Trends in management and outcomes of COVID patients admitted to a Swiss tertiary care hospital.

Two successive COVID-19 flares occurred in Switzerland in spring and autumn 2020. During these periods, therapeutic strategies have been constantly adapted based on emerging evidence. We aimed to describe these adaptations and evaluate their association with patient outcomes in a cohort of COVID-19 patients admitted to the hospital. Consecutive patients admitted to the Geneva Hospitals during two successive COVID-19 flares were included. Characteristics of patients admitted during these two periods were compared as well as therapeutic management including medications, respiratory support strategies and admission to the ICU and intermediate care unit (IMCU). A mutivariable model was computed to compare outcomes across the two successive waves adjusted for demographic characteristics, co-morbidities and severity at baseline. The main outcome was in-hospital mortality. Secondary outcomes included ICU admission, Intermediate care (IMCU) admission, and length of hospital stay. A total of 2'983 patients were included. Of these, 165 patients (16.3%, n = 1014) died during the first wave and 314 (16.0%, n = 1969) during the second (p = 0.819). The proportion of patients admitted to the ICU was lower in second wave compared to first (7.4 vs. 13.9%, p < 0.001) but their mortality was increased (33.6% vs. 25.5%, p < 0.001). Conversely, a greater proportion of patients was admitted to the IMCU in second wave compared to first (26.6% vs. 22.3%, p = 0.011). A third of patients received lopinavir (30.7%) or hydroxychloroquine (33.1%) during the first wave and none during second wave, while corticosteroids were mainly prescribed during second wave (58.1% vs. 9.1%, p < 0.001). In the multivariable analysis, a 25% reduction of mortality was observed during the second wave (HR 0.75; 95% confidence interval 0.59 to 0.96). Among deceased patients, 82.3% (78.2% during first wave and 84.4% during second wave) died without beeing admitted to the ICU. The proportion of patients with therapeutic limitations regarding ICU admission increased during the second wave (48.6% vs. 38.7%, p < 0.001). Adaptation of therapeutic strategies including corticosteroids therapy and higher admission to the IMCU to receive non-invasive respiratory support was associated with a reduction of hospital mortality in multivariable analysis, ICU admission and LOS during the second wave of COVID-19 despite an increased number of admitted patients. More patients had medical decisions restraining ICU admission during the second wave which may reflect better patient selection or implicit triaging.

Incidence of healthcare-associated coronavirus disease 2019 (COVID-19) in the state of Geneva.

An examination of all coronavirus disease 2019 (COVID-19) cases and patient movements in Geneva indicated important disease activity within the healthcare system since the beginning of the pandemic. We estimate that 4.3% of all COVID-19 cases were likely acquired within the healthcare system, contributing to 62% of the COVID-19-related deaths.

Cohort profile: SARS-CoV-2/COVID-19 hospitalised patients in Switzerland.

BACKGROUND: SARS-CoV-2/COVID-19, which emerged in China in late 2019, rapidly spread across the world with several million victims in 213 countries. Switzerland was severely hit by the virus, with 43,000 confirmed cases as of 1 September 2020. AIM: In cooperation with the Federal Office of Public Health, we set up a surveillance database in February 2020 to monitor hospitalised patients with COVID-19, in addition to their mandatory reporting system. METHODS: Patients hospitalised for more than 24 hours with a positive polymerase chain-reaction test, from 20 Swiss hospitals, are included. Data were collected in a customised case report form based on World Health Organisation recommendations and adapted to local needs. Nosocomial infections were defined as infections for which the onset of symptoms was more than 5 days after the patient’s admission date. RESULTS: As of 1 September 2020, 3645 patients were included. Most patients were male (2168, 59.5%), and aged between 50 and 89 years (2778, 76.2%), with a median age of 68 (interquartile range 54–79). Community infections dominated with 3249 (89.0%) reports. Comorbidities were frequently reported, with hypertension (1481, 61.7%), cardiovascular diseases (948, 39.5%) and diabetes (660, 27.5%) being the most frequent in adults; respiratory diseases and asthma (4, 21.1%), haematological and oncological diseases (3, 15.8%) were the most frequent in children. Complications occurred in 2679 (73.4%) episodes, mostly respiratory diseases (2470, 93.2% in adults; 16, 55.2% in children), and renal (681, 25.7%) and cardiac (631, 23.8%) complications for adults. The second and third most frequent complications in children affected the digestive system and the liver (7, 24.1%). A targeted treatment was given in 1299 (35.6%) episodes, mostly with hydroxychloroquine (989, 76.1%). Intensive care units stays were reported in 578 (15.8%) episodes. A total of 527 (14.5%) deaths were registered, all among adults. CONCLUSION: The surveillance system has been successfully initiated and provides a robust set of data for Switzerland by including about 80% (compared with official statistics) of SARS-CoV-2/COVID-19 hospitalised patients, with similar age and comorbidity distributions. It adds detailed information on the epidemiology, risk factors and clinical course of these cases and, therefore, is a valuable addition to the existing mandatory reporting.

