Katie Atkins, PhD

I am a lecturer in Infectious Disease Modelling in the Faculty of Epidemiology and Public Health (Department of Infectious Disease Epidemiology), London School of Hygiene and Tropical Medicine

I use mathematical modeling to answer questions in ecology and evolutionary biology, with a particular focus on infectious diseases.

Interested in a PhD, postdoc or collaboration? Please contact me

*****PhD Opportunity*****

Vaccination against influenza remains one of the most effective ways to reduce the disease complications associated with influenza such as pneumonia. Yet, despite the substantial burden of influenza-associated disease in China, vaccine coverage against seasonal influenza is extraordinarily low at 2%. It is currently unclear how best to vaccinate the population to alleviate the burden of disease.

This PhD would use countrywide data from Chinese disease surveillance systems to understand the transmission of influenza strains, and identify (cost-)effective programs to reduce influenza-associated illness in the world’s most populous country. Using a mathematical modelling approach, the studentship would evaluate the local impact of novel influenza vaccine programs, as well as the global consequences for worldwide seasonal influenza transmission.

Besides supervisors at LSHTM, the candidate is expected to form close links with Public Health officials in Beijing to ensure that the work will influence Chinese immunisation policy. By building on the mathematical modelling approach used to inform the recently introduced paediatric influenza vaccination programme in the UK, the candidate will also work closely with Public Health England staff. The candidate will learn about dynamic modelling of disease spread, surveillance systems, and cost-effectiveness modelling from experts in these fields.

Key references:
Characterization of Regional Influenza Seasonality Patterns in China and Implications for Vaccination Strategies: Spatio-Temporal Modeling of Surveillance Data. Yu H, Alonso WJ, Feng L, Tan Y, Shu Y, et al. (2013) PLoS Med 10(11): e1001552. doi: 10.1371/journal.pmed.1001552

Assessing Optimal Target Populations for Influenza Vaccination Programmes: An Evidence Synthesis and Modelling Study. Baguelin M, Flasche S, Camacho A, Demiris N, Miller E, et al. (2013) PLoS Med 10(10): e1001527. doi: 10.1371/journal.pmed.1001527

For more information: http://www.lshtm.ac.uk/study/funding/mrc_phd_studentships_in_vaccine_research.html