Preventable Premature Deaths from the Five Leading Causes of Death in Nonmetropolitan and Metropolitan Counties, United States, 2010-2022.

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.

Lessons Learned from Programmatic Gains in HIV Service Delivery During the COVID-19 Pandemic - 41 PEPFAR-Supported Countries, 2020.

The U.S. President's Emergency Plan for AIDS Relief (PEPFAR) supports country programs in identifying persons living with HIV infection (PLHIV), providing life-saving treatment, and reducing the spread of HIV in countries around the world (1,2). CDC used Monitoring, Evaluation, and Reporting (MER) data* to assess the extent to which COVID-19 mitigation strategies affected HIV service delivery across the HIV care continuum† globally during the first year of the COVID-19 pandemic. Indicators included the number of reported HIV-positive test results, the number of PLHIV who were receiving antiretroviral therapy (ART), and the rates of HIV viral load suppression. Percent change in performance was assessed between countries during the first 3 months of 2020, before COVID-19 mitigation efforts began (January-March 2020), and the last 3 months of the calendar year (October-December 2020). Data were reviewed for all 41 countries to assess total and country-level percent change for each indicator. Then, qualitative data were reviewed among countries in the upper quartile to assess specific strategies that contributed to programmatic gains. Overall, positive percent change was observed in PEPFAR-supported countries in HIV treatment (5%) and viral load suppression (2%) during 2020. Countries reporting the highest gains across the HIV care continuum during 2020 attributed successes to reducing or streamlining facility attendance through strategies such as enhancing index testing (offering of testing to the biologic children and partners of PLHIV)§ and community- and home-based testing; treatment delivery approaches; and improvements in data use through monitoring activities, systems, and data quality checks. Countries that reported program improvements during the first year of the COVID-19 pandemic offer important information about how lifesaving HIV treatment might be provided during a global public health crisis.

Social vulnerability and county stay-at-home behavior during COVID-19 stay-at-home orders, United States, April 7-April 20, 2020.

PURPOSE: Early COVID-19 mitigation relied on people staying home except for essential trips. The ability to stay home may differ by sociodemographic factors. We analyzed how factors related to social vulnerability impact a community's ability to stay home during a stay-at-home order. METHODS: Using generalized, linear mixed models stratified by stay-at-home order (mandatory or not mandatory), we analyzed county-level stay-at-home behavior (inferred from mobile devices) during a period when a majority of United States counties had stay-at-home orders (April 7-April 20, 2020) with the Centers for Disease Control and Prevention Social Vulnerability Index (CDC SVI). RESULTS: Counties with higher percentages of single-parent households, mobile homes, and persons with lower educational attainment were associated with lower stay-at-home behavior compared with counties with lower respective percentages. Counties with higher unemployment, higher percentages of limited-English-language speakers, and more multi-unit housing were associated with increases in stay-at-home behavior compared with counties with lower respective percentages. Stronger effects were found in counties with mandatory orders. CONCLUSIONS: Sociodemographic factors impact a community's ability to stay home during COVID-19 stay-at-home orders. Communities with higher social vulnerability may have more essential workers without work-from-home options or fewer resources to stay home for extended periods, which may increase risk for COVID-19. Results are useful for tailoring messaging, COVID-19 vaccine delivery, and public health responses to future outbreaks.

Hydroxychloroquine and Chloroquine Prescribing Patterns by Provider Specialty Following Initial Reports of Potential Benefit for COVID-19 Treatment - United States, January-June 2020.

