Hospital-based surveillance of COVID-19 in Switzerland

In 2018, an Influenza hospital based sentinel surveillance system was established under the partnership of the Geneva University Hospitals (HUG), Institute of Global Health at the University of Geneva (UNIGE), and the Federal Office of Public Health (FOPH) to supplement existing monitoring systems in Switzerland. During the height of the COVID-19 pandemic, this surveillance system was quickly adapted to also capture hospitalizations related to laboratory-confirmed SARS-CoV-2 infections.

Since March 1st 2020; just four days after the first confirmed COVID-19 case in Switzerland, the COVID-19 Hospital Based Surveillance system (CH-SUR) has been recording detailed clinical and epidemiological information on the burden of disease, clinical course, and risk factors. As of November 15th 2020, both CH-SUR and the Influenza surveillance project have been merged into a single registry, modified to account for both diseases and easily include other respiratory viruses if needed. There are currently 6 hospitals actively participating in CH-SUR. A detailed list of participating university and cantonal hospitals may be reviewed below.

The FOPH makes weekly reports on Influenza and COVID-19 available to the public in English, French, German, and Italian. For more details and access to the reports, visit the FOPH website: Monitoring (admin.ch)

OBJECTIVES

The primary aim of this project is to provide an emergency surveillance tool to the Federal Office of Public Health in order to monitor the COVID-19 distribution in Switzerland.

As a secondary goal, we wish to test the surveillance system implemented for Influenza to identify whether it can be easily used for other infectious diseases and outbreaks. This will allow for the collection of quality and trustworthy data which will be regularly checked for inconsistencies.

Participants

6 Swiss hospitals are currently participating in this surveillance system: 

• Hôpitaux Universitaires de Genève (HUG) in Geneva - GE
• Kantonsspital Sankt Gallen (KSSG) in Sankt Gallen - SG
• Universitätspital Basel (USB) in Basel - BS
• Luzerner Kantonsspital (LUKS) in Luzern - LU
• Spital Thurgau (STGAG) in Münsterlingen - TG
• Hirslanden Clinic St Ana - Luzern in Luzern - LU

Previous participants:

• Kantonsspital Niedwald (KSNW) in Stans - NW  (until 28/02/2022)
• Kantonsspital Aarau (KSA - pediatrics only) in Aarau - AG (until 31/01/2023)
• Hirslanden AG Zürich (HAGZH) in Zürich - ZH  (in-kind participation until 31/01/2023)
• Kantonsspital Winterthur (KSW - paediatrics only) in Winterthur - ZH (until 31/01/2023)
• Centre Hospitalier Universitaire Vaudois (CHUV) in Lausanne - VD (until 30/11/2023)
• Ente Ospedaliero Cantonale (EOC) in Lugano - TI (until 30/11/2023)
• Hôpital du Valais (HVS) in Sion - VS (until 30/11/2023)
• Inselspital Bern (INSEL) in Bern - BE (until 30/11/2023)
• Kinderspital Zürich (KISPI USZ) in Zürich - ZH (until 30/11/2023)
• Universitätspital Basel (USB) in Basel - BS (until 30/11/2023)
• Universitätspital Zürich (USZ) in Zürich - ZH (until 30/11/2023)
• Kantonsspital Graubuenden (KSGR) in Chur - GR (until 30/11/2023)
• Kindersspital St. Gallen (OKS) in Sankt Gallen - SG (until 30/11/2023)
• Hôpital de Fribourg (HFR - paediatrics only) in Fribourg - FR (until 30/11/2023)
• Spitaeler Schaffhausen (Spitaeler SH) in Schaffhausen - SH (until 30/11/2023)

ACCESSING DATA

Until December 31st 2023, the responsibility for ensuring access to the data was held by the ISG, in accordance with the provisions of a study protocol and a study agreement signed by all participating entities and approved by the Swissethics Comitees. From January 1 onward, the FOPH assumed this responsibility. Therefore, any requests for data access should be sent directly to them at the email address mt.data(at)bag.admin.ch.

