TY - JOUR

T1 - Preventing a cluster from becoming a new wave in settings with zero community COVID-19 cases

AU - Abeysuriya, Romesh G.

AU - Delport, Dominic

AU - Stuart, Robyn M.

AU - Sacks-Davis, Rachel

AU - Kerr, Cliff C.

AU - Mistry, Dina

AU - Klein, Daniel J.

AU - Hellard, Margaret

AU - Scott, Nick

N1 - Publisher Copyright: © 2022, The Author(s).

PY - 2022

Y1 - 2022

N2 - Background: In settings with zero community transmission, any new SARS-CoV-2 outbreaks are likely to be the result of random incursions. The level of restrictions in place at the time of the incursion is likely to considerably affect possible outbreak trajectories, but the probability that a large outbreak eventuates is not known. Methods: We used an agent-based model to investigate the relationship between ongoing restrictions and behavioural factors, and the probability of an incursion causing an outbreak and the resulting growth rate. We applied our model to the state of Victoria, Australia, which has reached zero community transmission as of November 2020. Results: We found that a future incursion has a 45% probability of causing an outbreak (defined as a 7-day average of > 5 new cases per day within 60 days) if no restrictions were in place, decreasing to 23% with a mandatory masks policy, density restrictions on venues such as restaurants, and if employees worked from home where possible. A drop in community symptomatic testing rates was associated with up to a 10-percentage point increase in outbreak probability, highlighting the importance of maintaining high testing rates as part of a suppression strategy. Conclusions: Because the chance of an incursion occurring is closely related to border controls, outbreak risk management strategies require an integrated approaching spanning border controls, ongoing restrictions, and plans for response. Each individual restriction or control strategy reduces the risk of an outbreak. They can be traded off against each other, but if too many are removed there is a danger of accumulating an unsafe level of risk. The outbreak probabilities estimated in this study are of particular relevance in assessing the downstream risks associated with increased international travel.

AB - Background: In settings with zero community transmission, any new SARS-CoV-2 outbreaks are likely to be the result of random incursions. The level of restrictions in place at the time of the incursion is likely to considerably affect possible outbreak trajectories, but the probability that a large outbreak eventuates is not known. Methods: We used an agent-based model to investigate the relationship between ongoing restrictions and behavioural factors, and the probability of an incursion causing an outbreak and the resulting growth rate. We applied our model to the state of Victoria, Australia, which has reached zero community transmission as of November 2020. Results: We found that a future incursion has a 45% probability of causing an outbreak (defined as a 7-day average of > 5 new cases per day within 60 days) if no restrictions were in place, decreasing to 23% with a mandatory masks policy, density restrictions on venues such as restaurants, and if employees worked from home where possible. A drop in community symptomatic testing rates was associated with up to a 10-percentage point increase in outbreak probability, highlighting the importance of maintaining high testing rates as part of a suppression strategy. Conclusions: Because the chance of an incursion occurring is closely related to border controls, outbreak risk management strategies require an integrated approaching spanning border controls, ongoing restrictions, and plans for response. Each individual restriction or control strategy reduces the risk of an outbreak. They can be traded off against each other, but if too many are removed there is a danger of accumulating an unsafe level of risk. The outbreak probabilities estimated in this study are of particular relevance in assessing the downstream risks associated with increased international travel.

KW - Containment strategy

KW - COVID-19

KW - Modeling

KW - Outbreaks

UR - http://www.scopus.com/inward/record.url?scp=85125977263&partnerID=8YFLogxK

U2 - 10.1186/s12879-022-07180-1

DO - 10.1186/s12879-022-07180-1

M3 - Journal article

C2 - 35255823

AN - SCOPUS:85125977263

VL - 22

SP - 1

EP - 15

JO - B M C Infectious Diseases

JF - B M C Infectious Diseases

SN - 1471-2334

IS - 1

M1 - 232

ER -