Development of Transmission Models of Dengue Hemorrhagic Fever in relation to Climate and Landscape Changes in Tourism and Urbanized Areas of Phuket Province

Authors

  • Surachart Koyadun Office of Disease Prevention and Control Region 11 Nakhon Si Thammarat

Keywords:

Model development, Dengue, Climate, Landscape, Urban, Tourism Areas

Abstract

This research aimed to 1) analyze factors that influence the population dynamics of Aedes vectors 2) create models for the spread of dengue fever. The study design was analytical observation research, quasi-experimental study. The study samples consisted of 740 households in urban and tourism areas from 6 study sites of 3 districts of Phuket Province [Mueang District: 1) Taladyai/Taladnua Sub-district, Taladyai community 120 Households (HHs) 2) Rawai Sub-district, Ban Taimai community 123 HHs Kathu District: 3) Pathong Sub-district, Bannanai community 121 HHs 4) Kamala Sub-district, Bannorkle Sub-district, 121 HHs Talang District: 5) Chuengtale Sub-district, Bangtaonork community 126 HHs 6) Sakoo Sub-district, Banbangmalao community 129 HHs]. A total of 6 study sites, which were urban and tourism areas, were selected using two criteria, including 1) landscape information and building styles, land use and social economic conditions 2) the boundaries of the study area which were related to the boundaries of the administrative area. The study was carried out during 2018 – 2019. Research results indicated that factors regarding landscape, geography and environmental conditions of buildings affected the number and abundance of Aedes mosquitoes and the emergence of dengue fever. The results of classifying and analyzing land use characteristics of Phuket Province from aerial or satellite imagery data could be summarized into 9 main categories: mostly agriculture, followed by forest, urban area, resort, golf court, sea & beach, commercial area, water body and livestock, respectively. The analysis results of the relationship between the dengue incidence and the topographic factors in the area of mean elevation from the sea concluded that almost all patients were in the altitude zone not exceeding 100 meters, consistent with the slope type topography, mostly found in flat areas. While the relationship between the dengue incidence and the climatic factor regarding total annual rainfall was found to be in the positive direction; areas in the south mostly appeared in the zones of Mueang and Kathu Districts showed high rainfall values and decreased when the position moved to the north, namely Thalang District. As for the number of dengue fever patients, when classified by district, it was found that Mueang Phuket District had the highest number of patients every year. Findings from this research have important implications for surveillance, prevention, and early control of dengue fever and can be applied to develop effective and sustainable models and approaches for integrated vector-borne disease management.

References

World Health Organization. Dengue-Global Situation. [Internet]. Geneva: World Health Organization; 2023 [Cited 2024 May 5]. Available from: https://www.who.int/emergencies/disease-outbreak-news/item/2023-DON498.

สุรชาติ โกยดุลย์. An Eco-Bio-Social Approach To Assess Dengue Transmission Dynamics in Thailand.[วิทยานิพนธ์ปริญญาเอกปรัชญาดุษฎีบัณฑิต]. กรุงเทพฯ: มหาวิทยาลัยมหิดล; 2553. 211 หน้า.

Neira M, Erguler K, Ahmady-Birgani H, AL-Hmoud ND, Fears R, Gogos C, et al. Climate change and human health in the Eastern Mediterranean and Middle East: Literature review, research priorities and policy suggestions. Environ Res 2023;216:114537.

Koyadun S, Butraporn P, Kittayapong P. Ecologic and sociodemographic risk determinants for dengue transmission in urban areas in Thailand. Interdiscip Perspect Infect Dis 2012: 2012;907494.

Gubler DJ. Dengue, urbanization and globalization: the unholy trinity of the 21stcentury. Trop Med Health 2011;39(4 Suppl):3-11.

Thammapalo S, Chongsuvivatwong V, Geater A, Dueravee M. Environmental factors and incidence of dengue fever and dengue haemorrhagic fever in an urban area, Southern Thailand. Epidemiol Infect 2008;136:135-143.

Tozan Y, Sjödin H, Muñoz ÁG, Rocklöv J. Transmission dynamics of dengue and chikungunya in a changing climate: do we understand the eco-evolutionary response? Expert Rev Anti Infect Ther. 2020;18(12):1187-93.

สุรชาติ โกยดุลย์, อดิศักดิ์ ภูมิรัตน์. นิเวศระบาดวิทยาและพลวัตการแพร่ไวรัสเด็งกี่. วารสารสาธารณสุขมหาวิทยาลัยบูรพา 2565;17(1);44-57.

Pasin C, Halloran ME, Gilbert PB, Langevin E, Ochiai RL, Pitisuttithum P, et al. Periods of high dengue transmission defined by rainfall do not impact efficacy of dengue vaccine in regions of endemic disease. PLoS One 2018;13(12):1-16.

Rahman KM, Sharker Y, Rumi RA, Khan MI, Shomik MS, Rahman MW, et al. An Association

between Rainy Days with Clinical Dengue Fever in Dhaka, Bangladesh: Findings from a Hospital Based Study. Int J Environ Res Public Health 2020;17(24):1-9.

Ibrahim Abdulsalam F, Yimthiang S, La-Up A, Ditthakit P, Cheewinsiriwat P, Jawjit W. Association between climate variables and dengue incidence in Nakhon Si Thammarat Province, Thailand. Geospat Health 2021;16(2):1-14.

