49 moderate Participation in operations 3.29 0.54 moderate Participating in receiving benefits 3.39 0.45 moderate Assessment participation 0.54 moderate 3.33 Overall level of participation 0.51 moderate International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

7. SUGGESTION P a g e | 47 Agencies involved with public health volunteers should be more likely to involve volunteers in collection in research to obtain more detailed decision-making by holding various meetings to information, such as in-depth interviews, and group allow public health volunteers to participate in chat. Should study or research in the area of other presenting their opinions or propose various districts to compare the results from this research. activities. This is because the health volunteers are local and know the needs of the people in the REFERENCES community. And know the health problems of the people in the community as well This will help Division of Communicable Diseases, Department of make working in the community more effective and Disease control, Ministry of Public Health, 2017, efficient. In making decisions volunteers should Annual Report 2017, (30). Aksorn Grphic and always be involved in their work. Volunteers should Design Publishing. be involved in meeting attendance every month. In further study, other factors related to participation in Khaopatumthip, K., 2014, Participation of Public health promotion of the elderly in Bang Khonthi Health Volunteers for Tambon Health Promoting District should be studied to gain more knowledge Hospital in Bhuddha - Monton District about the relationship with participation in Nakhonpathom Province. Srinakharinwirot promoting health of the elderly in Bang Khonthi University. District. Other techniques should be used for data Pongsaengpan, P. and Rodjarkpai, Y., 2014, Community Participation on Elderly Health Promotion. Burapha University. International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

P a g e | 48 MELIOIDOSIS IN NORTHEASTERN STATE OF MALAYSIA: SPATIAL ANALYSIS OF CASES AND THEIR SEQUENCE TYPES Siti Munirah Mohd Adib,1 Azian Harun,2 Ahmad Filza Ismail3* and Aziah Ismail4* 1Institute for Research in Molecular Medicine, Universiti Sains Malaysia, Malaysia E-mail: [email protected] 2Department of Medical Microbiology and Parasitlogy, School of Medical Sciences, Universiti Sains Malaysia, Malaysia E-mail: [email protected] 3Department of Community Medicine, School of Medical Sciences, Universiti Sains Malaysia, Malaysia E-mail: [email protected] 4Institute for Research in Molecular Medicine, Universiti Sains Malaysia, Malaysia E-mail: [email protected] *Corresponding authors ABSTRACT Melioidosis is caused by Burkholderia pseudomallei which can be found in water and soil, as well as in animals. This study was carried out to study the spatial distributions of the cases and their sequence types (ST) from the isolates. The cases were taken from the Hospital USM admission records from the years 2014 to 2019. There were 70 cases which from these cases 33 bacterial isolates were included in this study. Multi- locus Sequence Typing (MLST) was performed to the isolates. As the results, six novel STs were discovered. The cases were found to be clustered and concentrated in the northern part of the state. This study had revealed 15 different STs however, the predominant variant, ST371 (n=6) were found to be distributed in a dispersed manner. Meanwhile, the novel STs were found distributed sporadically in few districts of the state. KEYWORDS: Melioidosis, Sequence Types, Spatial Analysis 1. INTRODUCTION Malaysia. Thailand was reported to be the country Melioidosis is a highly pathogenic soil-dwelling with highest melioidosis cases compared to others infectious tropical disease caused by Gram-negative (Prakash et al., 2014). The expected worldwide bacilli named Burkholderia pseudomallei and incidence of melioidosis occurrence is reported as commonly found in rice paddy fields, ponds, 165,000 cases per year with the predicted annual stagnant streams and ground water (Baker et al., mortality of up to 54%. However, only less than 1% 2011). Melioidosis, also known as Whitmore’s was eventually reported reflecting to the burden of disease, was identified as a remarkable imitator and underreported and underdiagnosed of this neglected maladies mimicker (Vidyalakshmi et al., 2012). Its tropical disease in worldwide (Pumpuang et al., ability to resemble other pyogenic bacterial and 2017). Gram-negative bacterial infection leading to the manifestation of non-specific signs and symptoms Melioidosis was in recent years increase had limited the diagnosis and management of the reported sporadic cases in countries such as Middle disease (Vidyalakshmi et al., 2012 and Wiersinga et Eastern, Central and South American and African al., 2018). Melioidosis was highly transmitted countries (Chakravorty and Heath, 2019). Mortality through percutaneous inoculation of skin abrasion rate of melioidosis in worldwide is approximately to and in contact to contaminated soil and water 40% however the rate can be up to 90% if remain (Limmathurotsakul et al., 2016). This infection can untreated (Wiersinga et al., 2018). Due to lack of also be spread through the ingestion of any infected awareness among people especially the medical source of the bacteria and/or inhalation of aerosols practitioners had led to low diagnosis and low during extreme weather events such as typhoon and prognosis therefore high mortality was reported. cyclones (Chen et al., 2015 and Limmathurotsakul Annual incidence and fatality rate was highest in et al., 2016). Melioidosis is endemic in Northern Northeast Thailand while melioidosis was reported Australia and Southeast Asia such as Thailand and International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

P a g e | 49 as the fifth main cause of death in Singapore pubMLST (https://pubmlst.org/bpseudomallei/). (Hinjoy et al., 2018 and Liu et al., 2015). New allelic profiles of novel STs were submitted to curator to assign for new ST number. Predominant Melioidosis has been reported since 1913 and STs of B. pseudomallei isolates were determined. became one of the endemic diseases in Malaysia. Spatial analyses were done using ArcGIS 10.2 The incidence of the melioidosis in states of licensed to USM. Malaysia varies but six states had been recognized with higher melioidosis cases including Kedah, 4. RESULTS AND DISCUSSION Kelantan, Pahang, Johor, Sabah and Sarawak (Nathan et al., 2018). In Northeast Malaysia, 73.3% 4.1 Demographic Characteristics of patients with positive melioidosis infection were In this study, majority of cases were male due to known to be in contact with soil during working their nature of job in the field which involved (Yazid et al., 2017). More than 2000 patients die per farming and livestock which facilitate the exposure year in Malaysia due to melioidosis but no clear to environments (Wiersinga et al., 2018 and White, distribution between states was reported so far 2003). The highest incidence of melioidosis was (Nathan et al., 2018). reported in 48-63 years old (middle-aged group) patients followed by 15-47 years old (young-aged 2. OBJECTIVES group). These age groups were highly involved in The objectives of this study were to demonstrate the the agricultural and outdoor activities. Middle-aged spatial distribution of melioidosis cases in Kelantan group is known to have poor immune response from the years 2014 to 2019 and to determine the compared to other younger group (Puthucheary, sequence types of B. pseudomallei isolates in 2009). Comorbidities such as diabetes mellitus and Kelantan and their spatial distribution. hypertension were also most likely started to develop among this age group thus became highly 3. METHODOLOGY vulnerable for the infection (Deris et al., 2010). This study was conducted retrospectively with Three unknown age (4.3%) was reported due to the confirmed cases in Hospital USM from the years unavailable data from the patients’ records. Almost 2012 to 2019 were included into this study. The all of the cases were Malay ethnic since the majority coordinates for geographical information system of the Kelantan population is Malay ethnic (Sathian (GIS) were pointed to cases’ residential addresses. and Ngeow, 2014). Demographic characteristics of Genotyping using Multi-locus Sequence Typing the cases is shown in Table 1. (MLST) method of 33 isolates was performed from the 70 samples as the remaining samples were not 4.2 Distribution of the Cases feasible for isolates sequencing due to the inviable Cases of melioidosis in Kelantan were highly bacteria in the samples. Allelic profiles and reported in the northern part of Kelantan, namely in sequence type (ST) variants of the isolate sequences Kota Bharu (37.1%) and Bachok (27.1%) as shown were obtained from MLST database known as in Table 2. Table 1: Demographic characteristics of melioidosis cases (n=70) Variables Frequency (%) Gender 53 (75.7) Male 17 (24.3) Female Age group 6 (8.6) 0-14 years old (pediatric) 22 (31.4) 15-47 years old (young) 23 (32.9) 48-63 years old (middle) 16 (22.9) >63 years old (elderly) 3 (4.3) Unknown Ethnicity 69 (98.6) Malay 1 (1.4) Indian International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

