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.

Rotavirus genotypes in the post-vaccine era: A systematic review and meta-analysis of global, regional, and temporal trends in settings with and without rotavirus vaccine introduction.

BACKGROUND: Even moderate differences in rotavirus vaccine effectiveness against non-vaccine genotypes may exert selective pressures on circulating rotaviruses. Whether this vaccine effect or natural temporal fluctuations underlie observed changes in genotype distributions is unclear. METHODS: We systematically reviewed studies reporting rotavirus genotypes from children <5 years of age globally between 2005 and 2023. We compared rotavirus genotypes between vaccine-introducing and non-introducing settings globally and by World Health Organization (WHO) region, calendar time, and time since vaccine introduction. RESULTS: Crude pooling of genotype data from 361 studies indicated higher G2P[4], a non-vaccine genotype, prevalence in vaccine-introducing settings, both globally and by WHO region. This difference did not emerge when examining genotypes over time in the Americas, the only region with robust longitudinal data. Relative to non-introducing settings, G2P[4] detections were more likely in settings with recent introduction (e.g. 1-2 years post-introduction aOR: 4.39 (95% CI: 2.87-6.72)) but were similarly likely in settings with more time elapsed since introduction, (e.g. 7 or more years aOR (1.62 95% CI: 0.49-5.37)). CONCLUSIONS: When accounting for both regional and temporal trends, there was no substantial evidence of long-term vaccine-related selective pressures on circulating genotypes. Increased prevalence of G2P[4] may be transient after rotavirus vaccine introduction.

Monovalent Rotavirus Vaccine Efficacy Against Different Rotavirus Genotypes: A Pooled Analysis of Phase II and III Trial Data.

BACKGROUND: Rotavirus vaccine performance appears worse in countries with high rotavirus genotype diversity. Evidence suggests diminished vaccine efficacy (VE) against G2P[4], which is heterotypic with existing monovalent rotavirus vaccine formulations. Most studies assessing genotype-specific VE have been underpowered and inconclusive. METHODS: We pooled individual-level data from 10 Phase II and III clinical trials of rotavirus vaccine containing G1 and P[8] antigens (RV1) conducted between 2000 and 2012. We estimated VE against both any-severity and severe (Vesikari score ≥11) rotavirus gastroenteritis (RVGE) using binomial and multinomial logistic regression models for non-specific VE against any RVGE, genotype-specific VE, and RV1-typic VE against genotypes homotypic, partially heterotypic, or fully heterotypic with RV1 antigens. We adjusted models for concomitant oral poliovirus and RV1 vaccination and the country's designated child mortality stratum. RESULTS: Analysis included 87 644 infants from 22 countries in the Americas, Europe, Africa, and Asia. For VE against severe RVGE, non-specific VE was 91% (95% confidence interval [CI]: 87-94%). Genotype-specific VE ranged from 96% (95% CI: 89-98%) against G1P[8] to 71% (43-85%) against G2P[4]. RV1-typic VE was 92% (95% CI: 84-96%) against partially heterotypic genotypes but 83% (67-91%) against fully heterotypic genotypes. For VE against any-severity RVGE, non-specific VE was 82% (95% CI: 75-87%). Genotype-specific VE ranged from 94% (95% CI: 86-97%) against G1P[8] to 63% (41-77%) against G2P[4]. RV1-typic VE was 83% (95% CI: 72-90%) against partially heterotypic genotypes but 63% (40-77%) against fully heterotypic genotypes. CONCLUSIONS: RV1 VE is comparatively diminished against fully heterotypic genotypes including G2P[4].

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.

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.

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.

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.

Understanding Variation in Rotavirus Vaccine Effectiveness Estimates in the United States: The Role of Rotavirus Activity and Diagnostic Misclassification.

