Hospital capacities and shortages of healthcare resources among US hospitals during the coronavirus disease 2019 (COVID-19) pandemic, National Healthcare Safety Network (NHSN), March 27-July 14, 2020.
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ABSTRACT:
SUBMITTER: Wu H
PROVIDER: S-EPMC8280389 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:This overview of severe acute respiratory syndrome coronavirus 2 circulation over 1.5 years in Guinea demonstrates that virus clades and variants of interest and concern were progressively introduced, mostly by travellers through Conakry, before spreading through the country. Sequencing is key to following virus evolution and establishing efficient control strategies.
| S-EPMC8798712 | biostudies-literature
Project description:BackgroundExposure to COVID-19 is more likely among certain occupations compared with others. This descriptive study seeks to explore occupational differences in mortality due to COVID-19 among workers in Massachusetts.MethodsDeath certificates of those who died from COVID-19 in Massachusetts between March 1 and July 31, 2020 were collected. Occupational information was coded and age-adjusted mortality rates were calculated according to occupation.ResultsThere were 555 deaths among MA residents of age 16-64, with usable occupation information, resulting in an age-adjusted mortality rate of 16.4 per 100,000 workers. Workers in 11 occupational groups including healthcare support and transportation and material moving had mortality rates higher than that for workers overall. Hispanic and Black workers had age-adjusted mortality rates more than four times higher than that for White workers overall and also had higher rates than Whites within high-risk occupation groups.ConclusionEfforts should be made to protect workers in high-risk occupations identified in this report from COVID-19 exposure.
| S-EPMC8013546 | biostudies-literature
Project description:In April 2020, during the peak of the coronavirus disease 2019 (COVID-19) pandemic in Europe, a cluster of children with hyperinflammatory shock with features similar to Kawasaki disease and toxic shock syndrome was reported in England* (1). The patients' signs and symptoms were temporally associated with COVID-19 but presumed to have developed 2-4 weeks after acute COVID-19; all children had serologic evidence of infection with SARS-CoV-2, the virus that causes COVID-19 (1). The clinical signs and symptoms present in this first cluster included fever, rash, conjunctivitis, peripheral edema, gastrointestinal symptoms, shock, and elevated markers of inflammation and cardiac damage (1). On May 14, 2020, CDC published an online Health Advisory that summarized the manifestations of reported multisystem inflammatory syndrome in children (MIS-C), outlined a case definition,† and asked clinicians to report suspected U.S. cases to local and state health departments. As of July 29, a total of 570 U.S. MIS-C patients who met the case definition had been reported to CDC. A total of 203 (35.6%) of the patients had a clinical course consistent with previously published MIS-C reports, characterized predominantly by shock, cardiac dysfunction, abdominal pain, and markedly elevated inflammatory markers, and almost all had positive SARS-CoV-2 test results. The remaining 367 (64.4%) of MIS-C patients had manifestations that appeared to overlap with acute COVID-19 (2-4), had a less severe clinical course, or had features of Kawasaki disease.§ Median duration of hospitalization was 6 days; 364 patients (63.9%) required care in an intensive care unit (ICU), and 10 patients (1.8%) died. As the COVID-19 pandemic continues to expand in many jurisdictions, clinicians should be aware of the signs and symptoms of MIS-C and report suspected cases to their state or local health departments; analysis of reported cases can enhance understanding of MIS-C and improve characterization of the illness for early detection and treatment.
| S-EPMC7440126 | biostudies-literature
Project description:We report mean severe acute respiratory syndrome coronavirus 2 serial intervals for Montana, USA, from 583 transmission pairs; infectors' symptom onset dates occurred during March 1-July 31, 2020. Our estimate was 5.68 (95% CI 5.27-6.08) days, SD 4.77 (95% CI 4.33-5.19) days. Subperiod estimates varied temporally by nonpharmaceutical intervention type and fluctuating incidence.
| S-EPMC8084495 | biostudies-literature
Project description:Most reported cases of coronavirus disease 2019 (COVID-19) in children aged <18 years appear to be asymptomatic or mild (1). Less is known about severe COVID-19 illness requiring hospitalization in children. During March 1-July 25, 2020, 576 pediatric COVID-19 cases were reported to the COVID-19-Associated Hospitalization Surveillance Network (COVID-NET), a population-based surveillance system that collects data on laboratory-confirmed COVID-19-associated hospitalizations in 14 states (2,3). Based on these data, the cumulative COVID-19-associated hospitalization rate among children aged <18 years during March 1-July 25, 2020, was 8.0 per 100,000 population, with the highest rate among children aged <2 years (24.8). During March 21-July 25, weekly hospitalization rates steadily increased among children (from 0.1 to 0.4 per 100,000, with a weekly high of 0.7 per 100,000). Overall, Hispanic or Latino (Hispanic) and non-Hispanic black (black) children had higher cumulative rates of COVID-19-associated hospitalizations (16.4 and 10.5 per 100,000, respectively) than did non-Hispanic white (white) children (2.1). Among 208 (36.1%) hospitalized children with complete medical chart reviews, 69 (33.2%) were admitted to an intensive care unit (ICU); 12 of 207 (5.8%) required invasive mechanical ventilation, and one patient died during hospitalization. Although the cumulative rate of pediatric COVID-19-associated hospitalization remains low (8.0 per 100,000 population) compared with that among adults (164.5),* weekly rates increased during the surveillance period, and one in three hospitalized children were admitted to the ICU, similar to the proportion among adults. Continued tracking of SARS-CoV-2 infections among children is important to characterize morbidity and mortality. Reinforcement of prevention efforts is essential in congregate settings that serve children, including childcare centers and schools.
