SARS-CoV-2 Infection in Healthcare Personnel With High-risk Occupational Exposure: Evaluation of 7-Day Exclusion From Work Policy.

BACKGROUND: As of late February 2020, Greece has been experiencing the coronavirus disease 2019 (COVID-19) epidemic. Healthcare personnel (HCP) were disproportionately affected, accounting for ~10% of notified cases. Exclusion from work for 7 days was recommended for HCP with high-risk occupational exposure. Our aim was to evaluate the 7-day exclusion from work policy for HCP with high-risk exposure. METHODS: HCP with a history of occupational exposure to COVID-19 were notified to the Hellenic National Public Health Organization, regardless of their exposure risk category. Exposed HCP were followed for 14 days after last exposure. RESULTS: We prospectively studied 3398 occupationally exposed HCP; nursing personnel accounted for most exposures (n = 1705; 50.2%). Of the 3398 exposed HCP, 1599 (47.1%) were classified as low-risk, 765 (22.5%) as moderate-risk, and 1031 (30.4%) as high-risk exposures. Sixty-six (1.9%) HCP developed COVID-19 at a mean of 3.65 (range: 0-17) days postexposure. Of the 66 HCP with COVID-19, 46, 7, and 13 had a history of high-, moderate- or low-risk exposure (4.5%, 0.9%, and 0.8% of all high-, moderate-, and low-risk exposures, respectively). Hospitalization and absenteeism were more prevalent among HCP with high-risk exposure. A logistic regression analysis showed that the following variables were significantly associated with an increased risk for the onset of COVID-19: male, administrative personnel, underlying disease, and high-risk exposure. CONCLUSIONS: HCP with high-risk occupational exposure to COVID-19 had increased probability of serious morbidity, healthcare seeking, hospitalization, and absenteeism. Our findings justify the 7-day exclusion from work policy for HCP with high-risk exposure.

Influenza vaccine effectiveness against hospitalization with laboratory-confirmed influenza in Greece: A pooled analysis across six seasons, 2013-2014 to 2018-2019.

BACKGROUND: Monitoring seasonal influenza Vaccine Effectiveness (VE) is key to inform vaccination strategies and sustain uptake. Pooling data across multiple seasons increases precision and allows for subgroup analyses, providing more conclusive evidence. Our aim was to assess VE against hospitalization with laboratory-confirmed influenza in Greece over six seasons, from 2013 to 2014 to 2018-2019, using routinely collected surveillance data. METHODS: Swab samples from hospitalized patients across the country were tested for influenza by RT-PCR. We used the test-negative design, with patients testing positive for influenza serving as cases and those testing negative serving as controls. VE was calculated as one minus the Odds Ratio (OR) for influenza vaccination, estimated by mixed-effects logistic regression and adjusted for age, sex, hospitalization type (being in intensive care or not), time from symptom onset to swabbing, and calendar time. Stratified estimates by age and hospitalization type were obtained, and also subgroup estimates by influenza type/subtype and season. Antigenic and genetic characterization of a subset of circulating influenza strains was performed. RESULTS: A total of 3,882 test-positive cases and 5,895 test-negative controls were analyzed. Across all seasons, adjusted VE was 45.5% (95% CI: 31.6-56.6) against all influenza, 62.8% against A(H1N1)pdm09 (95% CI: 40.7-76.7), 28.2% against A(H3N2) (95% CI: 12.0-41.3) and 45.5% against influenza B (95% CI: 29.1-58.1). VE was slightly lower for patients aged 60 years and over, and similar between patients hospitalized inside or outside intensive care. Circulating A(H1N1)pdm09 and B strains were antigenically similar to the vaccine strains, whereas A(H3N2) were not. CONCLUSION: Our results confirm the public health benefits from seasonal influenza vaccination, despite the suboptimal effectiveness against A(H3N2) strains. Continued monitoring of VE is essential, and routinely collected surveillance data can be valuable in this regard.

Mortality attributable to seasonal influenza in Greece, 2013 to 2017: variation by type/subtype and age, and a possible harvesting effect.

