Use of COVIDTests.gov At-Home Test Kits Among Adults in a National Household Probability Sample - United States, 2022.

At-home rapid antigen COVID-19 tests were first authorized by the Food and Drug Administration in late 2020 (1-3). In January 2022, the White House launched COVIDTests.gov, which made all U.S. households eligible to receive free-to-the-user at-home test kits distributed by the U.S. Postal Service (2). By May 2022, more than 70 million test kit packages had been shipped to households across the United States (2); however, how these kits were used, and which groups were using them, has not been reported. Data from a national probability survey of U.S. households (COVIDVu), collected during April-May 2022, were used to evaluate awareness about and use of these test kits (4). Most respondent households (93.8%) were aware of the program, and more than one half (59.9%) had ordered kits. Among persons who received testing for COVID-19 during the preceding 6 months, 38.3% used a COVIDTests.gov kit. Among kit users, 95.5% rated the experience as acceptable, and 23.6% reported being unlikely to have tested without the COVIDTests.gov program. Use of COVIDTests.gov kits was similar among racial and ethnic groups (42.1% non-Hispanic Black or African American [Black]; 41.5% Hispanic or Latino [Hispanic]; 34.8% non-Hispanic White [White]; and 53.7% non-Hispanic other races [other races]). Use of other home COVID-19 tests differed by race and ethnicity (11.8% Black, 44.4% Hispanic, 45.8% White, 43.8% other races). Compared with White persons, Black persons were 72% less likely to use other home test kits (adjusted relative risk [aRR] = 0.28; 95% CI = 0.16-0.50). Provision of tests through this well-publicized program likely improved use of COVID-19 home testing and health equity in the United States, particularly among Black persons. National programs to address availability and accessibility of critical health services in a pandemic response have substantial health value.

Population-Level Relative Effectiveness of the COVID-19 Vaccines and the Contribution of Naturally Acquired Immunity.

BACKGROUND: Immune protection against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can be induced by natural infection or vaccination or both. Interaction between vaccine-induced immunity and naturally acquired immunity at the population level has been understudied. METHODS: We used regression models to evaluate whether the impact of coronavirus disease 2019 (COVID-19) vaccines differed across states with different levels of naturally acquired immunity from March 2021 to April 2022 in the United States. Analysis was conducted for 3 evaluation periods separately (Alpha, Delta, and Omicron waves). As a proxy for the proportion of the population with naturally acquired immunity, we used either the reported seroprevalence or the estimated proportion of the population ever infected in each state. RESULTS: COVID-19 mortality decreased as coverage of ≥1 dose increased among people ≥65 years of age, and this effect did not vary by seroprevalence or proportion of the total population ever infected. Seroprevalence and proportion ever infected were not associated with COVID-19 mortality, after controlling for vaccine coverage. These findings were consistent in all evaluation periods. CONCLUSIONS: COVID-19 vaccination was associated with a sustained reduction in mortality at state level during the Alpha, Delta, and Omicron periods. The effect did not vary by naturally acquired immunity.

Risk factors for severe acute respiratory coronavirus virus 2 (SARS-CoV-2) seropositivity among nursing home staff.

Objectives: To estimate prior severe acute respiratory coronavirus virus 2 (SARS-CoV-2) infection among skilled nursing facility (SNF) staff in the state of Georgia and to identify risk factors for seropositivity as of fall 2020. Design: Baseline survey and seroprevalence of the ongoing longitudinal Coronavirus 2019 (COVID-19) Prevention in Nursing Homes study. Setting: The study included 14 SNFs in the state of Georgia. Participants: In total, 792 SNF staff employed or contracted with participating SNFs were included in this study. The analysis included 749 participants with SARS-CoV-2 serostatus results who provided age, sex, and complete survey information. Methods: We estimated unadjusted odds ratios (ORs) and 95% confidence intervals (95% CIs) for potential risk factors and SARS-CoV-2 serostatus. We estimated adjusted ORs using a logistic regression model including age, sex, community case rate, SNF resident infection rate, working at other facilities, and job role. Results: Staff working in high-infection SNFs were twice as likely (unadjusted OR, 2.08; 95% CI, 1.45-3.00) to be seropositive as those in low-infection SNFs. Certified nursing assistants and nurses were 3 times more likely to be seropositive than administrative, pharmacy, or nonresident care staff: unadjusted OR, 2.93 (95% CI, 1.58-5.78) and unadjusted OR, 3.08 (95% CI, 1.66-6.07). Logistic regression yielded similar adjusted ORs. Conclusions: Working at high-infection SNFs was a risk factor for SARS-CoV-2 seropositivity. Even after accounting for resident infections, certified nursing assistants and nurses had a 3-fold higher risk of SARS-CoV-2 seropositivity than nonclinical staff. This knowledge can guide prioritized implementation of safer ways for caregivers to provide necessary care to SNF residents.

