The detection of evolutionary transitions in influenza A (H3N2) viruses' antigenicity is a major obstacle to effective vaccine design and development. In this study, we describe Novel Influenza Virus A Detector (NIAViD), an unsupervised machine learning tool, adept at identifying these transitions, using the HA1 sequence and associated physico-chemical properties. NIAViD performed with 88.9% (95% CI, 56.5-98.0%) and 72.7% (95% CI, 43.4-90.3%) sensitivity in training and validation, respectively, outperforming the uncalibrated null model-33.3% (95% CI, 12.1-64.6%) and does not require potentially biased, time-consuming and costly laboratory assays. The pivotal role of the Boman's index, indicative of the virus's cell surface binding potential, is underscored, enhancing the precision of detecting antigenic transitions. NIAViD's efficacy is not only in identifying influenza isolates that belong to novel antigenic clusters, but also in pinpointing potential sites driving significant antigenic changes, without the reliance on explicit modelling of haemagglutinin inhibition titres. We believe this approach holds promise to augment existing surveillance networks, offering timely insights for the development of updated, effective influenza vaccines. Consequently, NIAViD, in conjunction with other resources, could be used to support surveillance efforts and inform the development of updated influenza vaccines.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has evolved into numerous lineages with unique spike mutations and caused multiple epidemics domestically and globally. Although COVID-19 vaccines are available, new variants with the capacity for immune evasion continue to emerge. To understand and characterize the evolution of circulating SARS-CoV-2 variants in the U.S., the Centers for Disease Control and Prevention (CDC) initiated the National SARS-CoV-2 Strain Surveillance (NS3) program and has received thousands of SARS-CoV-2 clinical specimens from across the nation as part of a genotype to phenotype characterization process. Focus reduction neutralization with various antisera was used to antigenically characterize 143 SARS-CoV-2 Delta, Mu and Omicron subvariants from selected clinical specimens received between May 2021 and February 2023, representing a total of 59 unique spike protein sequences. BA.4/5 subvariants BU.1, BQ.1.1, CR.1.1, CQ.2 and BA.4/5 + D420N + K444T; BA.2.75 subvariants BM.4.1.1, BA.2.75.2, CV.1; and recombinant Omicron variants XBF, XBB.1, XBB.1.5 showed the greatest escape from neutralizing antibodies when analyzed against post third-dose original monovalent vaccinee sera. Post fourth-dose bivalent vaccinee sera provided better protection against those subvariants, but substantial reductions in neutralization titers were still observed, especially among BA.4/5 subvariants with both an N-terminal domain (NTD) deletion and receptor binding domain (RBD) substitutions K444M + N460K and recombinant Omicron variants. This analysis demonstrated a framework for long-term systematic genotype to antigenic characterization of circulating and emerging SARS-CoV-2 variants in the U.S., which is critical to assessing their potential impact on the effectiveness of current vaccines and antigen recommendations for future updates.

BACKGROUND: In 2019, the Louisiana Department of Health reported an early influenza B/Victoria (B/VIC) virus outbreak. METHOD: As it was an atypically large outbreak, we deployed to Louisiana to investigate it using genomics and a triplex real-time RT-PCR assay to detect three antigenically distinct B/VIC lineage variant viruses. RESULTS: The investigation indicated that B/VIC V1A.3 subclade, containing a three amino acid deletion in the hemagglutinin and known to be antigenically distinct to the B/Colorado/06/2017 vaccine virus, was the most prevalent circulating virus within the specimens evaluated (86/88 in real-time RT-PCR). CONCLUSION: This work underscores the value of portable platforms for rapid, onsite pathogen characterization.

The COVID-19 pandemic was accompanied by an unprecedented surveillance effort. The resulting data were and will continue to be critical for surveillance and control of SARS-CoV-2. However, some genomic surveillance methods experienced challenges as the virus evolved, resulting in incomplete and poor quality data. Complete and quality coverage, especially of the S-gene, is important for supporting the selection of vaccine candidates. As such, we developed a robust method to target the S-gene for amplification and sequencing. By focusing on the S-gene and imposing strict coverage and quality metrics, we hope to increase the quality of surveillance data for this continually evolving gene. Our technique is currently being deployed globally to partner laboratories, and public health representatives from 79 countries have received hands-on training and support. Expanding access to quality surveillance methods will undoubtedly lead to earlier detection of novel variants and better inform vaccine strain selection.

