The challenges of containing SARS-CoV-2 via test-trace-and-isolate

Contreras, Sebastián; Dehning, Jonas; Loidolt, Matthias; Zierenberg, Johannes; Spitzner, F. Paul; Urrea-Quintero, Jorge-Humberto; Mohr, Sebastian B.; Wilczek, Michael; Wibral, Michael; Priesemann, Viola

doi:10.1038/s41467-020-20699-8

Cited by 138 publications

(134 citation statements)

References 68 publications

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“…3 , control via TTQ produces strong positive feedback dynamics. This means that it is an especially effective control strategy when case numbers are low; however, even relatively small spikes in cases can cause the system to be overwhelmed, a result that has been seen both in theory 35 and in practice 11 , 12 . If this occurs,without high vaccination rates, then a return to mobility restrictions remains the only consistently effective strategy for regaining control.…”

Section: Discussionmentioning

confidence: 99%

Controlling COVID-19 via test-trace-quarantine

et al. 2021

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Initial COVID-19 containment in the United States focused on limiting mobility, including school and workplace closures. However, these interventions have had enormous societal and economic costs. Here, we demonstrate the feasibility of an alternative control strategy, test-trace-quarantine: routine testing of primarily symptomatic individuals, tracing and testing their known contacts, and placing their contacts in quarantine. We perform this analysis using Covasim, an open-source agent-based model, which has been calibrated to detailed demographic, mobility, and epidemiological data for the Seattle region from January through June 2020. With current levels of mask use and schools remaining closed, we find that high but achievable levels of testing and tracing are sufficient to maintain epidemic control even under a return to full workplace and community mobility and with low vaccine coverage. The easing of mobility restrictions in June 2020 and subsequent scale-up of testing and tracing programs through September provided real-world validation of our predictions. Although we show that test-trace-quarantine can control the epidemic in both theory and practice, its success is contingent on high testing and tracing rates, high quarantine compliance, relatively short testing and tracing delays, and moderate to high mask use. Thus, in order for test-trace-quarantine to control transmission with a return to high mobility, strong performance in all aspects of the program is required.

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Section: Discussionmentioning

confidence: 99%

Controlling COVID-19 via test-trace-quarantine

et al. 2021

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“…In particular, both values do not necessarily need a match, as they represent -slightly- different quantities. The observed

represents whether the overall trend is the spread or containment of the disease, purely driven by data, and is affected by testing and tracing governmental plans [12] . More extensive testing will uncover unnoticed infection chains, and also increase the numbers as the uncovering would be faster than the spread of the disease.…”

Section: Resultsmentioning

confidence: 99%

On the heterogeneous spread of COVID-19 in Chile

Freire-Flores

Llanovarced-Kawles

Sanchez-Daza

et al. 2021

Chaos, Solitons & Fractals

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Non-pharmaceutical interventions (NPIs) have played a crucial role in controlling the spread of COVID-19. Nevertheless, NPI efficacy varies enormously between and within countries, mainly because of population and behavioral heterogeneity. In this work, we adapted a multi-group SEIRA model to study the spreading dynamics of COVID-19 in Chile, representing geographically separated regions of the country by different groups. We use national mobilization statistics to estimate the connectivity between regions and data from governmental repositories to obtain COVID-19 spreading and death rates in each region. We then assessed the effectiveness of different NPIs by studying the temporal evolution of the reproduction number . Analyzing data-driven and model-based estimates of , we found a strong coupling of different regions, highlighting the necessity of organized and coordinated actions to control the spread of SARS-CoV-2. Finally, we evaluated different scenarios to forecast the evolution of COVID-19 in the most densely populated regions, finding that the early lifting of restriction probably will lead to novel outbreaks.

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“…in various online simulator tools [11]. For example, one such scenario study nicely illustrates the effectiveness of a Test-Trace-Isolate strategy [12]. For a data-driven approach focused on short-term forecasts, we need to be more practical: For extrapolation purposes, we fix…”

Section: Methodsmentioning

confidence: 99%

Data-Driven Prediction of COVID-19 Cases in Germany for Decision Making

Lorenz

Riedlinger

Taubenböck

et al. 2021

Preprint

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BackgroundThe COVID-19 pandemic has led to a high interest in mathematical models describing and predicting the diverse aspects and implications of the virus outbreak. Model results represent an important part of the information base for the decision process on different administrative levels. The Robert-Koch-Institute (RKI) initiated a project whose main goal is to predict COVID-19-specific occupation of beds in intensive care units: Steuerungs-Prognose von Intensivmedizinischen COVID-19 Kapazitäten (SPoCK). The incidence of COVID-19 cases is a crucial predictor for this occupation.MethodsWe developed a model based on ordinary differential equations for the COVID-19 spread with a time-dependent infection rate described by a spline. Furthermore, the model explicitly accounts for weekday-specific reporting and adjusts for reporting delay. The model is calibrated in a purely data-driven manner by a maximum likelihood approach. Uncertainties are evaluated using the profile likelihood method. The uncertainty about the appropriate modeling assumptions can be accounted for by including and merging results of different modelling approaches.ResultsThe model is calibrated based on incident cases on a daily basis and provides daily predictions of incident COVID-19 cases for the upcoming three weeks including uncertainty estimates for Germany and its subregions. Derived quantities such as cumulative counts and 7-day incidences with corresponding uncertainties can be computed. The estimation of the time-dependent infection rate leads to an estimated reproduction factor that is oscillating around one. Data-driven estimation of the dark figure purely from incident cases is not feasible.ConclusionsWe successfully implemented a procedure to forecast near future COVID-19 incidences for diverse subregions in Germany which are made available to various decision makers via an interactive web application. Results of the incidence modeling are also used as a predictor for forecasting the need of intensive care units.

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The challenges of containing SARS-CoV-2 via test-trace-and-isolate

Cited by 138 publications

References 68 publications

Controlling COVID-19 via test-trace-quarantine

Controlling COVID-19 via test-trace-quarantine

On the heterogeneous spread of COVID-19 in Chile

Data-Driven Prediction of COVID-19 Cases in Germany for Decision Making

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