Data scientists develop mathematical models to understand COVID-19 intervention strategies, informing public health policy in South Africa
Monday 26 October 2020
A project led by Coventry University’s Centre for Data Science (CDS) has developed mathematical models to predict outcomes of the COVID-19 pandemic in South Africa. In collaboration with researchers at institutions in South Africa, Zimbabwe and the USA, Dr Zindoga Mukandavire investigated how different public health intervention scenarios would affect the spread of the disease.
The lockdown measures in South Africa have been described as some of the most restrictive in the world. Allowing travel only for essential grocery shopping and medical reasons, the restrictions have been generally respected by citizens and have shown some success in controlling the coronavirus. However doubts as to the lockdown’s effectiveness have since emerged.
The research team has chosen to focus on South Africa due to the particular challenges faced by the country at this time. South Africa has one of the highest rates of HIV infection within its population and one of the most significant tuberculosis burdens in the world.
Therefore there is a clear need to develop a better understanding of the likely trajectory of COVID-19 cases in the country. The development of mathematical models enables researchers to predict public health outcomes based on various intervention scenarios, from the development and successful implementation of a vaccine to continued social distancing.
Dr Mukandavire and the team’s analysis of the early phase of the pandemic in South Africa has enabled them to estimate what the effectiveness of any potential vaccine in controlling COVID-19 could be. The team were able to predict that a vaccine with 70% efficacy would be able to contain the outbreak, however this would require almost 95% of the population to be vaccinated. These findings would be of significant help to inform the government in drafting policy in the event of a vaccine becoming available.
Dr Zindoga Mukandavire
The novel nature of COVID-19 means that there is a lack of evidence to inform legislative decisions. While the coronavirus was a relatively late arrival to the African continent compared to Eurasia and the Americas, pre-existing concerns regarding the general health of the South African population and infrastructural issues serve to create a unique set of challenges. The work undertaken as part of this project will therefore provide guidance to policymakers in determining efficient intervention approaches to minimise the impact of COVID-19 on the population moving forward.
The team continues to extract more data in order to build more detailed models for predicting the epidemic and impact of public health interventions at relevant scales.
About CDS: The Centre for Data Science works in the areas of Big Data, Computer Science, Artificial Intelligence and Statistics to apply its findings in diverse zones, such as Biological Sciences, Health, Finance and Digital Arts to ensure real impact where it matters the most. CDS’s multidisciplinary approach means that it regularly undertakes collaborative projects and as such is always interested in engaging new research partners.
Dr Zindoga Mukandavire is a specialist in the implementation of mathematical models to understand and solve problems in biology, medicine, epidemiology and public health.