Prevalence and Correlates of COVID-19 Vaccine Information on Family Medicine Practices' Websites in the United States: Cross-sectional Website Content Analysis.

BACKGROUND: Primary care providers are regarded as trustworthy sources of information about COVID-19 vaccines. Although primary care practices often provide information about common medical and public health topics on their practice websites, little is known about whether they also provide information about COVID-19 vaccines on their practice websites. OBJECTIVE: This study aimed to investigate the prevalence and correlates of COVID-19 vaccine information on family medicine practices' website home pages in the United States. METHODS: We used the Centers for Medicare and Medicaid National Provider Identifier records to create a sampling frame of all family medicine providers based in the United States, from which we constructed a nationally representative random sample of 964 family medicine providers. Between September 20 and October 8, 2021, we manually examined the practice websites of these providers and extracted data on the availability of COVID-19 vaccine information, and we implemented a 10% cross-review quality control measure to resolve discordances in data abstraction. We estimated the prevalence of COVID-19 vaccine information on practice websites and website home pages and used Poisson regression with robust error variances to estimate crude and adjusted prevalence ratios for correlates of COVID-19 vaccine information, including practice size, practice region, university affiliation, and presence of information about seasonal influenza vaccines. Additionally, we performed sensitivity analyses to account for multiple comparisons. RESULTS: Of the 964 included family medicine practices, most (n=509, 52.8%) had ≥10 distinct locations, were unaffiliated with a university (n=838, 87.2%), and mentioned seasonal influenza vaccines on their websites (n=540, 56.1%). In total, 550 (57.1%) practices mentioned COVID-19 vaccines on their practices' website home page, specifically, and 726 (75.3%) mentioned COVID-19 vaccines anywhere on their practice website. As practice size increased, the likelihood of finding COVID-19 vaccine information on the home page increased (n=66, 27.7% among single-location practices, n=114, 52.5% among practices with 2-9 locations, n=66, 56.4% among practices with 10-19 locations, and n=304, 77.6% among practices with 20 or more locations, P<.001 for trend). Compared to clinics in the Northeast, those in the West and Midwest United States had a similar prevalence of COVID-19 vaccine information on website home pages, but clinics in the south had a lower prevalence (adjusted prevalence ratio 0.8, 95% CI 0.7 to 1.0; P=.02). Our results were largely unchanged in sensitivity analyses accounting for multiple comparisons. CONCLUSIONS: Given the ongoing COVID-19 pandemic, primary care practitioners who promote and provide vaccines should strongly consider utilizing their existing practice websites to share COVID-19 vaccine information. These existing platforms have the potential to serve as an extension of providers' influence on established and prospective patients who search the internet for information about COVID-19 vaccines.

Use of surveillance data to elucidate household clustering of SARS-CoV-2 in Fulton County, Georgia a major metropolitan area.

BACKGROUND: Households are important for SARS-CoV-2 transmission due to high intensity exposure in enclosed spaces over prolonged durations. We quantified and characterized household clustering of COVID-19 cases in Fulton County, Georgia. METHODS: We used surveillance data to identify all confirmed COVID-19 cases in Fulton County. Household clustered cases were defined as cases with matching residential address. We described the proportion of COVID-19 cases that were clustered, stratified by age over time and explore trends in age of first diagnosed case within households and subsequent household cases. RESULTS: Between June 1, 2020 and October 31, 2021, 31,449(37%) of 106,233 cases were clustered in households. Children were the most likely to be in household clusters than any other age group. Initially, children were rarely (∼ 10%) the first cases diagnosed in the household but increased to almost 1 of 3 in later periods. DISCUSSION: One-third of COVID-19 cases in Fulton County were part of a household cluster. Increasingly children were the first diagnosed case, coinciding with temporal trends in vaccine roll-out among the elderly and the return to in-person schooling in Fall 2021. Limitations include restrictions to cases with a valid address and unit number and that the first diagnosed case may not be the infection source for the household.

Characteristics and Risk Factors for Mortality by Coronavirus Disease 2019 Pandemic Waves in Fulton County, Georgia: A Cohort Study March 2020-February 2021.

Background: We examined differences in mortality among coronavirus disease 2019 (COVID-19) cases in the first, second, and third waves of the COVID-19 pandemic. Methods: A retrospective cohort study of COVID-19 cases in Fulton County, Georgia, USA, reported to a public health surveillance from March 2020 through February 2021. We estimated case-fatality rates (CFR) by wave and used Cox proportional hazards random-effects models in each wave, with random effects at individual and long-term-care-facility level, to determine risk factors associated with rates of mortality. Results: Of 75 289 confirmed cases, 4490 (6%) were diagnosed in wave 1 (CFR 31 deaths/100 000 person days [pd]), 24 293 (32%) in wave 2 (CFR 7 deaths/100 000 pd), and 46 506 (62%) in wave 3 (CFR 9 deaths/100 000 pd). Compared with females, males were more likely to die in each wave: wave 1 (adjusted hazard ratio [aHR], 1.5; 95% confidence interval [CI], 1.2-1.8), wave 2 (aHR 1.5, 95% CI, 1.2-1.8), and wave 3 (aHR 1.7, 95% CI, 1.5-2.0). Compared with non-Hispanic whites, non-Hispanic blacks were more likely to die in each wave: wave 1 (aHR, 1.4; 95% CI, 1.1-1.8), wave 2 (aHR, 1.5; 95% CI, 1.2-1.9), and wave 3 (aHR, 1.7; 95% CI, 1.4-2.0). Cases with any disability, chronic renal disease, and cardiovascular disease were more likely to die in each wave compared with those without these comorbidities. Conclusions: Our study found gender and racial/ethnic disparities in COVID-19 mortality and certain comorbidities associated with COVID-19 mortality. These factors have persisted throughout the COVID-19 pandemic waves, despite improvements in diagnosis and treatment.

