Severe Acute Respiratory Syndrome Coronavirus 2 Neutralizing Antibody Responses After Community Infections in Children and Adults.

Background: We compared postinfection severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) neutralizing antibody (nAb) responses among children and adults while the D614G-like strain and Alpha, Iota, and Delta variants circulated. Methods: During August 2020-October 2021, households with adults and children were enrolled and followed in Utah, New York City, and Maryland. Participants collected weekly respiratory swabs that were tested for SARS-CoV-2 and had sera collected during enrollment and follow-up. Sera were tested for SARS-CoV-2 nAb by pseudovirus assay. Postinfection titers were characterized with biexponential decay models. Results: Eighty participants had SARS-CoV-2 infection during the study (47 with D614G-like virus, 17 with B.1.1.7, and 8 each with B.1.617.2 and B.1.526 virus). Homologous nAb geometric mean titers (GMTs) trended higher in adults (GMT = 2320) versus children 0-4 (GMT = 425, P = .33) and 5-17 years (GMT = 396, P = .31) at 1-5 weeks postinfection but were similar from 6 weeks. Timing of peak titers was similar by age. Results were consistent when participants with self-reported infection before enrollment were included (n = 178). Conclusions: The SARS-CoV-2 nAb titers differed in children compared to adults early after infection but were similar by 6 weeks postinfection. If postvaccination nAb kinetics have similar trends, vaccine immunobridging studies may need to compare nAb responses in adults and children 6 weeks or more after vaccination.

Epidemiology and risk factors related to severity of clinical manifestations of COVID-19 in outpatients: A retrospective study in Haiti.

BACKGROUND: Haiti's first COVID-19 cases were confirmed on March 18, 2020, and subsequently spread throughout the country. The objective of this study was to describe clinical manifestations of COVID-19 in Haitian outpatients and to identify risk factors for severity of clinical manifestations. METHODS: We conducted a retrospective study of COVID-19 outpatients diagnosed from March 18-August 4, 2020, using demographic, epidemiological, and clinical data reported to the Ministry of Health (MoH). We used univariate and multivariate analysis, including multivariable logistic regression, to explore the risk factors and specific symptoms related to persons with symptomatic COVID-19 and the severity of symptomatic COVID-19 disease. RESULTS: Of 5,389 cases reported to MOH during the study period, 1,754 (32.5%) were asymptomatic. Amongst symptomatic persons 2,747 (75.6%) had mild COVID-19 and 888 (24.4%) had moderate-to-severe disease; the most common symptoms were fever (69.6%), cough (51.9%), and myalgia (45.8%). The odds of having moderate-to-severe disease were highest among persons with hypertension (aOR = 1.72, 95% Confidence Interval [CI] (1.34, 2.20), chronic pulmonary disease (aOR = 3.93, 95% CI (1.93, 8.17)) and tuberculosis (aOR = 3.44, 95% CI (1.35, 9.14)) compared to persons without those conditions. The odds of having moderate-to-severe disease increased with age but was also seen among children aged 0-4 years (OR: 1.73, 95% CI (0.93, 3.08)), when using 30-39 years old as the reference group. All of the older age groups, 50-64 years, 65-74 years, 75-84 years, and 85+ years, had significantly higher odds of having moderate-to-severe COVID-19 compared with ages 30-39 years. Diabetes was associated with elevated odds of moderate-to-severe disease in bivariate analysis (OR = 2.17, 95% CI (1.58,2.98) but, this association did not hold in multivariable analyses (aOR = 1.22,95%CI (0.86,1.72)). CONCLUSION: These findings from a resource-constrained country highlight the importance of surveillance systems to track emerging infections and their risk factors. In addition to co-morbidities described elsewhere, tuberculosis was a risk factor for moderate-to-severe COVID-19 disease.

Estimated Number of COVID-19 Infections, Hospitalizations, and Deaths Prevented Among Vaccinated Persons in the US, December 2020 to September 2021.

Importance: The number of SARS-CoV-2 infections and COVID-19-associated hospitalizations and deaths prevented among vaccinated persons, independent of the effect of reduced transmission, is a key measure of vaccine impact. Objective: To estimate the number of SARS-CoV-2 infections and COVID-19-associated hospitalizations and deaths prevented among vaccinated adults in the US. Design, Setting, and Participants: In this modeling study, a multiplier model was used to extrapolate the number of SARS-CoV-2 infections and COVID-19-associated deaths from data on the number of COVID-19-associated hospitalizations stratified by state, month, and age group (18-49, 50-64, and ≥65 years) in the US from December 1, 2020, to September 30, 2021. These estimates were combined with data on vaccine coverage and effectiveness to estimate the risks of infections, hospitalizations, and deaths. Risks were applied to the US population 18 years or older to estimate the expected burden in that population without vaccination. The estimated burden in the US population 18 years or older given observed levels of vaccination was subtracted from the expected burden in the US population 18 years or older without vaccination (ie, counterfactual) to estimate the impact of vaccination among vaccinated persons. Exposures: Completion of the COVID-19 vaccination course, defined as 2 doses of messenger RNA (BNT162b2 or mRNA-1273) vaccines or 1 dose of JNJ-78436735 vaccine. Main Outcomes and Measures: Monthly numbers and percentages of SARS-CoV-2 infections and COVID-19-associated hospitalizations and deaths prevented were estimated among those who have been vaccinated in the US. Results: COVID-19 vaccination was estimated to prevent approximately 27 million (95% uncertainty interval [UI], 22 million to 34 million) infections, 1.6 million (95% UI, 1.4 million to 1.8 million) hospitalizations, and 235 000 (95% UI, 175 000-305 000) deaths in the US from December 1, 2020, to September 30, 2021, among vaccinated adults 18 years or older. From September 1 to September 30, 2021, vaccination was estimated to prevent 52% (95% UI, 45%-62%) of expected infections, 56% (95% UI, 52%-62%) of expected hospitalizations, and 58% (95% UI, 53%-63%) of expected deaths in adults 18 years or older. Conclusions and Relevance: These findings indicate that the US COVID-19 vaccination program prevented a substantial burden of morbidity and mortality through direct protection of vaccinated individuals.

