EXAMINE SEASONAL VARIATIONS OF DISEASE INCIDENCE IN THE FEDERAL CAPITAL TERRITORY (FCT), NIGERIA
Abstract
This study examines the impact of seasonal climatic elements on the incidence of malaria, measles, meningitis, and pneumonia within the Federal Capital Territory (FCT), Nigeria. Data were collected from 767 health facilities using secondary sources, including hospital records and health departments, across the six area councils of the FCT. Statistical analysis was conducted using the Statistical Package for Social Sciences (SPSS) version 25 and Microsoft Excel, the study employing descriptive and inferential statistics, including chi-square and multiple regression tests, to assess the relationship between climatic variables and disease incidence. The study found significant seasonal variations in disease incidence with Malaria peaked during the rainy season with 32.41% higher incidences than average, Measles exhibited no significant variation across seasons, with a marginal increase of 3.52% during warm months, Meningitis showed a significant increase of 6.40% during warm seasons and Pneumonia had minimal seasonal variations, with no statistically significant differences. The study revealed that climatic factors such as rainfall, temperature, and relative humidity significantly influence the incidence of malaria and meningitis in the FCT. Malaria incidence was notably higher during the rainy season, while meningitis outbreaks were more prevalent during warmer months. No significant seasonal variation was observed for measles and pneumonia. It’s also Concluded that Seasonal weather patterns in the FCT have a marked impact on disease transmission, particularly for malaria and meningitis. Understanding these seasonal variations is crucial for public health planning, allowing for targeted interventions during periods of high disease transmission. The study recommends enhanced disease surveillance systems, particularly during the rainy season for malaria and warmer months for meningitis, incorporating climatic variables into public health forecasting tools to predict and prevent disease outbreaks, and improving public health awareness and preventive measures during critical seasons to mitigate disease incidence.