ACCEPTED PROJECTS

(Accepted projects up to December 31st, 2023)

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

Lead: Amaury Thiabaud (ISG) & Anne Iten (HUG) 

Status: Published in Swiss Medical Weekly

Background. SARS-CoV-2/COVID-19, which emerged in China in late 2019, rapidly spread across the world causing several million victims in 213 countries. Switzerland was severely hit by the virus, with 43’000 confirmed cases as of September 1st, 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 PCR test, from 20 Swiss hospitals, are included. Data collection follows a custom Case Report Form based on WHO recommendations and adapted to local needs. Nosocomial infections were defined as infections for which the onset of symptoms started more than 5 days after the patient’s admission date.

Results. As of September 1st, 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 (IQR 54-79). Community infections dominated with 3249 (89.0%) reports. Comorbidities were frequently reported: 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%) being the most frequent in children. Complications occurred in 2679 (73.4%) episodes, mostly for respiratory diseases (2470 - 93.2% in adults, 16 – 55.2% in children), renal (681 – 25.7%) and cardiac (631 – 23.8%) complication 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. 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% of SARS-CoV-2/COVID-19 hospitalised patients compared to official statistics, with similar age and comorbidities 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.

Risk factors for severe outcome for 3264 COVID-19 patients hospitalized in Switzerland, February to June 2020: prospective observational cohort study 

Lead :Gertraud Schuepbach (VetSuisse/BAG) & Beatriz Vidondo (VetSuisse)

Status: Published in Swiss Medical Weekly

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.

COVID-19: More than "a little flu"? Insights from the Swiss hospital-based surveillance of Influenza and COVID-19

Lead: Georg Fröhlich (INSEL) & Rami Sommerstein (INSEL) 

Status: Published in Eurosurveillance

Background and study aim
It has been a matter of ongoing debate, whether in-hospital outcomes of infection with SARS-CoV-2 are comparable to outcomes of infection with Influenza A/B virus. Therefore, this study aims to compare adverse outcomes in patients, who were hospitalized with SARS-CoV-2 and/or Influenza A/B virus infection. To the best of our knowledge, only a few small case series were reported to directly compare outcomes for Coronavirus disease 2019 (COVID-19) with Influenza infection.

Methods

Data are derived from the prospective registries “Hospital based surveillance of COVID-19 and Influenza” that are based at the Geneva University Hospitals/Institute of Global Health, University of Geneva. In total, 15 hospitals all over Switzerland collected data on patient characteristics, concomitant medication and outcomes in 2 separate cohorts with similar data collection of various patient-related variables, including a diverse group patients with Covid-19 and Influenza. Data collection included Influenza patients, collected from 7 hospitals. All registered patients ≥ 18 years will be included into the analysis. The study groups consist of hospitalized patients with either laboratory-proven Covid-19 OR Influenza infection. The primary outcome measure is the in-hospital all-cause mortality. Secondary outcome measures are need for ICU care, need for non-invasive or invasive ventilation, need for readmission, and complications like pneumonia, kidney or liver. For the analysis we will use mixed-effects Cox proportional hazards model. To adjust for differences in baseline characteristics and clustering effects, inverse probability weighted propensity score matching and multivariate mixed-effects models with subdistribution analysis of competing outcomes (discharge) will be applied.

Results and Outlook

The results will provide a robust estimate regarding risks in outcomes for hospitalized Covid-19 patients when compared to seasonal influenza patients. These results will provide valuable elements for the ongoing discussion on morbidity and mortality of Covid-19 vs seasonal influenza patients. Moreover, it may help clinicians, scientists, policy makers and the population to make evidence-based decisions on the level of prevention/actions

Patterns of antimicrobial prescribing in patients hospitalized for influenza virus infection or COVID-19 

Lead:  Dr. Danielle Vuichard-Gysin (STGAG/Swissnoso), Dr. Julia Anna Bielicki (UKBB), Prof. Sarah Tschudin-Sutter(USB), Dr. Catherine Plüss-Suard (IFIK/UniBE), Prof. Stephan Harbarth (HUG), Prof. Olivia Keiser (ISG/UniGE), Prof. Andreas Widmer(USB)

Status: Ongoing

Background and objectives:

Widespread use of antimicrobials drives emergence of antibiotic resistance. Antibiotics are often prescribed for viral respiratory infections without clear indication representing inappropriate use. Designing effective interventions to improve antimicrobial use in patients admitted with viral respiratory infections requires understanding of prescribing practices. So far, antimicrobial prescribing in hospitalized patients with influenza has not been compared to patients with COVID-19. Our main goal is to characterize antimicrobial use in these patients.

