BACKGROUND: Rapid, accessible, and accurate testing was paramount to an effective US COVID-19 response. Federal partners supported SARS-CoV-2 testing scale-up through an interagency-coordinated approach that focused on expanding supply chains, research and development, validation, and improving patient access. We aimed to provide an overview of the federal efforts to scale up the testing response and study the impact of scale-up. METHODS: In this descriptive analysis, we mapped federal partner activities and milestones using the US Government Testing and Diagnostics Working Group (TDWG) and participating agency and department data from Jan 1, 2020, to Dec 31, 2022. Tests produced (TDWG), reported test positivity (US Centers for Disease Control and Prevention [CDC]'s COVID-19 Electronic Laboratory Reporting system and the Federal Direct Report testing data), reported COVID-19 case counts (CDC), hospitalisations (Department of Health and Human Services Unified Hospital Data Surveillance System and the CDC's National Healthcare Safety Network), and deaths (CDC) were analysed over time. We then developed an agent-based model to evaluate the impact testing had on COVID-19 outcomes using different scenarios. The scenarios were (1) if efforts led to substantially fewer tests produced, (2) if scale-up was delayed, affecting test access, and (3) if efforts led to substantially more tests produced. FINDINGS: Approximately 6·7 billion SARS-CoV-2 tests, including over 1·5 billion laboratory-based, 1·9 billion point-of-care (POC), and 3·2 billion over-the-counter (OTC) tests, were produced, and approximately 2·7 billion tests were performed between Jan 1, 2020, and Dec 31, 2022. Testing capacity exhibited various expansion phases, with laboratory-based capacity growing from approximately 6 million tests per month in March, 2020 to approximately 34 million tests per month in July, 2020; POC increased to approximately 126 million tests per month by December, 2020, and OTC increased to approximately 986 million tests per month by February, 2022. Comparison between the baseline (actual) and delay-in-testing scenario suggests the increased testing capacity potentially saved upwards of 1·4 million lives and averted 7 million hospitalisations. INTERPRETATION: Our study suggests that early development, manufacturing, and distribution of tests had a great impact on reducing severe COVID-19 outcomes. These results highlight the importance of robust and rapid test development, production, and distribution when addressing future public health threats. FUNDING: US Administration for Strategic Preparedness and Response and US Centers for Disease Control and Prevention.

PROBLEM/CONDITION: A 2019 report quantified the higher percentage of potentially excess (preventable) deaths in U.S. nonmetropolitan areas compared with metropolitan areas during 2010-2017. In that report, CDC compared national, regional, and state estimates of preventable premature deaths from the five leading causes of death in nonmetropolitan and metropolitan counties during 2010-2017. This report provides estimates of preventable premature deaths for additional years (2010-2022). PERIOD COVERED: 2010-2022. DESCRIPTION OF SYSTEM: Mortality data for U.S. residents from the National Vital Statistics System were used to calculate preventable premature deaths from the five leading causes of death among persons aged <80 years. CDC's National Center for Health Statistics urban-rural classification scheme for counties was used to categorize the deaths according to the urban-rural county classification level of the decedent's county of residence (1: large central metropolitan [most urban], 2: large fringe metropolitan, 3: medium metropolitan, 4: small metropolitan, 5: micropolitan, and 6: noncore [most rural]). Preventable premature deaths were defined as deaths among persons aged <80 years that exceeded the number expected if the death rates for each cause in all states were equivalent to those in the benchmark states (i.e., the three states with the lowest rates). Preventable premature deaths were calculated separately for the six urban-rural county categories nationally, the 10 U.S. Department of Health and Human Services public health regions, and the 50 states and the District of Columbia. RESULTS: During 2010-2022, the percentage of preventable premature deaths among persons aged <80 years in the United States increased for unintentional injury (e.g., unintentional poisoning including drug overdose, unintentional motor vehicle traffic crash, unintentional drowning, and unintentional fall) and stroke, decreased for cancer and chronic lower respiratory disease (CLRD), and remained stable for heart disease. The percentages of preventable premature deaths from the five leading causes of death were higher in rural counties in all years during 2010-2022. When assessed by the six urban-rural county classifications, percentages of preventable premature deaths in the most rural counties (noncore) were consistently higher than in the most urban counties (large central metropolitan and fringe metropolitan) for the five leading causes of death during the study period.During 2010-2022, preventable premature deaths from heart disease increased most in noncore (+9.5%) and micropolitan counties (+9.1%) and decreased most in large central metropolitan counties (-10.2%). Preventable premature deaths from cancer decreased in all county categories, with the largest decreases in large central metropolitan and large fringe metropolitan counties (-100.0%; benchmark achieved in both county categories in 2019). In all county categories, preventable premature deaths from unintentional injury increased, with the largest increases occurring in large central metropolitan (+147.5%) and large fringe metropolitan (+97.5%) counties. Preventable premature deaths from CLRD decreased most in large central metropolitan counties where the benchmark was achieved in 2019 and increased slightly in noncore counties (+0.8%). In all county categories, preventable premature deaths from stroke decreased from 2010 to 2013, remained constant from 2013 to 2019, and then increased in 2020 at the start of the COVID-19 pandemic. Percentages of preventable premature deaths varied across states by urban-rural county classification during 2010-2022. INTERPRETATION: During 2010-2022, nonmetropolitan counties had higher percentages of preventable premature deaths from the five leading causes of death than did metropolitan counties nationwide, across public health regions, and in most states. The gap between the most rural and most urban counties for preventable premature deaths increased during 2010-2022 for four causes of death (cancer, heart disease, CLRD, and stroke) and decreased for unintentional injury. Urban and suburban counties (large central metropolitan, large fringe metropolitan, medium metropolitan, and small metropolitan) experienced increases in preventable premature deaths from unintentional injury during 2010-2022, leading to a narrower gap between the already high (approximately 69% in 2022) percentage of preventable premature deaths in noncore and micropolitan counties. Sharp increases in preventable premature deaths from unintentional injury, heart disease, and stroke were observed in 2020, whereas preventable premature deaths from CLRD and cancer continued to decline. CLRD deaths decreased during 2017-2020 but increased in 2022. An increase in the percentage of preventable premature deaths for multiple leading causes of death was observed in 2020 and was likely associated with COVID-19-related conditions that contributed to increased mortality from heart disease and stroke. PUBLIC HEALTH ACTION: Routine tracking of preventable premature deaths based on urban-rural county classification might enable public health departments to identify and monitor geographic disparities in health outcomes. These disparities might be related to different levels of access to health care, social determinants of health, and other risk factors. Identifying areas with a high prevalence of potentially preventable mortality might be informative for interventions.