Table 2: Distribution of melioidosis cases according P a g e | 50 to district (n=70) Both districts are known to have higher density of District n (%) population with high agricultural activities resulting Kota Bharu 26 (37.1) in the high exposure to soil as melioidosis is Bachok 19 (27.1) identified to be transmitted mainly from Pasir Puteh 12 (17.1) environments (Nathan et al., 2018 and Corkeron et Pasir Mas 6 (8.6) al., 2010). Spatial analysis of the cases showed that Tumpat 2 (2.9) cases were clustered with Nearest Neighbor Ratio Tanah Merah 1 (1.4) (NNR) 0.852672, z-score -20374899 and p-value Kuala Krai 1(1.4) 0.017554 (Figures 1 and 2). It means, cases Machang 3 (4.3) occurred with 95% probability that they were in clustered manner. In an infectious disease, the manner of distribution is important in applying action of control. Melioidosis cases in Kelantan also found to have hotspot which concentrated at Kota Bahru district with 90% to 95% confidence (Figure 3). Therefore, people presenting with symptoms of bacterial infection from this hotspot area must be taken extra caution and need to be tested for melioidosis. Figure 1: Distribution of melioidosis cases in Kelantan (n=70) International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

P a g e | 51 Figure 2: Nearest Neighbor Ratio (NNR) for distribution of melioidosis cases in Kelantan (n=70) Legend Figure 3: Hotspot area of melioidosis cases in Kelantan (n=70) International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

P a g e | 52 Table 3: Sequence types and total number of isolates of B. pseudomallei based on districts and reported countries (n= 33) Sequence Total District Reported Country Type (ST) isolate Pasir Puteh, Kota Bharu Thailand, Malaysia ST10 2 ST50 3 Kota Bharu, Bachok Malaysia, Thailand, China, Singapore ST54 5 Pasir Puteh, Kota Bharu, Bachok, Thailand, Malaysia, Singapore, United Kingdom Tumpat ST84 3 Pasir Puteh, Kota Bharu Australia, Thailand, Malaysia, Singapore ST289 3 Pasir Puteh, Kota Bharu, Bachok Thailand, Malaysia, Singapore ST366 2 Bachok Thailand, Malaysia, Vietnam, China ST371 6 Kota Bharu, Bachok Thailand, Malaysia ST414 2 Pasir Puteh, Bachok Thailand, Malaysia, Singapore, France ST1731 1 Bachok Malaysia (in this study) ST1732 1 Pasir Puteh Malaysia (in this study) ST1733 1 Bachok Malaysia (in this study) ST1734 1 Pasir Puteh Malaysia (in this study) ST1735 1 Bachok Malaysia (in this study) ST1736 1 Tanah Merah Malaysia (in this study) ST1737 1 Kota Bharu Malaysia (in this study) Legend Figure 4: Distribution of STs of B. pseudomallei in Kelantan (n=33) International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

4.3 Distribution of Sequence Types (ST) P a g e | 53 Multi-locus sequence typing (MLST) was conducted from the samples, however only 33 ST366 was found unique in Bachok and not isolated isolates were able to be obtained from the 70 in other districts. Novel variants were highly found reported cases. Analysis of the 33 isolates of B. in Bachok with 3 different STs (ST1731, ST1733 pseudomallei in this study had found 15 STs. Seven and ST1735). Spatially, the novel ST found of them were novel ST namely ST1731 to ST1737. sporadically in few districts namely Bachok, Pasir Other eight STs which were identified as ST10, Puteh, Kota Bharu and Tanah Merah (Figure 5). The ST50, ST54, ST84, ST289, ST366, ST371 and predominant variant found in this study was ST371 ST414 were already reported in previous studies (17.1%). This variant was only found and isolated in (Table 3). All the variants were closely related and districts of Kota Bharu and Bachok. Interestingly, previously isolated from Southeast Asia such as ST371 was found to be unique for Kelantan and was Thailand, Singapore and Vietnam including not isolated in other geographical area of other Malaysia. Figure 4 shows the spatial distribution of previous studies in Malaysia (Arushothy et al., 2020 the STs throughout the state. Bachok, with 9 and Zueter et al., 2018). Sequence types are found different STs, was identified as the highest district dispersed in this study, even the predominant ST with STs variability followed by Kota Bharu and (ST371) also found dispersed with NNR 2.225159, Pasir Puteh with both reported with 7 different STs. z-score 5.741152 and p-value <0.001 (Figures 6 and 7). Other study done in larger scale may show multiple hotspot of STs (Rachlin et al., 2020). Figure 5: Distribution of novel STs isolated in Kelantan (n=7) International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

P a g e | 54 Figure 6: Distribution of predominant isolate ST371 in Kelantan (n=6) Figure 7: Nearest Neighbor Ratio (NNR) for distribution of predominant isolate ST371 in Kelantan (n=6) International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

P a g e | 55 5. CONCLUSION Corkeron, M. L., Norton, R. and Nelson, P. N., Melioidosis cases in the state of Kelantan in general 2010, Spatial Analysis of Melioidosis were clustering in nature and concentrated in the Distribution in a Suburban area. Epidemiology northern part with Kota Bharu as the hotspot area of and Infection. Epidemiol Infect, Vol. melioidosis. Novel STs were found sporadic in 138(9),1346-1352. districts. However, Bachok district has the highest variability and most novel STs. The novel STs may Deris, Z. Z., Hasan, H. and Suraiya, M. N. S., 2010, cause more severe infection compared to other STs, Clinical Characteristics and Outcomes of therefore cases of melioidosis from this area need to Bacteraemic Melioidosis in a Teaching Hospital be given extra caution when being diagnosed. In a Northeastern State of Malaysia: a Five-Year However, further study to confirm the severity Review. The Journal of Infection in Developing should be conducted. Variety of B. pseudomallei Countries, Vol. 4(07), 430-435. strains revealed to be circulating in Kelantan and dispersed in the district were important to formulate Hinjoy, S., Hantrakun, V., Kongyu, S., a management plan of melioidosis in future. Kaewrakmuk, J., Wangrangsimakul, T., Therefore, better preventive plan can be further Jitsuronk, S., Saengchun, W., Bhengsri, S., applied for faster diagnosis and better prognosis Akarachotpong, T., Thamthitiwat, S., especially in case of any outbreak of the disease. Sangwichian, O., Anunnatsiri, S., Sermswan, R. W., Lertmemongkolchai, G., Tharinjaroen, C. ACKNOWLEDGEMENT S., Preechasuth, K., Udpaun, R., Chuensombut, P., Waranyasirikul, N., Anudit, C., Narenpitak, This study was funded by Universiti Sains Malaysia S., Jutrakul, Y., Teparrukkul, P., Teerawattanasook, N., Thanvisej, K., Suphan, Research University Grants (RUI) A., Sukbut, P., Ploddi, K., Sirichotirat, P., Chiewchanyon, B., Rukseree, K., Hongsuwan, (1001/CIPPM/8012207). We would like to M., Wongsuwan, G., Sunthornsut, P., Wuthiekanun, V., Sachaphimukh, S., acknowledge Hospital Universiti Sains Malaysia Wannapinij, P., Chierakul, W., Chewapreecha, C., Thaipadungpanit, J., Chantratita, N., and Department of Medical Microbiology and Korbsrisate, S., Taunyok, A., Dunachie, S., Palittapongarnpim, P., Sirisinha, S., Kitphati, Parasitology, School of Medical Sciences, R., Iamsirithaworn, S., Chaowagul, W., Chetchotisak, P., Whistler, T., Universiti Sains Malaysia for providing the Wongratanacheewin, S. and Limmathurotsakul, D., 2018, Melioidosis in Thailand: Present and melioidosis data and bacterial isolates for this study. Future. Trop Med Infect Dis, Vol. 3(2), 1-16, doi: 10.3390/tropicalmed3020038. REFERENCES Limmathurotsakul, D., Golding, N., Dance, D. A. Arushothy, R., Amran, F., Samsuddin, N., Ahmad, B., Messina, J. P., Pigott, D. M., Moyes, C. L., N. and Nathan, S., 2020, Multi Locus Sequence Rolim, D. B., Bertherat, E., Day, N. P. J., Typing of Clinical Burkholderia Pseudomallei Peacock, S. J. and Hay, S. I., 2016, Predicted Isolates from Malaysia. PLOS Neglected Global Distribution of Burkholderia Tropical Diseases, Vol. 14(12), 1-14, doi: Pseudomallei and Burden of Melioidosis. Nature 10.1371/journal.pntd.0008979. Microbiology, Vol. 1(1), 1-5, doi: 10.1038/nmic- robiol.2015.8. Baker, A., Tahani, D., Gardiner, C., Bristow, K. L., Greenhill, A. R. and Warner, J., 2011, Liu, X., Pang, L., Sim, S. H., Goh, K. T., Groundwater Seeps Facilitate Exposure to Ravikumar, S., Win, M. S., Tan, G., Cook, A. Burkholderia Pseudomallei. Applied and R., Fisher, D. and Chai, L. Y. A., 2015, Environmental Microbiology, Vol. 77(20), 7243- Association of Melioidosis Incidence with 7246. Rainfall And Humidity, Singapore, 2003–2012. Emerging Infectious Diseases, Vol. 21(1), 159 - Chen, P. S., Chen, Y. S., Lin, H. H., Liu, P. J., Ni, 162. W. F., Hsueh, P. T., Liang, S. H., Chen, C. and Chen, Y. L. 2015, Airborne Transmission of Nathan, S., Chieng, S., Kingsley, P. V., Mohan, A., Melioidosis to Humans From Environmental Podin, Y., Ooi, M. H., Mariappan, V., Aerosols Contaminated with B. Pseudomallei. Vellasamy, K. M., Vadivelu, J., Daim, S. and PLoS Neglected Tropical Diseases, Vol. 9(6), 1- How, S. H., 2018, Melioidosis in Malaysia: 16. Incidence, Clinical Challenges, and Advances in Understanding Pathogenesis. Tropical Medicine Chakravorty, A. and Heath, C. H., 2019, Melioidosis: an Updated Review. Australian Journal of General Practice, Vol. 48(5), 327- 332. International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

