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We aim to determine whether a game-theoretic model between an insurer and a healthcare practice yields a predictive equilibrium that incentivizes either player to deviate from a fee-for-service to capitation payment system. Using United States data from various primary care surveys, we find that non-extreme equilibria (i.e., shares of patients, or shares of patient visits, seen under a fee-for-service payment system) can be derived from a Stackelberg game if insurers award a non-linear bonus to practices based on performance. Overall, both insurers and practices can be incentivized to embrace capitation payments somewhat, but potentially at the expense of practice performance. [ABSTRACT FROM AUTHOR]

Objective: The Centers for Disease Control and Prevention (CDC) coordinates a labor-intensive process to measure the prevalence of autism spectrum disorder (ASD) among children in the United States. Random forests methods have shown promise in speeding up this process, but they lag behind human classification accuracy by about 5%. We explore whether more recently available document classification algorithms can close this gap. Materials and methods: Using data gathered from a single surveillance site, we applied 8 supervised learning algorithms to predict whether children meet the case definition for ASD based solely on the words in their evaluations. We compared the algorithms’ performance across 10 random train-test splits of the data, using classification accuracy, F1 score, and number of positive calls to evaluate their potential use for surveillance. Results: Across the 10 train-test cycles, the random forest and support vector machine with Naive Bayes features (NB-SVM) each achieved slightly more than 87% mean accuracy. The NB-SVM produced significantly more false negatives than false positives (P = 0.027), but the random forest did not, making its prevalence estimates very close to the true prevalence in the data. The best-performing neural network performed similarly to the random forest on both measures. Discussion: The random forest performed as well as more recently available models like the NB-SVM and the neural network, and it also produced good prevalence estimates. NB-SVM may not be a good candidate for use in a fully-automated surveillance workflow due to increased false negatives. More sophisticated algorithms, like hierarchical convolutional neural networks, may not be feasible to train due to characteristics of the data. Current algorithms might perform better if the data are abstracted and processed differently and if they take into account information about the children in addition to their evaluations. Conclusion: Deep learning models performed similarly to traditional machine learning methods at predicting the clinician-assigned case status for CDC’s autism surveillance system. While deep learning methods had limited benefit in this task, they may have applications in other surveillance systems. [ABSTRACT FROM AUTHOR]

Prophylactic interventions such as vaccine allocation are some of the most effective public health policy planning tools. The supply of vaccines, however, is limited and an important challenge is to optimally allocate the vaccines to minimize epidemic impact. This resource allocation question (which we refer to as VID) has multiple dimensions: when, where, to whom, etc. Most of the existing literature in this topic deals with the latter (to whom), proposing policies that prioritize individuals by age and disease risk. However, since seasonal influenza spread has a typical spatial trend, and due to the temporal constraints enforced by the availability schedule, the when and where problems become equally, if not more, relevant. In this paper, we study the VID problem in the context of seasonal influenza spread in the United States. We develop a national scale metapopulation model for influenza that integrates both short and long distance human mobility, along with realistic data on vaccine uptake. We also design GA, a greedy algorithm for allocating the vaccine supply at the state level under temporal constraints and show that such a strategy improves over the current baseline of pro-rata allocation, and the improvement is more pronounced for higher vaccine efficacy and moderate flu season intensity. Further, the resulting strategy resembles a ring vaccination applied spatiallyacross the US. [ABSTRACT FROM AUTHOR]

Introduction: Reproducible research is increasingly gaining interest in the research community. Automating the production of research manuscript tables from statistical software can help increase the reproducibility of findings. Logistic regression is used in studying disease prevalence and associated factors in epidemiological studies and can be easily performed using widely available software including SAS, SUDAAN, Stata or R. However, output from these software must be processed further to make it readily presentable. There exists a number of procedures developed to organize regression output, though many of them suffer limitations of flexibility, complexity, lack of validation checks for input parameters, as well as inability to incorporate survey design. Methods: We developed a SAS macro, %svy_logistic_regression, for fitting simple and multiple logistic regression models. The macro also creates quality publication-ready tables using survey or non-survey data which aims to increase transparency of data analyses. It further significantly reduces turn-around time for conducting analysis and preparing output tables while also addressing the limitations of existing procedures. In addition, the macro allows for user-specific actions to handle missing data as well as use of replication-based variance estimation methods. Results: We demonstrate the use of the macro in the analysis of the 2013–2014 National Health and Nutrition Examination Survey (NHANES), a complex survey designed to assess the health and nutritional status of adults and children in the United States. The output presented here is directly from the macro and is consistent with how regression results are often presented in the epidemiological and biomedical literature, with unadjusted and adjusted model results presented side by side. Conclusions: The SAS code presented in this macro is comprehensive, easy to follow, manipulate and to extend to other areas of interest. It can also be incorporated quickly by the statistician for immediate use. It is an especially valuable tool for generating quality, easy to review tables which can be incorporated directly in a publication. [ABSTRACT FROM AUTHOR]

In the United States, breast cancer is one of the most common and the second leading cause of cancer-related death in women. Treatment modalities for mammary tumor are surgical removal of the tumor tissue followed by either chemotherapy or radiotherapy or both. Radiation therapy is a whole body irradiation regimen that suppresses the immune system leaving hosts susceptible to infection or secondary tumors. Boron neutron capture therapy (BNCT) in that regard is more selective, the cells that are mostly affected are those that are loaded with 109 or more 10B atoms. Previously, we have described that liposomal encapsulation of boron-rich compounds such as TAC and MAC deliver a high payload to the tumor tissue when injected intravenously. Here we report that liposome-mediated boron delivery to the tumor is inversely proportional to the size of the murine mammary (EMT-6) tumors. The plausible reason for the inverse ratio of boron and EMT-6 tumor size is the necrosis in these tumors, which is more prominent in the large tumors. The large tumors also have receding blood vessels contributing further to poor boron delivery to these tumors. We next report that the presence of boron in blood is essential for the effects of BNCT on EMT-6 tumor inhibition as direct injection of boron-rich liposomes did not provide any added advantage in inhibition of EMT-6 tumor in BALB/c mice following irradiation despite having a significantly higher amount of boron in the tumor tissue. BNCT reaction in PBMCs resulted in the modification of these cells to anti-tumor phenotype. In this study, we report the immunomodulatory effects of BNCT when boron-rich compounds are delivered systemically. [ABSTRACT FROM AUTHOR]

The prevalence of electronic cigarette (e-cigarette) use has rapidly increased among young people, while conventional cigarette use has decreased in this age group. However, some evidence suggests that e-cigarette use is likely to induce conventional cigarette smoking. The present study explored the social influence of the prevalence of e-cigarette use in the peer network and in the general population as a potential mechanism by which e-cigarette use affects adolescents’ overall smoking behaviours. For this purpose, we developed an agent-based model in which young agents repeatedly choose to smoke conventional cigarettes and/or e-cigarettes, or to remain non-smokers. The choice is based on the agent’s evaluation of the utility derived from smoking and attitude towards smoking (‘openness’), which is influenced by smoking prevalence in the agent’s peer network and in the broader society. We also assumed a ‘crossover’ effect between the different types of smoking. The model was calibrated with United States National Youth Tobacco Survey data to reflect real-world numbers. We further simulated the prevalence of different types of smoking under counterfactual scenarios with different levels of openness and crossover effects. The models developed successfully reproduced actual prevalence trends in different types of smoking from 2011 to 2014. Openness to smoking is associated with a dramatic increase in e-cigarette smoking and especially in dual smoking, which cancels out the decline in sole conventional smoking. Larger crossover effects are associated with a higher prevalence of conventional smoking. The simulation results indicate that the social influence of the prevalence of e-cigarette use may influence young people to initiate or continue conventional cigarette smoking. Assessing the impact of e-cigarettes in the general population as a ‘healthier’ alternative to conventional smoking may require carefully monitoring trends in young people’s smoking behaviours. [ABSTRACT FROM AUTHOR]

A causal association of air pollution with mental diseases is an intriguing possibility raised in a Short Report just published in PLOS Biology. Despite analyses involving large data sets, the available evidence has substantial shortcomings, and a long series of potential biases may invalidate the observed associations. Only bipolar disorder shows consistent results, with similar effects across United States and Denmark data sets, but the effect has modest magnitude, appropriate temporality is not fully secured, and biological gradient, plausibility, coherence, and analogy offer weak support. The signal seems to persist in some robustness analyses, but more analyses by multiple investigators, including contrarians, are necessary. Broader public sharing of data sets would also enhance transparency. [ABSTRACT FROM AUTHOR]

