https://doi.org/10.4081/gh.2022.1048

Clusters of malaria cases at sub-district level in endemic area in Java Island, Indonesia

Vol. 17 No. 1 (2022)
Submitted: 26 October 2021
Accepted: 24 April 2022
Published: 18 May 2022
Malaria, spatial, temporal, space-time, cluster, sub-district, Indonesia.
Abstract Views: 1083
PDF: 621
HTML: 113
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Authors

Dwi Sarwani Sri Rejeki
dwisarwanisr@yahoo.com
https://orcid.org/0000-0003-0180-4572
Department of Public Health, Faculty of Health Sciences, Universitas Jenderal Soedirman, Indonesia.
Sri Nurlaela
Department of Public Health, Faculty of Health Sciences, Universitas Jenderal Soedirman, Indonesia.
Devi Octaviana
Department of Public Health, Faculty of Health Sciences, Universitas Jenderal Soedirman, Indonesia.
Bangun Wijayanto
Department of informatics, Faculty of engineering, Universitas Jenderal Soedirman, Indonesia.
Solikhah Solikhah
https://orcid.org/0000-0001-6895-6840
Faculty of Public Health, Universitas Ahmad Dahlan, Yogyakarta, Indonesia.

Malaria remains one of the essential public health problems in Indonesia. The year 2015 was originally set as the elimination target in Java Island, but there are still several regencies on Java reporting malaria cases. Spatial technology helps determine local variations in malaria transmission, control risk areas and assess the outcome of interventions. Information on distribution patterns of malaria at the sub-district level, presented as spatial, temporal, and spatiotemporal data, is vital in planning control interventions. Information on malaria transmission at the sub-district level in three regencies in Java (Banyumas, Kebumen, and Purbalingga) was collected from the Agency for Regional Development (Bappeda), the Population and Civil Registration Agency (Disdukcapil) and Statistics Indonesia (BPS). Global spatial autocorrelation and space-time clustering was investigated together with purely spatial and purely temporal analyses using geographical information systems (GIS) by ArcGis 10.2 and SaTScan 8.0 to detect areas at high risk of malaria. Our results show that malaria was spatially clustered in the study area in central Java, in particular in the Banyumas and Purbalingga regencies. The temporal analysis revealed that malaria clusters predominantly appeared in the period January-April. The results of the spatiotemporal analysis showed that there was one most likely malaria cluster and three secondary clusters in southern central Java. The most likely cluster was located in Purbalingga Regency covering one sub-district and remaining from the beginning of 2016 to the end of 2018. The approach used can assist the setting of resource priorities to control and eliminate malaria.

Dimensions

Altmetric

PlumX Metrics

Downloads

Download data is not yet available.

