Spatially explicit models for exploring COVID‐19 lockdown strategies

O’Sullivan, David; Gahegan, Mark; Exeter, Daniel; Adams, Benjamin

doi:10.1111/tgis.12660

Cited by 51 publications

(37 citation statements)

References 40 publications

(43 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To the best of our knowledge, there is so far little evidence of how various disease control strategies differ in their efficacy across urban–rural gradients [ 8 ]. To address this gap, using an individual-based metapopulation model, we explore the outcomes of different control strategies to contain the epidemic size of COVID-19 in ever-changing disease landscapes of case numbers and susceptible depletion, which involve strong urban–rural gradients (see the illustration of the study concept in figure 1 ).…”

Section: Introductionmentioning

confidence: 99%

Disease control across urban–rural gradients

Wells

Lurgi

Collins

et al. 2020

J. R. Soc. Interface.

View full text Add to dashboard Cite

Controlling the regional re-emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) after its initial spread in ever-changing personal contact networks and disease landscapes is a challenging task. In a landscape context, contact opportunities within and between populations are changing rapidly as lockdown measures are relaxed and a number of social activities re-activated. Using an individual-based metapopulation model, we explored the efficacy of different control strategies across an urban–rural gradient in Wales, UK. Our model shows that isolation of symptomatic cases or regional lockdowns in response to local outbreaks have limited efficacy unless the overall transmission rate is kept persistently low. Additional isolation of non-symptomatic infected individuals, who may be detected by effective test-and-trace strategies, is pivotal to reducing the overall epidemic size over a wider range of transmission scenarios. We define an ‘urban–rural gradient in epidemic size' as a correlation between regional epidemic size and connectivity within the region, with more highly connected urban populations experiencing relatively larger outbreaks. For interventions focused on regional lockdowns, the strength of such gradients in epidemic size increased with higher travel frequencies, indicating a reduced efficacy of the control measure in the urban regions under these conditions. When both non-symptomatic and symptomatic individuals are isolated or regional lockdown strategies are enforced, we further found the strongest urban–rural epidemic gradients at high transmission rates. This effect was reversed for strategies targeted at symptomatic individuals only. Our results emphasize the importance of test-and-trace strategies and maintaining low transmission rates for efficiently controlling SARS-CoV-2 spread, both at landscape scale and in urban areas.

show abstract

Section: Introductionmentioning

confidence: 99%

Disease control across urban–rural gradients

Wells

Lurgi

Collins

et al. 2020

J. R. Soc. Interface.

View full text Add to dashboard Cite

show abstract

“…We show in this regard that compared to a common control strategy applied uniformly across all counties, minimizing both human health impacts as well as disruptions to economic and other social activities across a state could be better achieved through the deployment of a geographically-targeted approach that explicitly takes into account the impacts of locally-variable risks of virus transmission. These results also question the use of homogenous aggregate level models for reliably predicting and managing the epidemic over a broader spatial region, such as a state, across which the processes that govern the transmission of the virus are likely to vary 15,24,46 .…”

Section: Discussionmentioning

confidence: 99%

“…Partly this is an outcome of our goal to develop a modelling system that would support the generation of forecasts for the contagion in all counties of the United States based on the data presently publically available for facilitating model con gurations -and these currently lack information on these variables 38 . Extending our SEIR model to include these features, however, would allow better treatments of the exposure, risk, and transmission conditions that are likely to underlie the spatial heterogeneity in epidemic dynamics observed at the county level 15,24,46 . The addition of population structure and health composition into our current SEIR model will require deriving and adding more compartments and the applicable contact matrices 7,49,50 , but also, as noted, the con guration data for parameterizing these additions appropriately.…”

Section: Discussionmentioning

confidence: 99%

“…For forecasting epidemics over the near future, this data-model assimilation framework will allow shrinkage of forecast variance while also correcting for model bias and drift 22 . Finally, few currently available mathematical models of SARS-CoV-2 transmission provide predictions at lower administrative levels, such as the county 23,24 . Thus, they do not capture the spatial and social heterogeneity that drives epidemics in the real-world, and lack the resolution for evaluating interventions that take a fuller account of these heterogeneities at the lower spatial scales of an epidemic 15 .…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Iterative near-term forecasting of the transmission and management of SARS-CoV-2/COVID-19 using social interventions at the county-level in the United States

