Modelling the impact of rapid tests, tracing and distancing in lower-income countries suggest that optimal policies vary with rural-urban settings

  1. Xilin Jiang
  2. Wenfeng Gong
  3. Zlatina Dobreva
  4. Ya Gao
  5. Matthew Quaife
  6. Christophe Fraser
  7. Chris Holmes

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Abstract

Low- and middle-income countries (LMICs) remain of high potential for hotspots for COVID-19 deaths and emerging variants given the inequality of vaccine distribution and their vulnerable healthcare systems. We aim to evaluate containment strategies that are sustainable and effective for LMICs. We constructed synthetic populations with varying contact and household structures to capture LMIC demographic characteristics that vary across communities. Using an agent- based model, we explored the optimal containment strategies for rural and urban communities by designing and simulating setting-specific strategies that deploy rapid diagnostic tests, symptom screening, contact tracing and physical distancing. In low-density rural communities, we found implementing either high quality (sensitivity > 50%) antigen rapid diagnostic tests or moderate physical distancing could contain the transmission. In urban communities, we demonstrated that both physical distancing and case finding are essential for containing COVID-19 (average infection rate < 10%). In high density communities that resemble slums and squatter settlements, physical distancing is less effective compared to rural and urban communities. Lastly, we demonstrated contact tracing is essential for effective containment. Our findings suggested that rapid diagnostic tests could be prioritised for control and monitor COVID-19 transmission and highlighted that contact survey data could guide strategy design to save resources for LMICs. An accompanying open source R package is available for simulating COVID-19 transmission based on contact network models.

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  1. Version published to 10.1101/2021.03.17.21253853v3 on medRxiv
  2. Version published to 10.1101/2021.03.17.21253853v2 on medRxiv
  3. ScreenIT

    SciScore for 10.1101/2021.03.17.21253853: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Antibodies
    SentencesResources
    (Figure 1B) The testing methods considered were PCR, antigen RDT and antibody RDT.
    antigen RDT
    suggested: None

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

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    There are some limitations in our study. Firstly, our simulated population is an approximation to the communities in LMICs and is limited by the lack of empirical evidence from LMICs. Therefore, a majority of the parameters are set heuristically rather than by empirical evidence. Our simulation might be improved using detailed demographic data for LMICs, such as those collected from the Office of National Statistics (ONS) in the UK. Secondly, like many simulation studies, we had to choose our parameters from empirical studies that are not consistent with each other. (Omori et al., 2020) This difficulty is most pronounced when we are setting the parameters for age-dependent susceptibility and asymptomatic rate of the infected. Lastly, we scaled up our model by replicating simulations on independent contact networks (200,000 individuals divided into 200 populations of 1,000 individuals) due to the computation constraint of fitting large network models. Compared to simulations on larger networks, (Hinch et al., 2020) our strategy could not capture preparedness triggered by cases from nearby communities or repeated introduction of cases. A simulation framework that simulates large contact networks might provide insights to better coordinate policies for large communities.

    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.
    • No protocol registration statement was detected.

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  4. Version published to 10.1101/2021.03.17.21253853v1 on medRxiv