Estimating COVID-19 Hospitalizations in the United States With Surveillance Data Using a Bayesian Hierarchical Model: Modeling Study.

BACKGROUND: In the United States, COVID-19 is a nationally notifiable disease, meaning cases and hospitalizations are reported by states to the Centers for Disease Control and Prevention (CDC). Identifying and reporting every case from every facility in the United States may not be feasible in the long term. Creating sustainable methods for estimating the burden of COVID-19 from established sentinel surveillance systems is becoming more important. OBJECTIVE: We aimed to provide a method leveraging surveillance data to create a long-term solution to estimate monthly rates of hospitalizations for COVID-19. METHODS: We estimated monthly hospitalization rates for COVID-19 from May 2020 through April 2021 for the 50 states using surveillance data from the COVID-19-Associated Hospitalization Surveillance Network (COVID-NET) and a Bayesian hierarchical model for extrapolation. Hospitalization rates were calculated from patients hospitalized with a lab-confirmed SARS-CoV-2 test during or within 14 days before admission. We created a model for 6 age groups (0-17, 18-49, 50-64, 65-74, 75-84, and ≥85 years) separately. We identified covariates from multiple data sources that varied by age, state, and month and performed covariate selection for each age group based on 2 methods, Least Absolute Shrinkage and Selection Operator (LASSO) and spike and slab selection methods. We validated our method by checking the sensitivity of model estimates to covariate selection and model extrapolation as well as comparing our results to external data. RESULTS: We estimated 3,583,100 (90% credible interval [CrI] 3,250,500-3,945,400) hospitalizations for a cumulative incidence of 1093.9 (992.4-1204.6) hospitalizations per 100,000 population with COVID-19 in the United States from May 2020 through April 2021. Cumulative incidence varied from 359 to 1856 per 100,000 between states. The age group with the highest cumulative incidence was those aged ≥85 years (5575.6; 90% CrI 5066.4-6133.7). The monthly hospitalization rate was highest in December (183.7; 90% CrI 154.3-217.4). Our monthly estimates by state showed variations in magnitudes of peak rates, number of peaks, and timing of peaks between states. CONCLUSIONS: Our novel approach to estimate hospitalizations for COVID-19 has potential to provide sustainable estimates for monitoring COVID-19 burden as well as a flexible framework leveraging surveillance data.

Severe Acute Respiratory Syndrome Coronavirus 2 Seroprevalence and Reported Coronavirus Disease 2019 Cases in US Children, August 2020-May 2021.

BACKGROUND: Case-based surveillance of pediatric coronavirus disease 2019 (COVID-19) cases underestimates the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections among children and adolescents. Our objectives were to estimate monthly SARS-CoV-2 antibody seroprevalence and calculate ratios of SARS-CoV-2 infections to reported COVID-19 cases among children and adolescents in 8 US states. METHODS: Using data from the Nationwide Commercial Laboratory Seroprevalence Survey, we estimated monthly SARS-CoV-2 antibody seroprevalence among children aged 0-17 years from August 2020 through May 2021. We calculated and compared cumulative incidence of SARS-CoV-2 infection extrapolated from population-standardized seroprevalence of antibodies to SARS-CoV-2, cumulative COVID-19 case reports since March 2020, and infection-to-case ratios among persons of all ages and children aged 0-17 years for each state. RESULTS: Of 41 583 residual serum specimens tested, children aged 0-4, 5-11, and 12-17 years accounted for 1619 (3.9%), 10 507 (25.3%), and 29 457 (70.8%), respectively. Median SARS-CoV-2 antibody seroprevalence among children increased from 8% (range, 6%-20%) in August 2020 to 37% (range, 26%-44%) in May 2021. Estimated ratios of SARS-CoV-2 infections to reported COVID-19 cases in May 2021 ranged by state from 4.7-8.9 among children and adolescents to 2.2-3.9 for all ages combined. CONCLUSIONS: Through May 2021 in selected states, the majority of children with serum specimens included in serosurveys did not have evidence of prior SARS-CoV-2 infection. Case-based surveillance underestimated the number of children infected with SARS-CoV-2 more than among all ages. Continued monitoring of pediatric SARS-CoV-2 antibody seroprevalence should inform prevention and vaccination strategies.

