Dataset Information

The Effect of Varying Interval Definitions on the Prevalence of SARS-CoV-2 Reinfections: A Retrospective Cross-Sectional Cohort Study.

ABSTRACT: We assessed the SARS-CoV-2 reinfection rate in a large patient cohort, and evaluated the effect of varying time intervals between two positive tests on assumed reinfection rates using viral load data. All positive SARS-CoV-2 samples collected between 1 March 2020 and 1 August 2021 from a laboratory in the region Kennemerland, the Netherlands, were included. The reinfection rate was analyzed using different time intervals between two positive tests varying between 2 and 16 weeks. SARS-CoV-2 PCR crossing point (Cp) values were used to estimate viral loads. In total, 679,513 samples were analyzed, of which 53,366 tests (7.9%) were SARS-CoV-2 positive. The number of reinfections varied between 260 (0.52%) for an interval of 2 weeks, 89 (0.19%) for 4 weeks, 52 (0.11%) for 8 weeks, and 37 (0.09%) for a minimum interval of 16 weeks between positive tests. The median Cp-value (IQR) in the second positive samples decreased when a longer interval was chosen, but stabilized from week 8 onwards. Although the calculated reinfection prevalence was relatively low (0.11% for the 8-week time interval), choosing a different minimum interval between two positive tests resulted in major differences in reinfection rates. As reinfection Cp-values stabilized after 8 weeks, we hypothesize this interval to best reflect novel infection rather than persistent shedding.

SUBMITTER: Euser SM

PROVIDER: S-EPMC8947046 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature

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The Effect of Varying Interval Definitions on the Prevalence of SARS-CoV-2 Reinfections: A Retrospective Cross-Sectional Cohort Study.

Euser Sjoerd M SM Weenink Tieme T Prins Jan M JM Haverkort Milly M Manders Irene I van Lelyveld Steven S Herpers Bjorn L BL Sinnige Jan J Kalpoe Jayant J Snijders Dominic D Cohen Stuart James J Slijkerman Megelink Fred F Kapteijns Erik E den Boer Jeroen J Wagemakers Alex A Souverein Dennis D

Diagnostics (Basel, Switzerland) 20220315 3

<h4>Background</h4>We assessed the SARS-CoV-2 reinfection rate in a large patient cohort, and evaluated the effect of varying time intervals between two positive tests on assumed reinfection rates using viral load data.<h4>Methods</h4>All positive SARS-CoV-2 samples collected between 1 March 2020 and 1 August 2021 from a laboratory in the region Kennemerland, the Netherlands, were included. The reinfection rate was analyzed using different time intervals between two positive tests varying betwee ...[more]

PMID: 35328272

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Project description:BACKGROUNDIncreased SARS-CoV-2 reinfection rates have been reported recently, with some locations basing reinfection on a second positive PCR test at least 90 days after initial infection. In this study, we used Johns Hopkins SARS-CoV-2 genomic surveillance data to evaluate the frequency of sequencing-validated, confirmed, and inferred reinfections between March 2020 and July 2022.METHODSPatients who had 2 or more positive SARS-CoV-2 tests in our system, with samples sequenced as a part of our surveillance efforts, were identified as the cohort for our study. SARS-CoV-2 genomes of patients' initial and later samples were compared.RESULTSA total of 755 patients (920 samples) had a positive test at least 90 days after the initial test, with a median time between tests of 377 days. Sequencing was attempted on 231 samples and was successful in 127. Rates of successful sequencing spiked during the Omicron surge; there was a higher median number of days from initial infection in these cases compared with those with failed sequences. A total of 122 (98%) patients showed evidence of reinfection; 45 of these patients had sequence-validated reinfection and 77 had inferred reinfections (later sequencing showed a clade that was not circulating when the patient was initially infected). Of the 45 patients with sequence-validated reinfections, 43 (96%) had reinfections that were caused by the Omicron variant, 41 (91%) were symptomatic, 32 (71%) were vaccinated prior to the second infection, 6 (13%) were immunosuppressed, and only 2 (4%) were hospitalized.CONCLUSIONSequence-validated reinfections increased with the Omicron surge but were generally associated with mild infections.FUNDINGFunding was provided by the Johns Hopkins Center of Excellence in Influenza Research and Surveillance (HHSN272201400007C), CDC (75D30121C11061), Johns Hopkins University President's Fund Research Response, Johns Hopkins Department of Pathology, and the Maryland Department of Health.

Project description:BackgroundGlobal cases of COVID-19 continue to rise, causing havoc to several economies. So far, Ghana has recorded 48,643 confirmed cases with 320 associated deaths. Although summaries of data are usually provided by the Ministry of Health, detailed epidemiological profile of cases are limited. This study sought to describe the socio-demographic features, pattern of COVID-19 spread and the viral load dynamics among subjects residing in northern, middle and part of the southern belt of Ghana.MethodsThis was a cross-sectional retrospective study that reviewed records of samples collected from February to July, 2020. Respiratory specimens such as sputum, deep-cough saliva and nasopharyngeal swabs were collected from suspected COVID-19 subjects in 12 regions of Ghana for laboratory analysis and confirmation by real-time reverse transcription polymerase chain reaction (RT-PCR).ResultsA total of 72,434 samples were collected during the review period, with majority of the sampled individuals being females (37,464; 51.9%). The prevalence of SARS-CoV-2 identified in the study population was 13.2% [95%CI: 12.9, 13.4). Males were mostly infected (4,897; 51.5%) compared to females. Individuals between the ages 21-30 years recorded the highest number of infections (3,144, 33.4%). Symptomatic subjects had higher viral loads (1479.7 copies/μl; IQR = 40.6-178919) than asymptomatic subjects (49.9; IQR = 5.5-3641.6). There was significant association between gender or age and infection with SARS-CoV-2 (p<0.05). Among all the suspected clinical presentations, anosmia was the strongest predictor of SARS-CoV-2 infection (Adj. OR (95%CI): 24.39 (20.18, 29.49). We observed an average reproductive number of 1.36 with a minimum of 1.28 and maximum of 1.43. The virus trajectory shows a gradual reduction of the virus reproductive number.ConclusionThis study has described the epidemiological profile of COVID-19 cases in northern, middle and part of the southern belt of Ghana, with males and younger individuals at greater risk of contracting the disease. Health professionals should be conscious of individuals presenting with anosmia since this was seen as the strongest predictor of virus infection.

Dataset Information

The Effect of Varying Interval Definitions on the Prevalence of SARS-CoV-2 Reinfections: A Retrospective Cross-Sectional Cohort Study.

Publications

The Effect of Varying Interval Definitions on the Prevalence of SARS-CoV-2 Reinfections: A Retrospective Cross-Sectional Cohort Study.

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