Hospital Outcomes of Community-Acquired SARS-CoV-2 Omicron Variant Infection Compared With Influenza Infection in Switzerland.

Importance: With the ongoing COVID-19 pandemic, it is crucial to assess the current burden of disease of community-acquired SARS-CoV-2 Omicron variant in hospitalized patients to tailor appropriate public health policies. Comparisons with better-known seasonal influenza infections may facilitate such decisions. Objective: To compare the in-hospital outcomes of patients hospitalized with the SARS-CoV-2 Omicron variant with patients with influenza. Design, Setting, and Participants: This cohort study was based on a national COVID-19 and influenza registry. Hospitalized patients aged 18 years and older with community-acquired SARS-CoV-2 Omicron variant infection who were admitted between January 15 and March 15, 2022 (when B.1.1.529 Omicron predominance was >95%), and hospitalized patients with influenza A or B infection from January 1, 2018, to March 15, 2022, where included. Patients without a study outcome by August 30, 2022, were censored. The study was conducted at 15 hospitals in Switzerland. Exposures: Community-acquired SARS-CoV-2 Omicron variant vs community-acquired seasonal influenza A or B. Main Outcomes and Measures: Primary and secondary outcomes were defined as in-hospital mortality and admission to the intensive care unit (ICU) for patients with the SARS-CoV-2 Omicron variant or influenza. Cox regression (cause-specific and Fine-Gray subdistribution hazard models) was used to account for time-dependency and competing events, with inverse probability weighting to adjust for confounders with right-censoring at day 30. Results: Of 5212 patients included from 15 hospitals, 3066 (58.8%) had SARS-CoV-2 Omicron variant infection in 14 centers and 2146 patients (41.2%) had influenza A or B in 14 centers. Of patients with the SARS-CoV-2 Omicron variant, 1485 (48.4%) were female, while 1113 patients with influenza (51.9%) were female (P = .02). Patients with the SARS-CoV-2 Omicron variant were younger (median [IQR] age, 71 [53-82] years) than those with influenza (median [IQR] age, 74 [59-83] years; P < .001). Overall, 214 patients with the SARS-CoV-2 Omicron variant (7.0%) died during hospitalization vs 95 patients with influenza (4.4%; P < .001). The final adjusted subdistribution hazard ratio (sdHR) for in-hospital death for SARS-CoV-2 Omicron variant vs influenza was 1.54 (95% CI, 1.18-2.01; P = .002). Overall, 250 patients with the SARS-CoV-2 Omicron variant (8.6%) vs 169 patients with influenza (8.3%) were admitted to the ICU (P = .79). After adjustment, the SARS-CoV-2 Omicron variant was not significantly associated with increased ICU admission vs influenza (sdHR, 1.08; 95% CI, 0.88-1.32; P = .50). Conclusions and Relevance: The data from this prospective, multicenter cohort study suggest a significantly increased risk of in-hospital mortality for patients with the SARS-CoV-2 Omicron variant vs those with influenza, while ICU admission rates were similar.

SARS-CoV-2 seroprevalence study after the first wave among persons living and working in an overcrowded Swiss prison.

