key: cord-0717835-ihr12wrk
authors: Qureshi, Adnan I; Baskett, William I; Huang, Wei; Lobanova, Iryna; Naqvi, S Hasan; Shyu, Chi-Ren
title: Re-infection with SARS-CoV-2 in Patients Undergoing Serial Laboratory Testing
date: 2021-04-25
journal: Clin Infect Dis
DOI: 10.1093/cid/ciab345
sha: e37b16fd441d94abec4029da1e2f773f2c585dc7
doc_id: 717835
cord_uid: ihr12wrk

BACKGROUND: A better understanding of re-infection after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has become one of the healthcare priorities in the current pandemic. We determined the rate of re-infection, associated factors and mortality during follow up in a cohort of patients with SARS-CoV-2 infection. METHODS: We analyzed 9,119 patients with SARS-CoV-2 infection who received serial tests in total of 62 healthcare facilities in United States between December 1, 2019 to November 13, 2020. Re-infection was defined by two positive tests separated by interval of greater than 90 days two after resolution of first infection was confirmed by two or more consecutive negative tests. We performed logistic regression analysis to identify demographic and clinical characteristics associated with re-infection. RESULTS: Re-infection was identified in 0.7% (n=63, 95% confidence interval [CI] 0.5%-0.9%) during follow up of 9,119 patients with SARS-CoV-2 infection. The mean period (±standard deviation [SD]) between two positive tests was 116 ± 21 days. A logistic regression analysis identified that asthma (odds ratio [OR] 1.9, 95% CI 1.1-3.2) and nicotine dependence/tobacco use (OR 2.7, 95% CI 1.6-4.5) were associated with re-infection. There was a significantly lower rate of pneumonia, heart failure, and acute kidney injury observed with re-infection compared with primary infection among the 63 patients with re-infection There were two deaths (3.2%) associated with re-infection. CONCLUSIONS: We identified a low rate of re-infection confirmed by laboratory tests in a large cohort of patients with SARS-CoV-2 infection. Although re-infection appeared to be milder than primary infection, there was associated mortality.

By October 2020, five cases of re-infection with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) had been reported from Hong Kong, Belgium, the Netherlands, Ecuador, and United States [1] [2] [3] [4] [5] when over 37 million SARS-CoV-2 infected persons had been reported worldwide. [6] A better understanding of re-infection became one of the priorities for Centers for Disease Control and Prevention to inform public health action. [7] Identification of characteristics and frequency of reinfection was considered crucial by the European Centre for Disease Prevention and Control [8] due to implications for duration of acquired immunity, The results of SARS-CoV-2 Immunity and Reinfection Evaluation (SIREN) [9] were made available in January 2021. Between 18 June and 09 November 2020, 44 reinfections (2 probable, 42 possible) were detected in the baseline positive cohort of 6,614 healthcare workers. The study investigators acknowledged that there is paucity of data regarding re-infection limiting our understanding of public health implications. A better understanding of the risk of re-infection is necessary from the public health perspective and may have implications for vaccination strategy.

We analyzed data from the Cerner de-identified Coronavirus Disease 2019 dataset. This is a subset of Cerner Real-World Data extracted from the electronic medical records of health care facilities which have a data use agreement with Cerner Corporation. [10, 11] Patients with a positive laboratory test for SARS-CoV-2 were identified based on Logical Observation Identifiers Names and Codes (LOINC®) 41458-1, 94309-2, 94500-6, 94533-7, 94534-5, and 94646-7. These codes denote

detection of SAR-CoV-2 ribonucleic acid in respiratory (nasopharyngeal swabs, bronchoalveolar lavage, sputum) and other specimens or detection of SARS-CoV-2 N gene or RdRp gene in respiratory secretions, all by nucleic acid amplification with probe detection. The Food and Drug Administration has only approved assays for detection of SARS-CoV-2 N gene or RdRp gene in respiratory secretions in United States.

The methodological aspects of the dataset are available in other publications. [12, 13] The Cerner Real-World Data-COVID-2020 Q3 version of the data included data from 62 contributing Cerner Real-World Data health systems in United States. The data is based on electronic medical records between December 1, 2019 to November 13, 2020. The dataset, as part of the de-identification procedure, does not provide an identifier for the medical institution of a patient's data or its precise location. Our analysis included patients with at least one COVID-19 related inpatient or emergency department (ED) encounter who tested positive for COVID-19, had at least one medical encounter on record prior to their first COVID-19 related encounter, and who received at least four reliable COVID-19 tests which were conclusive.

