Sociodemographic and Occupational Factors Associated with Low Early Uptake of COVID-19 Vaccine in Hospital-Based Healthcare Workers, Georgia, March-July 2021.

In Georgia, an upper-middle income European country, the COVID-19 vaccine rollout began on 15 March 2021 with health workers (HWs), a priority group for vaccination. We assessed the factors associated with COVID-19 vaccination among HWs at six large hospitals in the early stages of the vaccine rollout (March-July 2021). Among 1533 HWs, 274 (17.9%) had received one dose of the COVID-19 vaccine. Strong independent predictors of early vaccine uptake were age > 40 years, especially 50-59 years old (aOR 2.40, 95% CI 1.50-3.88), considering the vaccine as "somewhat effective" or "very effective" rather than "not effective" (aOR 6.33, 95% CI 2.29-26.3 and aOR 10.9, 95% CI 3.88-45.70, respectively), and previous vaccination against seasonal influenza (aOR 2.98, 95% CI 2.19-4.08). Previous SARS-CoV-2 infection was negatively associated with receiving the vaccine (aOR 0.6, 95% CI 0.40-0.80). Compared to physicians, nurses/midwives (aOR 0.22, 95% CI 0.15-0.32), administrative staff (aOR 0.36, 95% CI 0.22-0.56), and ancillary staff (aOR 0.07, 95% CI 0.04-0.15) were less likely to have received the COVID-19 vaccine. Tailoring the COVID-19 vaccine communications campaign to younger and non-physician HWs, and emphasizing the benefits of the COVID-19 vaccine, could help further increase vaccine coverage among HWs in Georgia.

Risk of COVID-19 in Health Professionals: A Case-Control Study, Portugal Risco de COVID-19 em profissionais de saúde: estudo de caso-controlo, Portugal

Introduction Health professionals face higher occupational exposure to SARS-CoV-2. We aimed to estimate the risk of COVID-19 test positivity in health professionals compared to non-health professionals. Methods We conducted a test-negative case-control study using Portuguese national surveillance data (January to May 2020). Cases were suspected cases who tested positive for SARS-CoV-2;controls were suspected cases who tested negative. We used multivariable logistic regression modelling to estimate the odds ratio of a positive COVID-19 test (RT-PCR;primary outcome), comparing health professionals and non-health professionals (primary exposure), and adjusting for the confounding effect of demographic, clinical, and epidemiological characteristics, and the modification effect of the self-reported epidemiological link (i.e., self-reported contact with a COVID-19 case or person with COVID-19-like symptoms). Results Health professionals had a 2-fold higher risk of a positive COVID-19 test result (aOR = 1.89, 95% CI 1.69–2.11). However, this association was strongly modified by the self-report of an epidemiological link such that, among cases who did report an epidemiological link, being a health professional was a protective factor (aOR = 0.90, 95% CI 0.82–0.98). Conclusion Our findings suggest that health professionals might be primarily infected by unknown contacts, plausibly in the healthcare setting, but also that their occupational exposure does not systematically translate into a higher risk of transmission. We suggest that this could be interpreted in light of different types and timing of exposure, and variability in risk perception and associated preventive behaviours.

Clinical and hospitalisation predictors of COVID-19 in the first month of the pandemic, Portugal.

COVID-19 mainly presents as a respiratory disease with flu-like symptoms, however, recent findings suggest that non-respiratory symptoms can occur early in the infection and cluster together in different groups in different regions. We collected surveillance data among COVID-19 suspected cases tested in mainland Portugal during the first wave of the pandemic, March-April 2020. A multivariable logistic-regression analysis was performed to ascertain the effects of age, sex, prior medical condition and symptoms on the likelihood of testing positive and hospitalisation. Of 25,926 COVID-19 suspected cases included in this study, 5,298 (20%) tested positive. Symptoms were grouped into ten clusters, of which two main ones: one with cough and fever and another with the remainder. There was a higher odds of a positive test with increasing age, myalgia and headache. The odds of being hospitalised increased with age, presence of fever, dyspnoea, or having a prior medical condition although these results varied by region. Presence of cough and other respiratory symptoms did not predict COVID-19 compared to non-COVID respiratory disease patients in any region. Dyspnoea was a strong determinant of hospitalisation, as well as fever and the presence of a prior medical condition, whereas these results varied by region.