Imperial College London

Dr Natsuko Imai

Faculty of MedicineSchool of Public Health

Research Associate



n.imai Website




G26Medical SchoolSt Mary's Campus





I serve as the liaison between the MRC Centre for Global Infectious Disease Analysis (formerly Outbreak Analysis and Modelling) and the World Health Organization. I am responsible for developing and co-ordinating projects to support WHO activities and departments including The Global Influenza Programme, The Initiative for Vaccine Research, and the Global Outbreak Alert and Response Network. As a whole, the Centre provides technical assistance in several disease areas including malaria, HIV, yellow fever, influenza, polio, hepatitis, and dengue.

My personal research interests are in outbreaks, emerging pathogens, and arbovirus transmission dynamics. I am particularly interested in research questions that have a policy focus and in the interface between quantitative evidence and decision-making.

I am a member of the Imperial College COVID-19 and Ebola Response Teams. We have provided real-time outbreak analysis of the multiple Ebola Virus Disease outbreaks in the Democratic Republic of the Congo. 

Over the last 18 months I have been heavily involved in the Centre's COVID-19 response starting with the first assessments of epidemic size and transmissibility when the first cases were reported. More recently, I have supported the UK's response to the pandemic as part of the real-time modelling team, providing prospective and retrospective assessments of the Government's "Roadmap out of Lockdown".

From March to September 2020 I was seconded to the UK Government Office for Science, embedded in the Modelling and Interventions team within the secretariat for the Scientific Advisory Group for Emergencies (SAGE). As an External Science Cell Advisor, I provided scientific support across the COVID-19 response team, particularly on the production of SAGE’s epidemiological advice based on epidemiological analysis and modelling, primarily from the Scientific Pandemic Influenza Group on Modelling (SPI-M) in the Department of Health and Social Care (DHSC). 


I co-organise Imperial's short course, "Introduction to Mathematical Models of the Epidemiology & Control of Infectious Diseases", which is aimed at public health professionals, policy-makers and researchers who want to learn about the basic principles and practical applications of mathematical modelling and modern quantitative methods. For more information please see

quick cv

I studied Biological Sciences (Hons. Infectious Diseases) at the University of Edinburgh followed by a MSc Control of Infectious Diseases at the London School of Hygiene and Tropical Medicine. I joined the Department of Infectious Disease Epidemiology to study for my PhD under the supervision of Prof Neil Ferguson, Dr Simon Cauchemez (now at Institut Pasteur) and Dr Ilaria Dorigatti.

Selected Publications

Journal Articles

Sonabend R, Whittles LK, Imai N, et al., 2021, Non-pharmaceutical interventions, vaccination, and the SARS-CoV-2 delta variant in England: a mathematical modelling study, The Lancet, Vol:398, ISSN:0140-6736, Pages:1825-1835

Imai N, Hogan AB, Williams L, et al., 2021, Interpreting estimates of coronavirus disease 2019 (COVID-19) vaccine efficacy and effectiveness to inform simulation studies of vaccine impact: a systematic review, Wellcome Open Research, Vol:6, Pages:185-185

Djaafara B, Imai N, Hamblion E, et al., 2020, A quantitative framework for defining the end of an infectious disease outbreak: application to Ebola virus disease, American Journal of Epidemiology, Vol:190, ISSN:0002-9262, Pages:642-651

The Ebola Outbreak Epidemiology Team, Bhatia S, Cori A, et al., 2018, Outbreak of Ebola virus disease in the Democratic Republic of the Congo, April–May, 2018: an epidemiological study, The Lancet, Vol:392, ISSN:0140-6736, Pages:213-221

Imai N, Ferguson NM, 2018, Targeting vaccinations for the licensed dengue vaccine: considerations for serosurvey design, PLOS One, Vol:13, ISSN:1932-6203, Pages:1-15

Imai N, Dorigatti I, Cauchemez S, et al., 2015, Estimating Dengue Transmission Intensity from Sero-Prevalence Surveys in Multiple Countries, PLOS Neglected Tropical Diseases, Vol:9, ISSN:1935-2735

Imai N, White MT, Ghani AC, et al., 2014, Transmission and Control of Plasmodium knowlesi: A Mathematical Modelling Study, PLOS Neglected Tropical Diseases, Vol:8, ISSN:1935-2735

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