Long term anti-SARS-CoV-2 antibody kinetics and correlate of protection against Omicron BA.1/BA.2 infection.

Binding antibody levels against SARS-CoV-2 have shown to be correlates of protection against infection with pre-Omicron lineages. This has been challenged by the emergence of immune-evasive variants, notably the Omicron sublineages, in an evolving immune landscape with high levels of cumulative incidence and vaccination coverage. This in turn limits the use of widely available commercial high-throughput methods to quantify binding antibodies as a tool to monitor protection at the population-level. Here we show that anti-Spike RBD antibody levels, as quantified by the immunoassay used in this study, are an indirect correlate of protection against Omicron BA.1/BA.2 for individuals previously infected by SARS-CoV-2. Leveraging repeated serological measurements between April 2020 and December 2021 on 1083 participants of a population-based cohort in Geneva, Switzerland, and using antibody kinetic modeling, we found up to a three-fold reduction in the hazard of having a documented positive SARS-CoV-2 infection during the Omicron BA.1/BA.2 wave for anti-S antibody levels above 800 IU/mL (HR 0.30, 95% CI 0.22-0.41). However, we did not detect a reduction in hazard among uninfected participants. These results provide reassuring insights into the continued interpretation of SARS-CoV-2 binding antibody measurements as an independent marker of protection at both the individual and population levels.

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.

The lockdown effect: The impact of the COVID-19-related confinement on the nature of dental emergencies and the number of patients seen at the Geneva university hospital's dental clinic.

PURPOSE: The aim of this retrospective case study was to evaluate the impact of the COVID-19 confinement on consultation number and nature of dental emergencies. MATERIALS AND METHODS: The investigators implemented a retrospective case-control study and enrolled a sample of patients who presented to the University Hospital of Geneva for dental emergencies during the COVID-19 confinement from March 16 to April 26, 2020. They were compared to a matched case-control group treated in 2018 and 2019. The predictor variable was the COVID-19 confinement. The outcome variables were consultation number and nature of dental emergencies. Other study variables included age, gender, socio-economic status, delay from symptoms to consultation and type of treatment. Descriptive and bivariate statistics were computed and significance level was set at ≤ 0.05. RESULTS: The study sample was composed of 1104 patients, with 386 in the case-study and 718 in the control group. No significant change in patient numbers was observed. In the case-study group patients were significantly younger (P= 0.004), had a significantly higher proportion of acute toothache and dental infections (P= 0.01), the main reason for consultation was pain or swelling (P= 0.01) and the delay from first symptoms to consultation was shorter compared to the controls (P=0.008). CONCLUSION: The COVID-19 confinement had no impact on the consultation number of dental emergencies. However, changes in emergency type were noted, with an increase in acute toothaches and infections and patients waited less time between the onset of symptoms to consultation.

The pandemic toll and post-acute sequelae of SARS-CoV-2 in healthcare workers at a Swiss University Hospital.

Healthcare workers have potentially been among the most exposed to SARS-CoV-2 infection as well as the deleterious toll of the pandemic. This study has the objective to differentiate the pandemic toll from post-acute sequelae of SARS-CoV-2 infection in healthcare workers compared to the general population. The study was conducted between April and July 2021 at the Geneva University Hospitals, Switzerland. Eligible participants were all tested staff, and outpatient individuals tested for SARS-CoV-2 at the same hospital. The primary outcome was the prevalence of symptoms in healthcare workers compared to the general population, with measures of COVID-related symptoms and functional impairment, using prevalence estimates and multivariable logistic regression models. Healthcare workers (n = 3083) suffered mostly from fatigue (25.5 %), headache (10.0 %), difficulty concentrating (7.9 %), exhaustion/burnout (7.1 %), insomnia (6.2 %), myalgia (6.7 %) and arthralgia (6.3 %). Regardless of SARS-CoV-2 infection, all symptoms were significantly higher in healthcare workers than the general population (n = 3556). SARS-CoV-2 infection in healthcare workers was associated with loss or change in smell, loss or change in taste, palpitations, dyspnea, difficulty concentrating, fatigue, and headache. Functional impairment was more significant in healthcare workers compared to the general population (aOR 2.28; 1.76-2.96), with a positive association with SARS-CoV-2 infection (aOR 3.81; 2.59-5.60). Symptoms and functional impairment in healthcare workers were increased compared to the general population, and potentially related to the pandemic toll as well as post-acute sequelae of SARS-CoV-2 infection. These findings are of concern, considering the essential role of healthcare workers in caring for all patients including and beyond COVID-19.

