Evaluating COVID-19 screening strategies based on serological tests

  1. Michela Baccini
  2. Alessandra Mattei
  3. Emilia Rocco
  4. Giulia Vannucci
  5. Fabrizia Mealli

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Abstract

Background

Facing the SARS-CoV-2 epidemic requires intensive testing on the population to early identify and isolate infected subjects. Although RT-PCR is the most reliable technique to detect ongoing infections, serological tests are frequently proposed as tools in heterogeneous screening strategies. We analyze the performance of a screening strategy proposed in Tuscany (Italy), which first uses qualitative rapid tests for antibody detection, and then RT-PCR tests on the positive subjects.

Methods

We simulate the number of RT-PCR tests required by the screening strategy and the undetected ongoing infections in a pseudo-population of 500’000 subjects, under different prevalence scenarios and assuming a sensitivity of the serological test ranging from 0.50 to 0.80 (specificity=0.98). A compartmental model is used to predict the number of new infections generated by the false negatives two months after the screening, under different values of the infection reproduction number.

Results

Assuming a sensitivity equal to 0.80 and a prevalence of 0.3%, the screening procedure would require on average 11167.6 RT-PCR tests and would produce 300 false negatives, responsible after two months of a number of contagions ranging from 526 to 1132, under the optimistic scenario of a reproduction number between 0.5 to 1. Costs and false negatives increase with the prevalence.

Conclusions

The analyzed screening procedure should be avoided unless the prevalence and the rate of contagion are very low. The cost and effectiveness of the screening strategies should be evaluated in the actual context of the epidemic, accounting for the fact that it may change over time.

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  1. ScreenIT

    SciScore for 10.1101/2020.06.12.20129403: (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
    Serological tests generally have a relatively high sensitivity as tests for detecting the presence of antibodies (IgG and IgM) [8].
    IgM
    suggested: None

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    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.
    • No protocol registration statement was detected.

    About SciScore

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  2. Version published to 10.1101/2020.06.12.20129403v1 on medRxiv