Severe Acute Respiratory Syndrome Coronavirus 2 Seroprevalence and Reported Coronavirus Disease 2019 Cases in US Children, August 2020–May 2021

Background Case-based surveillance of pediatric coronavirus disease 2019 (COVID-19) cases underestimates the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections among children and adolescents. Our objectives were to estimate monthly SARS-CoV-2 antibody seroprevalence and calculate ratios of SARS-CoV-2 infections to reported COVID-19 cases among children and adolescents in 8 US states. Methods Using data from the Nationwide Commercial Laboratory Seroprevalence Survey, we estimated monthly SARS-CoV-2 antibody seroprevalence among children aged 0–17 years from August 2020 through May 2021. We calculated and compared cumulative incidence of SARS-CoV-2 infection extrapolated from population-standardized seroprevalence of antibodies to SARS-CoV-2, cumulative COVID-19 case reports since March 2020, and infection-to-case ratios among persons of all ages and children aged 0–17 years for each state. Results Of 41 583 residual serum specimens tested, children aged 0–4, 5–11, and 12–17 years accounted for 1619 (3.9%), 10 507 (25.3%), and 29 457 (70.8%), respectively. Median SARS-CoV-2 antibody seroprevalence among children increased from 8% (range, 6%–20%) in August 2020 to 37% (range, 26%–44%) in May 2021. Estimated ratios of SARS-CoV-2 infections to reported COVID-19 cases in May 2021 ranged by state from 4.7–8.9 among children and adolescents to 2.2–3.9 for all ages combined. Conclusions Through May 2021 in selected states, the majority of children with serum specimens included in serosurveys did not have evidence of prior SARS-CoV-2 infection. Case-based surveillance underestimated the number of children infected with SARS-CoV-2 more than among all ages. Continued monitoring of pediatric SARS-CoV-2 antibody seroprevalence should inform prevention and vaccination strategies. We estimated monthly pediatric SARS-CoV-2 infections from antibody seroprevalence compared to reported COVID-19 cases among children in 8 US states. As of May 2021, estimated numbers of children infected were 5 times higher than reported pediatric COVID-19 cases in included states.

Coronavirus Disease Case Definitions, Diagnostic Testing Criteria, and Surveillance in 25 Countries with Highest Reported Case Counts.

We compared case definitions for suspected, probable, and confirmed coronavirus disease (COVID-19), as well as diagnostic testing criteria, used in the 25 countries with the highest reported case counts as of October 1, 2020. Of the identified countries, 56% followed World Health Organization (WHO) recommendations for using a combination of clinical and epidemiologic criteria as part of the suspected case definition. A total of 75% of identified countries followed WHO recommendations on using clinical, epidemiologic, and diagnostic criteria for probable cases; 72% followed WHO recommendations to use PCR testing to confirm COVID-19. Finally, 64% of countries used testing eligibility criteria at least as permissive as WHO. We observed marked heterogeneity in testing eligibility requirements and in how countries define a COVID-19 case. This heterogeneity affects the ability to compare case counts, transmission, and vaccine effectiveness, as well as estimates derived from case surveillance data across countries.

Global Health Security Preparedness and Response: An Analysis of the Relationship between Joint External Evaluation Scores and COVID-19 Response Performance.

OBJECTIVES: The COVID-19 pandemic has highlighted the importance and complexity of a country's ability to effectively respond. The Joint External Evaluation (JEE) assessment was launched in 2016 to assess a country's ability to prevent, detect and respond to public health emergencies. We examined whether JEE indicators could be used to predict a country's COVID-19 response performance to tailor a country's support more effectively. DESIGN: From April to August 2020, we conducted interviews with Centers for Disease Control and Prevention country offices that requested COVID-19 support and previously completed the JEE (version 1.0). We used an assessment tool, the 'Emergency Response Capacity Tool' (ERCT), to assess COVID-19 response performance. We analysed 28 ERCT indicators aligned with eight JEE indicators to assess concordance and discordance using strict agreement and weighted kappa statistics. Generalised estimating equation (GEE) models were used to generate predicted probabilities for ERCT scores using JEE scores as the independent model variable. RESULTS: Twenty-three countries met inclusion criteria. Of the 163 indicators analysed, 42.3% of JEE and ERCT scores were in agreement (p value=0.02). The JEE indicator with the highest agreement (62%) was 'Emergency Operations Center (EOC) operating procedures and plans', while the lowest (16%) was 'capacity to activate emergency operations'. Findings were consistent with weighted kappa statistics. In the GEE model, EOC operating procedures and plans had the highest predicted probability (0.86), while indicators concerning response strategy and coordination had the lowest (≤0.5). CONCLUSIONS: Overall, there was low agreement between JEE scores and COVID-19 response performance, with JEE scores often trending higher. JEE indicators concerning coordination and operations were least predictive of COVID-19 response performance, underscoring the importance of not inferring country response readiness from JEE scores alone. More in-depth country-specific investigations are likely needed to accurately estimate response capacity and tailor countries' global health security activities.