PURPOSE: Prisons can be epicentres of infectious diseases. However, empirical evidence on the impact of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic in prison is still scarce. This study aims to estimate the seroprevalence rates of anti-SARS-CoV-2 in the largest and most crowded Swiss prison and compare them with the seroprevalence rate in the general population. DESIGN/METHODOLOGY/APPROACH: A cross-sectional study was conducted in June 2020, one month after the first wave of SARS-CoV-2 in Switzerland. Groups included: people living in detention (PLDs) detained before the beginning of the pandemic (n = 116), PLDs incarcerated after the beginning of the pandemic (n = 61), prison staff and prison healthcare workers (n = 227) and a sample from the general population in the same time period (n = 3,404). The authors assessed anti-SARS-CoV-2 IgG antibodies. FINDINGS: PLDs who were incarcerated before the beginning of the pandemic had a significantly lower seroprevalence rate [0.9%, confidence interval (CI)95%: 0.1%-5.9%] compared to the general population (6.3%, CI 95%: 5.6-7.3%) (p = 0.041). The differences between PLDs who were incarcerated before and other groups were marginally significant (PLDs incarcerated after the beginning of the pandemic: 6.6%, CI 95%: 2.5%-16.6%, p = 0.063; prison staff CI 95%: 4.8%, 2.7%-8.6%, p = 0.093). The seroprevalence of prison staff was only slightly and non-significantly lower than that of the general population. ORIGINALITY/VALUE: During the first wave, despite overcrowding and interaction with the community, the prison was not a hotspot of SARS-CoV-2 infection. Preventive measures probably helped avoiding clusters of infection. The authors suggest that preventive measures that impact social welfare could be relaxed when overall circulation in the community is low to prevent the negative impact of isolation.

Comparison of prognostic scores for inpatients with COVID-19: a retrospective monocentric cohort study.

BACKGROUND: The SARS-CoV-2 pandemic led to a steep increase in hospital and intensive care unit (ICU) admissions for acute respiratory failure worldwide. Early identification of patients at risk of clinical deterioration is crucial in terms of appropriate care delivery and resource allocation. We aimed to evaluate and compare the prognostic performance of Sequential Organ Failure Assessment (SOFA), Quick Sequential Organ Failure Assessment (qSOFA), Confusion, Uraemia, Respiratory Rate, Blood Pressure and Age ≥65 (CURB-65), Respiratory Rate and Oxygenation (ROX) index and Coronavirus Clinical Characterisation Consortium (4C) score to predict death and ICU admission among patients admitted to the hospital for acute COVID-19 infection. METHODS AND ANALYSIS: Consecutive adult patients admitted to the Geneva University Hospitals during two successive COVID-19 flares in spring and autumn 2020 were included. Discriminative performance of these prediction rules, obtained during the first 24 hours of hospital admission, were computed to predict death or ICU admission. We further exluded patients with therapeutic limitations and reported areas under the curve (AUCs) for 30-day mortality and ICU admission in sensitivity analyses. RESULTS: A total of 2122 patients were included. 216 patients (10.2%) required ICU admission and 303 (14.3%) died within 30 days post admission. 4C score had the best discriminatory performance to predict 30-day mortality (AUC 0.82, 95% CI 0.80 to 0.85), compared with SOFA (AUC 0.75, 95% CI 0.72 to 0.78), qSOFA (AUC 0.59, 95% CI 0.56 to 0.62), CURB-65 (AUC 0.75, 95% CI 0.72 to 0.78) and ROX index (AUC 0.68, 95% CI 0.65 to 0.72). ROX index had the greatest discriminatory performance (AUC 0.79, 95% CI 0.76 to 0.83) to predict ICU admission compared with 4C score (AUC 0.62, 95% CI 0.59 to 0.66), CURB-65 (AUC 0.60, 95% CI 0.56 to 0.64), SOFA (AUC 0.74, 95% CI 0.71 to 0.77) and qSOFA (AUC 0.59, 95% CI 0.55 to 0.62). CONCLUSION: Scores including age and/or comorbidities (4C and CURB-65) have the best discriminatory performance to predict mortality among inpatients with COVID-19, while scores including quantitative assessment of hypoxaemia (SOFA and ROX index) perform best to predict ICU admission. Exclusion of patients with therapeutic limitations improved the discriminatory performance of prognostic scores relying on age and/or comorbidities to predict ICU admission.

Reconstruction of transmission chains of SARS-CoV-2 amidst multiple outbreaks in a geriatric acute-care hospital: a combined retrospective epidemiological and genomic study.

