The scientific literature on COVID-19 is rapidly evolving and these articles were selected for review based on their relevance to Washington State decision making around COVID-19 response efforts. Included in these Lit Reps are some manuscripts that have been made available online as pre-prints but have not yet undergone peer review. Please be aware of this when reviewing articles included in the Lit Reps.<\/p>\n
Today’s summary is based on a review of 931 articles (880 published, 51 in preprint)<\/em><\/p>\n \t\t\t\t<\/p>\n Mobility data across 1,124 US counties show that individuals began to socially distance at a median of 5 days (IQR=3-8) after 10 cumulative confirmed COVID-19 cases in their state, but at a median of 12 days (IQR=8-17) before state governments issued stay-at-home orders (SAHOs). Using SAHO dates as a proxy for social distancing accounts for only 55% of the true impact of social distancing when compared with estimates using mobility. Delays in social distancing were found to be associated with county-level sociodemographic characteristics, including proportion of people without a high school diploma and proportion of racial and ethnic minorities.<\/p>\n Abdalla et al. (Nov 13, 2020). Asynchrony Between Individual and Government Actions Accounts for Disproportionate Impact of COVID-19 on Vulnerable Communities. American Journal of Preventive Medicine. <\/i>https:\/\/doi.org\/10.1016\/j.amepre.2020.10.012<\/a>\u00a0<\/span><\/i><\/p>\n<\/p>\n<\/div>\n \t\t\t\t\t\t\t\t\t<\/p>\n<\/div>\n<\/div>\n<\/div>\n \t\t\t\t<\/p>\n A nationwide serial sampling study in England (n=1.1 million samples from 280,000 individuals) shows that the first wave (April to June) and the first part of the second wave (August to November) were characterized by different risk factors. Having a patient-facing role was a significant factor in the first wave but not in the second, whereas younger age was strongly associated with infection risk in the second wave. By the end of September, the percentage of those aged 17 to 24 years testing positive was 6 times higher than those aged 70 years or older. Percentage of individuals not reporting symptoms around the time of their positive test ranged from 45 to 68% throughout the study period.<\/p>\n Pouwels et al. (Dec 10, 2020). Community Prevalence of SARS-CoV-2 in England from April to November, 2020: Results from the ONS Coronavirus Infection Survey. The Lancet Public Health. <\/i>https:\/\/doi.org\/10.1016\/S2468-2667(20)30282-6<\/a>\u00a0<\/span><\/i><\/p>\n<\/p>\n<\/div>\n \t\t\t\t\t\t\t\t\t<\/p>\n<\/div>\n \t\t\t\t<\/p>\n In a case-control study of 397 children and adolescents in Mississippi, in-person school or child care attendance two weeks prior to a SARS-CoV-2 test was not associated with a positive test result (aOR=0.8). Close contact with persons with COVID-19 (aOR=3.2), gatherings with persons outside the household such as social functions (aOR=2.4) and playdates (aOR=3.3), and having had visitors in the home (aOR=1.9) two weeks prior to a SARS-CoV-2 test were associated with a positive test result. A majority of parents of both case- and control-patients reported mask-use by their children and staff in school or child care facilities, while parents whose children attended social gatherings and had visitors at home reported lower rates of mask use and physical distancing adherence.<\/p>\n Hobbs et al. (Dec 15, 2020). Factors Associated with Positive SARS-CoV-2 Test Results in Outpatient Health Facilities and Emergency Departments Among Children and Adolescents Aged <18 Years \u2014 Mississippi, September\u2013November 2020. MMWR. <\/i>https:\/\/doi.org\/10.15585\/mmwr.mm6950e3<\/a>\u00a0<\/span><\/i><\/p>\n<\/p>\n<\/div>\n \t\t\t\t\t\t\t\t\t<\/p>\n<\/div>\n \t\t\t\t<\/p>\n Among 101,349 lab-confirmed SARS-CoV-2 cases in Qatar, the risk of reinfection was estimated to be 0.02%, with a reinfection incidence rate of 0.36 per 10,000 person-weeks. Out of 243 patients with at least one positive swab \u226545 days from the first positive swab, 54 (22%) had strong or good evidence for reinfection. Viral genome sequencing confirmed four reinfections out of 12 cases with available genetic evidence.