The early Omicron lineage variants evolved and gave rise to diverging lineages that fueled the COVID-19 pandemic in 2022. Bivalent mRNA vaccines, designed to broaden protection against circulating and future variants, were authorized by the U.S. Food and Drug Administration (FDA) in August 2022 and recommended by the U.S. Centers for Disease Control and Prevention (CDC) in September 2022. The impact of bivalent vaccination on eliciting neutralizing antibodies against homologous BA.4/BA.5 viruses as well as emerging heterologous viruses needs to be analyzed. In this study, we analyze the neutralizing activity of sera collected after a third dose of vaccination (2-6 weeks post monovalent booster) or a fourth dose of vaccination (2-7 weeks post bivalent booster) against 10 predominant/recent Omicron lineage viruses including BA.1, BA.2, BA.5, BA.2.75, BA.2.75.2, BN.1, BQ.1, BQ.1.1, XBB, and XBB.1. The bivalent booster vaccination enhanced neutralizing antibody titers against all Omicron lineage viruses tested, including a 10-fold increase in neutralization of BQ.1 and BQ.1.1 viruses that predominated in the U.S. during the last two months of 2022. Overall, the data indicate the bivalent vaccine booster strengthens protection against Omicron lineage variants that evolved from BA.5 and BA.2 progenitors. Copyright The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. This article is a US Government work. It is not subject to copyright under 17 USC 105 and is also made available for use under a CC0 license.

Recombination between SARS-CoV-2 virus variants can result in different viral properties (e.g., infectiousness or pathogenicity). In this report, we describe viruses with recombinant genomes containing signature mutations from Delta and Omicron variants. These genomes are the first evidence for a Delta-Omicron hybrid Spike protein in the United States. Copyright The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. This article is a US Government work. It is not subject to copyright under 17 USC 105 and is also made available for use under a CC0 license.

The novel coronavirus pandemic incited unprecedented demand for assays that detect viral nucleic acids, viral proteins, and corresponding antibodies. The 320 molecular diagnostics in receipt of FDA emergency use authorization mainly focus on viral detection; however, no currently approved test can be used to infer infectiousness, i.e., the presence of replicable virus. As the number of tests conducted increased, persistent SARS-CoV-2 RNA positivity by RT-PCR in some individuals led to concerns over quarantine guidelines. To this end, we attempted to design an assay that reduces the frequency of positive test results from individuals who do not shed culturable virus. We describe multiplex quantitative RT-PCR (qRT-PCR) assays that detect genomic RNA (gRNA) and subgenomic RNA (sgRNA) species of SARS-CoV-2, including spike (S), nucleocapsid (N), membrane (M), envelope (E), and ORF8. The absolute copy number of each RNA target was determined in longitudinal specimens from a household transmission study. Calculated viral RNA levels over the 14-day follow up period were compared with antigen testing and self-reported symptoms to characterize the clinical and molecular dynamics of infection and infer predictive values of these qRT-PCR assays relative to culture isolation. When detection of sgS RNA was added to the CDC 2019-Novel Coronavirus Real-Time RT-PCR Diagnostic Panel, we found a qRT-PCR positive result was 98% predictive of a positive culture (negative predictive value was 94%). Our findings suggest sgRNA presence correlates with active infection, may help identify individuals shedding culturable virus, and that similar multiplex assays can be adapted to current and future variants. Copyright The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. This article is a US Government work. It is not subject to copyright under 17 USC 105 and is also made available for use under a CC0 license.

The evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in the emergence of many new variant lineages that have exacerbated the COVID-19 pandemic. Some of those variants were designated as variants of concern/interest (VOC/VOI) by national or international authorities based on many factors including their potential impact on vaccines. To ascertain and rank the risk of VOCs and VOIs, we analyzed their ability to escape from vaccine-induced antibodies. The variants showed differential reductions in neutralization and replication titers by post-vaccination sera. Although the Omicron variant showed the most escape from neutralization, sera collected after a third dose of vaccine (booster sera) retained moderate neutralizing activity against that variant. Therefore, vaccination remains the most effective strategy to combat the COVID-19 pandemic.

CDC has used national genomic surveillance since December 2020 to monitor SARS-CoV-2 variants that have emerged throughout the COVID-19 pandemic, including the Omicron variant. This report summarizes U.S. trends in variant proportions from national genomic surveillance during January 2022-May 2023. During this period, the Omicron variant remained predominant, with various descendant lineages reaching national predominance (>50% prevalence). During the first half of 2022, BA.1.1 reached predominance by the week ending January 8, 2022, followed by BA.2 (March 26), BA.2.12.1 (May 14), and BA.5 (July 2); the predominance of each variant coincided with surges in COVID-19 cases. The latter half of 2022 was characterized by the circulation of sublineages of BA.2, BA.4, and BA.5 (e.g., BQ.1 and BQ.1.1), some of which independently acquired similar spike protein substitutions associated with immune evasion. By the end of January 2023, XBB.1.5 became predominant. As of May 13, 2023, the most common circulating lineages were XBB.1.5 (61.5%), XBB.1.9.1 (10.0%), and XBB.1.16 (9.4%); XBB.1.16 and XBB.1.16.1 (2.4%), containing the K478R substitution, and XBB.2.3 (3.2%), containing the P521S substitution, had the fastest doubling times at that point. Analytic methods for estimating variant proportions have been updated as the availability of sequencing specimens has declined. The continued evolution of Omicron lineages highlights the importance of genomic surveillance to monitor emerging variants and help guide vaccine development and use of therapeutics.

The report “Genomic Surveillance for SARS-CoV-2 Variants: Predominance of the Delta (B.1.617.2) and Omicron (B.1.1.529) Variants — United States, June 2021–January 2022” contained several errors.

Monitoring emerging SARS-CoV-2 lineages and their epidemiologic characteristics helps to inform public health decisions regarding vaccine policy, the use of therapeutics, and health care capacity. When the SARS-CoV-2 Alpha variant emerged in late 2020, a spike gene (S-gene) deletion (Δ69-70) in the N-terminal region, which might compensate for immune escape mutations that impair infectivity (1), resulted in reduced or failed S-gene target amplification in certain multitarget reverse transcription-polymerase chain reaction (RT-PCR) assays, a pattern referred to as S-gene target failure (SGTF) (2). The predominant U.S. SARS-CoV-2 lineages have generally alternated between SGTF and S-gene target presence (SGTP), which alongside genomic sequencing, has facilitated early monitoring of emerging variants. During a period when Omicron BA.5-related sublineages (which exhibit SGTF) predominated, an XBB.1.5 sublineage with SGTP has rapidly expanded in the northeastern United States and other regions.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of coronavirus disease 2019 (COVID-19), has spread globally and is being surveilled with an international genome sequencing effort. Surveillance consists of sample acquisition, library preparation, and whole genome sequencing. This has necessitated a classification scheme detailing Variants of Concern (VOC) and Variants of Interest (VOI), and the rapid expansion of bioinformatics tools for sequence analysis. These bioinformatic tools are means for major actionable results: maintaining quality assurance and checks, defining population structure, performing genomic epidemiology, and inferring lineage to allow reliable and actionable identification and classification. Additionally, the pandemic has required public health laboratories to reach high throughput proficiency in sequencing library preparation and downstream data analysis rapidly. However, both processes can be limited by a lack of a standardized sequence dataset. METHODS: We identified six SARS-CoV-2 sequence datasets from recent publications, public databases and internal resources. In addition, we created a method to mine public databases to identify representative genomes for these datasets. Using this novel method, we identified several genomes as either VOI/VOC representatives or non-VOI/VOC representatives. To describe each dataset, we utilized a previously published datasets format, which describes accession information and whole dataset information. Additionally, a script from the same publication has been enhanced to download and verify all data from this study. RESULTS: The benchmark datasets focus on the two most widely used sequencing platforms: long read sequencing data from the Oxford Nanopore Technologies platform and short read sequencing data from the Illumina platform. There are six datasets: three were derived from recent publications; two were derived from data mining public databases to answer common questions not covered by published datasets; one unique dataset representing common sequence failures was obtained by rigorously scrutinizing data that did not pass quality checks. The dataset summary table, data mining script and quality control (QC) values for all sequence data are publicly available on GitHub: https://github.com/CDCgov/datasets-sars-cov-2. DISCUSSION: The datasets presented here were generated to help public health laboratories build sequencing and bioinformatics capacity, benchmark different workflows and pipelines, and calibrate QC thresholds to ensure sequencing quality. Together, improvements in these areas support accurate and timely outbreak investigation and surveillance, providing actionable data for pandemic management. Furthermore, these publicly available and standardized benchmark data will facilitate the development and adjudication of new pipelines.

To detect new and changing SARS-CoV-2 variants, we investigated candidate Delta-Omicron recombinant genomes from Centers for Disease Control and Prevention national genomic surveillance. Laboratory and bioinformatic investigations identified and validated 9 genetically related SARS-CoV-2 viruses with a hybrid Delta-Omicron spike protein.

BACKGROUND: Neurological COVID-19 disease has been reported widely, but published studies often lack information on neurological outcomes and prognostic risk factors. We aimed to describe the spectrum of neurological disease in hospitalised COVID-19 patients; characterise clinical outcomes; and investigate factors associated with a poor outcome. METHODS: We conducted an individual patient data (IPD) meta-analysis of hospitalised patients with neurological COVID-19 disease, using standard case definitions. We invited authors of studies from the first pandemic wave, plus clinicians in the Global COVID-Neuro Network with unpublished data, to contribute. We analysed features associated with poor outcome (moderate to severe disability or death, 3 to 6 on the modified Rankin Scale) using multivariable models. RESULTS: We included 83 studies (31 unpublished) providing IPD for 1979 patients with COVID-19 and acute new-onset neurological disease. Encephalopathy (978 [49%] patients) and cerebrovascular events (506 [26%]) were the most common diagnoses. Respiratory and systemic symptoms preceded neurological features in 93% of patients; one third developed neurological disease after hospital admission. A poor outcome was more common in patients with cerebrovascular events (76% [95% CI 67-82]), than encephalopathy (54% [42-65]). Intensive care use was high (38% [35-41]) overall, and also greater in the cerebrovascular patients. In the cerebrovascular, but not encephalopathic patients, risk factors for poor outcome included breathlessness on admission and elevated D-dimer. Overall, 30-day mortality was 30% [27-32]. The hazard of death was comparatively lower for patients in the WHO European region. INTERPRETATION: Neurological COVID-19 disease poses a considerable burden in terms of disease outcomes and use of hospital resources from prolonged intensive care and inpatient admission; preliminary data suggest these may differ according to WHO regions and country income levels. The different risk factors for encephalopathy and stroke suggest different disease mechanisms which may be amenable to intervention, especially in those who develop neurological symptoms after hospital admission.

The novel coronavirus pandemic incited unprecedented demand for assays that detect viral nucleic acids, viral proteins, and corresponding antibodies. The 320 molecular diagnostics in receipt of FDA emergency use authorization mainly focus on viral detection; however, no currently approved test can be used to infer infectiousness, i.e., the presence of replicable virus. As the number of tests conducted increased, persistent SARS-CoV-2 RNA positivity by RT-PCR in some individuals led to concerns over quarantine guidelines. To this end, we attempted to design an assay that reduces the frequency of positive test results from individuals who do not shed culturable virus. We describe multiplex quantitative RT-PCR (qRT-PCR) assays that detect genomic RNA (gRNA) and subgenomic RNA (sgRNA) species of SARS-CoV-2, including spike (S), nucleocapsid (N), membrane (M), envelope (E), and ORF8. Viral RNA abundances calculated from these assays were compared with antigen presence, self-reported symptoms, and culture outcome (virus isolation) using samples from a 14-day longitudinal household transmission study. By characterizing the clinical and molecular dynamics of infection, we show sgRNA detection has higher predictive value for culture outcome compared to detection of gRNA alone. Our findings suggest sgRNA presence correlates with active infection and may help identify individuals shedding culturable virus.

