A prediction model of Dengue incidence using climate variability in Denpasar city

Khadijah Azhar, Rina Marina, Athena Anwar

Abstract


Latar belakang: Kota Denpasar di Provinsi Bali merupakan salah satu kota dengan kejadian dengue tertinggi di Indonesia. Faktor lingkungan seperti variabilitas iklim merupakan salah satu faktor yang mempengaruhi timbulnya demam berdarah.

Metode: Penelitian ini bertujuan untuk mendapatkan model prediksi kejadian dengue dengan menggunakan data sekunder iklim mingguan dan surveilans demam berdarah di Denpasar, Bali tahun 2010-2014. Data iklim diperoleh dari Badan Meteorologi, Klimatologi, dan Geofisika Indonesia (BMKG), sedangkan data kasus klinis demam berdarah diperoleh dari Sistem Kewaspadaan Dini dan Respon (SKDR), Kementerian Kesehatan RI. Analisis data menggunakan regresi linier dengan berbagai kombinasi variabel iklim dan lag time.

Hasil: Hasil penelitian menunjukkan hubungan yang signifikan antara jumlah kasus demam berdarah, curah hujan, suhu, kelembaban dengan kejadian demam berdarah (p <0,05). Kejadian demam berdarah di kota Denpasar dipengaruhi oleh variabilitas iklim periode 4 minggu (at lag 4 weeks) lebih awal dan jumlah kasus demam berdarah terjadi dua minggu sebelumnya. Dengan demikian faktor iklim mempengaruhi kejadian demam berdarah secara tidak langsung.

Kesimpulan: Model  prediksi  dapat  digunakan  sebagai  salah  satu  pertimbangan  peringatan  dini penyakit demam berdarah di kota Denpasar, disamping memberikan penyuluhan atau upaya edukasi kepada masyarakat tentang pencegahan demam berdarah dan eliminasi vektor. Selain itu memberikan kesempatan bagi sistem kesehatan dalam memahami dan merespon kasus dengue yang lebih baik.

Kata kunci: Denpasar, Dengue, Iklim, Regresi, Lag time.

 

Abstract

Background: Denpasar city in Bali province is one of cities with the highest dengue incidence in Indonesia. Environmental factors such as climate variability is one of the factors that influence the incidence of dengue.

Methods: This study aimed to obtain a predictive dengue incidence models using secondary data of weekly climate and surveillance of dengue cases in Denpasar, Bali, 2010-2014. Climate data was obtained from Indonesia Agency for Meteorological, Climatological, and Geophysical (BMKG), while  dengue clinical cases were obtained from Primary Health Care as reporting unit in Early Warning Alerts Respons System (EWARS) Ministry of Health. Data analysis was using linear regression with various combinations of climate variables and lag time.

Results: The study showed significant relationship between the number of dengue cases, rainfall, temperature, humidity and the incidence of dengue (p<0.05). Incidence of dengue in Denpasar city was affected by climate variability of  4-week period (at lag 4 weeks) earlier and the number of dengue cases was from two weeks earlier. Thus climate factors affected the incidence of dengue indirectly.

Conclusion: The prediction model can be used as one of the considerations on the early warning of dengue disease in Denpasar city, while providing counseling or education efforts to the community about prevention of dengue and vector elimination. It also allows sufficient time for health systems to be prepared to respond and better understanding of dengue cases.

Keywords: Denpasar, Dengue, Climate, Regression, Lag time.


 


 


References


Saxena H. Environmental ecology, biodiversity, and climate change – towards sustainable development. New Delhi: Rawat; 2015.

Wibowo S. Modul perubahan iklim. Jakarta: BMKG; 2013. Indonesian.

Patz JA, Githeko AK, McCarty JP, Hussein S, Confalonieri U, De Wet N. Climate change and infectious diseases. Climate change and human health: risks and responses [Internet]. Mc.Michael AJ, Campbell-Lendrum DH, Corvalan CF, Ebi KL, Githeko AK, Scheraga JD, et al., editors. World Health Organization. Geneva: World Health Organization; 2003.

-306 p. Available from: http://www.who.int/ globalchange/environment/en/ccSCREEN. pdf?ua=1%5Cnhttp://www .jstor .or g/ stable/2137486?origin=crossref

Ramasamy R, Surendran SN. Global climate change and its potential impact on disease transmission by salinity-tolerant mosquito vectors in coastal zones. Front Physiol. 2012 June 3;1–14.

Sly PD. Health impacts of climate change and biosecurity in the Asian Pacific region. Rev Environ Health. 2011 Jan 1;26(1):7–12.

