Nejvíce citovaný článek - PubMed ID 32087114
The impacts of climate change on human health are often underestimated or perceived to be in a distant future. Here, we present the projected impacts of climate change in the context of COVID-19, a recent human health catastrophe. We compared projected heat mortality with COVID-19 deaths in 38 cities worldwide and found that in half of these cities, heat-related deaths could exceed annual COVID-19 deaths in less than ten years (at + 3.0 °C increase in global warming relative to preindustrial). In seven of these cities, heat mortality could exceed COVID-19 deaths in less than five years. Our results underscore the crucial need for climate action and for the integration of climate change into public health discourse and policy.
- MeSH
- COVID-19 * mortalita epidemiologie MeSH
- klimatické změny * MeSH
- lidé MeSH
- SARS-CoV-2 * izolace a purifikace MeSH
- velkoměsta MeSH
- veřejné zdravotnictví MeSH
- vysoká teplota * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Geografické názvy
- velkoměsta MeSH
BACKGROUND: Long-term deterioration in the mental health of healthcare workers (HCWs) has been reported during and after the COVID-19 pandemic. Determining the impact of COVID-19 incidence and mortality rates on the mental health of HCWs is essential to prepare for potential new pandemics. This study aimed to investigate the association of COVID-19 incidence and mortality rates with depressive symptoms over 2 years among HCWs in 20 countries during and after the COVID-19 pandemic. METHODS: This was a multi-country serial cross-sectional study using data from the first and second survey waves of the COVID-19 HEalth caRe wOrkErS (HEROES) global study. The HEROES study prospectively collected data from HCWs at various health facilities. The target population included HCWs with both clinical and non-clinical roles. In most countries, healthcare centers were recruited based on convenience sampling. As an independent variable, daily COVID-19 incidence and mortality rates were calculated using confirmed cases and deaths reported by Johns Hopkins University. These rates represent the average for the 7 days preceding the participants' response date. The primary outcome was depressive symptoms, assessed by the Patient Health Questionnaire-9. A multilevel linear mixed model (LMM) was conducted to investigate the association of depressive symptoms with the average incidence and mortality rates. RESULTS: A total of 32,223 responses from the participants who responded to all measures used in this study on either the first or second survey, and on both the first and second surveys in 20 countries were included in the analysis. The mean age was 40.1 (SD = 11.1), and 23,619 responses (73.3%) were from females. The 9323 responses (28.9%) were nurses and 9119 (28.3%) were physicians. LMM showed that the incidence rate was significantly and positively associated with depressive symptoms (coefficient = 0.008, standard error 0.003, p = 0.003). The mortality rate was significantly and positively associated with depressive symptoms (coefficient = 0.049, se = 0.020, p = 0.017). CONCLUSIONS: This is the first study to show an association between COVID-19 incidence and mortality rates with depressive symptoms among HCWs during the first 2 years of the outbreak in multiple countries. This study's findings indicate that additional mental health support for HCWs was needed when the COVID-19 incidence and mortality rates increase during and after the early phase of the pandemic, and these findings may apply to future pandemics. TRIAL REGISTRATION: Clinicaltrials.gov, NCT04352634.
- Klíčová slova
- COVID-19, Depressive symptoms, Healthcare worker, Incidence rate, Mortality rate, Multi-country study, Serial cross-sectional study,
- MeSH
- COVID-19 * mortalita epidemiologie psychologie MeSH
- deprese * epidemiologie MeSH
- dospělí MeSH
- incidence MeSH
- lidé středního věku MeSH
- lidé MeSH
- průřezové studie MeSH
- SARS-CoV-2 MeSH
- zdravotnický personál * psychologie MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- multicentrická studie MeSH
- práce podpořená grantem MeSH
Healthcare workers (HCWs) were at increased risk for mental health problems during the COVID-19 pandemic, with prior data suggesting women may be particularly vulnerable. Our global mental health study aimed to examine factors associated with gender differences in psychological distress and depressive symptoms among HCWs during COVID-19. Across 22 countries in South America, Europe, Asia and Africa, 32,410 HCWs participated in the COVID-19 HEalth caRe wOrkErS (HEROES) study between March 2020 and February 2021. They completed the General Health Questionnaire-12, the Patient Health Questionnaire-9 and questions about pandemic-relevant exposures. Consistently across countries, women reported elevated mental health problems compared to men. Women also reported increased COVID-19-relevant stressors, including insufficient personal protective equipment and less support from colleagues, while men reported increased contact with COVID-19 patients. At the country level, HCWs in countries with higher gender inequality reported less mental health problems. Higher COVID-19 mortality rates were associated with increased psychological distress merely among women. Our findings suggest that among HCWs, women may have been disproportionately exposed to COVID-19-relevant stressors at the individual and country level. This highlights the importance of considering gender in emergency response efforts to safeguard women's well-being and ensure healthcare system preparedness during future public health crises.
