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Risk and protective factors for SARS-CoV-2 reinfections, surveillance data, Italy, August 2021 to March 2022.

ABSTRACT: We explored the risk factors associated with SARS-CoV-2 reinfections in Italy between August 2021 and March 2022. Regardless of the prevalent virus variant, being unvaccinated was the most relevant risk factor for reinfection. The risk of reinfection increased almost 18-fold following emergence of the Omicron variant compared with Delta. A severe first SARS-CoV-2 infection and age over 60 years were significant risk factors for severe reinfection.

SUBMITTER: Sacco C

PROVIDER: S-EPMC9121659 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature

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Risk and protective factors for SARS-CoV-2 reinfections, surveillance data, Italy, August 2021 to March 2022.

Sacco Chiara C Petrone Daniele D Del Manso Martina M Mateo-Urdiales Alberto A Fabiani Massimo M Bressi Marco M Bella Antonino A Pezzotti Patrizio P Rota Maria Cristina MC Riccardo Flavia F

Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin 20220501 20

We explored the risk factors associated with SARS-CoV-2 reinfections in Italy between August 2021 and March 2022. Regardless of the prevalent virus variant, being unvaccinated was the most relevant risk factor for reinfection. The risk of reinfection increased almost 18-fold following emergence of the Omicron variant compared with Delta. A severe first SARS-CoV-2 infection and age over 60 years were significant risk factors for severe reinfection. ...[more]

PMID: 35593164

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Project description:COVID-19 is an acute respiratory infectious disease caused by SARS-CoV-2. It was first reported in Wuhan, China in December 2019 and rapidly spread globally in early 2020, triggering a global pandemic. In December 2022, China adjusted the dynamic COVID-zero strategy that lasted for three years. The number of positive cases in China increased rapidly in the short term. Weihai was also affected during this period. We conducted genomic surveillance of SARS-CoV-2 variants in Weihai during this period, hoping to understand the changes in the genomic characteristics of SARS-CoV-2 before and after the adjustment of the epidemic policy. In this study,we collected SARS-CoV-2 positive samples from March 2022 to March 2023 in Weihai and performed SARS-CoV-2 whole genome sequencing on these samples using next-generation sequencing technology. we obtained a total of 704 SARS-CoV-2 whole genome sequences, and selected 581 high-quality sequences for further analysis. The analysis results showed that from March 2022 to November 2022, before the adjustment of epidemic policy, the COVID-19 cases in Weihai were mainly from four local clusters,which were caused by four variants, including BA.2,BA.1.1,P.1.15 and BA.5.2.1. Phylogenetic analysis showed that: In the same cluster,the sequences between each other were highly homologous, and the whole genome sequence were almost identical. After December 2022, the epidemic policy was adjusted, BF.7 and BA.5.2 became the dominant variants in Weihai, consistent with the main domestic strains in China during the same period. Phylodynamic analysis showed that BF.7 and BA.5.2 had a large amount of genetic diversities in December, and the effective population size of BF.7 and BA.5.2 also showed explosive growth in December. In conclusion, we reported the composition and dynamic trend of SARS-CoV-2 variants in Weihai from March 2022 to March 2023. We found that there have been significant changes in the variants and expansion patterns of SARS-CoV-2 before and after the adjustment of epidemic policies. But the dominant variants in Weihai were the same as the SARS-CoV-2 variants circulating globally at the same time and we found no persistently dominant variants or new lineages during this period.

Project description:ImportanceDuring the COVID-19 pandemic, children and adolescents were massively infected worldwide. In 2022, reinfections became a main feature of the endemic phase of SARS-CoV-2, so it is important to understand the epidemiology and clinical impact of reinfections.ObjectiveTo assess the incidence, risk, and severity of pediatric SARS-CoV-2 reinfection.Design, setting, and participantsThis retrospective cohort study used epidemiologic data of documented SARS-CoV-2 infections from the surveillance database of the Institute for Public Health of Vojvodina. A total of 32 524 children and adolescents from Vojvodina, Serbia, with laboratory-confirmed SARS-CoV-2 infection between March 6, 2020, and April 30, 2022, were followed up for reinfection until July 31, 2022.Main outcomes and measuresIncidence rates of documented SARS-CoV-2 reinfection per 1000 person-months, estimated risk of documented reinfection 90 days or more after laboratory confirmation of primary infection, reinfection severity, hospitalizations, and deaths.ResultsThe study cohort included 32 524 children and adolescents with COVID-19 (mean [SD] age, 11.2 [4.9] years; 15 953 [49.1%] male), including 964 children (3.0%) who experienced documented reinfection. The incidence rate of documented reinfections was 3.2 (95% CI, 3.0-3.4) cases per 1000 person-months and was highest in adolescents aged 12 to 17 years (3.4; 95% CI, 3.2-3.7). Most reinfections (905 [93.9%]) were recorded in 2022. The cumulative reinfection risk was 1.3% at 6 months, 1.9% at 9 months, 4.0% at 12 months, 6.7% at 15 months, 7.2% at 18 months, and 7.9% after 21 months. Pediatric COVID-19 cases were generally mild. The proportion of severe clinical forms decreased from 14 (1.4%) in initial episodes to 3 (0.3%) in reinfections. Reinfected children were approximately 5 times less likely to have severe disease during reinfection compared with initial infection (McNemar odds ratio, 0.2; 95% CI, 0.0-0.8). Pediatric reinfections rarely led to hospitalization (0.5% vs 1.3% during primary infections), and none resulted in death.Conclusions and relevanceThis cohort study found that the SARS-CoV-2 reinfection risk remained substantially lower for children and adolescents compared with adults as of July 2022. Pediatric infections were mild, and reinfections were even milder than primary infections.

