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Objectives. To determine whether geographic prioritization of limited COVID-19 vaccine supply was effective for reducing geographic disparities in case rates. Methods. Rhode Island allocated a portion of the initial COVID-19 vaccine supply to residents of Central Falls, a community already affected by structural policies and inadequate systems that perpetuate health inequities and experiencing disproportionately high COVID-19 morbidity and mortality. The policy was implemented with a culturally and linguistically appropriate community engagement plan and was intended to reduce observed disparities. Using a Bayesian causal analysis with population surveillance data, we evaluated the impact of this prioritization policy on recorded cases over the subsequent 16 weeks. Results. Early geographic prioritization of Central Falls accelerated vaccine uptake, averting an estimated 520 cases (95% confidence interval = 22, 1418) over 16 weeks and reducing cases by approximately 34% during this period (520 averted vs 1519 expected without early prioritization). Conclusions. Early geographic prioritization increased vaccine uptake and reduced cases in Central Falls, thereby reducing geographic disparities. Public Health Implications. Public health institutions should consider geographic prioritization of limited vaccine supply to reduce geographic disparities in case rates. (Am J Public Health. 2024;114(S7):S580–S589. https://doi.org/10.2105/AJPH.2024.307741) [ABSTRACT FROM AUTHOR]

Background In 2019, about 58 million individuals were chronically infected with hepatitis C virus. Some experts have proposed challenge trials for hepatitis C virus vaccine development. Methods We modeled incremental infections averted through a challenge approach, under varying assumptions regarding trial duration, number of candidates, and vaccine uptake. We computed the benefit-risk ratio of incremental benefits to risks for challenge versus traditional approaches. We also benchmarked against monetary costs of achieving incremental benefits through treatment. Results Our base case assumes 3 vaccine candidates, each with an 11% chance of success, corresponding to a 30% probability of successfully developing a vaccine. Given this probability, and assuming a 5-year difference in duration between challenge and traditional trials, a challenge approach would avert an expected 185 000 incremental infections with 20% steady-state uptake compared to a traditional approach and 832 000 with 90% uptake (quality-adjusted life-year benefit-risk ratio, 72 000 & 323 000). It would cost at least $92 million and $416 million, respectively, to obtain equivalent benefits through treatment. BRRs vary considerably across scenarios, depending on input assumptions. Conclusions Benefits of a challenge approach increase with more vaccine candidates, faster challenge trials, and greater uptake. [ABSTRACT FROM AUTHOR]

Throughout the COVID-19 pandemic, policymakers have proposed risk metrics, such as theCDCCommunity Levels, to guide local and state decision-making. However, risk metrics have not reliably predicted key outcomes and have often lacked transparency in terms of prioritization of false-positive versus false-negative signals. They have also struggled to maintain relevance over time due to slow and infrequent updates addressing new variants and shifts in vaccine- and infection-induced immunity. We make two contributions to address these weaknesses. We first present a framework to evaluate predictive accuracy based on policy targets related to severe disease and mortality, allowing for explicit preferences toward false-negative versus false-positive signals. This approach allows policymakers to optimize metrics for specific preferences and interventions. Second, we propose a method to update risk thresholds in real time. We show that this adaptive approach to designating areas as "high risk" improves performance over static metrics in predicting 3-wk-ahead mortality and intensive care usage at both state and county levels. We also demonstrate that with our approach, using only new hospital admissions to predict 3-wk-ahead mortality and intensive care usage has performed consistently as well as metrics that also include cases and inpatient bed usage. Our results highlight that a key challenge for COVID-19 risk prediction is the changing relationship between indicators and outcomes of policy interest. Adaptive metrics therefore have a unique advantage in a rapidly evolving pandemic context. [ABSTRACT FROM AUTHOR]