- Klíčová slova
- COVID-19, cross-country, gender differences, healthcare disparities, healthcare workers, mental health,
- Publikační typ
- časopisecké články MeSH
Proteases encoded by SARS-CoV-2 constitute a promising target for new therapies against COVID-19. SARS-CoV-2 main protease (Mpro, 3CLpro) and papain-like protease (PLpro) are responsible for viral polyprotein cleavage-a process crucial for viral survival and replication. Recently it was shown that 2-phenylbenzisoselenazol-3(2H)-one (ebselen), an organoselenium anti-inflammatory small-molecule drug, is a potent, covalent inhibitor of both the proteases and its potency was evaluated in enzymatic and antiviral assays. In this study, we screened a collection of 34 ebselen and ebselen diselenide derivatives for SARS-CoV-2 PLpro and Mpro inhibitors. Our studies revealed that ebselen derivatives are potent inhibitors of both the proteases. We identified three PLpro and four Mpro inhibitors superior to ebselen. Independently, ebselen was shown to inhibit the N7-methyltransferase activity of SARS-CoV-2 nsp14 protein involved in viral RNA cap modification. Hence, selected compounds were also evaluated as nsp14 inhibitors. In the second part of our work, we employed 11 ebselen analogues-bis(2-carbamoylaryl)phenyl diselenides-in biological assays to evaluate their anti-SARS-CoV-2 activity in Vero E6 cells. We present their antiviral and cytoprotective activity and also low cytotoxicity. Our work shows that ebselen, its derivatives, and diselenide analogues constitute a promising platform for development of new antivirals targeting the SARS-CoV-2 virus.
- MeSH
- antivirové látky farmakologie metabolismus MeSH
- COVID-19 * MeSH
- cysteinové endopeptidasy metabolismus MeSH
- inhibitory proteas farmakologie MeSH
- lidé MeSH
- methyltransferasy MeSH
- proteasy MeSH
- SARS-CoV-2 * metabolismus MeSH
- simulace molekulového dockingu MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Research Support, N.I.H., Extramural MeSH
- Názvy látek
- antivirové látky MeSH
- cysteinové endopeptidasy MeSH
- ebselen MeSH Prohlížeč
- inhibitory proteas MeSH
- methyltransferasy MeSH
- proteasy MeSH
BACKGROUND: Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive performance of such forecasts if multiple models are combined into an ensemble. Here, we report on the performance of ensembles in predicting COVID-19 cases and deaths across Europe between 08 March 2021 and 07 March 2022. METHODS: We used open-source tools to develop a public European COVID-19 Forecast Hub. We invited groups globally to contribute weekly forecasts for COVID-19 cases and deaths reported by a standardised source for 32 countries over the next 1-4 weeks. Teams submitted forecasts from March 2021 using standardised quantiles of the predictive distribution. Each week we created an ensemble forecast, where each predictive quantile was calculated as the equally-weighted average (initially the mean and then from 26th July the median) of all individual models' predictive quantiles. We measured the performance of each model using the relative Weighted Interval Score (WIS), comparing models' forecast accuracy relative to all other models. We retrospectively explored alternative methods for ensemble forecasts, including weighted averages based on models' past predictive performance. RESULTS: Over 52 weeks, we collected forecasts from 48 unique models. We evaluated 29 models' forecast scores in comparison to the ensemble model. We found a weekly ensemble had a consistently strong performance across countries over time. Across all horizons and locations, the ensemble performed better on relative WIS than 83% of participating models' forecasts of incident cases (with a total N=886 predictions from 23 unique models), and 91% of participating models' forecasts of deaths (N=763 predictions from 20 models). Across a 1-4 week time horizon, ensemble performance declined with longer forecast periods when forecasting cases, but remained stable over 4 weeks for incident death forecasts. In