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印度第三波 COVID-19 疫情可能性的数学建模分析。

Plausibility of a third wave of COVID-19 in India: A mathematical modelling based analysis.

机构信息

Clinical Studies, Projection & Policy Unit, Indian Council of Medical Research, New Delhi, India.

Department of Infectious Disease Epidemiology, MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK.

出版信息

Indian J Med Res. 2021;153(5&6):522-532. doi: 10.4103/ijmr.ijmr_1627_21.


DOI:10.4103/ijmr.ijmr_1627_21
PMID:34643562
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8555606/
Abstract

BACKGROUND & OBJECTIVES: In the context of India's ongoing resurgence of COVID-19 (second wave since mid-February 2021, following the subsiding of the first wave in September 2020), there has been increasing speculation on the possibility of a future third wave of infection, posing a burden on the healthcare system. Using simple mathematical models of the transmission dynamics of SARS-CoV-2, this study examined the conditions under which a serious third wave could occur. METHODS: Using a deterministic, compartmental model of SARS-CoV-2 transmission, four potential mechanisms for a third wave were examined: (i) waning immunity restores previously exposed individuals to a susceptible state, (ii) emergence of a new viral variant that is capable of escaping immunity to previously circulating strains, (iii) emergence of a new viral variant that is more transmissible than the previously circulating strains, and (iv) release of current lockdowns affording fresh opportunities for transmission. RESULTS: Immune-mediated mechanisms (waning immunity, or viral evolution for immune escape) are unlikely to drive a severe third wave if acting on their own, unless such mechanisms lead to a complete loss of protection among those previously exposed. Likewise, a new, more transmissible variant would have to exceed a high threshold (R>4.5) to cause a third wave on its own. However, plausible mechanisms for a third wave include: (i) a new variant that is more transmissible and at the same time capable of escaping prior immunity, and (ii) lockdowns that are highly effective in limiting transmission and subsequently released. In both cases, any third wave seems unlikely to be as severe as the second wave. Rapid scale-up of vaccination efforts could play an important role in mitigating these and future waves of the disease. INTERPRETATION & CONCLUSIONS: This study demonstrates plausible mechanisms by which a substantial third wave could occur, while also illustrating that it is unlikely for any such resurgence to be as large as the second wave. Model projections are, however, subject to several uncertainties, and it remains important to scale up vaccination coverage to mitigate against any eventuality. Preparedness planning for any potential future wave will benefit by drawing upon the projected numbers based on the present modelling exercise.

摘要

背景与目的:在印度 COVID-19 疫情再度爆发的背景下(自 2021 年 2 月中旬以来的第二波疫情,紧随 2020 年 9 月第一波疫情消退之后),人们越来越猜测未来是否会出现第三波感染高峰,从而给医疗系统带来负担。本研究使用 SARS-CoV-2 传播动力学的简单数学模型,探讨了严重的第三波疫情可能出现的条件。

方法:本研究使用 SARS-CoV-2 传播的确定性、隔室模型,研究了第三波疫情的四种可能机制:(i)免疫衰减使先前暴露的个体重新处于易感状态,(ii)出现能够逃避先前流行株免疫的新病毒变异株,(iii)出现比先前流行株更具传染性的新病毒变异株,以及(iv)解除当前封锁,为传播提供新机会。

结果:如果仅靠免疫介导的机制(免疫衰减或病毒进化以逃避免疫),不太可能引发严重的第三波疫情,除非这些机制导致先前暴露的人群完全丧失保护。同样,如果新的、更具传染性的变异株单独出现,其传播能力必须超过一个很高的阈值(R>4.5)才能引发第三波疫情。然而,第三波疫情可能出现的机制包括:(i)一种更具传染性、同时能够逃避先前免疫的新变异株,以及(ii)在限制传播方面非常有效的封锁措施随后被解除。在这两种情况下,任何第三波疫情似乎都不太可能像第二波疫情那样严重。快速扩大疫苗接种工作可能在减轻疾病的这些和未来波次方面发挥重要作用。

解释与结论:本研究表明,出现大量第三波疫情的机制是合理的,同时也表明,任何此类疫情的反弹都不太可能像第二波疫情那样大。然而,模型预测受到多种不确定性的影响,扩大疫苗接种覆盖率以应对任何可能性仍然非常重要。为任何潜在的未来波次做好准备的规划将受益于利用基于当前建模研究的预测数据。

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本文引用的文献

[1]
Reassessing Reported Deaths and Estimated Infection Attack Rate during the First 6 Months of the COVID-19 Epidemic, Delhi, India.

Emerg Infect Dis. 2022-4

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Science. 2021-11-19

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Sci Immunol. 2020-11-18

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