FORECASTING THE EFFECT OF TEMPERATURE, RAINFALL AND HUMIDITY ON MALARIA TRANSMISSION DYNAMICS IN BAUCHI STATE FROM 2015–2025
This study examines the impact of climatic variables temperature, rainfall, and humidity on malaria transmission in Bauchi State, Nigeria, from 2015 to 2025. Time series and regression analyses were employed to assess the influence of climate factors on malaria incidence. Secondary data on malaria cases were obtained from the Bauchi State Ministry of Health, while climatic data were sourced from the Nigerian Meteorological Agency (NiMet). The Autoregressive Integrated Moving Average (ARIMA) (2,0,1) model revealed strong seasonal patterns in malaria transmission, with cases peaking during the rainy season and declining during the dry months. Regression results indicated that rainfall and humidity had significant positive effects on malaria incidence, whereas temperature exhibited a significant negative relationship. The model demonstrated a high explanatory power (R² = .969), suggesting that climatic factors account for approximately 96.9% of the variation in malaria cases. Forecasting outcomes predict that malaria incidence will stabilize around 1,000 cases per period, implying sustained transmission unless preventive measures are intensified. The study concludes that climate variability significantly influences malaria dynamics in Bauchi State and recommends integrating climate monitoring into public health planning, enhancing seasonal interventions, and strengthening community awareness to mitigate the impacts of climate change on malaria transmission.