Background: There is ongoing uncertainty regarding transmission chains and the respective roles of healthcare workers (HCWs) and elderly patients in nosocomial outbreaks of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in geriatric settings. Methods: We performed a retrospective cohort study including patients with nosocomial coronavirus disease 2019 (COVID-19) in four outbreak-affected wards, and all SARS-CoV-2 RT-PCR positive HCWs from a Swiss university-affiliated geriatric acute-care hospital that admitted both Covid-19 and non-Covid-19 patients during the first pandemic wave in Spring 2020. We combined epidemiological and genetic sequencing data using a Bayesian modelling framework, and reconstructed transmission dynamics of SARS-CoV-2 involving patients and HCWs, to determine who infected whom. We evaluated general transmission patterns according to case type (HCWs working in dedicated Covid-19 cohorting wards: HCWcovid; HCWs working in non-Covid-19 wards where outbreaks occurred: HCWoutbreak; patients with nosocomial Covid-19: patientnoso) by deriving the proportion of infections attributed to each case type across all posterior trees and comparing them to random expectations. Results: During the study period (1 March to 7 May 2020), we included 180 SARS-CoV-2 positive cases: 127 HCWs (91 HCWcovid, 36 HCWoutbreak) and 53 patients. The attack rates ranged from 10% to 19% for patients, and 21% for HCWs. We estimated that 16 importation events occurred with high confidence (4 patients, 12 HCWs) that jointly led to up to 41 secondary cases; in six additional cases (5 HCWs, 1 patient), importation was possible with a posterior probability between 10% and 50%. Most patient-to-patient transmission events involved patients having shared a ward (95.2%, 95% credible interval [CrI] 84.2%-100%), in contrast to those having shared a room (19.7%, 95% CrI 6.7%-33.3%). Transmission events tended to cluster by case type: patientnoso were almost twice as likely to be infected by other patientnoso than expected (observed:expected ratio 2.16, 95% CrI 1.17-4.20, p=0.006); similarly, HCWoutbreak were more than twice as likely to be infected by other HCWoutbreak than expected (2.72, 95% CrI 0.87-9.00, p=0.06). The proportion of infectors being HCWcovid was as expected as random. We found a trend towards a greater proportion of high transmitters (≥2 secondary cases) among HCWoutbreak than patientnoso in the late phases (28.6% vs. 11.8%) of the outbreak, although this was not statistically significant. Conclusions: Most importation events were linked to HCW. Unexpectedly, transmission between HCWcovid was more limited than transmission between patients and HCWoutbreak. This finding highlights gaps in infection control and suggests the possible areas of improvements to limit the extent of nosocomial transmission. Funding: This study was supported by a grant from the Swiss National Science Foundation under the NRP78 funding scheme (Grant no. 4078P0_198363).

Infectious viral load in unvaccinated and vaccinated individuals infected with ancestral, Delta or Omicron SARS-CoV-2.

Infectious viral load (VL) expelled as droplets and aerosols by infected individuals partly determines transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). RNA VL measured by qRT-PCR is only a weak proxy for infectiousness. Studies on the kinetics of infectious VL are important to understand the mechanisms behind the different transmissibility of SARS-CoV-2 variants and the effect of vaccination on transmission, which allows guidance of public health measures. In this study, we quantified infectious VL in individuals infected with SARS-CoV-2 during the first five symptomatic days by in vitro culturability assay in unvaccinated or vaccinated individuals infected with pre-variant of concern (pre-VOC) SARS-CoV-2, Delta or Omicron BA.1. Unvaccinated individuals infected with pre-VOC SARS-CoV-2 had lower infectious VL than Delta-infected unvaccinated individuals. Full vaccination (defined as >2 weeks after receipt of the second dose during the primary vaccination series) significantly reduced infectious VL for Delta breakthrough cases compared to unvaccinated individuals. For Omicron BA.1 breakthrough cases, reduced infectious VL was observed only in boosted but not in fully vaccinated individuals compared to unvaccinated individuals. In addition, infectious VL was lower in fully vaccinated Omicron BA.1-infected individuals compared to fully vaccinated Delta-infected individuals, suggesting that mechanisms other than increased infectious VL contribute to the high infectiousness of SARS-CoV-2 Omicron BA.1. Our findings indicate that vaccines may lower transmission risk and, therefore, have a public health benefit beyond the individual protection from severe disease.

Evolution of COVID-19 mortality over time: results from the Swiss hospital surveillance system (CH-SUR).

