Abstract

Kabupaten Banyumas merupakan kabupaten endemis malaria di Provinsi Jawa Tengah. Data Dinas Kesehatan Kabupaten Banyumas tahun 2008 - 2013 menunjukkan angka annual paracite incidence (API) yang selalu mengalami fluktuasi. Dari 27 kecamatan, 22 di antaranya termasuk dalam kategori medium case incidence (MCI) dan low case incidence (LCI). Faktor lingkungan, perilaku, sosial ekonomi, dan iklim berdampak pada tinggi rendahnya kejadian malaria. Tujuan penelitian adalah mengetahui faktor yang berhubungan dengan API di Kabupaten Banyumas. Data dikumpulkan dari Januari 2011 - Desember 2013 menggunakan penelitian analitik dengan rancangan penelitian potong lintang dan menggunakan data sekunder dari Dinas Kesehatan, Dinas Pertanian, dan Badan Pusat Statistik Kabupaten Banyumas. Populasi adalah seluruh kecamatan di Kabupaten Banyumas dan sampel diambil menggunakan teknik total sampling, sebanyak 27 kecamatan dengan pengamatan selama 3 tahun menjadi 81 sampel. Hasil penelitian menunjukkan 44,4% pengamatan termasuk kategori LCI dan MCI, 48,1% termasuk kategori curah hujan tinggi, 49,4% termasuk kategori wilayah yang luas, 49,4% termasuk kategori jumlah pendatang tinggi, 48,1% termasuk kategori kepadatan penduduk sedang. Sementara itu, dari 27 kecamatan, yang termasuk ketinggian rendah adalah 63,0%. Faktor yang terbukti berhubungan dengan API adalah luas wilayah, jumlah pendatang, kepadatan penduduk, sedangkan yang tidak berhubungan adalah curah hujan dan ketinggian. Banyumas is malaria endemic district in Central Java. Banyumas Health Office data of 2008 - 2013 showed that, the Annual Parasite Incidence (API) always fluctuated. From 27 subdistricts in Banyumas, there are 22 subdistricts which fall into the category of middle case incidence (MCI) and low case incidence (LCI). Malaria is a disease that closely associated with the enviroment, behaviour, social economy, and climate. The purpose of this study was to determine factors associated with API in Banyumas. Data were collected from Januari 2011 - Desember 2011 using an analytic crosssectional design using secondary data from Banyumas Health Office, Agriculture Office and Statistic Center. The population in this study were all subdistricts in Banyumas and samples were taken using total sampling technique. The sample of this study was 27 districts. The results showed that from 81 samples we obtained 44.4% of observations included in LCI and MCI category, 48.1% with high rainfall, 49.4% with large areas, 49.4% with high number of entrants, 48.1% with medium population density. Meanwhile, from 27 districts, 63.0% included in low altitude category. Factors associated with API in Banyumas were the extensive areas, the number of entrants, and population density. The factors that are not associated to the API were the rainfall and altitude regions.

References

1. Badan Penelitian dan Pengembangan Kementerian Kesehatan Republik Indonesia. Riset kesehatan dasar tahun 2013. Jakarta: Kementerian Kesehatan Republik Indonesia; 2013.

2. Harijanto PN. Malaria, epidemiologi, patogenesis, manifestasi klinis dan penanganan. Jakarta: EGC; 2000.

3. Paaijmans KP, Read AF, Thomas MB. Understanding the link between malaria risk and climate. Proc Natl Acad Sci [serial on internet]. 2009 [cited 2014 jan 10]; 106: 13844–49. Available from: http://www.pnas. org/site/aboutpnas/index.xhtml)

4. Huang F, Zhou S, Zhang S, Wang H, Tang L. Temporal correlation analysis between malaria and meteorological factors in Motuo County , Tibet. Malaria Journal [serial on internet]. 2011 [cited 2015 Jan 13]; 10(1): [about 8 p.] Available from:: http://www.malariajournal. com/content/10/1/54.

5. Paaijmans KP, Imbahale SS, Thomas MB, Takken W. 2010. Relevant microclimate for determining the development rate of malaria mosquitoes and possible implications of climate change. Malaria Journal [serial on internet]. 2010 [cited 2015 Jan 15]; 9 (196): [about 8 p.] Available from: http://www.malariajournal.com/content/9/1/196

6. Alemu A, Abebe G, Tsegaye W, Golassa L. Climatic variables and malaria transmission dynamics in Jimma town, South West Ethiopia. Parasites & Vectors [serial on internet]. 2011 [cited 2015 Jan 15]; 7 (1): [about 9 p.], Available from: http://www.parasitesandvectors.com/content/4/1/30. 7. Suwito, Hadi UP, Sigit S. Hubungan iklim, kepadatan nyamuk anopheles dan kejadian penyakit malaria. Jurnal Entomologi Indonesia [internet]. 2010 [diakses tanggal 5 Desember 2013]; 7 (1): 42–53. Diunduh dalam: http://ilkom.journal.ipb.ac.id/index.php/entomologi /article/view/6069.