Re-infection was defined by two positive tests separated by interval of greater than 90 days two after resolution of first infection was confirmed by two or more consecutive negative tests consistent with definitions used in previous reports. [9, 14, 15 ] The associated medical diagnoses and outcomes were (E08, E09, E10, E11 and E13), atrial fibrillation (I48), hyperlipidemia (E78), stroke (I60, I61, I62.9, I63,   I65, I66), heart failure (I50), malignancy (Z85, C80 

A large proportion of patients in the dataset were excluded from the analysis due to lack of serial tests performed for detection of SARS-CoV-2. To better understand the selection bias, we compared patients' age, sex, race/ethnicity, cardiovascular risk factors, and medical complications between included and excluded patients.

We provided the rate of re-infection with 95% confidence interval (CI) without continuity correction. [16] We compared patients' age, sex, race/ethnicity, cardiovascular risk factors, medical complications, and discharge status (categorized into non-routine discharge, or expired in medical facility) for patients in strata based on presence or absence of re-infection during follow up among patients with SARS-CoV-2 infection. We used the χ 2 test for categorical data and analysis of variance (ANOVA) test for continuous variables. We performed logistic regression analysis including all patients with SARS-CoV-2 infection to identify the associations between various demographic and clinical characteristics and odds of reinfection. Stepwise feature selection was used to select variables. All the hypothesis tests were 2 sided, with P<0.05 considered statistically significant, and all the analyses were done using R (version 3.6.1).

We also provided estimates for rates of re-infection defined using different cut-off periods for time interval between first and second positive tests (>45 days, >60 days, >75 days, >90 days, and >105 days).

A total of 9,119 patients with SARS-CoV-2 infection met our inclusion criteria among 110,754 patients with positive SARS-CoV-2 tests in the data. Compared with patients who were excluded, patients who were included in the analysis were more likely to aged>65 years, African-American or Hispanic, and have higher proportion of those with hypertension, diabetes mellitus, atrial fibrillation, nicotine dependence, hyperlipidemia, prior stroke, COPD, asthma, and chronic kidney disease. Included patients also had a higher proportion of patients with new stroke, heart failure, cardiac arrest, pneumonia, respiratory failure,

and acute kidney injury. The proportion of patients who required intubation/mechanical ventilation was higher in included patients.

Re-infection was identified in 0.7% (n=63, 95% CI 0.5%-0.9%) of the patients (see Table 1 ). The mean period (± standard deviation [SD]) between two positive tests was 116 ± 21 days. There were no significant differences based on age or sex among patients with and without re-infection. The proportion of patients categorized under other race/ethnicity was higher in those with re-infection. The proportion of patients with nicotine dependence/tobacco use, asthma, and COPD were higher in patients with reinfection. The proportion of patients with non-routine discharge were similar between re-infection and without re-infection groups. In the logistic regression analysis, patients with asthma (odds ratio [OR] 1.9, 95% CI 1.1-3.2), and nicotine dependence/tobacco use (OR 2.7, 95% CI 1.6-4.5) were at higher risk for re-infection. Furthermore, compared with White patients, the patients categorized as other race/ethnicity (OR 2.3, 95% CI 1.2-4.5) were associated with higher risk for re-infection.

There were two deaths (3%) associated with re-infection. There was a significantly lower rate of pneumonia, heart failure, and acute kidney injury observed with re-infection compared with primary infection among the 63 patients with re-infection (see Table 2 ). There was a trend towards lower rates of respiratory failure and hepatic failure during re-infection. Intubation/mechanical ventilation in two (3%) patients required during primary infection but in none of the patients during re-infection.