| S-EPMC7440125 | biostudies-literature
Project description:As part of a multiyear project that monitored illness-related school closures, we conducted systematic daily online searches during July 27, 2020-June 30, 2022, to identify public announcements of COVID-19-related school closures (COVID-SCs) in the United States lasting >1 day. We explored the temporospatial patterns of COVID-SCs and analyzed associations between COVID-SCs and national COVID-19 surveillance data. COVID-SCs reflected national surveillance data: correlation was highest between COVID-SCs and both new PCR test positivity (correlation coefficient [r] = 0.73, 95% CI 0.56-0.84) and new cases (r = 0.72, 95% CI 0.54-0.83) during 2020-21 and with hospitalization rates among all ages (r = 0.81, 95% CI 0.67-0.89) during 2021-22. The numbers of reactive COVID-SCs during 2020-21 and 2021-22 greatly exceeded previously observed numbers of illness-related reactive school closures in the United States, notably being nearly 5-fold greater than reactive closures observed during the 2009 influenza (H1N1) pandemic.
| S-EPMC10756369 | biostudies-literature
Project description:Healthcare personnel are recognized to be at higher risk for infection with severe acute respiratory syndrome coronavirus 2. We conducted a serologic survey in 15 hospitals and 56 nursing homes across Rhode Island, USA, during July 17-August 28, 2020. Overall seropositivity among 9,863 healthcare personnel was 4.6% (95% CI 4.2%-5.0%) but varied 4-fold between hospital personnel (3.1%, 95% CI 2.7%-3.5%) and nursing home personnel (13.1%, 95% CI 11.5%-14.9%). Within nursing homes, prevalence was highest among personnel working in coronavirus disease units (24.1%; 95% CI 20.6%-27.8%). Adjusted analysis showed that in hospitals, nurses and receptionists/medical assistants had a higher likelihood of seropositivity than physicians. In nursing homes, nursing assistants and social workers/case managers had higher likelihoods of seropositivity than occupational/physical/speech therapists. Nursing home personnel in all occupations had elevated seropositivity compared with hospital counterparts. Additional mitigation strategies are needed to protect nursing home personnel from infection, regardless of occupation.
| S-EPMC7920685 | biostudies-literature
Project description: Not available
| S-EPMC7092506 | biostudies-literature
Project description:The geographic areas in the United States most affected by the coronavirus disease 2019 (COVID-19) pandemic have changed over time. On May 7, 2020, CDC, with other federal agencies, began identifying counties with increasing COVID-19 incidence (hotspots) to better understand transmission dynamics and offer targeted support to health departments in affected communities. Data for January 22-July 15, 2020, were analyzed retrospectively (January 22-May 6) and prospectively (May 7-July 15) to detect hotspot counties. No counties met hotspot criteria during January 22-March 7, 2020. During March 8-July 15, 2020, 818 counties met hotspot criteria for ?1 day; these counties included 80% of the U.S. population. The daily number of counties meeting hotspot criteria peaked in early April, decreased and stabilized during mid-April-early June, then increased again during late June-early July. The percentage of counties in the South and West Census regions* meeting hotspot criteria increased from 10% and 13%, respectively, during March-April to 28% and 22%, respectively, during June-July. Identification of community transmission as a contributing factor increased over time, whereas identification of outbreaks in long-term care facilities, food processing facilities, correctional facilities, or other workplaces as contributing factors decreased. Identification of hotspot counties and understanding how they change over time can help prioritize and target implementation of U.S. public health response activities.
| S-EPMC7439980 | biostudies-literature
Project description:BackgroundMany countries have implemented population-wide interventions to control COVID-19, with varying extent and success. Many jurisdictions have moved to relax measures, while others have intensified efforts to reduce transmission.AimWe aimed to determine the time frame between a population-level change in COVID-19 measures and its impact on the number of cases.MethodsWe examined how long it takes for there to be a substantial difference between the number of cases that occur following a change in COVID-19 physical distancing measures and those that would have occurred at baseline. We then examined how long it takes to observe this difference, given delays and noise in reported cases. We used a susceptible-exposed-infectious-removed (SEIR)-type model and publicly available data from British Columbia, Canada, collected between March and July 2020.ResultsIt takes 10 days or more before we expect a substantial difference in the number of cases following a change in COVID-19 control measures, but 20-26 days to detect the impact of the change in reported data. The time frames are longer for smaller changes in control measures and are impacted by testing and reporting processes, with delays reaching ≥ 30 days.ConclusionThe time until a change in control measures has an observed impact is longer than the mean incubation period of COVID-19 and the commonly used 14-day time period. Policymakers and practitioners should consider this when assessing the impact of policy changes. Rapid, consistent and real-time COVID-19 surveillance is important to minimise these time frames.
| S-EPMC8511756 | biostudies-literature