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1.
BMJ Open ; 13(4): e065221, 2023 04 17.
Article in English | MEDLINE | ID: covidwho-2304253

ABSTRACT

INTRODUCTION: The SARS-CoV-2 pandemic remains a threat to public health. Soon after its outbreak, it became apparent that children are less severely affected. Indeed, opposing clinical manifestations between children and adults are observed for other infections. The SARS-CoV-2 outbreak provides the unique opportunity to study the underlying mechanisms. This protocol describes the methods of an observational study that aims to characterise age dependent differences in immune responses to primary respiratory infections using SARS-CoV-2 as a model virus and to assess age differences in clinical outcomes including lung function. METHODS AND ANALYSIS: The study aims to recruit at least 120 children and 60 adults that are infected with SARS-CoV-2 and collect specimen for a multiomics analysis, including single cell RNA sequencing of nasal epithelial cells and peripheral blood mononuclear cells, mass cytometry of whole blood samples and nasal cells, mass spectrometry-based serum and plasma proteomics, nasal epithelial cultures with functional in vitro analyses, SARS-CoV-2 antibody testing, sequencing of the viral genome and lung function testing. Data obtained from this multiomics approach are correlated with medical history and clinical data. Recruitment started in October 2020 and is ongoing. ETHICS AND DISSEMINATION: The study was reviewed and approved by the Ethics Committee of Charité - Universitätsmedizin Berlin (EA2/066/20). All collected specimens are stored in the central biobank of Charité - Universitätsmedizin Berlin and are made available to all participating researchers and on request. TRIAL REGISTRATION NUMBER: DRKS00025715, pre-results publication.


Subject(s)
COVID-19 , Adult , Child , Humans , SARS-CoV-2 , Leukocytes, Mononuclear , Specimen Handling , Nose , Observational Studies as Topic
2.
Swiss Med Wkly ; 150: w20277, 2020 05 04.
Article in English | MEDLINE | ID: covidwho-2217319

ABSTRACT

In Switzerland, the COVID-19 epidemic is progressively slowing down owing to “social distancing” measures introduced by the Federal Council on 16 March 2020. However, the gradual ease of these measures may initiate a second epidemic wave, the length and intensity of which are difficult to anticipate. In this context, hospitals must prepare for a potential increase in intensive care unit (ICU) admissions of patients with acute respiratory distress syndrome. Here, we introduce icumonitoring.ch, a platform providing hospital-level projections for ICU occupancy. We combined current data on the number of beds and ventilators with canton-level projections of COVID-19 cases from two S-E-I-R models. We disaggregated epidemic projection in each hospital in Switzerland for the number of COVID-19 cases, hospitalisations, hospitalisations in ICU, and ventilators in use. The platform is updated every 3-4 days and can incorporate projections from other modelling teams to inform decision makers with a range of epidemic scenarios for future hospital occupancy.


Subject(s)
Coronavirus Infections , Forecasting/methods , Health Planning/methods , Hospital Bed Capacity , Intensive Care Units/supply & distribution , Pandemics , Pneumonia, Viral , Software , Ventilators, Mechanical/supply & distribution , COVID-19 , Coronavirus Infections/epidemiology , Decision Making, Computer-Assisted , Hospital Bed Capacity/statistics & numerical data , Hospitalization/statistics & numerical data , Hospitalization/trends , Humans , Intensive Care Units/statistics & numerical data , Models, Theoretical , Pandemics/statistics & numerical data , Patient Admission/statistics & numerical data , Pneumonia, Viral/epidemiology , Software/standards , Switzerland/epidemiology , Ventilators, Mechanical/statistics & numerical data
3.
PLoS One ; 17(3): e0263789, 2022.
Article in English | MEDLINE | ID: covidwho-1793525

ABSTRACT

Anticipating intensive care unit (ICU) occupancy is critical in supporting decision makers to impose (or relax) measures that mitigate COVID-19 transmission. Mechanistic approaches such as Susceptible-Infected-Recovered (SIR) models have traditionally been used to achieve this objective. However, formulating such models is challenged by the necessity to formulate equations for plausible causal mechanisms between the intensity of COVID-19 transmission and external epidemic drivers such as temperature, and the stringency of non-pharmaceutical interventions. Here, we combined a neural network model (NN) with a Susceptible-Exposed-Infected-Recovered model (SEIR) in a hybrid model and attempted to increase the prediction accuracy of existing models used to forecast ICU occupancy. Between 1st of October, 2020 - 1st of July, 2021, the hybrid model improved performances of the SEIR model at different geographical levels. At a national level, the hybrid model improved, prediction accuracy (i.e., mean absolute error) by 74%. At the cantonal and hospital levels, the reduction on the forecast's mean absolute error were 46% and 50%, respectively. Our findings illustrate those predictions from hybrid model can be used to anticipate occupancy in ICU, and support the decision-making for lifesaving actions such as the transfer of patients and dispatching of medical personnel and ventilators.


Subject(s)
COVID-19
4.
Swiss Med Wkly ; 1512021 07 19.
Article in English | MEDLINE | ID: covidwho-1320610

ABSTRACT

AIMS OF THE STUDY: During the ongoing COVID-19 pandemic, the launch of a large-scale vaccination campaign and virus mutations have hinted at possible changes in transmissibility and the virulence affecting disease progression up to critical illness, and carry potential for future vaccination failure. To monitor disease development over time with respect to critically ill COVID-19 patients, we report near real-time prospective observational data from the RISC-19-ICU registry that indicate changed characteristics of critically ill patients admitted to Swiss intensive care units (ICUs) at the onset of a third pandemic wave. METHODS: 1829 of 3344 critically ill COVID-19 patients enrolled in the international RISC-19-ICU registry as of 31 May 2021 were treated in Switzerland and were included in the present study. Of these, 1690 patients were admitted to the ICU before 1 February 2021 and were compared with 139 patients admitted during the emerging third pandemic wave RESULTS: Third wave patients were a mean of 5.2 years (95% confidence interval [CI] 3.2–7.1) younger (median 66.0 years, interquartile range [IQR] 57.0–73.0 vs 62.0 years, IQR 54.5–68.0; p <0.0001) and had a higher body mass index than patients admitted in the previous pandemic period. They presented with lower SAPS II and APACHE II scores, less need for circulatory support and lower white blood cell counts at ICU admission. P/F ratio was similar, but a 14% increase in ventilatory ratio was observed over time (p = 0.03) CONCLUSION: Near real-time registry data show that the latest COVID-19 patients admitted to ICUs in Switzerland at the onset of the third wave were on average 5 years younger, had a higher body mass index, and presented with lower physiological risk scores but a trend towards more severe lung failure. These differences may primarily be related to the ongoing nationwide vaccination campaign, but the possibility that changes in virus-host interactions may be a co-factor in the age shift and change in disease characteristics is cause for concern, and should be taken into account in the public health and vaccination strategy during the ongoing pandemic. (ClinicalTrials.gov Identifier: NCT04357275).


Subject(s)
COVID-19 , SARS-CoV-2 , Critical Illness , Hospital Mortality , Humans , Intensive Care Units , Pandemics , Prevalence , Prospective Studies , Switzerland/epidemiology
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