Estimation of influenza-like illness (ILI) using search trends activity was intended to supplement traditional surveillance systems, and was a motivation behind the development of Google Flu Trends (GFT). However, several studies have previously reported large errors in GFT estimates of ILI in the US. Following recent release of time-stamped surveillance data, which better reflects real-time operational scenarios, we reanalyzed GFT errors. Using three data sources—GFT: an archive of weekly ILI estimates from Google Flu Trends; ILIf: fully-observed ILI rates from ILINet; and, ILIp: ILI rates available in real-time based on partial reporting—five influenza seasons were analyzed and mean square errors (MSE) of GFT and ILIp as estimates of ILIf were computed. To correct GFT errors, a random forest regression model was built with ILI and GFT rates from the previous three weeks as predictors. An overall reduction in error of 44% was observed and the errors of the corrected GFT are lower than those of ILIp. An 80% reduction in error during 2012/13, when GFT had large errors, shows that extreme failures of GFT could have been avoided. Using autoregressive integrated moving average (ARIMA) models, one- to four-week ahead forecasts were generated with two separate data streams: ILIp alone, and with both ILIp and corrected GFT. At all forecast targets and seasons, and for all but two regions, inclusion of GFT lowered MSE. Results from two alternative error measures, mean absolute error and mean absolute proportional error, were largely consistent with results from MSE. Taken together these findings provide an error profile of GFT in the US, establish strong evidence for the adoption of search trends based 'nowcasts' in influenza forecast systems, and encourage reevaluation of the utility of this data source in diverse domains. [ABSTRACT FROM AUTHOR]

The Medical Monitoring Project (MMP) is an HIV surveillance system that provides national estimates of HIV-related behaviors and clinical outcomes. When first implemented, MMP excluded persons living with HIV not receiving HIV care. This analysis will describe new case-surveillance-based methods to identify and recruit persons living with HIV who are out of care and at elevated risk for mortality and ongoing HIV transmission. Stratified random samples of all persons living with HIV were selected from the National HIV Surveillance System in five public health jurisdictions from 2012–2014. Sampled persons were located and contacted through seven different data sources and five methods of contact to collect interviews and medical record abstractions. Data were weighted for non-response and case reporting delay. The modified sampling methodology yielded 1159 interviews (adjusted response rate, 44.5%) and matching medical record abstractions for 1087 (93.8%). Of persons with both interview and medical record data, 264 (24.3%) would not have been included using prior MMP methods. Significant predictors were identified for successful contact (e.g., retention in care, adjusted Odds Ratio [aOR] 5.02; 95% Confidence Interval [CI] 1.98–12.73), interview (e.g. moving out of jurisdiction, aOR 0.24; 95% CI: 0.12–0.46) and case reporting delay (e.g. rural residence, aOR 3.18; 95% CI: 2.09–4.85). Case-surveillance-based sampling resulted in a comparable response rate to existing MMP methods while providing information on an important new population. These methods have since been adopted by the nationally representative MMP surveillance system, offering a model for public health program, research and surveillance endeavors seeking inclusion of all persons living with HIV. [ABSTRACT FROM AUTHOR]

Background: Exposure to fine particulate matter pollution (PM2.5) is hazardous to health. Our aim was to directly estimate the health and longevity impacts of current PM2.5 concentrations and the benefits of reductions from 1999 to 2015, nationally and at county level, for the entire contemporary population of the contiguous United States.Methods and Findings: We used vital registration and population data with information on sex, age, cause of death, and county of residence. We used four Bayesian spatiotemporal models, with different adjustments for other determinants of mortality, to directly estimate mortality and life expectancy loss due to current PM2.5 pollution and the benefits of reductions since 1999, nationally and by county. The covariates included in the adjusted models were per capita income; percentage of population whose family income is below the poverty threshold, who are of Black or African American race, who have graduated from high school, who live in urban areas, and who are unemployed; cumulative smoking; and mean temperature and relative humidity. In the main model, which adjusted for these covariates and for unobserved county characteristics through the use of county-specific random intercepts, PM2.5 pollution in excess of the lowest observed concentration (2.8 μg/m3) was responsible for an estimated 15,612 deaths (95% credible interval 13,248-17,945) in females and 14,757 deaths (12,617-16,919) in males. These deaths would lower national life expectancy by an estimated 0.15 years (0.13-0.17) for women and 0.13 years (0.11-0.15) for men. The life expectancy loss due to PM2.5 was largest around Los Angeles and in some southern states such as Arkansas, Oklahoma, and Alabama. At any PM2.5 concentration, life expectancy loss was, on average, larger in counties with lower income and higher poverty rate than in wealthier counties. Reductions in PM2.5 since 1999 have lowered mortality in all but 14 counties where PM2.5 increased slightly. The main limitation of our study, similar to other observational studies, is that it is not guaranteed for the observed associations to be causal. We did not have annual county-level data on other important determinants of mortality, such as healthcare access and quality and diet, but these factors were adjusted for with use of county-specific random intercepts.Conclusions: According to our estimates, recent reductions in particulate matter pollution in the USA have resulted in public health benefits. Nonetheless, we estimate that current concentrations are associated with mortality impacts and loss of life expectancy, with larger impacts in counties with lower income and higher poverty rate. [ABSTRACT FROM AUTHOR]

Conotruncal heart defects (CTDs) are among the most common and severe groups of congenital heart defects. Despite evidence of an inherited genetic contribution to CTDs, little is known about the specific genes that contribute to the development of CTDs. We performed gene-based genome-wide analyses using microarray-genotyped and imputed common and rare variants data from two large studies of CTDs in the United States. We performed two case-parent trio analyses (N = 640 and 317 trios), using an extension of the family-based multi-marker association test, and two case-control analyses (N = 482 and 406 patients and comparable numbers of controls), using a sequence kernel association test. We also undertook two meta-analyses to combine the results from the analyses that used the same approach (i.e. family-based or case-control). To our knowledge, these analyses are the first reported gene-based, genome-wide association studies of CTDs. Based on our findings, we propose eight CTD candidate genes (ARF5, EIF4E, KPNA1, MAP4K3, MBNL1, NCAPG, NDFUS1 and PSMG3). Four of these genes (ARF5, KPNA1, NDUFS1 and PSMG3) have not been previously associated with normal or abnormal heart development. In addition, our analyses provide additional evidence that genes involved in chromatin-modification and in ribonucleic acid splicing are associated with congenital heart defects. [ABSTRACT FROM AUTHOR]

Prostate cancer was the most common form and had the second highest death rate of male cancer in the United States in 2015. Current diagnosis techniques, such as prostate-specific antigen tests, transrectal ultrasound scans, and biopsies, are often inconclusive, and in the latter case, invasive. Here, we explore the use of clofazimine hydrochloride nanoparticles (CFZ-HCl NPs), a repurposed formulation from an FDA-approved antimycobacterial agent, as a photoacoustic contrast agent for the evaluation of prostate cancer due to its macrophage-targeting capabilities and high optical absorbance at 495 nm. Using a transgenic adenocarcinoma of the mouse prostate (TRAMP) mouse model, our results indicate a preferential accumulation of intravenously injected CFZ-HCl NPs in cancerous prostates over normal prostates. Differences in accumulation of CFZ-HCl NPs between cancerous and normal prostates were determined using a two-wavelength unmixing technique via ex vivo photoacoustic imaging. Thus, intravenous injection of CFZ-HCl NPs leads to differences in the interactions of the particles with cancerous vs normal prostates, while allowing for photoacoustic detection and analysis of prostate cancer. These findings could lead to the development of a new noninvasive technique for the detection and monitoring of prostate cancer progression in an animal model that can potentially be translated to human patients. [ABSTRACT FROM AUTHOR]

Objective: To investigate the accuracy and precision of ultrasound shear wave elasticity measurements as a function of target elasticity and acquisition depth. Materials and methods: Using five ultrasound systems (VTQ, VTIQ, EPIQ 5, Aixplorer, and Aplio 500), two operators independently measured shear wave elasticities in two phantoms containing five different target elasticities (8±3, 14±4, 25±6, 45±8, and 80±12 kPa) at depths of 15, 30, 35, and 60 mm. Accuracy was assessed by evaluating measurement errors and the proportions of outliers, while factors affecting accuracy were assessed using logistic regression analysis. Measurement errors were defined as differences between the measured values and 1) the margins of the target elasticity, and 2) the median values of the target elasticity. Outliers were defined as measured values outside the margins of the target elasticity. Precision was assessed by calculating the reproducibility of measurements using the within-subject coefficient of variation (wCV). Results: Mean measurement errors and the proportions of outliers were higher for high than for low target elasticities (p<0.001), but did not differ in relation to acquisition depth, either within an elastography system or across the different systems. Logistic regression analysis showed that target elasticity (p<0.001) significantly affected accuracy, whereas acquisition depth (p>0.05) did not. The wCV for the 80±12 kPa target (31.33%) was significantly higher than that for lower elasticity targets (6.96–10.43 kPa; p<0.001). The wCV did not differ across acquisition depths. The individual elastography systems showed consistent results. Conclusions: Targets with high elasticity showed lower accuracy and lower precision than targets with low elasticity, while acquisition depth did not show consistent patterns in either accuracy or precision. [ABSTRACT FROM AUTHOR]

