Author: Mirjam E Kretzschmar; Ganna Rozhnova; Michiel E van Boven
Title: Effectiveness of isolation and contact tracing for containment and slowing down a COVID-19 epidemic: a modelling study Document date: 2020_3_13
ID: kgkcgpmq_2
Snippet: (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.03.10.20033738 doi: medRxiv preprint limited, it is important to assess which interventions are most effective in slowing down the 121 rate of increase of healthcare demand during an ongoing outbreak. As it is likely that, on the 122 one hand, isolation and contact tracing will be more effective in close contact settings with 123 well-defined conta.....
Document: (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.03.10.20033738 doi: medRxiv preprint limited, it is important to assess which interventions are most effective in slowing down the 121 rate of increase of healthcare demand during an ongoing outbreak. As it is likely that, on the 122 one hand, isolation and contact tracing will be more effective in close contact settings with 123 well-defined contacts (household, workplace) than in the community (commuting, public Table 1) . We distinguish 139 between household contacts and non-household contacts, which differ in the risk of 140 infection and the delay and effectiveness of tracing and isolation. Intervention effectiveness 141 is determined by the daily probability of being diagnosed during the infectious period (Table 142 2). Furthermore, intervention effectiveness depends on the delays in tracing household and 143 non-household contacts, respectively, and the proportions of contacts can be found and 144 isolated. We assume that isolation is perfect, i.e. that isolated persons cannot transmit any Natural history 150 We assume that the latent period lasts between 1 and 3 days. Individuals then become 151 infectious for at most 10 days. Infectivity is high at the beginning of the infectious period 152 and decays to low levels during these 10 days ( Figure S1a ). The probability of symptoms 153 onset increases during the first 4 days of the infectious period, thereby influencing the daily 154 probability of diagnosis during the infectious period (see below).
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