Estimation of outpatient SARS-CoV-2 reinfection and recurrence rates and associated factors among COVID-19 hospitalized patients over one-year old: a multicenter retrospective cohort study.

INTRODUCTION: Reinfection with SARS-Cov-2 after recovery can occur that most of them don't require hospitalization. The aim of this study is estimation of out-patient COVID-19 reinfection and recurrence rates and its associated factors among Iranian patients with history of confirmed SARS-Cov-2 infection and hospitalization. METHODS: This study is a retrospective cohort conducted from May 2021 to May 2022 in Iran. The national Medical Care Monitoring Center (MCMC) database, obtained from the Ministry of Health and Medical Education, includes all information about confirmed COVID-19 patients who are hospitalized and diagnosed during the pandemic. Using probability proportional to size sampling from 31 provinces, 1,532 patients over one years of age with a history of hospitalization in the MCMC data are randomly selected. After that, interviews by phone are performed with all of the selected patients using a researcher-made questionnaire about the occurrence of overall reinfection without considering the time of infection occurrence, reinfection occurring at least 90 days after the discharge and recurrence (occurring within 90 days after discharge). Univariate and multivariable Cox regression analyses are performed to assess the factors associated with each index. All of the analyses are performed using Stata software version 16. RESULTS: In general, 1,532 phone calls are made, out of which 1,095 individuals are willing to participate in the study (response rate ≃ 71%). After assessing the 1,095  patients with a positive history of COVID-19, the rates of non-hospitalized overall SARS-Cov-2 reinfection, reinfection and recurrence are 122.64, 114.09, and 8.55 per 1,000 person-years, respectively. The age range of 19-64 years (aHR:3.93, 95%CI : 1.24-12.41) and COVID-19-related healthcare worker (aHR: 3.67, 95%CI: 1.77-7.61) are identified as risk factors for reinfection, while having comorbidity, being fully vaccinated, and having a partial pressure of oxygen (PaO2) ≥ 93 mmHg during the initial infection are identified as factors that reduce the risk of non-hospitalized reinfection. CONCLUSION: Reinfection due to COVID-19 is possible because of the weakened immune system for various reasons and the mutation of the virus. Vaccination, timely boosters, and adherence to preventive measures can help mitigate this risk.

Evaluating the risk of SARS-CoV-2 reinfection with the Omicron or Delta variant in Wales, UK.

Recent studies suggest an increased risk of reinfection with the SARS-CoV-2 Omicron variant compared with previous variants, potentially due to an increased ability to escape immunity specific to older variants, high antigenic divergence of Omicron from earlier virus variants as well as its altered cell entry pathway. The present study sought to investigate epidemiological evidence for differential SARS-CoV-2 reinfection intervals and incidence rates for the Delta versus Omicron variants within Wales. Reinfections in Wales up to February 2022 were defined using genotyping and whole genome sequencing. The median inter-infection intervals for Delta and Omicron were 226 and 192 days, respectively. An incidence rate ratio of 2.17 for reinfection with Omicron compared to Delta was estimated using a conditional Poisson model, which accounted for several factors including sample collection date, age group, area of residence, vaccination and travel status. These findings are consistent with an increased risk of reinfection with the Omicron variant, and highlight the value of monitoring emerging variants that have the potential for causing further waves of cases.

SARS-CoV-2 reinfection broadens the antibody responses and promotes the phenotypic differentiation of virus-specific memory T cells in adolescents.

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron subvariants raises concerns regarding the effectiveness of immunity acquired from previous Omicron subvariants breakthrough infections (BTIs) or reinfections (RIs) against the current circulating Omicron subvariants. In this study, we prospectively investigate the dynamic changes of virus-specific antibody and T cell responses among 77 adolescents following Omicron BA.2.3 BTI with or without subsequent Omicron BA.5 RI. Notably, the neutralizing antibodies (NAbs) titers against various detected SARS-CoV-2 variants, especially the emerging Omicron CH.1.1, XBB.1.5, XBB.1.16, EG.5.1, and JN.1 subvariants, exhibited a significant decrease along the time. A lower level of IgG and NAbs titers post-BTI was found to be closely associated with subsequent RI. Elevated NAbs levels and shortened antigenic distances were observed following Omicron BA.5 RI. Robust T cell responses against both Omicron BA.2- and CH.1.1-spike peptides were observed at each point visited. The exposure to Omicron BA.5 promoted phenotypic differentiation of virus-specific memory T cells, even among the non-seroconversion adolescents. Therefore, updated vaccines are needed to provide effective protection against newly emerging SARS-CoV-2 variants among adolescents.

