Local measures enable COVID-19 containment with fewer restrictions due to cooperative effects

Bittihn, Philip; Hupe, Lukas; Isensee, Jonas; Golestanian, Ramin

doi:10.1016/j.eclinm.2020.100718

Cited by 14 publications

(12 citation statements)

References 26 publications

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“…On the other hand, it raises questions regarding the consequences related to population movements that may occur following or preceding the lockdown of a region. 10 In addition, some studies have shown that localized mitigation measures, less strict than national lockdown (curfew in specific metropolitan area, closing of shops or schools), have led to a reduction in the French population mobility 19 and a slowdown of the epidemic in nonrestricted areas. 18 This study highlights that the impact of a delayed regional lockdown greatly depends on the reproduction number in the region, with costs in terms of morbi-mortality growing exponentially with the delay.…”

Section: Discussionmentioning

confidence: 99%

“…5,7 To avoid saturation of the healthcare system, the French government ordered a national lockdown starting on March 17, 2020. The efficacy of lockdown strategies to control COVID-19 epidemics has been internationally demonstrated at the national 1,2,5,8,9 and county levels. 10 However, some have argued that the nationwide application in France of such measures was unnecessary and that lockdowns restricted to the two or three most impacted French regions would have been sufficient to contain the pandemic wave. The present study aimed at retrospectively comparing the impact of the nationwide lockdown on March 17 to regional lockdowns on the number of COVID-19 hospitalizations, occupied ICU beds, life-years gained, and deaths avoided during the first pandemic wave in France.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Impact of national and regional lockdowns on COVID-19 epidemic waves: Application to the 2020 spring wave in France

Roux

Massonnaud

Colizza

et al. 2021

Preprint

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Several countries have implemented lockdowns to control their COVID-19 epidemic. However, questions like "where" and "when" still require answers. We assessed the impact of national and regional lockdowns considering the French first epidemic wave of COVID-19 as a case study. In a regional lockdown scenario aimed at preventing intensive care units (ICU) saturation, almost all French regions would have had to implement a lockdown within 10 days and 96% of ICU capacities would have been used. For slowly growing epidemics, with a lower reproduction number, the expected delays between regional lockdowns increases. However, the public health costs associated with these delays tend to grow exponentially with time. In a quickly growing pandemic wave, defining the timing of lockdowns at a regional rather than national level delays by a few days the implementation of a nationwide lockdown but leads to substantially higher morbidity, mortality and stress on the healthcare system.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Impact of national and regional lockdowns on COVID-19 epidemic waves: Application to the 2020 spring wave in France

Roux

Massonnaud

Colizza

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…To describe the impact of mutations on the infection dynamics within a simple statistical framework, we first generalize the popular susceptible-infected-recovered (SIR) model [17][18][19][20][21][22][23][24][25][26][27][28][29], which has been intensively explored in the context of the COVID-19 pandemic [30][31][32][33][34][35][36][37][38][39][40][41]. While some recent works have generalized this model to account for two different infectious strains [42,43], here we allow for the continuous emergence of new strains with a rate ν, which in general depends on the present infection number.…”

Section: Modelmentioning

confidence: 99%

Mutation induced infection waves in diseases like COVID-19

Schwarzendahl

Grauer

Liebchen

et al. 2021

Preprint

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After almost 4 million deaths worldwide, the ongoing vaccination to conquer the COVID-19 disease is now competing with the emergence of increasingly contagious mutations, repeatedly supplanting earlier strains. Following the near-absence of historical examples of the long-time evolution of infectious diseases under similar circumstances, models are crucial to exemplify possible scenarios. Accordingly, in the present work we systematically generalize the popular susceptible-infected-recovered model to account for mutations leading to repeatedly occurring new strains, which we coarse grain based on tools from statistical mechanics to derive a model predicting the most likely outcomes. The model predicts that mutations can induce a super-exponential growth of infection numbers at early times, which can self-amplify to giant infection waves which are caused by a positive feedback loop between infection numbers and mutations and lead to a simultaneous infection of the majority of the population. At later stages - if vaccination progresses too slowly - mutations can interrupt an ongoing decrease of infection numbers and can cause infection revivals which can occur as single waves or even as whole wave trains featuring alternative periods of decreasing and increasing infection numbers. Our results might be useful for discussions regarding the importance of a release of vaccine-patents to reduce the risk of mutation-induced infection revivals but also to coordinate the release of measures following a downwards trend of infection numbers.

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“…Research into models of spatial epidemiology have produced a number of approaches to the limitations of well-mixed models. 5–9 These works range from exploring known social networks 7 to looking at possible policy responses to the current pandemic. 5 The current paper focuses on a simple random-walk model that lends itself to analytical analysis, in order to explore epidemic properties that arise in the presence of simple spacial dynamics.…”

Section: Introductionmentioning

confidence: 99%

A random-walk-based epidemiological model

Chu

Huber

McGeever

et al. 2020

Preprint

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Random walkers on a two-dimensional square lattice are used to explore the spatio-temporal growth of an epidemic. We have found that a simple random-walk system generates nontrivial dynamics compared with traditional well-mixed models. Phase diagrams characterizing the long-term behaviors of the epidemics are calculated numerically. The phase boundary separating those sets of parameters leading to outbreaks dying out and those leading to indefinite growth is mapped out in detail. The functional dependence of the basic reproductive number R0 on the model's defining parameters reveals the role of spatial fluctuations and leads to a novel expression for R0. Special attention is given to simulations of inter-regional transmission of the contagion. The attack rate and the (growing) radius of gyration of the affected zones are used as measures of the severity of the outbreaks, in cases where R0 is not sufficiently prescriptive to chart the epidemic dynamics.

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Local measures enable COVID-19 containment with fewer restrictions due to cooperative effects

Cited by 14 publications

References 26 publications

Impact of national and regional lockdowns on COVID-19 epidemic waves: Application to the 2020 spring wave in France

Impact of national and regional lockdowns on COVID-19 epidemic waves: Application to the 2020 spring wave in France

Mutation induced infection waves in diseases like COVID-19

A random-walk-based epidemiological model

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