every forecast across 32 countries, the ensemble outperformed most contributing models when forecasting either cases or deaths, frequently outperforming all of its individual component models. Among several choices of ensemble methods we found that the most influential and best choice was to use a median average of models instead of using the mean, regardless of methods of weighting component forecast models. CONCLUSIONS: Our results support the use of combining forecasts from individual models into an ensemble in order to improve predictive performance across epidemiological targets and populations during infectious disease epidemics. Our findings further suggest that median ensemble methods yield better predictive performance more than ones based on means. Our findings also highlight that forecast consumers should place more weight on incident death forecasts than incident case forecasts at forecast horizons greater than 2 weeks. FUNDING: AA, BH, BL, LWa, MMa, PP, SV funded by National Institutes of Health (NIH) Grant 1R01GM109718, NSF BIG DATA Grant IIS-1633028, NSF Grant No.: OAC-1916805, NSF Expeditions in Computing Grant CCF-1918656, CCF-1917819, NSF RAPID CNS-2028004, NSF RAPID OAC-2027541, US Centers for Disease Control and Prevention 75D30119C05935, a grant from Google, University of Virginia Strategic Investment Fund award number SIF160, Defense Threat Reduction Agency (DTRA) under Contract No. HDTRA1-19-D-0007, and respectively Virginia Dept of Health Grant VDH-21-501-0141, VDH-21-501-0143, VDH-21-501-0147, VDH-21-501-0145, VDH-21-501-0146, VDH-21-501-0142, VDH-21-501-0148. AF, AMa, GL funded by SMIGE - Modelli statistici inferenziali per governare l'epidemia, FISR 2020-Covid-19 I Fase, FISR2020IP-00156, Codice Progetto: PRJ-0695. AM, BK, FD, FR, JK, JN, JZ, KN, MG, MR, MS, RB funded by Ministry of Science and Higher Education of Poland with grant 28/WFSN/2021 to the University of Warsaw. BRe, CPe, JLAz funded by Ministerio de Sanidad/ISCIII. BT, PG funded by PERISCOPE European H2020 project, contract number 101016233. CP, DL, EA, MC, SA funded by European Commission - Directorate-General for Communications Networks, Content and Technology through the contract LC-01485746, and Ministerio de Ciencia, Innovacion y Universidades and FEDER, with the project PGC2018-095456-B-I00. DE., MGu funded by Spanish Ministry of Health / REACT-UE (FEDER). DO, GF, IMi, LC funded by Laboratory Directed Research and Development program of Los Alamos National Laboratory (LANL) under project number 20200700ER. DS, ELR, GG, NGR, NW, YW funded by National Institutes of General Medical Sciences (R35GM119582; the content is solely the responsibility of the authors and does not necessarily represent the official views of NIGMS or the National Institutes of Health). FB, FP funded by InPresa, Lombardy Region, Italy. HG, KS funded by European Centre for Disease Prevention and Control. IV funded by Agencia de Qualitat i Avaluacio Sanitaries de Catalunya (AQuAS) through contract 2021-021OE. JDe, SMo, VP funded by Netzwerk Universitatsmedizin (NUM) project egePan (01KX2021). JPB, SH, TH funded by Federal Ministry of Education and Research (BMBF; grant 05M18SIA). KH, MSc, YKh funded by Project SaxoCOV, funded by the German Free State of Saxony. Presentation of data, model results and simulations also funded by the NFDI4Health Task Force COVID-19 (https://www.nfdi4health.de/task-force-covid-19-2) within the framework of a DFG-project (LO-342/17-1). LP, VE funded by Mathematical and Statistical modelling project (MUNI/A/1615/2020), Online platform for real-time monitoring, analysis and management of epidemic situations (MUNI/11/02202001/2020); VE also supported by RECETOX research infrastructure (Ministry of Education, Youth and Sports of the Czech Republic: LM2018121), the CETOCOEN EXCELLENCE (CZ.02.1.01/0.0/0.0/17-043/0009632), RECETOX RI project (CZ.02.1.01/0.0/0.0/16-013/0001761). NIB funded by Health Protection Research Unit (grant code NIHR200908). SAb, SF funded by Wellcome Trust (210758/Z/18/Z).
