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Binny RN, Baker MG, Hendy SC, et al. Early intervention is the key to success in COVID-19 control. R Soc Open Sci. 2021;8(11):210488doi: 10.1098/rsos.210488.
Binny, R. N., Baker, M. G., Hendy, S. C., James, A., Lustig, A., Plank, M. J., Ridings, K. M., & Steyn, N. (2021). Early intervention is the key to success in COVID-19 control. Royal Society open science, 8(11), 210488. https://doi.org/10.1098/rsos.210488
Binny, Rachelle N, et al. "Early intervention is the key to success in COVID-19 control." Royal Society open science vol. 8,11 (2021): 210488. doi: https://doi.org/10.1098/rsos.210488
Binny RN, Baker MG, Hendy SC, James A, Lustig A, Plank MJ, Ridings KM, Steyn N. Early intervention is the key to success in COVID-19 control. R Soc Open Sci. 2021 Nov 17;8(11):210488. doi: 10.1098/rsos.210488. eCollection 2021 Nov. PMID: 34804563; PMCID: PMC8596003.
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R Soc Open Sci. 2021 Nov 17;8(11):210488. doi: 10.1098/rsos.210488. eCollection 2021 Nov.

Early intervention is the key to success in COVID-19 control.

Royal Society open science

Rachelle N Binny, Michael G Baker, Shaun C Hendy, Alex James, Audrey Lustig, Michael J Plank, Kannan M Ridings, Nicholas Steyn

Affiliations

  1. Manaaki Whenua, Lincoln, New Zealand.
  2. Te P?naha Matatini: the Centre for Complex Systems and Networks, Auckland, New Zealand.
  3. Department of Public Health, University of Otago, Wellington, New Zealand.
  4. Maurice Wilkins Centre for Molecular Biodiscovery, Auckland, New Zealand.
  5. Department of Physics, University of Auckland, Auckland, New Zealand.
  6. School of Mathematics and Statistics, University of Canterbury, Christchurch, New Zealand.

PMID: 34804563 PMCID: PMC8596003 DOI: 10.1098/rsos.210488

Abstract

New Zealand responded to the COVID-19 pandemic with a combination of border restrictions and an Alert Level (AL) system that included strict stay-at-home orders. These interventions were successful in containing an outbreak and ultimately eliminating community transmission of COVID-19 in June 2020. The timing of interventions is crucial to their success. Delaying interventions may reduce their effectiveness and mean that they need to be maintained for a longer period. We use a stochastic branching process model of COVID-19 transmission and control to simulate the epidemic trajectory in New Zealand's March-April 2020 outbreak and the effect of its interventions. We calculate key measures, including the number of reported cases and deaths, and the probability of elimination within a specified time frame. By comparing these measures under alternative timings of interventions, we show that changing the timing of AL4 (the strictest level of restrictions) has a far greater impact than the timing of border measures. Delaying AL4 restrictions results in considerably worse outcomes. Implementing border measures alone, without AL4 restrictions, is insufficient to control the outbreak. We conclude that the early introduction of stay-at-home orders was crucial in reducing the number of cases and deaths, enabling elimination.

© 2021 The Authors.

Keywords: COVID-19; border restrictions; coronavirus; infectious disease outbreak; non-pharmaceutical interventions; stochastic model

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