Dr Rosalind Eggo

Assistant 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. 

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


Mathematical Modelling of Infectious Diseases
Vaccine Centre


I completed Module 1 of PGCILT in 2018, 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.

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

Interventions targeting air travellers early in the pandemic may delay local outbreaks of SARS-CoV-2
Clifford S; Pearson C; Klepac P; Van Zandvoort K; Quilty B; Quilty B; Eggo R; Flasche S; CMMID COVID-19 working group
Feasibility of controlling 2019-nCoV outbreaks by isolation of cases and contacts
Hellewell J; Abbott S; Gimma A; Bosse N; Jarvis C; Russell T; Munday J; Kucharski A; Edmunds J; working group CMMIDN
Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts.
Hellewell J; Abbott S; Gimma A; Bosse NI; Jarvis CI; Russell TW; Munday JD; Kucharski AJ; Edmunds WJ; Centre for the Mathematical Modelling of Infectious Diseases COV
The Lancet. Global health
Early dynamics of transmission and control of COVID-19: a mathematical modelling study.
Kucharski AJ; Russell TW; Diamond C; Liu Y; Edmunds J; Funk S; Eggo RM; Centre for Mathematical Modelling of Infectious Diseases COVID-19 working group
The Lancet. Infectious diseases
Secondary attack rate and superspreading events for SARS-CoV-2.
Liu Y; Eggo RM; Kucharski AJ
Lancet (London, England)
The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: a modelling study.
Prem K; Liu Y; Russell TW; Kucharski AJ; Eggo RM; Davies N; Centre for the Mathematical Modelling of Infectious Diseases COVID-19 Working Group; Jit M; Klepac P
The Lancet. Public health
See more Publications