Characteristics and Risk Factors for Mortality by COVID-19 Pandemic Waves in Fulton County, Georgia: A Cohort Study March 2020–February 2021

Background We examined differences in mortality among COVID-19 cases in the first, second and third waves of the COVID-19 pandemic. Methods A retrospective cohort study of COVID-19 cases in Fulton County, Georgia, USA, reported to a public health surveillance from March 2020 through February 2021. We estimated case fatality rates (CFR) by wave and used Cox proportional hazards random effects models in each wave, with random effects at individual and long-term-care-facility level, to determine risk factors associated with rates of mortality. Results Of 75,289 confirmed cases, 4,490 (6%) were diagnosed in wave one (CFR 31 deaths/100,000 person days [pd]), 24,293 (32%) in wave two (CFR 7 deaths/100,000 pd), and 46,506 (62%) in wave three (CFR 9 deaths/100,000 pd). Compared to females, males were more likely to die in each wave: Wave one (adjusted hazard ratio [aHR] 1.5, 95% confidence interval [CI] 1.2–1.8), wave two (aHR 1.5, 95% CI 1.2–1.8), and wave three (aHR 1.7, 95% CI 1.5–2.0). Compared to non-Hispanic Whites, non-Hispanic Blacks were more likely to die in each wave: Wave one (aHR 1.4, 95% CI 1.1–1.8), wave two (aHR 1.5, 95% CI 1.2–1.9), and wave three (aHR 1.7, 95% CI 1.4–2.0). Cases with any disability, chronic renal disease, and cardiovascular disease were more likely to die in each wave compared to those without these comorbidities. Conclusions Our study found gender and racial/ethnic disparities in COVID-19 mortality, and certain comorbidities associated with COVID-19 mortality. These factors have persisted throughout the COVID-19 pandemic waves, despite improvements in diagnosis and treatment.

Cumulative Incidence of SARS-CoV-2 Infections Among Adults in Georgia, United States, August to December 2020.

BACKGROUND: Reported coronavirus disease 2019 (COVID-19) cases underestimate true severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. Data on all infections, including asymptomatic infections, are needed. To minimize biases in estimates from reported cases and seroprevalence surveys, we conducted a household-based probability survey and estimated cumulative incidence of SARS-CoV-2 infections adjusted for antibody waning. METHODS: From August to December 2020, we mailed specimen collection kits (nasal swabs and blood spots) to a random sample of Georgia addresses. One household adult completed a survey and returned specimens for virus and antibody testing. We estimated cumulative incidence of SARS-CoV-2 infections adjusted for waning antibodies, reported fraction, and infection fatality ratio (IFR). Differences in seropositivity among demographic, geographic, and clinical subgroups were explored with weighted prevalence ratios (PR). RESULTS: Among 1370 participants, adjusted cumulative incidence of SARS-CoV-2 was 16.1% (95% credible interval [CrI], 13.5%-19.2%) as of 16 November 2020. The reported fraction was 26.6% and IFR was 0.78%. Non-Hispanic black (PR, 2.03; 95% confidence interval [CI], 1.0-4.1) and Hispanic adults (PR, 1.98; 95% CI, .74-5.31) were more likely than non-Hispanic white adults to be seropositive. CONCLUSIONS: As of mid-November 2020, 1 in 6 adults in Georgia had been infected with SARS-CoV-2. The COVID-19 epidemic in Georgia is likely substantially underestimated by reported cases.

Retrospective cohort study of COVID-19 among children in Fulton County, Georgia, March 2020-June 2021.

OBJECTIVE: To describe case rates, testing rates and percent positivity of COVID-19 among children aged 0-18 years by school-age grouping. DESIGN: We 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). SETTING: Fulton County, Georgia. MAIN OUTCOME MEASURES: COVID-19 case rates, testing rates and percent positivity. RESULTS: Over 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. CONCLUSIONS: Low 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.

Assessment of US Public School District Policies for Pandemic Preparedness and Implications for COVID-19 Response Activities.

OBJECTIVES: To describe school district preparedness for school closures and other relevant strategies before the coronavirus disease 2019 (COVID-19) pandemic. METHODS: A stratified random sample of 957 public school districts from the 50 US states and the District of Columbia were surveyed between October 2015 and August 2016. The response rates for the questionnaires were as follows: Healthy and Safe School Environment, Crisis Preparedness Module (60%; N = 572), Nutrition Services (63%; N = 599), and Health Services (64%; N = 613). Data were analyzed using descriptive and regression techniques. RESULTS: Most school districts had procedures that would facilitate the implementation of school closures (88.7%). Fewer districts had plans for ensuring continuity of education (43.0%) or feeding students during closure (33.8%). The prevalence of continuity of education plans was lower in the Midwest than the Northeast (adjusted prevalence ratio [aPR] = 0.68; 95% confidence interval [CI]: 0.51-0.90). Presence of plans for feeding students was higher in high-poverty than low-poverty districts (aPR = 1.41; 95% CI: 1.01-1.99) and in large districts than small districts (aPR = 2.06; 95% CI: 1.37-3.09). CONCLUSIONS: Understanding factors associated with having comprehensive emergency plans could help decision makers to target assistance during the current COVID-19 pandemic and for future planning purposes.