Background In 2019, about 58 million individuals were chronically infected with hepatitis C virus. Some experts have proposed challenge trials for hepatitis C virus vaccine development. Methods We modeled incremental infections averted through a challenge approach, under varying assumptions regarding trial duration, number of candidates, and vaccine uptake. We computed the benefit-risk ratio of incremental benefits to risks for challenge versus traditional approaches. We also benchmarked against monetary costs of achieving incremental benefits through treatment. Results Our base case assumes 3 vaccine candidates, each with an 11% chance of success, corresponding to a 30% probability of successfully developing a vaccine. Given this probability, and assuming a 5-year difference in duration between challenge and traditional trials, a challenge approach would avert an expected 185 000 incremental infections with 20% steady-state uptake compared to a traditional approach and 832 000 with 90% uptake (quality-adjusted life-year benefit-risk ratio, 72 000 & 323 000). It would cost at least $92 million and $416 million, respectively, to obtain equivalent benefits through treatment. BRRs vary considerably across scenarios, depending on input assumptions. Conclusions Benefits of a challenge approach increase with more vaccine candidates, faster challenge trials, and greater uptake. [ABSTRACT FROM AUTHOR]

Background: Centers for Disease Control and Prevention (CDC) defines low, medium, and high "COVID-19 community levels" to guide interventions, but associated mortality rates have not been reported.Objective: To evaluate the diagnostic performance of CDC COVID-19 community level metrics as predictors of elevated community mortality risk.Design: Time series analysis over the period of 30 May 2021 through 4 June 2022.Setting: U.S. states and counties.Participants: U.S. population.Measurements: CDC "COVID-19 community level" metrics based on hospital admissions, bed occupancy, and reported cases; reported COVID-19 deaths; and sensitivity, specificity, and predictive values for CDC and alternative metrics.Results: Mean and median weekly mortality rates per 100 000 population after onset of high COVID-19 community level 3 weeks prior were, respectively, 2.6 and 2.4 (interquartile range [IQR], 1.7 to 3.1) across 90 high episodes in states and 4.3 and 2.1 (IQR, 0 to 5.4) across 7987 high episodes in counties. In 85 of 90 (94%) episodes in states and 4801 of 7987 (60%) episodes in counties, lagged weekly mortality after onset exceeded 0.9 per 100 000 population, and in 57 of 90 (63%) episodes in states and 4018 of 7987 (50%) episodes in counties, lagged weekly mortality after onset exceeded 2.1 per 100 000, which is equivalent to approximately 1000 daily deaths in the national population. Alternative metrics based on lower hospital admissions or case thresholds were associated with lower mortality and had higher sensitivity and negative predictive value for elevated mortality, but the CDC metrics had higher specificity and positive predictive value. Ratios between cases, hospitalizations, and deaths have varied substantially over time.Limitations: Aggregate mortality does not account for nonfatal outcomes or disparities. Continuing evolution of viral variants, immunity, clinical interventions, and public health mitigation strategies complicate prediction for future waves.Conclusion: Designing metrics for public health decision making involves tradeoffs between identifying early signals for action and avoiding undue restrictions when risks are modest. Explicit frameworks for evaluating surveillance metrics can improve transparency and decision support.Primary Funding Source: Council of State and Territorial Epidemiologists. [ABSTRACT FROM AUTHOR]

This study compares the COVID-19 per capita overall and excess mortality rates in the US vs rates for 20 Organization for Economic Co-operation and Development countries and the timing of any increases in excess mortality between June 2021 and December 2021 (Delta) and December 2021 to March 2022 (Omicron). [ABSTRACT FROM AUTHOR]