and Infectious Disease. Vol. 3(1). P a g e | 56 https://doi.org/10.3390/tropicalmed3010025. Prakash, A., Thavaselvam, D., Kumar, Ashu, Sathian, M. and Ngeow, Y., 2014, Essentialising Kumar, Ajith, Arora, S., Tiwari, S., Barua, A. Ethnic and State Identities: Strategic Adaptations and Sathyaseelan, K., 2014, Isolation, of Ethnic Chinese in Kelantan, Malaysia. Asian Identification and Characterization of Studies Review, Vol. 38(3), DOI:10.1080/1- Burkholderia Pseudomallei from Soil of Coastal 0357823.2014.936361. Region of India. SpringerPlus, Vol. 3(1), 1-10. Pumpuang, A., Dunachie, S. J., Phokrai, P., Vidyalakshmi, K., Lipika, S., Vishal, S., Damodar, Jenjaroen, K., Sintiprungrat, K., Boonsilp, S., S. and Chakrapani, M., 2012, Emerging Clinico- Brett, P. J., Burtnick, M. N. and Chantratita, N., Epidemiological Trends in Melioidosis: Analysis 2017, Comparison of O-polysaccharide and of 95 cases from Western Coastal India. Hemolysin Co-Regulated Protein as Target International Journal of Infectious Diseases, Antigens for Serodiagnosis of Melioidosis. PLoS Vol. 16(7), 491-497., DOI: 10.1016/j.ijid.2012- Neglected Tropical Diseases, Vol. 11(3), 1-20. .02.012. DOI:10.1371/journal.pntd.0005499. Puthucheary, S. D., 2009, Melioidosis in Malaysia. White, N. J., 2003, Melioidosis. Lancet, Vol. Medical Journal of Malaysia, Vol. 64(4), 266- 361(9370), 1715-1722. 274. Rachlin, A., Mayo, M., Webb, J. R., Kleinecke, M., Wiersinga, W. J., Virk, H. S., Torres, A. G., Currie, Rigas, V., Harrington, G., Currie, B. J. and B. J., Peacock, S. J., Dance, D. A. B. and Kaestli, M. 2020, Whole-genome Sequencing of Limmathurotsakul, D., 2018, Melioidosis. Burkholderia Pseudomallei from an Urban Nature Reviews Disease Primers, Vol. 4, 17107 Melioidosis Hot Spot Reveals a Fine-Scale - 17107. Population Structure and Localised Spatial Clustering in the Environment. Scientific Yazid, M. B., Fauzi, M. H., Hasan, H., Noh, A. Y. Reports, Vol. 10(1), DOI:10.1038/s41598-020- M. and Deris, Z. Z., 2017, An 11-Year Analysis 62300-8. of Emergency Presentations of Melioidosis in Northeastern Malaysia. Journal of Immigrant and Minority Health, Vol. 19(3), 774-777. Zueter, A. R., Rahman, Z. A., Abumarzouq, M. and Harun, A., 2018, Multilocus Sequence Types of Clinical Burkholderia Pseudomallei Isolates from Peninsular Malaysia and their Associations with Disease Outcomes. BMC Infectious Diseases, Vol. 18(1), 1-10. DOI:10.1186-/s12879-017-2912-9. International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

P a g e | 57 SPATIAL MAPPING AND TEMPORAL CORRELATION ANALYSIS BETWEEN MOSQUITO-BORNE DISEASES AND METEOROLOGICAL FACTORS IN MANNAR, SRI LANKA Withanage, K.K.S.A.,1*Tripathi1, N. K.,1 Chitrini Mozumder,1 RDJ Harishchandra,2 Prasad Ranaweera,2 AYK Perera,2 KGS Kalansooriya,2 Priyadarshan Emmanuel,3MAST Fernando2 and Mihirini Hewavitharane2* 1Remote Sensing and Geographic Information Systems, School of Engineering and Technology, Asian Institute of Technology, P.O. Box 4, Klong Luang, Pathumthani 12120, Thailand E-mail: [email protected], 2Anti Malaria Campaign, headquarters, Colombo 5, Sri Lanka, E-mail: [email protected] 3Regional Malaria Office, Anti Malaria Campaign, Mannar, Sri Lanka *Corresponding authors ABSTRACT: Mannar Island is 27.85 km² and belongs to the arid zone. Currently, no local malaria case has been found since October 2012, but there is a possibility of re-introducing malaria in Mannar due to its proximity to southern India. Dengue cases are recorded from the island. There is a general lack of studies on dengue and malaria mosquitoes’ behavior due to the island's unique climatic conditions. Therefore, the present study was carried out to analyze the temporal correlation between malaria and dengue vector mosquitoes and meteorological factors in Mannar Island in 2019. During 2019 year, 2063 breeding sites were surveyed, the 10% of sampling sites were identified with mosquito breeding. R studio was used to map spatial data for better visualization with its spatial packages. The most prevalent Malaria mosquitoes in Mannar were Anopheles stephensi, Anopheles culicifacies, Anopheles subpictus, and Anopheles varuna. The least pervasive was Anopheles tessellatus, An. nigerrimus, Aedes vittatus, Anopheles vagus, and Anopheles barbirostris. Dengue mosquitoes were Aedes aegypti and Aedes albopictus. For correlation analysis, Anopheles stephensi, Anopheles culicifacies, Anopheles subpictus, Anopheles varuna, Aedes aegypti, and Aedes albopictus were used. Spatial maps created using packages in R. Temporal correlation between monthly rainfall, temperature, relative humidity, and monthly mosquito larva density were studied using spearman correlation in R. Anopheles stephensi were correlated significantly and positively with all monthly meteorology factors. Both Dengue mosquitoes showed a negative correlation significantly with monthly temperature. Anopheles subpictus showed a significantly negative correlation with monthly temperature and humidity. Anopheles varuna showed a significantly negative correlation with rainfall and humidity. Except, Anopheles varuna and Anopheles stephensi, all other species showed a negative correlation with temperature. Humidity and rainfall have shown a higher correlation than temperature with Anopheles stephensi and Aedes aegypti incidences. There was a significant positive correlation between monthly rains with relative humidity. Meteorological variables play critical environmental roles in mosquito-borne disease transmission in Mannar Island. KEYWORDS: Anopheles stephensi, Malaria, Dengue, Vector Born Disease, Climatic Factors 1. INTRODUCTION culicifacies also breed in abandoned gem mining pits and agricultural wells. Other less notable 1.1 Background vectors include the Anopheles annularis, Anopheles There are two main species of malaria prevalent in subpictus, Anopheles tessellatus, and Anopheles Sri Lanka; Plasmodium falciparum and Plasmodium vagus, (Briet et al., 2003). Overall, each vector vivax. Predominantly, these malaria species' primary contributes to malaria's impact on Sri Lanka in vector is the Anopheles culicifacies, which mainly different dimensions ranging from zoophilic to breeds in pools and stagnant rivers; its density human infestation challenges. depends more on temporal and spatial variations in rainfall and the flow of the river. Notably, the An. International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

