Search

Abstract Background In the initial phase of the SARS-CoV-2 pandemic, masking has been widely accepted in healthcare institutions to mitigate the risk of healthcare-associated infection. Evidence, however, is still scant and the role of masks in preventing healthcare-associated SARS-CoV-2 acquisition remains unclear.We investigated the association of variation in institutional mask policies with healthcare-associated SARS-CoV-2 infections in acute care hospitals in Switzerland during the BA.4/5 2022 wave. Methods SARS-CoV-2 infections in hospitalized patients between June 1 and September 5, 2022, were obtained from the “Hospital-based surveillance of COVID-19 in Switzerland”-database and classified as healthcare- or community-associated based on time of disease onset. Institutions provided information regarding institutional masking policies for healthcare workers and other prevention policies. The percentage of healthcare-associated SARS-CoV-2 infections was calculated per institution and per type of mask policy. The association of healthcare-associated SARS-CoV-2 infections with mask policies was tested using a negative binominal mixed-effect model. Results We included 2’980 SARS-CoV-2 infections from 13 institutions, 444 (15%) were classified as healthcare-associated. Between June 20 and June 30, 2022, six (46%) institutions switched to a more stringent mask policy. The percentage of healthcare-associated infections subsequently declined in institutions with policy switch but not in the others. In particular, the switch from situative masking (standard precautions) to general masking of HCW in contact with patients was followed by a strong reduction of healthcare-associated infections (rate ratio 0.39, 95% CI 0.30–0.49). In contrast, when compared across hospitals, the percentage of health-care associated infections was not related to mask policies. Conclusions Our findings suggest switching to a more stringent mask policy may be beneficial during increases of healthcare-associated SARS-CoV-2 infections at an institutional level.

BACKGROUND: The COVID-19 pandemic has placed unprecedented pressure on hospitals worldwide. In such a context of tension in healthcare systems, efficiently allocating hospital resources is a crucial aspect of crisis management. The aim of this study was to describe the clinical characteristics of readmitted patients and to determine risk factors for hospital readmission using data from the Swiss COVID-19 Hospital-Based Surveillance system (CH-SUR). METHODS: We investigated hospital readmissions within 60 days after discharge of patients from the CH-SUR surveillance system with a first hospitalisation between 1 December 2020 and 1 December 2021. Only community-acquired cases were considered. We compared the baseline characteristics of readmitted and non-readmitted patients. We performed univariable and multivariable logistic regression analyses to investigate the risk factors for hospital readmission. FINDINGS: Of the 8039 eligible patients, 239 (3.0%, 95% confidence interval [CI] 2.6–3.3%) were readmitted to hospital within 60 days of discharge, with no significant variations observed over the study period; 80% of all readmissions occurred within 10 days of discharge of the index hospital stay. Based on our multivariable logistic regression models, factors increasing the odds of hospital readmission were age ≥65 years (odds ratio [OR] 1.63, 95% CI 1.24–2.15), male sex (OR 1.47, 95% CI 1.12–1.93), being discharged to home after first hospitalisation (OR 1.77, 95% CI 1.19–2.62), having oncological pathology (OR 1.82, 95% CI 1.27–2.61) and being immunosuppressed (OR 2.34, 95% CI 1.67–3.29). INTERPRETATIONS: Age, sex, cardiovascular diseases, oncological pathologies and immunosuppression were the main risk factors identified for hospital readmission.