- Klíčová slova
- COVID-19, Europe, ensemble, epidemiology, forecast, global health, modelling, none, prediction,
- MeSH
- COVID-19 * diagnóza epidemiologie MeSH
- epidemie * MeSH
- infekční nemoci * MeSH
- lidé MeSH
- předpověď MeSH
- retrospektivní studie MeSH
- statistické modely MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Research Support, N.I.H., Extramural MeSH
- Research Support, U.S. Gov't, Non-P.H.S. MeSH
- Research Support, U.S. Gov't, P.H.S. MeSH
BACKGROUND: The Collaborative Outcome study on Health and Functioning during Infection Times (COH-FIT; www.coh-fit.com) is an anonymous and global online survey measuring health and functioning during the COVID-19 pandemic. The aim of this study was to test concurrently the validity of COH-FIT items and the internal validity of the co-primary outcome, a composite psychopathology "P-score". METHODS: The COH-FIT survey has been translated into 30 languages (two blind forward-translations, consensus, one independent English back-translation, final harmonization). To measure mental health, 1-4 items ("COH-FIT items") were extracted from validated questionnaires (e.g. Patient Health Questionnaire 9). COH-FIT items measured anxiety, depressive, post-traumatic, obsessive-compulsive, bipolar and psychotic symptoms, as well as stress, sleep and concentration. COH-FIT Items which correlated r ≥ 0.5 with validated companion questionnaires, were initially retained. A P-score factor structure was then identified from these items using exploratory factor analysis (EFA) and confirmatory factor analyses (CFA) on data split into training and validation sets. Consistency of results across languages, gender and age was assessed. RESULTS: From >150,000 adult responses by May 6th, 2022, a subset of 22,456 completed both COH-FIT items and validated questionnaires. Concurrent validity was consistently demonstrated across different languages for COH-FIT items. CFA confirmed EFA results of five first-order factors (anxiety, depression, post-traumatic, psychotic, psychophysiologic symptoms) and revealed a single second-order factor P-score, with high internal reliability (ω = 0.95). Factor structure was consistent across age and sex. CONCLUSIONS: COH-FIT is a valid instrument to globally measure mental health during infection times. The P-score is a valid measure of multidimensional mental health.
- Klíčová slova
- COH-FIT, Covid-19, Pandemic, Survey: P-factor: well-being: mental health: psychiatry: psychometric,
- MeSH
- COVID-19 * MeSH
- dospělí MeSH
- faktorová analýza statistická MeSH
- hodnocení výsledků zdravotní péče MeSH
- lidé MeSH
- pandemie * MeSH
- průzkumy a dotazníky MeSH
- psychometrie MeSH
- reprodukovatelnost výsledků MeSH
- Check Tag
- dospělí MeSH
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
On March 11, 2020, the World Health Organization raised the coronavirus disease 2019 (COVID-19) status to a pandemic level. The disease caused a global outbreak with devastating consequences, and a fair percentage of patients who have recovered from it continue experiencing persistent sequelae. Hence, identifying the medium and long-term effects of the COVID-19 disease is crucial for its future management. In particular, cardiac complications, from affected function to myocardial injuries, have been reported in these patients. Considering that cardiovascular magnetic resonance (CMR) imaging is the gold standard in diagnosing myocardial involvement and has more advantages than other medical imaging modalities, assessing the outcomes of patients who recovered from COVID-19 with CMR could prove beneficial. This review compiles common findings in CMR in patients from the general population who recovered from COVID-19. The CMR-based techniques comprised parametric mapping for analyzing myocardial composition, feature tracking for studying regional heart deformation, and late gadolinium enhancement for detecting compromised areas in the cardiac muscle. A total of 19 studies were included. The evidence suggests that it is more likely to find signs of myocardial injury in patients who recovered from COVID-19 than in healthy controls, including changes in T1 and T2 mapping relaxation times, affected strain, or the presence of late gadolinium enhancement (LGE) lesions. However, more than two years after the outbreak, there is still a lack of consensus about how these parameters may indicate cardiac involvement in patients who recovered from the disease, as limited and contradictory data is available.
- Klíčová slova
- SARS-CoV-2, feature tracking, late gadolinium enhancement, magnetic resonance image, parametric mapping,
- Publikační typ
- časopisecké články MeSH
- přehledy MeSH
INTRODUCTION: Severe COVID-19 is associated with an important increase of von Willebrand factor and mild lowering of ADAMTS13 activity that may, in the presence of a strong inflammatory reaction, increase the risk of acute thrombotic thrombocytopenic purpura (TTP). Although acute episodes of immune-mediated TTP associated with COVID-19 or SARS-CoV-2 vaccination have been reported, data about clinical evolution of hereditary TTP (hTTP) during the pandemic are scarce. METHOD: We conducted a survey among adult patients of the International Hereditary TTP Registry about SARS-CoV-2 vaccination, COVID-19, and occurrence of acute hTTP episodes. RESULTS: Of 122 adult hTTP patients invited to participate, 86 (70.5%) responded. Sixty-five had been vaccinated (75.6%), of which 14 had received in addition a booster, resulting in 139 individual vaccine shots. Although vaccinations in patients on plasma prophylaxis were done within 1 week of the last plasma infusion, all 23 patients treated with plasma on demand were vaccinated without prior plasma infusions. One patient on uninterrupted weekly plasma infusions presented within 3 days from his second vaccination with neurological symptoms and computed tomography scan 9 days later showed subacute ischemic/hemorrhagic frontal lobe infarction. A second male patient developed acute myocarditis after his second dose of mRNA-1273 vaccine. Twelve (14%) patients had COVID-19, associated with an acute hTTP episode in three of them: one patient had a transient ischemic attack, one a stroke, and a pregnant woman was hospitalized to intensify plasma treatment. DISCUSSION: The risk of an acute episode triggered by COVID-19 seems higher than following vaccination in hTTP patients, who can be safely vaccinated against SARS-CoV-2.