<\/p>\n Abu-Raddad et al. (Dec 14, 2020). Assessment of the Risk of SARS-CoV-2 Reinfection in an Intense Re-Exposure Setting. Clinical Infectious Diseases. <\/i>https:\/\/doi.org\/10.1093\/cid\/ciaa1846<\/a>\u00a0<\/span><\/i><\/p>\n<\/p>\n<\/div>\n \t\t\t\t\t\t\t\t\t<\/p>\n<\/div>\n<\/div>\n<\/div>\n \t\t\t\t<\/p>\n Among 131,606 healthcare personnel (HCP) in the US Veterans Health Administration, 5,925 (4.5%) had positive SARS-CoV-2 PCR tests. HCP who were working in hospitals with >15% SARS-CoV-2 positivity among inpatients, as well as nursing staff, HCP who identify as Black or Hispanic, and veterans were at highest risk of SARS-CoV-2 infection. Male sex, age over 65 years, and veteran status were significant risk factors for mortality among the 18 HCP who died.<\/p>\n Oda et al. (Dec 11, 2020). COVID-19 Infections Among Healthcare Personnel in the United States Veterans Health Administration, March \u2013 August, 2020. Journal of Occupational & Environmental Medicine. <\/i>https:\/\/doi.org\/10.1097\/JOM.0000000000002109<\/a>\u00a0<\/span><\/i><\/p>\n<\/p>\n<\/div>\n \t\t\t\t\t\t\t\t\t<\/p>\n<\/div>\n \t\t\t\t<\/p>\n In a cohort of young adults aged 18 to 35 years admitted to hospital with COVID-19 in New York City (n=395), 58% of patients had at least one major comorbidity. The mortality among those with at least one major comorbidity was 17% (40 of 229), compared to 9% (15 of 166) among those without a major comorbidity. Comorbidities associated with mortality were diabetes, hypertension, renal disease, and cardiac disease. [EDITORIAL NOTE: The mortality percentages in this summary were directly calculated from the numbers reported in the manuscript and differ from the percentages reported by the authors. The percentages in the manuscript use a denominator of all patients rather than separate denominators for those with and without comorbidities.]<\/i>\u00a0<\/span><\/p>\n Altonen et al. (Dec 14, 2020). Characteristics, Comorbidities and Survival Analysis of Young Adults Hospitalized with COVID-19 in New York City. PLOS ONE. <\/i>https:\/\/doi.org\/10.1371\/journal.pone.0243343<\/a>\u00a0<\/span><\/i><\/p>\n<\/p>\n<\/div>\n \t\t\t\t\t\t\t\t\t<\/p>\n<\/div>\n<\/div>\n<\/div>\n \t\t\t\t<\/p>\n Routine testing of staff in care homes was shown to be more effective than other infection control interventions, according to a transmission model parameterized to a care home setting in Scotland. Using isolation of symptomatic residents, testing of new admissions, social distancing, and restricted visiting as the reference intervention, the addition of routine testing of staff outperformed 14-day quarantine of new admissions, closing care home to new admissions in the presence of a symptomatic case, or routine testing of residents.<\/p>\n Nguyen et al. (Dec 14, 2020). Evaluating Intervention Strategies in Controlling COVID-19 Spread in Care Homes: An Agent-Based Model. Infection Control & Hospital Epidemiology. <\/i>https:\/\/doi.org\/10.1017\/ice.2020.1369<\/a>\u00a0<\/span><\/i><\/p>\n<\/p>\n<\/div>\n \t\t\t\t\t\t\t\t\t<\/p>\n<\/div>\n \t\t\t\t<\/p>\n Jin et al. developed a model to produce absolute risk estimates for the general adult population across 477 US cities and for the Medicare population aged 65 years and older across 3,113 counties. Incorporating various sociodemographic factors and pre-existing conditions and validated with 54,444 deaths due to COVID-19 from June to October 2020, the model can identify small fractions of the population that could experience a disproportionately large number of deaths. The model, which shows wide variations in risks across communities, is available as a web-based risk calculator with interactive maps.<\/p>\n Jin et al. (Dec 11, 2020). Individual and Community-Level Risk for COVID-19 Mortality in the United States. Nature Medicine. <\/i>https:\/\/doi.org\/10.1038\/s41591-020-01191-8<\/a>\u00a0<\/span><\/i><\/p>\n<\/p>\n<\/div>\n \t\t\t\t\t\t\t\t\t<\/p>\n<\/div>\n \t\t\t\t<\/p>\n [Pre-print, not peer-reviewed]<\/i> A model based on King County data shows that if the vaccine efficacy of the Moderna and Pfizer vaccines are primarily driven by complete protection against infection, then prevention of a fourth epidemic wave in Spring 2021 and a reduction of subsequent cases and deaths by 60% is likely to occur, assuming rapid vaccine rollout (at least 5,000 vaccinations per day). If vaccine efficacy is primarily driven by a reduction of symptoms despite breakthrough infection, then vaccination would need to be combined with other transmission control measures that prevent at least 50% of secondary infections in order to prevent a fourth wave.