Prevalence of SARS-CoV-2 infection and associated risk factors: A testing program and nested case-control study conducted at Sapienza University of Rome between March and June 2021.

Background: To safely resume in-person activities during the COVID-19 pandemic, Sapienza University of Rome implemented rigorous infection prevention and control measures, a successful communication campaign and a free SARS-CoV-2 testing program. In this study, we describe the University's experience in carrying out such a program in the context of the COVID-19 response and identify risk factors for infection. Methods: Having identified resources, space, supplies and staff, from March to June 2021 Sapienza offered to all its enrollees a molecular test service (8.30 AM to 4 PM, Monday to Thursday). A test-negative case-control study was conducted within the program. Participants underwent structured interviews that investigated activity-related exposures in the 2 weeks before testing. Multivariable conditional logistic regression analyses were performed. Adjusted odds ratios (aORs) and 95% confidence intervals (95% CIs) were calculated. Results: A total of 8,959 tests were administered, of which 56 were positive. The detection trend followed regional tendencies. Among 40 cases and 80 controls, multivariable analysis showed that a known exposure to a COVID-19 case increased the likelihood of infection (aOR: 8.39, 95% CI: 2.38-29.54), while having a job decreased it (aOR: 0.23, 95% CI: 0.06-0.88). Of factors that almost reached statistical significance, participation in activities in the university tended to reduce the risk (aOR: 0.32, 95% CI: 0.09-1.06), while attendance at private gatherings showed an increasing risk trend (aOR: 3.48, 95% CI: 0.95-12.79). Age, gender, activities in the community, visiting bars or restaurants, and use of public transportation were not relevant risk factors. When those students regularly attending the university campus were excluded from the analysis, the results were comparable, except that attending activities in the community came close to having a statistically significant effect (aOR: 8.13, 95% CI: 0.91-72.84). Conclusions: The testing program helped create a safe university environment. Furthermore, promoting preventive behavior and implementing rigorous measures in public places, as was the case in the university setting, contributed to limit the virus transmission.

Prevalence of SARS-CoV-2 infection and associated risk factors: A testing program and nested case-control study conducted at Sapienza University of Rome between March and June 2021

Background To safely resume in-person activities during the COVID-19 pandemic, Sapienza University of Rome implemented rigorous infection prevention and control measures, a successful communication campaign and a free SARS-CoV-2 testing program. In this study, we describe the University's experience in carrying out such a program in the context of the COVID-19 response and identify risk factors for infection. Methods Having identified resources, space, supplies and staff, from March to June 2021 Sapienza offered to all its enrollees a molecular test service (8.30 AM to 4 PM, Monday to Thursday). A test-negative case-control study was conducted within the program. Participants underwent structured interviews that investigated activity-related exposures in the 2 weeks before testing. Multivariable conditional logistic regression analyses were performed. Adjusted odds ratios (aORs) and 95% confidence intervals (95% CIs) were calculated. Results A total of 8,959 tests were administered, of which 56 were positive. The detection trend followed regional tendencies. Among 40 cases and 80 controls, multivariable analysis showed that a known exposure to a COVID-19 case increased the likelihood of infection (aOR: 8.39, 95% CI: 2.38–29.54), while having a job decreased it (aOR: 0.23, 95% CI: 0.06–0.88). Of factors that almost reached statistical significance, participation in activities in the university tended to reduce the risk (aOR: 0.32, 95% CI: 0.09–1.06), while attendance at private gatherings showed an increasing risk trend (aOR: 3.48, 95% CI: 0.95–12.79). Age, gender, activities in the community, visiting bars or restaurants, and use of public transportation were not relevant risk factors. When those students regularly attending the university campus were excluded from the analysis, the results were comparable, except that attending activities in the community came close to having a statistically significant effect (aOR: 8.13, 95% CI: 0.91–72.84). Conclusions The testing program helped create a safe university environment. Furthermore, promoting preventive behavior and implementing rigorous measures in public places, as was the case in the university setting, contributed to limit the virus transmission.

Serological Response and Relationship with Gender-Sensitive Variables among Healthcare Workers after SARS-CoV-2 Vaccination.

Vaccine-induced immunity is a key strategy in the long-term control of the COVID-19 pandemic. The aim of our study was to explore the relationship between mRNA vaccine-induced antibodies and gender-sensitive variables among healthcare workers. Two thousand-sixty-five volunteers who received the BNT162b2 vaccine were enrolled in the study and followed up. Demographic, clinical, and social variables (educational level, marital status, occupation, childcare) were evaluated through a self-administered questionnaire. Anti-Spike (S) IgG were measured at 1 month (T1) and at 5 months (T2) after the second vaccine dose. At T1, median anti-S IgG values were 693 [394->800] AU/mL (1 AU = 2.6 BAU). Values > 800 AU/mL (2080 BAU/mL) were directly associated with a previous COVID-19 (p < 0.001) infection and inversely with age (p < 0.001), smoking habit (p < 0.001), and autoimmune diseases (p < 0.001). At T2, a significant decreasing in anti-S IgG values was observed (187 [81-262] AU/mL), with a median decrease of 72 [60-82]%. On multivariate data analysis, a reduction of more than 82% was directly associated with male sex (p < 0.021), age (p < 0.001), smoking (p = 0.038), hypertension (p = 0.042), and, inversely, with previous COVID-19 infection (p < 0.001) and being "cohabiting" (p = 0.005). Our findings suggest that demographic, clinical, and social variables play a role in anti-S IgG values decreasing in long-term follow up and should be considered to find personalized vaccine schedules.