Determinants of malaria from environmental and poverty aspects in Indonesia: A spatiotemporal perspective, 2016-2020

Afi Nursafingi , Prima Widayani , Sidiq Purwoko , Andy Bhermana

Asian Pacific Journal of Tropical Medicine ›› 2024, Vol. 17 ›› Issue (6) : 256 -267.

PDF (3026KB)
Asian Pacific Journal of Tropical Medicine ›› 2024, Vol. 17 ›› Issue (6) :256 -267. DOI: 10.4103/apjtm.apjtm_743_23
Original Article
research-article
Determinants of malaria from environmental and poverty aspects in Indonesia: A spatiotemporal perspective, 2016-2020
Author information +
History +
PDF (3026KB)

Abstract

Objective: To investigate the environmental and social aspects of poverty contributing to malaria incidence in Indonesia from 2016 to 2020.

Methods: Random forest regression was used to analyse the independent variables contributing to malaria incidence. Environmental conditions were extracted from remotely sensed data, including vegetation, land temperature, soil moisture, precipitation, and elevation. In contrast, the social aspects of poverty were obtained from government statistical reports.

Results: From 2016 to 2020, the contribution of each environmental and social aspect of poverty to malaria incidence fluctuated annually. Generally, the top three essential variables were people aged 15 years and above, experiencing poverty (variable importance/VI=32.0%), people experiencing poverty who work in the agricultural sector (VI=14.4%), and precipitation (VI=9.8%). It was followed by people experiencing poverty who are unemployed (VI=9.2%), land temperature (VI=5.2%), people experiencing poverty who have low education (VI=8.0%), soil moisture (VI=7.4%), elevation (VI=6.0%), and vegetation (VI=3.8%).

Conclusions: Poverty and variables related to climate have become the crucial determinants of malaria in Indonesia. The government must strengthen malaria surveillance through climate change mitigation and adaptation programs and accelerate poverty alleviation programs to support malaria elimination.

Keywords

Malaria / Poverty / Climate / Random forest / Indonesia

Cite this article

Download citation ▾
Afi Nursafingi, Prima Widayani, Sidiq Purwoko, Andy Bhermana. Determinants of malaria from environmental and poverty aspects in Indonesia: A spatiotemporal perspective, 2016-2020. Asian Pacific Journal of Tropical Medicine, 2024, 17 (6) : 256-267 DOI:10.4103/apjtm.apjtm_743_23

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

WHO . World, malaria report 2022. Geneva: 2022. [Online]. Available from: https://www.who.int/teams/global-malaria-programme/reports/world-malaria-report-2022. [Accessed on 29 July 2022].

[2]

Kementerian Kesehatan. Profil Kesehatan Indonesia Tahun 2021. Jakarta: Kementerian Kesehatan Republik Indonesia; 2022.

[3]

Sitohang V, Sariwati E, Fajariyani SB, Hwang D, Kurnia B, Hapsari RK, et al. Malaria elimination in Indonesia: Halfway there. Lancet Glob Health 2018; 6: e604-e606. doi: https://doi.org/10.1016/S2214-109X(18)30198-0.

[4]

Ministry of Health. Indonesia health profile 2015. Jakarta: Ministry of Health of the Republic of Indonesia; 2016. [Online]. Available from: https://ghdx.healthdata.org/record/indonesia-health-profile-2015. [Accessed on 29 July 2022].

[5]

WHO . Malaria: Fact sheet on sustainable development goals (SDGs): Health targets 2017. [Online]. Available from: https://apps.who.int/iris/handle/10665/340834. [Accessed on 29 July 2022].

[6]

Mafwele BJ, Lee JW. Relationships between transmission of malaria in Africa and climate factors. Sci Rep 2022; 12: 1-8.

[7]

Hasyim H, Dale P, Groneberg DA, Kuch U, Müller R. Social determinants of malaria in an endemic area of Indonesia. Malar J 2019; 18: 1-11.