In August 2013, the Food and Drug Administration (FDA) permitted marketing of the Xpert MTB/RIF assay (Cepheid, Sunnyvale, California) to detect DNA of the Mycobacterium tuberculosis complex (MTBC) and genetic mutations associated with resistance to rifampin (RMP) in unprocessed sputum and concentrated sputum sediments. Along with clinical, radiographic, and other laboratory findings, results of the assay aid in the diagnosis of pulmonary tuberculosis (TB). The assay is a nucleic acid amplification-based (NAA)* test using a disposable cartridge in conjunction with the GeneXpert Instrument System. Sensitivity and specificity of the Xpert MTB/RIF assay for detection of MTBC appear to be comparable with other FDA-approved NAA assays for this use, although direct comparison studies have not been performed. Sensitivity of detection of RMP resistance was 95% and specificity 99% in a multicenter study using archived and prospective specimens from subjects aged ≥18 years suspected of having TB who had 0-3 days of antituberculous treatment. CDC continues to recommend following published U.S. guidelines for TB diagnosis and infection control practice, including the use and interpretation of NAA test results. Providers and laboratories need to ensure that specimens are available for other recommended mycobacteriological testing. The Xpert MTB/RIF assay aids in the prompt diagnosis of TB and RMP-resistant disease. RMP resistance most often coexists with isoniazid (INH) resistance; TB that is resistant to both drugs is multidrug-resistant (MDR)† TB. Because the prevalence of RMP resistance is low in the United States (about 1.8% of TB cases), a positive result indicating a mutation in the rpoB gene of MTBC should be confirmed by rapid DNA sequencing for prompt reassessment of the treatment regimen and followed by growth-based drug susceptibility testing (DST). CDC offers these services free of charge.§

BACKGROUND: There is a need for validated and standardized severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) quantitative immunoglobulin G (IgG) and neutralization assays that can be used to understand the immunology and pathogenesis of SARS-CoV-2 infection and support the coronavirus disease 2019 (COVID-19) pandemic response. METHODS: Literature searches were conducted to identify English language publications from peer-reviewed journals and preprints from January 2020 through November 6, 2020. Relevant publications were reviewed for mention of IgG or neutralization assays for SARS-CoV-2, or both, and the methods of reporting assay results. RESULTS: Quantitative SARS-CoV-2 IgG results have been reported from a limited number of studies; most studies used in-house laboratory-developed tests in limited settings, and only two semiquantitative tests have received US Food and Drug Administration (FDA) Emergency Use Authorization (EUA). As of November 6, 2020, there is only one SARS-CoV-2 neutralization assay with FDA EUA. Relatively few studies have attempted correlation of quantitative IgG titers with neutralization results to estimate surrogates of protection. The number of individuals tested is small compared with the magnitude of the pandemic, and persons tested are not representative of disproportionately affected populations. Methods of reporting quantitative results are not standardized to enable comparisons and meta-analyses. CONCLUSIONS: Lack of standardized SARS-CoV-2 quantitative IgG and neutralization assays precludes comparison of results from published studies. Interassay and interlaboratory validation and standardization of assays will support efforts to better understand antibody kinetics and longevity of humoral immune responses postillness, surrogates of immune protection, and vaccine immunogenicity and efficacy. Public-private partnerships could facilitate realization of these advances in the United States and worldwide.