Virtual three-dimensional (3D) surface models of autopsied human brain hemispheres were constructed by integrating multiple two-dimensional (2D) photographs. To avoid gravity-dependent deformity, formalin-fixed hemispheres were placed on non-refractile, transparent acrylic plates, which allowed us to take 2D photographs from various different angles. Photogrammetric calculations using software (ReCap Pro cloud service, Autodesk, San Rafael, CA, USA) allowed us calculate the 3D surface of each brain hemisphere. Virtual brain models could be moved and rotated freely to allow smooth, seamless views from different angles and different magnifications. When viewing rotating 3D models on 2D screens, 3D aspects of the models were enhanced using motion parallax. Comparison of different brains using this method allowed us to identify disease-specific patterns of macroscopic atrophy, that were not apparent in conventional 2D photographs. For example, we observed frontal lobe atrophy in a progressive supranuclear palsy brain, and even more subtle atrophy in the superior temporal gyrus in amyotrophic lateral sclerosis-frontotemporal lobar degeneration. Thus, our method facilities recognition of gyral atrophy. In addition, it provides a much more powerful and suitable way of visualizing the overall appearance of the brain as a three-dimensional structure. Comparison of normal and diseased brains will allow us to associate different macroscopic changes in the brain to clinical manifestations of various diseases. [ABSTRACT FROM AUTHOR]

Resistance to insecticides can hamper the control of mosquitoes such as Culex quinquefasciatus, known to vector arboviruses such as West Nile virus and others. The strong selective pressure exerted on a mosquito population by the use of insecticides can result in heritable genetic changes associated with resistance. We sought to characterize genetic differences between insecticide resistant and susceptible Culex quinquefasciatus mosquitoes using targeted DNA sequencing. To that end, we developed a panel of 122 genes known or hypothesized to be involved in insecticide resistance, and used an Ion Torrent PGM sequencer to sequence 125 unrelated individuals from seven populations in the southern U.S. whose resistance phenotypes to permethrin and malathion were known from previous CDC bottle bioassay testing. Data analysis consisted of discovering SNPs (Single Nucleotide Polymorphism) and genes with evidence of copy number variants (CNVs) statistically associated with resistance. Ten of the seventeen genes found to be present in higher copy numbers were experimentally validated with real-time PCR. Of those, six, including the gene with the knock-down resistance (kdr) mutation, showed evidence of a ≥ 1.5 fold increase compared to control DNA. The SNP analysis revealed 228 unique SNPs that had significant p-values for both a Fisher’s Exact Test and the Cochran-Armitage Test for Trend. We calculated the population frequency for each of the 64 nonsynonymous SNPs in this group. Several genes not previously well characterized represent potential candidates for diagnostic assays when further validation is conducted. [ABSTRACT FROM AUTHOR]

The Gram-negative pathogen, Acinetobacter baumannii has emerged as a global nosocomial health threat affecting the majority of hospitals in the U.S. and abroad. The redox protein thioredoxin has been shown to play several roles in modulation of cellular functions affecting various virulence factors in Gram-negative pathogens. This study aims to explore the role of thioredoxin-A protein (TrxA) in A. baumannii virulence. We determined that deletion of the TrxA gene did not significantly affect resistance to environmental stressors such as temperature, salt, and pH. However, TrxA was critical for survival in the presence of elevated levels of hydrogen peroxide. Lack of TrxA was associated with decreased expression of type IV pili related genes and an inability to undergo normal twitching motility. Interestingly, the TrxA-null mutant was able to form biofilms better than the wildtype (WT) and was observed to be significantly less virulent than the WT in a pulmonary infection model. These results are supportive of thioredoxin playing a key role in A. baumannii virulence. [ABSTRACT FROM AUTHOR]

Evidence of involvement of novel biomarkers in disease pathogenesis from research cohorts often precedes an understanding of their distributions in broader populations. This study aimed to estimate the distribution of fibroblast growth factor 23 (FGF-23), an endocrine hormone that helps to regulate serum phosphate levels, in the overall US population and in important subgroups. We used a predictive model generated using data from the Framingham Health Study to estimate FGF-23 values for adults in the US National Health and Nutrition Examination Survey and the size of patient subgroups with levels of FGF-23 above selected thresholds. To assess the face validity of our FGF-23 estimates, we examined the relationship between estimated FGF-23 and cardiovascular and all-cause mortality within NHANES using Kaplan-Meier estimates and Cox proportional-hazards regression models and compared it to that observed in Framingham. Estimated FGF-23 values from NHANES were lower (median [interquartile range] 47.4 [35.8, 64.0] vs. 67.0 [54.0, 85.0] RU/mL) than the observed FGF-23 values from the Framingham cohort. Age- and sex-adjusted 10-year all-cause mortality was significantly higher (hazard ratio 2.43 [95% confidence interval: 1.42, 4.16]) for subjects with estimated FGF-23 levels in the highest versus lowest quartile. Estimating the distribution of biomarker values in the general population by applying predictive equations from smaller research cohorts is feasible and can inform drug research decision making. [ABSTRACT FROM AUTHOR]

Latent tuberculosis infection (LTBI) treatment in persons at increased risk of disease progression is a key strategy with the strong potential to increase rate of tuberculosis (TB) decline in the United States. However, LTBI treatment in homeless persons, a population at high-risk of active TB disease, is usually associated with poor adherence. We describe the impact of using directly observed treatment (DOT) versus self-administered treatments (SAT) as an adherence-improving intervention to administer four months of daily rifampin regimen for LTBI treatment among homeless adults in Atlanta. Retrospective analysis of clinical care data on 274 homeless persons who initiated daily rifampin treatment for LTBI treatment at a county health department between January 2014 and December 2016 was performed. To reduce bias from non-random assignment of treatment, an inverse probability of treatment weighted (IPTW) logistic regression model was used to assess the effect of treatment type on treatment completion. Subgroup analyses were performed to assess heterogeneity of treatment effect on LTBI completion. Of 274 LTBI treatment initiators, 177 (65%) completed treatment [DOT 118/181 (65%), SAT 59/93 (63%)]. In the fully adjusted and weighted analysis, the odds of completing LTBI treatment on DOT was 40% higher than the odds of completing treatment by SAT [adjusted odds ratio (95% CI), aOR: 1.40 (1.07, 1.82), p = 0.014]. The unstable nature of homeless persons’ lifestyle makes LTBI treatment difficult for many reasons. Our study lends support to the use of DOT to improve LTBI treatment completion among subgroups of homeless persons on treatment with daily rifampin. [ABSTRACT FROM AUTHOR]

Background: Persons with dementia have twice the acute hospital use as older persons without dementia. In addition to straining overburdened healthcare systems, acute hospital use impacts patient and caregiver quality of life and is associated with increased risk of adverse outcomes including death. Reducing avoidable acute hospital use in persons with dementia is thus a global healthcare priority. However, evidence regarding the impact of health service interventions as defined by the Effective Practice and Organization of Care Cochrane Group on acute hospital use is scant and inconclusive. The aim of this systematic review and meta-analysis was to synthesize available evidence on the impact of health service interventions on acute hospital use in community-dwelling persons with dementia compared to usual care. Methods: Data Sources: MEDLINE, EMBASE, CINAHL and Cochrane CENTRAL (from 01/1995 to 08/2017). Study eligibility criteria: Randomised controlled trials measuring the impact of health service interventions on acute hospital use (proportion and mean number of emergency department visits and hospitalisations, mean number of hospital days, measured at 12 months, and at longest follow-up) in community-dwelling persons with dementia, compared to usual care. Study selection, appraisal and synthesis methods: Reviewers independently identified studies, extracted data, and assessed the risk of bias, with the Cochrane risk of bias tool. Authors of relevant trials were queried about unpublished data. Random effects model was used for meta-analyses. Effect heterogeneity was assessed through prediction intervals, and explored using sub-group analyses. Findings: Seventeen trials provided data on 4,549 persons. Unpublished data were obtained for 13 trials, representing 65% of synthesized data. Most interventions included a case management or a self-management component. None of the outcome comparisons provided conclusive evidence supporting the hypothesis that these interventions would lead to a decrease in acute hospital use. Furthermore, prediction intervals indicated possible and important increased service use associated with these interventions, such as emergency department visits, hospital admissions, and hospital days. Subgroup analyses did not favour any type of intervention. A limitation of this study is the inclusion of any type of health service intervention, which may have increased the observed heterogeneity. Conclusion: Despite a comprehensive systematic review and meta-analysis, including predominantly unpublished data, no health service intervention beyond usual care was found to reduce acute hospital use in community-dwelling persons with dementia. An important increase in service use may be associated with these interventions. Further research is urgently needed to identify effective interventions for this vulnerable population to limit rising acute hospital use, associated costs and adverse outcomes. Systematic review registration PROSPERO CRD42016046444. [ABSTRACT FROM AUTHOR]

