AdeAdeB/Lassa-Fever-Analysis

Temporal Dynamics and Mortality Burden of Lassa Fever in Nigeria: A Descriptive and Inferential Time-Series Analysis. # Lassa-Fever-Analysis In Nigeria, Lassa fever remains a recurring public health concern with outbreaks reported annually. Despite ongoing surveillance by the Nigeria Centre for Disease Control (NCDC), there is limited statistical assessment of temporal trends, seasonal patterns, and mortality burden using longitudinal surveillance data. Understanding whether Lassa fever incidence exhibits significant seasonal variation, long-term trends, or changes in case fatality rate (CFR) is essential for improving preparedness, outbreak forecasting, and resource allocation. # Project Overview - - This project explores weekly confirmed cases, deaths, and case fatality rate (CFR) trends over time. - The analysis integrates descriptive and inferential statistical techniques to identify patterns, seasonal variation, and statistical significance in transmission dynamics. # Objectives - - Analyze weekly and annual case trends - Evaluate seasonal variation - Examine changes in Case Fatality Rate - Apply inferential statistical tests to determine significance # Tools Used - - Python - Pandas - Matplotlib & Seaborn - Inferential Statistics # Key Insights - - Early-year months showed the highest transmission intensity - A clear seasonal pattern was observed - Case Fatality Rate exhibited instability during peak transmission periods - Inferential analysis confirmed statistically significant variation across time # Files Included - Jupyter Notebook - Final statistical report