activity
20192021
most citedKey Questions for Modelling COVID-19 Exit Strategies

138 citations · 141 across the 4 of their papers we have counts for

collaborators

5 papers

stat.AP2021

A Space-time Model for Inferring A Susceptibility Map for An Infectious Disease

Xiaoxiao Li, Matthew Ferrari, Michael J. Tildesley +1

Motivated by foot-and-mouth disease (FMD) outbreak data from Turkey, we develop a model to estimate disease risk based on a space-time record of outbreaks. The spread of infectious…

physics.soc-ph20211 cited

Network structure and disease risk for an endemic infectious disease

Jose L. Herrera-Diestra, Michael Tildesley, Katriona Shea +1

The structure of contact networks affects the likelihood of disease spread at the population scale and the risk of infection at any given node. Though this has been well characteri…

q-bio.OT2020138 cited

Key Questions for Modelling COVID-19 Exit Strategies

Robin N Thompson, T Deirdre Hollingsworth, Valerie Isham +40

Combinations of intense non-pharmaceutical interventions ('lockdowns') were introduced in countries worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to impl…

stat.AP20192 cited

The spatiotemporal tau statistic: a review

Timothy M. Pollington, Michael J. Tildesley, T. Déirdre Hollingsworth +1

Introduction The tau statistic is a recent second-order correlation function that can assess the magnitude and range of global spatiotemporal clustering from epidemiological data c…

stat.ME2019

Developments in statistical inference when assessing spatiotemporal disease clustering with the tau statistic

Timothy M. Pollington, Michael J. Tildesley, T. Déirdre Hollingsworth +1

The tau statistic uses geolocation and, usually, symptom onset time to assess global spatiotemporal clustering from epidemiological data. We test different factors that could a…