Dynamics of SARS-CoV-2 and behaviour in Malawi

The 2024/25 application process is now closed

Visit the MRC DTP/CASE at LSTM pages for further information.

Abstract

Understanding where transmission of SARS-CoV-2 occurs and between whom is central to public health interventions, including population-scale interventions to reduce contacts and targeted vaccinations. Additionally, behaviour changes in response to both public health messaging and the threat of novel infectious diseases, such as covid-19. While this is the subject of much research in high-income countries, it has, to date, been little investigated in lower income settings. Unique data, collected by a cohort study in urban and rural sites in Malawi, offers the chance to unravel the relative contribution of various factors in the transmission of SARS-CoV-2, including socio-economic and demographic factors, social mixing rates, hygiene behaviours, and the effect of vaccination and prior infection.

 

Where does the project lie on the Translational Pathway?

T1 – Basic Research          

T2 Human / Clinical Research         

T3 Evidence into Practice 

T4 Practice to Policy / Population

Expected Outputs

The project will aim for a PhD by publication, where the expectation is that there would be at least 3 publications arising directly from the thesis.

Insight into the socioeconomic and behavioural drivers underlying SARS-CoV-2 transmission will be of significant interest to local public health agencies, wider scientific field, and international organisations such a WHO and BMGF. Outputs will be informative for future vaccination programmes in Malawi and other low-income settings.

Training Opportunities

Training in advanced quantitative methods will be delivered through the core MSc modules, and optional MSc modules for infectious disease modelling and geospatial modelling at Lancaster University. Also, training in Bayesian model development and fitting will be provided at Lancaster and where available at IDDconf conference workshops or similar. Additionally, the student will develop advanced skills in coding, data management, and repository version control.

Skills Required

Quantitatively orientated, with an aptitude for coding and mathematics/statistics. Experience in data handling and/or epidemiological fieldwork or immunology would be an advantage.

 

Key Publications associated with this project

Kleynhans J, Tempia S, Wolter N, von Gottberg A, Bhiman JN, Buys A, Moyes J, McMorrow ML, Kahn K, Gómez-Olivé FX, Tollman S. SARS-CoV-2 Seroprevalence in a rural and urban household cohort during first and second waves of infections, South Africa, July 2020–March 2021. Emerging infectious diseases. 2021 Dec;27(12):3020.

Lessler J, Riley S, Read JM, Wang S, Zhu H, Smith GJ, Guan Y, Jiang CQ, Cummings DA. Evidence for antigenic seniority in influenza A (H3N2) antibody responses in southern China. PLoS pathogens. 2012 Jul 19;8(7):e1002802.

Read JM, Bridgen JR, Cummings DA, Ho A, Jewell CP. Novel coronavirus 2019-nCoV (COVID-19): early estimation of epidemiological parameters and epidemic size estimates. Philosophical Transactions of the Royal Society B. 2021 Jul 19;376(1829):20200265.

Moore S, Hill EM, Tildesley MJ, Dyson L, Keeling MJ. Vaccination and non-pharmaceutical interventions for COVID-19: a mathematical modelling study. The Lancet Infectious Diseases. 2021 Jun 1;21(6):793-802.

Moore S, Hill EM, Dyson L, Tildesley MJ, Keeling MJ. Retrospectively modeling the effects of increased global vaccine sharing on the COVID-19 pandemic. Nature Medicine. 2022 Oct 27:1-8.