P a g e | 58 There is a varied distribution of Plasmodium vivax the Arid zone (Gunathilaka et al., 2016). The studies malaria incidence across the island. Similarly, about dengue and malaria mosquitoes’ behavior Plasmodium falciparum malaria presents with the with its unique climatic condition in the arid zone in same spatial patterns, though generally much lower. Sri Lanka are critical to mitigating. Moreover, Of particular interest is the prevalence of malaria in epidemiology studies with the application of the the North, where malaria shows one seasonal peak Geographic Information Systems (GIS) and R at the onset of each year (Gunathilakhe et al., 2019). software are widely used in spatial epidemiology to A southward range expansion of An. stephens was improve the management of the information first identified in India in the late 20th century. This obtained from the field survey and facilitate the can be attributed to urbanization's effects when analysis of the vector's distribution patterns species. water storage practices became more rampant and less healthy (Weeraratne et al., 2017). It was at this In 2016, Gunathilaka et al., (2016) identified time that attendant malaria transmission was further determinants and their potential impact on malaria experienced. An. stephensi was observed in Goa transmission in Mannar Island. But, there is no around 1970, Kanyakumari at India's southernmost study to understand the relationship between climate location in the 1980s, and spread out towards and malaria cases. In the malaria elimination phase Lakshadweep islands in the Arabian Sea in 2001. in Sri Lanka, investigation on spatial distribution Predictions in 2001 stated that An. stephensi may and association between malaria vectors and further move southwards to invade the Maldives and meteorological data are essential in planning Sri Lanka. In 2017, Anopheles stephensi was then appropriate vector control strategies. The Anti- detected for the first time in Sri Lanka on the island Malaria Program under the Ministry of Health is of Mannar along the northwestern coast of Sri currently in the anti-malaria mitigation and Lanka; accordingly, Mannar is in very close prevention stage to avoid malaria re-introduction. proximity with India (Briet et al., 2003). The year Therefore, they conduct an extensive survey over 2017 saw an escalation of dengue cases in Sri the past years in the northern province of Sri Lanka, Lanka. Almost 440 deaths were recorded about including Mannar Island. The present study aims to dengue, and nearly 187 thousand more cases were as the first study in Mannar island as an arid zone, recorded of those affected by dengue. On research, understand potential malaria vectors’ behavior, and it emerged that it was imminent with the Southwest dengue with the climate and spatially. monsoon's experience five weeks earlier. According to Tissera et al., (2020), Dengue is prevalently 1.2 Objectives increasing within areas that receive more than 2500 ▪To find the relationship between vector mosquitoes mm of rainfall. Mannar District is one of Sri Lanka's and meteorological factors in Mannar Island using R wetlands and so falls within the Dengu vulnerability studio zones (Gunathilake et al., 2015). ▪To map spatial data of mosquitoes using spatial packages in R and ArcGIS Malaria is an endemic and tropical and sub- tropic-based vector-borne disease. In the past, it was 2. METHODOLOGY a significant public health problem in Sri Lanka, with 100,000 cases of malaria each year 2.1 Study Area (Gunathilaka et al., 2016.). In 2017, the strain called The study area was Mannar Island in Mannar dengue plagued Sri Lanka raising the suspicion that District. Six Grama Niladari Divisions (GNDs) such vector-borne diseases do still have the potential were surveyed. These divisions are Periyakarisal, to wreak havoc on the island. Although Sri Lanka Siruthoppu, Pesalai North/ West/ South, and has not reported a local malaria case since 2012, Thullukudiyiruppu (Figure 1). there is a possibility of malaria re-emergence to Sri Lanka because of the island’s proximity to Southern 2.2 Data Collection and Analysis India. Furthermore, Anopheles stephensi, an During the 2019 year, 2063 sites: built wells, earth invasive potential urban malaria vector, recently wells, cement tank, rain pool and plastic buckeks. found new malaria species in the Northern Province, Metalic barrel, Ground pool and Stream Margin including Mannar Island (Gunathilaka et al., 2016 were surveyed. Ten Anopheles species were and Gayan Dharmasiri et al., 2017). It becomes a checked during data collection, namely (Table 1). major concern that newer Dengue cases are to be Monthly time series (for 2019) for mean expected in Sri Lanka. Although some studies on temperature, mean rainfall, and relative humidity Anopheles larval in Wet and Intermediate, it is hard data were collected from the Meteorological to find any published literature on Mannar island in Department in Sri Lanka. International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

P a g e | 59 Figure 1: Study area in Mannar Island Table 1: Mosquito species found in Mannar Island with their habitats and important to Sri Lanka Species Habitats Prevalence and Damage to Sri Lanka Anopheles stephensi Wells Potential vector for human malaria species Anopheles culicifacies Stream margins, wells, Majour vector for human malaria species Indoors, Spaceous Areas Anopheles subpictus Secondary vector for human malaria species Barrow pits, rainwater Anopheles varuna pools Zoophilic and highly distributed fatally Anopheles tessellatus Secondary vector for human malaria species Lagoon & wastewater Anopheles vagus Secondary vector for human malaria species Anopheles nigerrimus Dirty stagnant, sunlit 14.56% prevalence and major contributor of habitats malarial spread in some other countries. Rainwater, stagnant Open mashes, canals Anopheles barbirostris Clean biotic bodies of Feeding on both humans and animals increases Anopheles pallidus water the spread of diseases in some other countries. Canals and rainwater Risky cause of babesiosis & malaria in some pools other countries Aedes vittatus Rainwater pools and Human biter causing Zika virus Aedes aegypti marshes Aedes albopictus The main cause of Dengue and yellow fever Prefers clear water in man within its 4 wks life span made containers Top 100 invasive species. Secondary vector for Dengue Both artificial like tires and barrels and natural like tree holes International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

