Contact tracing and isolation reduces covid-19 incidence in a structured agent-based model

  1. Marcus Low
  2. Nathan Geffen

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Abstract

Background

The World Health Organization has identified contact tracing and isolation (CTI) as a key strategy to slow transmission of SARS-CoV-2. Structured agent-based models (ABMs) provide a means to investigate the efficacy of such strategies in heterogeneous populations and to explore the impact of factors such as changes in test turnaround times (TaT).

Methods

We developed a structured ABM to simulate key SARS-CoV-2 transmission and Covid-19 disease progression dynamics in populations of 10, 000 agents. We ran 10, 000 simulations of each of three scenarios: (1) No CTI with a TaT of two days, (2) CTI with a TaT of two days, and (3) CTI with a TaT of eight days. We conducted a secondary analysis in which TaT values were varied from two to 11. The primary outcome for all analyses was mean total infections.

Results

CTI reduced the mean number of infections from 5, 577 to 4, 157 (a relative reduction of 25.5%) when TaT was held steady at two days. CTI with a TaT of eight days resulted in a mean of 5, 163 infections (a relative reduction of 7.4% compared to no CTI and a TaT of two days). In the secondary analysis, every additional day added to the TaT increased the total number of infections – with the greatest increase in infections between four and five days, and the smallest increase between ten and 11 days.

Conclusions

In a structured ABM that simulates key dynamics of Covid-19 transmission and disease progression, CTI results in a substantial reduction in the mean number of total infections. The benefit is greater with shorter TaT times, but remained substantial even with TaTs of eight days. The results suggest that CTI may play a critical role in reducing the size of outbreaks and that TaTs should be kept as short as possible in order to maximise this benefit.

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    SciScore for 10.1101/2020.10.06.20207761: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: Thank you for sharing your code and data.

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a protocol registration statement.

    About SciScore

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  2. Version published to 10.1101/2020.10.06.20207761v1 on medRxiv