COVID-19 in a dialysis center in Milan from March to June 2020: understanding how to respond to the second wave of the pandemic.
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ABSTRACT:
SUBMITTER: Galassi A
PROVIDER: S-EPMC7857107 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundCOVID-19-related mortality in Belgium has drawn attention for two reasons: its high level, and a good completeness in reporting of deaths. An ad hoc surveillance was established to register COVID-19 death numbers in hospitals, long-term care facilities (LTCF) and the community. Belgium adopted broad inclusion criteria for the COVID-19 death notifications, also including possible cases, resulting in a robust correlation between COVID-19 and all-cause mortality.AimTo document and assess the COVID-19 mortality surveillance in Belgium.MethodsWe described the content and data flows of the registration and we assessed the situation as of 21 June 2020, 103 days after the first death attributable to COVID-19 in Belgium. We calculated the participation rate, the notification delay, the percentage of error detected, and the results of additional investigations.ResultsThe participation rate was 100% for hospitals and 83% for nursing homes. Of all deaths, 85% were recorded within 2 calendar days: 11% within the same day, 41% after 1 day and 33% after 2 days, with a quicker notification in hospitals than in LTCF. Corrections of detected errors reduced the death toll by 5%.ConclusionBelgium implemented a rather complete surveillance of COVID-19 mortality, on account of a rapid investment of the hospitals and LTCF. LTCF could build on past experience of previous surveys and surveillance activities. The adoption of an extended definition of 'COVID-19-related deaths' in a context of limited testing capacity has provided timely information about the severity of the epidemic.
| S-EPMC8641068 | biostudies-literature
Project description:.RAW files and Compound Discoverer peak lists used for a manuscript regarding changes the chemical fingerprint of sewage sludge during the COVID-19 pandemic
2021-01-08 | MSV000086676 | MassIVE
Project description: Not available
| S-EPMC7928947 | biostudies-literature
Project description:AimsCOVID-19 has dramatically impacted the healthcare system. Evidence from previous studies suggests a decline in in-hospital admissions for acute myocardial infarction (AMI) during the pandemic. However, the effect of the pandemic on mechanical complications (MC) in acute ST-segment elevation myocardial infarction (STEMI) has not been comprehensively investigated. Therefore, we evaluated the impact of the pandemic on MC and in-hospital outcomes in STEMI during the second wave, in which there was a huge SARS-CoV-2 diffusion in Italy.Methods and resultsBased on a single center cohort of AMI patients admitted with STEMI between February 1, 2019, and February 28, 2021, we compared the characteristics and outcomes of STEMI patients treated during the pandemic vs. those treated before the pandemic. In total, 479 STEMI patients were included, of which 64.5% were during the pandemic. Relative to before the pandemic, primary percutaneous coronary intervention (PCI) declined (87.7 vs. 94.7%, p = 0.014) during the pandemic. Compared to those admitted before the pandemic (10/2019 to 2/2020), STEMI patients admitted during the second wave (10/2020 to 2/2021) presented with a symptom onset-to-door time greater than 24 h (26.1 vs. 10.3%, p = 0.009) and a reduction of primary PCI (85.2 vs. 97.1%, p = 0.009). MC occurred more often in patients admitted during the second wave of the pandemic than in those admitted before the pandemic (7.0 vs. 0.0%, p = 0.032). In-hospital mortality increased during the second wave (10.6 vs. 2.9%, p = 0.058).ConclusionAlthough the experience gained during the first wave and a more advanced hub-and-spoke system for cardiovascular emergencies persists, late hospitalizations and a high incidence of mechanical complications in STEMI were observed even in the second wave.
| S-EPMC9573996 | biostudies-literature
Project description:BackgroundCOVID-19 mortality, excess mortality, deaths per million population (DPM), infection fatality ratio (IFR) and case fatality ratio (CFR) are reported and compared for many countries globally. These measures may appear objective, however, they should be interpreted with caution.AimWe examined reported COVID-19-related mortality in Belgium from 9 March 2020 to 28 June 2020, placing it against the background of excess mortality and compared the DPM and IFR between countries and within subgroups.MethodsThe relation between COVID-19-related mortality and excess mortality was evaluated by comparing COVID-19 mortality and the difference between observed and weekly average predictions of all-cause mortality. DPM were evaluated using demographic data of the Belgian population. The number of infections was estimated by a stochastic compartmental model. The IFR was estimated using a delay distribution between infection and death.ResultsIn the study period, 9,621 COVID-19-related deaths were reported, which is close to the excess mortality estimated using weekly averages (8,985 deaths). This translates to 837 DPM and an IFR of 1.5% in the general population. Both DPM and IFR increase with age and are substantially larger in the nursing home population.DiscussionDuring the first pandemic wave, Belgium had no discrepancy between COVID-19-related mortality and excess mortality. In light of this close agreement, it is useful to consider the DPM and IFR, which are both age, sex, and nursing home population-dependent. Comparison of COVID-19 mortality between countries should rather be based on excess mortality than on COVID-19-related mortality.