Background: Multimorbidity–having two or more coexisting chronic conditions–is highly prevalent, costly, and disabling to older adults. Questions remain regarding chronic diseases accumulation over time and whether this differs by racial and ethnic background. Answering this knowledge gap, this study identifies differences in rates of chronic disease accumulation and multimorbidity development among non-Hispanic white, non-Hispanic black, and Hispanic study participants starting in middle-age and followed up to 16 years. Methods and findings: We analyzed data from the Health and Retirement Study (HRS), a biennial, ongoing, publicly-available, longitudinal nationally-representative study of middle-aged and older adults in the United States. We assessed the change in chronic disease burden among 8,872 non-Hispanic black, non-Hispanic white, and Hispanic participants who were 51–55 years of age at their first interview any time during the study period (1998–2014) and all subsequent follow-up observations until 2014. Multimorbidity was defined as having two or more of seven somatic chronic diseases: arthritis, cancer, heart disease (myocardial infarction, coronary heart disease, angina, congestive heart failure, or other heart problems), diabetes, hypertension, lung disease, and stroke. We used negative binomial generalized estimating equation models to assess the trajectories of multimorbidity burden over time for non-Hispanic black, non-Hispanic white, and Hispanic participants. In covariate-adjusted models non-Hispanic black respondents had initial chronic disease counts that were 28% higher than non-Hispanic white respondents (IRR 1.279, 95% CI 1.201, 1.361), while Hispanic respondents had initial chronic disease counts that were 15% lower than non-Hispanic white respondents (IRR 0.852, 95% CI 0.775, 0.938). Non-Hispanic black respondents had rates of chronic disease accumulation that were 1.1% slower than non-Hispanic whites (IRR 0.989, 95% CI 0.981, 0.998) and Hispanic respondents had rates of chronic disease accumulation that were 1.5% faster than non-Hispanic white respondents (IRR 1.015, 95% CI 1.002, 1.028). Using marginal effects commands, this translates to predicted values of chronic disease for white respondents who begin the study period with 0.98 chronic diseases and end with 2.8 chronic diseases; black respondents who begin the study period with 1.3 chronic diseases and end with 3.3 chronic diseases; and Hispanic respondents who begin the study period with 0.84 chronic diseases and end with 2.7 chronic diseases. Conclusions: Middle-aged non-Hispanic black adults start at a higher level of chronic disease burden and develop multimorbidity at an earlier age, on average, than their non-Hispanic white counterparts. Hispanics, on the other hand, accumulate chronic disease at a faster rate relative to non-Hispanic white adults. Our findings have important implications for improving primary and secondary chronic disease prevention efforts among non-Hispanic black and Hispanic Americans to stave off greater multimorbidity-related health impacts. [ABSTRACT FROM AUTHOR]

As emerging and re-emerging infectious arboviruses like dengue, chikungunya, and Zika threaten new populations worldwide, officials scramble to assess local severity and transmissibility, with little to no epidemiological history to draw upon. Indirect estimates of risk from vector habitat suitability maps are prone to great uncertainty, while direct estimates from epidemiological data are only possible after cases accumulate and, given environmental constraints on arbovirus transmission, cannot be widely generalized beyond the focal region. Combining these complementary methods, we use disease importation and transmission data to improve the accuracy and precision of a priori ecological risk estimates. We demonstrate this approach by estimating the spatiotemporal risks of Zika virus transmission throughout Texas, a high-risk region in the southern United States. Our estimates are, on average, 80% lower than published ecological estimates—with only six of 254 Texas counties deemed capable of sustaining a Zika epidemic—and they are consistent with the number of autochthonous cases detected in 2017. Importantly our method provides a framework for model comparison, as our mechanistic understanding of arbovirus transmission continues to improve. Real-time updating of prior risk estimates as importations and outbreaks arise can thereby provide critical, early insight into local transmission risks as emerging arboviruses expand their global reach. [ABSTRACT FROM AUTHOR]

A small PCR-generated DNA fragment was introduced into a pharmaceutical grade ink as a molecular taggant, and the DNA tagged ink was delivered onto the surface of capsules by standard high-speed offset printing. The amount of DNA in the ink on each capsule is roughly 10−12 fold lower than that allowed as safe by the United States Food and Drug Administration (FDA) and the WHO with regards to acceptable limits of residual DNA. The printed ink on the capsule surface was sampled by swabbing, followed by direct analysis of the DNA-swab complex, without subsequent DNA purification. It was shown that DNA recovered from the ink by swabbing was suitable for PCR-CE analysis—a widely used method in forensic science and was also suitable for qPCR and isothermal DNA amplification, when coupled with portable devices similar to those used for environmental sampling and food safety testing. The data set a precedent: A small DNA fragment could be introduced as an excipient into a pharmaceutical application, and thereafter tracked through the pharmaceutical supply chain via forensic DNA authentication. [ABSTRACT FROM AUTHOR]

This goal of this study was to highlight the importance of minerals in the diet of fish for meeting micronutrient requirements in the human diet. First arsenic, calcium, cadmium, copper, iron, molybdenum, magnesium, manganese, sodium, phosphorus, potassium, selenium, and zinc concentrations of twelve commercially available tilapia samples were measured. The nutritional value of fillets in regard to their mineral content were assessed to establish potential health benefits or risks for consumers. The health benefit value of selenium was also calculated. Positive health benefit values indicate that tilapia fillets in the United States marketplace of this study do not pose health risks associated with mercury exposures. Selenium was the trace mineral of interest. After the market study, a seven-week fish feeding trial was conducted to study the influence of organic versus inorganic dietary selenium on Nile tilapia (Oreochromis niloticus). Fish were fed two different diets enriched with the same concentration (0.01g kg-1) of selenium in form of inorganic (sodium selenite) or organic (seleno-L-methionine) selenium in triplicate groups. There were no significant differences between growth and biometrics of fish fed different diets (p>0.05). At the end of trial twelve fish from each treatment were collected. Fillets of fish fed organic selenium had selenium concentrations of 0.55 ± 0.01 μg g-1 which were significantly (p<0.05) higher than fish fed inorganic selenium at levels of 0.22 ± 0.008 μg g-1 or fish samples from the marketplace with a selenium level of 0.2 ± 0.03 μg g-1. Fish fed organic selenium also had significantly higher (p<0.05) plasma and kidney selenium in comparison to fish fed inorganic selenium. No significant differences (p>0.05) were observed in glutathione peroxidase activities in either the plasma or liver of Nile tilapia in the different treatment groups. This study shows that organic selenium is a better option for production of Nile tilapia fillets rich in selenium. [ABSTRACT FROM AUTHOR]

Objective: Assessing the epidemiological association between herpes simplex virus type 1 (HSV-1) and type 2 (HSV-2) infections in the United States, and characterizing the trends in the standardized HSV-1 and HSV-2 antibody prevalences (seroprevalences), 1999–2016. Methods: Source of data was the cross-sectional and nationally-representative biennial surveys of the National Health and Nutrition Examination Survey (NHANES). All nine NHANES rounds for 1999–2016 were included in analysis. Datasets of these rounds were combined and analyzed accounting for survey design and applying weighting procedures. Logistic regressions were used to identify associations with seropositivity. Sensitivity analyses were conducted. Results: Odds of HSV-1 infection declined by 2.84% (95% CI: 1.70%-4.00%) annually among men, and by 2.22% (95% CI: 1.23%-3.21%) among women. Declines were highest at younger ages. Odds of HSV-2 infection declined by 2.23% (95% CI: 0.71%-3.82%) annually among men, and by 2.89% (95% CI: 1.57%-4.28%) among women. Odds ratio of the association between HSV-2 and HSV-1 seropositivity was 0.71 (95% CI: 0.60–0.84) for men and 0.81 (95% CI: 0.72–0.91) for women, after adjustment for age, ethnicity, and year. Conclusion: HSV-1 and HSV-2 seroprevalences showed a strong declining trend for at least two decades, for both sexes and for the different ethnicities, possibly reflecting improvements in hygiene and living conditions (for HSV-1), and safer sexual behavior (for HSV-2). HSV-1 seroprevalence declines are most pronounced among young individuals. There is evidence for cross protection between the two infections, suggestive of HSV-1 seropositivity being partially protective against HSV-2 infection. [ABSTRACT FROM AUTHOR]

Background: Foliar fungicide applications to corn (Zea mays L.) occur at one or more application timings ranging from early vegetative growth stages to mid-reproductive stages. Previous studies indicated that fungicide applications are profitable under high disease pressure when applied during the tasseling to silking growth stages. Few comprehensive studies in corn have examined the impact of fungicide applications at an early vegetative growth stage (V6) compared to late application timings (VT) for yield response and return on fungicide investment (ROI) across multiple locations. Objective: Compare yield response of fungicide application timing across multiple fungicide classes and calculate the probability of positive ROI. Methods: Data were collected specifically for this analysis using a uniform protocol conducted in 13 states in the United States and one province in Canada from 2014–2015. Data were subjected to a primary mixed-model analysis of variance. Subsequent univariate meta-analyses, with and without moderator variables, were performed using standard meta-analytic procedures. Follow-up power and prediction analyses were performed to aid interpretation and development of management recommendations. Results: Fungicide application resulted in a range of yield responses from -2,683.0 to 3,230.9 kg/ha relative to the non-treated control, with 68.2% of these responses being positive. Evidence suggests that all three moderator variables tested (application timing, fungicide class, and disease base level), had some effect (α = 0.05) on the absolute difference in yield between fungicide treated and non-treated plots (). Application timing influenced , with V6 + VT and the VT application timings resulting in greater yield responses than the V6 application timing alone. Fungicide formulations that combined demethylation inhibitor and quinone outside inhibitor fungicides significantly increased yield response. Conclusion: Foliar fungicide applications can increase corn grain yield. To ensure the likelihood of a positive ROI, farmers should focus on applications at VT and use fungicides that include a mix of demethylation inhibitor and quinone outside inhibitor active ingredients. [ABSTRACT FROM AUTHOR]

