Emergency risk communication (ERC) programs that activate when the ambient temperature is expected to cross certain extreme thresholds are widely used to manage relevant public health risks. In practice, however, the effectiveness of these thresholds has rarely been examined. The goal of this study is to test if the activation criteria based on extreme temperature thresholds, both cold and heat, capture elevated health risks for all-cause and cause-specific mortality and morbidity in the Minneapolis-St. Paul Metropolitan Area. A distributed lag nonlinear model (DLNM) combined with a quasi-Poisson generalized linear model is used to derive the exposure–response functions between daily maximum heat index and mortality (1998–2014) and morbidity (emergency department visits; 2007–2014). Specific causes considered include cardiovascular, respiratory, renal diseases, and diabetes. Six extreme temperature thresholds, corresponding to 1st–3rd and 97th–99th percentiles of local exposure history, are examined. All six extreme temperature thresholds capture significantly increased relative risks for all-cause mortality and morbidity. However, the cause-specific analyses reveal heterogeneity. Extreme cold thresholds capture increased mortality and morbidity risks for cardiovascular and respiratory diseases and extreme heat thresholds for renal disease. Percentile-based extreme temperature thresholds are appropriate for initiating ERC targeting the general population. Tailoring ERC by specific causes may protect some but not all individuals with health conditions exacerbated by hazardous ambient temperature exposure.

Interference occurs when the treatment (or exposure) of one individual affects the outcomes of others. In some settings it may be reasonable to assume individuals can be partitioned into clusters such that there is no interference between individuals in different clusters, i.e., there is partial interference. In observational studies with partial interference, inverse probability weighted (IPW) estimators have been proposed of different possible treatment effects. However, the validity of IPW estimators depends on the propensity score being known or correctly modeled. Alternatively, one can estimate the treatment effect using an outcome regression model. In this paper, we propose doubly robust (DR) estimators which utilize both models and are consistent and asymptotically normal if either model, but not necessarily both, is correctly specified. Empirical results are presented to demonstrate the DR property of the proposed estimators, as well as the efficiency gain of DR over IPW estimators when both models are correctly specified. The different estimators are illustrated using data from a study examining the effects of cholera vaccination in Bangladesh.

Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from which pinpointing causal genes remains challenging. Here we combined data from 718,734 individuals to discover rare and low-frequency (minor allele frequency (MAF) < 5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which 8 variants were in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2 and ZNF169) newly implicated in human obesity, 2 variants were in genes (MC4R and KSR2) previously observed to be mutated in extreme obesity and 2 variants were in GIPR. The effect sizes of rare variants are ~10 times larger than those of common variants, with the largest effect observed in carriers of an MC4R mutation introducing a stop codon (p.Tyr35Ter, MAF = 0.01%), who weighed ~7 kg more than non-carriers. Pathway analyses based on the variants associated with BMI confirm enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically supported therapeutic targets in obesity.

© 2018 The Authors. Journal of the International AIDS Society published by John Wiley & sons Ltd on behalf of the International AIDS Society. Introduction: Migration of men who have sex with men (MSM) from rural to urban areas is common across low- and middle-income countries and is widely believed to contribute to elevated HIV risk among migrant MSM in urban areas. Little consensus exists on whether their risk is due to their transplantation or their being from resource-constrained rural areas. This study seeks to clarify the relationship between migration and HIV risks by comparing differences in HIV-related risky sexual behaviours and healthcare utilization across competing conceptualizations of migratory statuses. Methods: In July 2016, MSM ≥16 years old currently residing in one of eight urban cities in China were recruited for an online cross-sectional survey, which collected information on socio-demographics, sexual behaviours, HIV care-seeking behaviours, and healthcare utilization. Based on a question about residency status, each participant was classified as an urban local resident, urban transplant, or rural transplant. Multivariable multinomial logistic regression was used to examine the associations between risky behaviours and healthcare utilization among these three groups. Results: Among 2007 MSM, the proportion of local, urban transplant and rural transplant were 32% (648/2007), 24% (478/2007), and 44% (881/2007), respectively. Compared with urban local resident MSM, urban transplant MSM were more likely to have ever tested for HIV (adjusted odds ratio (aOR) = 1.39, 95% confidence interval (CI): 1.08 to 1.80). Compared with urban transplant MSM, rural transplant MSM were less likely to have utilized any governmental sexual health services in the past three months (aOR = 0.75, 95% CI: 0.60 to 0.93), ever tested for HIV (aOR = 0.77, 95% CI: 0.61 to 0.96), ever initiated antiretroviral therapy (ART) (aOR = 0.16, 95% CI: 0.05 to 0.52), and ever purchased sex (aOR = 0.57, 95% CI: 0.38 to 0.85). No other significant differences were found in sexual behaviours among three groups. Conclusions: The widely used local/migrant categorization obscures important differences in HIV risk present between urban/rural subgroups among them. Previous studies of HIV risks in Chinese "migrant" may have failed to consider the role of structural factors such as discrimination or barriers to healthcare when interpreting their findings of higher HIV prevalence in this population. Low ART uptake among rural transplant MSM in this study is particularly concerning and underscore the need for HIV-related interventions tailored for this group.

