PhD Project Overview
The benefits of vaccines are critically dependent on the vaccination coverage in the target population. High vaccination coverage in the targeted population is essential to optimise the efficiency of their protection of the population against severe and often fatal diseases. Conventional methods of assessing coverage (administrative records -health facility registers/vaccine doses consumed, and/or household surveys of vaccine cards or recall of childhood vaccination history) have well known limitations. In addition, they provide little insight into population immunity which is important because vaccination does not always result in immunisation. Serological surveys are regularly used in developed countries to assess the impact of vaccination programmes, to identify at-risk groups, and to guide revisions to vaccination strategies or schedules (for example, for pertussis and Haemophilus influenzae type b in the United Kingdom).
In sub-Saharan Africa, the converse is true as serosurveys are very rarely used for monitoring vaccination, assessing the impact of vaccination programmes and to predict the need for the very frequently conducted mass vaccination campaigns. In other settings, mathematical modelling techniques have been successfully applied to serologic and other data to determine effective vaccination coverage, assess the impact of vaccination and to predict disease outbreaks.
Main Project Objective
The overall aim of this project is to apply mathematical modelling to serologic data to assess the impact of vaccination in Kenya. This PhD opportunity in infectious diseases modelling will expose the successful candidate to the application of statistical, mathematical and economic modelling approaches to answer a range of questions relevant to vaccine policy in Kenya using serologic and vaccination data.
Successful candidates will primarily be based at the KEMRI-Wellcome Trust Research Programme in Kilifi, Kenya. Registration for this PhD will be at the London School of Hygiene and Tropical Medicine. This studentship provides a full stipend in Kenya and for time at the LSHTM and, contributes towards travel and conference attendance.
- Master’s level degree in Biostatistics, Epidemiology, Mathematics or equivalent with previous/verifiable hands-on experience of infectious diseases modelling.
- Advanced/Expert level proficiency in the use of R, Stata.
- Experience in handling and analysing large datasets.
- Experience of working on human health research data.
- Strong applied mathematics skills.
- Strong quantitative research and numeracy skills.
- Self-motivated with a strong work ethic.
- Ability to think and work with limited supervision.
- Excellent self-organisational and management skills.
Application Deadline: 4 June 2019