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Reinfection Rates among Patients who Previously Tested Positive for COVID-19: a Retrospective Cohort Study

Our take —

The study sought to examine the rate of reinfection following initial infection using a retrospective cohort in Ohio and Florida from March 20, 2020 to February 24, 2021. The study found that, of 150,325 people tested during this period in the health system before August 30, 2020, 1,278 patients who initially tested positive later were tested again, 63 (4.9%) showed evidence of reinfection. Protection from reinfection due to prior infection was estimated at 81.8%. The study’s primary limitation was the use of infection occurrence within 6-month time blocks to infer re-infection, rather than having an initial positive test, a subsequent negative test, and a later positive test to determine that individuals cleared the infection. Therefore, the study may have incorrectly estimated the true reinfection rate. It should also be noted that there may have been unmeasured underlying behavioral differences in those who were and were not previously infected however, the contribution of such differences to risk of reinfection was not assessed.

Study design

Retrospective Cohort

Study population and setting

The study investigated the risk of re-infection among individuals previously infected with SARS-CoV-2. Patients within a single health system in Ohio and Florida who were tested for COVID-19 between March 12, 2020 and February 24, 2021 were included in the retrospective cohort, regardless of test results. Within individuals, positive SARS-CoV-2 tests prior to August 30, 2020 were considered an initial infection. Following this initial diagnosis, re-infection was defined as an individual’s second positive PCR test from September 1, 2020 onwards. Individuals who tested negative before August 30, 2020 and later positive from September 1 onwards were used as the comparison group to determine whether there were differences in the risk of infection in September onwards due to prior infection history. Reinfection was determined by the rate of second infection among all previously diagnosed patients tested 4 to 5 months after initial test, 6 to 7 months after, and 8 or more months after. Protection due to prior infection was defined as (1 – the ratio of infection among initially positive vs. initially negative patients). Repeated tests within 90 days of an initial test were ignored. Patients who tested negative at their initial test and then later positive within 90 days were excluded from the analysis. Symptoms were recorded by the ordering provider at the time of test order. Sensitivity analyses included examining only symptomatic infections.

Summary of Main Findings

Overall, 612,611 tests were conducted among 386,336 people with an overall positivity rate of 9.9% during the study period. Before August 30, 38.9% (N=150,325) patients were tested and included in the analysis. Of these, 8,845 (5.9%) tested positive and 141,480 (94.1%) tested negative. After 90 days, 1,278 positive patients were retested and 63 were identified as possible reinfections (4.9%). Of these, 31 were symptomatic (49.2%). The average time to reinfection was 138.9 days (range: 90.2 to 294.9 days). Protection from reinfection due to prior infection was estimated at 81.8% (95% CI: 76.6 – 85.8%) and 84.5% against symptomatic infection (95% CI: 77.9 – 89.1%). Protection was lowest at 4 to 5 months and greatest at 8 months after initial infection.

Study Strengths

The study included a large number of patients, which allowed them to make inferences around reinfection, a rare outcome. They also had multiple tests on individuals, which allowed them to compare individuals testing positive vs. negative at baseline to examine whether there was a potentially protective benefits for initial infection. They were also able to examine symptomatic infection and asymptomatic infection rates, which provides important granularity into the severity of disease following first infection.

Limitations

The major limitation was that they inferred a probable reinfection due to temporality, however it was not possible to confirm a reinfection with a negative test between the initial positive and later positive test. While it is expected that infections would clear within 3 months, there are cases of long-haul COVID-19 that may continue to test positive due to the same initial infection. This may have overestimated the actual reinfection rate in their sample. Additionally, the study did not have access to consumer testing data, such as at pharmacies or ordered online, or tests from other health facilities. The study also did not conduct any genetic testing to estimate if the infections were new or reflect novel variants. The use of timing as the cutoff to determine reinfection may also reflect temporal trends in different risk behaviors (such as less socializing outdoors during the summer than during September and the winter), and it is unclear if this confounded any results. Additionally, any re-tests that occurred in August were also ignored, which may have decreased their sample size unnecessarily and potentially underestimated reinfections. Finally, there may be behavioral differences between those previously infected with SARS-CoV-2 and those not previously infected which are difficult to predict (some may assume immunity, others may take further pre-cautions following an infection) which may lead to differences in infection rates between those previously infected and uninfected, but may be partially due to behavioral differences rather than just biological effects.

Value added

This is one of the largest studies of reinfection to date, though the study may have biased estimates of reinfection risk.

This review was posted on: 5 April 2021