Explores the correlation between climatic factors and malaria incidence in Kalahandi, indicating significant implications for public health.
BACKGROUND OBJECTIVES: Vector-borne diseases, particularly mosquito-bome illnesses, cause significant global health challenges, leading to approximately 700,000 deaths annually. In India, malaria remains a critical issue, especially in regions like Odisha state, where climatic factors heavily influence transmission dynamics. The study aimed to investigate the correlation between climatic factors (rainfall, temperature, and humidity) and malaria transmission in Kalahandi district of Odisha, India. This work focuses on understanding how local weather conditions affect mosquito breeding, population dynamics, and malaria incidence. METHODS: Epidemiological data from 2019 to 2021 on malaria cases was collected from the Chief District Medical Officer's office in Kalahandi. Entomological data were gathered bimonthly by capturing mosquitoes from various locations in Kalahandi using standard methods. Meteorological data, including monthly rainfall, temperature, and humidity, were obtained from the Odisha government database. The data were analyzed using correlation analysis, linear regression, and Pearson correlation to explore the relationship between weather parameters and malaria cases. RESULTS: The study found that rainfall positively correlates with malaria incidence, particularly during peak rainy seasons (July to September). Plasmodium falciparum cases showed a strong association with precipitation, while temperature and humidity showed mixed results. Excessive rainfall, however, may disrupt mosquito breeding sites. INTERPRETATION CONCLUSION: It was noticed that Anopheles culicifacies was prevalent year-round but was particularly dense during the winter and summer (pre-monsoon) seasons, often in conjunction with Anopheles fluviatilis . The findings highlight the complex interplay of climatic factors influencing malaria transmission in the region, with rainfall being the most significant driver.
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Panigrahi et al. (2025) studied this question.
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