The US COVID-19 Trends and Impact Survey (CTIS) is a large, cross-sectional, internet-based survey that has operated continuously since April 6, 2020. By inviting a random sample of Facebook active users each day, CTIS collects information about COVID-19 symptoms, risks, mitigating behaviors, mental health, testing, vaccination, and other key priorities. The large scale of the survey--over 20 million responses in its first year of operation--allows tracking of trends over short timescales and allows comparisons at fine demographic and geographic detail. The survey has been repeatedly revised to respond to emerging public health priorities. In this paper, we describe the survey methods and content and give examples of CTIS results that illuminate key patterns and trends and help answer high-priority policy questions relevant to the COVID-19 epidemic and response. These results demonstrate how large online surveys can provide continuous, real-time indicators of important outcomes that are not subject to public health reporting delays and backlogs. The CTIS offers high value as a supplement to official reporting data by supplying essential information about behaviors, attitudes toward policy and preventive measures, economic impacts, and other topics not reported in public health surveillance systems. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic has induced historic educational disruptions. In April 2021, about 40% of U.S. public school students were not offered full-time in-person education.Objective: To assess the risk for SARS-CoV-2 transmission in schools.Design: An agent-based network model was developed to simulate transmission in elementary and high school communities, including home, school, and interhousehold interactions.Setting: School structure was parametrized to reflect average U.S. classrooms, with elementary schools of 638 students and high schools of 1451 students. Daily local incidence was varied from 1 to 100 cases per 100 000 persons.Participants: Students, faculty, staff, and adult household members.Intervention: Isolation of symptomatic individuals, quarantine of an infected individual's contacts, reduced class sizes, alternative schedules, staff vaccination, and weekly asymptomatic screening.Measurements: Transmission was projected among students, staff, and families after a single infection in school and over an 8-week quarter, contingent on local incidence.Results: School transmission varies according to student age and local incidence and is substantially reduced with mitigation measures. Nevertheless, when transmission occurs, it may be difficult to detect without regular testing because of the subclinical nature of most children's infections. Teacher vaccination can reduce transmission to staff, and asymptomatic screening improves understanding of local circumstances and reduces transmission.Limitation: Uncertainty exists about the susceptibility and infectiousness of children, and precision is low regarding the effectiveness of specific countermeasures, particularly with new variants.Conclusion: With controlled community transmission and moderate mitigation, elementary schools can open safety, but high schools require more intensive mitigation. Asymptomatic screening can facilitate reopening at higher local incidence while minimizing transmission risk.Primary Funding Source: Centers for Disease Control and Prevention through the Council of State and Territorial Epidemiologists, National Institute of Allergy and Infectious Diseases, National Institute on Drug Abuse, and Facebook. [ABSTRACT FROM AUTHOR]

During the summer surge, peak worry about COVID-19 illness coincided with the peak of detected cases per capita, and mitigating risk behaviors similarly rose and fell with case rates (Fig. DISCUSSION Our analysis of a large national survey indicates strong correspondence between rising COVID-19 case reports and increases in individual risk perceptions and mitigating behaviors. Specifically, we assessed state-level patterns and trends in risk perceptions and risk-mitigating behaviors in relation to reported COVID-19 case rates. [Extracted from the article]

This Viewpoint compares the COVID-19 per capita overall and excess mortality rates in the US vs that of 18 OECD countries and the timing of any increases in excess mortality between February and September 2020. [ABSTRACT FROM AUTHOR]

HIV/AIDS remains the second most common cause of death in low and middle-income countries (LMICs), and only 34% of eligible patients in Africa received antiretroviral therapy (ART) in 2013. This study investigated the impact of ART decentralization on patient enrollment and retention in rural Malawi. We reviewed electronic medical records of patients registered in the Neno District ART program from August 1, 2006, when ART first became available, through December 31, 2013. We used GPS data to calculate patient-level distance to care, and examined number of annual ART visits and one-year lost to follow-up (LTFU) in HIV care. The number of ART patients in Neno increased from 48 to 3,949 over the decentralization period. Mean travel distance decreased from 7.3 km when ART was only available at the district hospital to 4.7 km when ART was decentralized to 12 primary health facilities. For patients who transferred from centralized care to nearer health facilities, mean travel distance decreased from 9.5 km to 4.7 km. Following a transfer, the proportion of patients achieving the clinic’s recommended ≥4 annual visits increased from 89% to 99%. In Cox proportional hazards regression, patients living ≥8 km from a health facility had a greater hazard of being LTFU compared to patients <8 km from a facility (adjusted HR: 1.7; 95% CI: 1.5–1.9). ART decentralization in Neno District was associated with increased ART enrollment, decreased travel distance, and increased retention in care. Increasing access to ART by reducing travel distance is one strategy to achieve the ART coverage and viral suppression objectives of the 90-90-90 UNAIDS targets in rural impoverished areas. [ABSTRACT FROM AUTHOR]

An essay discussing affordability of cost effective interventions in global health programs is presented. Topics discussed include Sustainable Development Goals for government to establish accessibility to quality healthcare; requirements for essential service packages; and budget impact analysis (BIA).

