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Quantifying human mixing patterns in Chinese provinces outside Hubei after the 2020 lockdown was lifted
- Source :
- BMC Infectious Diseases, Vol 22, Iss 1, Pp 1-10 (2022)
- Publication Year :
- 2022
- Publisher :
- BMC, 2022.
-
Abstract
- Abstract Background Contact patterns play a key role in the spread of respiratory infectious diseases in human populations. During the COVID-19 pandemic, the regular contact patterns of the population have been disrupted due to social distancing both imposed by the authorities and individual choices. Many studies have focused on age-mixing patterns before the COVID-19 pandemic, but they provide very little information about the mixing patterns in the COVID-19 era. In this study, we aim at quantifying human heterogeneous mixing patterns immediately after lockdowns implemented to contain COVID-19 spread in China were lifted. We also provide an illustrative example of how the collected mixing patterns can be used in a simulation study of SARS-CoV-2 transmission. Methods and results In this work, a contact survey was conducted in Chinese provinces outside Hubei in March 2020, right after lockdowns were lifted. We then leveraged the estimated mixing patterns to calibrate a mathematical model of SARS-CoV-2 transmission. Study participants reported 2.3 contacts per day (IQR: 1.0–3.0) and the mean per-contact duration was 7.0 h (IQR: 1.0–10.0). No significant differences in average contact number and contact duration were observed between provinces, the number of recorded contacts did not show a clear trend by age, and most of the recorded contacts occurred with family members (about 78%). The simulation study highlights the importance of considering age-specific contact patterns to estimate the COVID-19 burden. Conclusions Our findings suggest that, despite lockdowns were no longer in place at the time of the survey, people were still heavily limiting their contacts as compared to the pre-pandemic situation.
Details
- Language :
- English
- ISSN :
- 14712334
- Volume :
- 22
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- BMC Infectious Diseases
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.7d2aeb8921654d7abd94e7e6062fbf80
- Document Type :
- article
- Full Text :
- https://doi.org/10.1186/s12879-022-07455-7