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ObjectivesThis study aims to estimate the prevalence and longevity of detectable SARS-CoV-2 antibodies as well as memory cells T and B after recovery. In addition, the prevalence of COVID-19 reinfection, and the preventive efficacy of previous infection with SARS-CoV-2 were investigated. Methods and analysesA synthesis of existing research was conducted. The Cochrane Library for COVID-19 resources, the China Academic Journals Full Text Database, PubMed, and Scopus as well as preprint servers were searched for studies conducted between 1 January 2020 to 1 April 2021. We included studies with the relevant outcomes of interest. All included studies were assessed for methodological quality and pooled estimates of relevant outcomes were obtained in a meta-analysis using a bias adjusted synthesis method. Proportions were synthesized with the Freeman-Tukey double arcsine transformation and binary outcomes using the odds ratio (OR). Heterogeneity between included studies was assessed using the I2 and Cochrans Q statistics and publication bias was assessed using Doi plots. ResultsFifty-four studies, from 18 countries, with around 12 000 000 individuals, followed up to 8 months after recovery were included. At 6-8 months after recovery, the prevalence of SARS-CoV-2 specific immunological memory remained high; IgG - 90.4% (95%CI 72.2-99.9, I2=89.0%, 5 studies), CD4+ - 91.7% (95%CI 78.2 - 97.1, one study), and memory B cells 80.6% (95%CI 65.0-90.2, one study) and the pooled prevalence of reinfection was 0.2% (95%CI 0.0 - 0.7, I2 = 98.8, 9 studies). Individuals previously infected with SARS-CoV-2 had an 81% reduction in odds of a reinfection (OR 0.19, 95% CI 0.1 - 0.3, I2 = 90.5%, 5 studies). ConclusionAround 90% of people previously infected with SARS-CoV-2 had evidence of immunological memory to SARS-CoV-2, which was sustained for at least 6-8 months after recovery, and had a low risk of reinfection. RegistrationPROSPERO: CRD42020201234 What is already known on this topicIndividuals who recover from COVID-19 may have immunity against future infection but the proportion who develop immunity is uncertain. Further, there is uncertainty about the proportion of individuals who get reinfected with COVID-19. What this study addsUsing data from 54 studies with follow up time up to 8 months after recovery, during the period February 2020-February 2021, we found that, post-COVID-19, up to 90% of individuals had antibodies and memory T and B cells against SARS-CoV-2. We also found a pooled prevalence of reinfection of 0.2%, and that infection conferred an 81% decrease in odds of reinfection with SARS-CoV-2, compared to unimmunized individuals without previous COVID-19. This review of 12 million individuals presents evidence that most individuals who recover from COVID-19 develop immunological memory to SARS-CoV-2, which was still detectable for up to 8 months. Further, reinfection after recovery from COVID-19 was rare during the first 8 months after recovery, with a prevalence below 1%, while prior infection confers protection with an odds ratio of 0.19 and a preventive efficacy of 80% at a baseline prevalence of 5% for COVID-19 in a community. Implications of all the available evidenceIndividuals with a history of COVID-19 infection have immunity against the disease for up to 8 months, although this period could be longer. These individuals could be prioritized last for COVID-19 vaccinations or considered for single dose vaccinations. StrengthsThis comprehensive review addresses key questions on prevalent immunological memory and risk of reinfection in individuals with prior confirmed COVID-19 using robust systematic review methods. LimitationsSome of the included studies which examined prevalent immunological memory were small studies which were affected by loss to follow up. The review did not examine evidence for immunity against the new divergent variants, which may be more likely to have immune evasion behaviour and may present a higher risk of reinfection. Lastly, the review did not examine the effect of the severity of COVID-19 on both immunological memory and the risk of reinfection.
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@#Objective Zero-events studies frequently occur in systematic reviews of adverse events, which consist of an important source of evidence. We aimed to examine how evidence of zero-events studies was utilized in the meta-analyses of systematic reviews of adverse events. Methods We conducted a survey of systematic reviews published in two periods: January 1, 2015 to January 1, 2020 and January 1, 2008, to April 25, 2011. Databases were searched for systematic reviews that conducted at least one meta-analysis of any healthcare intervention and used adverse events as the exclusive outcome. An adverse event was defined as any untoward medical occurrence in a patient or subject in healthcare practice. We summarized the frequency of occurrence of zero-events studies in eligible systematic reviews and how these studies were dealt with in the meta-analyses of these systematic reviews. Results We included 640 eligible systematic reviews. There were 406 (63.45%) systematic reviews involving zero-events studies in their meta-analyses, among which 389 (95.11%) involved single-arm-zero-events studies and 223 (54.93%) involved double-arm-zero-events studies. The majority (98.71%) of these systematic reviews incorporated single-arm-zero-events studies into the meta-analyses. On the other hand, the majority (76.23%) of them excluded double-arm-zero-events studies from the meta-analyses, of which the majority (87.06%) did not discuss the potential impact of excluding such studies. Systematic reviews published at present (2015-2020) tended to incorporate zero-events studies in meta-analyses than those published in the past (2008-2011), but the difference was not significant [proportion difference=–0.09, 95%CI (–0.21, 0.03), P=0.12]. Conclusion Systematic review authors routinely treated studies with zero-events in both arms as "non-informative" carriers and excluded them from their reviews. Whether studies with no events are "informative" or not, largely depends on the methods and assumptions applied, thus sensitivity analyses using different methods should be considered in future meta-analyses.