ArticlePLoS computational biology2021
Projecting contact matrices in 177 geographical regions: An update and comparison with empirical data for the COVID-19 era.
Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 144 papers.
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Who cites it
144 citing papers in PubMed.
- Live Attenuated Influenza Vaccine (LAIV) for Children for the Prevention of Influenza Illness in Sweden: A Cost-Effectiveness Analysis.Infectious diseases and therapy · 2026Article
- Demographic changes and behavioural responses shape vulnerability to infectious disease outbreaks.PLoS computational biology · 2026Article
- Mapping spatial colleague connectivity patterns from individual-level registry data to inform regional pandemic interventions.PLoS computational biology · 2026Article
- Counterfactual evaluation of elementary and secondary school policies in the COVID-19 pandemic.Nature communications · 2026Article
- Estimating modern US social contact patterns, the ENGAGED study: a study protocol for a staggered longitudinal cohort study.BMJ open · 2026Article
- Dynamic shift in the dominant transmission route of clade Ib monkeypox virus across networks with sexual and nonsexual contacts.Science advances · 2026Article
- VIBES: A multiscale modeling approach integrating within-host and between-hosts dynamics in epidemics.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- A global analysis of patterns of tuberculosis exposure and transmission.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- A Nationwide Social Contact Survey Dataset for Public Health and Social Sciences Research in South Korea.Scientific data · 2026Article
- Retrospective analysis of age-specific non-pharmaceutical interventions on wild-type SARS-CoV-2 in Canada.BMC public health · 2026Article
- Social Mixing Patterns and Chikungunya Reemergence Risk in French Polynesia.JAMA network open · 2026Article
- Modeling the transmission dynamics and control strategies during the 2017 diphtheria outbreak in Jakarta, Indonesia.Infectious Disease Modelling · 2026Article
- Enhancing time-varying reproduction number estimates for COVID-19 with behavior and surveillance data in South Korea, 2020-2022.Archives of public health = Archives belges de sante publique · 2026Article
- Characterizing social behavior relevant for tuberculosis transmission in four low- and middle-income countries.BMC infectious diseases · 2026Article
- Estimating the global burden of viable Mycobacterium tuberculosis infection: A mathematical modelling study.PLoS medicine · 2026Article
- Mobility-driven synthetic contact matrices as a scalable solution for real-time pandemic response modeling.Nature communications · 2026Article
- Informing optimal testing and isolation strategies across different stages of the diagnostic development pipeline using mathematical models: SARS-CoV-2 in the UK as a case study.BMJ public health · 2026Article
- Estimating the basic reproduction number of measles in low-and middle-income settings using 172 seroprevalence studies: A modelling approach.PLOS global public health · 2026Article
- Mobility between communities can reduce the impact of measles intervention during an outbreak: a mathematical modeling study.Frontiers in public health · 2026Article
- Role of community and sexual contacts as drivers of MPXV clade I.Nature health · 2026Article
84 more citing papers are in PubMed but not listed here.
Corrections and comments
- Erratum issued
Authors and funding
8 authors.
Funding
Abstract
Mathematical models have played a key role in understanding the spread of directly-transmissible infectious diseases such as Coronavirus Disease 2019 (COVID-19), as well as the effectiveness of public health responses. As the risk of contracting directly-transmitted infections depends on who interacts with whom, mathematical models often use contact matrices to characterise the spread of infectious pathogens. These contact matrices are usually generated from diary-based contact surveys. However, the majority of places in the world do not have representative empirical contact studies, so synthetic contact matrices have been constructed using more widely available setting-specific survey data on household, school, classroom, and workplace composition combined with empirical data on contact patterns in Europe. In 2017, the largest set of synthetic contact matrices to date were published for 152 geographical locations. In this study, we update these matrices with the most recent data and extend our analysis to 177 geographical locations. Due to the observed geographic differences within countries, we also quantify contact patterns in rural and urban settings where data is available. Further, we compare both the 2017 and 2020 synthetic matrices to out-of-sample empirically-constructed contact matrices, and explore the effects of using both the empirical and synthetic contact matrices when modelling physical distancing interventions for the COVID-19 pandemic. We found that the synthetic contact matrices show qualitative similarities to the contact patterns in the empirically-constructed contact matrices. Models parameterised with the empirical and synthetic matrices generated similar findings with few differences observed in age groups where the empirical matrices have missing or aggregated age groups. This finding means that synthetic contact matrices may be used in modelling outbreaks in settings for which empirical studies have yet to be conducted.
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