How and When to End the COVID-19 Lockdown: An Optimization Approach

Rawson, Thomas; Brewer, Tom; Veltcheva, Dessislava; Huntingford, Chris; Bonsall, Michael B.

doi:10.3389/fpubh.2020.00262

Cited by 72 publications

(79 citation statements)

References 32 publications

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“…We set q = 20% to take into account the fact that these key workers continued to access their workplace during the lockdown period. This is also consistent with the methodology in Rawson et al [45] and empirical studies of Santana et al [51] on mobility changes before and after lockdown in the UK. Figure 4 shows the submatrix corresponding to daily mobility across London boroughs, and illustrates the observed dramatic drop in commute patterns.…”

Section: Inter-regional Mobility and Social Contact During Confinementsupporting

confidence: 91%

“…Several recent studies have used homogeneous compartmental models [3,36,17,29,42,48,45,49] or age-stratified versions of such models [1,15,16,34,44,52] to analyse the dynamics and impact of the COVID-19 epidemic in various countries. Our framework, while compatible with such homogeneous models at aggregate level, accounts for demographic and spatial heterogeneity in a more detailed manner, leading to regional outcomes which may substantially deviate from such models, as discussed in Section 5.2.…”

Section: Overviewmentioning

confidence: 99%

“…Homogeneous SIR models [3,36,17,29,42,48,45,49] or age-stratified versions of such models [1,15,16,44,52] have been used in many recent studies on COVID-19 in the UK and other countries.…”

Section: Impact Of Demographic and Spatial Heterogeneitymentioning

confidence: 99%

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Modelling COVID-19 Contagion: Risk Assessment and Targeted Mitigation Policies

Cont

Kotlicki

2020

SSRN Journal

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We use a spatial epidemic model with demographic and geographic heterogeneity to study the regional dynamics of COVID-19 across 133 regions in England. Our model emphasises the role of variability of regional outcomes and heterogeneity across age groups and geographic locations, and provides a framework for assessing the impact of policies targeted towards sub-populations or regions. We define a concept of efficiency for comparative analysis of epidemic control policies and show targeted mitigation policies based on local monitoring to be more efficient than country-level or non-targeted measures. In particular, our results emphasise the importance of shielding vulnerable sub-populations and show that targeted policies based on local monitoring can considerably lower fatality forecasts and, in many cases, prevent the emergence of second waves which may occur under centralised policies.

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Section: Inter-regional Mobility and Social Contact During Confinementsupporting

confidence: 91%

Section: Overviewmentioning

confidence: 99%

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Modelling COVID-19 Contagion: Risk Assessment and Targeted Mitigation Policies

Cont

Kotlicki

2020

SSRN Journal

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“…As a result, if these are addressed now, they will aid the planning of future exit strategies. 4. Data needs and communicating uncertainty (a) What are the additional challenges of data-limited settings?…”

Section: (C) What Is the Role Of Children In Sars-cov-2 Transmission?mentioning

confidence: 99%

Key questions for modelling COVID-19 exit strategies

et al. 2020

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Combinations of intense non-pharmaceutical interventions (lockdowns) were introduced worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement exit strategies that relax restrictions while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute ‘Models for an exit strategy’ workshop (11–15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, would allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. This roadmap requires a global collaborative effort from the scientific community and policymakers, and has three parts: (i) improve estimation of key epidemiological parameters; (ii) understand sources of heterogeneity in populations; and (iii) focus on requirements for data collection, particularly in low-to-middle-income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health.

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“…How long should these restrictions be in place? Several criteria could be applied to determine the end of the restrictive measures 19 . Here we assume that a region is released one week after reaching the peak in the daily incidence of reported cases.…”

Section: How Lockdown and Intervention Measures Affect The Severity Omentioning

confidence: 99%

Fleeing lockdown and its impact on the size of epidemic outbreaks in the source and target regions - a COVID-19 lesson

Barbarossa

Bogya

Dénes

et al. 2020

Preprint

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The COVID-19 pandemic forced authorities worldwide to implement moderate to severe restrictions in order to slow down or suppress the spread of the disease. It has been observed in several countries that a significant number of people fled a city or a region just before strict lockdown measures were implemented. This behavior carries the risk of seeding a large number of infections all at once in regions with otherwise small number of cases. In this work, we investigate the effect of fleeing on the size of an epidemic outbreak in the region under lockdown, and also in the region of destination. We propose a mathematical model that is suitable to describe the spread of an infectious disease over multiple geographic regions. Our approach is flexible to characterize the transmission of different viruses. As an example, we consider the COVID-19 outbreak in Italy. Projection of different scenarios shows that (i) timely and stricter intervention could have significantly lowered the number of cumulative cases in Italy, and (ii) fleeing at the time of lockdown possibly played a minor role in the spread of the disease in the country.

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How and When to End the COVID-19 Lockdown: An Optimization Approach

Cited by 72 publications

References 32 publications

Modelling COVID-19 Contagion: Risk Assessment and Targeted Mitigation Policies

Modelling COVID-19 Contagion: Risk Assessment and Targeted Mitigation Policies

Key questions for modelling COVID-19 exit strategies

Fleeing lockdown and its impact on the size of epidemic outbreaks in the source and target regions - a COVID-19 lesson

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