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1.
Ann Epidemiol ; 72: 57-64, 2022 May 29.
Article in English | MEDLINE | ID: covidwho-1866848

ABSTRACT

PURPOSE: To examine whether declines in the crude U.S. COVID-19 case fatality ratio is due to improved clinical care and/or other factors. METHODS: We used multivariable logistic regression, adjusted for age and other individual-level characteristics, to examine associations between report month and mortality among confirmed and probable COVID-19 cases and hospitalized cases in Georgia reported March 2, 2020 to March 31, 2021. RESULTS: Compared to August 2020, mortality risk among cases was lowest in November 2020 (OR = 0.84; 95% CI: 0.78-0.91) and remained lower until March 2021 (OR = 0.86; 95% CI: 0.77-0.95). Among hospitalized cases, mortality risk increased in December 2020 (OR = 1.16, 95% CI: 1.07-1.27) and January 2021 (OR = 1.25; 95% CI: 1.14-1.36), before declining until March 2021 (OR = 0.90, 95% CI: 0.78-1.04). CONCLUSIONS: After adjusting for other factors, including the shift to a younger age distribution of cases, we observed lower mortality risk from November 2020 to March 2021 compared to August 2020 among cases. This suggests that improved clinical management may have contributed to lower mortality risk. Among hospitalized cases, mortality risk increased again in December 2020 and January 2021, but then decreased to a risk similar to that among all cases by March 2021.

2.
Epidemiology ; 2022 May 19.
Article in English | MEDLINE | ID: covidwho-1853260

ABSTRACT

BACKGROUND: U.S. long-term care facilities have experienced a disproportionate burden of COVID-19 morbidity and mortality. METHODS: We examined SARS-CoV-2 transmission among residents and staff in 60 long-term care facilities in Fulton County, Georgia, from March 2020 to September 2021. Using the Wallinga-Teunis method to estimate the time-varying reproduction number, R(t), and linear mixed regression models, we examined associations between case characteristics and R(t). RESULTS: Case counts, outbreak size and duration, and R(t) declined rapidly and remained low after vaccines were first distributed to long-term care facilities in December 2020, despite increases in community incidence in summer 2021. Staff cases were more infectious than resident cases (average individual reproduction number, Ri = 0.6 [95%CI: 0.4-0.7] and 0.1 [95%CI: 0.1-0.2], respectively). Unvaccinated resident cases were more infectious than vaccinated resident cases (Ri = 0.5 [95%CI: 0.4-0.6] and 0.2 [95%CI: 0.0-0.8], respectively), but estimates were imprecise. CONCLUSIONS: COVID-19 vaccines slowed transmission and contributed to reduced caseload in long-term care facilities. However, due to data limitations, we were unable to determine whether breakthrough vaccinated cases were less infectious than unvaccinated cases. Staff cases were six times more infectious than resident cases, consistent with the hypothesis that staff were the primary drivers of SARS-CoV-2 transmission in long-term care facilities.

