Natural Immunity After Covid-19 Recovery

This 30-week study of 12,219 health care workers found that no symptomatic infections occurred for the 10.2% of the workers who were antibody-positive at the start of the study. 89 PCR-confirmed symptomatic infections occurred in the other workers.

This 35-week study of ~43,000 antibody-positive people by Cornell Univ's Weill Cornell Medicine in Qatar found that "the risk of reinfection was estimated at 0.10%”, “Incidence rate of reinfection versus month of follow-up did not show any evidence of waning of immunity”, “Reinfections were less severe than primary infections”, and “Only one reinfection was severe, two were moderate, and none were critical or fatal.”

In this study by the Ministry of Health and Family Welfare in India, a subsample of previous Covid-19 sero-survey participants were selected for a telephone interview in July 2021. Of the 1170 participants who were available and had tested positive for the antibodies in the sero-survey, 3 were reinfected with Covid-19, including only one who was hospitalized and none needing oxygen support. Of the 1068 participants who were available and had tested negative in the sero-survey, 127 reported contracting the Covid-19 infection, including 30 who required hospitalization and 12 who required oxygen therapy.

This 5-month study of ~53,000 healthcare workers, by experts in the prevention of infectious diseases at the Cleveland Clinic, found that “not one of the 1359 previously infected subjects who remained unvaccinated”, and “almost zero” of the workers who had been vaccinated, tested positive for Covid during the study, “compared with a steady increase in cumulative incidence among previously uninfected subjects who remained unvaccinated.”

Infections and re-infections in this study were those who had a positive PCR test for SARS-CoV-2, rather than those who were known to have recovered from Covid.

Their conclusion is that "Individuals who have had SARS-CoV-2 infection are unlikely to benefit from COVID-19 vaccination [and vaccines can safely be prioritized for others]”.

In this study, the workforce of a clinical lab was given a PCR test daily. Median employee age was 29; 75th percentile was 39.9 years old. "Infection" and "reinfection" were defined as two positive PCR tests within a 30-day period. The 4313 unvaccinated employees who had no prior evidence of SARS-CoV-2 infection had an infection rate during May 8 - Dec 15, 2020 of 25.9 per 100 person-years. The 254 who became "infected" had a reinfection rate of 0 during the remainer of that period. The 739 employees who completed 2 doses of the Pfizer or Moderna vaccine during Dec 15, 2020 - July 1, 2021, had an infection rate of 1.6 per 100 person-years during the remainder of that period.

This 6-month study of 25,661 health care workers “in all regions of England” reports on findings during June 2020-Jan 11, 2021.

8,278 of the workers were defined as “previously infected” at the start of the study, either due to a positive antibody test (91.2%) or due to a positive PCR test (8.8%) prior to June 2020. The other workers all had a negative antibody test and no positive PCR or antibody test prior to June 2020.

Participants were given PCR tests every 2 weeks and antibody tests every 4 weeks during the study. “Reinfections” are defined as a positive Covid test more than 90 days after the previous positive PCR test or more than 4 weeks after the previous positive antibody test.

Of the 8,278 “previously infected” workers, 1.9% had a positive PCR test (classified as a “reinfection”) during the study, 50% of which were symptomatic. Note that it's possible that very few, or even none, of the 91% who previously recovered from Covid were in the "reinfected" or symptomatic group. Unfortunately, the paper doesn't report their reinfection results for the 91% who had a positive antibody test from previous Covid recovery at the start of the experiment.

For the other 17,383 workers:

1. 9.8% had a positive PCR test classified as a “primary infection” during the 6-month period. 80.3% of these primary infections were symptomatic. These workers were moved to the “previously infected” cohort 21 days after their positive PCR test.
   
   
2. 5% of the 17,383 workers who were not “previously infected” tested positive for the antibodies during the study but didn’t have a positive PCR result. These were not classified as primary infections in this interim report, but these workers were moved to the “previously infected” cohort.

The CDC and other well-established medical centers cite and/or paraphrase the key conclusion of this CDC study as the principal evidence for their advice that those who have recovered from Covid-19 should vaccinate. The conclusion stated in this article is that those who've "previously been infected" with Covid-19 and have not been vaccinated are 2.34x as likely as fully vaccinated individuals to be reinfected. However:

• Unlike the studies linked above, this article wasn’t submitted for independent peer-review.