Jing Y, Wang X, Tang S, Wu J. Data informed analysis of 2014 dengue fever outbreak in Guangzhou: Impact of multiple environmental factors and vector control. J Theor Biol [Internet]. 2017;416(December 2016):161–79. Available from: http://dx.doi.org/10.1016/j. jtbi.2016.12.014

Gharbi M, Quenel P, Gustave J, Cassadou S, Ruche G La, Girdary L, et al. Time series analysis of dengue incidence in Guadeloupe, French West Indies: Forecasting models using climate variables as predictors. BMC Infect Dis [Internet]. 2011;11(1):166. Available from: http://bmcinfectdis.biomedcentral.com/ articles/10.1186/1471-2334-11-166

Chen SC, Hsieh MH. Modeling the transmission dynamics of dengue fever: Implications of temperature effects. Sci Total Environ [Internet].

;431:385–91. Available from: http://dx.doi. org/10.1016/j.scitotenv.2012.05.012

Struchiner CJ, Rocklöv J, Wilder-Smith A, Massad E. Increasing dengue incidence in Singapore over the past 40 years: Population growth, climate and mobility. Chowell G, editor. PLoS One [Internet].

Aug 31;10(8):1–14. Available from: http://

dx.plos.org/10.1371/journal.pone.0136286

Morin CW, Comrie AC, Ernst K. Climate and Dengue transmission: Evidence and implications. Environ Health Perspect [Internet].

Sep 20;121(11–12):1264–72. Available from: http://ehp.niehs.nih.gov/1306556/

Tun-Lin W, Burkot TR, Kay BH. Effects of temperature and larval diet on development rates and survival of the dengue vector Aedes aegypti in north Queensland, Australia. Med Vet Entomol [Internet]. 2000 Mar;14(1):31–7. Available from: http://doi.wiley.com/10.1046/ j.1365-2915.2000.00207.x

Rohani A, Wong YC, Zamre I, Lee HL, Zurainee MN. The effect of extrinsic incubation temperature on development of dengue serotype

and 4 viruses in Aedes aegypti (L.). Southeast

Asian J Trop Med Public Health [Internet]. 2009

Sep;40(5):942–50. Available from: http://www. ncbi.nlm.nih.gov/pubmed/19842378

Murray NEA, Quam MB, Wilder-Smith A.

Epidemiology of dengue: Past, present and future prospects. Clin Epidemiol. 2013;5(1):299–309.

CDC. Dengue and theAedes albopictus mosquito.

Centers Dis Control Prev Fact Sheet [Internet].

; Available from: www.cdc.gov/dengue/

resources/30Jan2012/albopictusfactsheet.pdf

Pusat Data dan Informasi. Situasi Demam

Berdarah Dengue di Indonesia. Vol. 1, Infodatin.

p. 1–2. Indonesian.

Dinkes Prov Bali. Provil kesehatan provinsi Bali tahun 2014. Dinas Kesehatan Provinsi Bali. Denpasar: Dinas Kesehatan Provinsi Bali; 2015.

-111 p. Indonesian.

Stoddard ST, Morrison AC, Vazquez-Prokopec GM, Soldan VP, Kochel TJ, Kitron U, et al. The role of human movement in the transmission of Vector-Borne Pathogens. PLoS Negl Trop Dis. 2009;3(7).

Hii YL, Zhu H, Ng N, Ng LC, Rocklöv J. Forecast of Dengue incidence using temperature and rainfall. Mutuku F, editor. PLoS Negl Trop Dis [Internet]. 2012 Nov 29;6(11):e1908. Available from: http://dx.plos.org/10.1371/journal. pntd.0001908

Setiawan O. Analisis variabilitas curah hujan

dan suhu di Bali. J Anal Kebijak Kehutan.

;9(1):66–79.

Grech M, Sartor P, Almiron W, Luduena- Almeida F. Effect of temperature on life history traits during immature development of Aedes aegypti and Culex quinquefasciatus (Diptera: Culicidae) from Córd... - PubMed - NCBI. Acta Trop [Internet]. 2015;(146):1–6.

Available from: http://www.ncbi.nlm.nih.gov/

pubmed/25733491

WHO. Dengue guidelines for diagnosis, treatment, prevention and control [Internet]. France: World Health Organization; 2009 [cited 2017 Oct 4]. Available from: www.who. int/neglected_diseases/en

Hii YL. Climate and dengue fever : Early warning based on temperature and rainfall. Sweden: The Dean of the Medical Faculty;

61 p.

Farjana T, Tuno N, Higa Y. Effects of temperature and diet on development and interspecies competition in Aedes aegypti and

Aedes albopictus. Med Vet Entomol [Internet].

Jun [cited 2016 Aug 5];26(2):210–7. Available from: http://doi.wiley.com/10.1111/ j.1365-2915.2011.00971.x

Sungkar S, Fadli RS, Sukmaningsih A. Trend of Dengue Hemorrhagic fever in North Jakarta. J Indian Med Assoc. 2011;61(10):394–9.

Focks DA, Barrera R. Dengue transmission dynamics: Assessment and implications for control [Internet]. Geneva; 2006 [cited 2017

Oct 9]. Available from: http://www.who.int/tdr/

publications/publications/swg_dengue_2.htm


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