Spatial analysis of dengue incidence and linear effects with climate conditions in Bandung City Indonesia in 2021-2023 10.55131/jphd/2025/230119
Article Sidebar
Main Article Content
Abstract
The dengue problem is getting more serious in Indonesia, there has been a threefold increase in dengue cases compared to the previous year. Bandung City is one of the areas contributing the most cases in 2024 (1,741 cases). As climate change progresses, rising temperatures are expected to exacerbate dengue incidence in Indonesia. This study aims to spatially analyze the impact of population density, altitude, and climatic conditions on dengue incidence in Bandung City. An ecological study was conducted using secondary data from all sub-districts in Bandung City from January 2021 to December 2023. Data on dengue cases, population density, altitude, and climatic conditions were analyzed using spatial analysis, correlation, and multiple linear regression. The highest dengue incidence was recorded in the Bojongloa Kaler sub-district, with 203, 337, and 116 cases in 2021, 2022, and 2023, respectively. Bojongloa Kaler also had the highest population density (402 people/ha) and is located at an altitude of ≥720 m above sea level. Correlation analysis revealed significant associations between dengue incidence and population density (R² = 0.221), minimum temperature (R² = 0.08), and maximum temperature (R² = 0.07). Climatic conditions significantly affected dengue incidence (p=0.017), explaining 30.7% of the variance. Climatic conditions, along with population density, play a crucial role in dengue transmission. Effective intervention strategies should prioritize areas with high case numbers and involve coordinated cross-sectoral efforts to address climate-related transmission risks.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
References
Ye J, Moreno-Madriñán MJ. Comparing different spatio-temporal modeling methods in dengue fever data analysis in Colombia during 2012–2015. Spat Spatiotemporal Epidemiol. 2020;34(August 2020):100360. doi: 10.1016/j.sste.2020.100360
WHO. Disease Outbreak News Dengue - Global situation [Internet]. WHO. 2024 [Cited 2024 Aug 27]. Available from: https://www.who.int/ emergencies/disease-outbreak-news/item/2024-DON518
WHO. Indonesia takes decisive, pioneering action to strengthen multisource collaborative surveillance for dengue [Internet]. WHO. 2024 [Cited 2024 Aug 27]. Available from: https://www.who.int/indonesia/news/detail/30-07-2024-indonesia-takes-decisive--pioneering-action-to-strengthen-multisource-collaborative-surveillance-for-dengue
Ministry of Health of the Republic of Indonesia. When Dengue Fever Comes Back [Internet]. Ministry of Health of the Republic of Indonesia. 2024 [Cited 2024 Aug 27]. Available from: https://sehatnegeriku.kemkes.go.id/baca/blog/20240605/0545670/ketika-demam-berdarah-kembali-merebak/
Ishak H, Aisyah AS, Mallongi A, Astuti RDP. Risk factors and fogging effectiveness of dengue hemorrhagic fever incidence in the Pontap Public Health Center area in Palopo City, Indonesia. Enferm Clin. 2020; 30(4):294–7. doi: 10.1016/j.enfcli. 2019.10.087
Kolimenakis A, Heinz S, Wilson ML, Winkler V, Yakob L, Michaelakis A, et al. The role of urbanisation in the spread of Aedes mosquitoes and the diseases they transmit—A systematic review. PLoS Negl Trop Dis. 2021; 15(9):e0009631. doi:10.1371/ journal.pntd.0009631
Sutriyawan A, Martini M, Sutiningsih D, Adi MS. Climatic variations and the incidence of dengue fever in Bandung, Indonesia. J Public Hlth Dev. 2023;21(3):222–31. doi: 10.55131/ jphd/2023/210317
Watts MJ, Kotsila P, Mortyn PG, Sarto I Monteys V, Urzi Brancati C. Influence of socio-economic, demographic and climate factors on the regional distribution of dengue in the United States and Mexico. Int J Health Geogr. 2020;19(44):1–15. doi: 10.1186/s12942-020-00241-1