| S-EPMC8855510 | biostudies-literature
Project description:Undetected infection with SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19) contributes to transmission in nursing homes, settings where large outbreaks with high resident mortality have occurred (1,2). Facility-wide testing of residents and health care personnel (HCP) can identify asymptomatic and presymptomatic infections and facilitate infection prevention and control interventions (3-5). Seven state or local health departments conducted initial facility-wide testing of residents and staff members in 288 nursing homes during March 24-June 14, 2020. Two of the seven health departments conducted testing in 195 nursing homes as part of facility-wide testing all nursing homes in their state, which were in low-incidence areas (i.e., the median preceding 14-day cumulative incidence in the surrounding county for each jurisdiction was 19 and 38 cases per 100,000 persons); 125 of the 195 nursing homes had not reported any COVID-19 cases before the testing. Ninety-five of 22,977 (0.4%) persons tested in 29 (23%) of these 125 facilities had positive SARS-CoV-2 test results. The other five health departments targeted facility-wide testing to 93 nursing homes, where 13,443 persons were tested, and 1,619 (12%) had positive SARS-CoV-2 test results. In regression analyses among 88 of these nursing homes with a documented case before facility-wide testing occurred, each additional day between identification of the first case and completion of facility-wide testing was associated with identification of 1.3 additional cases. Among 62 facilities that could differentiate results by resident and HCP status, an estimated 1.3 HCP cases were identified for every three resident cases. Performing facility-wide testing immediately after identification of a case commonly identifies additional unrecognized cases and, therefore, might maximize the benefits of infection prevention and control interventions. In contrast, facility-wide testing in low-incidence areas without a case has a lower proportion of test positivity; strategies are needed to further optimize testing in these settings.
| S-EPMC7440119 | biostudies-literature
Project description:Guangdong province, located in South China, is an important economic hub with a large domestic migrant population and was among the earliest areas to report COVID-19 cases outside of Wuhan. We conducted a cross-sectional, age-stratified serosurvey to determine the seroprevalence of antibodies against SARS-CoV-2 after the emergence of COVID-19 in Guangdong. We tested 14,629 residual serum samples that were submitted for clinical testing from 21 prefectures between March and June 2020 for SARS-CoV-2 antibodies using a magnetic particle based chemiluminescent enzyme immunoassay and validated the results using a pseudovirus neutralization assay. We found 21 samples positive for SARS-CoV-2 IgG, resulting in an estimated age- and sex-weighted seroprevalence of 0.15% (95% CI: 0.06-0.24%). The overall age-specific seroprevalence was 0.07% (95% CI: 0.01-0.24%) in persons up to 9 years old, 0.22% (95% CI: 0.03-0.79%) in persons aged 10-19, 0.16% (95% CI: 0.07-0.33%) in persons aged 20-39, 0.13% (95% CI: 0.03-0.33%) in persons aged 40-59 and 0.18% (95% CI: 0.07-0.40%) in persons ≥60 years old. Fourteen (67%) samples had pseudovirus neutralization titers to S-protein, suggesting most of the IgG-positive samples were true-positives. Seroprevalence of antibodies to SARS-CoV-2 was low, indicating that there were no hidden epidemics during this period. Vaccination is urgently needed to increase population immunity to SARS-CoV-2.
