We estimated monthly cross-sectional seroprevalence rates of anti-nucleocapsid (anti-N) and anti-spike (anti-S) antibodies to severe acute respiratory syndrome coronavirus 2 in two U.S. nationwide studies. The nationwide blood donor seroprevalence (NBDS) study included specimens from blood donors, while the nationwide commercial laboratory seroprevalence (NCLS) study included residual serum specimens tested in commercial laboratories for reasons unrelated to the assessment of coronavirus disease 2019 infection. In September-December 2021, specimens collected from both nationwide studies were tested for anti-N antibodies. In September-October 2021, specimens from both studies within a five-state area were tested for anti-S antibodies. We used raking methods to adjust all seroprevalence estimates by the population distribution of key demographics in included states. Seroprevalence estimates of each antibody type were compared across the two studies for specimens drawn in the same U.S. states during the same time period. Our analysis revealed that over a 4-month period, national NCLS monthly anti-N estimates were 0.5-1.9 percentage points higher than NBDS estimates. In contrast, across five states during a 2-month period, NBDS anti-S estimates were 7.6 and 8.2 percentage points higher than NCLS estimates. The observed differences in seroprevalence estimates between the NBDS and NCLS studies may be attributed to variations in the characteristics of the study sample populations, particularly with respect to health status, health behaviors, and vaccination status. These differences should be considered in the interpretation of seroprevalence study results based on blood donors or commercial lab residual specimens. IMPORTANCE: This study was the first systematic comparison between two nationwide severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) studies which estimated seroprevalence, or the proportion of the population with antibodies to the virus, using differing convenience sample populations. One study tested blood donor specimens; the other study tested specimens left over from clinical blood tests. The seroprevalence of anti-nucleocapsid and anti-spike antibodies was compared in the same states during the same months with statistical adjustments based on state demographics. Similar anti-nucleocapsid antibody seroprevalence estimates produced by two independent studies using differing convenience samples build confidence in the generalizability of their anti-nucleocapsid findings. Due to high blood donor vaccine rates, blood donor SARS-CoV-2 anti-spike antibody estimates might overestimate general population seroprevalence, an important consideration for interpreting national seroprevalence study results. Furthermore, because laboratory residuals and blood donations are two common sources of specimens for seroprevalence studies, study findings may be informative for other respiratory virus seroepidemiology studies.

PURPOSE: To facilitate use of timely, granular, and publicly available data on COVID-19 mortality, we provide a method for imputing suppressed COVID-19 death counts in the National Center for Health Statistic's 2020 provisional mortality data by quarter, county, and age. METHODS: We used a Bayesian approach to impute suppressed COVID-19 death counts by quarter, county, and age in provisional data for 3,138 US counties. Our model accounts for multilevel data structures; numerous zero death counts among persons aged <50 years, rural counties, early quarters in 2020; highly right-skewed distributions; and different levels of data granularity (county, state or locality, and national levels). We compared three models with different prior assumptions of suppressed COVID-19 deaths, including noninformative priors (M1), the same weakly informative priors for all age groups (M2), and weakly informative priors that differ by age (M3) to impute the suppressed death counts. After the imputed suppressed counts were available, we assessed three prior assumptions at the national, state/locality, and county level, respectively. Finally, we compared US counties by two types of COVID-19 death rates, crude (CDR) and age-standardized death rates (ASDR), which can be estimated only through imputing suppressed death counts. RESULTS: Without imputation, the total COVID-19 death counts estimated from the raw data underestimated the reported national COVID-19 deaths by 18.60%. Using imputed data, we overestimated the national COVID-19 deaths by 3.57% (95% CI: 3.37%-3.80%) in model M1, 2.23% (95% CI: 2.04%-2.43%) in model M2, and 2.96% (95% CI: 2.76%-3.16%) in model M3 compared with the national report. The top 20 counties that were most affected by COVID-19 mortality were different between CDR and ASDR. CONCLUSIONS: Bayesian imputation of suppressed county-level, age-specific COVID-19 deaths in US provisional data can improve county ASDR estimates and aid public health officials in identifying disparities in deaths from COVID-19.

PURPOSE: We report the prevalence and economic cost of skin cancer treatment compared to other cancers overall in the USA from 2012 to 2018. METHODS: Using the Medical Expenditure Panel Survey full-year consolidated data files and associated medical conditions and medical events files, we estimate the prevalence, total costs, and per-person costs of treatment for melanoma and non-melanoma skin cancer among adults aged ≥ 18 years in the USA. To understand the changes in treatment prevalence and treatment costs of skin cancer in the context of overall cancer treatment, we also estimate the prevalence, total costs, and per-person costs of treatment for non-skin cancer among US adults. RESULTS: During 2012-15 and 2016-18, the average annual number of adults treated for any skin cancer was 5.8 (95% CI: 5.2, 6.4) and 6.1 (95% CI: 5.6, 6.6) million, respectively, while the average annual number of adults treated for non-skin cancers rose from 10.8 (95% CI: 10.0, 11.5) to 11.9 (95% CI: 11.2, 12.6) million, respectively. The overall estimated annual costs rose from $8.0 (in 2012-2015) to $8.9 billion (in 2016-18) for skin cancer treatment and $70.2 to $79.4 billion respectively for non-skin cancer treatment. CONCLUSION: The prevalence and economic cost of skin cancer treatment modestly increased in recent years. Given the substantial cost of skin cancer treatment, continued public health attention to implementing evidence-based sun-safety interventions to reduce skin cancer risk may help prevent skin cancer and the associated treatment costs.

OBJECTIVE: State-issued behavioral policy interventions (BPIs) can limit community spread of COVID-19, but their effects on COVID-19 transmission may vary by level of social vulnerability in the community. We examined the association between the duration of BPIs and the incidence of COVID-19 across levels of social vulnerability in US counties. METHODS: We used COVID-19 case counts from USAFacts and policy data on BPIs (face mask mandates, stay-at-home orders, gathering bans) in place from April through December 2020 and the 2018 Social Vulnerability Index (SVI) from the Centers for Disease Control and Prevention. We conducted multilevel linear regression to estimate the associations between duration of each BPI and monthly incidence of COVID-19 (cases per 100000 population) by SVI quartiles (grouped as low, moderate low, moderate high, and high social vulnerability) for 3141 US counties. RESULTS: Having a BPI in place for longer durations (ie, 2 months) was associated with lower incidence of COVID-19 compared with having a BPI in place for <1 month. Compared with having no BPI in place or a BPI in place for <1 month, differences in marginal mean monthly incidence of COVID-19 per 100000 population for a BPI in place for 2 months ranged from -4 cases in counties with low SVI to -401 cases in counties with high SVI for face mask mandates, from -31 cases in counties with low SVI to -208 cases in counties with high SVI for stay-at-home orders, and from -227 cases in counties with low SVI to -628 cases in counties with high SVI for gathering bans. CONCLUSIONS: Establishing COVID-19 prevention measures for longer durations may help reduce COVID-19 transmission, especially in communities with high levels of social vulnerability.