P a g e | 60 R studio, Excel, and ArcGIS 10.7 are used for Anopheles stephensi was found to be abundantly descriptive analysis, correlation analysis, and spatial breeding in built wells used for domestic purposes. data analysis. Correlation between monthly rainfall, Larval densities of all anophelines were highest temperature, relative humidity, and monthly during the monsoonal rains (May to July and mosquitoes’ larva density was analyzed using October to December), except for An. varuna. Spearman correlation in R studio. Larva density of each vector species was calculated using the 3.2 Spearman Correlation Analysis equation: Only the most prevalent vectors (Four species of malaria: Anopheles stephensi, Anopheles Larva density = (Number of larvae collected from culicifacies, Anopheles subpictus, Anopheles each species/total dips taken)*100 – varuna, and two species of dengue were used to analyze of Spearman correlation between vectors Equation 1 and meteorological parameters using R studio. The study area temperature in 2019 ranged between 24 3. RESULTS AND DISCUSSION ºC to 33.5 ºC, relative humidity (RH) was 65%- 83%; and rainfall between 0.5 mm- 475 mm. 3.1 The Most and Least Prevalent Vector Larva Based on the Spearman correlation analysis: in Mannar 10% of sampling sites (total: 2062) were identified 1. Anopheles stephensi were correlated positively as anopheles and dengue larva breeding sites. The with all meteorology factors making it a major most prevalent malaria-causing mosquitoes in prevalence in Sri Lanka. Mannar were identified as the Anopheles stephensi, Anopheles culicifacies, Anopheles subpictus, and 2. Anopheles subpictus showed a positive Anopheles varuna. Anopheles stephensi is an correlation with monthly rainfall, a negative invasive potential urban malaria vector in Sri Lanka. correlation with Minimum temperature hence Presenting as an indoor and spacious areas species, causing minimal challenges. the Anopheles culicifacies are the primary malaria vector. The other two, Anopheles subpictus and 3. Anopheles varuna showed a positive correlation Anopheles varuna are secondary malaria vectors in with temperature (Minimum and Maximum), Sri Lanka with a lower infection rate. making it a concern within the location's regular conditions. The least prevalent Malaria mosquitoes were Anopheles tessellatus, Anopheles nigerrimus, 4. Both Dengue mosquitoes showed a negative Anopheles vagus, and Anopheles barberiostris. It correlation with monthly temperature making was further established that there were two malaria temperature less significant. species which were not found from the Mannar Island, such as Anopheles tessellatus and Anopheles 5. Anopheles pallidus, Anopheles varuna, and vagus. Dengue mosquitoes; in particular, Aedes Anopheles stephensi only showed a positive aegypti and Aedes albopictus were prevalent on the correlation with temperature thus because of the island due to the constant presence of suitable aridity of the land becomes a minor concern. breeding locations and environment. Furthermore, the aridity of an area can help prevent mosquito 6. Significantly humidity and rainfall have shown a attacks. Hence families can be trained on how to higher correlation than temperature to Anopheles maintain semi-arid domestic life. According to Briet stephensi and Aedes aegypti incidences. et al. (2003), dengue is a fatal disease with a high potential for life-threatening-at times within a few Meteorological variables play essential hours. It presents a wide range of symptoms that can environmental roles in mosquitoes borne disease be as mild as a fever to more lethal ones like transmission in Mannar Island. bleeding (Messer et al., 2002). Both the Aedes aegypti and the Aedes albopictus contribute mainly 3.3 Spatial Distribution of Malaria Species over to the spread of such high-risk diseases in Sri Lanka. the Island Some of the challenges that have been encountered Anopheles stephensi prefers salinity and urban in previous mitigation attempts have included the areas. They might be introduced from South India to ability of the species to develop immunity to most Mannar. Thus it is called invasive malaria insecticides Anopheles stephensi (36.65%) was the (Surendran et al., 2019). The study area is near the most abundant anopheline species in the larval habitats in Mannar. It was found breeding together with Anopheles culicifacies (20.7%), Anopheles subpictus (13.5%), and Anopheles varuna (28.13%). International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

harbor, where boats from India interact with locals P a g e | 61 (Figure 2). 3.4 Autocorrelation A Global Moran’s I analysis is a Spatial Autocorrelation tool used to measure spatial autocorrelation based on feature locations and feature values to evaluate the distribution of a specific feature. In this instance, it was utilized using geographic distances and nearest neighbor analysis to indicate no spatial autocorrelation pattern. There is no relationship of geography with species larva density in the study (Figure 3). The prevalence of malaria is exacerbated by the water supplies on the island, giving rise to several favorable conditions for the mosquitos to breed. However, following studies by Sisirena and Noordeen (2014), malaria's impact is less due to abundant larval density indices. It is more due to the interactions between people and breeding sites of these mosquitos. In areas where there might be fewer water bodies to breed mosquitoes, people tend to be less aggressive with removing and destroying malarial vectors. Figure 2: Spatial distribution of main Anopheles larva The recorded number of species and their habitats distribution in Mannar Island: 1. 32 number of Anopheles varuna : 31 from built wells and 1 earth wells 2. 23 Anopheles subpictus: 22 built wells, 1 cement Figure 3: Relationship of geography with species tank, and 1 rain pool and Stream Margin. larva density 3. 48 Anopheles culicifacies: 44 built well, 3 In that same frame, dengue prevalence was said to cement tank, 1 plastic bucket have resulted in more government and authoritative medical interventions. For instance, WHO saw the 4. 80 Anopheles stephensi: 75 built wells, 4 cement introduction of prevention methods before being tanks, and 1 plastic bucket hard-hit to effectively ward off the onset of infection and discouraging host mosquitoes in the The importance of wells and buckets as breeding area for a time. To control and eventually do away places for Anopheles indicates that these habitats act with malaria and dengue-causing vectors, there is a as larval reservoirs during the dry season. Therefore, need to establish the factors that promote them. For built wells are the main habitats for Anopheles in example, focusing on giving insecticide to Mannar. Thus, this creates a potential threat to mosquitoes can eventually get too accustomed and malaria transmissions because; most of these wells develop resistance. were close to human habitations (Gunathilaka et al., 2016). Anopheles culicifacies and Anopheles varuna On the other hand, by setting up or doing away were also observed in wells. with the habitats and conditions supporting infestation, there is a longer-lasting solution of International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

simply destroying the habitats and hosts. In areas P a g e | 62 where mosquito breeding has been discouraged, there have been improvements in the number of REFERENCES cases recorded and fewer deaths within the area from other medical conditions (Dharshini et al., Briët, O., Gunawardena, D., van der Hoek, W. and 2011). By examining the different factors that Amerasinghe, F., 2003, Sri Lanka Malaria Maps, potentially lead to presence of dengue and mosquito Malaria Journal, Vol. 2(1), 1-10, in an area that include climatic conditions, potency https://doi.org/10.1186/1475-2875-2-22. of host mosquito in transmitting disease, areas of habitation which all contribute in varying degrees to Dharshini, S., Vinobaba, M., Jude, P., Karunaratne, both diseases. Similarly, it is worth observing how S. and Surendran, S., 2011, Prevalence and certain individuals have no interest in learning about Insecticide Susceptibility of Dengue Vectors in an illness or situation that they can very easily deal the District of Batticaloa in eastern Sri Lanka. with; but when ignored, it can lead to a series of Tropical Medicine and Health, Vol. 39(2), 47-52. infections, deaths, and post-infection challenges https://doi.org/10.2149/tmh.2010-19. been severe. For that reason, all recommendations that may be made will be in line with expanding on Gayan Dharmasiri, A. G., Yashan Perera,A., those activities that actually reduce mosquito Harishchandra, J., Herath, H., Aravindan, K., prevalence, thwart mosquito breeding in areas close Jayasooriya, H. T. R., Ranawaka, G. R. and to human beings, and destroy existing mosquito Hewavitharane, M., 2017, First record of breeds. Anopheles stephensi in Sri Lanka: a Potential Challenge for Prevention of Malaria There was a significant positive correlation Reintroduction. Malaria Journal, Vol. 16(1). between monthly rainfalls with relative humidity in https://doi.org/10.1186/s12936-017-1977-7. light of the above observations. Meteorological variables play critical environmental roles in Gunathilaka, N., Abeyewickreme, W., Hapugoda, M. mosquitoes borne disease transmission in Mannar and Wickremasinghe, R., 2015, Species Island. For example, Anopheles stephensi, an Composition and Diversity of Malaria Vector invasive potential urban malaria vector, is the most Breeding Habitats in Trincomalee District of Sri prevalent. Anopheles stephensi correlated positively Lanka. Biomed Research International, Vol. 1- with all meteorology factors. No relationship of 10. https://doi.org/10.1155/2015/823810 geography with mosquito species on the island. ArcGIS and R spatial analysis on health data is a Gunathilaka, N., Abeyewickreme, W., Hapugoda, M. crucial application in spatial epidemiology. It is the and Wickremasinghe, R., 2016, Determination conditions of an area that will promote certain of Demographic, Epidemiological, And Socio- mosquito species breeding, not the area's location. Economic Determinants and their Potential . Impact on Malaria Transmission in Mannar and Trincomalee Districts of Sri Lanka. Malaria 4. CONCLUSIONS Journal, Vol. 15(1). https://doi.org/10.1186/- While malaria has not been fully experienced in Sri s12936-016-1390-7. Lanka for several years, dengue's emergence is a significant thrust on the need for proactive action Gunathilaka, N., Hapugoda, M., Wickremasinghe, R. towards mitigating the risk of infection and impact and Abeyewickreme, W., 2019, A on Sri Lanka, mainly on Mannar. With the spatial Comprehensive Analysis on Abundance, distribution of both Dengue and malaria strains Distribution, and Bionomics of Potential Malaria across the island, it is clear that there are ways to Vectors in Mannar District of Sri Lanka. tackle both in more poignant methods through Malaria Research and Treatment, Vol. 1-13. medical interventions, government policies, and https://doi.org/10.1155/2019/1650180. awareness programs. Messer, W., Vitarana, U., Elvtigala, J., Sivananthan, 5. RECOMMENDATIONS K., Preethimala, L. and Ramesh, R., Withana, N., Features like rivers, small streams, forests, roads, Gubler, D. J. and De Silva, A. M., 2002, and residential areas and using a combination of Epidemiology of Dengue in Sri Lanka before field data, satellite image analysis, and GIS and after the Emergence of Epidemic Dengue technique for risk area mapping in the Northern Hemorrhagic Fever. The American Journal of Province will need to be prominently attended to in Tropical Medicine and Hygiene, Vol. 66(6), mitigating both susceptibility risk and impact. 765-773. https://doi.org/10.4269/ajtmh.2002.- 66.765. Sirisena, P. and Noordeen, F., 2014, Evolution of Dengue in Sri Lanka—changes in the Virus, Vector, and Climate. International Journal of Infectious Diseases, Vol. 19, 6-12. https://doi.org/10.1016/j.ijid.2013.10.012. International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