[8]

Ipa M, Laksono AD, Astuti EP, Prasetyowati H, Hakim L. Predictors of malaria incidence in rural eastern Indonesia. Indian J Foren Med Toxicol 2020; 14: 3l05-3lll.

[9]

Rejeki DSS, Nurhayati N, Aji B, Murhandarwati EEH, Kusnanto H. A time series analysis: Weather factors, human migration and malaria cases in endemic area of Purworejo, Indonesia, 2005-2014. Iran J Public Health 2018; 47: 499-509.

[10]

Hasyim H, Nursafingi A, Haque U, Montag D, Groneberg DA, Dhimal M, et al. Spatial modelling of malaria cases associated with environmental factors in South Sumatra, Indonesia. Malar J 2018; 17: 1-15. doi: https://doi.org/10.1186/S12936-018-2230-8/TABLES/4.

[11]

Ministry of Health. Indonesia Health Profile 2020. Jakarta: Ministry of Health of the Republic of Indonesia; 2021. [Online]. Available from: https://ghdx.healthdata.org/series/indonesia-health-profile. [Accessed on 29 July 2022].

[12]

Bhutta ZA, Sommerfeld J, Lassi ZS, Salam RA, Das JK. Global burden, distribution, and interventions for infectious diseases of poverty. Infect Dis Poverty 2014; 3: 1-7. doi: https://doi.org/10.1186/2049-9957-3-21/TABLES/1.

[13]

Ge Y, Song Y, Wang J, Liu W, Ren Z, Peng J, et al. Geographically weighted regression-based determinants of malaria incidences in northern China. Transac GIS 2017; 21: 934-953. doi: https://doi.org/10.1111/TGIS.12259.

[14]

Ouédraogo M, Samadoulougou S, Rouamba T, Hien H, Sawadogo JEM, Tinto H, et al. Spatial distribution and determinants of asymptomatic malaria risk among children under 5 years in 24 districts in Burkina Faso. Malar J 2018; 17: 1-12. doi: https://doi.org/10.1186/S12936-018-2606-9/FIGURES/3.

[15]

Gopal S, Ma Y, Xin C, Pitts J, Were L. Characterizing the spatial determinants and prevention of malaria in Kenya. Int J Environ Res Public Health 2019; 16: 5078. doi: https://doi.org/10.3390/IJERPH16245078.

[16]

BPS-Statistics Indonesia. Statistical yearbook of Indonesia 2023. [Online]. Available from: https://ghdx.healthdata.org/series/indonesia-health-profile. [Accessed on 29 July 2022].

[17]

Taylor T, Agbenyega T. Malaria. Hunter's tropical medicine and emerging infectious disease. Ninth edition. Amsterdam: Elsevier; 2012.

[18]

Hasyim H, Nursafingi A, Haque U, Montag D, Groneberg DA, Dhimal M, et al. Spatial modelling of malaria cases associated with environmental factors in South Sumatra, Indonesia. Malar J 2018; doi: https://doi.org/10.1186/s12936-018-2230-8.

[19]

Wang Z, Liu Y, Li Y, Wang G, Lourenço J, Kraemer M, et al. The relationship between rising temperatures and malaria incidence in Hainan, China, from 1984 to 2010: A longitudinal cohort study. Lancet Planet Health 2022; 6: e350-e358. doi: https://doi.org/10.1016/S2542-5196(22)00039-0.

[20]

Mousam A, Maggioni V, Delamater PL, Quispe AM. Using remote sensing and modeling techniques to investigate the annual parasite incidence of malaria in Loreto, Peru. Adv Water Resour 2017; 108: 423-438. doi: https://doi.org/10.1016/J.ADVWATRES.20l6.11.009.

[21]

Hendri J, Astuti EP, Prasetyowati H, Dhewantara PW, Hadi UK. Anopheline diversity in Indonesia: An evaluation of animal-baited sampling techniques. J Med Entomol 2022; 59: 710-718. doi: https://doi.org/10.1093/JME/TJAB198.