The rates of re-infection ranged from 0.4% to 2.2% using different cut-offs for time intervals between first and second positive tests for definition with decrease in rates observed with increase in time intervals (see Figure 1 ). European Centre for Disease Prevention and Control [8] recognizes that longer time-interval between two RT-PCR positive samples increases the likelihood of re-infection as it relates to waning immunity and lower antibody levels. Re-detection of the primary episode is more likely the cause than a true reinfection with shorter period of time interval between two RT-PCR positive sample. We acknowledge that re-infection is possible within a time interval <90 days and therefore have also presented the rates based on various time intervals used to define re-infection. The rates of re-infection ranged from 0.4% to 2.2% in our analysis using different cut-offs for time intervals between first and second positive tests (see Figure 1 ). Another analysis of national surveillance database in Qatar reported a re-infection rate of 0.01% (95% CI: 0.01-0.02%) [18] when re-infection was defined by ≥45 days interval between two RT-PCR positive tests. The longitudinal study of healthcare workers in Oxford University Hospitals [19] reported a rate of 0.2% when using a time interval of ≥60 days between detection of serum antibodies against SARS-CoV-2 and subsequent positive RT-PCR test to define re-infection and exclude patients with persistent viral shedding from initial infection. One of the 3 patients with re-infection had two positive RT-PCR tests separated by an interval of 190 days (5 negative tests in the interim period).

In our analysis, age of the patient at the time of initial infection was not associated with re-infection either in the univariate or stepwise logistic regression analysis. We compared occurrence of medical events reflective of multi-organ involvement or requirement of mechanical ventilation during initial SARS-CoV-2 infection between patients with or without re-infection (see Table 1 ) but did not identify any differences in surrogate markers of severity of infection between the two groups. Re-infection was associated with pre-existing asthma and nicotine dependence/tobacco use. Patients with asthma are at higher risk for respiratory viral infections [20] and an increased risk of H1N1 infection has been reported in children with asthma. [21] Cigarette smokers are also at high risk for viral infection including SARS-CoV-2.because of deficits in muco-ciliary clearance mechanisms and cell-mediated immunity in the lung alveolus. [22] Additional evidence of immunosuppression such as depressed migration and chemotaxis of leukocytes, reduced natural killer cell activity, and lower levels of circulating serum immunoglobulin levels have been reported in cigarette smokers. [22] Cessation of cigarette smoking can result in recovery of immune function within 6-12 weeks. [23, 24] .

In our analysis, re-infection appeared to have less severe manifestations than the primary infection with lower rates of pneumonia, heart failure, and acute kidney injury. However, there were two deaths (3.2%) associated with re-infection. There seems to be some controversy whether re-infection is a less severe or more severe disease compared with the primary infection. [25] [26] [27] [28] Therefore, persistent immunity may result in less severe manifestations of infection. However, antibodydependent enhancement may facilitate viral entry during re-infection or exaggerated immune response may result in more severe manifestations. [30] We have to consider that survival in patients with SARS-CoV-2 infection has been improving over time [31] and appearance of less severe manifestations during re-infection may be partly due to more effective medical management in subsequent months. There is also another bias with patients with mild manifestations during initial SARS-CoV-2 infection being more likely to be more exposed to re-infection due to higher survival and shorter time in isolation.

Re-infection was initially attributed to heterogeneity in response and decline in immunity over time among patients with SARS-CoV-2 infection. Long et al. [32] and Muecksch et al. [33] reported a decline in IgG antibodies and neutralizing antibody against SARS-CoV-2 spike (S) or nucleocapsid (N) within the first 3 months after infection. However, Wajnberg et al. [34] and Ogega et al. [35] reported persistent neutralizing antibodies and memory B cells capable of providing humoral immunity against SARS-CoV-2 for a longer period of time. Persistent T cells specific to SARS-CoV-2 provide immunity even in absence of antibodies. [36] However, patients who have antibodies to SARS-CoV-2 are not completely immune to re-infection during follow up. [9, 37] Boyton and Altmann [38] pointed out that the exact immunological correlates of protection from SARS-CoV-2 infection are not well understood but the quality, quantity, and durability of protective immunity elicited by natural infection with SARS-CoV-2 are poor relative to the much higher levels of virus-neutralizing antibodies and T cells induced by the vaccines [39] European Centre for Disease Prevention and Control [8] also recommended the need for further studies to elaborate the role of cellular immunity in the prevention of re-infection with SARS-

