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PreprintCited by 1,037SARS-CoV-2 and COVID-19 ResearchCOVID-19 epidemiological studiesCOVID-19 Clinical Research Studies

Increased risk of SARS-CoV-2 reinfection associated with emergence of Omicron in South Africa

Open access
Pulliam, Juliet R.C., van Schalkwyk, Cari, Govender, Nevashan, Gottberg, Anne von, Cohen, Cheryl, Groome, Michelle J., Dushoff, Jonathan, Mlisana, Koleka +1 more·2021·Science
DOI 10.1101/2021.11.11.21266068PMC PMC8995029
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Abstract

Summary: Introduction: Globally, there have been more than 404 million cases of SARS-CoV-2, with 5.8 million confirmed deaths, as of February 2022. South Africa has experienced four waves of SARS-CoV-2 transmission, with the second, third, and fourth waves being driven by the Beta, Delta, and Omicron variants, respectively. A key question with the emergence of new variants is the extent to which they are able to reinfect those who have had a prior natural infection. Rationale: We developed two approaches to monitor routine epidemiological surveillance data to examine whether SARS-CoV-2 reinfection risk has changed through time in South Africa, in the context of the emergence of the Beta (B.1.351), Delta (B.1.617.2), and Omicron (B.1.1.529) variants. We analyze line list data on positive tests for SARS-CoV-2 with specimen receipt dates between 04 March 2020 and 31 January 2022, collected through South Africa’s National Notifiable Medical Conditions Surveillance System. Individuals having sequential positive tests at least 90 days apart were considered to have suspected reinfections. Our routine monitoring of reinfection risk included comparison of reinfection rates to the expectation under a null model (approach 1) and estimation of the time-varying hazards of infection and reinfection throughout the epidemic (approach 2) based on model-based reconstruction of the susceptible populations eligible for primary and second infections. Results: 105,323 suspected reinfections were identified among 2,942,248 individuals with laboratory-confirmed SARS-CoV-2 who had a positive test result at least 90 days prior to 31 January 2022. The number of reinfections observed through the end of the third wave in September 2021 was consistent with the null model of no change in reinfection risk (approach 1). Although increases in the hazard of primary infection were observed following the introduction of both the Beta and Delta variants, no corresponding increase was observed in the reinfection hazard (approach 2). Contrary to expectation, the estimated hazard ratio for reinfection versus primary infection was lower during waves driven by the Beta and Delta variants than for the first wave (relative hazard ratio for wave 2 versus wave 1: 0.71 (CI 95 : 0.60–0.85); for wave 3 versus wave 1: 0.54 (CI 95 : 0.45–0.64)). In contrast, the recent spread of the Omicron variant has been associated with an increase in reinfection hazard coefficient. The estimated hazard ratio for reinfection versus primary infection versus wave 1 was 1.75 (CI 95 : 1.48–2.10) for the period of Omicron emergence (01 November 2021 to 30 November 2021) and 1.70 (CI 95 : 1.44–2.04) for wave 4 versus wave 1. Individuals with identified reinfections since 01 November 2021 had experienced primary infections in all three prior waves, and an increase in third infections has been detected since mid-November 2021. Many individuals experiencing third infections had second infections during the third (Delta) wave that ended in September 2021, strongly suggesting that these infections resulted from immune evasion rather than waning immunity. Conclusion: Population-level evidence suggests that the Omicron variant is associated with substantial ability to evade immunity from prior infection. In contrast, there is no population-wide epidemiological evidence of immune escape associated with the Beta or Delta variants. This finding has important implications for public health planning, particularly in countries like South Africa with high rates of immunity from prior infection. Further development of methods to track reinfection risk during pathogen emergence, including refinements to assess the impact of waning immunity, account for vaccine-derived protection, and monitor the risk of multiple reinfections will be an important tool for future pandemic preparedness.

AI snapshot

Written from the paper’s full text.

TL;DR

Using national SARS-CoV-2 surveillance data from South Africa, the authors found no population-level evidence of increased reinfection risk associated with Beta or Delta, but clear evidence of immune evasion by Omicron in previously infected individuals. The increase in reinfections began in November 2021 and was temporally consistent with Omicron’s emergence.