| S-EPMC8619097 | biostudies-literature
Project description:ObjectiveTo describe case rates, testing rates and percent positivity of COVID-19 among children aged 0-18 years by school-age grouping.DesignWe abstracted data from Georgia's State Electronic Notifiable Disease Surveillance System on all 10 437 laboratory-confirmed COVID-19 cases among children aged 0-18 years during 30 March 2020 to 6 June 2021. We examined case rates, testing rates and percent positivity by school-aged groupings, namely: preschool (0-4 years), elementary school (5-10 years), middle school (11-13 years), and high school (14-18 years) and compared these data among school-aged children with those in the adult population (19 years and older).SettingFulton County, Georgia.Main outcome measuresCOVID-19 case rates, testing rates and percent positivity.ResultsOver time, the proportion of paediatric cases rose substantially from 1.1% (April 2020) to 21.6% (April 2021) of all cases in the county. Age-specific case rates and test rates were consistently highest among high-school aged children. Test positivity was similar across school-age groups, with periods of higher positivity among high-school aged children.ConclusionsLow COVID-19 testing rates among children, especially early in the pandemic, likely underestimated the true burden of disease in this age group. Despite children having lower measured incidence of COVID-19, we found when broader community incidence increased, incidence also increased among all paediatric age groups. As the COVID-19 pandemic continues to evolve, it remains critical to continue learning about the incidence and transmissibility of COVID-19 in children.
| S-EPMC8671844 | biostudies-literature
Project description:ObjectivesGiven finite ICU bed capacity, knowledge of ICU bed utilization during the coronavirus disease 2019 pandemic is critical to ensure future strategies for resource allocation and utilization. We sought to examine ICU census trends in relation to ICU bed capacity during the rapid increase in severe coronavirus disease 2019 cases early during the pandemic.DesignObservational cohort study.SettingThirteen geographically dispersed academic medical centers in the United States.Patients/subjectsWe obtained daily ICU censuses from March 26 to June 30, 2020, as well as prepandemic ICU bed capacities. The primary outcome was daily census of ICU patients stratified by coronavirus disease 2019 and mechanical ventilation status in relation to ICU capacity.InterventionsNone.Measurements and main resultsPrepandemic overall ICU capacity ranged from 62 to 225 beds (median 109). During the study period, the median daily coronavirus disease 2019 ICU census per hospital ranged from 1 to 84 patients, and the daily ICU census exceeded overall ICU capacity for at least 1 day at five institutions. The number of critically ill patients exceeded ICU capacity for a median (interquartile range) of 17 (12-50) of 97 days at these five sites. All 13 institutions experienced decreases in their noncoronavirus disease ICU population, whereas local coronavirus disease 2019 cases increased. Coronavirus disease 2019 patients reached their greatest proportion of ICU capacity on April 12, 2020, when they accounted for 44% of ICU patients across all participating hospitals. Maximum ICU census ranged from 52% to 289% of overall ICU capacity, with three sites less than 80%, four sites 80-100%, five sites 100-128%, and one site 289%.ConclusionsFrom March to June 2020, the coronavirus disease 2019 pandemic led to ICU censuses greater than ICU bed capacity at fives of 13 institutions evaluated. These findings demonstrate the short-term adaptability of U.S. healthcare institutions in redirecting limited resources to accommodate a public health emergency.
| S-EPMC7994039 | biostudies-literature
Project description:Research indicates that fear was an important factor in determining individual responses to COVID-19, predicting relevant behaviors such as compliance to preventive measures (e.g., hand washing) and stress reactions (e.g., poor sleep quality). Given this central role of fear, it is important to understand more about its temporal changes during the COVID-19 pandemic. This article describes a publicly available dataset that contains longitudinal assessment of fear of COVID-19 and other relevant constructs during the first 15 months of the pandemic. Particularly, the dataset contains data from two different samples. The first sample consists predominantly of Dutch respondents (N = 439) who completed a cross-sectional survey in March 2020. The second sample consists of a large-scale longitudinal survey (N = 2000 at T1), including respondents with a broad range of nationalities (though predominantly residing in Europe and North America; 95.6%). The respondents of the second sample completed the survey between April 2020 and August 2020 using the Prolific data collection platform. In addition, one follow-up assessment was completed in June 2021. The measures included in the survey were fear of COVID-19, demographic information (age, gender, country of residence, education level, and working in healthcare), anxious traits (i.e., intolerance of uncertainty, health anxiety, and worrying), media use, self-rated health, perceived ability to prevent infection, and perceived risk for loved ones. Additionally, at the follow-up assessment in June 2021, respondents were asked whether they were vaccinated against COVID-19 or were planning to get vaccinated. The datafiles of this study have been made available through the Open Science Framework and can be freely reused by psychologists, social scientists, and other researchers who wish to investigate the development, correlates, and consequences of fear of COVID-19.
| S-EPMC10127663 | biostudies-literature