One-year persistent symptoms and functional impairment in SARS-CoV-2 positive and negative individuals.

BACKGROUND: Persistent symptoms of SARS-CoV-2 are prevalent weeks to months following the infection. To date, it is difficult to disentangle the direct from the indirect effects of SARS-CoV-2, including lockdown, social, and economic factors. OBJECTIVE: The study aims to characterize the prevalence of symptoms, functional capacity, and quality of life at 12 months in outpatient symptomatic individuals tested positive for SARS-CoV-2 compared to individuals tested negative. METHODS: From 23 April to 27 July 2021, outpatient symptomatic individuals tested for SARS-CoV-2 at the Geneva University Hospitals were followed up 12 months after their test date. RESULTS: At 12 months, out of the 1447 participants (mean age 45.2 years, 61.2% women), 33.4% reported residual mild to moderate symptoms following SARS-CoV-2 infection compared to 6.5% in the control group. Symptoms included fatigue (16% vs. 3.1%), dyspnea (8.9% vs. 1.1%), headache (9.8% vs. 1.7%), insomnia (8.9% vs. 2.7%), and difficulty concentrating (7.4% vs. 2.5%). When compared to the control group, 30.5% of SARS-CoV-2 positive individuals reported functional impairment at 12 months versus 6.6%. SARS-CoV-2 infection was associated with the persistence of symptoms (adjusted odds ratio [aOR] 4.1; 2.60-6.83) and functional impairment (aOR 3.54; 2.16-5.80) overall, and in subgroups of women, men, individuals younger than 40 years, those between 40-59 years, and in individuals with no past medical or psychiatric history. CONCLUSION: SARS-CoV-2 infection leads to persistent symptoms over several months, including in young healthy individuals, in addition to the pandemic effects, and potentially more than other common respiratory infections. Symptoms impact functional capacity up to 12 months post infection.

Neighbourhood socio-economic vulnerability and access to COVID-19 healthcare during the first two waves of the pandemic in Geneva, Switzerland: A gender perspective.

Background: Neighbourhood socio-economic inequities have been shown to affect COVID-19 incidence and mortality, as well as access to tests. This article aimed to study how associations of inequities and COVID-19 outcomes varied between the first two pandemic waves from a gender perspective. Methods: We performed an ecological study based on the COVID-19 database of Geneva between Feb 26, 2020, and June 1, 2021. Outcomes were the number of tests per person, the incidence of COVID-19 cases, the incidence of COVID-19 deaths, the positivity rate, and the delay between symptoms and test. Outcomes were described by neighbourhood socio-economic levels and stratified by gender and epidemic waves (first wave, second wave), adjusting for the proportion of inhabitants older than 65 years. Findings: Low neighbourhood socio-economic levels were associated with a lower number of tests per person (incidence rate ratio [IRR] of 0.88, 0.85 and 0.83 for low, moderate, and highly vulnerable neighbourhood respectively), a higher incidence of COVID-19 cases and of COVID-19 deaths (IRR 2.3 for slightly vulnerable, 1.9 for highly vulnerable). The association between socio-economic inequities and incidence of COVID-19 deaths was mainly present during the first wave of the pandemic, and was stronger amongst women. The increase in COVID-19 cases amongst vulnerable populations appeared mainly during the second wave, and originated from a lower access to tests for men, and a higher number of COVID-19 cases for women. Interpretation: The COVID-19 pandemic affected people differently depending on their socio-economic level. Because of their employment and higher prevalence of COVID-19 risk factors, people living in neighbourhoods of lower socio-economic levels, especially women, were more exposed to COVID-19 consequences. Funding: This research was supported by the research project SELFISH, financed by the Swiss National Science Foundation, grant number 51NF40-160590 (LIVES centre international research project call).

Cohort profile: Actionable Register of Geneva Outpatients and inpatients with SARS-CoV-2 (ARGOS).

PURPOSE: The Actionable Register of Geneva Outpatients and inpatients with SARS-CoV-2 (ARGOS) is an ongoing prospective cohort created by the Geneva Directorate of Health. It consists of an operational database compiling all SARS-CoV-2 test results recorded in the Geneva area since late February 2020. This article aims at presenting this comprehensive cohort, in light of some of the varying public health measures in Geneva, Switzerland, since March 2020. PARTICIPANTS: As of 1 June 2021, the database included 360 525 patients, among which 65 475 had at least one positive test result for SARS-CoV-2. Among all positive patients, 37.6% were contacted only once, 10.6% had one follow-up call, 8.5% had two and 27.7% had three or more follow-up calls. Participation rate among positive patients is 94%. Data collection is ongoing. FINDINGS TO DATE: ARGOS data illustrates the magnitude of COVID-19 pandemic in Geneva, Switzerland, and details a variety of population factors and outcomes. The content of the cohort includes demographic data, comorbidities and risk factors for poor clinical outcome, self-reported COVID-19 symptoms, environmental and socioeconomic factors, prospective and retrospective contact tracing data, travel quarantine data and deaths. The registry has already been used in several publications focusing on symptoms and long COVID-19, infection fatality rate and re-infection. FUTURE PLANS: The data of this large real-world registry provides a valuable resource for various types of research, such as clinical research, epidemiological research or policy assessment as it illustrates the impact of public health policies and overall disease burden of COVID-19.