Surendran, S., Sivabalakrishnan, K., Sivasingham, P a g e | 63 A., Jayadas, T., Karvannan, K. and Santhirasegaram, S., Gajapathy, K., Tissera, H., Jayamanne, B., Raut, R., Janaki, S., Senthilnanthanan, M., Karunaratne, S. P. and Tozan, Y., & Samaraweera, P., Liyanag, P., Ramasamy, R., 2019, Anthropogenic Factors Ghouse, M., de Silva, A. M. and Fernando, D., Driving Recent Range Expansion of the Malaria 2020, Severe Dengue Epidemic, Sri Lanka, 2017. Vector Anopheles stephensi. Frontiers In Public Emerging Infectious Diseases, Vol. 26(4), 682- Health, Vol. 14(7), 1-11, https://doi.org/- 691. https://doi.org/10.3201/eid2604.190435. 10.3389/fpubh.2019.00053. Weeraratne, T., Surendran, S., Reimer, L., Wondji, C., Perera, M., Walton, C. and Parakrama Karunaratne, S. 2017, Molecular Characterization of Anopheline (Diptera: Culicidae) Mosquitoes from Eight Geographical Locations of Sri Lanka. Malaria Journal, Vol. 16(1). https://doi.org/10.1186/s12936-017-1876- y. International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

P a g e | 64 SURVEILLANCE MODEL FOR SOIL- TRANSMITTED HELMINTHIASIS IN MEKONG BASIN: A SPATIAL ANALYSIS USING TECHNOLOGY INFORMATION Yongyuth Puriboriboon1,2,3, Sutthisak Noradee1,2 and Choosak Nithikathkul1,2 1Health Science Program, Faculty of Medicine, Mahasarakham University, Thailand E-mail: [email protected] 2Tropical and Parasite Disease Research Unit, Master Program in Tropical Health Innovation, Faculty of Medicine, Mahasarakham University, Thailand, E-mail: [email protected] 3Faculty of Science, Asia-Pacific International University, Thailand ABSTRACT Soil-transmitted helminthiasis (STH) is the most common infectious helminth throughout the world, affecting the human population in tropical and subtropical regions. STH infections remain significant in public health in Southeast Asia, especially in countries along the Mekong basin. This study aimed to analyze spatial distribution characteristics of Ascaris lumbricoides, Trichuris trichiura, and hookworms in the Mekong basin countries: Cambodia, Laos, and Thailand with the application of geographical information system (GIS) relative to population density to generate predictive surveillance models. Recent modeling revealed that three countries showed a similar infection prevalence pattern; hookworm infection constituted 20.2%, followed by Trichuris trichiura (4.5%) and Ascaris lumbricoides (4.2%), respectively. STH infections were varied relative to population density in countries along the Mekong basin. Differences in the prevalence of infections relative to population density presumably reflect variations in environmental conditions and the type of works in each particular region. These GIS applications provide essential information to estimate the countries' helminth infection situation along the Mekong basin. They can be applied to formulate strategic plans to control STHs infection in the region. KEY WORDS: Soil-Transmitted Helminthiasis, Surveillance Model, GIS, Mekong Basin 1. INTRODUCTION filariform larva. The larva penetrates the host skin at Soil-transmitted helminth (STH) infections are one this infective stage primarily by walking barefoot of the neglected tropical diseases (NTDs) that affect and continuing their life cycle (CDC, 2015). over 1.5 billion people or 24% of the world Improper sanitation and hygiene, education, and population (Pullan et al., 2014). Because of its high socioeconomic status are the main risk factors for prevalence, the world health organization is seeking STHs infection. The morbidity caused by STHs is to reduce or eradicate the epidemic of STH varied, and most of the illness is asymptomatic in infections by 2030 as one of its sustainable low infection intensity. development goals (WHO, 2020). The most common STH infections are Ascaris lumbricoides However, a high number of embedded worms (roundworm), Trichuris trichiura (whipworm), may contribute to some crucial morbidities, for Necator americanus, and Ancylostoma duodenale example, intestinal obstruction caused by Ascaris (hookworms) (Bethony et al., 2006). A. lumbricoides, anemia caused by hookworm, and lumbricoides and T. trichiura have similar rectal prolapse in trichuriasis cases (Brooker et al., transmission routes. The adult worms live in the 2006, Pullan and Brooker, 2012 and Weller and intestine of their hosts and pass their eggs in the Nutman, 2018). The infections are widely feces of infected persons. Fertilized eggs distributed in tropical and subtropical regions, contaminate dirt, plants, or fruits and can be especially in low-income and low-middle-income transmitted by ingestion as a consequence of poor countries. STH infections remain significant in sanitation and hygiene. For hookworm, fertilized Southeast Asia's public health, especially in eggs that are passed in the feces develop into countries along the Mekong basin (Pullan et al., International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

2014). In the 21st century, geographical information P a g e | 65 system (GIS) plays a significant role in predicting and providing information on tropical diseases. association between STH prevalence and population There were several GIS models have been proposed density. These included the following countries: to understand the distribution of STHs in this Laos, Cambodia, and Thailand based on currently region. For example, geographic information of available data. This study's secondary data were helminthiasis in Thailand (Wongsaroj et al., 2012), mainly obtained from the national survey of health informatics models of STHs relative to land helminthiasis (Laymanivong et al., 2014, Wongsaroj use and soil type in Thailand (Nithikathkul et al., et al., 2014 and Yong et al., 2014) and population 2017), the geographical distribution of STHs in density data retrieved from the Worldometer South Asia and Southeast Asia related to website respected to the year of the national survey community type (Silver et al., 2018). However, of STH infections of each country there was little information on the association of (https://www.worldometers.info). An ArcGIS STH infections and population density in the Desktop program (ESRI, Bangkok, Thailand) was Mekong basin countries. Therefore, this study aimed implemented to generate predictive surveillance to analyze spatial distribution characteristics of models for STHs in the study region. Ascaris lumbricoides, Trichuris trichiura, and hookworms in the Mekong basin countries: 3. RESULTS Cambodia, Laos, and Thailand with the application Recent STH spatial surveillance modeling revealed of geographical information system (GIS) relative to that three countries showed a similar infection population density to generate predictive prevalence pattern; hookworm infection constituted surveillance models. 20.2%, followed by T. trichiura (4.5%) and A. lumbricoides (4.2%), respectively. According to the 2. MATERIALS AND METHODS national survey of helminthiasis in Thailand, it showed We reviewed open access literature from countries that people in the southern part of Thailand were along the Mekong river basin to assess the affected by the three STHs more than other regions, followed by the northern and northeastern part of Thailand, shown as prevalent red dots in Figure 1, 2, 3. Figure 1: Spatial distribution of hookworm Figure 2: Spatial distribution of Trichuris infections relative to the population distribution infections relative to the population distribution in Thailand in Thailand International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

