ObjectiveTo analyze the epidemiological characteristics of long COVID and to investigate its main influencing factors by examining individuals infected with SARS-CoV-2 between March and June 2022 in two communities in Shanghai, to lay the foundation for further research on the mechanism and clinical treatment of long COVID, and to provide the basis for the development of inexpensive, convenient, and feasible prevention and intervention strategies. MethodsA cross-sectional study was conducted, enrolling 6 410 individuals infected with SARS-CoV-2. Data were collected through a questionnaire survey. The incidence and common symptoms of long COVID were analyzed, along with their associations with demographic characteristics, medical history, and behavioral factors. A logistic regression model was used to identify the major factors associated with the development of long COVID symptoms. ResultsThe overall incidence rate of long COVID among the study population was 13.9%. The most commonly reported symptoms included fatigue (65.1%), attention disorders (23.1%), and cough (16.9%). The analysis showed that having underlying chronic diseases (OR=2.580, 95%CI: 2.165‒3.074), a history of allergies (OR=1.418, 95%CI: 1.003‒1.971), current smoking (OR=1.461, 95%CI: 1.013‒2.079), ever smoking (OR=2.462, 95%CI: 1.687‒3.551), a greater number of symptoms during the acute phase [1 symptom (OR=1.778, 95%CI: 1.459‒2.162), 2 symptoms (OR=2.749, 95%CI: 2.209‒3.409), ≥3 symptoms (OR=7.792, 95%CI: 6.333‒9.593)] and aggravated symptoms during the acute phase (OR=1.082, 95%CI: 1.070‒1.094) were factors associated with a higher risk of developing long COVID symptoms. Additionally, individuals who had consumed alcohol in the past year (OR=1.914, 95%CI: 1.344‒2.684) were more prone to objective long COVID symptoms. Among individuals under 50 years of age, females (OR=1.427, 95%CI: 1.052‒1.943) were more likely to develop objective long COVID symptoms. ConclusionThis study has identified the diversity of long COVID symptoms, which involve multiple organs and systems, including fatigue, attention disorders, cough, and joint pain. It has also revealed associations between long COVID and various demographic factors (e.g., age, gender), personal medical history (e.g., underlying chronic diseases, history of allergies), acute-phase characteristics (e.g., number and severity of symptoms), and behavioral factors (e.g., smoking, alcohol consumption). These findings highlight the need for further research and ongoing surveillance of long COVID and may inform the development of more targeted health management strategies for specific populations.

ObjectiveTo analyze the epidemiological characteristics and influencing factors of SARS-CoV-2 reinfection by conducting follow-up investigations among community residents who experienced their first SARS-CoV-2 infection between March and June 2022, so as to provide a scientific basis for predicting future epidemic trends and adjusting prevention and control strategies. MethodsA cohort study was conducted in Xuhui District, Shanghai. A total of 1 208 individuals with a documented primary SARS-CoV-2 infection between March and June 2022 were enrolled and followed-up longitudinally. Data were collected using structured questionnaire surveys to assess the reinfection rate, incidence density, and clinical manifestations of SARS-CoV-2 reinfection. A logistic regression model was used to analyze the influencing factors of SARS-CoV-2 reinfection. ResultsA total of 497 SARS-CoV-2 reinfection cases were observed among the 1 208 research subjects, with a reinfection rate of 41.14% and an incidence density of 0.63 cases per 1 000 person-days. The cumulative reinfection rates at 6, 9, 12, 15, and 18 months following the initial infection were 0.08%, 15.31%, 19.04%, 33.53%, and 38.25%, respectively. Compared with the primary infection, reinfection was more likely to be symptomatic, with a greater severity of fever, dry cough, sore throat, and runny nose. Being female, younger age, and symptom duration ≥7 days during the primary infection were identified as influencing factors for SARS-CoV-2 reinfection, while a higher socioeconomic status can reduce the risk of SARS-CoV-2 reinfection. ConclusionSARS-CoV-2 reinfection is relatively common and often symptomatic. Age, gender, income level, and the duration of symptoms during the primary infection are identified as infuencing factors for SARS-CoV-2 reinfection. Continuous monitoring of reinfection in the population is recommended, along with the development of effective strategies to mitigate the impact of reinfection.