Amelinda YS, Wulandari RA, Asyary A. The effects of climate factors, population density, and vector density on the incidence of dengue hemorrhagic fever in South Jakarta Administrative City 2016-2020: an ecological study. Acta Biomed. 2022;93(6):e2022323. doi: 10.23750/ abm.v93i6.13503
Sutriyawan A, Herdianti H, Cakranegara PA, Lolan YP, Sinaga Y. Predictive Index Using Receiver Operating Characteristic and Trend Analysis of Dengue Hemorrhagic Fever Incidence. Open Access Maced J Med Sci. 2022;10(E):681–7. doi: 10.3889/oamjms.2022.8975
Sutriyawan A, Manap A, Sulami N, Setiyadi A, Riskiah DM, Kurniawati RD, et al. Analysis of entomological indicators and distribution of Aedes aegypti larvae in dengue endemic areas. JMEI. 2023;100(4):314–20. doi: 10.36233/0372-9311-406
Kurniadi A, Sutikno S. Spatial Analysis of Dengue Fever Case Distribution and Susceptibility Mapping in Lumajang District with Spatial Pattern Analysis and Flexibly Shaped Spatial Scan Statistic. Jurnal Sains dan Seni ITS. 2018;7(2):32–9. doi: 10.12962/j23373520.v7i2.36634
Moutinho S, Rocha J, Gomes A, Gomes B, Ribeiro AI. Spatial Analysis of Mosquito-Borne Diseases in Europe: A Scoping Review. Sustainability. 2022;14(15):8975. doi: 10.3390/su14158975
Wangdi K, Clements ACA, Du T, Nery SV. Spatial and temporal patterns of dengue infections in Timor-Leste, 2005–2013. Parasit Vectors. 2018; 11(9):1–9. doi: 10.1186/s13071-017-2588-4
Reinhold JM, Lazzari CR, Lahondère C. Effects of the environmental temperature on Aedes aegypti and Aedes albopictus mosquitoes: a review. Insects. 2018;9(4):158. doi: 10.3390/insects9040158
Meza-Ballesta A, Gónima L. The influence of climate and vegetation cover on the occurrence of dengue cases (2001-2010). Revista de Salud Pública. 2014;16(2):293–306.
Liu C, Liu Q, Lin H, Xin B, Nie J. Spatial analysis of dengue fever in Guangdong Province, China, 2001-2006. Asia Pacific J Public Health. 2014;26(1):58–66. doi: 10.1177/ 1010539512472356
Beard R, Wentz E, Scotch M. A systematic review of spatial decision support systems in public health informatics supporting the identification of high risk areas for zoonotic disease outbreaks. Int J Health Geogr. 2018;17(1):1–19. doi: 10.1186/s12942-018-0157-5
Desjardins MR, Whiteman A, Casas I, Delmelle E. Space-time clusters and co-occurrence of chikungunya and dengue fever in Colombia from 2015 to 2016. Acta Trop. 2018;185(September 2018):77–85. doi: 10.1016/ j.actatropica.2018.04.023
Schultes OL, Morais MHF, Cunha MdCM, Sobral A, Caiaffa WT. Spatial analysis of dengue incidence and Aedes aegypti ovitrap surveillance in Belo Horizonte, Brazil. Trop Med Int Health. 2021;26(2):237–55. doi: 10.1111/tmi.13521
Marceló-Díaz C, Lesmes MC, Santamaría E, Salamanca JA, Fuya P, Cadena H, et al. Spatial Analysis of Dengue Clusters at Department, Municipality and Local Scales in the Southwest of Colombia, 2014–2019. Trop Med Infect Dis. 2023;8(5):262. doi: 10.3390/tropicalmed8050262
Masrani AS, Nik Husain NR, Musa KI, Yasin AS. Trends and Spatial Pattern Analysis of Dengue Cases in Northeast Malaysia. J Prev Med Public Health. 2022;55(1):80-87. doi: 10.3961/ jpmph.21.461
Kusuma AP, Sukendra DM. Spatial analysis of dengue hemorrhagic fever incidence based on population density. UJPH. 2016;5(1):48–56. doi: 10.15294/ujph.v5i1.9703
Faridah L, Mindra IGN, Putra RE, Fauziah N, Agustian D, Natalia YA, et al. Spatial and temporal analysis of hospitalized dengue patients in Bandung: demographics and risk. Trop Med Health. 2021;49(1):44. doi: 10.1186/s41182-021-00329-9
Messina JP, Brady OJ, Golding N, Kraemer MUG, Wint GRW, Ray SE, et al. The current and future global distribution and population at risk of dengue. Nature Microbio. 2019;4(9): 1508–15. doi: 10.1038/s41564-019-0476-8
Khalid B, Bueh C, Ghaffar A. Assessing the factors of dengue transmission in urban environments of Pakistan. Atmosphere (Basel). 2021; 12(6):773. doi: 10.3390/atmos 12060773
Sarker R, Roknuzzaman ASM, Haque MA, Islam MR, Kabir ER. Upsurge of dengue outbreaks in several WHO regions: Public awareness, vector control activities, and international collaborations are key to prevent spread. Health Sci Rep. 2024;7(4): e2034. doi: 10.1002/hsr2.2034