3.
Sci Rep ; 12(1): 4637, 2022 03 17.
Article in English | MEDLINE | ID: covidwho-1751759

ABSTRACT

Social distancing measures are effective in reducing overall community transmission but much remains unknown about how they have impacted finer-scale dynamics. In particular, much is unknown about how changes of contact patterns and other behaviors including adherence to social distancing, induced by these measures, may have impacted finer-scale transmission dynamics among different age groups. In this paper, we build a stochastic age-specific transmission model to systematically characterize the degree and variation of age-specific transmission dynamics, before and after lifting the lockdown in Georgia, USA. We perform Bayesian (missing-)data-augmentation model inference, leveraging reported age-specific case, seroprevalence and mortality data. We estimate that overall population-level transmissibility was reduced to 41.2% with 95% CI [39%, 43.8%] of the pre-lockdown level in about a week of the announcement of the shelter-in-place order. Although it subsequently increased after the lockdown was lifted, it only bounced back to 62% [58%, 67.2%] of the pre-lockdown level after about a month. We also find that during the lockdown susceptibility to infection increases with age. Specifically, relative to the oldest age group (> 65+), susceptibility for the youngest age group (0-17 years) is 0.13 [0.09, 0.18], and it increases to 0.53 [0.49, 0.59] for 18-44 and 0.75 [0.68, 0.82] for 45-64. More importantly, our results reveal clear changes of age-specific susceptibility (defined as average risk of getting infected during an infectious contact incorporating age-dependent behavioral factors) after the lockdown was lifted, with a trend largely consistent with reported age-specific adherence levels to social distancing and preventive measures. Specifically, the older groups (> 45) (with the highest levels of adherence) appear to have the most significant reductions of susceptibility (e.g., post-lockdown susceptibility reduced to 31.6% [29.3%, 34%] of the estimate before lifting the lockdown for the 6+ group). Finally, we find heterogeneity in case reporting among different age groups, with the lowest rate occurring among the 0-17 group (9.7% [6.4%, 19%]). Our results provide a more fundamental understanding of the impacts of stringent lockdown measures, and finer evidence that other social distancing and preventive measures may be effective in reducing SARS-CoV-2 transmission. These results may be exploited to guide more effective implementations of these measures in many current settings (with low vaccination rate globally and emerging variants) and in future potential outbreaks of novel pathogens.


Subject(s)
COVID-19 , Physical Distancing , Adolescent , Age Factors , Bayes Theorem , COVID-19/epidemiology , COVID-19/prevention & control , Child , Child, Preschool , Communicable Disease Control , Humans , Infant , Infant, Newborn , SARS-CoV-2 , Seroepidemiologic Studies
4.
Ann Intern Med ; 174(5): 649-654, 2021 05.
Article in English | MEDLINE | ID: covidwho-1726736

ABSTRACT

BACKGROUND: Identifying occupational risk factors for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection among health care workers (HCWs) can improve HCW and patient safety. OBJECTIVE: To quantify demographic, occupational, and community risk factors for SARS-CoV-2 seropositivity among HCWs in a large health care system. DESIGN: A logistic regression model was fitted to data from a cross-sectional survey conducted in April to June 2020, linking risk factors for occupational and community exposure to coronavirus disease 2019 (COVID-19) with SARS-CoV-2 seropositivity. SETTING: A large academic health care system in the Atlanta, Georgia, metropolitan area. PARTICIPANTS: Employees and medical staff members elected to participate in SARS-CoV-2 serology testing offered to all HCWs as part of a quality initiative and completed a survey on exposure to COVID-19 and use of personal protective equipment. MEASUREMENTS: Demographic risk factors for COVID-19, residential ZIP code incidence of COVID-19, occupational exposure to HCWs or patients who tested positive on polymerase chain reaction test, and use of personal protective equipment as potential risk factors for infection. The outcome was SARS-CoV-2 seropositivity. RESULTS: Adjusted SARS-CoV-2 seropositivity was estimated to be 3.8% (95% CI, 3.4% to 4.3%) (positive, n = 582) among the 10 275 HCWs (35% of the Emory Healthcare workforce) who participated in the survey. Community contact with a person known or suspected to have COVID-19 (adjusted odds ratio [aOR], 1.9 [CI, 1.4 to 2.6]; 77 positive persons [10.3%]) and community COVID-19 incidence (aOR, 1.5 [CI, 1.0 to 2.2]) increased the odds of infection. Black individuals were at high risk (aOR, 2.1 [CI, 1.7 to 2.6]; 238 positive persons [8.3%]). LIMITATIONS: Participation rates were modest and key workplace exposures, including job and infection prevention practices, changed rapidly in the early phases of the pandemic. CONCLUSION: Demographic and community risk factors, including contact with a COVID-19-positive person and Black race, are more strongly associated with SARS-CoV-2 seropositivity among HCWs than is exposure in the workplace. PRIMARY FUNDING SOURCE: Emory COVID-19 Response Collaborative.