[22]

Didan K. MODIS/Terra vegetation indices 16-day L3 global 250 m SIN grid V061. [Online]. Available from: https://doi.org/10.5067/MODIS/MOD13Q1.061. [Accessed on 20 November 2022].

[23]

Wan Z, Hook S, Hulley G. MODIS/Terra land surface temperature/emissivity 8-day L3 global 1 km SIN grid V061. [Online]. Available from: https://doi.org/10.5067/MODIS/MOD11A2.061. [Accessed on 20 November 2022].

[24]

NASA-USDA . NASA-USDA global soil moisture data. The hydrological science laboratory at NASA’s goddard space flight center and USDA foreign agricultural services 2022. [Online]. Available from: https://earth.gsfc.nasa.gov/hydro/data/nasa-usda-global-soil-moisture-data. [Accessed on 20 November 2022].

[25]

Huffman GJ, Bolvin DT, Braithwaite D, Hsu K, Joyce R, Kidd C, et al. GPM IMERG Final Precipitation L3 1 month 0.1 degree x 0.1 degree V06. Goddard Earth Sciences Data and Information Services Center (GES disc) 2019. doi:https://doi.org/10.1175/JHM-D-11-022.1.

[26]

CGIAR-CSI . SRTM 90m DEM Digital Elevation Database. CGIAR-Consortium for Spatial Information 2018. [Online]. Available from: https://srtm.csi.egiar.org/. [Accessed on 2l November 2022].

[27]

ESRI . Cell size and resampling in analysis-ArcMap | Documentation 2023. [Online]. Available from: https://desktop.arcgis.com/en/arcmap/latest/extensions/spatial-analyst/performing-analysis/cell-size-and-resampling-in-analysis.htm. [Accessed on 14 July 2023].

[28]

Breiman L. Random forests. Mach Learn 2001; 45: 5-32.

[29]

Biau G, Scornet E. A random forest guided tour. Test 2016; 25: 197-227.

[30]

Oshiro TM, Perez PS, Baranauskas JA. How many trees in a random forest? Lecture Notes Computer Sci 2012; 7376: 154-168. doi: https://doi.org/10.1007/978-3-642-3l537-4_13/COVER.

[31]

ESRI . Forest-based classification and regression 2023. [Online]. Available from: https://pro.arcgis.com/en/pro-app/latest/tool-reference/spatial-statistics/forestbasedclassificationregression.htm. [Accessed on 3 February 2023].

[32]

García-Carretero R, Holgado-Cuadrado R, Barquero-Pérez Ó, Jané R, Aramendi E, Poza J. Assessment of classification models and relevant features on nonalcoholic steatohepatitis using random forest. Entropy 2021; 23: 763. doi: https://doi.org/10.3390/E23060763.

[33]

ESRI . ArcGIS Pro 2023. [Online]. Available from: https://www.esri.com/en-us/arcgis/products/arcgis-pro/overview. [Accessed on 3 February 2023].

[34]

JASP Team. JASP Version 0.17.1.0. 2023. [Online]. Available from: https://jasp-stats.org/. [Accessed on 28 July 2023].

[35]

QGIS. org. Welcome to the QGIS project! 2023. [Online]. Available from: https://qgis.org/en/site/. [Accessed on 19 December 2023].

[36]

De Castro MC, Fisher MG. Is malaria illness among young children a cause or a consequence of low socioeconomic status? Evidence from the united Republic of Tanzania. Malar J 2012; 11: 1-12. doi: https://doi.org/10.1186/l475-2875-11-161/TABLES/5.

[37]

Sonko ST, Jaiteh M, Jafali J, Jarju LBS, D’Alessandro U, Camara A, et al. Does socio-economic status explain the differentials in malaria parasite prevalence? Evidence from the Gambia. Malar J 2014; 13: l-l2. doi: https://doi.org/10.1186/1475-2875-13-449/TABLES/8.