Subedi D, Taylor-Robinson AW. Epidemiology of dengue in Nepal: History of incidence, current prevalence and strategies for future control. J Vector Borne Dis. 2016; 53(1):1–7. Available from: https:// pubmed.ncbi.nlm.nih.gov/27004572/
Istiqamah SNA, Arsin AA, Salmah AU, Mallongi A. Correlation study between elevation, population density, and dengue hemorrhagic fever in Kendari city in 2014–2018. Open Access Maced J Med Sci. 2020;8(T2):63–6. doi: 10.3889/oamjms.2020.5187
Goto K, Kumarendran B, Mettananda S, Gunasekara D, Fujii Y, Kaneko S. Analysis of effects of meteorological factors on dengue incidence in Sri Lanka using time series data. PLoS One. 2013;8(5):e63717. doi: 10.1371/ journal.pone.0063717
Wu X, Lang L, Ma W, Song T, Kang M, He J, et al. Non-linear effects of mean temperature and relative humidity on dengue incidence in Guangzhou, China. Sci Total Environ. 2018;628–629:766–71. doi: 10.1016/ j.scitotenv.2018.02.136
Xiang J, Hansen A, Liu Q, Liu X, Tong MX, Sun Y, et al. Association between dengue fever incidence and meteorological factors in Guangzhou, China, 2005–2014. Environ Res. 2017; 153:17–26. doi: 10.1016/j.envres. 2016.11.009
Choi Y, Tang CS, McIver L, Hashizume M, Chan V, Abeyasinghe RR, et al. Effects of weather factors on dengue fever incidence and implications for interventions in Cambodia. BMC Public Health. 2016;16(1):1–7. doi: 10.1186/s12889-016-2923-2
Lana RM, Morais MM, Lima TFM, Carneiro TGS, Stolerman LM, Dos Santos JPC, et al. Assessment of a trap based Aedes aegypti surveillance program using mathematical modeling. PLoS One. 2018; 13(1):e0190673. doi: 10.1371/journal. pone.0190673
Peña-García VH, Triana-Chávez O, Arboleda-Sánchez S. Estimating effects of temperature on dengue transmission in colombian cities. Ann Glob Health. 2017;83(3–4):509–18. doi: 10.1016/j.aogh.2017.10.011
Mordecai EA, Cohen JM, Evans MV, Gudapati P, Johnson LR, Lippi CA, et al. Detecting the impact of temperature on transmission of Zika, dengue, and chikungunya using mechanistic models. PLoS Negl Trop Dis. 2017;11(4):e0005568. doi: 10.1371/ journal.pntd.0005568
Xu L, Stige LC, Chan KS, Zhou J, Yang J, Sang S, et al. Climate variation drives dengue dynamics. Proc Natl Acad Sci U S A. 2017;114(1):113–8. doi: 10.1073/pnas.1618558114
Silva FD, dos Santos AM, Corrêa Rda G, Caldas Ade J. T. Temporal relationship between rainfall, temperature and occurrence of dengue cases in São Luís, Maranhão, Brazil. Cien Saude Colet. 2016;21(2):641–6. doi: 10.1590/1413-81232015212.0959 2015
Stolerman LM, Maia PD, Kutz JN. Forecasting dengue fever in Brazil: An assessment of climate conditions. PLoS One. 2019;14(8):e0220106. doi: 10.1371/journal.pone.0220106
Simo Tchetgna H, Sado Yousseu F, Kamgang B, Tedjou A, McCall PJ, Wondji CS. Concurrent circulation of dengue serotype 1, 2 and 3 among acute febrile patients in Cameroon. PLoS Negl Trop Dis. 2021; 15(10):e0009860. doi: 10.1371/ journal.pntd.0009860
Jahan Y, Rahman A. Management of dengue hemorrhagic fever in a secondary level hospital in Bangladesh: A case report. IDCases. 2020;21:e00880. doi: 10.1016/j.idcr. 2020.e00880
Chen Y, Yang Z, Jing Q, Huang J, Guo C, Yang K, et al. Effects of natural and socioeconomic factors on dengue transmission in two cities of China from 2006 to 2017. Sci Total Environ. 2020;724(July 2020):138200. doi: 10.1016/j.scitotenv.2020.138200
Valdez L, Sibona, GJ, Condat C. A. Impact of rainfall on Aedes aegypti populations. Ecol Modell. 2018; 385(October 2018):96–105. doi: 10.1016/j.ecolmodel.2018.07.003
Sanna M, Hsieh YH. Ascertaining the impact of public rapid transit system on spread of dengue in urban settings. Sci Total Environ. 2017;598(15 November 2017):1151–9. doi: 10.1016/ j.scitotenv.2017.04.050
Tang B, Xiao Y, Tang S, Wu J. Modelling weekly vector control against dengue in the Guangdong Province of China. J Theor Biol. 2016;410(December 2016):65–76. doi: 10.1016/j.jtbi.2016.09.012