BACKGROUND: Estimates of rotavirus vaccine effectiveness (VE) in the United States appear higher in years with more rotavirus activity. We hypothesized rotavirus VE is constant over time but appears to vary as a function of temporal variation in local rotavirus cases and/or misclassified diagnoses. METHODS: We analyzed 6 years of data from eight US surveillance sites on 8- to 59-month olds with acute gastroenteritis symptoms. Children's stool samples were tested via enzyme immunoassay (EIA); rotavirus-positive results were confirmed with molecular testing at the US Centers for Disease Control and Prevention. We defined rotavirus gastroenteritis cases by either positive on-site EIA results alone or positive EIA with Centers for Disease Control and Prevention confirmation. For each case definition, we estimated VE against any rotavirus gastroenteritis, moderate-to-severe disease, and hospitalization using two mixed-effect regression models: the first including year plus a year-vaccination interaction, and the second including the annual percent of rotavirus-positive tests plus a percent positive-vaccination interaction. We used multiple overimputation to bias-adjust for misclassification of cases defined by positive EIA alone. RESULTS: Estimates of annual rotavirus VE against all outcomes fluctuated temporally, particularly when we defined cases by on-site EIA alone and used a year-vaccination interaction. Use of confirmatory testing to define cases reduced, but did not eliminate, fluctuations. Temporal fluctuations in VE estimates further attenuated when we used a percent positive-vaccination interaction. Fluctuations persisted until bias-adjustment for diagnostic misclassification. CONCLUSIONS: Both controlling for time-varying rotavirus activity and bias-adjusting for diagnostic misclassification are critical for estimating the most valid annual rotavirus VE.

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.

Impact of Nonpharmaceutical Interventions for Severe Acute Respiratory Syndrome Coronavirus 2 on Norovirus Outbreaks: An Analysis of Outbreaks Reported By 9 US States.

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.

Risk for Fomite-Mediated Transmission of SARS-CoV-2 in Child Daycares, Schools, Nursing Homes, and Offices.

Severe acute respiratory syndrome coronavirus 2 can persist on surfaces, suggesting possible surface-mediated transmission of this pathogen. We found that fomites might be a substantial source of transmission risk, particularly in schools and child daycares. Combining surface cleaning and decontamination with mask wearing can help mitigate this risk.

Evaluation of Intussusception after Monovalent Rotavirus Vaccination in Africa.

BACKGROUND: Postlicensure evaluations have identified an association between rotavirus vaccination and intussusception in several high- and middle-income countries. We assessed the association between monovalent human rotavirus vaccine and intussusception in lower-income sub-Saharan African countries. METHODS: Using active surveillance, we enrolled patients from seven countries (Ethiopia, Ghana, Kenya, Malawi, Tanzania, Zambia, and Zimbabwe) who had intussusception that met international (Brighton Collaboration level 1) criteria. Rotavirus vaccination status was confirmed by review of the vaccine card or clinic records. The risk of intussusception within 1 to 7 days and 8 to 21 days after vaccination among infants 28 to 245 days of age was assessed by means of the self-controlled case-series method. RESULTS: Data on 717 infants who had intussusception and confirmed vaccination status were analyzed. One case occurred in the 1 to 7 days after dose 1, and 6 cases occurred in the 8 to 21 days after dose 1. Five cases and 16 cases occurred in the 1 to 7 days and 8 to 21 days, respectively, after dose 2. The risk of intussusception in the 1 to 7 days after dose 1 was not higher than the background risk of intussusception (relative incidence [i.e., the incidence during the risk window vs. all other times], 0.25; 95% confidence interval [CI], <0.001 to 1.16); findings were similar for the 1 to 7 days after dose 2 (relative incidence, 0.76; 95% CI, 0.16 to 1.87). In addition, the risk of intussusception in the 8 to 21 days or 1 to 21 days after either dose was not found to be higher than the background risk. CONCLUSIONS: The risk of intussusception after administration of monovalent human rotavirus vaccine was not higher than the background risk of intussusception in seven lower-income sub-Saharan African countries. (Funded by the GAVI Alliance through the CDC Foundation.).

Estimating the Cumulative Incidence of SARS-CoV-2 Infection and the Infection Fatality Ratio in Light of Waning Antibodies.

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.

Theoretical Framework for Retrospective Studies of the Effectiveness of SARS-CoV-2 Vaccines.

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.

Immunologic and Epidemiologic Drivers of Norovirus Transmission in Daycare and School Outbreaks.