[38]

Y, Tong S. Poverty and malaria in the Yunnan province, China. Infect Dis Poverty 2014; 3: 1-4. doi: https://doi.org/10.1186/2049-9957-3-32/FIGURES/2.

[39]

Hanandita W, Tampubolon G. Geography and social distribution of malaria in Indonesian Papua: A cross-sectional study. Int J Health Geograph 2016; 15: 1-15. doi: https://doi.org/10.1186/Sl2942-016-0043-Y.

[40]

Ngatu NR, Kanbara S, Renzaho A, Wumba R, Mbelambela EP, Muchanga SMJ, et al. Environmental and sociodemographic factors associated with household malaria burden in the Congo. Malar J 2019; 18: 1-9. doi: https://doi.org/10.1186/S12936-019-2679-0/TABLES/2.

[41]

Ramdzan AR, Ismail A, Mohd Zanib ZS. Prevalence of malaria and its risk factors in Sabah, Malaysia. Int J Infect Dis 2020; 91: 68-72. doi: https://doi.org/10.1016/JJJID.20l9.11.026.

[42]

Mohan I, Kodali NK, Chellappan S, Karuppusamy B, Behera SK, Natarajan G, et al. Socio-economic and household determinants of malaria in adults aged 45 and above: Analysis of longitudinal ageing survey in India, 2017-2018. Malar J 2021; 20: 1-9. doi: https://doi.org/10.1186/S12936-021-03840-W/TABLES/3.

[43]

Degarege A, Fennie K, Degarege D, Chennupati S, Madhivanan P. Improving socioeconomic status may reduce the burden of malaria in sub Saharan Africa: A systematic review and meta-analysis. PLoS One 2019; 14: e0211205. doi: https://doi.org/10.1371/JOURNAL.PONE.0211205.

[44]

Sallum MAM, Conn JE, Bergo ES, Laporta GZ, Chaves LSM, Bickersmith SA, et al. Vector competence, vectorial capacity of Nyssorhynchus darlingi and the basic reproduction number of Plasmodium vivax in agricultural settlements in the Amazonian Region of Brazil. Malar J 2019; 18: 1-15. doi: https://doi.org/10.1186/S12936-019-2753-7/FIGURES/7.

[45]

Ivan E, Crowther NJ, Mutimura E, Osuwat LO, Janssen S, Grobusch MP. Helminthic infections rates and malaria in HIV-infected pregnant women on anti-retroviral therapy in Rwanda. PLoS Negl Trop Dis 2013; 7: e2380. doi: https://doi.org/10.1371/JOURNAL.PNTD.0002380.

[46]

Oladimeji KE, Tsoka-Gwegweni JM, Ojewole E, Yunga ST. Knowledge of malaria prevention among pregnant women and non-pregnant mothers of children aged under 5 years in Ibadan, South West Nigeria. Malar J 2019; 18: 1-12. doi: https://doi.org/10.1186/S12936-0l9-2706-1/TABLES/5.

[47]

Hasyim H, Nursafingi A, Haque U, Montag D, Groneberg DA, Dhimal M, et al. Spatial modelling of malaria cases associated with environmental factors in South Sumatra, Indonesia. Malar J 2018; 17: 1-15. doi: https://doi.org/10.1186/S12936-0l8-2230-8/TABLES/4.

[48]

Rejeki DSS, Nurhayati N, Aji B, Murhandarwati EEH, Kusnanto H. A time series analysis: Weather factors, human migration and malaria cases in endemic area of Purworejo, Indonesia, 2005-2014. Iran J Public Health 2018; 47: 499.

[49]

Guo C, Yang L, Ou CQ, Li L, Zhuang Y, Yang J, et al. Malaria incidence from 2005-2013 and its associations with meteorological factors in Guangdong, China. Malar J 2015; 14: 1-12. doi: https://doi.org/10.1186/S12936-015-0630-6/FIGURES/7.

