Moreover, the time course of NP positivity and seroconversion may vary and its related to the time of first contamination (Sethuraman et al

Moreover, the time course of NP positivity and seroconversion may vary and its related to the time of first contamination (Sethuraman et al., 2020). Our study has some limitations. 4.97% [95%CI 4.69C5.25]. No statistical difference was found among gender while seroprevalence was associated with subjects age, geographical location, and occupational sector. Significantly higher values of positivity were observed for the logistics sector (31.3%), weaving factory (12.6%), nursing homes (9.8%), and chemical industry (6.9%) workers. However, we Zfp622 observed some clusters of cases in single companies independently from the sector. Then, a detailed focus on 940 food workers shown a seroprevalence of 5.21% [95%CI 3.79C6.63] and subjects who self-reported COVID-19 symptoms and who worked during lockdown had a higher probability of being infected (< 0.001). Conclusions Data obtained might be useful for future public health decision; more than occupation sector, it seems that failure on prevention system in single companies increase the SARS-CoV-2 transmission. Keywords: seroprevalence, workers, SARS-CoV-2 Whats Important About This Paper? The effect of severe acute respiratory coronavirus 2 (SARS-CoV-2) viral circulation among active workers is usually poor known. Between March 28 and August 7 in North-West Italy, the proportion of SARS-CoV-2 positive workers was 4.97%, and significant differences were found among occupational sectors, with the highest seroprevalences in logistics (31.25%). However, single companies (independently of the sectors) may have had an important role in SARS-CoV-2 transmission, as clusters were detected. This indicates the need Bumetanide for infection prevention in workplaces. Introduction Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was identified in December 2019, as the cause of the illness designated Coronavirus Disease 2019 (COVID-19) (Zhu < 0.05 and data were analyzed using SAS 9.4 (SAS Institute, Cary, North Carolina) and R software. Results From 28 April to 7 August 2020, we collected the results for 23568 serological assessments from a convenience sample of 22708 workers from about 1000 companies; for 463 individuals more than one test was performed. About 60% (= 13613) of the participants were men with median age of 45 [IQR 36C52] years. The majority of subjects worked in Torino (41.0%), Biella (14.1%), Cuneo (12.2%), and Novara (8.0%); while the remaining were located in other Piedmont or North-Western Italian counties. Overall, 1129 workers had SARS-CoV-2 IgG positive measurements and the estimated seroprevalence was 4.97% [IC 95% 4.69C5.25]. Seroprevalences by general demographic characteristics are reported in Table 1. No statistical difference was found between genders (= 22708)= 1129)(%)< 0.001); details on seroprevalence across provinces are reported in Fig. 1. Despite few workers came from the provinces of Bergamo (= 32) and Brescia (= 20), these were the most affected areas, with prevalences of 25% and 15%, respectively. Significantly higher prevalences were observed for workers from Novara (6.70%, 95%CI 5.55C7.86), Alessandria (6.73%, 95%CI 5.18C8.29), and Vercelli (8.02%, 95%CI 6.51C9.54). Open in a separate window Physique 1. Map of seroprevalence of workers. Colors indicate lower and higher prevalence based on quartiles.Province abbreviation: AO = Aosta, Varese = VA, Asti = AT, Cuneo = CN, Biella = BI, Milano = MI, Torino = TO, Verbania = VB, Genova = GE, Novara = NO, Alessandria = AL, Vercelli = VC, Brescia = BS, Bergamo = BG. . A significant association was also found between seroprevalence and occupational sectors (< 0.0001). Significantly higher values of seroprevalence were observed for the logistics sector (31.25%, IC95% 8.54C53.96) and weaving factory (12.6%, IC95% 9.23C15.97) workers. However, in the first group the 95% CI were very wide due to low numbers of subjects analyzed (= 16), whereas in the second group possible clusters of infected cases were suggested, since in two weaving companies 41.5% and 9.9% of subjects (27/65, 9/91) were IgG positive. The health care workers, involved in private health services and private nursing homes, had IgG positive proportions of 5.20% [95%CI 3.90C6.51] and 9.78% [95%CI 7.66C11.89], respectively. In three nursing homes serological positivity was higher than 25% with 22/57 (38.6%), 10/32 (31.3%) and 7/28 (25.0%) positive subjects. Also in the chemical industry widespread of contamination was observed with a prevalence of positive IgG of 6.93% [95%CI 5.37C8.48], with peaks of 81.8% and 46.2% in two small companies (9/11, 6/13). Conversely, significant low prevalences were found in agriculture (2.79%, 95%CI Bumetanide 1.08C4.49), mechanical engineering (3.38%, 95%CI 2.59C4.16), and other manufacturing sector (3.64 95%CI 2.83C4.45). Finally, subjects involved in the food industry had a mean seroprevalence close to Bumetanide 5%, with important differences, since in some plants we observed more than 13% of positive workers (14/106 = 13.2% and 14/99 = 14.1%). Four thousand three hundred sixty-six NP swabs were performed for the search of SARS-CoV-2 computer virus after the result of the serological test:.