The spatial mapping of melioidosis exposure in the eastern Indian state of Odisha

Melioidosis, a potentially fatal yet treatable disease complex caused by environmental Gram-negative saprophyte Burkholderia pseudomallei, is an ignored and neglected clinical entity. Excluding the hyperendemic regions of Thailand and Australia, the Indian subcontinent is among the areas with the highest predicted global burden of this disease. Melioidosis is not a notifiable disease in India, and in the last decade, most of the published cases have come from western coastal India and Odisha. The extent of the prevalence of melioidosis and its relationship with various climatic elements need to be better understood, and only a small number of studies have focused on it. Given the mortality of melioidosis, which is around 50 % worldwide, the identification of vulnerable locations is crucial for government entities and policymakers for the effective management and mitigation of the disease. In numerous studies, the prevalence of melioidosis is significantly linked to weather parameters such as rainfall, soil temperature, air temperature, soil moisture, and solar radiation. In this study, using hospital records of the disease and weather parameters from reanalysis datasets, we estimated the potential exposure of different regions in Odisha, a state in eastern India, a leading recorder of melioidosis cases annually. Our analysis reveals that the disease exhibits a clear seasonality, with most cases occurring during the monsoon season (higher by a factor of two compared to other seasons). Disease occurrence also exhibits relationships with temperature, rainfall, cloud cover and solar radiation. Analysis using these variables on disease exposure reveals that all regions of Odisha are vulnerable to melioidosis to variable degrees, out of which the districts of Cuttack, Balasore, Khordha and Jajpur are most vulnerable. The results obtained are expected to increase awareness regarding the potential risk of the issue and help government agencies develop effective mitigation measures.