The influence of climate variables on dengue in Singapore

Abstract

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°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.

Hot spot detection and spatio-temporal dynamics of dengue in Queensland, Australia

“…The Cairns region is one of the fastest growing regions in Australia, with (Van Den Hurk et al, 2010). In addition, stagnant water and higher humidity could augment the epidemic during a rainy season (Pinto et al, 2011).…”

Exploratory Analysis of Dengue Fever Niche Variables within the Río Magdalena Watershed

“…A study of DF in Singapore described an increase of 22%-184% in reported cases given a 2-10 • C rise in maximum or minimum temperature [8]. Additional laboratory and field research in Cali, Colombia have also demonstrated a strong relationship between DF dispersion and temperature range [26,27].…”

“…However, more recently it was reported present (although not abundant) at 2130 m in Central Mexico [18] and 2300 m in Colombia [33]. Cultural parameters can involve the presence of anthropogenic water storing activities, which may be responsible for up to 79% of the reported cases [3,8]. Water storage tanks, potted plants, and similar peridomestic related containers can provide larval rearing sites proximal to populated areas.…”

“…Public health agencies can use such tools to implement monitoring and surveillance programs for multiple purposes, including the estimation of vector abundance, implement prevention strategies, or to control for further dispersion of the disease and vector [4,5]. Additionally, local metrics and research are needed to improve current vector disease monitoring practices before cost effective predictive or forewarning systems can be studied or implemented [6][7][8][9]. Therefore, the goal of this study was to investigate the variables which would provide the most benefit to future investigations of predictive modeling.…”

Influência das variáveis climáticas em casos de dengue nas cidades da Baixada Santista (sudeste do Brasil) e Cingapura(sudeste asiático)

“…Portanto, é de grande importância estudar o relacionando entre saúde e clima, pois esta é uma área preocupante quando se leva em consideração a ocorrência das mudanças climáticas (Caseiro et al 2003, Glasser 1997. Este fato é, potencialmente, a maior ameaça à saúde mundial no século 21 (Costello et al 2009 (Jetfen e Focks 1997, Halstead 2008, Smith e Gubler 2008, Camara et al 2009, Johansson et al 2009, Pinto et al 2011. A temperatura, por exemplo, afeta a taxa de maturação e replicação do patógeno no mosquitos, na densidade do vetor em um área particular e aumenta a probabilidade de infecção (Costello et al 2009 (Reiter, 2001).…”