Subject(s)
COVID-19/epidemiology , Health Personnel , Infectious Disease Transmission, Patient-to-Professional , Occupational Diseases/epidemiology , Occupational Exposure/adverse effects , Pneumonia, Viral/epidemiology , Adult , COVID-19/ethnology , Cross-Sectional Studies , Female , Georgia/epidemiology , Humans , Male , Middle Aged , Occupational Diseases/ethnology , Pandemics , Personal Protective Equipment , Pneumonia, Viral/ethnology , Pneumonia, Viral/virology , Risk Factors , SARS-CoV-2 , Surveys and Questionnaires , United States/epidemiology
5.
Infect Control Hosp Epidemiol ; : 1-8, 2022 Feb 14.
Article in English | MEDLINE | ID: covidwho-1713057

ABSTRACT

OBJECTIVES: To determine the incidence of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) infection among healthcare personnel (HCP) and to assess occupational risks for SARS-CoV-2 infection. DESIGN: Prospective cohort of healthcare personnel (HCP) followed for 6 months from May through December 2020. SETTING: Large academic healthcare system including 4 hospitals and affiliated clinics in Atlanta, Georgia. PARTICIPANTS: HCP, including those with and without direct patient-care activities, working during the coronavirus disease 2019 (COVID-19) pandemic. METHODS: Incident SARS-CoV-2 infections were determined through serologic testing for SARS-CoV-2 IgG at enrollment, at 3 months, and at 6 months. HCP completed monthly surveys regarding occupational activities. Multivariable logistic regression was used to identify occupational factors that increased the risk of SARS-CoV-2 infection. RESULTS: Of the 304 evaluable HCP that were seronegative at enrollment, 26 (9%) seroconverted for SARS-CoV-2 IgG by 6 months. Overall, 219 participants (73%) self-identified as White race, 119 (40%) were nurses, and 121 (40%) worked on inpatient medical-surgical floors. In a multivariable analysis, HCP who identified as Black race were more likely to seroconvert than HCP who identified as White (odds ratio, 4.5; 95% confidence interval, 1.3-14.2). Increased risk for SARS-CoV-2 infection was not identified for any occupational activity, including spending >50% of a typical shift at a patient's bedside, working in a COVID-19 unit, or performing or being present for aerosol-generating procedures (AGPs). CONCLUSIONS: In our study cohort of HCP working in an academic healthcare system, <10% had evidence of SARS-CoV-2 infection over 6 months. No specific occupational activities were identified as increasing risk for SARS-CoV-2 infection.

6.
J Am Med Dir Assoc ; 23(6): 942-946.e1, 2022 06.
Article in English | MEDLINE | ID: covidwho-1712740

ABSTRACT

OBJECTIVES: Estimate incidence of and risks for SARS-CoV-2 infection among nursing home staff in the state of Georgia during the 2020-2021 Winter COVID-19 Surge in the United States. DESIGN: Serial survey and serologic testing at 2 time points with 3-month interval exposure assessment. SETTING AND PARTICIPANTS: Fourteen nursing homes in the state of Georgia; 203 contracted or employed staff members from those 14 participating nursing homes who were seronegative at the first time point and provided a serology specimen at second time point, at which time they reported no COVID-19 vaccination or only very recent vaccination (≤4 weeks). METHODS: Interval infection was defined as seroconversion to antibody presence for both nucleocapsid protein and spike protein. We estimated adjusted odds ratios (aORs) and 95% CIs by job type, using multivariable logistic regression, accounting for community-based risks including interval community incidence and interval change in resident infections per bed. RESULTS: Among 203 eligible staff, 72 (35.5%) had evidence of interval infection. In multivariable analysis among unvaccinated staff, staff SARS-CoV-2 infection-induced seroconversion was significantly higher among nurses and certified nursing assistants accounting for race and interval infection incidence in both the community and facility (aOR 5.3, 95% CI 1.0-28.4). This risk persisted but was attenuated when using the full study cohort including those with very recent vaccination. CONCLUSIONS AND IMPLICATIONS: Midway through the first year of the pandemic, job type continues to be associated with increased risk for infection despite enhanced infection prevention efforts including routine screening of staff. These results suggest that mitigation strategies prior to vaccination did not eliminate occupational risk for infection and emphasize critical need to maximize vaccine utilization to eliminate excess risk among front-line providers.