Background: Tardive dyskinesia (TD) is a movement disorder resulting from treatment with typical and atypical antipsychotics. An estimated 16–50% of patients treated with antipsychotics have TD, but this number may be underestimated. The objectives of this study were to build an algorithm for use in electronic health records (EHRs) for the detection and characterization of TD patients, and to estimate the prevalence of TD in a population of patients exposed to antipsychotic medications. Methods: This retrospective observational study included patients identified in the Optum EHR Database who received a new or refill prescription for an antipsychotic medication between January 2011 and December 2015 (follow-up through June 2016). TD mentions were identified in the natural language–processed clinical notes, and an algorithm was built to classify the likelihood that the mention represented documentation of a TD diagnosis as probable, possible, unlikely, or negative. The final TD population comprised a subgroup identified using this algorithm, with ≥1 probable TD mention (highly likely TD). Results: 164,417 patients were identified for the antipsychotic population, with1,314 comprising the final TD population. Conservatively, the estimated average annual prevalence of TD in patients receiving antipsychotics was 0.8% of the antipsychotic user population. The average annual prevalence may be as high as 1.9% per antipsychotic user per year, allowing for a more-inclusive algorithm using both probable and possible TD. Most TD patients were prescribed atypical antipsychotics (1049/1314, 79.8%). Schizophrenia (601/1314, 45.7%), and paranoid and schizophrenia-like disorders (277/1314, 21.1%) were more prevalent in the TD population compared with the entire antipsychotic drug cohort (13,308/164,417; 8.1% and 19,359/164,417; 11.8%, respectively). Conclusions: Despite a lower TD prevalence than previously estimated and the predominant use of atypical antipsychotics, identified TD patients appear to have a substantial comorbidity burden that requires special treatment and management consideration. [ABSTRACT FROM AUTHOR]

Objectives: Reviews of violence against children in disaster settings focus on armed conflict. Little is understood about natural disasters which has implications in planning humanitarian response. We examined the magnitude and direction of the association between exposure to natural disasters and physical, emotional, and sexual violence against children, and assessed the quality of the evidence. Methods: We searched 15 health and social science databases from first record until May 16, 2018. Publications describing all types of quantitative study design were eligible for inclusion. We presented study characteristics and quality in a narrative form and generated pooled estimates using a three-level random effects model. We evaluated Cochrane’s Q with p-values below 0.10 and radial plots to assess heterogeneity. Planned subgroup analyses explored differential results by violence form, study design, and analysis method. Results: 11 publications met inclusion criteria. The majority were cross-sectional studies examining physical or sexual violence in the United States. We found no evidence of a consistent association or directional influence between natural disasters and violence against children. Combined categorical violence outcomes had substantial heterogeneity [Q (df = 66) = 252.83, p < 0.001]. Subgroups without evidence of heterogeneity had confidence intervals that included a possible null effect. Our findings were mainly limited by inconsistencies in operational definitions of violence, a lack of representative sampling, and unclear establishment of temporal order between natural disaster exposure and violence outcomes. Conclusions: Based on the available evidence, we cannot confidently conclude that natural disasters increase the level or severity of violence against children above non-disaster settings, however heterogeneity and study quality hamper our ability to draw firm conclusions. More nuanced and rigorous research is needed to inform practice and policy as natural disasters increasingly affect human populations. [ABSTRACT FROM AUTHOR]

Detection of clusters of Legionnaires’ disease, a leading waterborne cause of pneumonia, is challenging. Clusters vary in size and scope, are associated with a diverse range of aerosol-producing devices, including exposures such as whirlpool spas and hotel water systems typically associated with travel, and can occur without an easily identified exposure source. Recently, jurisdictions have begun to use SaTScan spatio-temporal analysis software prospectively as part of routine cluster surveillance. We used data collected by the Active Bacterial Core surveillance platform to assess the ability of SaTScan to detect Legionnaires’ disease clusters. We found that SaTScan analysis using traditional surveillance data and geocoded residential addresses was unable to detect many common Legionnaires’ disease cluster types, such as those associated with travel or a prolonged time between cases. Additionally, signals from an analysis designed to simulate a real-time search for clusters did not align with clusters identified by traditional surveillance methods or a retrospective SaTScan analysis. A geospatial analysis platform better tailored to the unique characteristics of Legionnaires’ disease epidemiology would improve cluster detection and decrease time to public health action. [ABSTRACT FROM AUTHOR]

The maximum entropy model, a commonly used species distribution model (SDM) normally combines observations of the species occurrence with environmental information to predict the geographic distributions of animal or plant species. However, it only produces point estimates for the probability of species existence. To understand the uncertainty of the point estimates, we analytically derived the variance of the outputs of the maximum entropy model from the variance of the input. We applied the analytic method to obtain the standard deviation of dengue importation probability and Aedes aegypti suitability. Dengue occurrence data and Aedes aegypti mosquito abundance data, combined with demographic and environmental data, were applied to obtain point estimates and the corresponding variance. To address the issue of not having the true distributions for comparison, we compared and contrasted the performance of the analytical expression with the bootstrap method and Poisson point process model which proved of equivalence of maximum entropy model with the assumption of independent point locations. Both Dengue importation probability and Aedes aegypti mosquito suitability examples show that the methods generate comparatively the same results and the analytic method we introduced is dramatically faster than the bootstrap method and directly apply to maximum entropy model. [ABSTRACT FROM AUTHOR]

Health planners use forecasts of key metrics associated with influenza-like illness (ILI); near-term weekly incidence, week of season onset, week of peak, and intensity of peak. Here, we describe our participation in a weekly prospective ILI forecasting challenge for the United States for the 2016-17 season and subsequent evaluation of our performance. We implemented a metapopulation model framework with 32 model variants. Variants differed from each other in their assumptions about: the force-of-infection (FOI); use of uninformative priors; the use of discounted historical data for not-yet-observed time points; and the treatment of regions as either independent or coupled. Individual model variants were chosen subjectively as the basis for our weekly forecasts; however, a subset of coupled models were only available part way through the season. Most frequently, during the 2016-17 season, we chose; FOI variants with both school vacations and humidity terms; uninformative priors; the inclusion of discounted historical data for not-yet-observed time points; and coupled regions (when available). Our near-term weekly forecasts substantially over-estimated incidence early in the season when coupled models were not available. However, our forecast accuracy improved in absolute terms and relative to other teams once coupled solutions were available. In retrospective analysis, we found that the 2016-17 season was not typical: on average, coupled models performed better when fit without historically augmented data. Also, we tested a simple ensemble model for the 2016-17 season and found that it underperformed our subjective choice for all forecast targets. In this study, we were able to improve accuracy during a prospective forecasting exercise by coupling dynamics between regions. Although reduction of forecast subjectivity should be a long-term goal, some degree of human intervention is likely to improve forecast accuracy in the medium-term in parallel with the systematic consideration of more sophisticated ensemble approaches. [ABSTRACT FROM AUTHOR]

Disease spread in populations is a consequence of the interaction between host, pathogen, and environment, i.e. the epidemiological triad. Yet the influences of each triad component may vary dramatically for different settings. Comparison of environmental, demographic, socio-economic, and historical backgrounds may support tailoring site-specific control measures. Because of the long-term survival of Bacillus anthracis, Anthrax is a suitable example for studying the influence of triad components in different endemic settings. We compared the spatiotemporal patterns of historic animal Anthrax records in two endemic areas, located at northern latitudes in the western and eastern hemispheres. Our goal was to compare the spatiotemporal patterns in Anthrax progression, intensity, direction, and recurrence (disease hot spots), in relation to epidemiological factors and potential trigger events. Reported animal cases in Minnesota, USA (n = 289 cases between 1912 and 2014) and Kazakhstan (n = 3,997 cases between 1933 and 2014) were analyzed using the spatiotemporal directionality test and the spatial scan statistic. Over the last century Anthrax occurrence in Minnesota was sporadic whereas Kazakhstan experienced a long-term epidemic. Nevertheless, the seasonality was comparable between sites, with a peak in August. Declining number of cases at both sites was attributed to vaccination and control measures. The spatiotemporal directionality test detected a relative northeastern directionality in disease spread for long-term trends in Minnesota, whereas a southwestern directionality was observed in Kazakhstan. In terms of recurrence, the maximum timespans between cases at the same location were 55 and 60 years for Minnesota and Kazakhstan, respectively. Disease hotspots were recognized in both settings, with spatially overlapping clusters years apart. Distribution of the spatiotemporal cluster radii between study sites supported suggestion of site-specific control zones. Spatiotemporal patterns of Anthrax occurrence in both endemic regions were attributed to multiple potential trigger events including major river floods, changes in land use, agriculture, and susceptible livestock populations. Results here help to understand the long-term epidemiological dynamics of Anthrax while providing suggestions to the design and implementation of prevention and control programs, in endemic settings. [ABSTRACT FROM AUTHOR]

