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Optimal timing of one-shot interventions for epidemic control.
Di Lauro, Francesco; Kiss, István Z; Miller, Joel C.
  • Di Lauro F; Department of Mathematics, School of Mathematical and Physical Sciences, University of Sussex, Falmer, Brighton United Kingdom.
  • Kiss IZ; Department of Mathematics, School of Mathematical and Physical Sciences, University of Sussex, Falmer, Brighton United Kingdom.
  • Miller JC; Department of Mathematics and Statistics, School of Engineering and Mathematical Sciences, La Trobe University, Bundoora, Australia.
PLoS Comput Biol ; 17(3): e1008763, 2021 03.
Article in English | MEDLINE | ID: covidwho-1140525
ABSTRACT
The interventions and outcomes in the ongoing COVID-19 pandemic are highly varied. The disease and the interventions both impose costs and harm on society. Some interventions with particularly high costs may only be implemented briefly. The design of optimal policy requires consideration of many intervention scenarios. In this paper we investigate the optimal timing of interventions that are not sustainable for a long period. Specifically, we look at at the impact of a single short-term non-repeated intervention (a "one-shot intervention") on an epidemic and consider the impact of the intervention's timing. To minimize the total number infected, the intervention should start close to the peak so that there is minimal rebound once the intervention is stopped. To minimise the peak prevalence, it should start earlier, leading to initial reduction and then having a rebound to the same prevalence as the pre-intervention peak rather than one very large peak. To delay infections as much as possible (as might be appropriate if we expect improved interventions or treatments to be developed), earlier interventions have clear benefit. In populations with distinct subgroups, synchronized interventions are less effective than targeting the interventions in each subcommunity separately.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pandemics / SARS-CoV-2 / COVID-19 Type of study: Experimental Studies / Observational study Topics: Vaccines Limits: Humans Language: English Journal: PLoS Comput Biol Journal subject: Biology / Medical Informatics Year: 2021 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pandemics / SARS-CoV-2 / COVID-19 Type of study: Experimental Studies / Observational study Topics: Vaccines Limits: Humans Language: English Journal: PLoS Comput Biol Journal subject: Biology / Medical Informatics Year: 2021 Document Type: Article