
Dr Juliette Unwin
MEng, PhD
Current positions
Lecturer
School of Mathematics
Contact
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Research interests
I am a Lecturer in Statistical Science in the School of Mathematics at the University of Bristol. I am interested in developing and applying novel methods for infectious disease outbreak analysis to help inform policy makers in real time. My current research focuses on developing spatial temporal renewal based transmission models alongside estimating the number of children affected by COVID-19 and crises.
I am an active member of the Machine Learning and Global Health Network, which is a network of academics across the UK, Denmark, Germany and Singapore doing applied and methodological research in the field of Global Health.
Publications
Selected publications
31/07/2021Global minimum estimates of children affected by COVID-19-associated orphanhood and deaths of caregivers: a modelling study
The Lancet
Global, regional, and national minimum estimates of children affected by COVID-19-associated orphanhood and caregiver death, by age and family circumstance up to Oct 31, 2021: an updated modelling study
The Lancet Child and Adolescent Health
Using Hawkes Processes to model imported and local malaria cases in near-elimination settings
PLoS Computational Biology
Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe
Nature
State-level tracking of COVID-19 in the United States
Nature Communications
Recent publications
20/02/2025Artificial intelligence for modelling infectious disease epidemics
Nature
Exploring the Potential and Limitations of Deep Learning and Explainable AI for Longitudinal Life Course Analysis
BMC Public Health
Orphanhood and caregiver death among children in the United States by all-cause mortality, 2000-2021
Nature Medicine
Protecting Africa's children from extreme risk
The Lancet
Severe acute respiratory syndrome (SARS) mathematical models and disease parameters
The Lancet Microbe