Muin Khoury and co-authors discuss anticipated contributions of genomics and other forms of large-scale data in public health.

Twenty percent of the US population, or about 60 million persons, live in rural areas.1 Rural and urban counties differ in their demographic, environmental, economic, and social characteristics, which influences health and the prevalence of disease risk factors. The rates of cigarette smoking, hypertension, obesity, and physical inactivity during leisure time are higher in rural areas than in urban areas.2 About 30% of persons living in rural counties live in poverty, whereas 19% of persons living in large central and large fringe metropolitan counties and 15% of persons living in medium and small metropolitan counties live in poverty.3 The availability of preventive services and health care access also differ in rural and urban areas. Residents of rural counties are more likely to report lower levels of health care access and lower-quality care than residents of urban counties.2 Urban areas generally have a higher density and diversity of health care providers than rural areas.4,5

PROBLEM/CONDITION: A 2017 report quantified the higher percentage of potentially excess (or preventable) deaths in nonmetropolitan areas (often referred to as rural areas) compared with metropolitan areas. In that report, CDC compared national, regional, and state estimates of potentially excess deaths among the five leading causes of death in nonmetropolitan and metropolitan counties for 2010 and 2014. This report enhances the geographic detail by using the six levels of the 2013 National Center for Health Statistics (NCHS) urban-rural classification scheme for counties and extending estimates of potentially excess deaths by annual percent change (APC) and for additional years (2010-2017). Trends were tested both with linear and quadratic terms. PERIOD COVERED: 2010-2017. DESCRIPTION OF SYSTEM: Mortality data for U.S. residents from the National Vital Statistics System were used to calculate potentially excess deaths from the five leading causes of death among persons aged <80 years. CDC's NCHS urban-rural classification scheme for counties was used to categorize the deaths according to the urban-rural county classification level of the decedent's county of residence (1: large central metropolitan [most urban], 2: large fringe metropolitan, 3: medium metropolitan, 4: small metropolitan, 5: micropolitan, and 6: noncore [most rural]). Potentially excess deaths were defined as deaths among persons aged <80 years that exceeded the number expected if the death rates for each cause in all states were equivalent to those in the benchmark states (i.e., the three states with the lowest rates). Potentially excess deaths were calculated separately for the six urban-rural county categories nationally, the 10 U.S. Department of Health and Human Services public health regions, and the 50 states and District of Columbia. RESULTS: The number of potentially excess deaths among persons aged <80 years in the United States increased during 2010-2017 for unintentional injuries (APC: 11.2%), decreased for cancer (APC: -9.1%), and remained stable for heart disease (APC: 1.1%), chronic lower respiratory disease (CLRD) (APC: 1.7%), and stroke (APC: 0.3). Across the United States, percentages of potentially excess deaths from the five leading causes were higher in nonmetropolitan counties in all years during 2010-2017. When assessed by the six urban-rural county classifications, percentages of potentially excess deaths in the most rural counties (noncore) were consistently higher than in the most urban counties (large central metropolitan) for the study period. Potentially excess deaths from heart disease increased most in micropolitan counties (APC: 2.5%) and decreased most in large fringe metropolitan counties (APC: -1.1%). Potentially excess deaths from cancer decreased in all county categories, with the largest decreases in large central metropolitan (APC: -16.1%) and large fringe metropolitan (APC: -15.1%) counties. In all county categories, potentially excess deaths from the five leading causes increased, with the largest increases occurring in large central metropolitan (APC: 18.3%), large fringe metropolitan (APC: 17.1%), and medium metropolitan (APC: 11.1%) counties. Potentially excess deaths from CLRD decreased most in large central metropolitan counties (APC: -5.6%) and increased most in micropolitan (APC: 3.7%) and noncore (APC: 3.6%) counties. In all county categories, potentially excess deaths from stroke exhibited a quadratic trend (i.e., decreased then increased), except in micropolitan counties, where no change occurred. Percentages of potentially excess deaths also differed among and within public health regions and across states by urban-rural county classification during 2010-2017. INTERPRETATION: Nonmetropolitan counties had higher percentages of potentially excess deaths from the five leading causes than metropolitan counties during 2010-2017 nationwide, across public health regions, and in the majority of states. The gap between the most rural and most urban counties for potentially excess deaths increased during 2010-2017 for three causes of death (cancer, heart disease, and CLRD), decreased for unintentional injury, and remained relatively stable for stroke. Urban and suburban counties (large central metropolitan and large fringe metropolitan, medium metropolitan, and small metropolitan) experienced increases in potentially excess deaths from unintentional injury during 2010-2017, leading to a narrower gap between the already high (approximately 55%) percentage of excess deaths in noncore and micropolitan counties. PUBLIC HEALTH ACTION: Routine tracking of potentially excess deaths by urban-rural county classification might help public health departments and decision-makers identify and monitor public health problems and focus interventions to reduce potentially excess deaths in these areas.