Key findings

  • No evidence of increased reinfection risk was associated with circulation of Beta (B.1.351) or Delta (B.1.617.2); in contrast, reinfections rose sharply with Omicron (B.1.1.529), with observed reinfections exceeding the 95% projection interval from the null model from early November 2021.
  • Among 105,323 individuals with at least two suspected infections, 1,778 had at least three suspected infections and 18 had four; 1,492 of those with multiple reinfections (83.9%) experienced their third infection after 31 October 2021.
  • During the fourth wave, the 7-day moving average of suspected second infections reached nearly 2,700, and all suspected reinfections reached approximately 2,750.
  • The mean ratio of reinfection hazard to primary infection hazard increased to 0.25 for 01 November 2021 to the beginning of the fourth wave and 0.27 during the fourth wave; in a generalized linear mixed model, the relative hazard ratio was 1.75 (CI95: 1.48–2.10) for Omicron emergence versus wave 1 and 1.70 (CI95: 1.44–2.04) for wave 4 versus wave 1.

Methods

  • The study used routinely collected National Institute for Communicable Diseases (NICD) line list data with specimen receipt dates from 04 March 2020 to 31 January 2022; a suspected reinfection was a positive SARS-CoV-2 test at least 90 days after the most recent positive test.
  • Two approaches were used: a catalytic null model assuming a constant reinfection hazard proportional to the 7-day moving average of detected infections, fitted through 28 February 2021 and projected forward; and a time-varying hazard reconstruction of susceptible groups, plus a Poisson generalized linear mixed model with log link to estimate relative hazard by wave.
  • Analyses were conducted in R version 4.0.5, with descriptive analysis of time between successive positive tests and of individuals with multiple suspected reinfections.

Limitations

  • The paper states that changes in testing practices, health-seeking behavior, or access to care were not accounted for; rapid antigen tests may be under-reported; civil unrest in July 2021 disrupted testing in Gauteng and KwaZulu-Natal and violated the model assumption that force of infection is proportional to positive tests; reinfections were not confirmed by sequencing or a negative test between episodes; vaccination status was unknown and coverage was low (22.5% fully vaccinated by 30 November 2021); and estimates of the extent of immune evasion should be treated with caution.
  • The paper also states that it aimed to detect changing trends rather than precisely estimate reinfection risk, and that undetected primary infections, undetected reinfections, and deaths not linked to test data could inflate the estimated denominator at risk and reduce apparent reinfection risk.
  • Evident from the text: the temporal-trend analyses considered only suspected second infections, while third and fourth infections were described descriptively; observation probabilities were assumed (for example, pobs = 0.1 and pobs2 = 0.5), and the authors note that absolute hazard values are sensitive to these assumptions.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1101/2021.11.11.21266068

Cites

25 of 25 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

0 of 21 cited sources checked · 0 supported · 0 flagged

  • Findingown data

    A similar pattern of deviation from the null model projection has been seen across all provinces.

    “A similar pattern has now been seen across all provinces (figs. S5 to S7).”
    Quote in the paperNot a substantial claim
    • The authors state this as an assumption: The reinfection hazard coefficient is constant through time in the null model.
    • The authors state this as an assumption: The reinfection hazard is proportional to the 7-day moving average of the total number of diagnosed infections (primary infections and reinfections).
  • Findingown data

    The estimated mean ratio of reinfection hazard to primary infection hazard decreased from 0.15 in wave 1 to 0.12 in wave 2 and 0.09 in wave 3.

    “The estimated mean ratio of reinfection hazard to primary infection hazard decreased slightly from 0.15 in wave 1 to 0.12 in wave 2 and 0.09 in wave 3.”
    Quote in the paperNot a substantial claim
    • The authors state this as an assumption: Observation probabilities for primary infections and reinfections are assumed for the hazard estimates.
  • Findingown data

    The estimated hazard coefficient for reinfection remained relatively constant through the end of the third wave, with the exception of an initial spike in mid-2020.