Project description:BackgroundDuring the COVID-19 pandemic, wastewater-based surveillance gained great international interest as an additional tool to monitor SARS-CoV-2. In autumn 2021, the Norwegian Institute of Public Health decided to pilot a national wastewater surveillance (WWS) system for SARS-CoV-2 and its variants between June 2022 and March 2023. We evaluated the system to assess if it met its objectives and its attribute-based performance.MethodsWe adapted the available guidelines for evaluation of surveillance systems. The evaluation was carried out as a descriptive analysis and consisted of the following three steps: (i) description of the WWS system, (ii) identification of users and stakeholders, and (iii) analysis of the system's attributes and performance including sensitivity, specificity, timeliness, usefulness, representativeness, simplicity, flexibility, stability, and communication. Cross-correlation analysis was performed to assess the system's ability to provide early warning signal of new wave of infections.ResultsThe pilot WWS system was a national surveillance system using existing wastewater infrastructures from the largest Norwegian municipalities. We found that the system was sensitive, timely, useful, representative, simple, flexible, acceptable, and stable to follow the general trend of infection. Preliminary results indicate that the system could provide an early signal of changes in variant distribution. However, challenges may arise with: (i) specificity due to temporary fluctuations of RNA levels in wastewater, (ii) representativeness when downscaling, and (iii) flexibility and acceptability when upscaling the system due to limited resources and/or capacity.ConclusionsOur results showed that the pilot WWS system met most of its surveillance objectives. The system was able to provide an early warning signal of 1-2 weeks, and the system was useful to monitor infections at population level and complement routine surveillance when individual testing activity was low. However, temporary fluctuations of WWS values need to be carefully interpreted. To improve quality and efficiency, we recommend to standardise and validate methods for assessing trends of new waves of infection and variants, evaluate the WWS system using a longer operational period particularly for new variants, and conduct prevalence studies in the population to calibrate the system and improve data interpretation.

Project description:IntroductionIndia experienced 2 waves of COVID-19 pandemic caused by SARS-CoV-2 and reported the second highest caseload globally. Seroepidemiologic studies were done to track the course of the pandemic. We systematically reviewed and synthesized the seroprevalence of SARS-CoV-2 in the Indian population.MethodsWe included studies reporting seroprevalence of IgG antibodies against SARS-CoV-2 from March 1, 2020 to August 11, 2021 and excluded studies done only among patients with COVID-19 and vaccinated individuals. We searched published databases, preprint servers, and government documents using a combination of keywords and medical subheading (MeSH) terms of "Seroprevalence AND SARS-CoV-2 AND India". We assessed risk of bias using the Newcastle-Ottawa scale, the appraisal tool for cross-sectional studies (AXIS), the Joanna Briggs Institute (JBI) critical appraisal tool, and WHO's statement on the Reporting of Seroepidemiological Studies for SARS-CoV-2 (ROSES-S). We calculated pooled seroprevalence along with 95% Confidence Intervals (CI) during the first (March 2020 to February 2021) and second wave (March to August 2021). We also estimated seroprevalence by selected demographic characteristics.ResultsWe identified 3821 studies and included 53 studies with 905379 participants after excluding duplicates, screening of titles and abstracts and full-text screening. Of the 53, 20 studies were of good quality. Some of the reviewed studies did not report adequate information on study methods (sampling = 24% (13/53); laboratory = 83% [44/53]). Studies of 'poor' quality had more than one of the following issues: unjustified sample size, nonrepresentative sample, nonclassification of nonrespondents, results unadjusted for demographics and methods insufficiently explained to enable replication. Overall pooled seroprevalence was 20.7% in the first (95% CI = 16.1 to 25.3) and 69.2% (95% CI = 64.5 to 73.8) in the second wave. Seroprevalence did not differ by age in first wave, whereas in the second, it increased with age. Seroprevalence was slightly higher among women in the second wave. In both the waves, the estimate was higher in urban than in rural areas.ConclusionSeroprevalence increased by 3-fold between the 2 waves of the pandemic in India. Our review highlights the need for designing and reporting studies using standard protocols.

Dataset Information

Risk and protective factors for SARS-CoV-2 reinfections, surveillance data, Italy, August 2021 to March 2022.

Publications

Risk and protective factors for SARS-CoV-2 reinfections, surveillance data, Italy, August 2021 to March 2022.

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