An Effort to Collate COVID-19 Case Data Across Africa

The first confirmed case of COVID-19 in sub-Saharan Africa was reported in Nigeria on February 28th. The patient was an Italian man who had recently arrived in Lagos from Milan. At the time of this writing, more than 2,400 cases have been reported across Africa. South Africa, Egypt and Algeria have the highest number of cases - 709, 402, and 264 cases, respectively. Most African countries are reporting new cases every day.

Earlier this year, a group of epidemiologists led by Dr. Moritz Kraemer at Oxford University started collating data on the epidemic in China. This effort has grown to include contributions from around the world. As part of this global effort, we have put together a team of more than twenty volunteers from across Africa to develop an open dataset of cases as they are reported. The dataset includes patient demographics, date of diagnosis, location, symptoms, travel history, source of information and other necessary information. The location data is at the city, town or village level, and does not include household geographical coordinates so as to preserve individuals’ privacy. We obtain the data from official sources (such as the WHO, Ministries of Health, Africa CDC) and unofficial sources (such as online News sites).

These data have many uses. It can help us understand the spread of the SARS-COV-2 in Africa, epidemiological characteristics of cases and how it compares to reports in other parts of the world. The data can also be used in models to study the impact of various interventions (such as social distancing) and for making recommendations on resource allocation. For example, this dashboard developed by Dr. Vukosi Marivate and colleagues provides a picture of COVID-19 in South Africa based on currently available data.

How can you help?

First, we need more volunteers who can help in collating data. The data collation process can be a tedious effort for a few people, but many contributors will make the task easier. To volunteer to join this effort, please send an email to onelaine@bu.edu and also take a look at the Github Repo for additional instructions.

Second, we would like to support data collection efforts by Ministries of Health (MOH) in Africa by connecting them with volunteers in Africa. Volunteers with technical and public health expertise can support the collection, organization, and visualization of relevant data on MOH websites. The rapid increase in new cases is putting a significant burden on the MOH and impacting the reporting of data. This is understandable because MOHs are addressing multiple challenges at this time - including tracking, testing, and quarantining cases, while implementing social distancing and other public health measures to control the local epidemics.

Lastly, we want to encourage everyone to follow the advice of public health experts and clinicians who are dedicating their time and lives to fighting this pandemic in Africa. Stay safe and healthy.

Elaine Nsoesie is a Computational Epidemiologist and Assistant Professor of Global Health at Boston University. She was born and raised in Cameroon. You can contact her by email at onelaine@bu.edu or Twitter: @ensoesie.

Vukosi Marivate is the ABSA UP Chair of Data Science and a Senior Lecturer in the Department of Computer Science, University of Pretoria. He leads the Data Science for Social Impact research group. Vukosi is also a visiting Principal Data Scientist at Council for Scientific and Industrial Research, South Africa. You can contact him by email vukosi.marivate@cs.up.ac.za or Twitter @vukosi.