Modeling the effect of climatic conditions and topography on malaria incidence using Poisson regression: a Retrospective study in Bannu, Khyber Pakhtunkhwa, Pakistan.

Abstract

Malaria has been identified as a crucial vector-borne disease around the globe. The primary aim of this study was to investigate the incidence of malaria in the district of Bannu and its relationship with climatic conditions such as temperature, rainfall, relative humidity, and topography. Secondary data were obtained from the metrological office and government hospitals across the district for 5 years (2013-2017). A Poisson regression model was applied for the statistical analysis. The number of reported cases of malaria was 175,198. The regression analysis showed that temperature, relative humidity, and rainfall had a significant association (p < 0.05) with malaria incidence. In addition, the topographic variables were significantly associated (p < 0.05) with malaria incidence in the region. The percent variation in the odds ratio of incidence was 4% for every unit increase in temperature and 2% in humidity. In conclusion, this study indicated that the temperature, humidity, rainfall, and topographic variables were significantly associated with the incidence of malaria. Effective malaria control and interventions integrated with climatic factors must be considered to overcome the disease burden.