    “The estimated hazard coefficient for reinfection, in contrast, remained relatively constant throughout this period, with the exception of an initial spike in mid-2020 (Fig. 5).”
    Quote in the paperNot a substantial claim
    • The authors state this as an assumption: Observation probabilities for primary infections and reinfections are assumed for the hazard estimates.
  • Findingown data

    Almost all suspected third infections occurred after 31 October 2021, during the period of Omicron circulation.

    “Almost all suspected third infections occurred after 31 October 2021, i.e., during the period of Omicron circulation.”
    Quote in the paperSubstantial claim
  • Findingreasoning

    The estimated hazard coefficient for primary infection increased steadily through the end of the third wave.

    “the estimated hazard coefficient for primary infection increased steadily through the end of the third wave”
    Quote in the paperNot a substantial claim
    • The authors state this as an assumption: Observation probabilities for primary infections and reinfections are assumed for the hazard estimates.
  • May combine two claims. 25
  • Classified as probably not a substantial claim. 16

  • May combine two claims.

    Findingown data

    No suspected reinfections were detected until 23 June 2020, after which the number of suspected reinfections increased gradually.

    “No suspected reinfections were detected until 23 June 2020, after which the number of suspected reinfections increased gradually.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    During the fourth wave, the 7-day moving average of suspected second infections reached nearly 2,700 and the 7-day moving average of all suspected reinfections reached approximately 2,750.

    “During the fourth wave, the 7-day moving average of suspected second infections reached nearly 2,700 and the 7-day moving average of all suspected reinfections (including second, third, and fourth infections) reached approximately 2,750.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    In a generalized linear mixed model based on the reconstructed data set, the relative hazard ratio for wave 2 versus wave 1 was 0.71 (CI95: 0.60-0.85) and for wave 3 versus wave 1 was 0.54 (CI95: 0.45-0.64).

    “In this analysis, the relative hazard ratio for wave 2 versus wave 1 was 0.71 (CI95: 0.60–0.85) and for wave 3 versus wave 1 was 0.54 (CI95: 0.45–0.64).”
    Quote in the paperSubstantial claim
    • The authors state this as an assumption: Observation probabilities for primary infections and reinfections are assumed for the hazard estimates.

  • May combine two claims.

    Findingown data

    In NICD line list data with specimen receipt dates between 04 March 2020 and 31 January 2022, 105,323 individuals had at least two suspected infections, 1,778 had at least three suspected infections, and 18 had four suspected infections.

    “we identified 105,323 individuals with at least two suspected infections, 1,778 individuals with at least three suspected infections, and 18 individuals with four suspected infections.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    From early November 2021, the 7-day moving average of observed reinfections reached the upper bound of the null model projection interval, with many individual daily numbers falling well above it, both nationally and in Gauteng.

    “From early November 2021, however, the 7-day moving average of observed reinfections reached the upper bound of the projection interval, with many individual daily numbers falling well above the projection interval, both nationally and in Gauteng (Fig. 4).”
    Quote in the paperSubstantial claim
    • The authors state this as an assumption: The reinfection hazard coefficient is constant through time in the null model.
    • The authors state this as an assumption: The reinfection hazard is proportional to the 7-day moving average of the total number of diagnosed infections (primary infections and reinfections).

  • May combine two claims.

    Findingown data

    Although there is substantial uncertainty in the estimated hazard coefficient for primary infection, it appeared to decrease from early October 2021, with a simultaneous increase in the estimated reinfection hazard coefficient.

    “Although there is substantial uncertainty in the estimated hazard coefficient for primary infection, it appeared to decrease from early October 2021, with a simultaneous increase in the estimated reinfection hazard coefficient (Fig. 5).”
    Quote in the paperSubstantial claim
    • The authors state this as an assumption: Observation probabilities for primary infections and reinfections are assumed for the hazard estimates.

  • May combine two claims.

    Findingown data

    The 7-day moving average of suspected second infections reached a peak of approximately 160 during the second epidemic wave and 350 during the third wave.

    “The 7-day moving average of suspected second infections reached a peak of approximately 160 during the second epidemic wave and 350 during the third wave (Fig. 1).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    The mean ratio of reinfection hazard to primary infection hazard increased to 0.25 for the period from 01 November 2021 to the beginning of the fourth wave, and to 0.27 during the fourth wave.