Drug overdose is the leading cause of unintentional injury-associated death in the United States. Among 70,237 fatal drug overdoses in 2017, prescription opioids were involved in 17,029 (24.2%) (1). Higher rates of opioid-related deaths have been recorded in nonmetropolitan (rural) areas (2). In 2017, 14 rural counties were among the 15 counties with the highest opioid prescribing rates.* Higher opioid prescribing rates put patients at risk for addiction and overdose (3). Using deidentified data from the Athenahealth electronic health record (EHR) system, opioid prescribing rates among 31,422 primary care providers(dagger) in the United States were analyzed to evaluate trends from January 2014 to March 2017. This analysis assessed how prescribing practices varied among six urban-rural classification categories of counties, before and after the March 2016 release of CDC's Guideline for Prescribing Opioids for Chronic Pain (Guideline) (4). Patients in noncore (the most rural) counties had an 87% higher chance of receiving an opioid prescription compared with persons in large central metropolitan counties during the study period. Across all six county groups, the odds of receiving an opioid prescription decreased significantly after March 2016. This decrease followed a flat trend during the preceding period in micropolitan and large central metropolitan county groups; in contrast, the decrease continued previous downward trends in the other four county groups. Data from EHRs can effectively supplement traditional surveillance methods for monitoring trends in opioid prescribing and other areas of public health importance, with minimal lag time under ideal conditions. As less densely populated areas appear to indicate both substantial progress in decreasing opioid prescribing and ongoing need for reduction, community health care practices and intervention programs must continue to be tailored to community characteristics.

Public health surveillance is the cornerstone of public health practice.1 In the United States, the Centers for Disease Control and Prevention (CDC) and states share responsibility for the surveillance enterprise. States have primary responsibility for traditional name-based disease reporting, and they subsequently share anonymized data with CDC. At the same time, CDC maintains many surveillance systems at the federal level. For decades, the number of these single-disease or condition, single-purpose surveillance systems has grown as CDC has needed to expand surveillance data collection to address new public health problems. Currently, CDC has more than 110 surveillance systems. Although these systems provide CDC with the surveillance data needed by the agency, many are experienced as repetitive and burdensome by state and local public health departments, with little or no coordination. This profusion of CDC systems results in duplication of effort, discrepancies among the data elements collected by various programs, and the need to use multiple information technology (IT) systems, which may not be interoperable.

At the intersection of new technology advancements, ever-changing health policy, and fiscal constraints, public health agencies seek to leverage modern technical innovations and benefit from a more comprehensive and cooperative approach to transforming public health, health care, and other data into action. State health agencies recognized a way to advance population health was to integrate public health with clinical health data through electronic infectious disease case reporting. The Public Health Community Platform (PHCP) concept of bidirectional data flow and knowledge management became the foundation to build a cloud-based system connecting electronic health records to public health data for a select initial set of notifiable conditions. With challenges faced and lessons learned, significant progress was made and the PHCP grew into the Digital Bridge, a national governance model for systems change, bringing together software vendors, public health, and health care. As the model and technology advance together, opportunities to advance future connectivity solutions for both health care and public health will emerge.

Public health surveillance is the foundation of effective public health practice. Public health surveillance is defined as the ongoing systematic collection, analysis, and interpretation of data, closely integrated with the dissemination of these data to the public health practitioners, clinicians, and policy makers responsible for preventing and controlling disease and injury.1 Ideally, surveillance systems should support timely, efficient, flexible, scalable, and interoperable data acquisition, analysis, and dissemination. However, many current systems rely on disease-specific approaches that inhibit efficiency and interoperability (eg, manual data entry and data recoding that place a substantial burden on data partners) and use slow, inefficient, out-of-date technologies that no longer meet user needs for data management, analysis, visualization, and dissemination.2–4 Advances in information technology, data science, analytic methods, and information sharing provide an opportunity to substantially enhance surveillance. As a global leader in public health surveillance, the Centers for Disease Control and Prevention (CDC) is working with public health partners to transform and modernize CDC’s surveillance systems and approaches. Here, we describe recent enhancements in surveillance data analysis and visualization, information sharing, and dissemination at CDC and identify the challenges ahead.

