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Infect Dis (Lond) ; : 1-6, 2021 Nov 16.
Article in English | MEDLINE | ID: covidwho-1517764


BACKGROUND: Italy experienced SARS-CoV-2 spread during the second wave and the southern regions were severely affected. In this prospective study, we assessed the changes in SARS-CoV-2 seroprevalence rates in non-vaccinated blood donors to evaluate the spread of SARS-CoV-2 among healthy individuals in our geographical area. METHODS: 8,183 healthy blood donors visiting the Transfusion Centre at the University Hospital "Riuniti" of Foggia (Italy) to donate blood from May 2020 to March 2021 were tested twice for anti-SARS-CoV-2 antibodies by Ortho Clinical Diagnostics VITROS® 3600 through anti-SARS-CoV-2 Total and IgG reagent kit. None of the subjects had diagnosed symptomatic COVID-19 infection, and none had received vaccination. RESULTS: Overall, 516 out of 8,183 had antibodies to SARS-CoV-2 (total and IgG antibodies) (6.3%, 95% CI: 0.03-0.15%), 387 were male and 129 female. There was a significant increase of seropositive donors from May 2020 to March 2021 (p < .001). The difference in seroprevalence was significantly associated with age but not sex (2-sided p < .05 for age; 2-sided p ≥ .05 for sex) in both groups. CONCLUSIONS: Our study showed a significant increase in SARS-CoV-2 seroprevalence in blood donors and suggests that asymptomatic individuals might contribute to the spread of SARS-CoV-2. These results may contribute to revised containment measures, priorities in vaccine campaigns and monitoring of seroprevalence in public places like Transfusion Centres. Serologic testing of blood donors may be relevant to monitor SARS-CoV-2 circulation in the general population.

Educ Inf Technol (Dordr) ; : 1-18, 2021 Sep 14.
Article in English | MEDLINE | ID: covidwho-1427316


During the COVID-19 lockdown, all the courses at Imam Abdulrahman Bin Faisal University (IAU) were delivered fully online, including field-training courses. Since there was no previous experience in offering field-training courses in a distance format, the current study aims to identify factors that could impact students' behavioral intention to accept the e-training approach in teaching field training courses at IAU. In order to gather the data, the researchers designed a questionnaire based on the UTAUT model and they ensured the face, content, and construct validity of the questionnaire by sending it to five experts in the relevant field and by using exploratory factor analysis. Also, all the questionnaire's items were reliable since the Cronbach's alpha values were above 0.77 for all the items. A total of 397 participants provided valid responses. The result of this study indicated that Effort Expectancy (EE), Facilitating Condition (FC), Performance Expectancy (PE), and Social Influence (SI), respectively were the primary predictors for students' intention to use e-training. These factors explained 32.1% of the variance in students' behavioral intentions. As far as students' gender is concerned, there were significant differences between students' PE, FC, and SI. Based on these results, policymakers at IAU will have a clear image of the most essential factors that colleges should target to increase students' acceptance of e-training.