Adequate identification of estrus is crucial to achieve satisfactory reproductive performance in dairy farms. Even though several studies evaluated expression and identification of estrus at the cow level, limited data exist regarding estrus identification parameters at the herd level. The objectives of this study were to use data from large dairy farms located in Kansas to describe temporal patterns of insemination risk (IR), and to investigate associations between IR and various herd-level factors. Nine herds that housed lactating cows in dry-lots or free-stalls were used in the study. Data from 2012 to 2017 were extracted and categorized in 21-day intervals in a total of 85 cycles, which were classified by season of the year. Mean (SD) IR was 67.6% (4.0) and increased 0.067% (0.009) for each 21-day cycle during the period evaluated. Annual, semi-annual, and trimestral IR peaks were detected using autoregressive integrated moving average analysis. Most of these variations, however, were considered minimal and likely not of economic concern for commercial herds. Insemination risk was greatest during autumn, but did not differ among winter, spring, and summer. Insemination risk was not associated with herd milk yield per season, incidence risk of mastitis during first 21 days in milk, proportion of primiparous cows in the milking herd, or voluntary waiting period of multiparous cows. Herds that housed lactating dairy cows in dry-lots had IR 2.4 percentage points greater than free-stall herds. In addition, mortality during the first 60 days in milk, and category of voluntary waiting period for primiparous cows were associated with IR. In conclusion, seasonal variability in IR was minimal, with increased values observed during the autumn. Insemination risk was greater for dry-lot than free-stall herds. In addition, reduced mortality of lactating cows by 60 days in milk and longer voluntary waiting period for primiparous cows seem to favor greater IR. [ABSTRACT FROM AUTHOR]

Purpose: To investigate whether hyperreflective foci (HRF) exhibit flow projection artifact on OCTA, and study the efficacy of commercial projection artifact removal software (PAR-OCTA, Optovue, Inc), and a custom projection resolved OCTA (PR-OCTA) in distinguishing artifacts from true flow in retinal angiomatous proliferation (RAP). Methods: The study included five eyes with HRF representing pigment migration in dry age-related macular degeneration (AMD), five eyes with leaking treatment-naïve RAP, and ten eyes with diabetic hard exudates. We examined flow signal on OCTA cross-sections using PAR, and performed PR-OCTA to study the effect of increasingly stringent projection removal thresholds. Flow signal intensity was analyzed and quantified using imageJ (NIH, Bethesda, MD, USA), by calculating the percentage of red pixels (R) representing flow, compared to green (G) and blue (B) pixels. Results: PAR-OCTA cross sections revealed persistent flow signal in all HRF, including RAP, hard exudates and pigment migration. In RAP, PR-OCTA detected intransigent flow, irrespective of the flow removal threshold. Mean R in the five RAP lesions remained higher than mean G and B at the most stringent PR-OCTA threshold (40.96% vs 29.52 and 29.52%, respectively), denoting persistence of flow. In contrast, increasing the PR-OCTA threshold in pigment migration and hard exudates removed the flow signal, with a statistically significant decrease in mean R with increasing threshold. (p = 0.017 and 0.0029, respectively) Conclusion: Commercial PAR-OCTA is not completely effective at removing artifactual flow in hard exudates and HRF related to pigment migration. Custom built PR-OCTA, using a sliding scale of threshold, allowed us to distinguish true flow in RAP from artifactual flow in avascular HRF. Further studies are needed to validate the optimum threshold for projection artifact removal, which would preserve true flow in RAP and the small intraretinal capillaries. [ABSTRACT FROM AUTHOR]

Water polo is a contact sport that is gaining popularity in the United States and carries a risk of repeated head impacts and concussion. The frequency and magnitude of sport-related head impacts have not been described for water polo. We aimed to compare patterns of empirically measured head impact exposure of male collegiate water polo players to patterns previously reported by a survey of current and former water polo athletes. Participants wore water polo caps instrumented with head impact sensors during three seasons of collegiate water polo. Peak linear acceleration (PLA) and peak rotational acceleration (PRA) were recorded for head impacts. Athlete positions were recorded by research staff at the occurrence of each head impact. Head impacts were sustained by athletes in offensive positions more frequently than in defensive and transition positions (246, 59.9% vs. 93, 22.6% vs. 72, 17.5%). 37% of all head impacts during gameplay were sustained by athletes playing the offensive center position. Impact magnitude (means ± SD: PLA = 36.1±12.3g, PRA = 5.0±2.9 krads/sec2) did not differ between position or game scenario. Among goalies, impact frequency and magnitude were similar between games (means ± SD: 0.54±.51 hits/game, PLA = 36.9±14.2g, PRA = 4.3±4.2 krads/sec2) and practices (means ± SD: 0.96±1.11 hits/practice, PLA = 43.7±14.5g, PRA = 3.9±2.5 krads/sec2). We report that collegiate water polo athletes are at risk for sport-related head impacts and impact frequency is dependent on game scenario and player position. In contrast, magnitude does not differ between scenarios or across positions. [ABSTRACT FROM AUTHOR]

Author summary A subset of anti-infective drugs are increasingly unavailable for patients in the United States due to pricing or withdrawal from the market. Timely market solutions are needed. We assert that solutions to ensure access to some essential anti-infective agents lie outside capital markets and that public-private partnerships may be the most viable solution. [ABSTRACT FROM AUTHOR]

Rationale: As part of the End TB Strategy, the World Health Organization calls for low-tuberculosis (TB) incidence settings to achieve pre-elimination (<10 cases per million) and elimination (<1 case per million) by 2035 and 2050, respectively. These targets require testing and treatment for latent tuberculosis infection (LTBI). Objectives: To estimate the ability and costs of testing and treatment for LTBI to reach pre-elimination and elimination targets in California. Methods: We created an individual-based epidemic model of TB, calibrated to historical cases. We evaluated the effects of increased testing (QuantiFERON-TB Gold) and treatment (three months of isoniazid and rifapentine). We analyzed four test and treat targeting strategies: (1) individuals with medical risk factors (MRF), (2) non-USB, (3) both non-USB and MRF, and (4) all Californians. For each strategy, we estimated the effects of increasing test and treat by a factor of 2, 4, or 10 from the base case. We estimated the number of TB cases occurring and prevented, and net and incremental costs from 2017 to 2065 in 2015 U.S. dollars. Efficacy, costs, adverse events, and treatment dropout were estimated from published data. We estimated the cost per case averted and per quality-adjusted life year (QALY) gained. Measurements and main results: In the base case, 106,000 TB cases are predicted to 2065. Pre-elimination was achieved by 2065 in three scenarios: a 10-fold increase in the non-USB and persons with MRF (by 2052), and 4- or 10-fold increase in all Californians (by 2058 and 2035, respectively). TB elimination was not achieved by any intervention scenario. The most aggressive strategy, 10-fold in all Californians, achieved a case rate of 8 (95% UI 4–16) per million by 2050. Of scenarios that reached pre-elimination, the incremental net cost was $20 billion (non-USB and MRF) to $48 billion. These had an incremental cost per QALY of $657,000 to $3.1 million. A more efficient but somewhat less effective single-lifetime test strategy reached as low as $80,000 per QALY. Conclusions: Substantial gains can be made in TB control in coming years by scaling-up current testing and treatment in non-USB and those with medical risks. [ABSTRACT FROM AUTHOR]

Background: Emergency department (ED) crowding is associated with negative health outcomes, patient dissatisfaction, and longer length of stay (LOS). The addition of advanced diagnostic imaging (ADI), namely CT, ultrasound (U/S), and MRI to ED encounter work up is a predictor of longer length of stay. Earlier and improved prediction of patients’ need for advanced imaging may improve overall ED efficiency. The aim of the study was to detect the association between ADI utilization and the structured and unstructured information immediately available during ED triage, and to develop and validate models to predict utilization of ADI during an ED encounter. Methods: We used the United States National Hospital Ambulatory Medical Care Survey data from 2009 to 2014 to examine which sociodemographic and clinical factors immediately available at ED triage were associated with the utilization of CT, U/S, MRI, and multiple ADI during a patient’s ED stay. We used natural language processing (NLP) topic modeling to incorporate free-text reason for visit data available at time of ED triage in addition to other structured patient data to predict the use of ADI using multivariable logistic regression models. Results: Among the 139,150 adult ED visits from a national probability sample of hospitals across the U.S, 21.9% resulted in ADI use, including 16.8% who had a CT, 3.6% who had an ultrasound, 0.4% who had an MRI, and 1.2% of the population who had multiple types of ADI. The c-statistic of the predictive models was greater than or equal to 0.78 for all imaging outcomes, and the addition of text-based reason for visit information improved the accuracy of all predictive models. Conclusions: Patient information immediately available during ED triage can accurately predict the eventual use of advanced diagnostic imaging during an ED visit. Such models have the potential to be incorporated into the ED triage workflow in order to more rapidly identify patients who may require advanced imaging during their ED stay and assist with medical decision-making. [ABSTRACT FROM AUTHOR]

Diabetes, a chronic disease affecting over 29 million people in the United States, requires the integration of complex medical tasks into a person’s daily life. Patient-centered care and compassion are recognized as essential dimensions of the quality care experience. This research examined provider attributes that influence adherence to type 2 diabetes mellitus (T2DM) regimens and sought to understand the phenomena of provider attributes, treatment adherence, and their relationship to coping ability and treatment outcomes. This quantitative study sampled 474 people with T2DM using a 62-item online survey administered to three different groups. The sample population included people over age 18 diagnosed with T2DM. The first group included 91 persons with T2DM identified through a Facebook group and personal social media connections, the second group included 120 Amazon Mechanical Turk participants with T2DM, and the third group included 263 respondents from a Qualtrics panel who had T2DM. Results indicated that perceived provider compassion (β = .41, ρ < .001) and optimism (β = .48, ρ < .001) positively affected coping ability. Additionally, full mediation effects for self-management were revealed, with coping ability positively mediating the effect of compassion on self-management and the effects of optimism on self-management. Furthermore, full mediation effects were found for treatment satisfaction, with coping ability positively mediating the effect of compassion on treatment satisfaction and the effects of optimism on treatment satisfaction. This research has implications for patients, healthcare professionals, and leaders suggesting that providers who communicate with optimism and compassion positively affect coping ability. As a result, healthcare providers and professionals have an opportunity to enhance self-management adherence by helping their patients cope with the burdens of diabetes. In addition, this study has implications for developing provider communication tools aimed at assessing patients’ coping capacity and increasing compassionate communication. [ABSTRACT FROM AUTHOR]

Cost-effective heat mitigation strategies are imperative for maintaining milk production and dairy farm profitability in the U.S. with projected climate change. This study investigated the cost-effectiveness of four heat abatement strategies, including Minimal (open barn or shading), Moderate (forced ventilation), High (fans and misting), and Intense (air conditioning). Heat stress and subsequent impacts on milk production per cow were predicted across nine climatic regions in the U.S. for early (2015 to 2034), mid (2045 to 2064) and late (2081 to 2100) 21st century, using downscaled climate projections. Heat abatements were used to adjust predicted milk production losses and illustrate the potential to reduce milk production losses due to heat stress. Economic analysis included a cost-benefit ratio calculation associated with the implementation of each heat abatement. Results showed that milk production losses were expected to accelerate across the U.S. at a mean rate of 174±7 kg/cow/decade, with the fastest rate in the Southeast region. Relative to Minimal heat abatement, Moderate, High, and Intense heat abatements increased annual milk production per cow by 3%, 4%, and 6% during early-21st century, 3%, 6%, and 11% during mid-21st century, and 3%, 8%, and 21% during late-21st century, respectively. The cost effectiveness of different heat abatement strategies generally increased with subsequently stronger heat abatements. In mid- and late-21st century, mean annual net values of High and Intense heat stress abatement implementation approached -$30 to $190 /cow and -$20 to $590 /cow, respectively, with the largest net annual benefit in late-21st century under Intense abatement. Findings from the study demonstrate the value of using downscaled climate projections to shed light on local and regional strategies to abate heat stress on cattle and mitigate potential milk production losses due to climate change. [ABSTRACT FROM AUTHOR]

No studies have investigated the association between living arrangements and disability-free life expectancy in the United States, nor worldwide. This study aims to examine the differences in total and disability-free life expectancy among older Americans according to living arrangements. Data from the Health and Retirement Study (1998 to 2014) for non-Hispanic whites aged 50 and over (N = 21,612). Disability-free life expectancy by gender, living arrangement, and education are obtained from incidence-based multistate life tables. Overall, those who live only with their spouses/partners live 1–19 years longer with 3–25 more years without disability and 1–7 fewer years with disability than do those with other living arrangements. Among those with the same living arrangement, the higher educated live up to 6 years longer with up to 8 more years in a disability-free state and up to 2 fewer years in a disabled state. The study shows strong association between living arrangement and disability-free life expectancy by gender and education. Long-term care policy should take into account the length of life with/without disability by living arrangements and socioeconomic status and make use of the potential family resources. [ABSTRACT FROM AUTHOR]

The ability to produce timely and accurate flu forecasts in the United States can significantly impact public health. Augmenting forecasts with internet data has shown promise for improving forecast accuracy and timeliness in controlled settings, but results in practice are less convincing, as models augmented with internet data have not consistently outperformed models without internet data. In this paper, we perform a controlled experiment, taking into account data backfill, to improve clarity on the benefits and limitations of augmenting an already good flu forecasting model with internet-based nowcasts. Our results show that a good flu forecasting model can benefit from the augmentation of internet-based nowcasts in practice for all considered public health-relevant forecasting targets. The degree of forecast improvement due to nowcasting, however, is uneven across forecasting targets, with short-term forecasting targets seeing the largest improvements and seasonal targets such as the peak timing and intensity seeing relatively marginal improvements. The uneven forecasting improvements across targets hold even when “perfect” nowcasts are used. These findings suggest that further improvements to flu forecasting, particularly seasonal targets, will need to derive from other, non-nowcasting approaches. [ABSTRACT FROM AUTHOR]

Breweries across the country are investing in energy efficient and low-carbon brewing practices. Drawing insights from the sustainable consumption and ecological economics literature, this analysis evaluates whether consumers are willing to pay more for sustainable beer and what predicts the value of the premium. Based on a survey of beer consumers from across the U.S. that contained one of two willingness-to-pay exercises, we evaluate what respondent attributes are associated with a higher willingness-to-pay for sustainably brewed beer. We find that the majority of beer consumers are willing to pay more for sustainable beer. Consumers who are prepared to pay a premium tend to already pay more per unit of beer, are more aware of their purchasing behavior and the manner in which their consumption patterns may affect the environment, and pursue lifestyles based on professional advancement, helping the environment, and helping other causes. [ABSTRACT FROM AUTHOR]

Reports of emotions experienced over the past week can be influenced by memory bias, which is more pronounced for people with depression. No studies, however, have examined memory bias for specific emotion clusters (e.g., sadness, anxiety, and anger) experienced on a day-to-day basis among people with depression or a history of depression. Participants (N = 1,657) from the Midlife in the United States Study were assessed for depression. Approximately 6 months later, participants reported their emotional experiences for 8 days and recalled these experiences on the final day. Differences in recalled and reported emotion were compared between participants with and without a history of depression. Participants overestimated experience only of negative emotions, particularly anger, and this negativity bias was greatest for participants with a history of depression. Feelings related to anger were prone to greater overestimation than sadness or anxiety. These findings emphasize the role of memory bias in retrospective reports of specific emotions and illustrate the presence of an amplified memory bias among people who are at a greater risk for recurrent depressive episodes. [ABSTRACT FROM AUTHOR]

Background: No prior study to our knowledge has examined the joint contribution of a polygenic risk score (PRS), mammographic density (MD), and postmenopausal endogenous hormone levels-all well-confirmed risk factors for invasive breast cancer-to existing breast cancer risk prediction models.Methods and Findings: We conducted a nested case-control study within the prospective Nurses' Health Study and Nurses' Health Study II including 4,006 cases and 7,874 controls ages 34-70 years up to 1 June 2010. We added a breast cancer PRS using 67 single nucleotide polymorphisms, MD, and circulating testosterone, estrone sulfate, and prolactin levels to existing risk models. We calculated area under the curve (AUC), controlling for age and stratified by menopausal status, for the 5-year absolute risk of invasive breast cancer. We estimated the population distribution of 5-year predicted risks for models with and without biomarkers. For the Gail model, the AUC improved (p-values < 0.001) from 55.9 to 64.1 (8.2 units) in premenopausal women (Gail + PRS + MD), from 55.5 to 66.0 (10.5 units) in postmenopausal women not using hormone therapy (HT) (Gail + PRS + MD + all hormones), and from 58.0 to 64.9 (6.9 units) in postmenopausal women using HT (Gail + PRS + MD + prolactin). For the Rosner-Colditz model, the corresponding AUCs improved (p-values < 0.001) by 5.7, 6.2, and 6.5 units. For estrogen-receptor-positive tumors, among postmenopausal women not using HT, the AUCs improved (p-values < 0.001) by 14.3 units for the Gail model and 7.3 units for the Rosner-Colditz model. Additionally, the percentage of 50-year-old women predicted to be at more than twice 5-year average risk (≥2.27%) was 0.2% for the Gail model alone and 6.6% for the Gail + PRS + MD + all hormones model. Limitations of our study included the limited racial/ethnic diversity of our cohort, and that general population exposure distributions were unavailable for some risk factors.Conclusions: In this study, the addition of PRS, MD, and endogenous hormones substantially improved existing breast cancer risk prediction models. Further studies will be needed to confirm these findings and to determine whether improved risk prediction models have practical value in identifying women at higher risk who would most benefit from chemoprevention, screening, and other risk-reducing strategies. [ABSTRACT FROM AUTHOR]