Methods

We propose to use data from the prospective national surveillances on influenza and COVID-19, respectively, to investigate and compare antimicrobial use in these two cohorts. We will consider all adults, hospitalized for > 24 hours with either laboratory confirmed influenza virus infection or COVID-19. The primary outcome measure is the proportion of patients prescribed antimicrobial agents in each cohort. Secondary outcomes are the relative proportions of AWaRe group antibiotics among treated patients, the proportion of patients with single or combined antibiotic treatment, distribution of different antimicrobial classes between the two cohorts, proportion of broad-spectrum antibiotic and the proportion of patients with infectious complications.

For our primary analysis, we will use univariable logistic regression to calculate odds ratios for antimicrobial use among influenza and COVID-19 patients. To adjust for potential confounders, we perform multivariable logistic regression analysis. We will use Generalized Estimating Equations to adjust for clustering at the hospital level.

Results and outlook

Results derived from these analyses may eventually help to design new interventions for rational use of antibiotics in patients admitted with respiratory viral infections.

Characteristics and Outcomes of Patients who Developed a Healthcare Associated SARS-CoV-2 Infection

Lead: Dre. Gaud Catho (HUG), Dre. Stéphanie D’Incau (INSEL), Dr. Andrew Atkinson (INSEL), Dre. Anne Iten (HUG), Prof. Stephan Harbarth (HUG), Prof. Jonas Marschall (INSEL)

Status: Ongoing

Background and objectives:

Healthcare associated COVID-19 (HA-COVID-19) infections have been described since the beginning of the COVID-19 pandemic (1). Since then, several healthcare-associated outbreaks have been reported (2-4) and have shown that hospitals are an important platform for viral transmission. Because hospitalized patients are usually more fragile and comorbid, HA-COVID-19 might cause significant morbidity and mortality. Nevertheless, an intensive screening strategy to break transmission chains inside healthcare facilities may also lead to increased detection of mild COVID-19, including asymptomatic cases, even among elderly. Thus, uncertainty remains on the clinical outcome of patients who contracted SARS-CoV-2 in healthcare facilities. The main objectives of the current work are (1) to describe and compare characteristics of patients who acquired COVID in the community, versus acute care hospital versus Long Term Care Facilities (LTCF), and (2) to assess and compare clinical outcomes of all these patients.

Methods

We will use data from the prospective national surveillance on COVID-19 (CH-SUR) which includes all hospitalized COVID-19 cases with a laboratory confirmed infection. COVID-19 cases are classified in three main categories, stratified by the likely place of SARS-CoV-2 acquisition: 1) community –acquired, 2) acute care hospital-acquired or 3) LTCF-acquired. Hospital-acquired cases are defined as those detected more than 5 days after in-hospital admission. 

All routinely collected variables and available clinical features will be retrieved and described in the 3 subcohorts of patients: demographics characteristics (age, gender and comorbidities), transfer to intensive care or intermediate care unit, in-hospital length of stay, and in-hospital deaths.

In addition, for the subgroup of HA-COVID-19 cases, we will record the following items: time to nosocomial acquisition from admission, unit of acquisition (geriatric, medicine, surgery, obstetrics, intensive care unit, other), symptoms at the time of the diagnosis, complications, antiviral treatment, corticosteroids, time to detection if the patient was symptomatic before the day of the first positive test, time to onset of symptoms if the patient was asymptomatic at the time of the first positive test.

The primary outcome will be a composite outcome of in-hospital all-cause mortality and intensive care unit transfer. 

In a first step, we will perform descriptive statistics between the different groups. In a second step we will evaluate mortality and ICU transfer in the different groups using complementary analytical methods (i.e., multilevel Poisson regression and failure-time models, accounting for clustering effect and competing risks). 