BACKGROUND: Norovirus outbreaks are notoriously explosive, with dramatic symptomology and rapid disease spread. Children are particularly vulnerable to infection and drive norovirus transmission due to their high contact rates with each other and the environment. Despite the explosive nature of norovirus outbreaks, attack rates in schools and daycares remain low with the majority of students not reporting symptoms. METHODS: We explore immunologic and epidemiologic mechanisms that may underlie epidemic norovirus transmission dynamics using a disease transmission model. Towards this end, we compared different model scenarios, including innate resistance and acquired immunity (collectively denoted 'immunity'), stochastic extinction, and an individual exclusion intervention. We calibrated our model to daycare and school outbreaks from national surveillance data. RESULTS: Including immunity in the model led to attack rates that were consistent with the data. However, immunity alone resulted in the majority of outbreak durations being relatively short. The addition of individual exclusion (to the immunity model) extended outbreak durations by reducing the amount of time that symptomatic people contribute to transmission. Including both immunity and individual exclusion mechanisms resulted in simulations where both attack rates and outbreak durations were consistent with surveillance data. CONCLUSIONS: The epidemiology of norovirus outbreaks in daycare and school settings cannot be well described by a simple transmission model in which all individuals start as fully susceptible. More studies on how best to design interventions which leverage population immunity and encourage more rigorous individual exclusion may improve venue-level control measures. See video abstract at http://links.lww.com/EDE/B795.

Quantifying the roles of vomiting, diarrhea, and residents vs. staff in norovirus transmission in U.S. nursing home outbreaks.

The role of individual case characteristics, such as symptoms or demographics, in norovirus transmissibility is poorly understood. Six nursing home norovirus outbreaks occurring in South Carolina, U.S. from 2014 to 2016 were examined. We aimed to quantify the contribution of symptoms and other case characteristics in norovirus transmission using the reproduction number (REi) as an estimate of individual case infectivity and to examine how transmission changes over the course of an outbreak. Individual estimates of REi were calculated using a maximum likelihood procedure to infer the average number of secondary cases generated by each case. The associations between case characteristics and REi were estimated using a weighted multivariate mixed linear model. Outbreaks began with one to three index case(s) with large estimated REi's (range: 1.48 to 8.70) relative to subsequent cases. Of the 209 cases, 155 (75%) vomited, 164 (79%) had diarrhea, and 158 (76%) were nursing home residents (vs. staff). Cases who vomited infected 2.12 (95% CI: 1.68, 2.68) times the number of individuals as non-vomiters, cases with diarrhea infected 1.39 (95% CI: 1.03, 1.87) times the number of individuals as cases without diarrhea, and resident-cases infected 1.53 (95% CI: 1.15, 2.02) times the number of individuals as staff-cases. Index cases tended to be residents (vs. staff) who vomited and infected considerably more secondary cases compared to non-index cases. Results suggest that individuals, particularly residents, who vomit are more infectious and tend to drive norovirus transmission in U.S. nursing home norovirus outbreaks. While diarrhea also plays a role in norovirus transmission, it is to a lesser degree than vomiting in these settings. Results lend support for prevention and control measures that focus on cases who vomit, particularly if those cases are residents.

The DIOS framework for optimizing infectious disease surveillance: Numerical methods for simulation and multi-objective optimization of surveillance network architectures.

Infectious disease surveillance systems provide vital data for guiding disease prevention and control policies, yet the formalization of methods to optimize surveillance networks has largely been overlooked. Decisions surrounding surveillance design parameters-such as the number and placement of surveillance sites, target populations, and case definitions-are often determined by expert opinion or deference to operational considerations, without formal analysis of the influence of design parameters on surveillance objectives. Here we propose a simulation framework to guide evidence-based surveillance network design to better achieve specific surveillance goals with limited resources. We define evidence-based surveillance design as an optimization problem, acknowledging the many operational constraints under which surveillance systems operate, the many dimensions of surveillance system design, the multiple and competing goals of surveillance, and the complex and dynamic nature of disease systems. We describe an analytical framework-the Disease Surveillance Informatics Optimization and Simulation (DIOS) framework-for the identification of optimal surveillance designs through mathematical representations of disease and surveillance processes, definition of objective functions, and numerical optimization. We then apply the framework to the problem of selecting candidate sites to expand an existing surveillance network under alternative objectives of: (1) improving spatial prediction of disease prevalence at unmonitored sites; or (2) estimating the observed effect of a risk factor on disease. Results of this demonstration illustrate how optimal designs are sensitive to both surveillance goals and the underlying spatial pattern of the target disease. The findings affirm the value of designing surveillance systems through quantitative and adaptive analysis of network characteristics and performance. The framework can be applied to the design of surveillance systems tailored to setting-specific disease transmission dynamics and surveillance needs, and can yield improved understanding of tradeoffs between network architectures.

