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Integrated vaccination and non-pharmaceutical interventions based strategies in Ontario, Canada, as a case study: a mathematical modelling study
Journal of The Royal Society Interface ( IF 3.9 ) Pub Date : 2021-07-14 , DOI: 10.1098/rsif.2021.0009
Matthew Betti 1 , Nicola Luigi Bragazzi 2, 3 , Jane M Heffernan 2, 4 , Jude Kong 2, 4 , Angie Raad 2, 4
Affiliation  

Recently, two coronavirus disease 2019 (COVID-19) vaccine products have been authorized in Canada. It is of crucial importance to model an integrated/combined package of non-pharmaceutical (physical/social distancing) and pharmaceutical (immunization) public health control measures. A modified epidemiological, compartmental SIR model was used and fit to the cumulative COVID-19 case data for the province of Ontario, Canada, from 8 September 2020 to 8 December 2020. Different vaccine roll-out strategies were simulated until 75% of the population was vaccinated, including a no-vaccination scenario. We compete these vaccination strategies with relaxation of non-pharmaceutical interventions. Non-pharmaceutical interventions were supposed to remain enforced and began to be relaxed on 31 January, 31 March or 1 May 2021. Based on projections from the data and long-term extrapolation of scenarios, relaxing the public health measures implemented by re-opening too early would cause any benefits of vaccination to be lost by increasing case numbers, increasing the effective reproduction number above 1 and thus increasing the risk of localized outbreaks. If relaxation is, instead, delayed and 75% of the Ontarian population gets vaccinated by the end of the year, re-opening can occur with very little risk. Relaxing non-pharmaceutical interventions by re-opening and vaccine deployment is a careful balancing act. Our combination of model projections from data and simulation of different strategies and scenarios, can equip local public health decision- and policy-makers with projections concerning the COVID-19 epidemiological trend, helping them in the decision-making process.



中文翻译:

以加拿大安大略省基于综合疫苗接种和非药物干预策略的案例研究:数学模型研究

近日,两种2019冠状病毒病(COVID-19)疫苗产品在加拿大获得授权。对非药物(身体/社交距离)和药物(免疫)公共卫生控制措施的综合/组合方案进行建模至关重要。使用了修改后的流行病学分区 SIR 模型,该模型适合加拿大安大略省 2020 年 9 月 8 日至 2020 年 12 月 8 日累计的 COVID-19 病例数据。模拟了不同的疫苗推广策略,直到 75% 的人口已接种疫苗,包括未接种疫苗的情况。我们通过放松非药物干预措施来竞争这些疫苗接种策略。非药物干预措施本应继续执行,并于2021年1月31日、3月31日或5月1日开始放松。根据数据预测和长期情景推断,放松重新开放所实施的公共卫生措施过早接种疫苗会导致病例数量增加、有效繁殖数增加到 1 以上,从而导致局部疫情暴发的风险增加,从而导致疫苗接种的任何益处丧失。相反,如果推迟放松,并且到今年年底安省 75% 的人口接种了疫苗,那么重新开放的风险很小。通过重新开放和部署疫苗来放松非药物干预措施是一种谨慎的平衡行为。我们将数据模型预测与不同策略和情景的模拟相结合,可以为当地公共卫生决策者和政策制定者提供有关 COVID-19 流行病学趋势的预测,帮助他们进行决策。

更新日期:2021-07-14
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