Results and outlook

Results derived from these analyses may help clinicians to better understand and compare outcomes of HA-COVID-19. Moreover, results may help to target interventions for prevention of HA-COVID-19.

Evolution of mortality over time in CH-SUR

Lead: Alexis Martin (ISG) & Maroussia Roelens (ISG)

Status: Published in Swiss Medical Weekly

Background and objectives

When comparing the periods of time before and after the first wave of the ongoing SARS-CoV-2/COVID-19 pandemic, the mortality rate seems to be lower in the second period. However, many confounders could explain this decreasing mortality rate, especially changes in demographic characteristics of the population. The goal of this study is to analyse to what extent observed changes in mortality, intensive care units use (ICU), intermediate care use and duration of both hospitalizations and ICU use may be explained by various cofactors such as age, sex, and comorbidities.

Methods

We will conduct a Cox proportional hazard regression model to compare mortality and ICU/intermediate care use between three time periods (first wave, summer and second wave). We will account for competing risks.

Duration of hospitalization (overall and in ICU/intermediate care) will be analysed using Kaplan Meier graphs and Cox regression.

SUPER-COVID- Superinfections in patients with COVID-19

Lead: Dr Werner Albrich (KSSG) & Dre Carol Strahm (KSSG) - initially a mono-centric study, this was deemed of interest by several other centers.

Status: Ongoing

Note: Due to the need of additional data, Ethics agreed to the use of further data (Project ID: 2021-00785, EKOS 21/060)

Background

Co- and superinfections in COVID-19 patients represent a major concern for clinicians as a factor complicating clinical management and contributing to morbidity and mortality of COVID-19. While data from the first wave indicated a low overall incidence of coinfections, newer publications from the second wave report higher rates of bacterial and fungal coinfections, particularly in critically ill COVID-19 patients, and are consistent with the increase of respiratory coinfections in COVID-19 patients that we noticed in St. Gallen during the second wave. However, time-varying risk factors as well as epidemiology and clinical impact of such infections are understudied yet. 

Aims/Objectives

We aim to describe the epidemiology, predictors and clinical characteristics of co- and superinfections in COVID-19 patients and their changes over the course of the pandemic, with particular focus on respiratory co- and superinfections.

Methods

Retrospective observational cohort study of all patients with COVID-19 and suspected or confirmed co- and superinfection who were admitted to any of the acute care hospitals that are part of the infectious disease care network of the Cantonal Hospital of St. Gallen (OSKI) between 1st March 2020 and 1st March 2021. 

Significance

This study will provide valuable evidence on nature, risk factors and impact of coinfections in COVID-19 patients in Switzerland, which will help to optimize management of COVID-19 patients and to guide antibiotic stewardship strategies in the hospital setting in Switzerland.

60-day readmissions after hospital discharge among COVID-19 patients in Switzerland

Lead: Kene David Nwosu (ISG) & Prof Olivia Keiser (ISG) & Dre Anne Iten (HUG) 

Status: Ongoing

Background

Within a few weeks of discharge, COVID-19 patients often deteriorate and require readmission to the hospital. Understanding the incidence of such readmissions, and the associated risk factors, is crucial to facilitating effective healthcare delivery and optimising hospital capacity.

Aims/Objectives

This study aims to assess the rate of 60-day readmission among COVID-19 patients discharged from participating hospitals, to describe the trajectory of readmission risk over time, and to determine the risk factors for readmission.

Methods 

We will conduct a retrospective observational cohort study of all COVID-19 patients in participating hospitals who were discharged. We will describe the characteristics of patients readmitted versus those not readmitted, construct cumulative incidence curves of readmission, and use multivariable logistic regression models with hospital-level random intercepts to determine the risk factors for readmission.

Significance

This study will provide valuable evidence on the nature and risk factors of hospital readmissions for COVID-19 patients, helping inform healthcare resource allocation and clinical decisions on when to discharge COVID-19 ‌patients.