Subject(s)
COVID-19 , COVID-19/epidemiology , Georgia/epidemiology , Humans , Nursing Homes , Pandemics , SARS-CoV-2 , United States
7.
Clin Infect Dis ; 74(7): 1141-1150, 2022 Apr 09.
Article in English | MEDLINE | ID: covidwho-1700667

ABSTRACT

BACKGROUND: Reported 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. METHODS: From 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. RESULTS: Among 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. CONCLUSIONS: One 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.


Subject(s)
COVID-19 , SARS-CoV-2 , Adult , Antibodies, Viral , COVID-19/epidemiology , Humans , Immunoglobulin A , Incidence , Pandemics , United States/epidemiology
8.
J Infect Dis ; 225(3): 396-403, 2022 02 01.
Article in English | MEDLINE | ID: covidwho-1672203

ABSTRACT

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.


Subject(s)
COVID-19 , Adult , Antibodies, Viral/blood , COVID-19/epidemiology , Georgia/epidemiology , Humans , Incidence , Seroepidemiologic Studies
9.
Nat Commun ; 12(1): 7063, 2021 12 03.
Article in English | MEDLINE | ID: covidwho-1550283

ABSTRACT

Serological testing remains a passive component of the public health response to the COVID-19 pandemic. Using a transmission model, we examine how serological testing could have enabled seropositive individuals to increase their relative levels of social interaction while offsetting transmission risks. We simulate widespread serological testing in New York City, South Florida, and Washington Puget Sound and assume seropositive individuals partially restore their social contacts. Compared to no intervention, our model suggests that widespread serological testing starting in late 2020 would have averted approximately 3300 deaths in New York City, 1400 deaths in South Florida and 11,000 deaths in Washington State by June 2021. In all sites, serological testing blunted subsequent waves of transmission. Findings demonstrate the potential benefit of widespread serological testing, had it been implemented in the pre-vaccine era, and remain relevant now amid the potential for emergence of new variants.


Subject(s)
COVID-19 Serological Testing/statistics & numerical data , COVID-19/diagnosis , Pandemics/prevention & control , Physical Distancing , COVID-19/mortality , COVID-19/transmission , COVID-19/virology , Computer Simulation , Florida/epidemiology , Humans , New York City/epidemiology , Pandemics/statistics & numerical data , Washington/epidemiology
10.
Open Forum Infect Dis ; 8(8): ofab379, 2021 Aug.
Article in English | MEDLINE | ID: covidwho-1526178

ABSTRACT

BACKGROUND: California has reported the largest number of coronavirus disease 2019 (COVID-19) cases of any US state, with more than 3.5 million confirmed as of March 2021. However, the full breadth of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission in California is unknown as reported cases only represent a fraction of all infections. METHODS: We conducted a population-based serosurvey, utilizing mailed, home-based SARS-CoV-2 antibody testing along with a demographic and behavioral survey. We weighted data from a random sample to represent the adult California population and estimated period seroprevalence overall and by participant characteristics. Seroprevalence estimates were adjusted for waning antibodies to produce statewide estimates of cumulative incidence, the infection fatality ratio (IFR), and the reported fraction. RESULTS: California's SARS-CoV-2 weighted seroprevalence during August-December 2020 was 4.6% (95% CI, 2.8%-7.4%). Estimated cumulative incidence as of November 2, 2020, was 8.7% (95% CrI, 6.4%-11.5%), indicating that 2 660 441 adults (95% CrI, 1 959 218-3 532 380) had been infected. The estimated IFR was 0.8% (95% CrI, 0.6%-1.0%), and the estimated percentage of infections reported to the California Department of Public Health was 31%. Disparately high risk for infection was observed among persons of Hispanic/Latinx ethnicity and people with no health insurance and who reported working outside the home. CONCLUSIONS: We present the first statewide SARS-CoV-2 cumulative incidence estimate among adults in California. As of November 2020, ~1 in 3 SARS-CoV-2 infections in California adults had been identified by public health surveillance. When accounting for unreported SARS-CoV-2 infections, disparities by race/ethnicity seen in case-based surveillance persist.