Newcomb¹,

Smith²,

Donohue³

et al. 2020

Preprint

View full text Add to dashboard Cite

The control of the initial outbreak and spread of SARS-CoV-2/COVID-19 by the implementation of unprecedented population-wide non-pharmaceutical mitigation measures has led to remarkable success in dampening the pandemic globally. With many countries easing or beginning to lift these measures to restart activities presently, concern is growing regarding the impacts that such reopening of societies could have on the subsequent transmission of the virus. While mathematical models of COVID-19 transmission have played important roles in evaluating the general population-level impacts of these measures for curbing virus transmission, a key need is for models that are able to effectively capture the effects of the spatial and social heterogeneities that drive the epidemic dynamics observed at the local community level. Iterative near-term forecasting that uses new incoming epidemiological and social behavioural data to sequentially update locally-applicable transmission models can overcome this gap, potentially leading to better predictions and intervention actions. Here, we present the development of one such data-driven iterative modelling tool based on publically-available data and an extended SEIR model for forecasting SARS-CoV-2 at the county level in the United States, and demonstrate, using data from the state of Florida, how this tool can be used to explore the outcomes of the social measures proposed for containing the course of the pandemic as a result of easing the initially imposed lockdown in the state. We provide comprehensive results showing the use of the locally identified models for accessing the impacts and societal tradeoffs of using specific strategies involving movement restriction, social distancing and mass testing, and conclude that while it is absolutely vital to continue with these measures over the near-term and likely to the end of March 2021 in all counties for containing the ongoing pandemic before less socially-disruptive vaccination strategies come into play, it could be possible to lift the more disruptive movement restriction/social distancing measures by end of December 2020 if these are accompanied by widespread testing and contact tracing. Our findings further show that such intensified social interventions could potentially also bring about the control of the epidemic in low and some medium incidence counties first, supporting the development and deployment of a geographically-phased approach to reopening the economy of Florida. We have made our data-driven forecasting system publicly available for policymakers and health officials to use in their own locales, with the hope that a more efficient coordinated strategy for controlling SARS-CoV-2 state-wide, based on effective control of viral transmission at the county level, can be developed and successfully implemented.

show abstract

“…[9][10][11][12][13][14][15][16] Effective control measures that prevent spatial spread of SARS-CoV-2 are urgently demanded, and how NPIs such as travel restrictions and social distancing mitigate the epidemic must be investigated. [17][18][19][20][21][22][23][24][25][26][27] The present study aims to provide meaningful implications for combating the COVID-19 pandemic through interregional mobility restrictions.…”

Section: Introductionmentioning

confidence: 99%

Simulating the Impacts of Interregional Mobility Restriction on the Spatial Spread of COVID-19 in Japan

Kondo

2021

Preprint

View full text Add to dashboard Cite

This study develops a spatial Susceptible–Exposed–Infectious–Recovered (SEIR) model that analyzes the effect of interregional mobility on the spatial spread of the coronavirus disease 2019 (COVID-19) outbreak in Japan. National and local governments have requested that residents refrain from traveling between 47 prefectures during the state of emergency. However, the extent to which restricting the interregional mobility prevents infection expansion has not been elucidated. Our spatial SEIR model describes the spatial spread pattern of COVID-19 when people commute to a prefecture where they work or study during the daytime and return to their residential prefecture at night. We assume that people are exposed to infection risk during their daytime activities. According to our simulation results, interregional mobility restriction can prevent geographical expansion of the infection. However, in prefectures with many infectious individuals, residents are exposed to higher infection risk when their mobility is restricted. Our simulation results also show that interregional mobility restriction plays a limited role in reducing the national total number of infected individuals.

show abstract

Spatially explicit models for exploring COVID‐19 lockdown strategies

Cited by 51 publications

References 40 publications

Disease control across urban–rural gradients

Disease control across urban–rural gradients

Iterative near-term forecasting of the transmission and management of SARS-CoV-2/COVID-19 using social interventions at the county-level in the United States

Simulating the Impacts of Interregional Mobility Restriction on the Spatial Spread of COVID-19 in Japan

Contact Info

Product

Resources

About