Characteristics and outcomes of fully vaccinated, incompletely vaccinated and non-vaccinated COVID-19 hospitalized patients in CH-SUR

Lead: Dr. Philipp Jent (INSEL),  Dr. Omar Al-Khalil (INSEL) & Andrew Atkinson (INSEL) 

Status: Ongoing

Background and Objectives

In the SARS-CoV-2 pandemic, vaccines have been developed rapidly. Approved vaccines in Switzerland have well established vaccine efficacy (1, 2), but with mass application breakthrough infections have been reported increasingly (9, 10). To date, little is known on the characteristics of individuals suffering from breakthrough SARS-CoV-2 infection with the need of hospitalization, as well as on their disease course and outcome compared to unvaccinated COVID-19 patients. Knowledge on this population is crucial in order to guide public health efforts aiming at avoiding hospital overload in coming surges of the pandemic.

We aim to investigate the differences in patient characteristics, disease severity, disease course and outcome between fully vaccinated, incompletely vaccinated and non-vaccinated individuals hospitalized with COVID-19 in Switzerland.

Methods

We will perform a retrospective cohort study to compare the characteristics and outcomes of the mentioned groups. Data will be derived from the prospective national surveillance on hospitalized COVID-19 patients (CH-SUR). Adult patients hospitalized for >24 hours in participating Swiss hospitals with laboratory-confirmed COVID-19 from December 23, 2020 onwards will be included.

In a first step, we will use descriptive statistics to establish demographic characteristics and outcomes, and identify differences between fully vaccinated, incompletely and non-vaccinated patients in the inpatient setting.

Due to the still limited number of vaccine breakthrough cases in the database, a complementary in-depth analysis is planned as a second step, when case numbers are sufficient for regression analysis. We will use competing risk models (Fine-Gray) in order to analyse the outcome of vaccine breakthroughs in comparison to other hospitalized SARS-CoV-2 cases in the cohort, and determinants of the outcome. The primary outcome will be time to hospital discharge, secondary endpoints further outcome parameters like in-hospital mortality, proportion of patients with oxygen support, non-invasively-ventilated and ventilated patients, time in ICU, amongst others.

Drug therapy decisions for COVID-19 during the 1st year of the pandemic in Switzerland - a retrospective analysis of the national hospital-based surveillance database 

Lead : Michèle Birrer (INSEL), Vanja Piezzi (INSEL),  Lukas Baumann (INSEL) & Christine Thurnheer (INSEL)

 Status: Ongoing

Background and objectives

The COVID-19 pandemic is a major challenge for clinicians due to the lack of evidence- based treatment recommendations. At an unprecedented speed, research data is being published, potentially effective drugs emerge, receive emergency authorizations and some of them are revoked soon after. The drug prescription practice for COVID- 19 patients in Switzerland is largely unknown, as well as the drivers behind treatment decisions.

The main objectives of this study are 1) to assess drug treatment diversity and investigate changes in therapeutic approaches for COVID-19 over the course of the first year of the pandemic in Switzerland in comparison to the recommendations of international and national authorities, and 2) to correlate drug choices with potential drivers of treatment decisions: the severity of COVID-19, demographic characteristics and other influencing variables.

Materials and Methods

Data is retrieved from the prospective registry “hospital-based surveillance of COVID- 19” which includes hospitalised COVID-19 patients from 21 hospitals in Switzerland. All registered patients aged >18 years, hospitalised from 01.03.2020 to 28.02.2021, will be included. Primary outcome will be a description of the proportion of patients receiving specific immunomodulatory/antiviral drugs and the frequency of each drug used against COVID-19 overall and during four time periods 03-05/20 (first wave), 06- 08/20 (summer, low incidence), 09-11/20 (second wave), and 12/20-02/21. Secondary outcome will be the drug use overall and during the four time periods stratified by severity of illness, demographic characteristics, time since symptoms / positive test, hospital acquisition of infection, type of hospital ward, Swiss language region (German, French/Italian).

Differential treatment effect of remdesivir on the mortality of hospitalized patients with COVID-19

Lead: Plamenna Venkova (ISG) and Janne Estill (ISG)

Status: Published Swiss Med Wkly

Background and objectives

Remdesivir was the first antiviral drug fully licensed for the treatment of COVID-19, but it has subsequently been suspended from the WHO prequalification list after the results of clinical trials showed no benefit. We analysed routinely collected data from the CH-SUR database to explore whether the treatment response differed by patient characteristics.

Methods

We included patients in the CH-SUR enrolled by 9 November 2020 who either did not receive any treatment, who received remdesivir, and who received a treatment other than remdesivir. Patients receiving both remdesivir and other drugs were excluded.

We used model-based recursive partitioning to group the patients according to the association between remdesivir use and the risk of death. In this method, a Cox regression is performed iteratively for subgroups defined based on one of the pre-selected partitioning variables at a time. At each round, the dataset is split according to the variable that caused most instability in the parameters of the Cox model; this process is repeated until the instability in all possible partitionings is above the significance level.

We conducted two analyses. In the first analysis, we adjusted the Cox model for treatment (none, remdesivir, other), sex and age, and included the following partitioning variables: body mass index; urea nitrogen level >19 mg/dl; respiratory rate >30/min; low blood pressure (diastolic >65 years, metal score <9, high urea nitrogen, high respiratory rate, low blood pressure (CURB65). In the second analysis, we adjusted the Cox model for treatment only, and used the same variables plus age and sex in the partitioning. To control for selection bias, we conducted both analyses twice: using either the treatment variables directly; or with a method called local centering where the treatment variable was modified according to the propensity to receive treatment.

Results and outlook

We will present the results graphically as trees, where the leave nodes represent subgroups of patients that differ by the effect of remdesivir on mortality. The results will help to identify groups of COVID-19 who may potentially benefit from remdesivir treatment.

Comparison of clinical characteristics and outcomes of children hospitalized with COVID-19 and seasonal influenza in Switzerland

Lead: Dr Julia Bielicki (UKBB)

Status: Ongoing

Background and objectives

Seasonal influenza and acute SARS-CoV-2 infection in childhood can both result in admission to hospital. However, it is unclear whether there is a difference in the clinical spectrum, severity and outcomes between the two diseases.

The objectives of this project are

•  To describe the spectrum of clinical disease and outcomes of children hospitalized with COVID-19 related disease (either acute or post-infectious, such as PIMS-TS) in Switzerland
• To compare the clinical characteristics of children hospitalized with seasonal influenza and those hospitalized with acute COVID-19.
• To compare undesirable clinical outcomes between children hospitalized with seasonal influenza and those hospitalized with acute COVID-19.
•  To investigate and compare risk factors for undesirable clinical outcomes in children hospitalized with seasonal influenza and those hospitalized with acute COVID-19.

Methods

This will be a retrospective cohort study using data from the hospital-based surveillance of COVID-19 and influenza in Switzerland. Patients of any age hospitalized with either laboratory confirmed influenza virus infection or COVID-19 on a neonatal or paediatric ward and patients

The clinical characteristics and outcomes of the children hospitalized with seasonal influenza and those hospitalized with acute COVID-19 will be analysed descriptively. Categorical variables will be described as percentages, and continuous variables will be described using mean, median, and interquartile ranges (IQR). We will compare characteristics using Chi-square tests for categorical variables and Mann-Whitney U tests for continuous variables.

The primary outcome measure of interest will be a composite of in-hospital death, need for intensive care and readmission within fourteen days after discharge from the index episode. Secondary outcomes will be in-hospital mortality, admission to intermediate or intensive care, readmission within 14 and 28 days of discharge from the index episode, requirements for and duration of ventilation and inotropic support and length of stay in hospital and in ICU.

We will further use univariable and multivariable logistic regression analysis to investigate the risk factors associated with the primary outcome of interest. The analysis will be adjusted for important confounders, such as age, sex, pre-existing chronic comorbidities. Missing explanatory variables will be imputed by multiple imputation.

Relevance

Results may inform planning of acute paediatric inpatient services and support targeting of preventive measures for both seasonal influenza and COVID-19 in this population, including vaccination. 

Hospital outcomes of community acquired Sars-CoV-2 Omicron variant versus Influenza

Lead: Lea Portmann (Uni Luzern), Prof. Rami Sommerstein (Hirsl LUZ), PD Dr. Georg Fröhlich (Hirsl)

Status: Published. JAMA Netw Open.