8. Pinsent A, Read JM, Griffin JT, Smith V, Gething P, Ghani AC, et al. Risk factor for UK Plasmodium falciparum cases. Malaria J [serial on internet]. 2014 [cited 2015 mar 19]; 13 (298): [about 8 p.] Available from: http://www.malariajournal.com/content/13/1/298.

9. Ricotta EE, Frese SA, Choobwe C, Loise TA, Shiff CJ. Evaluating local vegetation cover as a risk factor for malaria transmission: a new analytical approach using image. Malaria J [serial on internet]. 2014 [cited 2015 Jan 15]; 13 (94): [about 7 p.] Available from: http://www.malariajournal.com/content/13/1/94.

10. Dinas Kesehatan Kabupaten Banyumas. Profil kesehatan Kabupaten Banyumas tahun 2013. Purwokerto: Dinas Kesehatan Kabupaten Banyumas; 2013.

11. Badan Pusat Statistik. Kabupaten Banyumas dalam angka 2013. Purwokerto: Badan Pusat Statistik Kabupaten Banyumas; 2013.

12. Ernawati K, Soesilo B, Duarsa A, Rifqatussa’adah. Hubungan faktor resiko individu dan lingkungan rumah dengan malaria di punduh pedada kabupaten pesawaran provinsi lampung. Makara Kesehatan. 2010; 15 (2): 51-7.

13. Honrado ER, Fungleda W. Social and behavioral risk faktors related to malaria in southeast asia countries. Bangkok: Department of Tropical Medicine, Faculty of Tropical Medicine, Mahidol University; 2013.

14. Yani F, Bakoro T. Faktor resiko kejadian malaria dan pemetaan pola sebaran vektor pada desa endemis malaria di Kabupaten Banyumas Provinsi Jawa Tengah Tahun 2012 [tesis]. Yogyakarta: Ilmu Kesehatan Masyarakat Universitas Gadjah Mada; 2013.

15. Pim M, Lisbeth H. Malaria on the move: human population movement and malaria transmission. Journal Emerging Infectious Diseases. 2000; 6:103-9.

16. Pindolia DK, Garcia AJ, Huang Z, Fik T, Smith DL, Tatem AJ. Quantifying cross-border movements and migrations for guiding the strategic planning of malaria control and elimination. Malaria J [serial on internet]. 2014 [cited 2014 Des 5]: 13 (169); [about 11 p.]. Available from: http://www.malariajournal.com/content/13/1/94.

17. Tompkins AM, Ermert V. A regional-scale, high resolution dynamical malaria model that accounts for population density, climate and surface hydrology. Malaria J [serial on internet]. 2013 [cited 2014 Des 5] ; 12(65): [about 24 p]. Available from: http://www.malariajournal. com/content/pdf/1475-2875-12-65.pdf

18. Hakim L, Sugianto. Hubungan kepadatan populasi nyamuk Anopheles sundaicus dengan tempat perkembangbiakan di Kabupaten Ciamis. Jurnal Ekologi Kesehatan. 2009; 8 (2): 964-70.

19. Reiter P. 2001. Climate change and mosquito-borne disease. Environmental Health Perspectives. 2001; 109: 223–34. 20. Bi P. Climatic variables and transmission of malaria?: a 12-year data analysis in Shuchen County, China. Public Health Reports. 2003; 118 (February): 65–71.

21. Krefis AC, Schwarz NG, Kruger A, Fobil J, Nkrumah B, Acquah S, et al. Modeling the relationship between precipitation and malaria incidence in children from a holoendemic area in Ghana. Am J Trop Med Hyg [serial on internet]. 2011 [cited 2015 Jan 15]; 84 (2): [about 6 p.] Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3029183&tool=pmcentrez&rendertype=abstract.

22. Hakim L, Ipa M. Sistem kewaspadaan dini KLB malaria berdasarkan curah hujan, kepadatan vertor, dan kesakitan malaria di Kabupaten Sukabumi. Media Litbang Kesehatan. 2007; 17(2): 34-40.

23. Vanderwal T, Paulton R. Malaria in the limbe river valley of Northern Haiti: a hospital-based retrospective study, 1975-1997. Revista Panamarica de Salud Publica. 2000; 7(3): 162-7.

24. Raharjo M. Studi karakteristik wilayah sebagai determinan penyebaran malaria di lereng barat dan timur Pegunungan Muria Jawa Tengah [tesis]. Yogyakarta: Ilmu Lingkungan UGM; 2003.

25. Drakeley CJ, Carneiro I, Reyburn H, Malima R, Lusingu JPA, Cox J, et al. Altitude dependent and independent variations in Plasmodium falciparum prevalence in Northeastern Tanzania. The Journal of Infectious Diseases. 2005; 191: 1589-98.

Download

Share

COinS