Association of Guideline Complexity With Individuals' Ability to Determine Eligibility for COVID-19 Vaccination.

This cross-sectional study examines the association between the complexity of consumer guidelines for COVID-19 vaccination and identification of eligibility.

Nationally representative social contact patterns among U.S. adults, August 2020-April 2021.

The response to the COVID-19 pandemic in the U.S prompted abrupt and dramatic changes to social contact patterns. Monitoring changing social behavior is essential to provide reliable input data for mechanistic models of infectious disease, which have been increasingly used to support public health policy to mitigate the impacts of the pandemic. While some studies have reported on changing contact patterns throughout the pandemic, few have reported differences in contact patterns among key demographic groups and none have reported nationally representative estimates. We conducted a national probability survey of US households and collected information on social contact patterns during two time periods: August-December 2020 (before widespread vaccine availability) and March-April 2021 (during national vaccine rollout). Overall, contact rates in Spring 2021 were similar to those in Fall 2020, with most contacts reported at work. Persons identifying as non-White, non-Black, non-Asian, and non-Hispanic reported high numbers of contacts relative to other racial and ethnic groups. Contact rates were highest in those reporting occupations in retail, hospitality and food service, and transportation. Those testing positive for SARS-CoV-2 antibodies reported a higher number of daily contacts than those who were seronegative. Our findings provide evidence for differences in social behavior among demographic groups, highlighting the profound disparities that have become the hallmark of the COVID-19 pandemic.

Declining COVID-19 case-fatality in Georgia, USA, March 2020 to March 2021: a sign of real improvement or a broadening epidemic?

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.

The Role of Staff in Transmission of SARS-CoV-2 in Long-term Care Facilities.

BACKGROUND: US long-term care facilities (LTCFs) have experienced a disproportionate burden of COVID-19 morbidity and mortality. METHODS: We examined SARS-CoV-2 transmission among residents and staff in 60 LTCFs 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 LTCFs in December 2020, despite increases in community incidence in summer 2021. Staff cases were more infectious than resident cases (average individual reproduction number, R i = 0.6 [95% confidence intervals [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 (R i = 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 LTCFs. 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 LTCFs.

Post-lockdown changes of age-specific susceptibility and its correlation with adherence to social distancing measures.

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.

Quantification of Occupational and Community Risk Factors for SARS-CoV-2 Seropositivity Among Health Care Workers in a Large U.S. Health Care System.

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.

Occupational risk factors for severe acute respiratory coronavirus virus 2 (SARS-CoV-2) infection among healthcare personnel: A 6-month prospective analysis of the COVID-19 Prevention in Emory Healthcare Personnel (COPE) Study.

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.

Quantifying Risk for SARS-CoV-2 Infection Among Nursing Home Workers for the 2020-2021 Winter Surge of the COVID-19 Pandemic in Georgia, USA.

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.

Severe Acute Respiratory Syndrome Coronavirus 2 Cumulative Incidence, United States, August 2020-December 2020.

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.

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.

Modeling serological testing to inform relaxation of social distancing for COVID-19 control.

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.

SARS-CoV-2 Cumulative Incidence and Period Seroprevalence: Results From a Statewide Population-Based Serosurvey in California.

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.

Dynamic network strategies for SARS-CoV-2 control on a cruise ship.

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.

A framework for monitoring population immunity to SARS-CoV-2.

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.