Background and objectives

Previous studies have shown that COVID-19 is associated with an adverse outcome compared with seasonal influenza A/B infections. However, the virus has emerged in different types and the variant B.1.1.529 (Omicron) is less virulent than earlier variants. Therefore, this study aims to compare adverse outcomes in patients hospitalized with COVID-19 between 15.01.22 and 15.03.22 in Switzerland and Influenza A/B virus infection. This will provide an important information for public health authorities and may enable some planning for the 2022/2023 Covid-Influenza season.

Methods

Data are from the prospective registry “Hospital based surveillance of COVID-19 and Influenza” based at the Geneva University Hospitals/Institute of Global Health. 17 hospitals all over Switzerland collected data on patient characteristics, concomitant medication and outcomes in patients hospitalized because of/with COVID-19. 7 hospitals collected corresponding data in patients hospitalized because of/with Influenza A/B. All registered patients ≥ 18 years will be included into the analysis. Study groups consist of patients with laboratory-proven Covid-19 hospitalized between 15.01.22 and 15.03.22 and hospitalized patients with an Influenza infection. We expect to include ~2000 patients with Covid and ~1500 patients with influenza. The primary outcome measure is in-hospital all-cause mortality. Secondary outcome measures are need for ICU care, need for non-invasive or invasive ventilation, 28-day readmission, and complications like pneumonia, kidney, or liver failure. One limitation will be that information on the vaccination status for influenza cases is largely missing.

Results and Outlook

The results will show if the outcomes for hospitalized COVID-19 patients with Omicron variant are comparable to seasonal influenza patients. These results may help clinicians, scientists, policy makers and the population to make evidence-based decisions on the level of prevention/actions to protect the population as well as HCWs in the post pandemic phase.

Base and booster vaccine waning: evidence from the fifth wave of COVID-19 hospitalizations in Switzerland 

Lead: Laure Vancauwenberghe (ISG), Maroussia Roelens (ISG)

Status: Ongoing

As vaccinated individuals make up a significant share of COVID-19 patients in Swiss hospitals, it is important to understand the risk factors for these breakthrough hospitalizations. One important contributor is the decline of vaccine-elicited immunity over time, a phenomenon known as vaccine waning. The proposed study will describe the waning of vaccine protection over time, among both the base vaccinated and the boosted populations. We will compare the incidence of hospitalizations between cohorts of Swiss residents vaccinated in different periods, controlling for age group and the type of vaccine received. The denominators for the hospitalization incidences (e.g. counts of individuals boosted in month X) will be obtained from the Swiss vaccination database, while the numerators (correspondingly, counts of individuals base immunized or boosted in month X who were hospitalized during the fifth wave) will be obtained from the Swiss COVID-19 hospital-based surveillance system (CH-SUR). We will use the derived incidence rate ratios to estimate the proportion of vaccinated hospitalizations attributable to waning vaccine effectiveness. These findings will help guide decisions over how frequently booster vaccines should be administered to different segments of the population.

Association of institutional masking policies with the proportion of healthcareassociated SARS-CoV-2 infections and staff absenteeism during the BA.4/5 wave in Switzerland

Lead: Prof. Dr. med. Stefan Kuster (KSSG), Dr. med. Domenica Flury (KSSG), PD Dr. med. Philipp Kohler (KSSG).

Status: Ongoing

Background and objectives

With the end of the specialsituation (besondere Lage; situation particulière) on April 1, 2022, the requirement to wear masks indoors has also been eliminated in health care facilities. As a result, masking policies vary between hospitals ever since, even during the period of increased community circulation of BA.4/5 in Summer 2022. It is unclear to what extent this variation in management has affected the proportion of nosocomial covid-19 infections and staff absenteeism in different institutions. The proposed study aims to address this question. The null hypothesis for the primary outcome is that different mask policies during the BA.4/5 wave were not associated with the proportion of healthcare-associated SARS-CoV-2 infections in different healthcare institutions.

Methods

Using data from the participating institutions in the CH-SUR framework, we will compare the proportions of healthcare-associated SARS-CoV-2 infections in relation to masking policies on an institutional level during the BA.4/5 summer 2022 wave as a primary outcome. A secondary outcome will be staff absenteeism in relation to mask policy.