In 2014, the all-cause age-adjusted death rate in the United States reached a historic low of 724.6 per 100,000 population (1). However, mortality in rural (nonmetropolitan) areas of the United States has decreased at a much slower pace, resulting in a widening gap between rural mortality rates (830.5) and urban mortality rates (704.3) (1). During 1999-2014, annual age-adjusted death rates for the five leading causes of death in the United States (heart disease, cancer, unintentional injury, chronic lower respiratory disease (CLRD), and stroke) were higher in rural areas than in urban (metropolitan) areas (Figure 1). In most public health regions (Figure 2), the proportion of deaths among persons aged <80 years (U.S. average life expectancy) (2) from the five leading causes that were potentially excess deaths was higher in rural areas compared with urban areas (Figure 3). Several factors probably influence the rural-urban gap in potentially excess deaths from the five leading causes, many of which are associated with sociodemographic differences between rural and urban areas. Residents of rural areas in the United States tend to be older, poorer, and sicker than their urban counterparts (3). A higher proportion of the rural U.S. population reports limited physical activity because of chronic conditions than urban populations (4). Moreover, social circumstances and behaviors have an impact on mortality and potentially contribute to approximately half of the determining causes of potentially excess deaths (5).

PROBLEM/CONDITION: Higher rates of death in nonmetropolitan areas (often referred to as rural areas) compared with metropolitan areas have been described but not systematically assessed. PERIOD COVERED: 1999-2014 DESCRIPTION OF SYSTEM: Mortality data for U.S. residents from the National Vital Statistics System were used to calculate age-adjusted death rates and potentially excess deaths for nonmetropolitan and metropolitan areas for the five leading causes of death. Age-adjusted death rates included all ages and were adjusted to the 2000 U.S. standard population by the direct method. Potentially excess deaths are defined as deaths among persons aged <80 years that exceed the numbers that would be expected if the death rates of states with the lowest rates (i.e., benchmark states) occurred across all states. (Benchmark states were the three states with the lowest rates for each cause during 2008-2010.) Potentially excess deaths were calculated separately for nonmetropolitan and metropolitan areas. Data are presented for the United States and the 10 U.S. Department of Health and Human Services public health regions. RESULTS: Across the United States, nonmetropolitan areas experienced higher age-adjusted death rates than metropolitan areas. The percentages of potentially excess deaths among persons aged <80 years from the five leading causes were higher in nonmetropolitan areas than in metropolitan areas. For example, approximately half of deaths from unintentional injury and chronic lower respiratory disease in nonmetropolitan areas were potentially excess deaths, compared with 39.2% and 30.9%, respectively, in metropolitan areas. Potentially excess deaths also differed among and within public health regions; within regions, nonmetropolitan areas tended to have higher percentages of potentially excess deaths than metropolitan areas. INTERPRETATION: Compared with metropolitan areas, nonmetropolitan areas have higher age-adjusted death rates and greater percentages of potentially excess deaths from the five leading causes of death, nationally and across public health regions. PUBLIC HEALTH ACTION: Routine tracking of potentially excess deaths in nonmetropolitan areas might help public health departments identify emerging health problems, monitor known problems, and focus interventions to reduce preventable deaths in these areas.

Public health surveillance is focused on the detection of acute, chronic, and emerging threats to the health of the population to direct disease control and prevention efforts.1 Public health surveillance relies on health care providers to report to public health agencies conditions or outbreaks that may impact the broader population. This case reporting is mandated through laws and regulations at the state and local levels. Notification of cases to the Centers for Disease Control and Prevention (CDC) is facilitated by agreements between states and the federal government.2 Historically, case reporting has been based on paper reports or Internet-based entry of reports to state health department systems, but these reports are often slow or incomplete and place a substantial burden of work on health care providers and public health agencies.3 The future of surveillance is electronic case reporting (eCR), by which cases of reportable conditions are automatically generated from electronic health record (EHR) systems and transmitted to public health agencies for review and action. | eCR holds promise for enhancing the quality and effectiveness of public health surveillance.4 Greater use of eCR could result in (1) more complete and accurate case data in near real time for public health action; (2) earlier detection of cases, permitting earlier intervention and lowered transmission of disease; (3) improved detection of outbreaks to allow earlier investigation and, potentially, earlier identification of risk factors for the spread of disease; and (4) creation of a new infrastructure to support rapid reporting of newly recognized and emerging conditions. In this commentary, we review the promise of eCR and present our vision for a nationally interoperable eCR system that allows for timely reporting to public health and information sharing among jurisdictions.

Death rates by specific causes vary across the 50 states and the District of Columbia.* Information on differences in rates for the leading causes of death among states might help state health officials determine prevention goals, priorities, and strategies. CDC analyzed National Vital Statistics System data to provide national and state-specific estimates of potentially preventable deaths among the five leading causes of death in 2014 and compared these estimates with estimates previously published for 2010. Compared with 2010, the estimated number of potentially preventable deaths changed (supplemental material at https://stacks.cdc.gov/view/cdc/42472); cancer deaths decreased 25% (from 84,443 to 63,209), stroke deaths decreased 11% (from 16,973 to 15,175), heart disease deaths decreased 4% (from 91,757 to 87,950), chronic lower respiratory disease (CLRD) (e.g., asthma, bronchitis, and emphysema) deaths increased 1% (from 28,831 to 29,232), and deaths from unintentional injuries increased 23% (from 36,836 to 45,331). A better understanding of progress made in reducing potentially preventable deaths in the United States might inform state and regional efforts targeting the prevention of premature deaths from the five leading causes in the United States.