Synaptic transmission and its activity-dependent modulation, known as synaptic plasticity, are fundamental processes in the nervous system function. Neurons may receive thousands of synaptic contacts, but synaptic regulation may occur only at individual or discrete subsets of synapses, which may have important consequences on the spatial extension of the modulation of synaptic information. Moreover, while several electrophysiological methods are used to assess synaptic transmission at different levels of observation, i.e, through local field potential and individual whole-cell recordings, their experimental limitations to detect synapse-specific modulation is poorly defined. We have investigated how well-known synapse-specific short-term plasticity, where some synapses are regulated and others left unregulated, mediated by astrocytes and endocannabinoid signaling can be assessed at different observational levels. Using hippocampal slices, we have combined local field potential and whole-cell recordings of CA3-CA1 synaptic activity evoked by Schaffer collateral stimulation of either multiple or single synapses through bulk or minimal stimulation, respectively, to test the ability to detect short-term synaptic changes induced by endocannabinoid signaling. We also developed a mathematical model assuming a bimodal distribution of regulated and unregulated synapses based on realistic experimental data to simulate physiological results and to predict the experimental requirements of the different recording methods to detect discrete changes in subsets of synapses. We show that endocannabinoid-induced depolarization-induced suppression of excitation (DSE) and astrocyte-mediated synaptic potentiation can be observed when monitoring single or few synapses, but are statistically concealed when recording the activity of a large number of synapses. These results indicate that the electrophysiological methodology is critical to properly assess synaptic changes occurring in subsets of synapses, and they suggest that relevant synapse-specific regulatory phenomena may be experimentally undetected but may have important implications in the spatial extension of synaptic plasticity phenomena.

When the primary outcome is difficult to collect, surrogate endpoint is typically used as a substitute. It is possible that for every individual, treatment has a positive effect on surrogate, and surrogate has a positive effect on primary outcome, but for some individuals, treatment has a negative effect on primary outcome. For example, a treatment may be substantially effective in preventing the stroke for everyone, and lowering the risk of stroke is universally beneficial for a longer survival time, however, the treatment may still cause death for some individuals. We define such paradoxical phenomenon as individual surrogate paradox. The individual surrogate paradox is preposed to capture the treatment effect heterogeneity, which is unable to be described by either the surrogate paradox based on average causal effect (ACE) (Chen et al., 2007) or that based on distributional causal effect (DCE) (Ju and Geng, 2010). We investigate existing surrogate criteria in terms of whether the individual surrogate paradox could manifest. We find that only the strong binary surrogate can avoid such paradox without additional assumptions. Utilizing the sharp bounds, we propose novel criteria to exclude the individual surrogate paradox. Our methods are illustrated in an application to determine the effect of the intensive glycemia on the risk of development or progression of diabetic retinopathy.

Background Tobacco taxation and smoke-free workplaces reduce smoking, tobacco-related premature deaths and associated out-of- pocket health care expenditures. We examine the distributional consequences of a price increase in tobacco products through an excise tax hike, and of an implementation of smoke-free workplaces, in China. Methods We use extended cost-effectiveness analysis (ECEA) to evaluate, across income quintiles of the male population (the large majority of Chinese smokers), the premature deaths averted, the change in tax revenues generated, and the financial risk protection procured (eg, poverty cases averted, defined as the number of individuals no longer facing tobacco-related out-of-pocket expenditures for disease treatment, that would otherwise impoverish them), that would follow a 75% increase in cigarette prices through substantial increments in excise tax fully passed onto consumers, and a nationwide total implementation of workplace smoking bans. Results A 75% increase in cigarette prices would avert about 24 million premature deaths among the current Chinese male population, with a third among the bottom income quintile, increase additional tax revenues by US$ 46 billion annually, and prevent around 9 million poverty cases, 19% of which among the bottom income quintile. Implementation of smoking bans in workplaces would avert about 12 million premature deaths, with a fifth among the bottom income quintile, decrease tax revenues by US$ 7 billion annually, and prevent around 4 million poverty cases, 12% of which among the bottom income quintile. Conclusions Increased excise taxes on tobacco products and workplace smoking bans can procure large health and economic benefits to the Chinese population, especially among the poor.