SARS-CoV-2 Dynamics in the Premier League Testing Program, United Kingdom.

During 2020-2022, players and staff in the English Premier League in the United Kingdom were tested regularly for SARS-CoV-2 with the aim of creating a biosecure bubble for each team. We found that prevalence and reinfection estimates were consistent with those from other studies and with community infection trends.

Specific immunological characteristics and risk factor of XBB variants re-infection in nasopharyngeal carcinoma patients after BA.5 infection.

OBJECTIVES: The specific humoral immune response resulting from inactivated vaccination following by BA.5 infection, and predictors of XBB variants re-infection in BA.5 infection-recovered nasopharyngeal carcinoma (BA.5-RNPC) patients, were explored. METHODS: Serum SARS-CoV-2 specific antibody levels were assessed using enzyme-linked-immunosorbent-assay. Univariate and multivariate binary logistic regression analyses were conducted to identify factors associated with the magnitude of specific humoral immunity and susceptibility to re-infection by XBB variants. RESULTS: Our data demonstrates that SARS-CoV-2 specific antibody levels were comparable between BA.5-RNPC patients and BA.5 infection-recovered-non-cancerous (BA.5-RNC) individuals. Specifically, serum levels of anti-ancestral-S1-IgG, anti-ancestral-nucleocapsid-protein (NP)-IgG, anti-BA.5-receptor binding domain (RBD)-IgG and anti-XBB.1.1.6-RBD-IgG were higher in BA.5-RNPC patients compared to those without a prior infection. Compared to BA.5-RNPC patients without vaccination, individuals who received inactivated vaccination exhibited significantly higher levels of anti-ancestral-S1-IgG and anti-XBB.1.16-RBD-IgG. Multivariate logistic regression analysis revealed that inactivated vaccination was the most significant predictor of all tested SARS-CoV-2 specific antibodies response. Subsequent analysis indicated that a low globulin level is an independent risk factor for XBB re-infection in BA.5-RNPC patients. CONCLUSIONS: The SARS-CoV-2 specific antibodies have been improved in vaccinated BA.5-RNPC patients. However, the baseline immunity status biomarker IgG is an indicators of XBB variant re-infection risk in BA.5-RNPC patients.

Coordinated expansion of memory T follicular helper and B cells mediates spontaneous clearance of HCV reinfection.

Introduction: Follicular helper T cells are essential for helping in the maturation of B cells and the production of neutralizing antibodies (NAbs) during primary viral infections. However, their role during recall responses is unclear. Here, we used hepatitis C virus (HCV) reinfection in humans as a model to study the recall collaborative interaction between circulating CD4 T follicular helper cells (cTfh) and memory B cells (MBCs) leading to the generation of NAbs. Methods: We evaluated this interaction longitudinally in subjects who have spontaneously resolved primary HCV infection during a subsequent reinfection episode that resulted in either another spontaneous resolution (SR/SR, n = 14) or chronic infection (SR/CI, n = 8). Results: Both groups exhibited virus-specific memory T cells that expanded upon reinfection. However, early expansion of activated cTfh (CD4+CXCR5+PD-1+ICOS+FoxP3-) occurred in SR/SR only. The frequency of activated cTfh negatively correlated with time post-infection. Concomitantly, NAbs and HCV-specific MBCs (CD19+CD27+IgM-E2-Tet+) peaked during the early acute phase in SR/SR but not in SR/CI. Finally, the frequency of the activated cTfh1 (CXCR3+CCR6-) subset correlated with the neutralization breadth and potency of NAbs. Conclusion: These results underscore a key role for early activation of cTfh1 cells in helping antigen-specific B cells to produce NAbs that mediate the clearance of HCV reinfection.

The serological IgG and neutralizing antibody of SARS-CoV-2 omicron variant reinfection in Jiangsu Province, China.

