OkyereBiew/COVID-19-Statistical-Surveillance-System

A statistical surveillance framework for monitoring COVID-19 transmission dynamics in Ghana using early warning signals, risk classification, correlation analysis, and regression modeling. # COVID-19 Statistical Surveillance System for Ghana ## Executive Summary This project develops a statistical surveillance framework for monitoring COVID-19 transmission dynamics in Ghana using daily epidemiological data from the Our World in Data (OWID) COVID-19 database. The study applies descriptive statistics, time-series analysis, statistical process monitoring, correlation analysis, and regression modeling to identify transmission patterns, evaluate public health indicators, and detect potential outbreak signals. Using 190 daily observations collected between 13 March 2020 and 19 September 2020, the project investigates trends in reported cases, deaths, testing activity, positivity rates, and government intervention measures. A seven-day moving average surveillance framework was implemented to reduce daily reporting variability and improve outbreak detection. Statistical warning and alert thresholds were developed using rolling means and standard deviations to identify periods of elevated transmission risk. The analysis identified 67 warning signals and 14 alert signals, with the longest alert period occurring from 8 July 2020 to 10 July 2020. Correlation and regression analyses further revealed significant relationships between COVID-19 case counts, positivity rates, testing levels, and government response measures. This project demonstrates how statistical surveillance methodologies can support early outbreak detection, public health decision-making, and evidence-based policy evaluation in resource-constrained settings. ## Research Objectives The primary objective of this project is to develop a statistical surveillance system capable of monitoring and detecting unusual increases in COVID-19 transmission within Ghana. Specific objectives include: 1. Examine temporal trends in daily COVID-19 cases and deaths. 2. Assess testing activity and positivity rates throughout the study period. 3. Develop a statistical surveillance framework using moving avera …