Longitudinal datasets hub for predicting and monitoring COVID-19 evolution in the community and mitigation measures outcomes in Rwanda (Predict Project)

A: Background: The coronavirus disease 2019 (COVID19) caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has spread to the whole world in a very fast manner. All countries worldwide elaborated strategies to prevent and manage COVID-19 and mitigate its effects. Diagnostic tests have been designed to detect COVID-19 ARN or antibodies against the virus. Strategies to prevent and control COVID-19 and mitigate its effects have been initiated in all countries at different levels. However, these strategies need continuous adjustment as the characteristics and the dynamics of the virus are progressively discovered. There is need for accurate data on the prevalence, incidence and evolution of the disease. This project comes to add new knowledge on the dynamics of COVID-19 in Rwanda by highlighting the trends in its characteristics. B. Goal and Objectives The goal of this project is to provide data and predictions models for the control and management of COVID-19. Objectives: 1. To gather all existing collected data on COVID-19 in Rwanda in a single data hub server. 2. To collect prospective data on COVID-19 in the community through mobile surveys applications 3. To leverage both traditional mathematical modelling techniques, statistical methods and machine learning methods for prediction models. 4. To provide a live monitoring dashboard for the burden of COVID-19 in the community but also the potential impact on hospital/treatment centre admissions and overall infection rates 5. To predict the impact of various public health measures on the pandemic evolution in the country C. Methods The set objectives will be achieved through 2 approaches: Building a longitudinal datasets hub for predicting and monitoring COVID-19 evolution in the community and in health facilities:  Gathering all existing datasets on Covid-19 in Rwanda (National Joint Taskforce for COVID-19, RBC, MOH)  Integrating other data collected from ongoing cohorts or similar covid-19 projects, including a) the International citizen project to assess adherence to public health measures and their impact on the COVID-19 outbreak (20-country research consortium led by Antwerp University); and b) the National Institute of Statistics of Rwanda (NISR) data.  The survey that will leverage mobile App questionnaires: A minimum of 1200 people per district (36.000 person throughout Rwanda) will be required for mobile App responses weekly (minimum frequency being 2 times per week). A minimum sample of 200 persons per district will be reached out by the data collector with validation call or face-to-face questionnaire. The 32 questionnaires will be translated in 3 languages, Kinyarwanda, English and French in Mobile applications Building an analytical layer on top of the Data Hub, which will leverage both traditional mathematical modelling techniques, statistical methods and machine learning methods for predicting and monitoring the burden of COVID-19 in the community, on hospital/treatment centre admissions and overall infection rates and monitor the impact of various public health measures on the pandemic evolution in the country D: Expected Outcomes are:  Establishment of a robust database gathering various source of data useful for basic epidemiological studies and daily policy-driven decisions but ultimately to be used for the predicting model.  Improved understanding of national, regional and international dynamics of COVID-19 as a result of this study findings aggregated with other research findings.  COVID-19 prevention methods and strategies will be developed based on study findings  COVID-19 pandemic controlled through application of the findings from this study