12.
Epidemics ; 37: 100488, 2021 12.
Article in English | MEDLINE | ID: covidwho-1364011

ABSTRACT

SARS-CoV-2 outbreaks have occurred on several nautical vessels, driven by the high-density contact networks on these ships. Optimal strategies for prevention and control that account for realistic contact networks are needed. We developed a network-based transmission model for SARS-CoV-2 on the Diamond Princess outbreak to characterize transmission dynamics and to estimate the epidemiological impact of outbreak control and prevention measures. This model represented the dynamic multi-layer network structure of passenger-passenger, passenger-crew, and crew-crew contacts, both before and after the large-scale network lockdown imposed on the ship in response to the disease outbreak. Model scenarios evaluated variations in the timing of the network lockdown, reduction in contact intensity within the sub-networks, and diagnosis-based case isolation on outbreak prevention. We found that only extreme restrictions in contact patterns during network lockdown and idealistic clinical response scenarios could avert a major COVID-19 outbreak. Contact network changes associated with adequate outbreak prevention were the restriction of passengers to their cabins, with limited passenger-crew contacts. Clinical response strategies required for outbreak prevention may be infeasible in many cruise settings: early mass screening with an ideal PCR test (100 % sensitivity) and immediate case isolation upon diagnosis. Personal protective equipment (e.g., facemasks) had limited impact in this environment because the majority of transmissions after the ship lockdown occurred between passengers in cabins where masks were not consistently used. Public health restrictions on optional leisure activities like these should be considered until longer-term effective solutions such as a COVID-19 vaccine become widely available.


Subject(s)
COVID-19 , Ships , COVID-19 Vaccines , Communicable Disease Control , Humans , SARS-CoV-2
13.
Ann Epidemiol ; 63: 75-78, 2021 11.
Article in English | MEDLINE | ID: covidwho-1363868

ABSTRACT

In the effort to control SARS-CoV-2 transmission, public health agencies in the United States and globally are aiming to increase population immunity. Immunity through vaccination and acquired following recovery from natural infection are the two means to build up population immunity, with vaccination being the safe pathway. However, measuring the contribution to population immunity from vaccination or natural infection is non-trivial. Historical COVID-19 case counts and vaccine coverage are necessary information but are not sufficient to approximate population immunity. Here, we consider the nuances of measuring each and propose an analytical framework for integrating the necessary data on cumulative vaccinations and natural infections at the state and national level. To guide vaccine roll-out and other aspects of control over the coming months, we recommend analytics that combine vaccine coverage with local (e.g. county-level) history of case reports and adjustment for waning antibodies to establish local estimates of population immunity. To do so, the strategic use of minimally-biased serology surveys integrated with vaccine administration data can improve estimates of the aggregate level of immunity to guide data-driven decisions to re-open safely and prioritize vaccination efforts.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19 Vaccines , Humans , Public Health , United States/epidemiology , Vaccination
14.
Science ; 373(6552): 280-281, 2021 07 16.
Article in English | MEDLINE | ID: covidwho-1315791
15.
Elife ; 102021 07 13.
Article in English | MEDLINE | ID: covidwho-1308531