    “with the mean ratio of reinfection hazard to primary infection hazard for the period from 01 November 2021 to the beginning of the fourth wave increasing to 0.25, and a mean ratio during the fourth wave of 0.27.”
    Quote in the paperSubstantial claim
    • The authors state this as an assumption: Observation probabilities for primary infections and reinfections are assumed for the hazard estimates.

  • May combine two claims.

    Findingown data

    The population at risk of reinfection has risen monotonically since the beginning of the epidemic, with relatively rapid increases associated with each wave, delayed by 90 days because of the reinfection definition.

    “The population at risk of reinfection has risen monotonically since the beginning of the epidemic, with relatively rapid increases associated with each wave (delayed by 90 days because of our definition of reinfection; Fig. 1B).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    In November 2021, the number of daily new reinfections spiked and exceeded the 95% projection interval from the null model, accompanied by a notable increase in the hazard ratio for reinfection versus primary infection.

    “In contrast, in November 2021, the number of daily new reinfections spiked and exceeded the 95% projection interval from the null model, accompanied by a notable increase in the hazard ratio for reinfection versus primary infection.”
    Quote in the paperSubstantial claim
    • The authors state this as an assumption: The reinfection hazard coefficient is constant through time in the null model.
    • The authors state this as an assumption: The reinfection hazard is proportional to the 7-day moving average of the total number of diagnosed infections (primary infections and reinfections).

  • May combine two claims.

    Findingown data

    In the generalized linear mixed model, the relative hazard ratio for the period of Omicron emergence (01 November 2021 to the start of the fourth wave) versus wave 1 was 1.75 (CI95: 1.48-2.10), and for wave 4 versus wave 1 was 1.70 (CI95: 1.44-2.04).

    “The relative hazard ratio for the period of Omicron emergence (01 November 2021 to the start of the fourth wave) versus wave 1 was 1.75 (CI95: 1.48–2.10), and for wave 4 versus wave 1 was 1.70 (CI95: 1.44–2.04).”
    Quote in the paperSubstantial claim
    • The authors state this as an assumption: Observation probabilities for primary infections and reinfections are assumed for the hazard estimates.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    Focal estimates from the two models (day as random effect and day as fixed effect) were indistinguishable.

    “As focal estimates from the two models were indistinguishable, we present only the results based on the random effect assumption.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingown data

    Of the 18,585 cases reported on 23 November, 93% had a specimen receipt date before 01 November 2021, and 6% had specimen receipt dates on or after 21 November 2021.

    “We note that, of the 18,585 cases reported on 23 November, 93% had a specimen receipt date before 01 November 2021, and 6% had specimen receipt dates on or after 21 November 2021.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationreasoning

    The increase in the primary infection hazard through the end of the third wave is expected under a combination of relaxing restrictions, behavioral fatigue, and introduction of Beta and Delta variants with increased transmissibility.

    “as expected under a combination of relaxing of restrictions, behavioral fatigue, and introduction of variants with increased transmissibility (Beta and Delta).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationown data

    There is clear population-level evidence of immune evasion by the Omicron variant in previously infected individuals in South Africa, and Omicron's selection advantage is at least partially driven by an increased ability to infect previously infected individuals.

    “we find clear, population-level evidence to suggest immune evasion by the Omicron (B.1.1.529) variant in previously infected individuals in South Africa.”
    • Also stated in: § Discussion and limitations · hedged
      “The timing of these changes strongly suggests that they were driven by the emergence of the Omicron variant.”
    • Also stated in: § Conclusion · hedged
      “We find evidence of a substantial increase in the risk of reinfection that is temporally consistent with the timing of the emergence of the Omicron variant in South Africa, suggesting that Omicron’s selection advantage is at least partially driven by an increased ability to infect previously infected individuals.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Study design and conductown data

    The absolute values of the hazard coefficients and hazard ratio are sensitive to assumed observation probabilities for primary infections and reinfections, but the temporal trends are robust.

    “The absolute values of the hazard coefficients and hazard ratio are sensitive to assumed observation probabilities for primary infections and reinfections; however, the temporal trends are robust (fig. S8).”
    Quote in the paperSubstantial claim
    • The authors state this as an assumption: Observation probabilities for primary infections and reinfections are assumed for the hazard estimates.