  A rigorous independent peer review would

  1. request changes to address any ambiguities and other issues, such as those listed below, before publication and wide circulation, and
  2. ask the authors to explain why the results in this paper differ greatly from previously published peer-reviewed studies. Note that bullets below which point out overestimation of unvaccinated reinfection rates and underestimation of vaccinated reinfection rates in this study, provide some possible explanations.

  These are key reasons that independent peer review is so highly valued by authors and readers of the scientific literature. Instead, this study was published in the weekly CDC newsletter, MMWR, which uses a "rigorous multilevel clearance process before publication" "to ensure that the content of MMWR comports with CDC policy". As noted below the author list in the preprint of the Oxford Univ. study at the top of this page, "studies that have not been peer reviewed shouldn't be used to guide clinical practice."

• The article doesn't provide the data that was used to calculate the key 2.34 result, and also doesn't define how the 2.34 factor was calculated. It's highly unusual for a scientific paper to omit such important data and the explanation of how the results are calculated from the data. Without that information, it's not possible to assess the validity of the results or conclusions of the study. For comparison, each of the other studies summarized on this site provides the data and how the results are computed.


• The residents who were defined as "previously infected" in this study had a "positive NAAT or antigen test", rather than a confirmed case of Covid. The (rapid-result) antigen test as well as the PCR and other NAAT tests are significantly less reliable than the antibody test that was used to determine previous recovery from Covid in most of the studies on this site. Hence, each cohort in this study likely has a higher percentage of members who are classified incorrectly.


• Overestimation of reintection rate for the unvaccinated cohort:

  The study measures "reinfection" as simply a new positive PCR test during May-June 2021, rather than a confirmed new Covid infection. Moreover,

  • May and June 2021 was also a period of very low Covid infection rate in the United States - for example, the total weekly deaths in the U.S. during those months was at the baseline for pre-pandemic years,
  
  
  • a large fraction of unvaccinated individuals were required to take frequent (e.g., weekly) screening PCR tests during those months for employment, entertainment, travel and other activities, and
  
  
  • as shown in False Positive Results With SARS-CoV-2 RT-PCR Tests, the percentage of positive test results that are false positives is much higher when used for routine screening than when used to confirm a diagnosis. Per the example given in the paper, when individuals are screened for routine activities, and particularly during periods of relatively low overall Covid infection rate, it's reasonable to expect that less than 1% of the screening test cases actually have a Covid infection (i.e., most of those screened are able to work and travel most of the time). In that case, using CDC's standards for the test parameters, more than 2/3 of the positive screening test results are false positives!
  
  For these reasons, (1) it's likely that the screening tests dominated the PCR tests administered to the unvaccinated residents, (2) the unvaccinated reinfection rate measured in this study has an unknown overestimation due to false positive test results, and (3) that overestimation may well be greater than a factor of three. Since vaccinated individuals were generally exempt from the frequent screening tests for employment, entertainment venues and so forth, they were more often taking PCR tests for diagnostic purposes, which has a relatively small percentage of false positives (e.g. on the order of 15%). Hence, a very rough "best guess" correction in the 2.34 factor to remove the impact of the false positives would be to multiply by (0.33/0.85) which yields a corrected value of about 0.9. This is a very rough approximation that motivates the need for more complete data in this study.


• Underestimation of reinfection rate for the vaccinated cohort:

  As briefly acknowledged in the CDC report paragraph on limitations of the study, there is a further unknown underestimation of the reinfection rate that dispropotionately applies to the vaccinated cohort. In particular, “not reinfected” was defined as not having a positive test result during May-June 2021, which includes the case that no test was taken during that period.

  Because the vaccinated individuals were frequently, if not typically, exempt from required screening Covid tests for employment, entertainment and other activities, it's likely that this study detected a lower percentage of the mild and/or asymptomatic infections in the vaccinated individuals than in the unvaccinated individuals. Correcting for this bias in the measures used in the study would further reduce the estimated 2.34 factor. Unfortunately, this paper doesn't provide the data that is needed to quantify this underestimation.