Background: It is important to figure out the immunity of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) reinfection to understand the response of humans to viruses. A serological survey for previously infected populations in Jiangsu Province was conducted to compare the antibody level of SARS-CoV-2 in reinfection by Omicron or not. Methods: Reinfection with SARS-CoV-2 was defined as an individual being infected again after 90 days of the initial infection. Telephone surveys and face-to-face interviews were implemented to collect information. Experimental and control serum samples were collected from age-sex-matched reinfected and non-reinfected cases, respectively. IgG anti-S and neutralizing antibodies (Nab) concentrations were detected by the Magnetism Particulate Immunochemistry Luminescence Method (MCLIA). Antibody titers were log(2)-transformed and analyzed by a two-tailed Mann-Whitney U test. Subgroup analysis was conducted to explore the relationship between the strain type of primary infection, SARS-Cov-2 vaccination status, and antibody levels. Multivariate linear regression models were used to identify associations between reinfection with IgG and Nab levels. Results: Six hundred thirty-one individuals were enrolled in this study, including 327 reinfected cases and 304 non-reinfected cases. The reinfection group had higher IgG (5.65 AU/mL vs. 5.22 AU/mL) and Nab (8.02 AU/mL vs. 7.25 AU/mL) levels compared to the non-reinfection group (p < 0.001). Particularly, individuals who had received SARS-CoV-2 vaccination or were initially infected with the Wild type and Delta variant showed a significant increase in antibody levels after reinfection. After adjusting demographic variables, vaccination status and the type of primary infection together, IgG and Nab levels in the reinfected group increased by log(2)-transformed 0.71 and 0.64 units, respectively (p < 0.001). This revealed that reinfection is an important factor that affects IgG and Nab levels in the population. Conclusion: Reinfection with Omicron in individuals previously infected with SARS-CoV-2 enhances IgG and Nab immune responses.

Chronic active Epstein-Barr virus infection with reinfection of SARS-CoV-2: a case report.

We describe the case of a 57-year-old male with jaundice, abdominal distension and fatigue. He was diagnosed as chronic active Epstein-Barr virus infection (CAEBV) due to intermittent elevated liver enzymes, hepatosplenomegaly and pancytopenia, with persistent positive of EBV biomarkers in blood and also positive in liver tissue. The patient was reinfected by SARS-CoV-2 within 2 months companied with CAEBV. The patient's second infection with SARS-CoV-2 led to the aggravated liver dysfunction with pneumonia and re-admission. After receiving symptomatic treatment, the patient showed significantly improvement of symptoms with partially restoration of liver function. After discharge, the patient's health status continued to deteriorate and eventually died. The instances of SARS-CoV-2 co-infection with the original chronic virus are not uncommon, but the exact mechanism of EBV and SARS-CoV-2 coinfection and the relationship between them are still unclear. Since co-infection of SARS-CoV-2 with original chronic virus might affect each other and lead disease aggravated and complicated, it is necessary to differentiate in the diagnosis of disease and it is important to be aware of the re-infection signs of SARS-CoV-2 in people with chronic virus infection diseases, as well as the risk of co-infection of SARS-CoV-2 with other viruses.

Immune responses and reinfection of SARS-CoV-2 Omicron variant in patients with lung cancer.

A significant Omicron wave emerged in China in December 2022. To explore the duration of humoral and cellular response postinfection and the efficacy of hybrid immunity in preventing Omicron reinfection in patients with lung cancer, a total of 447 patients were included in the longitudinal study after the Omicron wave from March 2023 to August 2023. Humoral responses were measured at pre-Omicron wave, 3 months and 7 months postinfection. The detected severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) specific antibodies including total antibodies, anti-receptor binding domain (RBD) specific IgG, and neutralizing antibodies against SARS-CoV-2 wild type (WT) and BA.4/5 variant. T cell responses against SARS-CoV-2 WT and Omicron variant were evaluated in 101 patients by ELISpot at 3 months postinfection. The results showed that Omicron-infected symptoms were mild, while fatigue (30.2%), shortness of breath (34.0%) and persistent cough (23.6%) were long-lasting, and vaccines showed efficacy against fever in lung cancer patients. Humoral responses were higher in full or booster vaccinated patients than those unvaccinated (p < .05 for all four antibodies), and the enhanced response persisted for at least 7 months. T cell response to Omicron was higher than WT peptides (21.3 vs. 16.0 SFUs/106 PBMCs, p = .0093). Moreover, 38 (9.74%) patients were reinfected, which had lower antibody responses than non-reinfected patients (all p < .05), and those patients of unvaccinated at late stage receiving anti-cancer immunotherapy alone were at high risk of reinfection. Collectively, these data demonstrate the Omicron infection induces a high and durable immune response in vaccinated patients with lung cancer, which protects vaccinated patients from reinfection.