Hydroxychloroquine and chloroquine, primarily used to treat autoimmune diseases and to prevent and treat malaria, received national attention in early March 2020, as potential treatment and prophylaxis for coronavirus disease 2019 (COVID-19) (1). On March 20, the Food and Drug Administration (FDA) issued an emergency use authorization (EUA) for chloroquine phosphate and hydroxychloroquine sulfate in the Strategic National Stockpile to be used by licensed health care providers to treat patients hospitalized with COVID-19 when the providers determine the potential benefit outweighs the potential risk to the patient.* Following reports of cardiac and other adverse events in patients receiving hydroxychloroquine for COVID-19 (2), on April 24, 2020, FDA issued a caution against its use† and on June 15, rescinded its EUA for hydroxychloroquine from the Strategic National Stockpile.§ Following the FDA's issuance of caution and EUA rescindment, on May 12 and June 16, the federal COVID-19 Treatment Guidelines Panel issued recommendations against the use of hydroxychloroquine or chloroquine to treat COVID-19; the panel also noted that at that time no medication could be recommended for COVID-19 pre- or postexposure prophylaxis outside the setting of a clinical trial (3). However, public discussion concerning the effectiveness of these drugs on outcomes of COVID-19 (4,5), and clinical trials of hydroxychloroquine for prophylaxis of COVID-19 continue.¶ In response to recent reports of notable increases in prescriptions for hydroxychloroquine or chloroquine (6), CDC analyzed outpatient retail pharmacy transaction data to identify potential differences in prescriptions dispensed by provider type during January-June 2020 compared with the same period in 2019. Before 2020, primary care providers and specialists who routinely prescribed hydroxychloroquine, such as rheumatologists and dermatologists, accounted for approximately 97% of new prescriptions. New prescriptions by specialists who did not typically prescribe these medications (defined as specialties accounting for ≤2% of new prescriptions before 2020) increased from 1,143 prescriptions in February 2020 to 75,569 in March 2020, an 80-fold increase from March 2019. Although dispensing trends are returning to prepandemic levels, continued adherence to current clinical guidelines for the indicated use of these medications will ensure their availability and benefit to patients for whom their use is indicated (3,4), because current data on treatment and pre- or postexposure prophylaxis for COVID-19 indicate that the potential benefits of these drugs do not appear to outweigh their risks.

Timing of State and Territorial COVID-19 Stay-at-Home Orders and Changes in Population Movement - United States, March 1-May 31, 2020.

SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), is thought to spread from person to person primarily by the respiratory route and mainly through close contact (1). Community mitigation strategies can lower the risk for disease transmission by limiting or preventing person-to-person interactions (2). U.S. states and territories began implementing various community mitigation policies in March 2020. One widely implemented strategy was the issuance of orders requiring persons to stay home, resulting in decreased population movement in some jurisdictions (3). Each state or territory has authority to enact its own laws and policies to protect the public's health, and jurisdictions varied widely in the type and timing of orders issued related to stay-at-home requirements. To identify the broader impact of these stay-at-home orders, using publicly accessible, anonymized location data from mobile devices, CDC and the Georgia Tech Research Institute analyzed changes in population movement relative to stay-at-home orders issued during March 1-May 31, 2020, by all 50 states, the District of Columbia, and five U.S. territories.* During this period, 42 states and territories issued mandatory stay-at-home orders. When counties subject to mandatory state- and territory-issued stay-at-home orders were stratified along rural-urban categories, movement decreased significantly relative to the preorder baseline in all strata. Mandatory stay-at-home orders can help reduce activities associated with the spread of COVID-19, including population movement and close person-to-person contact outside the household.

Potentially Excess Deaths from the Five Leading Causes of Death in Metropolitan and Nonmetropolitan Counties - United States, 2010-2017.

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.

Update: Characteristics of Patients in a National Outbreak of E-cigarette, or Vaping, Product Use-Associated Lung Injuries - United States, October 2019.

CDC, the Food and Drug Administration, state and local health departments, and other public health and clinical stakeholders are investigating a national outbreak of electronic-cigarette (e-cigarette), or vaping, product use-associated lung injury (EVALI) (1). As of October 22, 2019, 49 states, the District of Columbia (DC), and the U.S. Virgin Islands have reported 1,604 cases of EVALI to CDC, including 34 (2.1%) EVALI-associated deaths in 24 states. Based on data collected as of October 15, 2019, this report updates data on patient characteristics and substances used in e-cigarette, or vaping, products (2) and describes characteristics of EVALI-associated deaths. The median age of EVALI patients who survived was 23 years, and the median age of EVALI patients who died was 45 years. Among 867 (54%) EVALI patients with available data on use of specific e-cigarette, or vaping, products in the 3 months preceding symptom onset, 86% reported any use of tetrahydrocannabinol (THC)-containing products, 64% reported any use of nicotine-containing products, and 52% reported use of both. Exclusive use of THC-containing products was reported by 34% of patients and exclusive use of nicotine-containing products by 11%, and for 2% of patients, no use of either THC- or nicotine-containing products was reported. Among 19 EVALI patients who died and for whom substance use data were available, 84% reported any use of THC-containing products, including 63% who reported exclusive use of THC-containing products; 37% reported any use of nicotine-containing products, including 16% who reported exclusive use of nicotine-containing products. To date, no single compound or ingredient used in e-cigarette, or vaping, products has emerged as the cause of EVALI, and there might be more than one cause. Because most patients reported using THC-containing products before symptom onset, CDC recommends that persons should not use e-cigarette, or vaping, products that contain THC. In addition, because the specific compound or ingredient causing lung injury is not yet known, and while the investigation continues, persons should consider refraining from the use of all e-cigarette, or vaping, products.