Although improving health systems promises important benefits, most developing nations lack the resources to support nationally driven clinical research. Strengthened clinical research capacity can advance national health goals by supporting greater autonomy in aligning research with national priorities. From March through June 2010, we assessed six elements of clinical research capacity in Vietnam: research agenda; clinical investigators and biostatisticians; donors and sponsors; community involvement; scientific, ethical, safety, and quality oversight; and clinical research institutions. Assessments were drawn from interviews with investigators, Ministry of Health staff members, nongovernment organizations, and U.S. Mission staff members, and document review. Observations and recommendations were shared with collaborators. Reassessment in 2015 found growth in the number of clinical trials, improved regulation in human subjects protection and community engagement, and modest advances in research agenda setting. Training and investment in institutions remain challenging. A framework for assessing clinical research capacity can affirm strengths and weaknesses and guide the coordination of capacity-building efforts. © 2016, Association of Schools of Public Health. All rights reserved.

The Precision Medicine Initiative1 promises a new healthcare era. A proposed 1 million—person cohort could create a deeper understanding of disease causation. Improvements in quality of sequencing, reduction in price, and advances in “omic” fields and biotechnology promise a new era, variably labeled personalized or precision medicine. Although genomics is one driver of precision health care, other factors may be as important (e.g., health information technology). | Both excitement and skepticism met the announcement. 2 Public health experts are concerned about the disproportionate emphasis on genes, drugs, and disease, while neglecting strategies to address social determinants of health. A prime concern for public health is promoting health, preventing disease, and reducing health disparities by focusing on modifiable morbidity and mortality. In 2014, CDC estimated the annual number of potentially preventable deaths from the top five causes in the U.S.3 Data suggest that at least one third of deaths are potentially preventable by reducing prevalence of known risk factors (e.g., smoking, poor diet, and inadequate physical activity).

Public health surveillance is the cornerstone of public health practice and can be defined as the “… systematic, ongoing collection, management, analysis, and interpretation of data followed by the dissemination of these data to public health programs to stimulate public health action.”1 Stakeholders in the United States at all levels of government (i.e., federal and state, territorial, local, and tribal [STLT]), in academia and industry, and the general public rely on high-quality, timely surveillance data to detect and monitor diseases, injuries, and conditions; assess the impact of interventions; and assist in the management of large-scale disease incidents. Surveillance data are crucially important to inform policy changes, guide new program interventions, sharpen public communications, and help agencies assess research investments. | The public health surveillance enterprise in the U.S. is a long-term partnership that operates through thousands of agencies at the federal and STLT levels. The U.S. Centers for Disease Control and Prevention (CDC) generally does not collect public health surveillance information directly, but relies on state and local health departments and other systems to do so. CDC, however, plays an important collaborative role in aggregating, analyzing, and disseminating surveillance data; creating tools for surveillance; providing technical assistance to states and territories; researching surveillance policy; and funding surveillance activities. In the past few years, observers inside and outside CDC have identified some of the most important influences shaping surveillance in the 21st century (e.g., security concerns, technological advances, and health-care reform) and how these influences may affect the surveillance enterprise. Observers have touched on the need for ongoing evaluation of surveillance systems; standardization, with the goal of developing sustainable and integrated systems; and system and workforce adaptability to current demands. These observers have recognized many challenges that could impede progress, such as funding, workforce, information technology standards, patient confidentiality, and concerns about data access, quality, and sharing.1–3 For example, one fundamental challenge is the tension, both at the federal and STLT levels, between the needs of the whole surveillance enterprise and specific disease control programs, which require specialized surveillance data and are organized and funded along disease-specific lines.

Increasingly, the need to strengthen global capacity to prevent, detect, and respond to public health threats around the globe is being recognized. CDC, in partnership with the World Health Organization (WHO), has committed to building capacity by assisting member states with strengthening their national capacity for integrated disease surveillance and response as required by International Health Regulations (IHR). CDC and other U.S. agencies have reinforced their pledge through creation of global health security (GHS) demonstration projects. One such project was conducted during March-September 2013, when the Uganda Ministry of Health (MoH) and CDC implemented upgrades in three areas: 1) strengthening the public health laboratory system by increasing the capacity of diagnostic and specimen referral networks, 2) enhancing the existing communications and information systems for outbreak response, and 3) developing a public health emergency operations center (EOC) (Figure 1). The GHS demonstration project outcomes included development of an outbreak response module that allowed reporting of suspected cases of illness caused by priority pathogens via short messaging service (SMS; i.e., text messaging) to the Uganda District Health Information System (DHIS-2) and expansion of the biologic specimen transport and laboratory reporting system supported by the President's Emergency Plan for AIDS Relief (PEPFAR). Other enhancements included strengthening laboratory management, establishing and equipping the EOC, and evaluating these enhancements during an outbreak exercise. In 6 months, the project demonstrated that targeted enhancements resulted in substantial improvements to the ability of Uganda's public health system to detect and respond to health threats.