Over 20,000 rabies deaths occur annually in India, representing one-third of global human rabies. The Indian state of Tamil Nadu has pioneered a "One Health" committee to address the challenge of rabies in dogs and humans. Currently, rabies control in Tamil Nadu involves postexposure vaccination of humans after dog bites, whereas potential supplemental approaches include canine vaccination and sterilization. We developed a data-driven rabies transmission model fit to human rabies autopsy data and human rabies surveillance data from Tamil Nadu. Integrating local estimates for canine demography and costs, we predicted the impact of canine vaccination and sterilization on human health outcomes and evaluated cost-effectiveness according to the WHO criteria for India, which correspond to thresholds of $1,582 and $4,746 per disability-adjusted life-years (DALYs) for very cost-effective and cost-effective strategies, respectively. We found that highly feasible strategies focused on stray dogs, vaccinating as few as 7% of dogs annually, could very cost-effectively reduce human rabies deaths by 70% within 5 y, and a modest expansion to vaccinating 13% of stray dogs could cost-effectively reduce human rabies by almost 90%. Through integration over parameter uncertainty, we find that, for a cost-effectiveness threshold above $1,400 per DALY, canine interventions are at least 95% likely to be optimal. If owners are willing to bring dogs to central point campaigns at double the rate that campaign teams can capture strays, expanded annual targets become cost-effective. This case study of cost-effective canine interventions in Tamil Nadu may have applicability to other settings in India and beyond. [ABSTRACT FROM AUTHOR]

Rabies causes more than 24 000 human deaths annually in Sub-Saharan Africa. The World Health Organization recommends annual canine vaccination campaigns with at least 70% coverage to control the disease. While previous studies have considered optimal coverage of animal rabies vaccination, variation in the frequency of vaccination campaigns has not been explored. To evaluate the cost-effectiveness of rabies canine vaccination campaigns at varying coverage and frequency, we parametrized a rabies virus transmission model to two districts of northwest Tanzania, Ngorongoro (pastoral) and Serengeti (agro-pastoral). We found that optimal vaccination strategies were every 2 years, at 80% coverage in Ngorongoro and annually at 70% coverage in Serengeti. We further found that the optimality of these strategies was sensitive to the rate of rabies reintroduction from outside the district. Specifically, if a geographically coordinated campaign could reduce reintroduction, vaccination campaigns every 2 years could effectively manage rabies in both districts. Thus, coordinated campaigns may provide monetary savings in addition to public health benefits. Our results indicate that frequency and coverage of canine vaccination campaigns should be evaluated simultaneously and tailored to local canine ecology as well as to the risk of disease reintroduction from surrounding regions. [ABSTRACT FROM AUTHOR]

Objectives. We examined associations of geographic measures of poverty, race, ethnicity, and city status with rates of cervical intraepithelial neoplasia grade 2 or higher and adenocarcinoma in situ (CIN2+/AIS), known precursors to cervical cancer. Methods. We identified 3937 cases of CIN2+/AIS among women aged 20 to 39 years in statewide surveillance data from Connecticut for 2008 to 2009. We geocoded cases to census tracts and used census data to calculate overall and age-specific rates. Poisson regression determined whether rates differed by geographic measures. Results. The average annual rate of CIN2+/AIS was 417.6 per 100 000 women. Overall, higher rates of CIN2+/AIS were associated with higher levels of poverty and higher proportions of Black residents. Poverty was the strongest and most consistently associated measure. However, among women aged 20 to 24 years, we observed inverse associations between poverty and CIN2+/AIS rates. Conclusions. Disparities in cervical cancer precursors exist for poverty and race, but these effects are age dependent. This information is necessary to monitor human papillomavirus vaccine impact and target vaccination strategies. [ABSTRACT FROM AUTHOR]