<\/p>\n Swan et al. (Dec 14, 2020). Vaccines That Prevent SARS-CoV-2 Transmission May Prevent or Dampen a Spring Wave of COVID-19 Cases and Deaths in 2021. Pre-print downloaded Dec 15 from <\/i>https:\/\/www.medrxiv.org\/content\/10.1101\/2020.12.13.20248120v1<\/a><\/p>\n<\/p>\n<\/div>\n \t\t\t\t\t\t\t\t\t<\/p>\n<\/div>\n<\/div>\n<\/div>\n \t\t\t\t<\/p>\n Missouri Department of Health data show that Black populations in the St. Louis and Kansas City regions had lower COVID-19 testing rates per diagnosed cases compared to white populations consistently throughout the pandemic. During March to June 2020, zip codes in the lowest quartile of testing rates, which had higher proportions of Black, uninsured, and lower-income residents, accounted for only 12% of all tests in the St. Louis and 9% of all tests in Kansas City, despite accounting for 25% of all cases in both regions. Black individuals had consistently lower rates of COVID-19 tests per case compared to their white peers residing in the same zip code.<\/p>\n Mody et al. (Dec 14, 2020). Understanding Drivers of COVID-19 Racial Disparities: A Population-Level Analysis of COVID-19 Testing among Black and White Populations. Clinical Infectious Diseases. <\/i>https:\/\/doi.org\/10.1093\/cid\/ciaa1848<\/a>\u00a0<\/span><\/i><\/p>\n<\/p>\n<\/div>\n \t\t\t\t\t\t\t\t\t<\/p>\n<\/div>\n \t\t\t\t<\/p>\n Accounting for changes in the population age in the four-year period between 2015 and 2019 compared to the period between March and August of 2020 reduced estimates of excess deaths in the US from 301,400 deaths to 218,000 deaths, which substantially increased the contribution of COVID-19-related deaths (173,300 from March to August) to an excess of deaths from 57% to 80%. Most excess non-COVID-19 deaths occurred in April, July and August, primarily among people 25 to 64 years. Diabetes, Alzheimer disease, and heart disease caused the most non-COVID-19 excess deaths.<\/p>\n Shiels et al. (Dec 15, 2020). Impact of Population Growth and Aging on Estimates of Excess U.S. Deaths During the COVID-19 Pandemic, March to August 2020. Annals of Internal Medicine. <\/i>https:\/\/doi.org\/10.7326\/M20-7385<\/a>\u00a0<\/span><\/i><\/p>\n<\/p>\n<\/div>\n \t\t\t\t\t\t\t\t\t<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n Report prepared by the UW Alliance for Pandemic Preparedness and the START Center in collaboration with and on behalf of WA DOH COVID-19 Incident Management Team.<\/p>\n","protected":false},"excerpt":{"rendered":" Attending school or child care was not associated with receiving a positive SARS-CoV-2 test result among children and adolescents aged <18 years in Mississippi. By contrast, infection was more likely among children who had close contact with a person with COVID-19 and among those who attended gatherings with persons outside their household.\n\n\n\nKey Takeaways<\/h2>\n
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Article Summaries<\/h3>\n
Non-Pharmaceutical Interventions<\/h2>\n
Asynchrony Between Individual and Government Actions Accounts for Disproportionate Impact of COVID-19 on Vulnerable Communities<\/h5>\n
Transmission<\/h2>\n
Community Prevalence of SARS-CoV-2 in England from April to November, 2020: Results from the ONS Coronavirus Infection Survey<\/h5>\n
Factors Associated with Positive SARS-CoV-2 Test Results in Outpatient Health Facilities and Emergency Departments Among Children and Adolescents Aged <18 Years \u2014 Mississippi, September\u2013November 2020<\/h5>\n
Assessment of the Risk of SARS-CoV-2 Reinfection in an Intense Re-Exposure Setting<\/h5>\n
Clinical Characteristics and Health Care Setting<\/h2>\n
COVID-19 Infections Among Healthcare Personnel in the United States Veterans Health Administration, March \u2013 August, 2020<\/h5>\n
Characteristics, Comorbidities and Survival Analysis of Young Adults Hospitalized with COVID-19 in New York City<\/h5>\n
Modeling and Prediction<\/h2>\n
Evaluating Intervention Strategies in Controlling COVID-19 Spread in Care Homes: An Agent-Based Model<\/h5>\n
Individual and Community-Level Risk for COVID-19 Mortality in the United States<\/h5>\n
Vaccines That Prevent SARS-CoV-2 Transmission May Prevent or Dampen a Spring Wave of COVID-19 Cases and Deaths in 2021<\/h5>\n
Public Health Policy and Practice<\/h2>\n
Understanding Drivers of COVID-19 Racial Disparities: A Population-Level Analysis of COVID-19 Testing among Black and White Populations<\/h5>\n
Impact of Population Growth and Aging on Estimates of Excess U.S. Deaths During the COVID-19 Pandemic, March to August 2020<\/h5>\n
Other Resources and Commentaries<\/h2>\n
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