IntroductionEstimating the contribution of influenza to excess mortality in the population presents substantial methodological challenges.AimIn a modelling study we combined environmental, epidemiological and laboratory surveillance data to estimate influenza-attributable mortality in Greece, over four seasons (2013/14 to 2016/17), specifically addressing the lag dimension and the confounding effect of temperature.MethodsAssociations of influenza type/subtype-specific incidence proxies and of daily mean temperature with mortality were estimated with a distributed-lag nonlinear model with 30 days of maximum lag, separately by age group (all ages, 15-64 and ≥ 65 years old). Total and weekly deaths attributable to influenza and cold temperatures were calculated.ResultsOverall influenza-attributable mortality was 23.6 deaths per 100,000 population per year (95% confidence interval (CI): 17.8 to 29.2), and varied greatly between seasons, by influenza type/subtype and by age group, with the vast majority occurring in persons aged ≥ 65 years. Most deaths were attributable to A(H3N2), followed by influenza B. During periods of A(H1N1)pdm09 circulation, weekly attributable mortality to this subtype among people ≥ 65 years old increased rapidly at first, but then fell to zero and even negative, suggesting a mortality displacement (harvesting) effect. Mortality attributable to cold temperatures was much higher than that attributable to influenza.ConclusionsStudies of influenza-attributable mortality need to consider distributed-lag effects, stratify by age group and adjust both for circulating influenza virus types/subtypes and daily mean temperatures, in order to produce reliable estimates. Our approach addresses these issues, is readily applicable in the context of influenza surveillance, and can be useful for other countries.

Effect of Early Oseltamivir Treatment on Mortality in Critically Ill Patients With Different Types of Influenza: A Multiseason Cohort Study.

BACKGROUND: The available evidence on whether neuraminidase inhibitors reduce mortality in patients with influenza is inconclusive and focuses solely on influenza A/H1N1pdm09. We assessed whether early oseltamivir treatment (≤48 hours from symptom onset) decreases mortality compared to late treatment in a large cohort of critically ill patients with influenza of all types. METHODS: The study included all adults with laboratory-confirmed influenza hospitalized in intensive care units (ICUs) in Greece over 8 seasons (2010-2011 to 2017-2018) and treated with oseltamivir. The association of early oseltamivir with mortality was assessed with log-binomial models and a competing risks analysis estimating cause-specific and subdistribution hazards for death and discharge. Effect estimates were stratified by influenza type and adjusted for multiple covariates. RESULTS: A total of 1330 patients were studied, of whom 622 (46.8%) died in the ICU. Among patients with influenza A/H3N2, early treatment was associated with significantly lower mortality (relative risk, 0.69 [95% credible interval {CrI}, .49-.94]; subdistribution hazard ratio, 0.58 [95% CrI, .37-.88]). This effect was purely due to an increased cause-specific hazard for discharge, whereas the cause-specific hazard for death was not increased. Among survivors, the median length of ICU stay was shorter with early treatment by 1.8 days (95% CrI, .5-3.5 days). No effect on mortality was observed for A/H1N1 and influenza B patients. CONCLUSIONS: Severely ill patients with suspected influenza should be promptly treated with oseltamivir, particularly when A/H3N2 is circulating. The efficacy of oseltamivir should not be assumed to be equal against all types of influenza.

Interventions to increase seasonal influenza vaccine coverage in healthcare workers: A systematic review and meta-regression analysis.

Influenza vaccination is recommended for healthcare workers (HCWs), but coverage is often low. We reviewed studies evaluating interventions to increase seasonal influenza vaccination coverage in HCWs, including a meta-regression analysis to quantify the effect of each component. Fourty-six eligible studies were identified. Domains conferring a high risk of bias were identified in most studies. Mandatory vaccination was the most effective intervention component (Risk Ratio of being unvaccinated [RRunvacc] = 0.18, 95% CI: 0.08-0.45), followed by "soft" mandates such as declination statements (RRunvacc = 0.64, 95% CI: 0.45-0.92), increased awareness (RRunvacc = 0.83, 95% CI: 0.71-0.97) and increased access (RRunvacc = 0.88, 95% CI: 0.78-1.00). For incentives the difference was not significant, while for education no effect was observed. Heterogeneity was substantial (τ(2) = 0.083). These results indicate that effective alternatives to mandatory HCWs influenza vaccination do exist, and need to be further explored in future studies.