BACKGROUND: When the periods of time during and after the first wave of the ongoing SARS-CoV-2/COVID-19 pandemic in Europe are compared, the associated COVID-19 mortality seems to have decreased substantially. Various factors could explain this trend, including changes in demographic characteristics of infected persons and the improvement of case management. To date, no study has been performed to investigate the evolution of COVID-19 in-hospital mortality in Switzerland, while also accounting for risk factors. METHODS: We investigated the trends in COVID-19-related mortality (in-hospital and in-intermediate/intensive-care) over time in Switzerland, from February 2020 to June 2021, comparing in particular the first and the second wave. We used data from the COVID-19 Hospital-based Surveillance (CH-SUR) database. We performed survival analyses adjusting for well-known risk factors of COVID-19 mortality (age, sex and comorbidities) and accounting for competing risk. RESULTS: Our analysis included 16,984 patients recorded in CH-SUR, with 2201 reported deaths due to COVID-19 (13.0%). We found that overall in-hospital mortality was lower during the second wave of COVID-19 than in the first wave (hazard ratio [HR] 0.70, 95% confidence interval [CI] 0.63- 0.78; p <0.001), a decrease apparently not explained by changes in demographic characteristics of patients. In contrast, mortality in intermediate and intensive care significantly increased in the second wave compared with the first wave (HR 1.25, 95% CI 1.05-1.49; p = 0.029), with significant changes in the course of hospitalisation between the first and the second wave. CONCLUSION: We found that, in Switzerland, COVID-19 mortality decreased among hospitalised persons, whereas it increased among patients admitted to intermediate or intensive care, when comparing the second wave to the first wave. We put our findings in perspective with changes over time in case management, treatment strategy, hospital burden and non-pharmaceutical interventions. Further analyses of the potential effect of virus variants and of vaccination on mortality would be crucial to have a complete overview of COVID-19 mortality trends throughout the different phases of the pandemic.

Hospital outcomes of community-acquired COVID-19 versus influenza: Insights from the Swiss hospital-based surveillance of influenza and COVID-19.

BackgroundSince the onset of the COVID-19 pandemic, the disease has frequently been compared with seasonal influenza, but this comparison is based on little empirical data.AimThis study compares in-hospital outcomes for patients with community-acquired COVID-19 and patients with community-acquired influenza in Switzerland.MethodsThis retrospective multi-centre cohort study includes patients > 18 years admitted for COVID-19 or influenza A/B infection determined by RT-PCR. Primary and secondary outcomes were in-hospital mortality and intensive care unit (ICU) admission for patients with COVID-19 or influenza. We used Cox regression (cause-specific and Fine-Gray subdistribution hazard models) to account for time-dependency and competing events with inverse probability weighting to adjust for confounders.ResultsIn 2020, 2,843 patients with COVID-19 from 14 centres were included. Between 2018 and 2020, 1,381 patients with influenza from seven centres were included; 1,722 (61%) of the patients with COVID-19 and 666 (48%) of the patients with influenza were male (p < 0.001). The patients with COVID-19 were younger (median 67 years; interquartile range (IQR): 54-78) than the patients with influenza (median 74 years; IQR: 61-84) (p < 0.001). A larger percentage of patients with COVID-19 (12.8%) than patients with influenza (4.4%) died in hospital (p < 0.001). The final adjusted subdistribution hazard ratio for mortality was 3.01 (95% CI: 2.22-4.09; p < 0.001) for COVID-19 compared with influenza and 2.44 (95% CI: 2.00-3.00, p < 0.001) for ICU admission.ConclusionCommunity-acquired COVID-19 was associated with worse outcomes compared with community-acquired influenza, as the hazards of ICU admission and in-hospital death were about two-fold to three-fold higher.

Management and outcomes of patients on maintenance dialysis during the first and second wave of the COVID-19 pandemic in Geneva, Switzerland.

