Seasonal Variation and Environmental Correlates of Dengue Outbreaks in Purba Medinipur: A Retrospective Study (2017-2023).

Background Dengue fever is a significant public health issue, particularly in tropical regions such as Purba Medinipur, West Bengal. The mosquito, the primary vector for the dengue virus, thrives in warm and humid environments. Previous studies have shown that climatic variables, including rainfall and temperature, significantly impact mosquito breeding and the transmission dynamics of dengue. This study seeks to explore the correlation between these environmental factors and the seasonal variation of dengue outbreaks in Purba Medinipur from 2017 to 2023. Methods This retrospective study used monthly dengue positivity data obtained from local health authorities, along with meteorological data from the Indian Meteorological Department (IMD), to analyze the correlation between dengue outbreaks, rainfall, and temperature. Descriptive statistics were calculated, and Pearson correlation analysis was applied to determine relationships between climatic factors and dengue transmission. A polynomial regression model was used to identify seasonal trends, and a 3D scatter plot was generated to visualize the combined effects of rainfall and temperature. Multivariate regression analysis was also employed to assess the simultaneous impact of these environmental factors while controlling for demographic variables. Results The analysis revealed significant seasonal variation, with dengue outbreaks peaking during the monsoon season (July to September). A strong positive correlation was found between monthly rainfall and dengue positivity rates, indicating that higher rainfall levels provide optimal conditions for mosquito breeding. Temperature also played a critical role, with moderate temperatures (30-35°C) being associated with higher positivity rates, while extreme temperatures were less conducive to mosquito activity and virus transmission. The 3D scatter plot showed that the highest dengue positivity rates occurred when both rainfall and temperature were within specific optimal ranges. Conclusions This study underscores the importance of integrating climatic data into dengue surveillance systems to improve the accuracy of outbreak forecasting. By incorporating environmental factors such as rainfall and temperature into predictive models, public health authorities can better anticipate dengue outbreaks and allocate resources more effectively during high-risk periods, such as the monsoon season. Further research is needed to refine these models by including additional factors like urbanization and vector control measures.