Incidence of malaria is clustered and buffers around plantations: a spatial analysis
Main Article Content
Malaria is re-emerging because of imported cases and the presence of potential vectors that can transmit and spread malaria. Malaria is a health problem in Banyumas District. Mapping the spread of infectious diseases is epidemiologically important. The purpose of this study was to determine the relationship between the variables and the epidemiology of malaria that were spatially modeled using the geographic information system (GIS).
This was a case-control study with ratio of 1:1. Cases were malaria-positive patients and controls were people without malaria, as diagnosed by microscopic examination. Minimum sample size was 139 per group and total sample size was 282 people. Chi-square was used to test the relationship between the variables, and GIS modeling to determine the spatial distribution of malaria cases.
There were significant relationships between level of income below minimum wage, not using mosquito nets, not using wire netting, not using insect repellents, habit of going out at night, history of malaria, cattle sheds not located between woods and residential area, history of going to endemic areas, residence at distances <1000 m from plantations, bushes, swamps and puddles, with incidence of confirmed malaria (p<0.001). The group of cases living <1000 meters from plantations numbered 141 (100%).
Malaria incidence is clustered and buffers around plantations at <1000 m. Malaria hot spots are displayed as risk maps that are useful for monitoring and spatial targeting of prevention and control measures against the disease.
The journal allows the authors to hold the copyright without restrictions and allow the authors to retain publishing rights without restrictions.
Elyazar IRF, Hay SI, Baird JK. Malaria distribution, prevalence, drug resistance and control in Indonesia. Adv Parasitol 2011;74: 41-175. doi: 10.1016/B978-0-12-385897-9.00002-1.
Fisher RP, Myers BA. Free and simple GIS as appropriate for health mapping in a low resource setting: a case study in eastern Indonesia. Int J Health Geogr 2011;10:15. doi: 10.1186/1476-072X-10-15.
Dinas Kesehatan Kota Banyumas. Laporan hasil kegiatan Program Pengendalian Penyakit Malaria Kabupaten Banyumas Tahun 2013. Purwokerto: Dinas Kesehatan Kota Banyumas; 2013.
Kazembe LN, Kleinschmidt I, Holtz TH, et al. Spatial analysis and mapping of malaria risk in Malawi using point-referenced prevalence of infection data. Int J Health Geogr 2006;5:41. doi: 10.1186/1476-072X-5-41.
Thanh PV, Hong NV, Van NV, et al. Epidemiology of forest malaria in Central Vietnam: the hidden parasite reservoir. Malar J 2015;14:86. doi: 10.1186/s12936-015-0601-y.
Thang ND, Erhart A, Speybroeck N, et al. Malaria in Central Vietnam: analysis of risk factors by multivariate analysis and classification tree models. Malar J 2008;7:28. doi: 10.1186/1475-2875-7-28.
Ompusunggu S, Tati S, Dewi RM. Faktor risiko malaria di Indonesia (analisis data Riskesdas 2007). Bul Penelit Kesehat 2009; Suppl 11-22.
Parmanto B, Paramita MV, Sugiantara W, et al. Spatial and multidimensional visualization of Indonesia’s village health statistics. Int J Health Geogr 2008;7:30. doi: 10.1186/1476-072X-7-30.
Zhang W, Wang L, Fang L, et al. Spatial analysis of malaria in Anhui Province, China. Malar J 2008;7:206. doi: 10.1186/1475-2875-7-206.
Tilaki-Haijan M. Sample size estimation in epidemiologic studies. Caspian J Intern Med 2011;2:289-98
Eryando T, Susanna D, Pratiwi D, et al. Standard deviational ellipse (SDE) models for malaria surveillance, case study: Sukabumi district-Indonesia, in 2012. Malar J 2012; 11 Suppl 1: 130. doi: 10.1186/1475-2875-11-S1-P130.
Erhart A, Ngo DT, Phan VK, et al. Epidemiology of forest malaria in central Vietnam: a large scale cross-sectional survey. Malar J 2005;4:58.
Ndoen E, Wild C, Dale P, et al. Relationships between Anopheline mosquitoes and topography in west Timor and Java, Indonesia. Malar J 2010; 9:242. doi: 10.1186/1475-2875-9-242.
Sinka ME, Bangs MJ, Manguin S, et al. The dominant Anopheles vectors of human malaria in the Asia-Pacific Region: occurrence data, distribution maps and bionomic précis. Parasit Vectors 2011;4:89.
Dale P, Sipe N, Anto S, et al. Malaria in Indonesia: a summary of recent into its environmental relationship. Southest Asian J Trop Med Public Health 2005;36:1-13.
Lozano DR, Rodriguez MH, Betnzos-Reyes AF, et al. Individual risk factors for Plasmodium vivax infection in the residual malaria transmission focus of Oaxaca, Mexico. Salud Publica de Mexico 2007;49:199-209.
Badan Penelitian dan Pengembangan Departemen Kesehatan RI. Laporan nasional riset kesehatan dasar tahun 2010. Jakarta: Badan Penelitian dan Pengembangan Departemen Kesehatan RI;2010.
Winskill P, Rowland M, Mtove G, et al. Malaria risk factors in north-east Tanzania. Malar J 2011; 10:98. doi: 10.1186/1475-2875-10-98.
Alemu A, Tsegaye W, Golassa L, et al. Urban malaria and associated risk factors in Jimma town, south-west Ethiopia. Malar J 2011;10:173.
Kuswanto. Analisis faktor-faktor risiko kejadian malaria di kecamatan Kemranjen Kabupaten Banyumas [tesis]. Semarang: Program Pascasarjana Universitas Diponegoro;2005.
Mushinzimana E, Munga S, Minakawa N, et al. Landscape determinants and remote sensing of Anopheline mosquito larval habitats in the western Kenya highlands. Malar J 2006;5:13.
Kazwaini M, Martini S. Tempat perindukan vektor, spesies nyamuk Anopheles, dan pengaruh jarak tempat perindukan vektor nyamuk Anopheles terhadap kejadian malaria pada balita. J Kesehatan Lingkungan 2006;2:173-82.