BACKGROUND: Patients on maintenance dialysis are at high risk for serious complications from COVID-19 infection, including death. We present an overview of local experience with dialysis unit management and reorganisation, local epidemiology and outcomes during the COVID-19 outbreak in Geneva, Switzerland, where SARS-CoV-2 incidence was one of the highest in Europe. METHODS: All SARS-CoV-2-positive outpatients on maintenance dialysis were transferred from their usual dialysis facility to the Geneva University Hospitals dialysis unit to avoid creation of new clusters of transmission. Within this unit, appropriate mitigation measures were enforced, as suggested by the institutional team for prevention and control of infectious diseases. RESULTS: From 25 February to 31 December 2020, 82 of 279 patients on maintenance dialysis tested positive for SARS-CoV-2 during two distinct waves, with an incidence rate of 73 cases per 100,000 person-days during the first wave and 342 cases per 100,000 during the second wave, approximately four- to six-fold higher than the general population. The majority of infections (55%) during both waves were traced to clusters. Most infections (62%) occurred in men. Sixteen patients (34%) died from COVID-19 related complications. Deceased patients were older and had a lower body mass index as compared with patients who survived the infection. CONCLUSION: SARS-CoV-2 is associated with high infection and fatality rates in the dialysis population. Strict mitigation measures seemed to be effective in controlling infection spread among patients on maintenance dialysis outside of clusters. Large scale epidemiological studies are needed to assess the efficacy of preventive measures in decreasing infection and mortality rates within the dialysis population.

Risk factors for severe outcomes for COVID-19 patients hospitalised in Switzerland during the first pandemic wave, February to August 2020: prospective observational cohort study.

BACKGROUND: As clinical signs of COVID-19 differ widely among individuals, from mild to severe, the definition of risk groups has important consequences for recommendations to the public, control measures and patient management, and needs to be reviewed regularly. AIM: The aim of this study was to explore risk factors for in-hospital mortality and intensive care unit (ICU) admission for hospitalised COVID-19 patients during the first epidemic wave in Switzerland, as an example of a country that coped well during the first wave of the pandemic. METHODS: This study included all (n = 3590) adult polymerase chain reaction (PCR)-confirmed hospitalised patients in 17 hospitals from the hospital-based surveillance of COVID-19 (CH-Sur) by 1 September 2020. We calculated univariable and multivariable (adjusted) (1) proportional hazards (Fine and Gray) survival regression models and (2) logistic regression models for in-hospital mortality and admission to ICU, to evaluate the most common comorbidities as potential risk factors. RESULTS AND DISCUSSION: We found that old age was the strongest factor for in-hospital mortality after having adjusted for gender and the considered comorbidities (hazard ratio [HR] 2.46, 95% confidence interval [CI] 2.33−2.59 and HR 5.6 95% CI 5.23−6 for ages 65 and 80 years, respectively). In addition, male gender remained an important risk factor in the multivariable models (HR 1.47, 95% CI 1.41−1.53). Of all comorbidities, renal disease, oncological pathologies, chronic respiratory disease, cardiovascular disease (but not hypertension) and dementia were also risk factors for in-hospital mortality. With respect to ICU admission risk, the pattern was different, as patients with higher chances of survival might have been admitted more often to ICU. Male gender (OR 1.91, 95% CI 1.58−2.31), hypertension (OR  1.3, 95% CI 1.07−1.59) and age 55–79 years (OR 1.15, 95% CI 1.06−1.26) are risk factors for ICU admission. Patients aged 80+ years, as well as patients with dementia or with liver disease were admitted less often to ICU. CONCLUSION: We conclude that increasing age is the most important risk factor for in-hospital mortality of hospitalised COVID-19 patients in Switzerland, along with male gender and followed by the presence of comorbidities such as renal diseases, chronic respiratory or cardiovascular disease, oncological malignancies and dementia. Male gender, hypertension and age between 55 and 79 years are, however, risk factors for ICU admission. Mortality and ICU admission need to be considered as separate outcomes when investigating risk factors for pandemic control measures and for hospital resources planning.

Severe acute respiratory coronavirus virus 2 (SARS-CoV-2) seroconversion and occupational exposure of employees at a Swiss university hospital: A large longitudinal cohort study.

