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The impact of contact tracing and household bubbles on deconfinement strategies for COVID-19: an individual-based modelling study
Preprint
en En
| PREPRINT-MEDRXIV
| ID: ppmedrxiv-20144444
ABSTRACT
BackgroundThe rising COVID-19 pandemic caused many governments to impose policies restricting social interactions. These policies have slowed down the spread of the SARS-CoV-2 virus to the extent that restrictions can be gradually lifted. Models can be useful to assess the consequences of deconfinement strategies with respect to business, school and leisure activities. MethodsWe adapted the individual-based model "STRIDE" to simulate interactions between the 11 million inhabitants of Belgium at the levels of households, workplaces, schools and communities. We calibrated our model to observed hospital incidence and seroprevalence data. STRIDE can explore contact tracing options and account for repetitive leisure contacts in extended household settings (so called "household bubbles") with varying levels of connectivity. FindingsHousehold bubbles have the potential to reduce the number of COVID-19 hospital admissions by up to 90%. The effectiveness of contact tracing depends on its timing, as it becomes futile more than 4 days after the index case developed symptoms. Assuming that children have a lower level of susceptibility and lower probability to experience symptomatic SARS-CoV-2 infection, (partial) school closure options have relatively little impact on COVID-19 burden. InterpretationNot only the absolute number and intensity of physical contacts drive the transmission dynamics and COVID-19 burden, also their repetitiveness is influential. Contact tracing seems essential for a controlled and persistent release of lockdown measures, but requires timely compliance to testing, reporting and self-isolation. Rapid tracing and testing, and communication ensuring continued involvement of the population are therefore essential.
cc_by_nc_nd
Texto completo:
1
Colección:
09-preprints
Base de datos:
PREPRINT-MEDRXIV
Tipo de estudio:
Experimental_studies
/
Observational_studies
Idioma:
En
Año:
2020
Tipo del documento:
Preprint