The influence of climate variables on dengue in Singapore
Carregando...
Citações na Scopus
73
Tipo de produção
article
Data de publicação
2011
Título da Revista
ISSN da Revista
Título do Volume
Editora
TAYLOR & FRANCIS LTD
Autores
Citação
INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH, v.21, n.6, p.415-426, 2011
Resumo
In this work we correlated dengue cases with climatic variables for the city of Singapore. This was done through a Poisson Regression Model (PRM) that considers dengue cases as the dependent variable and the climatic variables (rainfall, maximum and minimum temperature and relative humidity) as independent variables. We also used Principal Components Analysis (PCA) to choose the variables that influence in the increase of the number of dengue cases in Singapore, where PC1 (Principal component 1) is represented by temperature and rainfall and PC2 (Principal component 2) is represented by relative humidity. We calculated the probability of occurrence of new cases of dengue and the relative risk of occurrence of dengue cases influenced by climatic variable. The months from July to September showed the highest probabilities of the occurrence of new cases of the disease throughout the year. This was based on an analysis of time series of maximum and minimum temperature. An interesting result was that for every 2-10 degrees C of variation of the maximum temperature, there was an average increase of 22.2-184.6% in the number of dengue cases. For the minimum temperature, we observed that for the same variation, there was an average increase of 26.1-230.3% in the number of the dengue cases from April to August. The precipitation and the relative humidity, after analysis of correlation, were discarded in the use of Poisson Regression Model because they did not present good correlation with the dengue cases. Additionally, the relative risk of the occurrence of the cases of the disease under the influence of the variation of temperature was from 1.2-2.8 for maximum temperature and increased from 1.3-3.3 for minimum temperature. Therefore, the variable temperature (maximum and minimum) was the best predictor for the increased number of dengue cases in Singapore.
Palavras-chave
dengue, Poisson Regression Model, Principal Component Analysis, temperature, relative risk
Referências
- Andrade IS, 2004, ESTUDO INFLUENCIA EL
- Hales S, 2002, LANCET, V360, P830, DOI 10.1016/S0140-6736(02)09964-6
- Halstead SB, 2008, ANNU REV ENTOMOL, V53, P273, DOI 10.1146/annurev.ento.53.103106.093326
- Burattini MN, 2008, EPIDEMIOL INFECT, V136, P309, DOI 10.1017/S0950268807008667
- Costello A, 2009, LANCET, V373, P1693, DOI 10.1016/S0140-6736(09)60935-1
- Patz JA, 2005, NATURE, V438, P310, DOI 10.1038/nature04188
- Camara FP, 2009, REV SOC BRAS MED TRO, V42, P137, DOI 10.1590/S0037-86822009000200008
- Coelho MZ, 2010, J ENV PUBLIC HLTH, V11, DOI [10.1155/2010/209270, DOI 10.1155/2010/209270]
- Coelho-Zanotti MSS, 2007, THESIS DOUTORADO MET
- Dhang CC, 2005, TROPICAL BIOMEDICINE, V22, P39
- Donalísio Maria Rita, 2002, Rev. bras. epidemiol., V5, P259, DOI 10.1590/S1415-790X2002000300005
- Husain Tahir, 2008, Int J Environ Res Public Health, V5, P204, DOI 10.3390/ijerph5040204
- Jetfen TH, 1997, AM J TROP MED HYG, V57, P285
- Johansson MA, 2009, PLOS NEGLECT TROP D, V3, DOI 10.1371/journal.pntd.0000382
- Ministry of Health of Singapore (MOH), 2005, FIN REP EXP PAN DENG
- Murray CJL, 1996, GLOBAL BURDEN DIS
- National Environmental Agency (NEA), 2005, NEAS KEY OP STRAT DE
- Ooi EE, 2008, CAD SAUDE PUBLICA, V25, P115
- Ooi EE, 2001, DENGUE B, V25
- Ooi EE, 2006, EMERG INFECT DIS, V12, P6
- Parry ML, 2007, CONTRIBUTION WORKING
- Smith AW, 2008, MED CLIN N AM, V92, P1377
- Wilder-Smith A, 2004, TROP MED INT HEALTH, V9, P305, DOI 10.1046/j.1365-3156.2003.01177.x
- Wilder-Smith A, 2010, EPIDEMIOL INFECT, V138, P962, DOI 10.1017/S0950268810000683
- Wilks D.S., 1995, STAT METHODS ATMOSPH, P467
- World Health Organization (WHO), 2010, DENG DENG HAEM