Postvaccination Serum Antirotavirus Immunoglobulin A as a Correlate of Protection Against Rotavirus Gastroenteritis Across Settings.

BACKGROUND: A correlate of protection for rotavirus gastroenteritis would facilitate rapid assessment of vaccination strategies and the next generation of rotavirus vaccines. We aimed to quantify a threshold of postvaccine serum antirotavirus immunoglobulin A (IgA) as an individual-level immune correlate of protection against rotavirus gastroenteritis. METHODS: Individual-level data on 5074 infants in 9 GlaxoSmithKline Rotarix Phase 2/3 clinical trials from 16 countries were pooled. Cox proportional hazard models were fit to estimate hazard ratios (HRs) describing the relationship between IgA thresholds and occurrence of rotavirus gastroenteritis. RESULTS: Seroconversion (IgA ≥ 20 U/mL) conferred substantial protection against any and severe rotavirus gastroenteritis to age 1 year. In low child mortality settings, seroconversion provided near perfect protection against severe rotavirus gastroenteritis (HR, 0.04; 95% confidence interval [CI], .01-.31). In high child mortality settings, seroconversion dramatically reduced the risk of severe rotavirus gastroenteritis (HR, 0.46; 95% CI, .25-.86). As IgA threshold increased, risk of rotavirus gastroenteritis generally decreased. A given IgA threshold provided better protection in low compared to high child mortality settings. DISCUSSION: Postvaccination antirotavirus IgA is a valuable correlate of protection against rotavirus gastroenteritis to age 1 year. Seroconversion provides an informative threshold for assessing rotavirus vaccine performance.

Social Mixing and Clinical Features Linked With Transmission in a Network of Extensively Drug-resistant Tuberculosis Cases in KwaZulu-Natal, South Africa.

BACKGROUND: Tuberculosis (TB) is the leading infectious cause of death globally, and drug-resistant TB strains pose a serious threat to controlling the global TB epidemic. The clinical features, locations, and social factors driving transmission in settings with high incidences of drug-resistant TB are poorly understood. METHODS: We measured a network of genomic links using Mycobacterium tuberculosis whole-genome sequences. RESULTS: Patients with 2-3 months of cough or who spent time in urban locations were more likely to be linked in the network, while patients with sputum smear-positive disease were less likely to be linked than those with smear-negative disease. Associations persisted using different thresholds to define genomic links and irrespective of assumptions about the direction of transmission. CONCLUSIONS: Identifying factors that lead to many transmissions, including contact with urban areas, can suggest settings instrumental in transmission and indicate optimal locations and groups to target with interventions.

Modeling Missing Cases and Transmission Links in Networks of Extensively Drug-Resistant Tuberculosis in KwaZulu-Natal, South Africa.

Patterns of transmission of drug-resistant tuberculosis (TB) remain poorly understood, despite over half a million incident cases worldwide in 2017. Modeling TB transmission networks can provide insight into drivers of transmission, but incomplete sampling of TB cases can pose challenges for inference from individual epidemiologic and molecular data. We assessed the effect of missing cases on a transmission network inferred from Mycobacterium tuberculosis sequencing data on extensively drug-resistant TB cases in KwaZulu-Natal, South Africa, diagnosed in 2011-2014. We tested scenarios in which cases were missing at random, missing differentially by clinical characteristics, or missing differentially by transmission (i.e., cases with many links were under- or oversampled). Under the assumption that cases were missing randomly, the mean number of transmissions per case in the complete network needed to be larger than 20, far higher than expected, to reproduce the observed network. Instead, the most likely scenario involved undersampling of high-transmitting cases, and models provided evidence for super-spreading. To our knowledge, this is the first analysis to have assessed support for different mechanisms of missingness in a TB transmission study, but our results are subject to the distributional assumptions of the network models we used. Transmission studies should consider the potential biases introduced by incomplete sampling and identify host, pathogen, or environmental factors driving super-spreading.