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Emily Nightingale

MSc

Research Fellow
in Statistical Modelling

LSHTM
15-17 Tavistock Place
London
WC1H 9SH
United Kingdom

Tel.
+44 (0)20 7612 7896

Following my BSc in Mathematics and Statistics at the University of Bath, I went on to do the MSc in Medical Statistics here at the School. My MSc thesis was in the field of genetic epidemiology, using random forest classification methods to identify the geographical origin of malaria parasites. I then worked as a Lecturer in Medical Statistics at the Wolfson Institute of Preventive Medicine at QMUL, before returing to the School in May 2018 to join the SPEAK India modelling group. 

Affiliations

Department of Global Health and Development
Faculty of Public Health and Policy

Centres

Centre for the Mathematical Modelling of Infectious Diseases (CMMID)
Centre for Statistical Methodology

Research

I am currently developing statistical models to predict disease incidence and outbreak risk of Visceral Leishmaniasis in North-Eastern India, in order to assist elimination efforts.

Research Area
Statistical methods
Surveillance
Spatial analysis
Modelling
Discipline
Epidemiology
Mathematical modelling
Statistics
Disease and Health Conditions
Neglected Tropical Diseases (NTDs)
Vector borne disease
Leishmaniasis

Selected Publications

Routine childhood immunisation during the COVID-19 pandemic in Africa: a benefit-risk analysis of health benefits versus excess risk of SARS-CoV-2 infection.
Abbas K; Procter SR; van Zandvoort K; Clark A; Funk S; Mengistu T; Hogan D; Dansereau E; Jit M; Flasche S
2020
The Lancet Global Health
Human movement can inform the spatial scale of interventions against COVID-19 transmission
Gibbs H; Nightingale E; Liu Y; Cheshire J; Danon L; Smeeth L; Pearson CAB; Grundy C; Kucharski AJ; Eggo RM
2020
Estimating number of cases and spread of coronavirus disease (COVID-19) using critical care admissions, United Kingdom, February to March 2020.
Jit M; Jombart T; Nightingale ES; Endo A; Abbott S; LSHTM Centre for Mathematical Modelling of Infectious Diseases C; Edmunds WJ
2020
EUROSURVEILLANCE
Real-time monitoring of COVID-19 dynamics using automated trend fitting and anomaly detection
Jombart T; Ghozzi S; Schumacher D; Leclerc Q; Jit M; Flasche S; Greaves F; Ward T; Eggo R; Nightingale E
2020
Analysis of temporal trends in potential COVID-19 cases reported through NHS Pathways England
Leclerc Q; Nightingale E; Abbott S; Jombart T; CMMID COVID-19 Working Group
2020
The importance of saturating density dependence for predicting SARS-CoV-2 resurgence
Nightingale E; Brady O; Yakob L; CMMID Covid-19 working group
2020
A spatio-temporal approach to short-term prediction of visceral leishmaniasis diagnoses in India.
Nightingale ES; Chapman LAC; Srikantiah S; Subramanian S; Jambulingam P; Bracher J; Cameron MM; Medley GF
2020
PLoS neglected tropical diseases
COVID-19 length of hospital stay: a systematic review and data synthesis
Rees EM; Nightingale ES; Jafari Y; Waterlow N; Clifford S; Pearson CAB; Jombert T; Procter SR; Knight GM
2020
BMC medicine
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