Background: The Cardiac Arrest Survival Postresuscitation In-hospital (CASPRI) score is a useful tool for predicting neurological outcome following in-hospital cardiac arrest (IHCA), and was derived from a cohort selected from the Get With The Guidelines-Resuscitation registry between 2000 and 2009 in the United States. In an East Asian population, we aimed to identify the factors associated with outcomes of resuscitated IHCA patients and assess the validity of the CASPRI score. Methods: A retrospective study was conducted in a single centre in Taiwan. Patients with IHCA between 2006 and 2014 were screened. Results: Among the 796 included patients, 94 (11.8%) patients achieved neurologically intact survival. Multivariable logistic regression analyses identified factors significantly associated with neurological outcome. Six of these factors were also components of the CASPRI score, including duration of resuscitation, neurological status before IHCA, malignant disease, initial arrest rhythms, renal insufficiency and age. In univariate logistic regression analysis, the CASPRI score was significantly associated with neurological outcome (odds ratio [OR]: 0.83, 95% confidence interval [CI]: 0.80–0.87); the area under the receiver operating characteristics curve was 0.79 (95% CI: 0.74–0.84). Conclusion: In this retrospective study conducted in a single centre at Taiwan, we identified the common prognosticators of IHCA shared by both East Asian and Western societies. As a composite prognosticator, CASPRI score predicts outcomes with excellent accuracy among successfully resuscitated IHCA patients in an East Asian population. This tool allows accurate IHCA prognostication in an East Asian population. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to clarify whether serum matrix metalloproteinase 3 (MMP-3) levels are associated with an effect of iguratimod as add-on therapy to biological DMARDs (bDMARDs) in patients with rheumatoid arthritis (RA). Methods: Forty three patients with RA were treated with iguratimod as add-on therapy to bDMARDs. They were classified into remission and non-remission groups at 24 weeks of iguratimod therapy. Remission was defined as a state with a disease activity score (DAS) <2.6 in 28 joints (termed DAS remission) and total power Doppler ultrasound (US) score <3 (termed US remission). The serum MMP-3 levels at baseline and at 12 weeks were compared between these two groups. Results: There were no significant differences in the serum MMP-3 levels at baseline between the DAS and US remission groups and the non-remission group. The serum MMP-3 levels at 12 weeks in the US remission group were significantly lower than those in the non-remission group. The ratios of the serum MMP-3 levels at baseline to those at 12 weeks in both the DAS and US remission groups were significantly lower than those in the non-remission group. An MMP-3 ratio <0.86 was determined as the cut-off value to predict US remission at 24 weeks. Conclusion: Our findings suggest that the ratios of the serum MMP-3 levels at baseline to those at 12 weeks could be used to predict remission in RA patients who are administered iguratimod as an add-on to bDMARDs. [ABSTRACT FROM AUTHOR]

This study’s objective was to describe long-term trends and patterns in first cigarette use (cigarette initiation) and daily cigarette use (daily initiation) among youth and young adults in the U.S. We used cross-sectional survey data from the National Survey on Drug Use and Health, 2002–2015, to estimate annual incidence of first cigarette use (N = 270,556) and first daily cigarette use (N = 373,464) for each year by age groups, race/ethnicity and gender, examining trends over time and the average annual change in initiation for each group. Several clear patterns emerged: 1) cigarette initiation and daily initiation significantly decreased over time among those aged 12–14 and 15–17 and these trends were consistent among nearly all racial/ethnic and gender subgroups; 2) among 18–21 year olds, cigarette initiation sharply increased through 2009, surpassing rates among 15–17 year olds, and sharply declined through 2015 while remaining higher than rates among the younger group, and this trend was consistent for almost all racial/ethnic subgroups; 3) daily initiation for those aged 18–21 significantly declined, and this was significant among most subgroups 4) there was no change in cigarette initiation and daily initiation for 22–25 year olds overall and most subgroups; 5) there was a significant increase in cigarette initiation for 22–25 year old Hispanics males and daily initiation for 22–25 year old males. This study provides a comprehensive look at trends in cigarette and daily initiation among U.S. youth and young adults. Despite notable declines in smoking initiation among youth and young adult populations over the last two decades, targeted prevention and policy efforts are needed for subgroups at higher risk, including young adults and Hispanic males. [ABSTRACT FROM AUTHOR]

Introduction: Early diagnosis of cutaneous melanoma is critical in preventing melanoma-associated deaths, but the role of primary care providers (PCPs) in diagnosing melanoma is underexplored. We aimed to explore the association of PCP density with melanoma incidence and mortality. Methods: All cases of cutaneous melanoma diagnosed in the United States from 2008–2012 and reported in the Surveillance, Epidemiology, and End Results (SEER) database were analyzed in 2016. County-level primary care physician density was obtained from the Area Health Resources File (AHRF). We conducted multivariate linear regression using 1) average annual melanoma incidence or 2) average annual melanoma mortality by county as primary outcomes, adjusting for demographic confounders and dermatologist density. Cox proportional hazard regression was conducted using individual outcome data from SEER with the same covariates. Results: Across 611 counties, 167,305 cases of melanoma were analyzed. Per 100,000 people, an additional 10 PCPs per county was associated with 1.62 additional cases of melanoma per year (95% CI 1.06–2.18, p<0.001). This increased incidence occurred disproportionally in early-stage melanoma (Stage 0: 0.69 cases (0.38–1.00), p<0.001; Stage I: 0.63 cases (0.37–0.89), p<0.001; Stage II: 0.11 cases (0.03–0.19), p = 0.005). There was no statistically significant association between PCP density and incidence of stage III or IV melanoma, or with melanoma-specific mortality. Survival analysis demonstrated elimination of 5-year post-diagnosis mortality risk in medically underserved counties after adjusting for stage. Conclusions: Higher densities of PCPs may be linked to increased diagnosis of early-stage melanoma without corresponding decreases in late-stage diagnoses or melanoma-associated mortality. [ABSTRACT FROM AUTHOR]

For patients with chronic lower respiratory disease, hypobaric hypoxia at a high altitude is considered a risk factor for mortality. However, the effects of residing at moderately high altitudes remain unclear. We investigated the association between moderate altitude and chronic lower respiratory disease mortality. In particular, we examined the lower 48 United States counties for age-adjusted chronic lower respiratory disease mortality rates, altitude, and socioeconomic factors, including tobacco use, per capita income, population density, sex ratio, unemployment, poverty, and education between 1979 and 1998. The socioeconomic factors were incorporated into the correlation analysis as potential covariates. Considerable positive (R = 0.235; P <0.001) and partial (R = 0.260; P <0.001) correlations were observed between altitude and chronic lower respiratory disease mortality rate. In the subgroup with high COPD prevalence subgroup, even stronger positive (R = 0.346; P <0.001) and partial (R = 0.423, P <0.001) correlations were observed. Multivariate regression analysis of all available socioeconomic factors revealed that additional knowledge on altitude improved the adjusted R2 values from 0.128 to 0.186 for all counties and from 0.301 to 0.421 for counties with high COPD prevalence. We concluded that in the lower 48 United States counties, even a moderate altitude may pose considerable risks in patients with chronic lower respiratory disease. [ABSTRACT FROM AUTHOR]

Background: In many regions globally, buildings designed for harnessing heat during the cold exacerbate thermal exposures during heat waves (HWs) by maintaining elevated indoor temperatures even when high ambient temperatures have subdued. While previous experimental studies have documented the effects of ambient temperatures on cognitive function, few have observed HW effects on indoor temperatures following subjects' habitual conditions. The objective was to evaluate the differential impact of having air conditioning (AC) on cognitive function during a HW among residents of AC and non-AC buildings using a prospective observational cohort study.Methods: We followed 44 students (mean age = 20.2 years; SD = 1.8 years) from a university in the Greater Boston area, Massachusetts in the United States living in AC (n = 24) and non-AC (n = 20) buildings before, during, and after a HW. Two cognition tests were self-administered daily for a period of 12 days (July 9-July 20, 2016), the Stroop color-word test (STROOP) to assess selective attention/processing speed and a 2-digit, visual addition/subtraction test (ADD) to evaluate cognitive speed and working memory. The effect of the HW on cognitive function was evaluated using difference-in-differences (DiD) modelling.Findings: Mean indoor temperatures in the non-AC group (mean = 26.3°C; SD = 2.5°C; range = 19.6-30.4°C) were significantly higher (p < 0.001) than in the AC group (mean = 21.4°C; SD = 1.9°C; range = 17.5-25.0°C). DiD estimates show an increase in reaction time (STROOP = 13.4%, p < 0001; ADD = 13.3%, p < 0.001) and reduction in throughput (STROOP = -9.9%, p < 0.001; ADD = -6.3%, p = 0.08) during HWs among non-AC residents relative to AC residents at baseline. While ADD showed a linear relationship with indoor temperatures, STROOP was described by a U-shaped curve with linear effects below and above an optimum range (indoor temperature = 22°C-23°C), with an increase in reaction time of 16 ms/°C and 24 ms/°C for STROOP and ADD, respectively. Cognitive tests occurred right after waking, so the study is limited in that it cannot assess whether the observed effects extended during the rest of the day. Although the range of students' ages also represents a limitation of the study, the consistent findings in this young, healthy population might indicate that greater portions of the population are susceptible to the effects of extreme heat.Conclusions: Cognitive function deficits resulting from indoor thermal conditions during HWs extend beyond vulnerable populations. Our findings highlight the importance of incorporating sustainable adaptation measures in buildings to preserve educational attainment, economic productivity, and safety in light of a changing climate. [ABSTRACT FROM AUTHOR]