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: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:Coronavirus disease has disproportionately affected persons in congregate settings and high-density workplaces. To determine more about the transmission patterns of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in these settings, we performed whole-genome sequencing and phylogenetic analysis on 319 (14.4%) samples from 2,222 SARS-CoV-2-positive persons associated with 8 outbreaks in Minnesota, USA, during March-June 2020. Sequencing indicated that virus spread in 3 long-term care facilities and 2 correctional facilities was associated with a single genetic sequence and that in a fourth long-term care facility, outbreak cases were associated with 2 distinct sequences. In contrast, cases associated with outbreaks in 2 meat-processing plants were associated with multiple SARS-CoV-2 sequences. These results suggest that a single introduction of SARS-CoV-2 into a facility can result in a widespread outbreak. Early identification and cohorting (segregating) of virus-positive persons in these settings, along with continued vigilance with infection prevention and control measures, is imperative.
| S-EPMC8314815 | biostudies-literature
Project description:Most cases of coronavirus disease 2019 are mild or asymptomatic. Therefore, many cases remain unrecorded. We determined seroprevalence of IgG antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in 3,186 regular blood donors in three German federal states between 9 March and 3 June 2020. The IgG seroprevalence was 0.91% (95% confidence interval (CI): 0.58-1.24) overall, ranging from 0.66% (95% CI: 0.13-1.19) in Hesse to 1.22% (95% CI: 0.33-2.10) in Lower-Saxony.
| S-EPMC7376847 | biostudies-literature
Project description:Nursing homes are high-risk settings for outbreaks of SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19) (1,2). During the COVID-19 pandemic, U.S. health departments worked to improve infection prevention and control (IPC) practices in nursing homes to prevent outbreaks and limit the spread of COVID-19 in affected facilities; however, limited resources have hampered health departments' ability to rapidly provide IPC support to all nursing homes within their jurisdictions. Since 2008, the Centers for Medicare & Medicaid Services (CMS) has published health inspection results and quality ratings based on their Five-Star Quality Rating System for all CMS-certified nursing homes (3); these ratings might be associated with facility-level risk factors for COVID-19 outbreaks. On April 17, 2020, West Virginia became the first state to mandate and conduct COVID-19 testing for all nursing home residents and staff members to identify and reduce transmission of SARS-CoV-2 in these settings (4). West Virginia's census of nursing home outbreaks was used to examine associations between CMS star ratings and COVID-19 outbreaks. Outbreaks, defined as two or more cases within 14 days (with at least one resident case), were identified in 14 (11%) of 123 nursing homes. Compared with 1-star-rated (lowest rated) nursing homes, the odds of a COVID-19 outbreak were 87% lower among 2- to 3-star-rated facilities (adjusted odds ratio [aOR] = 0.13, 95% confidence interval [CI] = 0.03-0.54) and 94% lower among 4- to 5-star-rated facilities (aOR = 0.06, 95% CI = 0.006-0.39). Health departments could use star ratings to help identify priority nursing homes in their jurisdictions to inform the allocation of IPC resources. Efforts to mitigate outbreaks in high-risk nursing homes are necessary to reduce overall COVID-19 mortality and associated disparities. Moreover, such efforts should incorporate activities to improve the overall quality of life and care of nursing home residents and staff members and address the social and health inequities that have been recognized as a prominent feature of the COVID-19 pandemic in the United States (5).
| S-EPMC7498166 | biostudies-literature
Project description:IntroductionHuman mobility was considerably reduced during the COVID-19 pandemic. To support disease surveillance, it is important to understand the effect of mobility on transmission.AimWe compared the role of mobility during the first and second COVID-19 wave in Switzerland by studying the link between daily travel distances and the effective reproduction number (Rt) of SARS-CoV-2.MethodsWe used aggregated mobile phone data from a representative panel survey of the Swiss population to measure human mobility. We estimated the effects of reductions in daily travel distance on Rt via a regression model. We compared mobility effects between the first (2 March-7 April 2020) and second wave (1 October-10 December 2020).ResultsDaily travel distances decreased by 73% in the first and by 44% in the second wave (relative to February 2020). For a 1% reduction in average daily travel distance, Rt was estimated to decline by 0.73% (95% credible interval (CrI): 0.34-1.03) in the first wave and by 1.04% (95% CrI: 0.66-1.42) in the second wave. The estimated mobility effects were similar in both waves for all modes of transport, travel purposes and sociodemographic subgroups but differed for movement radius.ConclusionMobility was associated with SARS-CoV-2 Rt during the first two epidemic waves in Switzerland. The relative effect of mobility was similar in both waves, but smaller mobility reductions in the second wave corresponded to smaller overall reductions in Rt. Mobility data from mobile phones have a continued potential to support real-time surveillance of COVID-19.
| S-EPMC8915405 | biostudies-literature