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Dr David Hodgson

BSc MSci MRes PhD

Research Fellow

LSHTM
Keppel Street
London
WC1E 7HT
United Kingdom

I completed my undergraduate studies in Mathematics at University College London (UCL) in 2013. After completing a Masters in Biophysical Sciences at Durham University, I started research into Mathemtical Biology at the Center of Mathematics and Physics in Life sciences and Experimental Biology (CoMPLEX) at UCL. During my time at CoMPLEX, I worked on various infectious disease modelling projects which led me to pursue a PhD in Mathematical modelling and cost-effectivess of future RSV intervention strategies between 2015-2020. During this time I also worked at Public Health England as a Senior Mathematical Modeller, where I used mathematical models to evaluate the effectiveness of existing Influenza vaccination programmes in England and Wales.

 

I joined The London School of Hygeine and Tropical Medicine as a Research Fellow in 2020.

Affiliations

Faculty of Epidemiology and Population Health
Department of Infectious Disease Epidemiology

Centres

Centre for the Mathematical Modelling of Infectious Diseases (CMMID)

Teaching

I am a tutor on two courses at LSHTM, EPM202: Statistical methods in epidemiology, and EPM302: Modelling and the dynamics of infectious diseases.

Research

My main research uses mathematical and statistical models to better inform vaccination resource allocation against respiratory viruses. My work on RSV evaluates the impact of future vaccine candidates and determines cost-effective ways to roll-out potential vaccination programmes. My work on Influenza has previously explored ways to re-allocate the existing seasonal vaccination programme to generate a greater level of herd immunity. My current research is still focused on Influenza, but I am now looking at host-level Influenza antibody dynamics to try and answer questions such as i) how does influenza immunity influence the severity of disease? and ii) how does influenza immunity affect the effectiveness of vaccination strategies?

From a statistical and mathematical perspective, I’m interested in research into Bayesian parameter estimation though Markov chain Monte Carlo (MCMC) methods. In particular, I like exploring contemporary MCMC algorithms and evaluating which are optimised to solving the types of complex non-linear models that arise in infectious disease modelling.

Research Area
Decision analysis
Economic evaluation
Health care policy
Public health
Statistical methods
Vaccines
Viruses
Bayesian Analysis
Disease control
Immunisation
Modelling
Discipline
Epidemiology
Immunology
Mathematics
Mathematical modelling
Statistics
Virology
Disease and Health Conditions
Infectious disease
Pandemic diseases
Influenza
Respiratory disease
Coronavirus

Selected Publications

Estimates for quality of life loss due to Respiratory Syncytial Virus.
Hodgson D; Atkins KE; Baguelin M; Panovska-Griffiths J; Thorrington D; van Hoek AJ; Zhao H; Fragaszy E; Hayward AC; Pebody R
2019
Influenza Other Respir Viruses
A6 Does treatment cause virulence changes in HIV-1?
Hodgson D; Hué S; Panovska-Griffiths J; Iamarino A; Atkins KE
2019
Virus Evolution
Effect of mass paediatric influenza vaccination on existing influenza vaccination programmes in England and Wales: a modelling and cost-effectiveness analysis.
Hodgson D; Baguelin M; van Leeuwen E; Panovska-Griffiths J; Ramsay M; Pebody R; Atkins KE
2017
The lancet Public health
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