  • May combine two claims.

    Interpretationown data

    The observed deviation from the null model projection is a signature of immune evasion, and its timing suggests it is associated with the emergence of the Omicron variant.

    “This observed deviation from the projection under the null model is a signature of immune evasion, and the timing of this deviation suggests it is associated with the emergence of the Omicron variant.”
    Quote in the paperSubstantial claim
    • The authors state this as an assumption: The reinfection hazard coefficient is constant through time in the null model.
    • The authors state this as an assumption: The reinfection hazard is proportional to the 7-day moving average of the total number of diagnosed infections (primary infections and reinfections).

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    Estimates based on serological data from blood donors suggest substantial geographic variability in detection rates, which may contribute to observed differences in reinfection patterns by province.

    “Estimates based on serological data from blood donors suggest substantial geographic variability in detection rates ( 22 ), which may contribute to the observed differences in reinfection patterns by province (fig. S1).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [22] source

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Interpretationreasoning

    The decrease in the relative hazard of reinfection versus primary infection through September 2021 is expected if the risk of primary infection increased without a corresponding increase in reinfection risk.

    “as would be expected if the risk of primary infection increased without a corresponding increase in reinfection risk.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation

    A preliminary analysis of reinfection trends in England suggested that the Delta variant may have a higher risk of reinfection compared to the Alpha variant, but this analysis did not take into account the temporal trend in the population at risk for reinfection, which may have biased the findings.

    “A preliminary analysis of reinfection trends in England suggested that the Delta variant may have a higher risk of reinfection compared to the Alpha variant ( 20 ); however, this analysis did not take into account the temporal trend in the population at risk for reinfection, which may have biased the findings.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [20] source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductreasoning

    Rapid antigen tests may be under-reported despite mandatory reporting requirements; although adjustments for late reporting were incorporated, time-varying under-reporting could still influence the findings.

    “In particular, rapid antigen tests, which were introduced in South Africa in late 2020, may be under-reported despite mandatory reporting requirements. Although we have incorporated adjustments that account for late reporting of antigen tests, if under-reporting of antigen tests was substantial and time-varying it could still influence our findings.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Study design and conductown data

    The study analyzed a large routine national data set comprising all confirmed cases in South Africa, allowing a comprehensive analysis of suspected reinfections in the country.

    “First, we analyzed a large routine national data set comprising all confirmed cases in the country, allowing a comprehensive analysis of suspected reinfections in the country.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    Both the Beta and Delta variants are associated with decreased neutralization by some anti-RBD and anti-NTD monoclonal antibodies, though each remains responsive to at least one anti-RBD.

    “Both the Beta and Delta variants are associated with decreased neutralization by some anti-receptor binding-domain (anti-RBD) and anti-N-terminal domain (anti-NTD) monoclonal antibodies though both Beta and Delta each remain responsive to at least one anti-RBD ( 8 , 9 , 21 ).”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites [8] source

      Not checked in the free run.

    • cites [9] D. Planas , D. Veyer , A. Baidaliuk , I. Staropoli , F. Guivel-Benhassine , M. M. Rajah , C. Planchais , F. Porrot , N. Robillard , J. Puech , M. Prot , F. Gallais , P. Gantner , A. Velay , J. Le Guen , N. Kassis-Chikhani , D. Edriss , L. Belec , A. Seve , L. Courtellemont , H. Péré , L. Hocqueloux , S. Fafi-Kremer , T. Prazuck , H. Mouquet , T. Bruel , E. Simon-Lorière , F. A. Rey , O. Schwartz , Reduced sensitivity of SARS-CoV-2 variant Delta to antibody neutralization. Nature, 1–7 (2021). source

      Not checked in the free run.

    • cites [21] 2021, Antibody Responses in Seropositive Persons after a Single Dose of SARS-CoV-2 mRNA Vaccine, N Engl J Med source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Beta and Delta are relatively poorly neutralized by convalescent sera obtained from unvaccinated individuals infected with non-VOC virus.