© 2017 The Author(s). Background: HIV testing for marginalized populations is critical to controlling the HIV epidemic. However, the HIV testing rate among men who have sex with men (MSM) in China remains low. Crowdsourcing, the process of shifting individual tasks to a group, has been increasingly adopted in public health programs and may be a useful tool for spurring innovation in HIV testing campaigns. We designed a multi-site study to develop a crowdsourced HIV test promotion campaign and evaluate its effectiveness against conventional campaigns among MSM in China. Methods: This study will use an adaptation of the stepped wedge, randomized controlled trial design. A total of eight major metropolitan cities in China will be randomized to sequentially initiate interventions at 3-month intervals. The intervention uses crowdsourcing at multiple steps to sustain crowd contribution. Approximately 1280 MSM, who are 16 years of age or over, live in the intervention city, have not been tested for HIV in the past 3 mmonths, and are not living with HIV, will be recruited. Recruitment will take place through banner advertisements on a large gay dating app along with other social media platforms. Participants will complete one follow-up survey every 3 months for 12 months to evaluate their HIV testing uptake in the past 3 months and secondary outcomes including syphilis testing, sex without condoms, community engagement, testing stigma, and other related outcomes. Discussion: MSM HIV testing rates remain poor in China. Innovative methods to promote HIV testing are urgently needed. With a large-scale, stepped wedge, randomized controlled trial our study can improve understanding of crowdsourcing's long-term effectiveness in public health campaigns, expand HIV testing coverage among a key population, and inform intervention design in related public health fields. Trial Registration: ClinicalTrials.gov, NCT02796963. Registered on 23 May 2016.

Background Sustained viral suppression through ART reduces sexual HIV transmission risk, but may require routine access to reliable and effective medical care which may be difficult to obtain in resource constrained areas. We investigated the roles of patient load and travel distance to HIV care clinic on transmission risk in HIV serodiscordant couples in Henan Province, China. Methods Cox proportional hazard models were used to compare HIV transmission events across couples living near, medium, or farther distances from their assigned HIV care clinics, as well as those attending clinics where clinicians bore high versus low patient loads. Results Most (84 · 4%) of the 3695 serodiscordant couples lived within 10 kilometers of their assigned HIV clinic, and most (73 · 5%) attended clinics with patient-to-provider ratios of at least 100:1. In adjusted Cox models, attending clinics where clinicians bore average patient loads of 100 or more elevated HIV transmission risk (aHR, 1 · 50, 95% CI, 1 · 00-4 · 84), an effect amplified in village tier clinics (aHR = 1 · 55; 95% CI, 1 · 23-6 · 78). Travel distance was associated with HIV transmission only after stratification; traveling medium distances to village clinics (5-10km) increased transmission risk (aHR = 1 · 83, 95% CI, 1 · 04-3 · 21) whereas traveling longer distances to township or county level clinics lowered transmission risk (aHR = 0 · 10, 95% CI, 0 · 01-0 · 75). Conclusion Higher patient loads at HIV clinics was associated with risk of HIV transmission in our population, particularly at village level clinics. Farther travel distance had divergent effects based on clinic tier, suggesting unique mechanisms operating across levels of resource availability. The resource intensity of long-term HIV treatment may place significant strains on small rural clinics, for which investments in additional support staff or time-saving tools such as point-of-care laboratory testing may bring about impactful change in treatment outcomes.This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Missing data occur frequently in empirical studies in health and social sciences, often compromising our ability to make accurate inferences. An outcome is said to be missing not at random (MNAR) if, conditional on the observed variables, the missing data mechanism still depends on the unobserved outcome. In such settings, identification is generally not possible without imposing additional assumptions. Identification is sometimes possible, however, if an instrumental variable (IV) is observed for all subjects which satisfies the exclusion restriction that the IV affects the missingness process without directly influencing the outcome. In this paper, we provide necessary and sufficient conditions for nonparametric identification of the full data distribution under MNAR with the aid of an IV. In addition, we give sufficient identification conditions that are more straightforward to verify in practice. For inference, we focus on estimation of a population outcome mean, for which we develop a suite of semiparametric estimators that extend methods previously developed for data missing at random. Specifically, we propose inverse probability weighted estimation, outcome regression-based estimation and doubly robust estimation of the mean of an outcome subject to MNAR. For illustration, the methods are used to account for selection bias induced by HIV testing refusal in the evaluation of HIV seroprevalence in Mochudi, Botswana, using interviewer characteristics such as gender, age and years of experience as IVs.