Genomic surveillance is a critical tool for tracking emerging variants of SARS-CoV-2 (the virus that causes COVID-19), which can exhibit characteristics that potentially affect public health and clinical interventions, including increased transmissibility, illness severity, and capacity for immune escape. During June 2021-January 2022, CDC expanded genomic surveillance data sources to incorporate sequence data from public repositories to produce weighted estimates of variant proportions at the jurisdiction level and refined analytic methods to enhance the timeliness and accuracy of national and regional variant proportion estimates. These changes also allowed for more comprehensive variant proportion estimation at the jurisdictional level (i.e., U.S. state, district, territory, and freely associated state). The data in this report are a summary of findings of recent proportions of circulating variants that are updated weekly on CDC's COVID Data Tracker website to enable timely public health action.(†) The SARS-CoV-2 Delta (B.1.617.2 and AY sublineages) variant rose from 1% to >50% of viral lineages circulating nationally during 8 weeks, from May 1-June 26, 2021. Delta-associated infections remained predominant until being rapidly overtaken by infections associated with the Omicron (B.1.1.529 and BA sublineages) variant in December 2021, when Omicron increased from 1% to >50% of circulating viral lineages during a 2-week period. As of the week ending January 22, 2022, Omicron was estimated to account for 99.2% (95% CI = 99.0%-99.5%) of SARS-CoV-2 infections nationwide, and Delta for 0.7% (95% CI = 0.5%-1.0%). The dynamic landscape of SARS-CoV-2 variants in 2021, including Delta- and Omicron-driven resurgences of SARS-CoV-2 transmission across the United States, underscores the importance of robust genomic surveillance efforts to inform public health planning and practice.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in late 2019, and the outbreak rapidly evolved into the current coronavirus disease pandemic. SARS-CoV-2 is a respiratory virus that causes symptoms similar to those caused by influenza A and B viruses. On July 2, 2020, the US Food and Drug Administration granted emergency use authorization for in vitro diagnostic use of the Influenza SARS-CoV-2 Multiplex Assay. This assay detects influenza A virus at 10(2.0), influenza B virus at 10(2.2), and SARS-CoV-2 at 10(0.3) 50% tissue culture or egg infectious dose, or as few as 5 RNA copies/reaction. The simultaneous detection and differentiation of these 3 major pathogens increases overall testing capacity, conserves resources, identifies co-infections, and enables efficient surveillance of influenza viruses and SARS-CoV-2.

Alpha-thalassemia comprises a group of inherited disorders in which alpha-hemoglobin chain production is reduced. Depending on the genotype, alpha-thalassemia results in moderate to profound anemia, hemolysis, growth delays, splenomegaly, and increased risk for thromboembolic events; certain patients might require chronic transfusions. Although alpha-thalassemia is not a core condition of the United States Recommended Uniform Screening Panel* for state newborn screening programs, methodologies used by some newborn screening programs to detect sickle cell disease, which is a core panel condition, also detect a quantitative marker of alpha-thalassemia, hemoglobin (Hb) Bart's, an abnormal type of hemoglobin. The percentage of Hb Bart's detected correlates with alpha-thalassemia severity. The Association of Public Health Laboratories' Hemoglobinopathy Workgroup conducted a survey of state newborn screening programs' alpha-thalassemia screening methodologies and reporting and follow-up practices. Survey findings indicated that 41 of 44 responding programs (93%) report some form of alpha-thalassemia results and 57% used a two-method screening protocol. However, the percentage of Hb Bart's used for thalassemia classification, the types of alpha-thalassemia reported, and the recipients of this information varied widely. These survey findings highlight the opportunity for newborn screening programs to revisit their policies as they reevaluate their practices in light of the recently released guideline from the Clinical and Laboratory Standards Institute (CLSI) on Newborn Screening for Hemoglobinopathies (1). Although deferring to local programs for policies, the report used a cutoff of 25% Hb Bart's in its decision tree, a value many programs do not use. Standardization of screening and reporting might lead to more timely diagnoses and health care services and improved outcomes for persons with a clinically significant alpha-thalassemia.