    “In addition, Beta and Delta are relatively poorly neutralized by convalescent sera obtained from unvaccinated individuals infected with non-VOC virus ( 7 – 9 , 21 ).”
    Quote in the paperNot a substantial claim0 of 4 sources checked
    • cites [7] 2021, Escape of SARS-CoV-2 501Y.V2 from neutralization by convalescent plasma, Nature source

      Not checked in the free run.

    • cites [8] source

      Not checked in the free run.

    • cites [9] D. Planas , D. Veyer , A. Baidaliuk , I. Staropoli , F. Guivel-Benhassine , M. M. Rajah , C. Planchais , F. Porrot , N. Robillard , J. Puech , M. Prot , F. Gallais , P. Gantner , A. Velay , J. Le Guen , N. Kassis-Chikhani , D. Edriss , L. Belec , A. Seve , L. Courtellemont , H. Péré , L. Hocqueloux , S. Fafi-Kremer , T. Prazuck , H. Mouquet , T. Bruel , E. Simon-Lorière , F. A. Rey , O. Schwartz , Reduced sensitivity of SARS-CoV-2 variant Delta to antibody neutralization. Nature, 1–7 (2021). source

      Not checked in the free run.

    • cites [21] 2021, Antibody Responses in Seropositive Persons after a Single Dose of SARS-CoV-2 mRNA Vaccine, N Engl J Med source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Sera obtained from individuals after one and two doses of BNT162b2 or ChAdOx1 vaccines displayed lower neutralization of the Beta and Delta variants compared to non-VOC and Alpha variant.

    “Lastly sera obtained from individuals after both one and two doses of the BNT162b2 (Pfizer) or ChAdOx1 (AstraZeneca) vaccines displayed lower neutralization of the Beta and Delta variants when compared to non-VOC and Alpha variant ( 9 )”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [9] D. Planas , D. Veyer , A. Baidaliuk , I. Staropoli , F. Guivel-Benhassine , M. M. Rajah , C. Planchais , F. Porrot , N. Robillard , J. Puech , M. Prot , F. Gallais , P. Gantner , A. Velay , J. Le Guen , N. Kassis-Chikhani , D. Edriss , L. Belec , A. Seve , L. Courtellemont , H. Péré , L. Hocqueloux , S. Fafi-Kremer , T. Prazuck , H. Mouquet , T. Bruel , E. Simon-Lorière , F. A. Rey , O. Schwartz , Reduced sensitivity of SARS-CoV-2 variant Delta to antibody neutralization. Nature, 1–7 (2021). source

      Not checked in the free run.

  • May combine two claims.

    Interpretationreasoning

    The effect of misclassification during the period of Omicron's emergence would likely be small and would be expected to bias subsequent reinfection hazard estimates downwards.

    “The effect of this misclassification on the signal of immune escape during the period of Omicron’s emergence would likely be small and would be expected to bias subsequent reinfection hazard estimates downwards.”
    Quote in the paperNot a substantial claim
    • The authors state this as an assumption: The force of infection is proportional to the number of positive tests.

  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductown data

    The specimen receipt date was chosen as the reference point for analysis because it is complete within the data set; however, problems have been identified with accuracy of specimen receipt dates for tests associated with substantially delayed reporting from some laboratories.

    “The specimen receipt date was chosen as the reference point for analysis because it is complete within the data set; however, problems have been identified with accuracy of specimen receipt dates for tests associated with substantially delayed reporting from some laboratories.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Study design and conductnone given

    Reinfections were not confirmed by sequencing or by requiring a negative test between putative infections.

    “The other main limitation of this study is that reinfections were not confirmed by sequencing or by requiring a negative test between putative infections.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationreasoning

    The discrepancy between the population-level evidence presented here and expectations based on laboratory-based neutralization assays for Beta and Delta highlights the need to identify better correlates of immunity for assessing immune escape in vitro.

    “The discrepancy between the population-level evidence presented here and expectations based on laboratory-based neutralization assays for Beta and Delta highlights the need to identify better correlates of immunity for assessing immune escape in vitro.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductcitation

    Convergence of the MCMC chains was assessed using the Gelman-Rubin diagnostic.

