Contact matrices for the COVID-19 era
Please join this seminar where experts from the LSHTM Centre for the Mathematical Modelling of Infectious Diseases will discuss the topic “contact matrices for the COVID-era”.
The risk of contracting a directly-transmitted infectious disease like COVID-19 depends on who interacts with whom and varies by age and locations, for instance at home, at work or in the community, because of the different social structures and mixing patterns in those locations. These social structures, and thus contact patterns, vary across and within countries and are usually generated from diary-based contact surveys.
Mathematical models often use contact patterns to characterise the spread of infectious pathogens. However, but in large swathes of the world, particularly low- and middle-income countries, contact patterns remain unmeasured, which makes it challenging to build mathematical or computer models of disease spread and control.
In 2017, the largest set of age- and location-specific synthetic contact matrices to date were published for 152 geographical locations by adapting contact pattern data from eight European countries using country-specific data on household size, school and workplace composition. These synthetic matrices have since been updated with the most recent data from Demographic Household Surveys, World Bank, UN Population Division extending the coverage to 177 geographical locations, covering 97.2% of the world's population.
The recent CoMix surveys of social contacts across Europe measured changes in people's behaviors during COVID-19-related physical distancing measures. Individuals' contact patterns reduced by 70% during the lockdown in the UK, but the return to pre-lockdown levels have been far slower than initially anticipated in COVID-19 modelling.
- Mark Jit, Professor of Vaccine Epidemiology, LSHTM
- Alex R Cook, Associate Professor, Saw Swee Hock School of Public Health, National University of Singapore
- Kiesha Prem, Research Fellow, LSHTM
- Rosalind Eggo, Assistant Professor, LSHTM
- John Edmunds, Professor, LSHTM
- Amy Gimma, Research Fellow, LSHTM
Please note that the recording link will be made available in due course
For further information, please find the speakers' presentation below:
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