Chumpu R, Khamsemanan N, Nattee C. The association between dengue incidences and provincial-level weather variables in Thailand from 2001 to 2014. PLoS One 2019 Dec 26;14(12):1-14.

Rahman MS, Ekalaksananan T, Zafar S, Poolphol P, Shipin O, Haque U, et al. Ecological, Social, and Other Environmental Determinants of Dengue Vector Abundance in Urban and Rural Areas of Northeastern Thailand. Int J Environ Res Public Health. 2021;18(11):5971.

Saifur RG, Dieng H, Hassan AA, Salmah MC, Satho T, Miake F, et al. Changing domesticity of Aedes aegypti in northern Peninsular Malaysia: reproductive consequences and potential epidemiological implications. PLoS One 2012; 7(2):e30919.

Meyer WB, Turner II BL. Human population growth and land-use/cover change. Annu Rev Ecol Syst 1992; 23(1):93–61.

Pakaya, R., Daniel, D., Widayani, Utarini A. Spatial model of Dengue Hemorrhagic Fever (DHF) risk: scoping review. BMC Public Health 2023;23(2448):1-16.

Akter R, Hu W, Naish S, Banu S, Tong S. Joint effects of climate variability and socioecological factors on dengue transmission: epidemiological evidence. Trop Med Int Health 2017;22(6):656-69.

Zellweger RM, Cano J, Mangeas M, Taglioni F, Mercier A, Despinoy M, et al. Socioeconomic and environmental determinants of dengue transmission in an urban setting: An ecological study in Nouméa, New Caledonia. PLoS Negl Trop Dis 2017;11(4):e0005471.

Bekoe C, Pansombut T, Riyapan P, Kakchapati S, Phon-On A. Modeling the Geographic Consequence and Pattern of Dengue Fever Transmission in Thailand. J Res Health Sci. 2016;17(2):378.

Chen Y, Zhao Z, Li Z, Li W, Li Z, Guo R, Yuan Z, et al. Spatiotemporal Transmission Patterns and Determinants of Dengue Fever: A Case Study of Guangzhou, China. Int J Environ Res Public Health. 2019;16(14):2486.

Wu C, Wong PJY. Dengue transmission: mathematical model with discrete time delays and estimation of the reproduction number. J Biol Dyn 2019;13(1):1-25.

de Los Reyes VAA, Escaner JML. Dengue in the Philippines: model and analysis of parameters affecting transmission. J Biol Dyn 2018;12(1):894-912.

Saima A, Jin Z. Simulations and fractional modeling of dengue transmission in Bangladesh. Math Biosci Eng 2023;20(6):9891-922.

Romero-Leiton JP, Acharya KR, Parmley JE, Arino J, Nasri B. Modelling the transmission of dengue, zika and chikungunya: a scoping review protocol. BMJ Open. 2023;13(9):e074385.

Ninphanomchai S, Chansang C, Hii YL, Rocklöv J, Kittayapong P. Predictiveness of disease risk in a global outreach tourist setting in Thailand using meteorological data and vector-borne disease incidences. Int J Environ Res Public Health. 2014;11(10):10694-709.

กองโรคติดต่อนำโดยแมลง กรมควบคุมโรค กระทรวงสาธารณสุข. สถานการณ์โรคติดต่อนำโดยแมลง [อินเทอร์เน็ต]. 2566 [เข้าถึงเมื่อวันที่ 9 ตุลาคม 2566]. เข้าถึงได้จาก https://drive.google.com/drive/folders/1TTaSvaYYamVwA5Ig7ATZJmIcHBuGXOSb.

สุรชาติ โกยดุลย์. นวัตกรรมการเฝ้าระวังเชื้อไวรัสเด็งกี่ ไวรัสชิคุนกุนยา และไวรัสซิกา ในยุงลายบ้าน Aedes aegypti และ ยุงลายสวน Aedes albopictus. วารสารวิชาการสาธารณสุข 2565;31(6);1071-84.

Karl S, Halder N, Kelso JK, Ritchie SA, Milne GJ. A spatial simulation model for dengue virus infection in urban areas. BMC Infect Dis 2014;14:447.

Abdul-Ghani R, Mahdy MAK, Al-Eryani SMA, Fouque F, Lenhart AE, Alkwri A, et al. Impact of population displacement and forced movements on the transmission and outbreaks of Aedes-borne viral diseases: Dengue as a model. Acta Trop 2019;197:105066.

Liu K, Hou X, Wang Y, Sun J, Xiao J, Li R, et al. The driver of dengue fever incidence in two high-risk areas of China: A comparative study. Sci Rep 2019;9(1):19510.

Downloads

Published

31-07-2024

How to Cite

1.
Koyadun S. Development of Transmission Models of Dengue Hemorrhagic Fever in relation to Climate and Landscape Changes in Tourism and Urbanized Areas of Phuket Province. jodpc12sk [internet]. 2024 Jul. 31 [cited 2025 Jun. 7];2(1):30-49. available from: https://he04.tci-thaijo.org/index.php/jodpc12sk/article/view/1283

Issue

Section

Original article