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  1. Our take

    This retrospective study, available as a preprint and thus not yet peer-reviewed, assessed whether the emergence of the Omicron SARS-CoV-2 variant of concern was associated with an increased risk of reinfection using data for all positive test results in South Africa between March 4, 2020, and November 27, 2021 (n= 2,796,982). Suspected reinfection (two positive tests >90 days apart) was identified for 35,670 participants. Two statistical models were used to assess changes in risk—one based on a constant hazard of reinfection throughout the study period, and one based on time-varying hazards of primary infection and reinfection. Both approaches demonstrated that the emergence of the Omicron variant was associated with an increased risk of reinfection. For the second model, the hazard ratio for reinfection vs. primary infection following the introduction of the Omicron variant was 2.39 (95% CI: 1.88–3.11), demonstrating population-level evidence of immune escape, a finding not observed with emergence of either Beta or Delta variants. This study demonstrates the risk that the Omicron variant poses for reinfection in the setting of high rates of prior SARS-CoV-2 infection. Additional research is urgently needed to assess the ability of prior infection and/or vaccination to protect against severe disease and death from Omicron.

    Study design


    Study population and setting

    This study examined whether the emergence of the Beta, Delta, and Omicron SARS-CoV-2 variants of concern led to increased risk of reinfection in South Africa. Study data included all laboratory-confirmed SARS-CoV-2 positive test results received by the Notifiable Medical Conditions Surveillance System (NMC-SS) between March 4, 2020, and November 27, 2021 (n= 2,796,982). For the sake of consistency and data completeness, the date that each specimen was received in the lab was used as a proxy for calendar date of infection. Reinfection was defined as two positive SARS-CoV-2 tests at least 90 days apart for the same participant. Two statistical approaches were used to assess changes in risk of reinfection over time. In the first approach, observed reinfection patterns were compared to a null model that assumed risk of reinfection was proportional to overall incidence with a constant hazard coefficient. In the second approach, empirical hazard coefficients for primary infection vs. reinfection were calculated at each time point and compared over time. A sensitivity analysis was conducted to assess the impact of vaccination.

    Summary of main findings

    The study population included 35,670 participants with at least two suspected SARS-CoV-2 infections. Using the first approach (constant hazard of reinfection), the emergence of the Omicron variant was associated with an increase in observed vs. projected reinfections, which is a signature of immune escape. Similar deviations from the null model were not observed after the introduction of the Beta or Delta variants. Using the second approach (time-varying hazards of primary infection and reinfection), the emergence of the Beta and Delta variants was associated with an increased hazard of primary infection without corresponding changes to the hazard of reinfection. In contrast, the introduction of the Omicron variant was association with a decreased hazard of primary infection and an increased hazard of reinfection; the hazard ratio for reinfection vs. primary infection in November 2021 was 2.39 (CI: 1.88–3.11). Sensitivity analyses demonstrated that vaccination may be partially responsible for the observed decline in the hazard of primary infection, but vaccine coverage during the study period was quite low.

    Study strengths

    This study analyzed a large, comprehensive national data set for all confirmed SARS-CoV-2 cases in South Africa. Results were consistent between both statistical approaches used.


    These analyses do not account for changes in testing practices, rates of detection, participant behavior, participant demographics (age, occupation, socioeconomic status), or healthcare access which may have occurred over the course of the pandemic. Results from rapid antigen tests may be underreported despite mandatory reporting requirements, so the study may underestimate rates of both primary infection and reinfection. Civil unrest in July 2021 in Gauteng and KwaZulu-Natal provinces may have also led to underreporting of test results and underestimation of infections during this period. Reinfection was not confirmed by sequencing and did not require negative test results between primary infection and reinfection. Symptom severity in primary infection vs. reinfection was not assessed because these data were not collected. While vaccine coverage in South Africa was low during the study period, vaccination may have impacted hazards of both primary infection and reinfection. The vaccination status of individual study participants was unknown.

    Value added

    This study demonstrated early population-level evidence of an increased risk of SARS-CoV-2 reinfection immediately following the emergence of the Omicron variant in South Africa.

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  2. SciScore for 10.1101/2021.11.11.21266068: (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

    Software and Algorithms
    The reinfection hazard coefficient (λ) and the inverse of the negative binomial dispersion parameter (κ) are fitted to the data using a Metropolis-Hastings Monte Carlo Markov Chain (MCMC) estimation procedure implemented in the R Statistical Programming Language.
    R Statistical Programming
    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:
    Limitations of this study: The primary limitation of this study is that changes in testing practices, health-seeking behavior, or access to care have not been accounted for in these analyses. Estimates based on serological data from blood donors suggests substantial geographic variability in detection rates (14), which may contribute to the observed differences in reinfection patterns by province. Detection rates likely also vary through time and by other factors affecting access to testing, which may include occupation, age, and socioeconomic status. In particular, rapid antigen tests, which were introduced in South Africa in late 2020, may be under-reported despite mandatory reporting requirements. If under-reporting of antigen tests was substantial and time-varying it could influence our findings. However, comparing temporal trends in infection risk among those eligible for reinfection with the rest of the population, as in approach 2, mitigates against potential failure to detect a substantial increase in risk. Reinfections were not confirmed by sequencing or by requiring a negative test between putative infections. Nevertheless, the 90-day window period between consecutive positive tests reduces the possibility that suspected reinfections were predominantly the result of prolonged viral shedding. Furthermore, due to data limitations, we were unable to examine whether symptoms and severity in primary episodes correlate with protection against subsequent reinfection. Lastl...

    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.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

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