Over the past decade, Vietnam has successfully responded to global health security (GHS) challenges, including domestic elimination of severe acute respiratory syndrome (SARS) and rapid public health responses to human infections with influenza A(H5N1) virus. However, new threats such as Middle East respiratory syndrome coronavirus (MERS-CoV) and influenza A(H7N9) present continued challenges, reinforcing the need to improve the global capacity to prevent, detect, and respond to public health threats. In June 2012, Vietnam, along with many other nations, obtained a 2-year extension for meeting core surveillance and response requirements of the 2005 International Health Regulations (IHR). During March-September 2013, CDC and the Vietnamese Ministry of Health (MoH) collaborated on a GHS demonstration project to improve public health emergency detection and response capacity. The project aimed to demonstrate, in a short period, that enhancements to Vietnam's health system in surveillance and early detection of and response to diseases and outbreaks could contribute to meeting the IHR core capacities, consistent with the Asia Pacific Strategy for Emerging Diseases. Work focused on enhancements to three interrelated priority areas and included achievements in 1) establishing an emergency operations center (EOC) at the General Department of Preventive Medicine with training of personnel for public health emergency management; 2) improving the nationwide laboratory system, including enhanced testing capability for several priority pathogens (i.e., those in Vietnam most likely to contribute to public health emergencies of international concern); and 3) creating an emergency response information systems platform, including a demonstration of real-time reporting capability. Lessons learned included awareness that integrated functions within the health system for GHS require careful planning, stakeholder buy-in, and intradepartmental and interdepartmental coordination and communication.

IN THIS YEAR-IN-REVIEW ARTICLE, we review | 52 of 55 articles published on tuberculosis (TB) in the | International Journal of Tuberculosis and Lung Disease from August through December 2011, complementing the 104 summarized by Chang and Nuermberger,1 and using the same categories (Table 1). We | also summarize 33 of 36 non-TB articles for the entire year (Table 2). | ACTIVE TB | Epidemiology | There was diversity in six epidemiological publications. | Over 8 years, one Madrid hospital showed an overall | incidence of disease of 1.9 cases per 100 person-years | in a retrospective cohort of 1824 human immunodefi ciency virus (HIV) infected patients receiving ART; | 19% had TST-positive results, with an increased risk | of progression to disease (odds ratio [OR] 4.4). Baseline CD4 count was a factor only in patients with tuberculin skin test (TST) negative results, elevating the | risk 16-fold.2 A 2-year Polish hospital-based survey | affi rmed that the current genotyping triage methodology, the combination of 15-loci MIRU-VNTR (mycobacterial interspersed repetitive units-variable number of tandem repeats) typing with spoligotyping for | primary analysis, with insertion sequence 6110-RFLP | (restriction fragment length polymorphism) typing | reserved as a fi nal step, is suffi cient for disaggregating epidemiologically linked clusters.3 A 5-month | nationwide Mongolian survey among new and previously treated sputum smear-positive TB patients demonstrated striking emergence of multidrug-resistant | (MDR) disease among those previously treated: 28% | vs. 1.4% among new cases. MDR-TB among new | cases had risen slightly from 1.0% in 1999, in a survey excluding retreatment cases.4

TO SOME, the title may seem overstated and to others perhaps ironic, from a total lung health perspective. In 1974, following similar policy changes in many | countries, the World Health Organization (WHO) | Committee on Tuberculosis concluded that case fi nding by mass screening using chest radiography should | be abandoned.1 The WHO Committee placed a strong | emphasis on pursuing a diagnosis among symptomatic patients by sputum smear microscopy because | chest radiography could not be used independently | for diagnosis and was too expensive. Even after such | recommendations, and although it was often criticized | over the decades for its insuffi cient specifi city and sensitivity, the use of chest radiography was maintained | in clinical practice, including in many low-resource | country settings, as part of the diagnostic algorithm. | Chest radiography screening has been used for | prevalence surveys, and more recently it has been revived using targeted approaches among high-risk | populations. Its importance is being recognized again, | including in persons infected with the human immunodefi ciency virus and in children with tuberculosis. | As early as 1992, the WHO’s Essential Technologies | group made recommendations that stressed the role | of and access to chest radiographs (and ultrasound) | at the primary referral level.2 With the advent of digital technology, the operational and expense barriers | are declining for radiography as they are with mycobacterial culture, including in low-resource countries. | In 2006, the International Standards for Tuberculosis | Care carefully defi ned the role of chest radiography | in a clinical context,3 and the International Union | Against Tuberculosis and Lung Disease has also been | active in this area.* The use of mobile digital technology, dedicated expertise, and emerging techniques for | computer-aided reading may help address the challenges with observer error and experience