BACKGROUND: The dynamics of coronavirus disease 2019 (COVID-19) seroconversion of hospital employees are understudied. We measured the proportion of seroconverted employees and evaluated risk factors for seroconversion during the first pandemic wave. METHODS: In this prospective cohort study, we recruited Geneva University Hospitals employees and sampled them 3 times, every 3 weeks from March 30 to June 12, 2020. We measured the proportion of seroconverted employees and determined prevalence ratios of risk factors for seroconversion using multivariate mixed-effects Poisson regression models. RESULTS: Overall, 3,421 participants (29% of all employees) were included, with 92% follow-up. The proportion of seroconverted employees increased from 4.4% (95% confidence interval [CI], 3.7%-5.1%) at baseline to 8.5% [(95% CI, 7.6%-9.5%) at the last visit. The proportions of seroconverted employees working in COVID-19 geriatrics and rehabilitation (G&R) wards (32.3%) and non-COVID-19 G&R wards (12.3%) were higher compared to office workers (4.9%) at the last visit. Only nursing assistants had a significantly higher risk of seroconversion compared to office workers (11.7% vs 4.9%; P = .006). Significant risk factors for seroconversion included the use of public transportation (adjusted prevalence ratio, 1.59; 95% CI, 1.25-2.03), known community exposure to severe acute respiratory coronavirus virus 2 (2.80; 95% CI, 2.22-3.54), working in a ward with a nosocomial COVID outbreak (2.93; 95% CI, 2.27-3.79), and working in a COVID-19 G&R ward (3.47; 95% CI, 2.45-4.91) or a non-COVID-19 G&R ward (1.96; 95% CI, 1.46-2.63). We observed an association between reported use of respirators and lower risk of seroconversion (0.73; 95% CI, 0.55-0.96). CONCLUSION: Additional preventive measures should be implemented to protect employees in G&R wards. Randomized trials on the protective effect of respirators are urgently needed.

Impact of an e-learning module on personal protective equipment knowledge in student paramedics: a randomized controlled trial.

BACKGROUND: Prehospital professionals such as emergency physicians or paramedics must be able to choose and adequately don and doff personal protective equipment (PPE) in order to avoid COVID-19 infection. Our aim was to evaluate the impact of a gamified e-learning module on adequacy of PPE in student paramedics. METHODS: This was a web-based, randomized 1:1, parallel-group, triple-blind controlled trial. Student paramedics from three Swiss schools were invited to participate. They were informed they would be presented with both an e-learning module and an abridged version of the current regional prehospital COVID-19 guidelines, albeit not in which order. After a set of 22 questions designed to assess baseline knowledge, the control group was shown the guidelines before answering a set of 14 post-intervention questions. The e-learning group was shown the gamified e-learning module right after the guidelines, and before answering post-intervention questions. The primary outcome was the difference in the percentage of adequate choices of PPE before and after the intervention. RESULTS: The participation rate was of 71% (98/138). A total of 90 answer sets was analyzed. Adequate choice of PPE increased significantly both in the control (50% [33;83] vs 25% [25;50], P = .013) and in the e-learning group (67% [50;83] vs 25% [25;50], P = .001) following the intervention. Though the median of the difference was higher in the e-learning group, there was no statistically significant superiority over the control (33% [0;58] vs 17% [- 17;42], P = .087). The e-learning module was of greatest benefit in the subgroup of student paramedics who were actively working in an ambulance company (42% [8;58] vs 25% [- 17;42], P = 0.021). There was no significant effect in student paramedics who were not actively working in an ambulance service (0% [- 25;33] vs 17% [- 8;50], P = .584). CONCLUSIONS: The use of a gamified e-learning module increases the rate of adequate choice of PPE only among student paramedics actively working in an ambulance service. In this subgroup, combining this teaching modality with other interventions might help spare PPE and efficiently protect against COVID-19 infection.

Nosocomial transmission and outbreaks of coronavirus disease 2019: the need to protect both patients and healthcare workers.

OBJECTIVES: To compile current published reports on nosocomial outbreaks of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), evaluate the role of healthcare workers (HCWs) in transmission, and evaluate outbreak management practices. METHODS: Narrative literature review. SHORT CONCLUSION: The coronavirus disease 2019 (COVID-19) pandemic has placed a large burden on hospitals and healthcare providers worldwide, which increases the risk of nosocomial transmission and outbreaks to "non-COVID" patients or residents, who represent the highest-risk population in terms of mortality, as well as HCWs. To date, there are several reports on nosocomial outbreaks of SARS-CoV-2, and although the attack rate is variable, it can be as high as 60%, with high mortality. There is currently little evidence on transmission dynamics, particularly using genomic sequencing, and the role of HCWs in initiating or amplifying nosocomial outbreaks is not elucidated. There has been a paradigm shift in management practices of viral respiratory outbreaks, that includes widespread testing of patients (or residents) and HCWs, including asymptomatic individuals. These expanded testing criteria appear to be crucial in identifying and controlling outbreaks.