[50]

Roy S Sen. Spatial patterns of malaria case burden and seasonal precipitation in India during 1995-2013. Int J Biometeorol 2023; 67: 157-164. doi: https://doi.org/10.1007/S00484-022-02395-Y/FIGURES/4.

[51]

Gunda R, Chimbari MJ, Shamu S, Sartorius B, Mukaratirwa S. Malaria incidence trends and their association with climatic variables in rural Gwanda, Zimbabwe, 2005-2015. Malar J 2017; 16: 1-13. doi: https://doi.org/10.H86/S12936-017-2036-0/FIGURES/7.

[52]

Chuang TW, Soble A, Ntshalintshali N, Mkhonta N, Seyama E, Mthethwa S, et al. Assessment of climate-driven variations in malaria incidence in Swaziland: Toward malaria elimination. Malar J 2017; 16: MO. doi: https://doi.org/10.1186/S12936-O17-1874-O/FIGURES/4.

[53]

Ikeda T, Behera SK, Morioka Y, Minakawa N, Hashizume M, Tsuzuki A, et al. Seasonally lagged effects of climatic factors on malaria incidence in South Africa. Sci Rep 2017; 7: 1-9. doi: https://doi.org/10.1038/s41598-017-02680-6.

[54]

Rejeki DSS, Solikhah S, Wijayanti SPM. Risk factors analysis of malaria transmission at cross-boundaries area in Menoreh Hills, Java, Indonesia. Iran J Public Health 2021; 50: 1816. doi: https://doi.org/10.18502/IJPH.V5019.7054.

[55]

Dabaro D, Birhanu Z, Negash A, Hawaria D, Yewhalaw D. Effects of rainfall, temperature and topography on malaria incidence in elimination targeted district of Ethiopia. Malar J 2021; 20: 1-10. doi: https://doi.org/10.1186/S12936-021-03641-1/TABLES/5.

[56]

Reid HL, Haque U, Roy S, Islam N, Clements ACA. Characterizing the spatial and temporal variation of malaria incidence in Bangladesh, 2007. Malar J 2012; 11: 1-8. doi: https://doi.org/10.1186/1475-2875-11-l70/TABLES/3.

[57]

Siraj AS, Santos-Vega M, Bouma MJ, Yadeta D, Ruiz Carrascal D, Pascual M. Altitudinal changes in malaria incidence in highlands of Ethiopia and Colombia. Science 2014; 343: 1154-1158. doi: https://doi. org/10.1126/SCIENCE.1244325/SUPPL_FILE/SIRAJ.SM.PDF.

[58]

Himeidan YE, Kweka EJ. Malaria in East African highlands during the past 30 years: Impact of environmental changes. Front Physiol 2012; 3: 315. doi: https://doi.org/10.3389/FPHYS.2012.00315/BIBTEX.

[59]

Lee E, Burkhart J, Olson S, Billings AA, Patz JA, Harner EJ. Relationships of climate and irrigation factors with malaria parasite incidences in two climatically dissimilar regions in India. J Arid Environ 2016; 124: 214-224. doi: https://doi.org/10.1016/J.JARIDENV.2015.08.010.

[60]

Yang T, Ala M, Zhang Y, Wu J, Wang A, Guan D. Characteristics of soil moisture under different vegetation coverage in Horqin Sandy Land, northern China. PLoS One 2018; 13: e0198805. doi: https://doi.org/10.1371/JOURNAL.PONE.0198805.

[61]

Kar NP, Kumar A, Singh OP, Carlton JM, Nanda N. A review of malaria transmission dynamics in forest ecosystems. Parasit Vectors 2014; 7: 1-12. doi: https://doi.org/10.1186/1756-3305-7-265.

[62]

Zhou XN. China declared malaria-free: A milestone in the world malaria eradication and Chinese public health. Infect Dis Poverty 2021; 10: 1-2. doi: https://doi.org/10.1186/S40249-021-00882-9/METRICS.

PDF (3026KB)

4

Accesses

0

Citation

Detail

Sections
Recommended

/