P a g e | 66 Figure 3: Spatial distribution of Ascaris infections Figure 5: Spatial distribution of hookworm infections relative to the population distribution in Thailand relative to the population distribution in Cambodia Figure 4: Spatial distribution of STH infections Figure 6: Spatial distribution of Trichuris infections relative to population distribution in Laos; (Red) relative to the population distribution in Cambodia hookworm, (Blue) Ascaris lumbricoides, and (Yellow) Trichuris trichiura International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

Figure 7: Spatial distribution of Ascaris infections P a g e | 67 relative to the population distribution in Cambodia This study suggests that geographical diversity in The findings demonstrated in Figure 3 regarding STH the prevalence of STH infection and species prevalence distributions showed that hookworm was distribution presumably reflect variations in the highest burden in all regions compared to the other environmental conditions as well as the type of two STH species. Interestingly, these STH surveillance works in each particular area. Earlier studies models of Thailand revealed that regions with low indicated that the dynamic processes involved in population density had higher STH infections. STH transmission primarily depend on Inversely, in Laos, hookworm infection was higher in environmental conditions. Suitable soil moisture, the high population density region, the southern part of relative atmospheric humidity, and warm Laos, and it was the most significant burden in all temperature enhance eggs and larvae's development regions (Figure 4). and survival (Dold and Holland, 2011, Mascarini- Serra, 2011 and O’Lorcain and Holland, 2000). However, Trichuris. trichiura seemed to have more Moreover, land use, soil type, rainfall, and work effect in low population density area, as shown in the types might also influence the human host's northern part of the model. Figures 5, 6, 7 are STH infection intensity (Mabaso et al., 2003 and spatial surveillance models generated from the national Nithikathkul et al., 2017). The pattern of species survey of helminthiasis in Cambodia in 2015. The distributions are disproportionate in all countries models illustrated that the infections of STHs were regarding population density; all three STH species widely distributed in all regions regardless of found higher infection in low population density in population density, represented by big prevalent red Thailand, hookworm was more prominent in high dots found in both high and low population density population density and Trichuris infection was areas. Similar to Thailand and Laos, hookworm was higher in the northern region of Laos. STH the highest infection in all regions. infections were widely distributed in Cambodia. This is not consistent with Bartsch and colleagues 4. DISCUSSION AND CONCLUSION (2016) finding that rural communities in Southeast The prevalence of STH infections varies relative to Asia had higher hookworm infections than urban population density in countries along the Mekong communities. Hookworm infection is a significant River. burden in all countries, followed by Trichuris tirchiura, and Ascaris lumbricoides. The southern region of Thailand and Laos have a higher prevalence of hookworm compared to the other areas. It is suggested that this is associated with local climate and environmental conditions rather than individual behavior. These GIS applications provide essential information to estimate the countries' helminth infection situation along the Mekong basin. They can be applied to formulate strategic plans to monitor STH infection in the region. This study suggests that further research is needed to provide updated information and other variants that can be applied to generate an effective STH surveillance model for long-term control and prevention of STH infections in the region. ACKNOWLEDGEMENTS We also would like to thank the following institutes for their great supports to this research: Health Science Program, Faculty of Medicine, Mahasarakham University, Thailand; Tropical and Parasite Disease Research Unit, Faculty of Medicine, Mahasarakham University, Thailand; Faculty of Science, Asia-Pacific International University International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

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P a g e | 69 FACTORS OF KNOWLEDGE AND ATTITUDE ABOUT DENGUE HAEMORRHAGIC FEVER (DHF) THAT AFFECT THE BEHAVIOR OF DHF PREVENTION USING GEOGRAPHIC INFORMATION SYSTEMS (GIS) IN AGRICULTURIST IN TAKET SUB-DISTRICT UTHUMPHON PHISAI DISTRICT SISAKET PROVINCE Klarnarong Wongpituk,1* Aree Sanguanchue,1 Nirobon Ma-oon,1 Sutthida kaewmoongkun,1 Nonlapan Khantikulanon,1 Naphatsaran Roekruangrit,1 Sasiwimol Chanmalee,1 Tammasak Saykaew,1 Warangkana Chankong2 and Tiwakron Prachaiboon1 1Faculty of public health, Valaya Alongkorn Rajabhat University under the Royal Patronage, Thailand 2School of Health Sciences, Sukhothai Thammathirat Open University, Thailand *E-mail: [email protected] ABSTRACT This study was based on a survey. The purpose of this study was to investigate the aspects of knowledge and attitude regarding Dengue Haemorrhagic Fever (DHF) that influence DHF preventative behavior using Geographic Information Systems (GIS). The population of 282 agriculturists in Taket sub-district Uthumphon Phisai District, Sisaket Province was studied. Statistics such as frequency, percentage, mean, standard deviation, and Chi-square statistics are used to analyze data. The study's findings indicated that factors like occupation and attitudes toward DHF were associated with Agriculturists' DHF preventative actions. However, the findings revealed that gender, age, and DHF awareness were not associated with DHF preventative activities among agriculturists in the Taket sub-district, Uthumphon Phisai District, Sisaket Province. A spatial map was built in real-time utilizing GIS as a tool for site design. Recommendations should encourage the development of health network partners' ability in DHF knowledge, attitudes toward DHF prevention, and DHF preventative behavior. The community should be encouraged to take independent action. There should be a DHF knowledge program activity that is up to date. Continue to expand the use of GIS in public health. KEYWORDS: Dengue Haemorrhagic Fever (DHF), Knowledge, Attitude, Behavior, Health Network, GIS 1. INTRODUCTION The situation of dengue fever in Sisaket province Dengue fever is a mosquito-borne disease that was discovered to be as follows: from January 1st, affects many tropical and subtropical countries. 2020, to December 31th, 2020, there were 908 cases Dengue fever is common in Asia, the Caribbean, of DHF cases, representing 61.71 cases per 100,000 America, and Africa. Mosquito bites transmit the people. No deaths were reported. There were male dengue virus to humans. The dengue virus comes in patients equal to females, with 9 males and 9 four varieties. Once infected with one of the viruses, females. The female and male ratio was 1.13: 1. The you develop immunity to it for the rest of your life. most common age group was the 10-14 years of age This immunity, however, will not protect you from group, accounting for the morbidity rate of 290.7 other infections. It is possible to become infected per 100,000 people. Followed by the age group 15- with all four types of dengue virus during your 24 years, 5-9 years, 0–4 years, 25-34 years, 35-44 lifetime. According to current scientific research, years, 55-64 years, 45–54 years, 65 years and over. continuous infections may raise the likelihood of The morbidity rates were 246.68, 179.39, 55.54, severe dengue fever infections. Dengue fever has 45.7, 19.84, 16.32, 7.35 and 6.06 per 100,000 become the leading cause of infection and mortality people, respectively, Sisaket Provincial Health in certain Asian nations, Vector borne diseases Office, (2021). prevention and control program, (2021). International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

