Stochastic effects on the dynamics of an epidemic due to population subdivision

Bittihn, Philip; Golestanian, Ramin

doi:10.1063/5.0028972

Cited by 19 publications

(17 citation statements)

References 22 publications

(20 reference statements)

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“…1 c). This is the result of a cooperative effect between the local measures in different regions: Because of the targeted way in which local measures are applied, they have the chance of rendering individual regions disease-free by the end of the local lockdown or shortly afterwards through extinction [20] , initiating periods of quiescence without the need for restrictions. This happens at a faster rate than infections can be reintroduced through cross infections for sufficiently low ξ .…”

Section: Resultsmentioning

confidence: 99%

“…1 d), using restrictions that are triggered and implemented locally can lead to a large reduction in the required restrictions. Note that these benefits are based explicitly on discrete, low numbers of infected individuals, similar to effects such as extinction [20] and persistence [ 18 , 19 ] observed for the ‘free’ evolution of the epidemic. They would therefore not be present in a deterministic mean-field description [6] (see Supplementary Information) as commonly used to track the dynamics of the pandemic.…”

Section: Discussionmentioning

confidence: 99%

“…Conceivably, the performance of such adaptive, local containment strategies depends on the regional structure of the country and the ability of the disease to spread between the regions within which infection numbers are independently monitored and controlled via contact restrictions. While the free spread of diseases through such subdivided populations [18] , [19] , [20] , networks [ 21 , 22 ] or other spatiotemporal contexts [23] has been investigated theoretically, the effect of other community-based measures has been assessed [24] and general contact patterns have been determined empirically [25] , we are not aware of previous studies that have considered the regional structure of specific countries and its relation to local containment measures in the context of COVID-19.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2021

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

et al. 2021

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“…If local eradication is successful, these countries can profit from the absorbing state of zero SARS-CoV-2 infections, i.e. after local eradication new infection chains are only started if a virus is de novo carried into the country 65;66 . However, the local eradication is constantly put at risk by undetected influx of new viruses from abroad, requiring very strict quarantine for international travel, and – once the spread got out of control – decisive action to completely stop all infection chains.…”

Section: Supplementary Notesmentioning

confidence: 99%

Low case numbers enable long-term stable pandemic control without lockdowns

Contreras

Dehning

Mohr

et al. 2020

Preprint

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The traditional long-term solutions for epidemic control involve eradication or herd immunity 1;2. Neither of them will be attained within a few months for the COVID-19 pandemic. Here, we analytically derive the existence of a third, viable solution: a stable equilibrium at low case numbers, where test-trace-and-isolate policies partially compensate for local spreading events, and only moderate contact restrictions remain necessary. Across wide parameter ranges of our complementary compartmental model 3, the equilibrium is reached at or below 10 daily new cases per million people. Such low levels had been maintained over months in most European countries. However, this equilibrium is endangered (i) if contact restrictions are relaxed, or (ii) if case numbers grow too high. The latter destabilisation marks a novel tipping point beyond which the spread self-accelerates because test-trace-and-isolate capacities are overwhelmed. To reestablish control quickly, a lockdown is required. We show that a lockdown is either effective within a few weeks, or tends to fail its aim. If effective, recurring lockdowns are not necessary — contrary to the oscillating dynamics previously presented in the context of circuit breakers 4;5;6, and contrary to a regime with high case numbers — if moderate contact reductions are maintained. Hence, at low case numbers, the control is easier, and more freedom can be granted. We demonstrate that this strategy reduces case numbers and fatalities by a factor of 5 compared to a strategy focused only on avoiding major congestion of hospitals. Furthermore, our solution minimises lockdown duration, and hence economic impact. In the long term, control will successively become easier due to immunity through vaccination or large scale testing programmes. International coordination would facilitate even more the implementation of this solution.

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“…Epidemiological modelling of the COVID-19 outbreak has been used for forecasting the healthcare demand 2 and to develop containment strategies using non-pharmaceutical interventions (NPI). 3,4,5 Modelling is also used to determine key parameters such as population immunity and infection fatality rate (IFR), and to analyse the impact of imposing and revoking social-distancing measures. 6,7,8,9,10 A well-established class of models is the Susceptible(S)-Exposed(E)-Infected(I)-Recovered(R)-Deceased(D) compartmental model.…”

Section: Introductionmentioning

confidence: 99%

Social-distancing effectiveness tracking of the COVID-19 hotspot Stockholm

Oberhammer

2020

Preprint

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Background: The COVID-19 outbreak in Stockholm, Sweden, is characterized by a near-absence of governmental interventions and high fatalities in the care home population. This study analyses the outbreak and the social-distancing effectiveness timeline in the general population and the care homes. Methods: A novel distributed-compartmental, time-variant epidemiological model was designed specifically for COVID-19 transmission characteristics, featuring a/pre/symptomatic transmission, a non-linear hospital model, a weakly-coupled sub-model for the care-home population, and parametrized continuous social-distancing functions. The model parameters and the social-distancing timelines are determined by randomization and Monte-Carlo simulations analysing real-world data. Findings: Despite a high initial reproduction number (3.29) and the near-absence of governmental interventions, the model quantitated that the transmission rate in the general population was suppressed by 73%, and in the care homes by 79%. The measures in the care homes took effect 4.8 days delayed; and if applied 4 or 8 days earlier, the fatalities could have been reduced by 63.2% or 89.9%. The infected population is estimated to 16.2% (June 10). An expected underestimation of population immunity by antibody studies is confirmed. The infection fatality ratio extrapolates to 0.61% (peak: 1.34%). The model indicates a seasonal effect which effectively suppressed a new rise. An analysed large-scale public event had no large influence. The asymptomatic ratio was determined to 35%. Interpretation: The proposed model and methods have proven to analyse a COVID-19 outbreak and to re-construct the social-distancing behaviour with unprecedented accuracy, confirming even minor details indicated by mobility-data analysis, and are applicable to other regions and other emerging infectious diseases of similar transmission characteristics. The self-regulation of the population in Stockholm, influenced by advices by the authorities, was able to suppress a COVID-19 outbreak to a level far beyond that the stringency index of governmental interventions suggests. Proper timing of effective measures in the care homes is important to reduce fatalities.

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Stochastic effects on the dynamics of an epidemic due to population subdivision

Cited by 19 publications

References 22 publications

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

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

Low case numbers enable long-term stable pandemic control without lockdowns

Social-distancing effectiveness tracking of the COVID-19 hotspot Stockholm

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