    “Convergence was assessed using the Gelman-Rubin diagnostic ( 29 ).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [29]

      Not checked in the free run.

  • May combine two claims.

    Study design and conductnone given

    Civil unrest during July 2021 severely disrupted testing in Gauteng and KwaZulu-Natal; case data are unreliable during that period and the assumption that the force of infection is proportional to the number of positive tests was violated.

    “Civil unrest during July 2021 severely disrupted testing in Gauteng and KwaZulu-Natal, the two most populous provinces in the country. Case data are unreliable during the period of unrest and a key assumption of our models - that the force of infection is proportional to the number of positive tests - was violated during this period”
    Quote in the paperNot a substantial claim
    • The authors state this as an assumption: The force of infection is proportional to the number of positive tests.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    Uncertainty intervals around λ1t, λ2t, and their ratio were constructed taking into account both measurement noise and uncertainty in the observation parameters.

    “We constructed uncertainty intervals around λ1t , λ2t , and their ratio, taking into account both measurement noise and uncertainty in the observation parameters (see the supplementary materials for details).”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductown data

    For tests with equivalent entries for specimen receipt date and specimen report date that were more than 7 days after the sample collection date, the specimen receipt date was adjusted to be 1 day after the sample collection date, reflecting the median delay across all tests.

    “For these tests, which had equivalent entries for specimen receipt date and specimen report date that were more than 7 days after the sample collection date, the specimen receipt date was adjusted to be 1 day after the sample collection date, reflecting the median delay across all tests.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Study design and conductcitation

    All positive tests conducted in South Africa appear in the combined data set, regardless of the reason for testing or type of test (PCR or antigen detection), and include the large number of positive tests that were retrospectively added to the data set on 23 November 2021.

    “All positive tests conducted in South Africa appear in the combined data set, regardless of the reason for testing or type of test (PCR or antigen detection), and include the large number of positive tests that were retrospectively added to the data set on 23 November 2021 ( 28 ).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [28] source

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    A combination of deterministic (national identity number, names, dates of birth) and probabilistic linkage methods were utilized to identify repeated tests conducted on the same person.

    “A combination of deterministic (national identity number, names, dates of birth) and probabilistic linkage methods were utilized to identify repeated tests conducted on the same person.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    The vaccination status of individuals with suspected reinfections identified in this study was unknown.

    “The vaccination status of individuals with suspected reinfections identified in this study was unknown.”
    Quote in the paperNot a substantial claim
36 of 36

  • The authors state this as an assumption.

    The reinfection hazard coefficient is constant through time in the null model.

    “under the assumption of a constant reinfection hazard coefficient (i.e., a null model of no change in reinfection risk)”

  • The authors state this as an assumption.

    The reinfection hazard is proportional to the 7-day moving average of the total number of diagnosed infections (primary infections and reinfections).

    “The model assumes the reinfection hazard is proportional to the 7-day moving average of the total number of diagnosed infections (primary infections and reinfections).”

  • The authors state this as an assumption.

    The force of infection is proportional to the number of positive tests.

    “a key assumption of our models - that the force of infection is proportional to the number of positive tests - was violated during this period”

  • The authors state this as an assumption.

    Observation probabilities for primary infections and reinfections are assumed for the hazard estimates.

    “The absolute values of the hazard coefficients and hazard ratio are sensitive to assumed observation probabilities for primary infections and reinfections”

  • The authors state this as an assumption.

    The reinfection hazard experienced by previously diagnosed individuals is proportional to the incidence of detected infections.

    “First, we constructed a simple null model based on the assumption that the reinfection hazard experienced by previously diagnosed individuals is proportional to the incidence of detected infections and fit this model to the pattern of suspected second infections observed through 28 February 2021.”

  • The authors state this as an assumption.

    The reinfection hazard coefficient does not change through time.

    “The null model assumes no change in the reinfection hazard coefficient through time.”

  • The authors state this as an assumption.

    For a case testing positive on day t, the reinfection hazard is 0 for each day from t+1 to t+89 and λI^τ for each day τ≥t+90.

    “For a case testing positive on day t (by specimen receipt date), we assumed the reinfection hazard is 0 for each day from t+1 to t+89 and λI^τ for each day τ≥t+90 , where I^τ is the 7-day moving average of the detected case incidence (first infections and reinfections) for day τ .”