P a g e | 70 The highest number of cases was found in July 191 Figure 1: Sisaket province cases. There were 105 cases of municipal cases, the Sub-District Administrative Organization area of Figure 2: Taket sub-district 804. More patients were found in sub-district administrative areas than in municipalities. The This study collected data on the gender factor that number of cases in the Sub-District Administrative was not associated with the prevalence of Dengue Organization was 88.45%, while municipal patients Fever in Western Uttar Pradesh, India: a gender- were 11.55%. In 2020, the morbidity rate for DHF based study. The difference in male and female in Uthumporn Phisai district is 52.31, and there have preponderance among all seropositive patients was been reports of morbidity. Every year, Taket sub- statistically significant, according to the findings district and the area close to the dengue epidemic (P< 0 . 0 0 1 ) , Kumar et al., (2020). The factor of area have recorded DHF rates greater than the occupation could not be shown to be associated with required threshold, Sisaket Provincial Health Office, dengue prevention in the risk factors of dengue (2021). fever in a Vietnamese urban region, Nguyen-Tien et al., (2021). According to the examination of Literature review related factors found that thrombocytopenia in Dengue infection, coupled Knowledge and awareness regarding dengue, with seasonal change in rural Melmaruvathur, age (prevention of the vector breeding, bites of was a factor, with a statistically significant mosquitoes, disease symptoms, and waste association (p<0 . 0 5 ) was found between the age management) and attitudes of the community groups, Khan et al., (2014). (towards home gardening, composting, waste management, and maintenance of a clean and The data collected from this research were DHF dengue free environment) are associated with the knowledge factors associated with DHF dengue fever, Udayanga et al., (2018). Furthermore, preventative behavior among agriculturists, which research has indicated that the increasing or were the variables included in the knowledge. decreasing incidence of dengue infection is dependent on people's knowledge, attitude, and behavior about dengue, and it appears to be low among educated individuals as well, Nisha et al., (2020). At the time, there was no association between knowledge and attitude and dengue cases. As a result, the researcher must perform studies on this subject. The purpose of this study was to investigate the aspects of knowledge and attitude regarding DHF that influence DHF preventative behavior using Geographic Information Systems (GIS). 2. MATERIAL AND METHOD This study was based on a survey. The purpose of the study was to investigate the determinants of knowledge and attitude regarding DHF that influence DHF preventative behavior among agriculturists using Geographic Information Systems (GIS). The population was agriculturists in twelve villages, totaling 282 people. Taket sub- district, Uthumphon Phisai District, Sisaket Province served as the research site, shown in figure 1 and 2. Participants were those who stayed in the study field for at least a year and took part in community public-interest activities. Agriculture is the most common occupation, though there are a few others. Taket Sub-district is located on the border of Uthumphon Phisai District and Muang Sisaket District, and it is the scene of an annual epidemic. There are certain characteristics of places that spread quickly. International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

P a g e | 71 According to studies in socio-economic, knowledge was used to assess the questionnaire's reliability. For attitude practices (KAP), household related and accurate and effective collecting, a trained research demographic based appearance of non-dengue assistant was used in this study. The frequency, infected individuals in high dengue risk areas of percentage, mean, and standard deviation were used Kandy District, Sri Lanka. It contains a variable that to analyze the data in this study. Using chi-square knowledge. That knowledge was associated with the testing with a GIS program to analyze the dengue free status of the study populations, association between factors. Udayanga et al., ( 2018) . While not according to research on community knowledge, awareness, and 3. Result preventative behaviors for dengue fever in The results showed that the majority of female Puducherry, South India. It has a variable called participants were 59.6%, average age of 43.4 years, knowledge. There is no significant difference in with the most ages being 68 and the lowest being dengue knowledge. It has a variable called 18. While the secondary occupations of the knowledge. That understanding was linked to the participants showed that the most agriculture 59.2%, study communities' lack of dengue fever, Jeelani et followed by trade 14.5%, freelance 9.2%, and al., (2015). Which was the variable included the laborer 6.7%, respectively, and the least were attitude about DHF. According to studies in officialdom, company employees and students, 7%, Knowledge, attitude, practices related to dengue shown in Table 1. The results of this study showed fever among rural population in Terengganu, the relationship between gender age and secondary Malaysia. It contains a variable that attitude. That occupation with DHF preventive behavior. The attitude were found to be significant associated second occupation includes agriculture, trade, factors for having good practice against Dengue, freelance, laborer, other, officialdom, company Aung et al., (2016). Not according to studies in employee, and the student was significantly social-ecological factors and preventive actions associated with Behavior of DHF Prevention at decrease the risk of dengue infection at the level 0.05. However, there was no correlation household-level: Results from a prospective dengue between gender and age group with DHF preventive surveillance study in Machala, Ecuador. It contains behavior, represented by Table 2. Tests showed that a variable that attitude. There was not associated the relationship between attitudes about DHF with with attitude to prevention activities, Kenneson et the behavior of DHF prevention was significantly al., (2017). The instrumentation used to collect data correlated at 0.05, while knowledge of DHF had no for this study was a questionnaire. Quality relationship to the behavior of DHF Prevention, validation of the content validity instrumentation by represented by Table 3. five experts. Cronbach's Alpha coefficient of 0.82 Table 1: Demographic information of population International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

P a g e | 72 Table 2: Relationship between gender, age and secondary occupation and behavior of DHF prevention * p < 0.05 Table 3: Relationship between knowledge of the DHF and attitude about DHF with behavior of DHF prevention * p < 0.05 Figure 3: Knowledge of DHF in agriculturist using GIS The application of geographic information system application of GIS to create maps, spatial models, to (GIS) in the knowledge level of spatial simulation identify attitudes about DHF of agriculturists in maps to identify the level of DHF knowledge of research areas. The most common results showed agriculturists in research areas. Results were found villages with high levels of attitudes about DHF, 6 that the most were villages with a medium level of areas (villages 1, 4, 5, 6, 7, and 8). The second was DHF knowledge, 6 areas (villages 1, 4, 5, 6, 7, and 4 villages with a medium level of attitude about 8). The second was a low level of DHF knowledge, DHF (villages 3, 9, 10, and 12). Followed by the 5 areas (village 2, 3, 9, 10, and 12). Followed by most level of attitude and a minimal level of attitude One village with a high level of DHF knowledge is were villages 11 and 2 respectively, represented by village 11, represented by Figure 3. Demonstrate the Figure 4. International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International

P a g e | 73 Figure 4: The attitude about DHF in agriculturist using GIS 4. Conclusion and Discussion significant associated factors for having good The results of this study showed the second practice against Dengue, as represented by Aung et occupation (agriculture, trade, freelance, laborer, al., (2016). Not according to studies in social- other, officialdom, company employee, and the ecological factors and preventive actions decrease student) was significantly associated with Behavior the risk of dengue infection at the household-level: of DHF Prevention at level 0.05. Indicated that the Results from a prospective dengue surveillance second occupation was an important factor in the study in Machala, Ecuador. It contains a variable occurrence of self-defense behaviors from DHF for that attitude. There was not associated with attitude the participants (agriculturist primary occupation). to prevention activities, as reported by Kenneson et The reasons for different occupational traits have al., (2017). Geographic information system (GIS) is different activity characteristics that may be applied in this study. A spatial simulation map has contributing to the promotion of self-defense against been created that facilitates the management, DHF. However, there may be occupational activities prevention, and control of DHF with accurate and that facilitate the neglect of self-defense from DHF. real-time operation in vulnerable areas. The spatial Consistent with attitude, and practice regarding simulation maps identify the level of DHF dengue virus infection among inhabitants of Aceh, knowledge of agriculturists in research areas. That Indonesia found that attitudes are associated with identify attitudes about DHF of agriculturists in the prevention of DHF, as reported by Harapan et research areas. According to studies in estimating al., (2018). It contradicted the findings of a study of and mapping the incidence of dengue and preventative behaviors linked to dengue fever chikungunya in Honduras during 2015 using control methods among adults in the community. Geographic Information Systems (GIS), as reported There were not associated with attitudes towards by Zambrano et al., (2017). Also, according to dengue fever in the capital of Laos, as reported by studies in Using analytic hierarchy process with GIS Sayavong et al., (2015). for Dengue risk mapping in Kolkata Municipal Corporation, West Bengal, India, as represented by However, the result showed the relationship Ali et al., (2018). However, the development of between attitude about DHF with the behavior of DHF preventive and control processes is still DHF Prevention was significantly correlated at 0.05. required in order to analyze the effect factors for The reason that positive attitudes are the thoughts of prompt correction as they change over time. This each person arising from experiences such as includes both individual and societal factors. This is training, campaign, etc. When considering the issue essential required in order to design efficient disease of dengue prevention among agriculturists, it can be preventive and control measures. GIS has always linked to behaviors that arise from positive played a key role in maintaining consistent and up- attitudes. Therefore, it is necessary to establish a to-date driving. good attitude, which depends on the context. According to studies in Knowledge, attitude, Acknowledgement practices related to dengue fever among rural Researchers would like to thank the President and population in Terengganu, Malaysia. It contains a administrators of Valaya Alongkorn Rajabhat variable that attitude. That attitude were found to be International Journal of Geoinformatics, Conference Proceedings for 7th HealthGIS Conference ISBN No: 978-616-90698-5-0 © Geoinformatics International