BACKGROUND: VZV vasculopathy is characterized by persistent arterial inflammation leading to stroke. Studies show that VZV induces amyloid formation that may aggravate vasculitis. Thus, we determined if VZV central nervous system (CNS) infection produces amyloid. METHODS: Aβ peptides, amylin, and amyloid were measured in CSF from 16 VZV vasculopathy subjects and 36 stroke controls. To determine if infection induced amyloid deposition, mock- and VZV-infected quiescent primary human perineurial cells (qHPNCs), present in vasculature, were analyzed for intracellular amyloidogenic transcripts/proteins and amyloid. Supernatants were assayed for amyloidogenic peptides and ability to induce amyloid formation. To determine amylin's function during infection, amylin was knocked down with siRNA and viral cDNA quantitated. RESULTS: Compared to controls, VZV vasculopathy CSF had increased amyloid that positively correlated with amylin and anti-VZV antibody levels; Aβ40 was reduced and Aβ42 unchanged. Intracellular amylin, Aβ42, and amyloid were seen only in VZV-infected qHPNCs. VZV-infected supernatant formed amyloid fibrils following addition of amyloidogenic peptides. Amylin knockdown decreased viral cDNA. CONCLUSIONS: VZV infection increased levels of amyloidogenic peptides and amyloid in CSF and qHPNCs, indicating that VZV-induced amyloid deposition may contribute to persistent arterial inflammation in VZV vasculopathy. In addition, we identified a novel proviral function of amylin.

Newborn screening (NBS) identifies infants with rare conditions to prevent death or the onset of irreversible morbidities. Conditions on the Health and Human Services Secretary's Recommended Uniform Screening Panel have been adopted by most state NBS programs, providing a consistent approach for identification of affected newborns across the United States. Screen-positive newborns are identified and referred for confirmatory diagnosis and follow-up. The designation of a clinically significant phenotype precursor to a clinical diagnosis may vary between clinical specialists, resulting in diagnostic variation. Determination of disease burden and birth prevalence of the screened conditions by public health tracking is made challenging by these variations. This report describes the development of a core group of new case definitions, along with implications, plans for their use, and links to the definitions that were developed by panels of clinical experts. These definitions have been developed through an iterative process and are piloted in NBS programs. Consensus public health surveillance case definitions for newborn screened disorders will allow for consistent categorization and tracking of short- and long-term follow-up of identified newborns at the local, regional, and national levels.

Approximately 100,000 Americans have sickle cell disease (SCD), a group of recessively inherited red blood cell disorders characterized by abnormal hemoglobin, called hemoglobin S or sickle hemoglobin, in the red blood cells. Persons with hemoglobin SS or hemoglobin Sss0 thalassemia, also known as sickle cell anemia (SCA), have the most severe form of SCD. Hemoglobin SC disease and hemoglobin Sss+ thalassemia are other common forms of SCD. Red blood cells that contain sickle hemoglobin are inflexible and can stick to vessel walls, causing a blockage that slows or stops blood flow. When this happens, oxygen cannot reach nearby tissues, leading to attacks of sudden, severe pain, called pain crises, which are the clinical hallmark of SCD. The red cell sickling and poor oxygen delivery can also cause damage to the brain, spleen, eyes, lungs, liver, and multiple other organs and organ systems. These chronic complications can lead to increased morbidity, early mortality, or both. Tremendous strides in treating and preventing the complications of SCD have extended life expectancy. Now, nearly 95% of persons born with SCD in the United States reach age 18 years (1); however, adults with the most severe forms of SCD have a life span that is 20-30 years shorter than that of persons without SCD (2).

