OBJECTIVES

: Dengue is caused an arbovirus which is transmitted by Aedes mosquito. The mosquito lifecycle is known to be influenced by various climatic factors like temperature, rainfall, and relative humidity. This study was carried out to examine whether the climatic factors data can be used to predict yearly dengue cases of Bhopal city, of central India.

METHODS

: Monthly reported dengue cases and climate data for the years 2012–2016 were obtained from the Chief Medical and Health officer(CMHO) ,Bhopal and Meteorological Department , respectively. One-way analysis of variance was used to analyse whether the climatic parameters differed significantly among seasons. Four models were developed using negative binomial generalized linear model analysis. Monthly rainfall, temperature, humidity, were used as independent variables, and the number of dengue cases reported monthly was used as the dependent variable. . The first model consider data from the same month, while the other three models involved incorporating data with a lag phase of 1, 2, and 3 months, respectively.

RESULTS

: Climatic factors, i.e. rainfall, maximum temperature and relative humidity were significantly correlated with monthly reported dengue cases. The greatest number of cases was reported during the post-monsoon period each year. Temperature, rainfall, and humidity varied significantly across the pre-monsoon, monsoon, and post-monsoon periods. The best correlation between these three climatic factors and dengue occurrence was at a time lag of 2 months.

CONCLUSIONS

: Our results showed that the climate had a major effect on the occurrence of dengue infection in Bhopal city. Though the prediction model had some limitations in predicting the monthly number of dengue cases, it could forecast possible outbreak two months in advance with considerable accuracy, and can act as early warning system for intensifying dengue control measures.