ABSTRACT

Background: Vaccination is one of the most effective public health interventions. We investigate the impact of vaccination activities for Haemophilus influenzae type b, hepatitis B, human papillomavirus, Japanese encephalitis, measles, Neisseria meningitidis serogroup A, rotavirus, rubella, Streptococcus pneumoniae, and yellow fever over the years 2000-2030 across 112 countries. Methods: Twenty-one mathematical models estimated disease burden using standardised demographic and immunisation data. Impact was attributed to the year of vaccination through vaccine-activity-stratified impact ratios. Results: We estimate 97 (95%CrI[80, 120]) million deaths would be averted due to vaccination activities over 2000-2030, with 50 (95%CrI[41, 62]) million deaths averted by activities between 2000 and 2019. For children under-5 born between 2000 and 2030, we estimate 52 (95%CrI[41, 69]) million more deaths would occur over their lifetimes without vaccination against these diseases. Conclusions: This study represents the largest assessment of vaccine impact before COVID-19-related disruptions and provides motivation for sustaining and improving global vaccination coverage in the future. Funding: VIMC is jointly funded by Gavi, the Vaccine Alliance, and the Bill and Melinda Gates Foundation (BMGF) (BMGF grant number: OPP1157270 / INV-009125). Funding from Gavi is channelled via VIMC to the Consortium's modelling groups (VIMC-funded institutions represented in this paper: Imperial College London, London School of Hygiene and Tropical Medicine, Oxford University Clinical Research Unit, Public Health England, Johns Hopkins University, The Pennsylvania State University, Center for Disease Analysis Foundation, Kaiser Permanente Washington, University of Cambridge, University of Notre Dame, Harvard University, Conservatoire National des Arts et Métiers, Emory University, National University of Singapore). Funding from BMGF was used for salaries of the Consortium secretariat (authors represented here: TBH, MJ, XL, SE-L, JT, KW, NMF, KAMG); and channelled via VIMC for travel and subsistence costs of all Consortium members (all authors). We also acknowledge funding from the UK Medical Research Council and Department for International Development, which supported aspects of VIMC's work (MRC grant number: MR/R015600/1).JHH acknowledges funding from National Science Foundation Graduate Research Fellowship; Richard and Peggy Notebaert Premier Fellowship from the University of Notre Dame. BAL acknowledges funding from NIH/NIGMS (grant number R01 GM124280) and NIH/NIAID (grant number R01 AI112970). The Lives Saved Tool (LiST) receives funding support from the Bill and Melinda Gates Foundation.This paper was compiled by all coauthors, including two coauthors from Gavi. Other funders had no role in study design, data collection, data analysis, data interpretation, or writing of the report. All authors had full access to all the data in the study and had final responsibility for the decision to submit for publication.


Subject(s)
Bacterial Infections/prevention & control , Bacterial Vaccines/therapeutic use , COVID-19 , Global Health , Models, Biological , SARS-CoV-2 , Bacterial Infections/epidemiology , Humans
16.
Clin Infect Dis ; 74(7): 1141-1150, 2022 Apr 09.
Article in English | MEDLINE | ID: covidwho-1303900

ABSTRACT

BACKGROUND: Reported 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. METHODS: From 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. RESULTS: Among 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. CONCLUSIONS: One 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.


Subject(s)
COVID-19 , SARS-CoV-2 , Adult , Antibodies, Viral , COVID-19/epidemiology , Humans , Immunoglobulin A , Incidence , Pandemics , United States/epidemiology
17.
J Infect Dis ; 224(1): 9-13, 2021 07 02.
Article in English | MEDLINE | ID: covidwho-1294727

ABSTRACT

In April 2020, the incidence of norovirus outbreaks reported to the National Outbreak Reporting System dramatically declined. We used regression models to determine if this decline was best explained by underreporting, seasonal trends, or reduced exposure due to nonpharmaceutical interventions (NPIs) implemented for severe acute respiratory syndrome coronavirus 2 using data from 9 states from July 2012 to July 2020. The decline in norovirus outbreaks was significant for all 9 states, and underreporting and/or seasonality are unlikely to be the primary explanation for these findings. These patterns were similar across a variety of settings. NPIs appear to have reduced incidence of norovirus, a nonrespiratory pathogen.