The development, evaluation, and implementation of new and improved diagnostics have been identified as critical needs by human immunodeficiency virus (HIV) and tuberculosis researchers and clinicians alike. These needs exist in international and domestic settings and in adult and pediatric populations. Experts in tuberculosis and HIV care, researchers, healthcare providers, public health experts, and industry representatives, as well as representatives of pertinent US federal agencies (Centers for Disease Control and Prevention, Food and Drug Administration, National Institutes of Health, United States Agency for International Development) assembled at a workshop proposed by the Diagnostics Working Group of the Federal Tuberculosis Taskforce to review the state of tuberculosis diagnostics development in adult and pediatric populations.

We present a statistical summary of results from the Model Performance Evaluation Program (MPEP) for Mycobacterium tuberculosis Drug Susceptibility Testing, 1994-2008 implemented by the U.S. Centers for Disease Control and Prevention (CDC). During that period, a total of 57,733 test results for culture isolates were reported by 216 participating laboratories for the first-line anti-tuberculosis drugs used in the United States- isoniazid (INH), rifampin (RMP), ethambutol (EMB), and pyrazinamide (PZA). Using Clinical Laboratory and Standards Institute (CLSI) recommended concentrations for one or more of three methods, agar proportion (AP), BACTEC460 (BACTEC), and MGIT-960 (MGIT), yielded overall agreement of 97.0% for first-line drugs. For susceptible strains, agreement was 98.4%; for resistant strains, agreement was 91.0%, with significantly lower accuracy (Chi-sq p<0.0001). For resistant strains, overall agreement by methods was: AP 91.3%; BACTEC 93.0%; and MGIT 82.6% and by drugs was: INH 92.2%; RMP 91.5%; EMB 79.0%; and PZA 97.5%. For some strains, performance by method varied significantly. Use of duplicate strains in the same shipment and repeat strains over time, revealed consistent performance even for strains with higher levels of inter-laboratory discordance. No overall differences in performance between laboratories were observed based on volume of testing or type of facility (e.g., health department, hospital, independent). By all methods, decreased performance was observed for strains with low-level INH resistance, RMP resistance, and EMB-resistant strains. These results demonstrate a high level of performance in detection of drug resistant M. tuberculosis in U.S. laboratories.

Patients receiving anti-tumor necrosis factor-oc (anti-TNF-oc) therapy are at increased risk for tuberculosis and other granulomatous diseases, but little is known about illness caused by nontuberculous mycobacteria (NTM) in this setting. We reviewed the US Food and Drug Administration MedWatch database for reports of NTM disease in patients receiving anti-TNF-oc therapy. Of 239 reports collected, 105 (44%) met NTM disease criteria. Median age was 62 years; the majority of patients (66, 65%) were female, and most (73, 70%) had rheumatoid arthritis. NTM infections were associated with infliximab (n = 73), etanercept (n = 25), and adalimumab (n = 7); most patients were taking prednisone (n = 68, 65%) or methotrexate (n = 58, 55%) concurrently. Mycobacteria avium (n = 52, 50%) was most commonly implicated, and 9 patients (9%) had died at the time their infections were reported. A high rate of extrapulmonary manifestations (n = 46, 44%) was also reported.

INTRODUCTION: Delays in the diagnosis of tuberculosis can result in progression to advanced disease. Pulmonary tuberculosis patients with advanced disease are more likely to transmit disease and fail treatment. METHODS: Pulmonary tuberculosis cases in persons >15 years of age reported to the U.S. National Tuberculosis Surveillance System with advanced disease (cavitation on chest radiograph and acid-fast-bacilli smear-positive sputum result) were compared with those without advanced disease using trend and binomial regression analysis. RESULTS: There were 35,584 cases of advanced pulmonary tuberculosis (APT) and 125,077 cases of non-APT reported from 1993 through 2006. Proportions of pulmonary tuberculosis cases with APT increased from 18.5% in 1993 to 26.1% in 2006, and the increase in the proportion of APT was most notable for national tuberculosis rates below 6.6 per 100,000. At the county level, the association between APT and low tuberculosis incidence has grown incrementally stronger since 2000. The proportion of APT increased greatest among whites (65.4%), the employed (63.3%), and the U.S. born (59.2%). The prevalence of APT was 44% greater among persons with multidrug-resistant tuberculosis compared to those without it. CONCLUSION: This study highlights the need for tuberculosis diagnosis at early stages of the disease to minimize APT and decrease the risk of transmission. Additional efforts should concentrate on reducing time to treatment initiation in low-incidence areas and among groups traditionally seen as being at low-risk for tuberculosis disease.