Abstract 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

AIMS OF THE STUDY: Remdesivir has shown benefits against COVID-19. However, it remains unclear whether, to what extent, and among whom remdesivir can reduce COVID-19-related mortality. We explored whether the treatment response to remdesivir differed by patient characteristics. METHODS: We analysed data collected from a hospital surveillance study conducted in 21 referral hospitals in Switzerland between 2020 and 2022. We applied model-based recursive partitioning to group patients by the association between treatment levels and mortality. We included either treatment (levels: none, remdesivir within 7 days of symptom onset, remdesivir after 7 days, or another treatment), age and sex, or treatment only as regression variables. Candidate partitioning variables included a range of risk factors and comorbidities (and age and sex unless included in regression). We repeated the analyses using local centring to correct the results for the propensity to receive treatment. RESULTS: Overall (n = 21,790 patients), remdesivir within 7 days was associated with increased mortality (adjusted hazard ratios 1.28–1.54 versus no treatment). The CURB-65 score caused the most instability in the regression parameters of the model. When adjusted for age and sex, patients receiving remdesivir within 7 days of onset had higher mortality than those not treated in all identified eight patient groups. When age and sex were included as partitioning variables instead, the number of groups increased to 19–20; in five to six of those branches, mortality was lower among patients who received early remdesivir. Factors determining the groups where remdesivir was potentially beneficial included the presence of oncological comorbidities, male sex, and high age. CONCLUSIONS: Some subgroups of patients, such as individuals with oncological comorbidities or elderly males, may benefit from remdesivir.

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.

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).

Abstract 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.

Abstract 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.

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

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.

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.

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.

Abstract The International Consortium for Prevention and Infection Control (ICPIC) organises a biannual conference (ICPIC) on various subjects related to infection prevention, treatment and control. During ICPIC 2015, held in Geneva in June 2015, a full one-day session focused on the 2014–2015 Ebola virus disease (EVD) outbreak in West Africa. This article is a non-exhaustive compilation of these discussions. It concentrates on lessons learned and imagining a way forward for the communities most affected by the epidemic. The reader can access video recordings of all lectures delivered during this one-day session, as referenced. Topics include the timeline of the international response, linkages between the dynamics of the epidemic and infection prevention and control, the importance of community engagement, and updates on virology, diagnosis, treatment and vaccination issues. The paper also includes discussions from public health, infectious diseases, critical care and infection control experts who cared for patients with EVD in Africa, in Europe, and in the United Sates and were involved in Ebola preparedness in both high- and low-resource settings and countries. This review concludes that too little is known about the pathogenesis and treatment of EVD, therefore basic and applied research in this area are urgently required. Furthermore, it is clear that epidemic preparedness needs to improve globally, in particular through the strengthening of health systems at local and national levels. There is a strong need for culturally sensitive approaches to public health which could be designed and delivered by social scientists and medical professionals working together. As of December 2015, this epidemic killed more than 11,000 people and infected more than 28,000; it has also generated more than 17,000 survivors and orphans, many of whom face somatic and psychological complications. The continued treatment and rehabilitation of these people is a public health priority, which also requires an integration of specific medical and social science approaches, not always available in West Africa.

IntroductionHand hygiene is a key component of infection control in healthcare. WHO recommends that healthcare workers perform six specific poses during each hand hygiene action. SureWash (Glanta Ltd, Dublin, Ireland) is a novel device that uses video-measurement technology and immediate feedback to teach this technique. We assessed the impact of self-directed SureWash use on healthcare worker hand hygiene technique and evaluated the device's diagnostic capacity.MethodsA controlled before-after study: subjects in Group A were exposed to the SureWash for four weeks followed by Group B for 12 weeks. Each subject's hand hygiene technique was assessed by blinded observers at baseline (T0) and following intervention periods (T1 and T2). Primary outcome was performance of a complete hand hygiene action, requiring all six poses during an action lasting ≥20 seconds. The number of poses per hand hygiene action (maximum 6) was assessed in a post-hoc analysis. SureWash's diagnostic capacity compared to human observers was assessed using ROC curve analysis.ResultsThirty-four and 29 healthcare workers were recruited to groups A and B, respectively. No participants performed a complete action at baseline. At T1, one Group A participant and no Group B participants performed a complete action. At baseline, the median number of poses performed per action was 2.0 and 1.0 in Groups A and B, respectively (p = 0.12). At T1, the number of poses per action was greater in Group A (post-intervention) than Group B (control): median 3.8 and 2.0, respectively (pDiscussionWhile no impact on complete actions was demonstrated, SureWash significantly increased the number of poses per hand hygiene action and demonstrated good diagnostic capacity.