Analysis of Malaria Incidence in Banyumas Using Spacial-Temporal Approach

Supriyanto Supriyanto(1), Nunung Nurhayati(2), Dwi Sarwani Sri Rejeki(3),

DOI: https://doi.org/10.15294/kemas.v13i1.7602


(1) Jurusan Matematika FMIPA Universitas jenderal Soedirman
(2) Universitas Jenderal Soedirman Purwokerto
(3) Universitas Jenderal Soedirman Purwokerto

Abstract

Malaria still becomes a public health problem in Indonesia although has declined the last decades. The incidences of malaria in Banyumas shows unstable transmission and still risk of epidemic . Thus, the spatial and temporal distribution is required as part of efforts towards the elimination of malaria in Banyumas. Temporal spatial statistical methods is used to identify a group of malaria incidence at the district level. Purely spatial clusters of malaria incidence from 2004 to 2015 shows that the disease is not distributed randomly in the study area. A total of nine districts of high risk is determined by analysis of Moran’s I. The analysis showed that by the Moran’s I test, there is spatial autocorrelation found in the percentage malaria incidence from 2004 to 2015 in Banyumas. The use of the model can provide a means to detect the spatial distribution, temporal, and spatiotemporal malaria, as well as to identify areas of high risk of malaria. This research may help in prioritizing resources on high-risk areas for malaria control in the future and towards the elimination of malaria in Banyumas.

Keywords

spatial, temporal, malaria, Moran’s I, Banyumas

Full Text:

PDF

References

Alemu, K., Worku, A., Berhane, Y., & Kumie, A. (2014). Spatiotemporal Clusters of Malaria Cases at Village Level, Northwest Ethiopia. Malaria Journal, 13(1), 223. http://doi.org/10.1186/1475-2875-13-223

Badan penelitian dan pengembangan kesehatan Kemenkes RI. (2013). Riset Kesehatan Dasar. http://doi.org/1 Desember 2013

Jeremy, L, W. Ic., Theodore, S, R. I., Susan, S, A. H., Ranzreb. (2002). Spatial Autocorrelation and Autofegressive Models in Ecology. Ecological Monograph2, 72(3), 445–463.

Lee, L. (2010). Estimation of Spatial Autoregressive Panel Data Models with Fixed Effects Journal of Econometrics 154(2):165-185 · February 2010

Mariella, L., & Tarantino, M. (2010). Spatial Temporal Conditional Auto-Regressive Model : A New Autoregressive Matrix 1 Introduction. Austria Journal of Statistics, 39(3), 223–244.

Rejeki, D. S. S., Nurlaela, S., Octaviana, D., Kusnanto, H., & Murhandarwati, E. E. H. (2016). Malaria Community Helath Workers Eliminating Malaria in Banyumas Regency. KEMAS, 12(1), 90–99.

Rejeki, D. S. S., Sari, R. A., & Nurhayati, N. (2014). Annual Parasite Incidence Malaria di Kabupaten Banyumas. Kesmas (Jurnal Kesehatan Masyarakat Nasional), 9(2), 137–143.

Ristiyanto, Dh, F., Wahyuni, S., Gambiro, & Sucipto. (2007). Survei dinamika penularan malaria di Desa Banjaretno, Kecamatan Kajoran, Kabupaten Magelang, Jawa Tengah. Media Litbang Kesehatan, XVII(Mci), 8 – 19. Retrieved from http://ejournal.litbang.depkes.go.id/index.php/MPK/article/view/809/1664

Xia, J., Cai, S., Zhang, H., Lin, W., Fan, Y., Qiu, J., … Nie, S. (2015). Spatial, temporal, and spatiotemporal analysis of malaria in Hubei Province, China from 2004–2011. Malaria Journal, 14(1), 145. http://doi.org/10.1186/s12936-015-0650-2

Refbacks

  • There are currently no refbacks.


Bookmark and Share


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