Dr Rosalind Eggo

Associate Professor


Keppel Street
United Kingdom

I work as an infectious disease modeller in public health epidemiology. I received my PhD in infectious disease modelling from Imperial College London, and worked at The University of Texas at Austin, before joining the School in May 2015.

My general research interests are in the role of population heterogeneity in epidemics, and vaccination planning and evaluation. I work on influenza, respiratory viruses, Ebola virus disease, zika, and theoretical aspects of disease transmission and control. 

Since the start of the COVID-19 pandemic, I have worked extensively on interventions and response for epidemics in the UK and internationally.

As well as research, I enjoy communicating science to people, and have participated in many outreach activities, such as contributing to the Royal Institution Christmas Lectures in 2019, doing a talk at TEDxThessaloniki in 2018 (video here), and other sorts of activities (Let's play video, RI Apocalypse event, Web App for modelling).


Department of Infectious Disease Epidemiology
Faculty of Epidemiology and Population Health


Centre for the Mathematical Modelling of Infectious Diseases (CMMID)
Vaccine Centre


I've completed LSHTM teaching qualificaitions and  am an Associate Fellow of the HEA. At LSHTM, I teach on modelling short courses, face-to-face modules, and on distance learning courses in mathematical modelling.

I am one of three short-course organisers of a new 3-day short course in modelling in R:

I supervise MSc student summer projects in modelling, usually from MSc Epidemiology, but also CID, and Med Stats.

I also supervise 3 excellent PhD students. Please contact me if you are looking to do a PhD in modelling.


My work involves studying how infectious diseases spread between individuals, and how to design efficient vaccination strategies to mitigate outbreaks and epidemics.

In 2018 I received an HDR UK Innovation Fellowship, to study the dynamics of respiratory viruses and the impact on those with chronic lung diseases like asthma and COPD.

Since the start of the COVID-19 pandemic, I have worked extensively on understanding transmission dynamics, and in the design of interventions and responses for epidemics in the UK and internationally.

I am part of the OpenSAFELY consortium to harness NHS data for COVID-19 response in the UK.

I also study the transmission of Ebola virus disease, especially examining recent outbreaks such as in West Africa and DRC. I develop models that can help determine optimal vaccination deployment schemes in the event of a new EVD outbreak, as well as methods for assessing new vaccines during outbreaks. 

Research Area
Clinical trials
Health care policy
Infectious disease policy
Public health
Bayesian Analysis
Disease control
Global Health
Mathematical modelling
Disease and Health Conditions
Infectious disease
Pandemic diseases
Emerging Infectious Disease
Respiratory disease
Zoonotic disease

Selected Publications

Detecting behavioural changes in human movement to inform the spatial scale of interventions against COVID-19.
Gibbs H; Nightingale E; Liu Y; Cheshire J; Danon L; Smeeth L; Pearson CAB; Grundy C; LSHTM CMMID COVID-19 working group; Kucharski AJ
PLoS computational biology
Population disruption: estimating changes in population distribution in the UK during the COVID-19 pandemic
Gibbs H; Waterlow N; Cheshire J; Danon L; Liu Y; Grundy C; Kucharski A; Eggo R; LSHTM CMMID COVID-19 Working Group
Real-time monitoring of COVID-19 dynamics using automated trend fitting and anomaly detection.
Jombart T; Ghozzi S; Schumacher D; Taylor TJ; Leclerc QJ; Jit M; Flasche S; Greaves F; Ward T; Eggo RM
Philosophical transactions of the Royal Society of London. Series B, Biological sciences
Models of COVID-19 vaccine prioritisation: a systematic literature search and narrative review
Saadi N; Chi Y-L; Ghosh S; Eggo R; McCarthy C; Quaife M; Dawa J; Jit M; Vassall A
Mortality among Care Home Residents in England during the first and second waves of the COVID-19 pandemic: an analysis of 4.3 million adults over the age of 65
Schultze A; Nightingale E; Evans D; Hulme W; Rosello A; Bates C; Cockburn J; MacKenna B; Curtis HJ; Morton CE
See more Publications