In the Limelight: December 2020.
Ontology highlight
ABSTRACT:
SUBMITTER: Nath KA
PROVIDER: S-EPMC7706498 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description: Not available
| S-EPMC7528879 | biostudies-literature
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| S-EPMC7449886 | biostudies-literature
Project description:BackgroundReported coronavirus disease 2019 (COVID-19) cases underestimate severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. We conducted a national probability survey of US households to estimate cumulative incidence adjusted for antibody waning.MethodsFrom August-December 2020 a random sample of US addresses were mailed a survey and self-collected nasal swabs and dried blood spot cards. One adult household member completed the survey and mail specimens for viral detection and total (immunoglobulin [Ig] A, IgM, IgG) nucleocapsid antibody by a commercial, emergency use authorization-approved antigen capture assay. We estimated cumulative incidence of SARS-CoV-2 adjusted for waning antibodies and calculated reported fraction (RF) and infection fatality ratio (IFR). Differences in seropositivity among demographic, geographic, and clinical subgroups were explored.ResultsAmong 39 500 sampled households, 4654 respondents provided responses. Cumulative incidence adjusted for waning was 11.9% (95% credible interval [CrI], 10.5%-13.5%) as of 30 October 2020. We estimated 30 332 842 (CrI, 26 703 753-34 335 338) total infections in the US adult population by 30 October 2020. RF was 22.3% and IFR was 0.85% among adults. Black non-Hispanics (Prevalence ratio (PR) 2.2) and Hispanics (PR, 3.1) were more likely than White non-Hispanics to be seropositive.ConclusionsOne in 8 US adults had been infected with SARS-CoV-2 by October 2020; however, few had been accounted for in public health reporting. The COVID-19 pandemic is likely substantially underestimated by reported cases. Disparities in COVID-19 by race observed among reported cases cannot be attributed to differential diagnosis or reporting of infections in population subgroups.
| S-EPMC8406864 | biostudies-literature
Project description:ObjectiveThis study aimed to investigate coronavirus disease (COVID-19) epidemiology in Alberta, British Columbia, and Ontario, Canada.MethodsUsing data through December 1, 2020, we estimated time-varying reproduction number, Rt, using EpiEstim package in R, and calculated incidence rate ratios (IRR) across the 3 provinces.ResultsIn Ontario, 76% (92 745/121 745) of cases were in Toronto, Peel, York, Ottawa, and Durham; in Alberta, 82% (49 878/61 169) in Calgary and Edmonton; in British Columbia, 90% (31 142/34 699) in Fraser and Vancouver Coastal. Across 3 provinces, Rt dropped to ≤ 1 after April. In Ontario, Rt would remain < 1 in April if congregate-setting-associated cases were excluded. Over summer, Rt maintained < 1 in Ontario, ~1 in British Columbia, and ~1 in Alberta, except early July when Rt was > 1. In all 3 provinces, Rt was > 1, reflecting surges in case count from September through November. Compared with British Columbia (684.2 cases per 100 000), Alberta (IRR = 2.0; 1399.3 cases per 100 000) and Ontario (IRR = 1.2; 835.8 cases per 100 000) had a higher cumulative case count per 100 000 population.ConclusionsAlberta and Ontario had a higher incidence rate than British Columbia, but Rt trajectories were similar across all 3 provinces.
| S-EPMC8134904 | biostudies-literature
Project description: Not available
| S-EPMC7972945 | biostudies-literature
Project description:PurposeGovernment of Tamil Nadu, India, mandated the face mask wearing in public places as one of the mitigation measures of COVID-19. We established a surveillance system for monitoring the face mask usage. This study aimed to estimate the proportion of the population who wear face masks appropriately (covering nose, mouth, and chin) in the slums and non-slums of Chennai at different time points.MethodsWe conducted cross-sectional surveys among the residents of Chennai at two-time points of October and December 2020. The sample size for outdoor mask compliance for the first and second rounds of the survey was 1800 and 1600, respectively, for each of the two subgroups-slums and non-slums. In the second round, we included 640 individuals each in the slums and non-slums indoor public places and 1650 individuals in eleven shopping malls. We calculated the proportions and 95% confidence interval (95%CI) for the mask compliance outdoors and indoors by age, gender, region, and setting (slum and non-slum).ResultsWe observed 3600 and 3200 individuals in the first and second surveys, respectively, for outdoor mask compliance. In both rounds, the prevalence of appropriate mask use outdoors was significantly lower in the slums (28%-29%) than non-slum areas (36%-35%) of Chennai (p<0.01). Outdoor mask compliance was similar within slum and non-slum subgroups across the two surveys. Lack of mask use was higher in the non-slums in the second round (50%) than in the first round of the survey (43%) (p<0.05). In the indoor settings in the 2nd survey, 10%-11% among 1280 individuals wore masks appropriately. Of the 1650 observed in the malls, 947 (57%) wore masks appropriately.ConclusionNearly one-third of residents of Chennai, India, correctly wore masks in public places. We recommend periodic surveys, enforcement of mask compliance in public places, and mass media campaigns to promote appropriate mask use.
| S-EPMC8462676 | biostudies-literature
Project description:In December 2020, research surveillance detected the B.1.1.7 lineage of severe acute respiratory syndrome coronavirus 2 in São Paulo, Brazil. Rapid genomic sequencing and phylogenetic analysis revealed 2 distinct introductions of the lineage. One patient reported no international travel. There may be more infections with this lineage in Brazil than reported.
| S-EPMC7920684 | biostudies-literature
Project description: Not available
| S-EPMC8014236 | biostudies-literature
Project description: Not available
| S-EPMC8091457 | biostudies-literature
Project description:ObjectivesTo describe COVID-19 vaccine distribution operations in United States Federal Bureau of Prisons (BOP) institutions and offices from December 16, 2020-April 14, 2021, report vaccination coverage among staff and incarcerated people, and identify factors associated with vaccination acceptance among incarcerated people.MethodsThe BOP COVID-19 vaccination plan and implementation timeline are described. Descriptive statistics and vaccination coverage were calculated for the BOP incarcerated population using data from the BOP electronic medical record. Coverage among staff was calculated using data from the Centers for Disease Control and Prevention Vaccination Administration Management System. Vaccination coverage in the BOP versus the overall United States adult population was compared by state/territory. Univariate and multivariable logistic regression models were developed to identify demographic, health-related, and institution-level factors associated with vaccination acceptance among incarcerated people, using hierarchical linear modeling to account for institution-level clustering.ResultsBy April 14, 2021, BOP had offered COVID-19 vaccination to 37,870 (100%) staff and 88,173/126,413 (69.8%) incarcerated people, with acceptance rates of 50.2% and 64.2%, respectively. At the time of analysis, vaccination coverage in BOP was comparable to coverage in the overall adult population in the states and territories where BOP institutions and offices are located. Among incarcerated people, factors associated with lower vaccination acceptance included younger age, female sex, non-Hispanic Black and Asian race/ethnicity, and having few underlying medical conditions; factors associated with higher acceptance included having a prior SARS-CoV-2 infection, being born outside the United States, and being assigned to a Federal Detention Center.ConclusionsEarly COVID-19 vaccination efforts in BOP have achieved levels of coverage similar to the general population. To build on this initial success, BOP can consider strategies including re-offering vaccination to people who initially refused and tailoring communication strategies to groups with lower acceptance rates.
| S-EPMC8363472 | biostudies-literature