A longitudinal study on SARS-CoV-2 seroconversion, reinfection and neutralisation spanning several variant waves and vaccination campaigns, Heinsberg, Germany, April 2020 to November 2022.

BackgroundSince its emergence in December 2019, over 700 million people worldwide have been infected with SARS-CoV-2 up to May 2024. While early rollout of mRNA vaccines against COVID-19 has saved many lives, there was increasing immune escape of new virus variants. Longitudinal monitoring of population-wide SARS-CoV-2 antibody responses from regular sample collection irrespective of symptoms provides representative data on infection and seroconversion/seroreversion rates.AimTo examine adaptive and cellular immune responses of a German SARS-CoV-2 outbreak cohort through several waves of infection with different virus variants.MethodsUtilising a 31-month longitudinal seroepidemiological study (n = 1,446; mean age: 50 years, range: 2-103) initiated during the first SARS-CoV-2 superspreading event (February 2020) in Heinsberg, Germany, we analysed acute infection, seroconversion and virus neutralisation at five follow-up visits between October 2020 and November 2022; cellular and cross-protective immunity against SARS-CoV-2 Omicron variants were also examined.ResultsSARS-CoV-2 spike (S)-specific IgAs decreased shortly after infection, while IgGs remained stable. Both increased significantly after vaccination. We predict an 18-month half-life of S IgGs upon infection. Nucleocapsid (N)-specific responses declined over 12 months post-infection but increased (p < 0.0001) during Omicron. Frequencies of SARS-CoV-2-specific TNF-alpha+/IFN-gamma+ CD4+ T-cells declined over 12 months after infection (p < 0.01). SARS-CoV-2 S antibodies and neutralisation titres were highest in triple-vaccinated participants infected between April 2021 and November 2022 compared with infections between April 2020 and January 2021. Cross neutralisation against Omicron BQ.1.18 and XBB.1.5 was very low in all groups.ConclusionInfection and/or vaccination did not provide the population with cross-protection against Omicron variants.

Post-Covid-19 condition (Long Covid) in children and young people 12 months after infection or reinfection with the Omicron variant: a prospective observational study.

Our previous study in children and young people (CYP) at 3- and 6-months post-infection showed that 12-16% of those infected with the Omicron (B.1.1.529) variant of SARS-CoV-2 met the research definition of Long Covid, with no differences between first-positive and reinfected CYP. The primary objective of the current study is to explore the impact of the Omicron variant of SARS-CoV-2 infection on young people 12 months post infection. 345 CYP aged 11-17 years with a first laboratory-confirmed infection with the Omicron variant and 360 CYP reinfected with the Omicron variant completed an online questionnaire assessing demographics, symptoms, and their impact shortly after testing and again at 3-, 6-and 12-months post-testing. Vaccination status was determined from information held at UKHSA. Comparisons between groups were made using chi-squared, Mann-Whitney U, and Kruskal-Wallis tests. The most common symptoms in first-positive and reinfected CYP 12-months post-testing were tiredness (35.7 and 33.6% respectively) and sleeping difficulties (27.5 and 28.3% respectively). Symptom profiles, severity and impact were similar in the two infection status groups. Overall, by 12-months, 17.4% of first-positives and 21.9% of reinfected CYP fulfilled the research consensus Long Covid definition (p = 0.13). 12-months post Omicron infection, there is little difference between first-positive and reinfected CYP with respect to symptom profiles and impact. Clinicians may not therefore need to consider number of infections and type of variant when developing treatment plans. Further studies are needed to assess causality of reported symptoms up to 12-months after SARS-CoV-2 infection.

Long-term monitoring of SARS-CoV-2 seroprevalence and variants in Ethiopia provides prediction for immunity and cross-immunity.

Under-reporting of COVID-19 and the limited information about circulating SARS-CoV-2 variants remain major challenges for many African countries. We analyzed SARS-CoV-2 infection dynamics in Addis Ababa and Jimma, Ethiopia, focusing on reinfection, immunity, and vaccination effects. We conducted an antibody serology study spanning August 2020 to July 2022 with five rounds of data collection across a population of 4723, sequenced PCR-test positive samples, used available test positivity rates, and constructed two mathematical models integrating this data. A multivariant model explores variant dynamics identifying wildtype, alpha, delta, and omicron BA.4/5 as key variants in the study population, and cross-immunity between variants, revealing risk reductions between 24% and 69%. An antibody-level model predicts slow decay leading to sustained high antibody levels. Retrospectively, increased early vaccination might have substantially reduced infections during the delta and omicron waves in the considered group of individuals, though further vaccination now seems less impactful.