Mutations in the SARS-CoV-2 receptor-binding domain (RBD) of the viral spike protein that escape antibody binding are also implicated in re-infection. [40] Our study is based on the Cerner Real-World data which lacks the design strengths such as patient selection and systematic ascertainment methodologies seen in prospective studies. There is heterogeneity in timing, assays used, and indications for repeat testing. Mandatory serial testing for all patients was not possible or justified. A total of 9,119 patients with SARS-CoV-2 infection met our inclusion criteria of serial testing among 110,754 patients with positive SARS-CoV-2 tests. We noted that patients who were included based on performance of serial testing appeared to have more medical co-morbidities and severe disease manifestations compared with those who were excluded. Thus, there is perhaps an underrepresentation of patients with minimal co-morbidities and mild disease manifestations in our analysis. However, such data is more representative of broader population and provides large unselected cohorts. We acknowledge that a positive test after being considered infection free based on serial negative laboratory test may be due to other reasons in addition to re-infection. There may be a relapse or recrudescent of infection with the "first" SARS-CoV-2 inoculum or prolonged shedding of remnant ribonucleic acid (RNA) fragments of the "first" SARS-CoV-2 infection[41] confounded by laboratory errors, or technical limits of RT-PCR assays. The mean time between initial positive RT-PCR testing and subsequent negative change was 6.9 days with a range of 4-15 days and a median of 7 days in a previous study [42] suggesting that it is uncommon to have to have persistent infection beyond 15 days and persistent positive status by RT-PCR for up to 80 days is perhaps the longest period reported in rare cases.[43, 44] Therefore, using a time interval of greater than 90 days should eliminate those with persistence of primary infection. RT-PCR tests have an estimated false negative rate of 13% (95% CI 9 to 19%) for detection of SARS-CoV-2. [45, 46] Therefore, the possibility that some patients classified as reinfection were those with persistent viral shedding and interim RT-PCR test was falsely negative. [47] However, the rate of false negative tests decreases if two false negative tests are used like in ours and other studies.[1-5, 48] We did not have access to any genomic characterization of SARS-CoV-2 detected in re-infected patients and are unable to comment upon the role of phylogenetically distinct variants of SARS-CoV-2 in re-infection. We could not identify the role of any specific therapeutic interventions used during primary infection in preventing re-infection due to lack of data and small number of re-infections.

We were also unable to identify immunodeficiency by laboratory tests or use of immunosuppressive medication which precluded a more detailed analysis.

The exact prevalence of re-infection may be confounded by the selection criteria of our analysis which only included those with serial laboratory tests. This approach eliminates those patients who may have undetected SARS-CoV-2 re-infection because follow up laboratory tests were not performed. We also included those patients who had at least one qualifying ED or inpatient encounter which was considered related to SARS-CoV-2 infection. ED and inpatient encounters are more reliable due to completeness of data recorded in electronic medical records [13] but may exclude some patients with mild disease who were not seen in ED or hospitalized. We acknowledge the effect of variability in hospitalization criteria over time and between institutions on our analysis is not known. We also cannot exclude the possibility that in a certain proportion of patients, some tests may be performed in centers not included in the Cerner Real-World data and thus not available for analysis. The possibility of such occurrence is very low as all included patients had serial tests performed within centers in Cerner Real-World data. The vulnerability for re-infection may be underestimated due to implementation of social distancing policies (March 2020) and universal face mask use (July 2020) recommended by Centers for Disease Control and Prevention. [49, 50] Re-infection may be additionally reduced due to behavioral changes among SARS-CoV-2 infection survivors[51] which may result in high compliance with social distancing measures [52] thus reducing the chance of a re-infection.

Our observations strongly suggest that survivors from SARS-CoV-2 infection must not relax compliance with proven interventions in prevention of SARS-CoV-2 transmission such as social distancing [53] and universal face mask use. [50] Our study supports the position taken by European Centre for Disease Prevention and Control [8] and Centers for Disease Control and Prevention[54] that individuals that have been infected once with SARS-CoV-2 are not always immune and infection prevention/control and contact principles should be followed even after infection. Due to concerns for re-infection, the Centers for Disease Control and Prevention[54] currently recommends vaccination for patients who had SARS-CoV-2 infection after 90 days but acknowledges the limited data is available to support the recommendation.

FUNDING This work was supported by the National Institutes of Health (grant number: 5T32LM012410) to WIB.

The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

No potential conflict of interest relevant to this article was reported. 

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