Comparison of different exit scenarios from the lock-down for COVID-19 epidemic in the UK and assessing uncertainty of the predictions

Zhigljavsky, Anatoly; Whitaker, Roger M.; Fesenko, Ivan; Kremnizer, Kobi; Noonan, Jack

doi:10.1101/2020.04.09.20059451

Cited by 9 publications

(8 citation statements)

References 5 publications

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“…Here we looked into the issue of assessing the level of collective immunity [16][17][18][19] , which would be safe for lifting anti-epidemic restrictions. We assumed that the basic reproductive number would be approximately 2.5 without restrictions [20][21][22] .…”

Section: Discussionmentioning

confidence: 99%

Reaching collective immunity for COVID-19: an estimate with a heterogeneous model based on the data for Italy

Герасимов

Lebedev

et al. 2020

Preprint

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Background. At the current stage of COVID-19 pandemic, forecasts become particularly important regarding the possibility that the total incidence could reach the level where the disease stops spreading because a considerable portion of the population has become immune and collective immunity could be reached. Such forecasts are valuable because the currently undertaken restrictive measures prevent mass morbidity but do not result in the development of a robust collective immunity. Thus, in the absence of efficient vaccines and medical treatments, lifting restrictive measures carries the risk that a second wave of the epidemic could occur. Methods. We developed a heterogeneous model of COVID-19 dynamics. The model accounted for the differences in the infection risk across subpopulations, particularly the age-depended susceptibility to the disease. Based on this model, an equation for the minimal number of infections was calculated as a condition for the epidemic to start declining. The basic reproductive number of 2.5 was used for the disease spread without restrictions. The model was applied to COVID-19 data from Italy. Findings. We found that the heterogeneous model of epidemic dynamics yielded a lower proportion, compared to a homogeneous model, for the minimal incidence needed for the epidemic to stop. When applied to the data for Italy, the model yielded a more optimistic assessment of the minimum total incidence needed to reach collective immunity: 43% versus 60% estimated with a homogeneous model. Interpretation. Because of the high heterogeneity of COVID-19 infection risk across the different age groups, with a higher susceptibility for the elderly, homogeneous models overestimate the level of collective immunity needed for the disease to stop spreading. This inaccuracy can be corrected by the homogeneous model introduced here. To improve the estimate even further additional factors should be considered that contribute to heterogeneity, including social and professional activity, gender and individual resistance to the pathogen.

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Section: Discussionmentioning

confidence: 99%

Reaching collective immunity for COVID-19: an estimate with a heterogeneous model based on the data for Italy

Герасимов

Lebedev

et al. 2020

Preprint

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“…attling the spread of SARS-CoV-2, most countries have resorted to social distancing policies, imposing restrictions 1 , from complete lockdowns to severe mobility constraints [2][3][4][5] , gravely impacting socioeconomic stability and growth. Current observations indicate that such policies must be put in place for extended periods (typically months) to avoid the reemergence of the epidemic once lifted [6][7][8] . This, however, may be unsustainable, as individual social and economic needs will, at some point surpass the perceived risk of the pandemic 9 .…”

mentioning

confidence: 99%

Alternating quarantine for sustainable epidemic mitigation

et al. 2021

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Absent pharmaceutical interventions, social distancing, lock-downs and mobility restrictions remain our prime response in the face of epidemic outbreaks. To ease their potentially devastating socioeconomic consequences, we propose here an alternating quarantine strategy: at every instance, half of the population remains under lockdown while the other half continues to be active - maintaining a routine of weekly succession between activity and quarantine. This regime minimizes infectious interactions, as it allows only half of the population to interact for just half of the time. As a result it provides a dramatic reduction in transmission, comparable to that achieved by a population-wide lockdown, despite sustaining socioeconomic continuity at ~50% capacity. The weekly alternations also help address the specific challenge of COVID-19, as their periodicity synchronizes with the natural SARS-CoV-2 disease time-scales, allowing to effectively isolate the majority of infected individuals precisely at the time of their peak infection.

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“…al. [16] predict the end of the pandemic in England by August and Vattay [17] predicts the end of Coronavirus in Italy by May. The former work however allows the disease to spread upto herd immunity while the latter is based on a logistic equation and appears overly simplified.…”

Section: §0 Introductionmentioning

confidence: 99%

Self-Burnout – A New Path to the End of COVID-19

Shayak

Rand

2020

Preprint

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In this work we use mathematical modeling to describe one possible route to the end of COVID-19, which does not feature either vaccination or herd immunity. We consider a region where the following conditions hold true : (a) there is no influx of cases from the outside, (b) there is extensive social distancing, though not necessarily a full lockdown, so that mass transmission events do not occur, and (c) testing capacity is high relative to the actual number of new cases per day. These conditions can make it possible for the region to initiate the endgame phase of epidemic management, wherein the virus is slowly starved of new targets through a combination of social distancing, sanitization, contact tracing and extensive testing. The dynamics of the cases in this regime is governed by a single-variable first order linear delay differential equation, whose stability criterion can be obtained explicitly. Analysis of the equation can tell us which social restrictions may be relaxed during the endgame, and which may not. For example, in an academic institution, a small research group might be allowed to meet in person once a week while classroom instruction should remain fully suspended. If the endgame can be played out for a long enough time, we claim that the disease can eventually get completely contained without affecting a significant fraction of the region's population. We present estimates of the duration for which the epidemic is expected to last, finding an interval of approximately 5-15 weeks after the endgame strategy is initiated.

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Comparison of different exit scenarios from the lock-down for COVID-19 epidemic in the UK and assessing uncertainty of the predictions

Cited by 9 publications

References 5 publications

Reaching collective immunity for COVID-19: an estimate with a heterogeneous model based on the data for Italy

Reaching collective immunity for COVID-19: an estimate with a heterogeneous model based on the data for Italy

Alternating quarantine for sustainable epidemic mitigation

Self-Burnout – A New Path to the End of COVID-19

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