Heterogeneous SARS-CoV-2 kinetics due to variable timing and intensity of immune responses.

The viral kinetics of documented SARS-CoV-2 infections exhibit a high degree of interindividual variability. We identified 6 distinct viral shedding patterns, which differed according to peak viral load, duration, expansion rate, and clearance rate, by clustering data from 768 infections in the National Basketball Association cohort. Omicron variant infections in previously vaccinated individuals generally led to lower cumulative shedding levels of SARS-CoV-2 than other scenarios. We then developed a mechanistic mathematical model that recapitulated 1,510 observed viral trajectories, including viral rebound and cases of reinfection. Lower peak viral loads were explained by a more rapid and sustained transition of susceptible cells to a refractory state during infection as well as by an earlier and more potent late, cytolytic immune response. Our results suggest that viral elimination occurs more rapidly during Omicron infection, following vaccination, and following reinfection due to enhanced innate and acquired immune responses. Because viral load has been linked with COVID-19 severity and transmission risk, our model provides a framework for understanding the wide range of observed SARS-CoV-2 infection outcomes.

Patient and Immunological Factors Associated With Delayed Clearance of Mucosal Severe Acute Respiratory Syndrome Coronavirus 2 RNA and Symptom Persistence.

Serial blood and mucosal samples were characterized for 102 participants enrolled a median of 7.0 days after coronavirus disease 2019 diagnosis. Mucosal RNA was detectable for a median of 31.5 (95% confidence interval [CI], 20.5-63.5) days, with persistence ≥1 month associated with obesity (body mass index [BMI] ≥30 kg/m2; odds ratio [OR], 3.9 [95% CI, 1.2-13.8]) but not age, sex, or chronic conditions. Fifteen participants had likely reinfection; lower serum anti-spike IgG levels were associated with reinfection risk. Nearly half of participants (47%) reported symptoms lasting ≥2-3 months; persistence ≥3 months was associated with BMI ≥30 kg/m2 (OR, 4.2 [95% CI, 1.1-12.8]) and peak anti-spike and anti-nucleocapsid antibody levels.

A mathematical model for the within-host (re)infection dynamics of SARS-CoV-2.

Interactions between SARS-CoV-2 and the immune system during infection are complex. However, understanding the within-host SARS-CoV-2 dynamics is of enormous importance for clinical and public health outcomes. Current mathematical models focus on describing the within-host SARS-CoV-2 dynamics during the acute infection phase. Thereby they ignore important long-term post-acute infection effects. We present a mathematical model, which not only describes the SARS-CoV-2 infection dynamics during the acute infection phase, but extends current approaches by also recapitulating clinically observed long-term post-acute infection effects, such as the recovery of the number of susceptible epithelial cells to an initial pre-infection homeostatic level, a permanent and full clearance of the infection within the individual, immune waning, and the formation of long-term immune capacity levels after infection. Finally, we used our model and its description of the long-term post-acute infection dynamics to explore reinfection scenarios differentiating between distinct variant-specific properties of the reinfecting virus. Together, the model's ability to describe not only the acute but also the long-term post-acute infection dynamics provides a more realistic description of key outcomes and allows for its application in clinical and public health scenarios.

How does the SARS-CoV-2 reinfection rate change over time? The global evidence from systematic review and meta-analysis.

BACKGROUND: There is a significant increase in the number of SARS-CoV-2 reinfection reports in various countries. However, the trend of reinfection rate over time is not clear. METHODS: We searched PubMed, Web of Science, Medline, Embase, Cochrane Central Register of Controlled Trials, China National Knowledge Infrastructure, and Wanfang for cohort studies, case-control studies, and cross-sectional studies up to March 16, 2023, to conduct a meta-analysis of global SARS-CoV-2 reinfection rate. Subgroup analyses were performed for age, country, study type, and study population, and time-varying reinfection rates of SARS-CoV-2 were estimated using meta-regression. The risk of bias was assessed using the Newcastle-Ottawa Scale and the Joanna Briggs Institute critical appraisal tool. RESULT: A total of 55 studies involving 111,846 cases of SARS-CoV-2 reinfection were included. The pooled SARS-CoV-2 reinfection rate was 0.94% (95% CI: 0.65 -1.35%). In the subgroup analyses, there were statistically significant differences in the pooled reinfection rates by reinfection variant, and study type (P < 0.05). Based on meta-regression, the reinfection rate fluctuated with time. CONCLUSION: Meta-regression analysis found that the overall reinfection rate increased and then decreased over time, followed by a period of plateauing and then a trend of increasing and then decreasing, but the peak of the second wave of reinfection rate was lower than the first wave. SARS-CoV-2 is at risk of reinfection and the Omicron variant has a higher reinfection rate than other currently known variants. The results of this study could help guide public health measures and vaccination strategies in response to the Coronavirus Disease 2019 (COVID-19) pandemic.