Opioid Prescribing Rates in Nonmetropolitan and Metropolitan Counties Among Primary Care Providers Using an Electronic Health Record System - United States, 2014-2017.

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† 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.

An Assessment of Information Exchange Practices, Challenges, and Opportunities to Support US Disease Surveillance in 3 States.

BACKGROUND: State and local public health agencies collect and use surveillance data to identify outbreaks, track cases, investigate causes, and implement measures to protect the public's health through various surveillance systems and data exchange practices. PURPOSE: The purpose of this assessment was to better understand current practices at state and local public health agencies for collecting, managing, processing, reporting, and exchanging notifiable disease surveillance information. METHODS: Over an 18-month period (January 2014-June 2015), we evaluated the process of data exchange between surveillance systems, reporting burdens, and challenges within 3 states (California, Idaho, and Massachusetts) that were using 3 different reporting systems. RESULTS: All 3 states use a combination of paper-based and electronic information systems for managing and exchanging data on reportable conditions within the state. The flow of data from local jurisdictions to the state health departments varies considerably. When state and local information systems are not interoperable, manual duplicative data entry and other work-arounds are often required. The results of the assessment show the complexity of disease reporting at the state and local levels and the multiple systems, processes, and resources engaged in preparing, processing, and transmitting data that limit interoperability and decrease efficiency. CONCLUSIONS: Through this structured assessment, the Centers for Disease Control and Prevention (CDC) has a better understanding of the complexities for surveillance of using commercial off-the-shelf data systems (California and Massachusetts), and CDC-developed National Electronic Disease Surveillance System Base System. More efficient data exchange and use of data will help facilitate interoperability between National Notifiable Diseases Surveillance Systems.

Reducing Potentially Excess Deaths from the Five Leading Causes of Death in the Rural United States

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 1999­2014, 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).

Leading Causes of Death in Nonmetropolitan and Metropolitan Areas- United States, 1999-2014.

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.

Potentially Preventable Deaths Among the Five Leading Causes of Death - United States, 2010 and 2014.

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.

Declines in Opioid Prescribing After a Private Insurer Policy Change - Massachusetts, 2011-2015.

Overdose deaths involving opioid pain medications are epidemic in the United States, in part because of high opioid prescribing rates and associated abuse of these drugs (1). In 2014, nearly 2 million U.S. residents either abused or were dependent on prescription opioids (2). In Massachusetts, unintentional opioid-related overdose deaths, including deaths involving heroin, increased 45% from 2012 to 2013.* In 2014, the rate of these deaths reached 20.0 per 100,000, nearly 2.5 times higher than the U.S. rate overall (3,4). On July 1, 2012, Blue Cross Blue Shield of Massachusetts (BCBSMA), the largest insurer in the state with approximately 2.8 million members,† implemented a comprehensive opioid utilization program after learning that many of its members were receiving new prescriptions with a >30-day supply of opioids. The 2016 CDC Guideline for Prescribing Opioids for Chronic Pain recommends avoiding opioids as a first-line therapy for chronic pain and limiting quantities when initiating opioids for acute pain (5). CDC analyzed BCBSMA prescription claims data for the period 2011-2015 to assess the effect of the new utilization program on opioid prescribing rates. During the first 3 years after policy implementation, the average monthly prescribing rate for opioids decreased almost 15%, from 34 per 1,000 members to 29. The percentage of BCBSMA members per month with current opioid prescriptions also declined. The temporal association between implementation of the program and statistically significant declines in both prescribing rates and proportion of members using opioids suggests that the BCBSMA initiative played a role in reducing the use of prescription opioids among its members. Public and private insurers in the United States could benefit from developing their own best practices for prescription opioid utilization that ensure accessible pain care, while reducing the risk for dependence and abuse associated with these drugs.