Effect of an E-Learning Module on Personal Protective Equipment Proficiency Among Prehospital Personnel: Web-Based Randomized Controlled Trial.

BACKGROUND: To avoid misuse of personal protective equipment (PPE), ensure health care workers' safety, and avoid shortages, effective communication of up-to-date infection control guidelines is essential. As prehospital teams are particularly at risk of contamination given their challenging work environment, a specific gamified electronic learning (e-learning) module targeting this audience might provide significant advantages as it requires neither the presence of learners nor the repetitive use of equipment for demonstration. OBJECTIVE: The aim of this study was to evaluate whether a gamified e-learning module could improve the rate of adequate PPE choice by prehospital personnel in the context of the coronavirus disease (COVID-19) pandemic. METHODS: This was an individual-level randomized, controlled, quadruple-blind (investigators, participants, outcome assessors, and data analysts) closed web-based trial. All emergency prehospital personnel working in Geneva, Switzerland, were eligible for inclusion, and were invited to participate by email in April 2020. Participants were informed that the study aim was to assess their knowledge regarding PPE, and that they would be presented with both the guidelines and the e-learning module, though they were unaware that there were two different study paths. All participants first answered a preintervention quiz designed to establish their profile and baseline knowledge. The control group then accessed the guidelines before answering a second set of questions, and were then granted access to the e-learning module. The e-learning group was shown the e-learning module right after the guidelines and before answering the second set of questions. RESULTS: Of the 291 randomized participants, 176 (60.5%) completed the trial. There was no significant difference in baseline knowledge between groups. Though the baseline proportion of adequate PPE choice was high (75%, IQR 50%-75%), participants' description of the donning sequence was in most cases incorrect. After either intervention, adequate choice of PPE increased significantly in both groups (P<.001). Though the median of the difference in the proportion of correct answers was slightly higher in the e-learning group (17%, IQR 8%-33% versus 8%, IQR 8%-33%), the difference was not statistically significant (P=.27). Confidence in the ability to use PPE was maintained in the e-learning group (P=.27) but significantly decreased in the control group (P=.04). CONCLUSIONS: Among prehospital personnel with an already relatively high knowledge of and experience with PPE use, both web-based study paths increased the rate of adequate choice of PPE. There was no major added value of the gamified e-learning module apart from preserving participants' confidence in their ability to correctly use PPE.

Teaching Adequate Prehospital Use of Personal Protective Equipment During the COVID-19 Pandemic: Development of a Gamified e-Learning Module.

BACKGROUND: The coronavirus disease (COVID-19) pandemic has led to increased use of personal protective equipment (PPE). Adequate use of this equipment is more critical than ever because the risk of shortages must be balanced against the need to effectively protect health care workers, including prehospital personnel. Specific training is therefore necessary; however, the need for social distancing has markedly disrupted the delivery of continuing education courses. Electronic learning (e-learning) may provide significant advantages because it requires neither the physical presence of learners nor the repetitive use of equipment for demonstration. OBJECTIVE: Inclusion of game mechanics, or "gamification," has been shown to increase knowledge and skill acquisition. The objective of this research was to develop a gamified e-learning module to interactively deliver concepts and information regarding the correct choice and handling of PPE. METHODS: The SERES framework was used to define and describe the development process, including scientific and design foundations. After we defined the target audience and learning objectives by interviewing the stakeholders, we searched the scientific literature to establish relevant theoretical bases. The learning contents were validated by infection control and prehospital experts. Learning mechanics were then determined according to the learning objectives, and the content that could benefit from the inclusion of game mechanics was identified. RESULTS: The literature search resulted in the selection and inclusion of 12 articles. In addition to gamification, pretesting, feedback, avoiding content skipping, and demonstrations using embedded videos were used as learning mechanics. Gamification was used to enhance the interactivity of the PPE donning and doffing sequences, which presented the greatest learning challenges. The module was developed with Articulate Storyline 3 to ensure that it would be compatible with a wide array of devices, as this software generates HTML5-compatible output that can be accessed on smartphones, tablets, and regular computers as long as a recent browser is available. CONCLUSIONS: A gamified e-learning module designed to promote better knowledge and understanding of PPE use among prehospital health care workers was created by following the SERES framework. The impact of this module should now be assessed by means of a randomized controlled trial.