Researchers to develop predictive COVID-19 Intervention Modelling for East Africa

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A £1m grant from the Wellcome Trust has enabled researchers from the School of Life Sciences at the University of Warwick, to work with East African countries in their emergency preparations for COVID-19 as the pandemic spreads across Africa.

The Wellcome Trust has announced £12m of grants to partnerships with the UK Department for International Development, in a bid to speed up global COVID-19 research and development, in order to help low and middle-income countries prepare for the pandemic.

£1m has been awarded to researchers at the School of Life Sciences and Mathematics Institute at the University of Warwick, who will be working with colleagues in Uganda and Kenya to help East Africa develop optimal control strategies for COVID-19.

The full list of researchers who are all in the Zeeman Institute at Warwick include: Professor James Nokes, Professor Xavier Didelot, both from the School of Life Sciences at the University of Warwick, along with Professor Matt Keeling from the School of Life Sciences and the Mathematics Institute at Warwick, will work with Dr George Githinji from the KEMRI-Wellcome Trust Research program in Kenya, and Professor Matthew Cotten from the MRC/ UVRI and LSHTM Uganda Research Unit.

COVID-19 cases have been recorded in almost all African countries and it's imminent that East Africa will experience onward transmission, as SARS-CoV-2 virus spreads rapidly, meaning control will be difficult.

Researchers will support the emergency response through predictive modeling, incorporating known demographic population structures, age related contact patterns and existing mobile phone population movement data. In Uganda and Kenya they will collect epidemiological, genomic and behavioral data through health facility surveillance, household follow-up and contact studies. This will allow them to quantify uncertainties of SARS-CoV-2 virus epidemiology and contact patterns in well and unwell individuals, and under different social distance interventions.

Work will be done in close collaboration with partner institutes in East Africa (Kenya and Uganda), with other modeling and epidemiology groups in the Region, and in cooperation with government health ministries. This will ensure the modeling is tailored to each country setting and policy relevant questions are addressed, and hence results will be distributed rapidly to the relevant authorities, so that national plans for dealing with this public health emergency can benefit from predictions of the expected rate, distribution and extent of spread in countries throughout the region, and on the likely impact and feasibility of a range of interventions.

We hope that by closely combining our efforts with in-country expertise in modeling, epidemiology, health economics and systems and vulnerability mapping we can develop models appropriate to each setting with results that will immediately feed into the policy making process to have the greatest impact.

Our modeling code and analyses, and data including sequences, will be placed in the public domain in near real-time, in the hope that the project output can be widely adopted and also the evidence to policy links made will have lasting impact on the role of predictive modeling in supporting infectious disease control decisions making."

Professor James Nokes, School of Life Sciences, University of Warwick

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