- Klíčová slova
- COVID‐19, SARS‐CoV‐2, congenital thrombotic thrombocytopenic purpura (cTTP), hereditary thrombotic thrombocytopenic purpura (hTTP), vaccines,
- Publikační typ
- časopisecké články MeSH
Higher body mass index (BMI) has been associated with a higher risk for severe COVID-19 outcomes. The aim of this study was to investigate associations among BMI, underlying health conditions and hospital admission as well as the effects of COVID-19 vaccines in adults aged 50 years and older in Europe using data from the Survey of Health, Ageing and Retirement in Europe (SHARE) which was collected from June to August 2021, shortly after the second wave of the COVID-19 pandemic occurred in Europe. Survey data totalling 1936 individuals were used for statistical analyses to calculate the likelihood of hospitalization due to COVID-19 infection in relation to BMI, sociodemographic factors, comorbidities and COVID vaccination status. Approximately 16% of individuals testing positive for COVID-19 were hospitalized for COVID-19, and over 75% of these hospitalized individuals were either overweight or obese. The likelihood of hospitalization for individuals with obesity was approximately 1.5 times (CI [1.05-2.05]) higher than those with a healthy weight (BMI = 18.5-24.9 kg/m2) after adjusting for BMI, sex and age. After adjusting for sociodemographic factors, vaccination and comorbidities, the likelihood of hospitalization for individuals with obesity was 1.34 times higher than those with a healthy weight (CI [0.94-1.90]). Vaccine uptake was lowest in individuals with obesity (BMI ≥ 30 kg/m2) in all age groups. Individuals who had not received a vaccine were 1.8 times more likely to be hospitalized (CI [1.34-2.30]). Across European regions, obesity is associated with higher odds of hospitalization, and vaccination may be effective to reduce these odds for older adults.
- Klíčová slova
- BMI, COVID-19, European population, comorbidity, diabetes, obesity, older adults,
- MeSH
- COVID-19 * epidemiologie MeSH
- hospitalizace MeSH
- index tělesné hmotnosti MeSH
- lidé středního věku MeSH
- lidé MeSH
- obezita komplikace epidemiologie MeSH
- pandemie MeSH
- rizikové faktory MeSH
- senioři MeSH
- vakcíny proti COVID-19 MeSH
- Check Tag
- lidé středního věku MeSH
- lidé MeSH
- senioři MeSH
- Publikační typ
- časopisecké články MeSH
- Geografické názvy
- Evropa epidemiologie MeSH
- Názvy látek
- vakcíny proti COVID-19 MeSH
Although seasonal variation has a known influence on the transmission of several respiratory viral infections, its role in SARS-CoV-2 transmission remains unclear. While there is a sizable and growing literature on environmental drivers of COVID-19 transmission, recent reviews have highlighted conflicting and inconclusive findings. This indeterminacy partly owes to the fact that seasonal variation relates to viral transmission by a complicated web of causal pathways, including many interacting biological and behavioural factors. Since analyses of specific factors cannot determine the aggregate strength of seasonal forcing, we sidestep the challenge of disentangling various possible causal paths in favor of a holistic approach. We model seasonality as a sinusoidal variation in transmission and infer a single Bayesian estimate of the overall seasonal effect. By extending two state-of-the-art models of non-pharmaceutical intervention (NPI) effects and their datasets covering 143 regions in temperate Europe, we are able to adjust our estimates for the role of both NPIs and mobility patterns in reducing transmission. We find strong seasonal patterns, consistent with a reduction in the time-varying reproduction number R(t) (the expected number of new infections generated by an infectious individual at time t) of 42.1% (95% CI: 24.7%-53.4%) from the peak of winter to the peak of summer. These results imply that the seasonality of SARS-CoV-2 transmission is comparable in magnitude to the most effective individual NPIs but less than the combined effect of multiple interventions.
- MeSH
- Bayesova věta MeSH
- COVID-19 * epidemiologie MeSH
- lidé MeSH
- podnebí MeSH
- roční období MeSH
- SARS-CoV-2 * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH