BACKGROUND: Although supervision is a ubiquitous approach to support health programs and improve health care provider (HCP) performance in low- and middle-income countries (LMICs), quantitative evidence of its effects is unclear. The objectives of this study are to describe the effect of supervision strategies on HCP practices in LMICs and to identify attributes associated with greater effectiveness of routine supervision. METHODS: We performed a secondary analysis of data on HCP practice outcomes (e.g., percentage of patients correctly treated) from a systematic review on improving HCP performance. The review included controlled trials and interrupted time series studies. We described distributions of effect sizes (defined as percentage-point [%-point] changes) for each supervision strategy. To identify attributes associated with supervision effectiveness, we performed random-effects linear regression modeling and examined studies that directly compared different approaches of routine supervision. RESULTS: We analyzed data from 81 studies from 36 countries. For professional HCPs, such as nurses and physicians, primarily working at health facilities, routine supervision (median improvement when compared to controls: 10.7%-points; IQR: 9.9, 27.9) had similar effects on HCP practices as audit with feedback (median improvement: 10.1%-points; IQR: 6.2, 23.7). Two attributes were associated with greater mean effectiveness of routine supervision (p < 0.10): supervisors received supervision (by 8.8-11.5%-points), and supervisors participated in problem-solving with HCPs (by 14.2-20.8%-points). Training for supervisors and use of a checklist during supervision visits were not associated with effectiveness. The effects of supervision frequency (i.e., number of visits per year) and dose (i.e., the number of supervision visits during a study) were unclear. For lay HCPs, the effect of routine supervision was difficult to characterize because few studies existed, and effectiveness in those studies varied considerably. Evidence quality for all findings was low primarily because many studies had a high risk of bias. CONCLUSIONS: Although evidence is limited, to promote more effective supervision, our study supports supervising supervisors and having supervisors engage in problem-solving with HCPs. Supervision's integral role in health systems in LMICs justifies a more deliberate research agenda to identify how to deliver supervision to optimize its effect on HCP practices.

OBJECTIVE: The purpose of this study was to report the "Outcome Reporting in Brief Intervention Trials: Alcohol" (ORBITAL) recommended core outcome set (COS) to improve efficacy and effectiveness trials/evaluations for alcohol brief interventions (ABIs). METHOD: A systematic review identified 2,641 outcomes in 401 ABI articles measured by 1,560 different approaches. These outcomes were classified into outcome categories, and 150 participants from 19 countries participated in a two-round e-Delphi outcome prioritization exercise. This process prioritized 15 of 93 outcome categories for discussion at a consensus meeting of key stakeholders to decide the COS. A psychometric evaluation determined how to measure the outcomes. RESULTS: Ten outcomes were voted into the COS at the consensus meeting: (a) typical frequency, (b) typical quantity, (c) frequency of heavy episodic drinking, (d) combined consumption measure summarizing alcohol use, (e) hazardous or harmful drinking (average consumption), (f) standard drinks consumed in the past week (recent, current consumption), (g) alcohol-related consequences, (h) alcohol-related injury, (i) use of emergency health care services (impact of alcohol use), and (j) quality of life. CONCLUSIONS: The ORBITAL COS is an international consensus standard for future ABI trials and evaluations. It can improve the synthesis of new findings, reduce redundant/selective reporting (i.e., reporting only some, usually significant outcomes), improve between-study comparisons, and enhance the relevance of trial and evaluation findings to decision makers. The COS is the recommended minimum and does not exclude other, additional outcomes.

Middle East respiratory syndrome-related coronavirus (MERS-CoV) is a persistent zoonotic pathogen with frequent spillover from dromedary camels to humans in the Arabian Peninsula, resulting in limited outbreaks of MERS with a high case-fatality rate. Full genome sequence data from camel-derived MERS-CoV variants show diverse lineages circulating in domestic camels with frequent recombination. More than 90% of the available full MERS-CoV genome sequences derived from camels are from just two countries, the Kingdom of Saudi Arabia (KSA) and United Arab Emirates (UAE). In this study, we employ a novel method to amplify and sequence the partial MERS-CoV genome with high sensitivity from nasal swabs of infected camels. We recovered more than 99% of the MERS-CoV genome from field-collected samples with greater than 500 TCID(50) equivalent per nasal swab from camel herds sampled in Jordan in May 2016. Our subsequent analyses of 14 camel-derived MERS-CoV genomes show a striking lack of genetic diversity circulating in Jordan camels relative to MERS-CoV genome sequences derived from large camel markets in KSA and UAE. The low genetic diversity detected in Jordan camels during our study is consistent with a lack of endemic circulation in these camel herds and reflective of data from MERS outbreaks in humans dominated by nosocomial transmission following a single introduction as reported during the 2015 MERS outbreak in South Korea. Our data suggest transmission of MERS-CoV among two camel herds in Jordan in 2016 following a single introduction event.

INTRODUCTION: In low/middle-income countries (LMICs), training is often used to improve healthcare provider (HCP) performance. However, important questions remain about how well training works and the best ways to design training strategies. The objective of this study is to characterise the effectiveness of training strategies to improve HCP practices in LMICs and identify attributes associated with training effectiveness. METHODS: We performed a secondary analysis of data from a systematic review on improving HCP performance. The review included controlled trials and interrupted time series, and outcomes measuring HCP practices (eg, percentage of patients correctly treated). Distributions of effect sizes (defined as percentage-point (%-point) changes) were described for each training strategy. To identify effective training attributes, we examined studies that directly compared training approaches and performed random-effects linear regression modelling. RESULTS: We analysed data from 199 studies from 51 countries. For outcomes expressed as percentages, educational outreach visits (median effect size when compared with controls: 9.9 %-points; IQR: 4.3-20.6) tended to be somewhat more effective than in-service training (median: 7.3 %-points; IQR: 3.6-17.4), which seemed more effective than peer-to-peer training (4.0 %-points) and self-study (by 2.0-9.3 %-points). Mean effectiveness was greater (by 6.0-10.4 %-points) for training that incorporated clinical practice and training at HCPs' work site. Attributes with little or no effect were: training with computers, interactive methods or over multiple sessions; training duration; number of educational methods; distance training; trainers with pedagogical training and topic complexity. For lay HCPs, in-service training had no measurable effect. Evidence quality for all findings was low. CONCLUSIONS: Although additional research is needed, by characterising the effectiveness of training strategies and identifying attributes of effective training, decision-makers in LMICs can improve how these strategies are selected and implemented.

Fine particulate matter (PM2.5) is a well-established risk factor for public health. To support both health risk assessment and epidemiological studies, data are needed on spatial and temporal patterns of PM2.5 exposures. This review article surveys publicly available exposure datasets for surface PM2.5 mass concentrations over the contiguous U.S., summarizes their applications and limitations, and provides suggestions on future research needs. The complex landscape of satellite instruments, model capabilities, monitor networks, and data synthesis methods offers opportunities for research development, but would benefit from guidance for new users. Guidance is provided to access publicly available PM2.5 datasets, to explain and compare different approaches for dataset generation, and to identify sources of uncertainties associated with various types of datasets. Three main sources used to create PM2.5 exposure data are: ground-based measurements (especially regulatory monitoring), satellite retrievals (especially aerosol optical depth, AOD), and atmospheric chemistry models. We find inconsistencies among several publicly available PM2.5 estimates, highlighting uncertainties in the exposure datasets that are often overlooked in health effects analyses. Major differences among PM2.5 estimates emerge from the choice of data (ground-based, satellite, and/or model), the spatiotemporal resolutions, and the algorithms used to fuse data sources.

BACKGROUND: Health care provider (HCP) performance in low- and middle-income countries (LMICs) is often inadequate. The Health Care Provider Performance Review (HCPPR) is a comprehensive systematic review of the effectiveness and cost of strategies to improve HCP performance in LMICs. We present the HCPPR's methods, describe methodological and contextual attributes of included studies, and examine time trends of study attributes. METHODS: The HCPPR includes studies from LMICs that quantitatively evaluated any strategy to improve HCP performance for any health condition, with no language restrictions. Eligible study designs were controlled trials and interrupted time series. In 2006, we searched 15 databases for published studies; in 2008 and 2010, we completed searches of 30 document inventories for unpublished studies. Data from eligible reports were double-abstracted and entered into a database, which is publicly available. The primary outcome measure was the strategy's effect size. We assessed time trends with logistic, Poisson, and negative binomial regression modeling. We were unable to register with PROSPERO (International Prospective Register of Systematic Reviews) because the protocol was developed prior to the PROSPERO launch. RESULTS: We screened 105,299 citations and included 824 reports from 499 studies of 161 intervention strategies. Most strategies had multiple components and were tested by only one study each. Studies were from 79 countries and had diverse methodologies, geographic settings, HCP types, work environments, and health conditions. Training, supervision, and patient and community supports were the most commonly evaluated strategy components. Only 33.6% of studies had a low or moderate risk of bias. From 1958-2003, the number of studies per year and study quality increased significantly over time, as did the proportion of studies from low-income countries. Only 36.3% of studies reported information on strategy cost or cost-effectiveness. CONCLUSIONS: Studies have reported on the efficacy of many strategies to improve HCP performance in LMICs. However, most studies have important methodological limitations. The HCPPR is a publicly accessible resource for decision-makers, researchers, and others interested in improving HCP performance.

BACKGROUND: Inadequate health-care provider performance is a major challenge to the delivery of high-quality health care in low-income and middle-income countries (LMICs). The Health Care Provider Performance Review (HCPPR) is a comprehensive systematic review of strategies to improve health-care provider performance in LMICs. METHODS: For this systematic review we searched 52 electronic databases for published studies and 58 document inventories for unpublished studies from the 1960s to 2016. Eligible study designs were controlled trials and interrupted time series. We only included strategy-versus-control group comparisons. We present results of improving health-care provider practice outcomes expressed as percentages (eg, percentage of patients treated correctly) or as continuous measures (eg, number of medicines prescribed per patient). Effect sizes were calculated as absolute percentage-point changes. The summary measure for each comparison was the median effect size (MES) for all primary outcomes. Strategy effectiveness was described with weighted medians of MES. This study is registered with PROSPERO, number CRD42016046154. FINDINGS: We screened 216 477 citations and selected 670 reports from 337 studies of 118 strategies. Most strategies had multiple intervention components. For professional health-care providers (generally, facility-based health workers), the effects were near zero for only implementing a technology-based strategy (median MES 1.0 percentage points, IQR -2.8 to 9.9) or only providing printed information for health-care providers (1.4 percentage points, -4.8 to 6.2). For percentage outcomes, training or supervision alone typically had moderate effects (10.3-15.9 percentage points), whereas combining training and supervision had somewhat larger effects than use of either strategy alone (18.0-18.8 percentage points). Group problem solving alone showed large improvements in percentage outcomes (28.0-37.5 percentage points), but, when the strategy definition was broadened to include group problem solving alone or other strategy components, moderate effects were more typical (12.1 percentage points). Several multifaceted strategies had large effects, but multifaceted strategies were not always more effective than simpler ones. For lay health-care providers (generally, community health workers), the effect of training alone was small (2.4 percentage points). Strategies with larger effect sizes included community support plus health-care provider training (8.2-125.0 percentage points). Contextual and methodological heterogeneity made comparisons difficult, and most strategies had low quality evidence. INTERPRETATION: The impact of strategies to improve health-care provider practices varied substantially, although some approaches were more consistently effective than others. The breadth of the HCPPR makes its results valuable to decision makers for informing the selection of strategies to improve health-care provider practices in LMICs. These results also emphasise the need for researchers to use better methods to study the effectiveness of interventions. FUNDING: Bill & Melinda Gates Foundation, CDC Foundation.

Commercial chikungunya virus (CHIKV)-specific IgM detection kits were evaluated at the Centers for Disease Control and Prevention (CDC), the Public Health Agency of Canada National Microbiology Laboratory, and the Caribbean Public Health Agency (CARPHA). The Euroimmun Anti-CHIKV IgM ELISA kit had ≥ 95% concordance with all three reference laboratory results. The limit of detection for low CHIK IgM+ samples, as measured by serial dilution of seven sera up to 1:12,800 ranged from 1:800 to 1:3,200. The Euroimmun IIFT kit evaluated at CDC and CARPHA performed well, but required more retesting of equivocal results. The InBios CHIKjj Detect MAC-ELISA had 100% and 98% concordance with CDC and CARPHA results, respectively, and had equal sensitivity to the CDC MAC-ELISA to 1:12,800 dilution in serially diluted samples. The Abcam Anti-CHIKV IgM ELISA initially had high performance at CDC and CARPHA, but at CDC, performance was inconsistent between lots. After replacement of the biotinylated IgM antibody controls with serum containing CHIKV-specific IgM and additional quality assurance/control measures, the Abcam kit was rereleased and reevaluated at CDC. The reformatted Abcam kit had 97% concordance with CDC results and limit of detection of 1:800 to 1:3,200. Two rapid tests and three other CHIKV MAC-ELISAs evaluated at CDC had low sensitivity, as the CDC CHIKV IgM in-house positive controls were below the level of detection. In conclusion, laboratories have options for CHIKV serological diagnosis using validated commercial kits.

The complexities of planning for and responding to the emergence of novel influenza viruses emphasize the need for systematic frameworks to describe the progression of the event; weigh the risk of emergence and potential public health impact; evaluate transmissibility, antiviral resistance, and severity; and make decisions about interventions. On the basis of experience from recent influenza responses, CDC has updated its framework to describe influenza pandemic progression using six intervals (two prepandemic and four pandemic intervals) and eight domains. This updated framework can be used for influenza pandemic planning and serves as recommendations for risk assessment, decision-making, and action in the United States. The updated framework replaces the U.S. federal government stages from the 2006 implementation plan for the National Strategy for Pandemic Influenza (US Homeland Security Council. National strategy for pandemic influenza: implementation plan. Washington, DC: US Homeland Security Council; 2006. Available at http://www.flu.gov/planning-preparedness/federal/pandemic-influenza-implementatio n.pdf). The six intervals of the updated framework are as follows: 1) investigation of cases of novel influenza, 2) recognition of increased potential for ongoing transmission, 3) initiation of a pandemic wave, 4) acceleration of a pandemic wave, 5) deceleration of a pandemic wave, and 6) preparation for future pandemic waves. The following eight domains are used to organize response efforts within each interval: incident management, surveillance and epidemiology, laboratory, community mitigation, medical care and countermeasures, vaccine, risk communications, and state/local coordination. Compared with the previous U.S. government stages, this updated framework provides greater detail and clarity regarding the potential timing of key decisions and actions aimed at slowing the spread and mitigating the impact of an emerging pandemic. Use of this updated framework is anticipated to improve pandemic preparedness and response in the United States. Activities and decisions during a response are event-specific. These intervals serve as a reference for public health decision-making by federal, state, and local health authorities in the United States during an influenza pandemic and are not meant to be prescriptive or comprehensive. This framework incorporates information from newly developed tools for pandemic planning and response, including the Influenza Risk Assessment Tool and the Pandemic Severity Assessment Framework, and has been aligned with the pandemic phases restructured in 2013 by the World Health Organization.

BACKGROUND: The United States has experienced two shortages of heptavalent pneumococcal conjugate vaccine (PCV7). National guidelines called for deferring the third and fourth PCV7 doses from healthy children during these shortages. However, recommendations were not the same during the first and second shortages, and recommendations changed over time during each of the shortages as shortages worsened. OBJECTIVES: To measure PCV7 immunizing behavior for healthy children during shortage and non-shortage periods and assess the accuracy of the physicians' reported immunizing behavior when compared to their actual immunizing behavior. METHODS: We reviewed medical records in 14 randomly selected practices to measure actual immunizing behavior during shortage and non-shortage periods. We surveyed pediatricians in the Greater Cincinnati area to ascertain reported immunizing behavior. Actual and reported immunizing behaviors were compared. RESULTS: 2888 medical records were reviewed; surveys were obtained from 51 pediatricians (65% response rate). During periods of non-shortage, 74% of healthy children received their first two doses of PCV7 on time, whereas during periods of shortage, only 66% of healthy children received their first two doses of PCV7 on time. Compared with measured immunizing behavior from chart reviews, 54-76% of the pediatricians overestimated their compliance with guidelines to defer the fourth PCV7 dose while only 5-20% underestimated their compliance. CONCLUSIONS: Physicians often overestimated the percentage of children whose vaccine doses they deferred during vaccine shortages. Despite these findings, physicians were able to maintain high coverage with the first two PCV7 doses among healthy children.

Gene-lifestyle interactions have been suggested to contribute to the development of type 2 diabetes. Glucose levels 2 h after a standard 75-g glucose challenge are used to diagnose diabetes and are associated with both genetic and lifestyle factors. However, whether these factors interact to determine 2-h glucose levels is unknown. We meta-analyzed single nucleotide polymorphism (SNP) x BMI and SNP x physical activity (PA) interaction regression models for five SNPs previously associated with 2-h glucose levels from up to 22 studies comprising 54,884 individuals without diabetes. PA levels were dichotomized, with individuals below the first quintile classified as inactive (20%) and the remainder as active (80%). BMI was considered a continuous trait. Inactive individuals had higher 2-h glucose levels than active individuals (beta = 0.22 mmol/L [95% CI 0.13-0.31], P = 1.63 x 10(-6)). All SNPs were associated with 2-h glucose (beta = 0.06-0.12 mmol/allele, P ≤ 1.53 x 10(-7)), but no significant interactions were found with PA (P > 0.18) or BMI (P ≥ 0.04). In this large study of gene-lifestyle interaction, we observed no interactions between genetic and lifestyle factors, both of which were associated with 2-h glucose. It is perhaps unlikely that top loci from genome-wide association studies will exhibit strong subgroup-specific effects, and may not, therefore, make the best candidates for the study of interactions.

OBJECTIVE: Implementation of the Integrated Management of Childhood Illness (IMCI) strategy with an 11-day training course for health workers improves care for ill children in outpatient settings in developing countries. The 11-day course duration is recommended by the World Health Organization, which developed IMCI. Our aim was to determine if shortening the training (to reduce cost) reduces its effectiveness. METHODS: We conducted a systematic review to compare IMCI's effectiveness with standard training (duration ≥11 days) versus shortened training (5-10 days). Studies were identified from a search of MEDLINE, two existing systematic reviews, and by contacting investigators. We included published or unpublished studies that evaluated IMCI's effectiveness in developing countries and reported quantitative measures of health worker practices related to managing ill children under 5 years old in public or private health facilities. Summary measures were the median of effect sizes for all outcomes from a given study, and the percentage of patients needing oral antimicrobials or rehydration who were treated according to IMCI guidelines. FINDINGS: Twenty-nine studies were included. Direct comparisons from three studies showed little difference between standard and shortened training. Indirect comparisons from 26 studies revealed that effect sizes for standard training versus no IMCI were greater than shortened training versus no IMCI. Across all comparisons, differences ranged from -3 to +23 percentage-points, and our best estimate was a 2 to 16 percentage-point advantage for standard training. No result was statistically significant. After IMCI training (of any duration), 34% of ill children needing oral antimicrobials or rehydration were not receiving these treatments according to IMCI guidelines. CONCLUSIONS: Based on limited evidence, standard IMCI training seemed more effective than shortened training, although the difference might be small. As sizable performance gaps often existed after IMCI training, countries should consider implementing other interventions to support health workers after training, regardless of training duration.

A framework based on five major theories of health behavior was used to identify the correlates of adolescent cigarette smoking. The framework emphasizes intentions to smoke cigarettes, factors that influence these intentions, and factors that moderate the intention-behavior relationship. Five hundred sixteen randomly selected Latino middle school youth in New York completed self-administered questionnaires. Adolescents reported their intentions to smoke, smoking-related expectancies, normative pressures to smoke, image implications of smoking, emotional reactions to smoking, and self-efficacy with respect to smoking. The framework yielded high levels of association with intentions to smoke. Specific smoking-related emotions, norms, and expectancies were associated with the likelihood of smoking. The framework can help guide the development of effective interventions tailored to specific populations. (PsycINFO Database Record (c) 2011 APA, all rights reserved) (journal abstract).