Apoptosis and pyroptosis in the nasal mucosa of Syrian hamster during SARS-CoV-2 infection and reinfection.

In SARS-CoV-2 infection, it has been observed that viral replication lasts longer in the nasal mucosa than in the lungs, despite the presence of a high viral load at both sites. In hamsters, we found that the nasal mucosa exhibited a mild inflammatory response and minimal pathological injuries, whereas the lungs displayed a significant inflammatory response and severe injuries. The underlying cellular events may be induced by viral infection in three types of cell death: apoptosis, pyroptosis, and necroptosis. Our findings indicate that apoptosis was consistently activated during infection in the nasal mucosa, and the levels of apoptosis were consistent with the viral load. On the other hand, pyroptosis and a few instances of necroptosis were observed only on 7 dpi in the nasal mucosa. In the lungs, however, both pyroptosis and apoptosis were prominently activated on 3 dpi, with lower levels of apoptosis compared to the nasal mucosa. Interestingly, in reinfection, obvious viral load and apoptosis in the nasal mucosa were detected on 3 dpi, while no other forms of cell death were detected. We noted that the inflammatory reactions and pathological injuries in the nasal mucosa were milder, indicating that apoptosis may play a role in promoting lower inflammatory reactions and milder pathological injuries and contribute to the generation of long-term viral replication in the nasal mucosa. Our study provides valuable insights into the differences in cellular mechanisms during SARS-CoV-2 infection and highlights the potential significance of apoptosis regulation in the respiratory mucosa for controlling viral replication.

Incidence and outcome of SARS-CoV-2 reinfection in the pre-Omicron era: A global systematic review and meta-analysis.

Background: With the emergence of new variants and sub-lineages of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), reinfections can significantly impact herd immunity, vaccination policies, and decisions on other public health measures. We conducted a systematic review and meta-analysis to synthesise the global evidence on SARS-CoV-2 reinfections in the pre-Omicron era. Methods: We searched five global databases (MEDLINE, Embase, CINAHL Plus, Global Health, WHO COVID-19) on 12 May 2022 and 28 July 2023 and three Chinese databases (CNKI, Wanfang, CQvip) on 16 October 2022 for articles reporting incidence and outcomes of SARS-CoV-2 reinfection before the period of Omicron (B.1.1.529) predominance. We assessed risk of bias using Joanna Briggs Institute critical appraisal tools and conducted meta-analyses with random effects models to estimate the proportion of SARS-CoV-2 reinfection among initially infected cases and hospitalisation and mortality proportions among reinfected ones. Results: We identified 7593 studies and extracted data from 64 included ones representing 21 countries. The proportion of SARS-CoV-2 reinfection was 1.16% (95% confidence interval (CI) = 1.01-1.33) based on 11 639 247 initially infected cases, with ≥45 days between the two infections. Healthcare providers (2.28%; 95% CI = 1.37-3.40) had a significantly higher risk of reinfection than the general population (1.00%; 95% CI = 0.81-1.20), while young adults aged 18 to 35 years (1.01%; 95% CI = 0.8-1.25) had a higher reinfection burden than other age groups (children <18 years old: 0.57%; 95% CI = 0.39-0.79, older adults aged 36-65 years old: 0.53%; 95% CI = 0.41-0.65, elderly >65 years old: 0.37%; 95% CI = 0.15-0.66). Among the reinfected cases, 8.12% (95% CI = 5.30-11.39) were hospitalised, 1.31% (95% CI = 0.29-2.83) were admitted to the intensive care unit, and 0.71% (95% CI = 0.02-2.01) died. Conclusions: Our data suggest a relatively low risk of SARS-CoV-2 reinfection in the pre-Omicron era, but the risk of hospitalisation was relatively high among the reinfected cases. Considering the possibility of underdiagnosis, the reinfection burden may be underestimated. Registration: PROSPERO: CRD42023449712.