Prevalence of Symptoms More Than Seven Months After Diagnosis of Symptomatic COVID-19 in an Outpatient Setting.

BACKGROUND: With millions of SARS-CoV-2 infections worldwide, increasing numbers of patients are coming forward with long-term clinical effects of the disease lasting several weeks to months. OBJECTIVE: To characterize symptoms 7 to 9 months after diagnosis of COVID-19. DESIGN: Self-reported surveys and semistructured telephone interviews at enrollment and 30 to 45 days and 7 to 9 months from diagnosis. SETTING: From 18 March to 15 May 2020, symptomatic persons who tested positive for SARS-CoV-2 at the Geneva University Hospitals were followed by CoviCare, a virtual, clinical, outpatient follow-up program. Persons were contacted again at 30 to 45 days and 7 to 9 months from diagnosis. PARTICIPANTS: Persons who were a part of the CoviCare program from 18 March to 15 May 2020. MEASUREMENTS: A standardized interview of symptoms consistent with COVID-19, with grading of intensity. RESULTS: Of the 629 participants in the study who completed the baseline interviews, 410 completed follow-up at 7 to 9 months after COVID-19 diagnosis; 39.0% reported residual symptoms. Fatigue (20.7%) was the most common symptom reported, followed by loss of taste or smell (16.8%), dyspnea (11.7%), and headache (10.0%). LIMITATION: Limitations include generalizability and missing data for 34.8% of participants. CONCLUSION: Residual symptoms after SARS-CoV-2 infection are common among otherwise young and healthy persons followed in an outpatient setting. These findings contribute to the recognition of long-term effects in a disease mostly counted by its death toll to date by promoting communication on postacute sequelae of SARS-CoV-2 and encouraging physicians to continue long-term monitoring of their patients. PRIMARY FUNDING SOURCE: None.

Deep learning diagnostic and risk-stratification pattern detection for COVID-19 in digital lung auscultations: clinical protocol for a case-control and prospective cohort study.

BACKGROUND: Lung auscultation is fundamental to the clinical diagnosis of respiratory disease. However, auscultation is a subjective practice and interpretations vary widely between users. The digitization of auscultation acquisition and interpretation is a particularly promising strategy for diagnosing and monitoring infectious diseases such as Coronavirus-19 disease (COVID-19) where automated analyses could help decentralise care and better inform decision-making in telemedicine. This protocol describes the standardised collection of lung auscultations in COVID-19 triage sites and a deep learning approach to diagnostic and prognostic modelling for future incorporation into an intelligent autonomous stethoscope benchmarked against human expert interpretation. METHODS: A total of 1000 consecutive, patients aged ≥ 16 years and meeting COVID-19 testing criteria will be recruited at screening sites and amongst inpatients of the internal medicine department at the Geneva University Hospitals, starting from October 2020. COVID-19 is diagnosed by RT-PCR on a nasopharyngeal swab and COVID-positive patients are followed up until outcome (i.e., discharge, hospitalisation, intubation and/or death). At inclusion, demographic and clinical data are collected, such as age, sex, medical history, and signs and symptoms of the current episode. Additionally, lung auscultation will be recorded with a digital stethoscope at 6 thoracic sites in each patient. A deep learning algorithm (DeepBreath) using a Convolutional Neural Network (CNN) and Support Vector Machine classifier will be trained on these audio recordings to derive an automated prediction of diagnostic (COVID positive vs negative) and risk stratification categories (mild to severe). The performance of this model will be compared to a human prediction baseline on a random subset of lung sounds, where blinded physicians are asked to classify the audios into the same categories. DISCUSSION: This approach has broad potential to standardise the evaluation of lung auscultation in COVID-19 at various levels of healthcare, especially in the context of decentralised triage and monitoring. TRIAL REGISTRATION: PB_2016-00500, SwissEthics. Registered on 6 April 2020.