A 10% excise tax on sugar sweetened beverages (SSBs) was implemented in Barbados in September 2015. A national evaluation has been established to assess the impact of the tax. We present a descriptive analysis of initial price changes following implementation of the SSB tax using price data provided by a major supermarket chain in Barbados over the period 2014-2016. We summarize trends in price change before and after the tax using year-on-year mean price per liter change between SSBs and non-SSBs. We find that prior to the tax, year-on-year price growth of SSBs and non-SSBs was very similar (approximately 1%). During the quarter in which the tax was implemented, the trends diverged, with SSB prices growing by almost 3% while prices of non-SSBs decreased slightly. The growth of SSB prices outpaced non-SSBs prices in each quarter thereafter, reaching 5.9% growth compared to <1% for non-SSBs. Future analyses will assess the trends in prices of SSBs and non-SSBs over a longer period and will integrate price data from additional sources to assess heterogeneity of post-tax price changes. A continued examination of the impact of the SSB tax in Barbados will expand the evidence base available to policymakers worldwide in considering SSB taxes as a lever for reducing the consumption of added sugars at the population level.

Hypertension is the leading remediable risk factor for cardiovascular disease, affecting more than 1 billion people worldwide, and is responsible for more than 10 million preventable deaths globally each year. While hypertension can be successfully diagnosed and treated, only one in seven persons with hypertension have controlled blood pressure. To meet the challenge of improving the control of hypertension, particularly in low- and middle-income countries, the authors developed the Standardized Hypertension Treatment and Prevention Project, which involves a health systems-strengthening approach that advocates for standardized hypertension management using evidence-based interventions. These interventions include the use of standardized treatment protocols, a core set of medications along with improved procurement mechanisms to increase the availability and affordability of these medications, registries for cohort monitoring and evaluation, patient empowerment, team-based care (task shifting), and community engagement. With political will and strong partnerships, this approach provides the groundwork to reduce high blood pressure and cardiovascular disease-related morbidity and mortality.

Newborn screening (NBS) is intended to identify congenital conditions prior to the onset of symptoms in order to provide early intervention that leads to improved outcomes. NBS is a public health success, providing reduction in mortality and improved developmental outcomes for screened conditions. However, it is less clear to what extent newborn screening achieves the long-term goals relating to improved health, growth, development and function. We propose a framework for assessing outcomes for the health and well-being of children identified through NBS programs. The framework proposed here, and this manuscript, were approved for publication by the Secretary of Health and Human Services' Advisory Committee on Heritable Disorders in Newborns and Children (ACHDNC). This framework can be applied to each screened condition within the Recommended Uniform Screening Panel (RUSP), recognizing that the data elements and measures will vary by condition. As an example, we applied the framework to sickle cell disease and phenylketonuria (PKU), two diverse conditions with different outcome measures and potential sources of data. Widespread and consistent application of this framework across state NBS and child health systems is envisioned as useful to standardize approaches to assessment of outcomes and for continuous improvement of the NBS and child health systems. SIGNIFICANCE: Successful interventions for newborn screening conditions have been a driving force for public health newborn screening for over fifty years. Organizing interventions and outcome measures into a standard framework to systematically assess outcomes has not yet come into practice. This paper presents a customizable outcomes framework for organizing measures for newborn screening condition-specific health outcomes, and an approach to identifying sources and challenges to populating those measures.

OBJECTIVES: We evaluated a strategy for preventing tuberculosis (TB) in communities most affected by it. METHODS: In 1996, we mapped reported TB cases (1985-1995) and positive tuberculin skin test (TST) reactors (1993-1995) in Smith County, Texas. We delineated the 2 largest, densest clusters, identifying 2 highest-incidence neighborhoods (180 square blocks, 3153 residents). After extensive community preparation, trained health care workers went door-to-door offering TST to all residents unless contraindicated. TST-positive individuals were escorted to a mobile clinic for radiography, clinical evaluation, and isoniazid preventive treatment (IPT) as indicated. To assess long-term impact, we mapped all TB cases in Smith County during the equivalent time period after the project. RESULTS: Of 2258 eligible individuals, 1291 (57.1%) were tested, 229 (17.7%) were TST positive, and 147 were treated. From 1996 to 2006, there were no TB cases in either project neighborhood, in contrast with the preintervention decade and the continued occurrence of TB in the rest of Smith County. CONCLUSIONS: Targeting high-incidence neighborhoods for active, community-based screening and IPT may hasten TB elimination in the United States.