  • The authors state this as an assumption.

    The observed reinfection incidence data are negative binomially distributed with mean Dx.

    “The model was fitted to observed reinfection incidence through 28 February 2021 assuming data are negative binomially distributed with mean Dx .”

  • The authors state this as an assumption.

    Individuals whose first infection was missed experience the same infection hazard as individuals whose primary infection was diagnosed and who have not yet been reinfected.

    “These individuals are assumed to experience the same infection hazard as individuals whose primary infection was diagnosed and who have not yet been reinfected, estimated as h2t=X^t/pobs2S2t .”

  • The authors state this as an assumption.

    Individuals are not eligible for reinfection until at least 90 days after their primary infection.

    “Because individuals are not eligible for reinfection until at least 90 days after their primary infection, we set Ut=h2t=0 when t<90 .”

  • The authors state this as an assumption.

    The hazard of infection is proportional to the 7-day moving average of infection incidence.

    “If we assume that the hazard of infection is proportional to the 7-day moving average of infection incidence ( Yt^=P^t+U^t+Xt^/pobs2 ), we can then examine the infectiousness of the virus through time as λ1t=h1t/Yt^ and λ2t=h2t/Yt^ .”

  • The authors state this as an assumption.

    The probability of detection for primary infections (pobs) is 0.1 and for individuals with a previously identified infection (pobs2) is 0.5.

    “For this analysis, we assume pobs=0.1 and pobs2=0.5 , which falls within the plausible range of observation probabilities (fig. S8).”
12 of 12

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • The findings are consistent with emerging clinical data on the Omicron variant demonstrating higher rates of reinfection and vaccine breakthroughs.

    “These findings are consistent with emerging clinical data on the Omicron variant demonstrating higher rates of reinfection 11 and vaccine breakthroughs.”

    From Striking antibody evasion manifested by the Omicron variant of SARS-CoV-2 (2022) · cites this paper as [11]

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Eligibility sums include infections only 89 days old

    Minor

    The susceptibility sums include infections on day t−89, making those individuals eligible on day t after only 89 days. The stated rule requires at least 90 days before reinfection eligibility.

1 of 1

Cites

Flagged first, then by citations

Research works printed but not linked: 3

  1. 10.1016/j.cell.2021.06.020/attachment/10183911-f97e-4da5-ae05-227854f207f4/mmc1.pdf · DOI
  2. 10.1101/2021.11.11.21266068v1 · DOI
  3. Sahai H , Khurshid A. Statistics in Epidemiology: Methods, Techniques and Applications. 1st ed. CRC Press; 1995. 352 p.

Cited by

Sorted by citations

Related

Authors
Pulliam, J. R. C., van Schalkwyk, C., Govender, N., Gottberg, A. V., Cohen, C., Groome, M. J., Dushoff, J., Mlisana, K., & Moultrie, H.
Affiliations
  • Stellenbosch University (ZA)
  • National Health Laboratory Service (ZA)
Corresponding author
Pulliam, Juliet R.C.
ORCID
Venue
Science
Publisher
openRxiv
Published
2021-11-11
Volume
376
Issue
6593
Pages
eabn4947-eabn4947
ISSN
0036-8075 (ISSN-L)
DOI
10.1101/2021.11.11.21266068
PMC
PMC8995029
OpenAlex
W4220987557
Cited by
1,037
References
25
Citations by year
2026: 24 · 2025: 48 · 2024: 161 · 2023: 260 · 2022: 485 · 2021: 58 · 2013: 1
FWCI
116.60
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Science (publishedVersion, cc-by)
  • medRxiv (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Funders
  • Wellcome Trust (221003/Z/20/Z)
  • Department of Science and Innovation, South Africa
  • National Research Foundation
  • Foreign, Commonwealth and Development Office
Topics
  • Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
  • Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
  • Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
Keywords
SARS-CoV-2 reinfection, Omicron variant, immune evasion, Beta variant, Delta variant
MeSH terms
Reinfection, COVID-19, SARS-CoV-2, Humans, South Africa

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-10.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-10.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

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