Citations

Crossref
Scopus
Google Scholar
Europe PMC
Ahmad RA, Ferdiana A, Surendra H, Sy TR, Herbianto D, Rahayujati, TB, Rejeki, DSS, Murhandarwati EEH, 2021. A participatory approach to address within ‐ country cross ‐ border malaria: the case of Menoreh Hills in Java, Indonesia. Malar J 20:1-9.
Alemu K, Worku A, Berhane Y, 2013. Malaria infection has spatial, temporal, and spatiotemporal heterogeneity in unstable malaria transmission areas in northwest Ethiopia. PLoS One 8:1-10.
Alemu K, Worku A, Berhane Y, Kumie A, 2014. Spatiotemporal clusters of malaria cases at village level, northwest Ethiopia. Malar J 13:1-8.
Anselin L, 1995. Local indicators of spatial association-LISA. Wiley Online Library 27:93-115.
Barcus MJ, Laihad F, Sururi M, Sismadi P, Marwoto H, Bangs MJ, Baird JK, 2002. Epidemic malaria in the Menoreh Hills of Central Java. Am J Trop Med Hyg 66:287-92.
Barodji TB, Boesri H, Sudini, Sumardi, 2003. Bionomik vektor di Kokap di Kulonprogo. J Ekol Kes 2:209-16.
Bousema T, Griffin JT, Sauerwein RW, Smith DL, Churcher TS, Takken W, Ghani A, Drakeley C, & Gosling R, 2012. Hitting hotspots: Spatial targeting of malaria for control and elimination. PLoS Med 9:1-7.
Dhaniasri D, Rejeki DSS, Raharjo S, 2020. Analisis spasial kasus malaria di Kabupaten Banyumas Tahun 2009-2018. Balaba 16:169-79.
Dhimal M, Hara RBO, Karki R, Thakur GD, Kuch U, Ahrens B, 2014. Spatio-temporal distribution of malaria and its association with climatic factors and vector-control interventions in two high-risk districts of Nepal. Malar J 13:1-14.
Ernst KC, Adoka SO, Kowuor DO, Wilson ML, John CC, 2006. Malaria hotspot areas in a highland Kenya site are consistent in epidemic and non-epidemic years and are associated with ecological factors. Malar J 5:1-10.
Gebreslasie MT, 2015. A review of spatial technologies with applications for malaria transmission modelling and control in Africa. Geospat Health 10:239-47.
The Global Fund, 2013. Transitional funding mechanism (TFM) single country applicant sections 1–2. Available from: http://www.theglobalfund.org
Haque U, Sunahara T, Hashizume M, Shields T, Yamamoto T, Haque R, Glass GEE, 2011. Malaria prevalence, risk factors and spatial distribution in a hilly forest area of Bangladesh. PLoS One 6:1-9.
Hariastuti NI, 2011. Koleksi referensi nyamuk Anopheles di beberapa kabupaten dengan masalah malaria di Pulau Jawa. Balaba 7:1-6.
Health Office Kebumen, 2018. Annually Health Distric Report. Available from: https://kesehatanppkb.kebumen.go.id
Kohara Melchior LAK, Neto FC, 2016. Spatial and spatio-temporal analysis of malaria in the state of acre,western Amazon, Brazil. Geospat Health 11:233-9.
Kulldorff M, 2015. SaTScan User Guide. V9.4. 1-113.
Kulldorff M, 2018. Software for spatial and space-time scan statistics. Kulldorff and Harvard Medical School, Boston and Information Management Services Inc., SaTScan™v9.6. Available from: http://www.satscan.org/
Moonasar D, Maharaj R, Kunene S, Candrinho B, Saute F, Ntshalintshali N, Morris N, 2016. Towards malaria elimination in the MOSASWA (Mozambique, South Africa and Swaziland) region. Malar J 15:419.
Murhandarwati EEH, Fuad A, Sulistyawati, Wijayanti MA, Bia MB, Widartono BS, Kuswantoro, Lobo NF, Supargiyono, Hawley WA, 2015. Change of strategy is required for malaria elimination: a case study in Purworejo District, Central Java Province, Indonesia. Malar J 14:1-14.
Rejeki DSS, Fuad A, Widartono BS, Murhandarwati EEH, 2019. Spatiotemporal patterns of malaria at cross ‑ boundaries area in Menoreh Hills, Java, Indonesia. Malar J 18:1-12.
Rejeki DSS, Murhandarwati EEH, Kusnanto H, 2018. Analisis spasial malaria di Ekosistem Perbukitan Menoreh: studi kasus malaria Bulan September-Desember 2015. Kes Mas 12:120-32.
Rejeki DSS, Nurhayati N, Aji B, 2021. A spatiotemporal analysis of dengue hemorrhagic fever in Banyumas, Indonesia. Int J Public Health Sci 10:231-40.
Rejeki DSS, Nurhayati N, Aji B, Murhandarwati EEH, Kusnanto H, 2018. A time series analysis: Weather factors, human migration and malaria cases in endemic area of Purworejo, Indonesia, 2005-2014. Iran J Public Health 47:499-509.
Rejeki DSS, Wijayanti SPM, Octaviana D, Suratman S, 2019. The effect of climate and intervention methods on malaria incidence: a time series analysis. Ann Trop Med Public Health 22:1-7.
Roosihermiatie B, Pratiwi NL, Rukmini R, Widodo JP, 2016. Analysis of Implementation The Policy on Malaria Elimination in Indonesia. Buletin Penelitian Sistem Kesehatan 18:277-84.
Rosas-Aguirre A, Ponce OJ, Carrasco-Escobar G, Speybroeck N, Contreras-Mancilla J, Gamboa D, Pozo E, Herrera S, Llanos-Cuentas A, 2015. Plasmodium vivax malaria at households: spatial clustering and risk factors in a low endemicity urban area of the northwestern Peruvian coast. Malar J 14:1-11.
Setiyaningsih R, Widiarti A, 2014. Studi Bioekologi Vektor Malaria. Vektora 6:52-8.
Siti ZT, Sahariyani MHP, Rani M, 2020. Faktor Sikap dan Perilaku yang Berhubungan dengan Malaria di Wilayah Kerja Puskesmas Banjarmangu I Banjarnegara. J Prev Med Public Health14:51-7.
WHO, 2013. Word Malaria Report 2013. World Health Organisation, Geneva, Switzerland.
WHO 2022. WHO fact sheets on malaria. World Health Organisation, Geneva, Switzerland. Available from: https://www.who.int/news-room/fact-sheets/detail/malaria
Xia J, Cai S, Zhang H, Lin W, Fan Y, Qiu J, Sun L, Chang B, Zhang Z, Nie S, 2015. Spatial, temporal, and spatiotemporal analysis of malaria in Hubei Province, China from 2004-2011. Malar J 14:1-10.
Xu J, Liu H, 2012. Review the challenges of malaria elimination in Yunnan Province, People’s Republic of China. Southeast Asian J Trop Med Public Health 43:819-24.
Xu JW, Li JJ, Guo HP, Pu SW, Li SM, Wang RH, Liu H, 2017. Malaria from hyperendemicity to elimination in Hekou County on China - Vietnam border: an ecological study. Malar J 16:1-11.
Zhang W, WangL, FangL, Ma J, Xu Y, Jiang J, Hui F, Wang J, Liang S, Yang H, Cao W, 2008. Spatial analysis of malaria in Anhui province, China. Malar J 7:1-10.

How to Cite

Rejeki, D. S. S., Nurlaela, S. ., Octaviana, D. ., Wijayanto, B. ., & Solikhah, S. . (2022). Clusters of malaria cases at sub-district level in endemic area in Java Island, Indonesia. Geospatial Health, 17(1). https://doi.org/10.4081/gh.2022.1048
Copyright (c) 2022 the Author(s) Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

PAGEPress has chosen to apply the Creative Commons Attribution NonCommercial 4.0 International License (CC BY-NC 4.0) to all manuscripts to be published.


Similar Articles

You may also start an advanced similarity search for this article.