Patterns and risk factors of inconsistent condom use among men who have sex with men in Viet Nam: Results from an Internet-based cross-sectional survey.

Survey data from men who have sex with men (MSM) in Asian cities indicate drastic increases in HIV prevalence. It is unknown which factors are most important in driving these epidemics. The objective of this study was to identify patterns of condom use among MSM Internet users living in Viet Nam, as well as risk factors associated with inconsistent condom use and non-condom use. A national Internet-based survey of sexual behaviours was administered in 2011. Results showed that 44.9% of MSM reported not using a condom during their last anal sex encounter with a male partner. MSM were less likely to report condom use during anal sex with long-term partners than with casual partners. Twenty-three and a half per cent of MSM surveyed had ever taken an HIV test and received the results. Study findings highlight the urgent need for targeted strategies focused on increasing the rate of consistent condom use during anal sex with male partners among MSM in Viet Nam.

Voluntary medical male circumcision programs can address low HIV testing and counseling usage and ART enrollment among young men: lessons from Lesotho.

BACKGROUND: Early diagnosis of HIV and treatment initiation at higher CD4 counts improves outcomes and reduces transmission. However, Lesotho is not realizing the full benefits of ART because of the low proportion of men tested (40%). Public sector VMMC services, which were launched in district hospitals in February 2012 by the Lesotho MOH supported by USAID/MCHIP, include HIV testing with referral to care and treatment. The objective of this study was to better understand the contribution of VMMC services to HIV diagnosis and treatment. METHODS: VMMC clients diagnosed with HIV were traced after 6 months to ascertain whether they: (1) presented to the referral HIV center, (2) had a CD4 count done and (3) were enrolled on ART. Linkages between VMMC and HIV services were assessed by comparing the proportion of HIV-infected males referred from VMMC services with those from other hospital departments. RESULTS: Between March and September 2012, 72 men presenting for VMMC services tested positive for HIV, representing 65% of the total male tests at the hospital; 45 of these men (62.5%) received an immediate CD4 count and went to the HIV referral site; 40 (89%) were eligible for treatment and initiated ART. 27 clients did not have a CD4 count due to stock-out of reagents. Individuals who did not receive a CD4 count on the same day did not return to the HIV center. CONCLUSION: All VMMC clients testing positive for HIV and receiving a CD4 count on the testing day began ART. Providing VMMC services in a district hospital offering the continuum of care could increase diagnoses and treatment uptake among men, but requires an investment in communication between VMMC and ART clinics. In high HIV prevalence settings, investing in PIMA CD4 devices at integrated VMMC clinics is likely to increase male ART enrolment.

Elevated HIV prevalence and risk behaviours among men who have sex with men (MSM) in Vietnam: a systematic review.

OBJECTIVES: To review and analyse original studies on HIV prevalence and risk behaviours among men who have sex with men (MSM) in Vietnam. DESIGN: Systematic literature review. Comprehensive identification of material was conducted by systematic electronic searches of selected databases. Inclusion criteria included studies conducted from 2002 onwards, following a systematic review concluding in 2001 conducted by Colby, Nghia Huu and Doussantousse. Data analysis was undertaken through the application of both the Cochrane Collaboration and ePPI Centre approaches to the synthesis of qualitative and quantitative studies. SETTING: Vietnam. RESULTS: Sixteen studies, undertaken during 2005-2011, were identified that met the inclusion criteria. The analysis showed that HIV prevalence among MSM in Vietnam has increased significantly (eg, from 9.4% in 2006 to 20% in 2010 in Hanoi) and that protective behaviours, such as condom use and HIV testing and counselling, continue at inadequately low levels. CONCLUSIONS: Increasing HIV prevalence and the lack of effective protective behaviours such as consistent condom use during anal sex among MSM in Vietnam indicate a potential for a more severe HIV epidemic in the future unless targeted and segmented comprehensive HIV prevention strategies for MSM in Vietnam are designed and programmes implemented.