Subject(s)
COVID-19/epidemiology , COVID-19/virology , Caliciviridae Infections/epidemiology , Caliciviridae Infections/virology , Coinfection , Norovirus , SARS-CoV-2 , COVID-19/diagnosis , COVID-19/therapy , Cross Infection , Disease Management , Disease Outbreaks , Humans , Incidence , Seasons , United States/epidemiology
18.
Infect Control Hosp Epidemiol ; 43(3): 381-386, 2022 03.
Article in English | MEDLINE | ID: covidwho-1246283

ABSTRACT

Among 353 healthcare personnel in a longitudinal cohort in 4 hospitals in Atlanta, Georgia (May-June 2020), 23 (6.5%) had severe acute respiratory coronavirus virus 2 (SARS-CoV-2) antibodies. Spending >50% of a typical shift at the bedside (OR, 3.4; 95% CI, 1.2-10.5) and black race (OR, 8.4; 95% CI, 2.7-27.4) were associated with SARS-CoV-2 seropositivity.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/prevention & control , Cross-Sectional Studies , Delivery of Health Care , Health Personnel , Humans , Risk Factors
19.
Epidemiology ; 32(4): 508-517, 2021 07 01.
Article in English | MEDLINE | ID: covidwho-1232231

ABSTRACT

Observational studies of the effectiveness of vaccines to prevent COVID-19 are needed to inform real-world use. Such studies are now underway amid the ongoing rollout of SARS-CoV-2 vaccines globally. Although traditional case-control and test-negative design studies feature prominently among strategies used to assess vaccine effectiveness, such studies may encounter important threats to validity. Here, we review the theoretical basis for estimation of vaccine direct effects under traditional case-control and test-negative design frameworks, addressing specific natural history parameters of SARS-CoV-2 infection and COVID-19 relevant to these designs. Bias may be introduced by misclassification of cases and controls, particularly when clinical case criteria include common, nonspecific indicators of COVID-19. When using diagnostic assays with high analytical sensitivity for SARS-CoV-2 detection, individuals testing positive may be counted as cases even if their symptoms are due to other causes. The traditional case-control design may be particularly prone to confounding due to associations of vaccination with healthcare-seeking behavior or risk of infection. The test-negative design reduces but may not eliminate this confounding, for instance, if individuals who receive vaccination seek care or testing for less-severe illness. These circumstances indicate the two study designs cannot be applied naively to datasets gathered through public health surveillance or administrative sources. We suggest practical strategies to reduce bias in vaccine effectiveness estimates at the study design and analysis stages.


Subject(s)
COVID-19 , Vaccines , COVID-19 Vaccines , Humans , Retrospective Studies , SARS-CoV-2
20.
Epidemiology ; 32(4): 518-524, 2021 07 01.
Article in English | MEDLINE | ID: covidwho-1211432

ABSTRACT

BACKGROUND: Serology tests can identify previous infections and facilitate estimation of the number of total infections. However, immunoglobulins targeting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been reported to wane below the detectable level of serologic assays (which is not necessarily equivalent to the duration of protective immunity). We estimate the cumulative incidence of SARS-CoV-2 infection from serology studies, accounting for expected levels of antibody acquisition (seroconversion) and waning (seroreversion), and apply this framework using data from New York City and Connecticut. METHODS: We estimated time from seroconversion to seroreversion and infection fatality ratio (IFR) using mortality data from March to October 2020 and population-level cross-sectional seroprevalence data from April to August 2020 in New York City and Connecticut. We then estimated the daily seroprevalence and cumulative incidence of SARS-CoV-2 infection. RESULTS: The estimated average time from seroconversion to seroreversion was 3-4 months. The estimated IFR was 1.1% (95% credible interval, 1.0%, 1.2%) in New York City and 1.4% (1.1, 1.7%) in Connecticut. The estimated daily seroprevalence declined after a peak in the spring. The estimated cumulative incidence reached 26.8% (24.2%, 29.7%) at the end of September in New York City and 8.8% (7.1%, 11.3%) in Connecticut, higher than maximum seroprevalence measures (22.1% and 6.1%), respectively. CONCLUSIONS: The cumulative incidence of SARS-CoV-2 infection is underestimated using cross-sectional serology data without adjustment for waning antibodies. Our approach can help quantify the magnitude of underestimation and adjust estimates for waning antibodies.


Subject(s)
COVID-19 , SARS-CoV-2 , Antibodies, Viral , Connecticut/epidemiology , Cross-Sectional Studies , Humans , Incidence , New York City , Seroepidemiologic Studies
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