The average treatment effect (ATE) is popularly used to assess the treatment effect. However, the ATE implicitly assumes a homogenous treatment effect even amongst individuals with different characteristics. In this paper, we mainly focus on assessing the treatment effect heterogeneity, which has important implications in designing the optimal individual treatment regimens and in policy making. The treatment benefit rate (TBR) and treatment harm rate (THR) have been defined to characterize the magnitude of heterogeneity for binary outcomes. When the outcomes are continuous, we extend the definitions of the TBR and THR to compare the difference between potential outcomes with a pre-specified level c. Unlike the ATE, these rates involve the joint distribution of the potential outcomes and can not be identified without further assumptions even in randomized clinical trials. In this article, we assume the potential outcomes are independent conditional on the observed covariates and an unmeasured latent variable. Under this assumption, we prove the identification of the TBR and THR in non-separable (generalized) linear models for both continuous and binary outcomes. We then propose estimators and derive their asymptotic distributions. In the simulation studies, we implement our proposed methods to assess the performance of our estimators and carry out a sensitive analysis for different underlying distribution for the latent variable. Finally, we illustrate the proposed methods in two randomized controlled trials.

When the primary outcome is hard to collect, surrogate endpoint is typically used as a substitute. However, even when the treatment has a positive average causal effect (ACE) on the surrogate endpoint, which also has a positive ACE on the primary outcome, it is still possible that the treatment has a negative ACE on the primary outcome. Such a phenomenon is called the surrogate paradox and greatly challenges the use of surrogate. In this paper, we provide novel criteria to exclude the surrogate paradox. Unlike other conditions previously proposed, our conditions are testable since they only involve observed data. Furthermore, our criteria are optimal in the sense that they are sufficient and "almost necessary" to exclude the paradox: if the conditions are satisfied, the surrogate paradox is guaranteed to be absent while if the conditions fail, there exists a data generating process with surrogate paradox that can generate the same observed data. That is, our criteria capture all the information in the observed data to exclude the surrogate paradox rather than relying on unverifiable distributional assumptions.

BACKGROUND: Antiretroviral therapy (ART) administered in clinical trial settings virtually eliminates the sexual transmission of human immunodeficiency virus (HIV) in serodiscordant couples, but effectiveness of treatment as prevention in the community is debated. Conflicting results from previous analyses in a Chinese cohort underscore the importance of determining effectiveness of ART delivered in resource limited settings.\n\nMETHODS: All available years of data (2006-2012) from local disease control records of HIV patients and their seronegative spouses in Henan Province, China, were analyzed using marginal structural Cox models to estimate the effect of ART in the initially infected partner his or her partner's HIV seroconversion risk.\n\nRESULTS: We observed 157 seroconversion events in 4916 serosdiscordant couples, for an incidence rate of 0.59 cases per 100 person-years (PY) (95% confidence interval [CI], .51-.70). Of these, 84 occurred after the index partner had initiated ART (0.43/100PY; 95% CI, .35-.53) and 73, whereas index partners were untreated (5.87/100 PY; 95% CI, 4.65-7.42). In a marginal structural Cox model weighted for confounding and censoring, the hazard ratio (HR) for HIV transmission was 0.52 (95% CI, .34-.82). ART efficacy varied significantly by time period; least effective in the early phase from 2006 to 2008 (HR, 0.68; 95% CI, .34-1.36) but far more protective from 2009 onward (HR, 0.33; 95% CI, .20-.55).\n\nCONCLUSIONS: ART can provide HIV-infected persons in resource-limited setting substantial protection against sexual transmission. Effectiveness in the Henan cohort appears to have increased over time, suggesting that quality of care and service infrastructure may be integral to successful use of treatment for prevention.

BACKGROUND In 2010, Nicaragua implemented an adult immunization program with the 23-valent pneumococcal polysaccharide vaccine (PPSV-23) and a pediatric immunization program with the 13-valent pneumococcal conjugate vaccine (PCV-13). We assessed incidence rates of ambulatory visits and hospitalizations for pneumonia and pneumonia-related mortality in adults over the age of 50 years before and after the program's implementation in the Department of León, Nicaragua. METHODS We collected visit diagnoses from all 107 public health facilities between 2008 and 2012 in León. We compared incidence rates of ambulatory visits for pneumonia, pneumonia hospitalizations, and pneumonia-related mortality in the pre-vaccine (2008–2009) and vaccine (2011–2012) periods among older adults using Poisson regression with generalized estimating equations (GEE), controlling for age group, municipality, and proportions of adults who were immunized against influenza. Exposure time was estimated by official municipality population estimates. RESULTS We did not observe lower incidence rates of ambulatory visits or hospitalizations for pneumonia among adults during the vaccine period versus the pre-vaccine period. However, pneumonia-related mortality was lower in the vaccine period versus the pre-vaccine period, with an adjusted incidence rate ratio (IRRa) of 0.73 (0.56, 0.94) among adults aged 50–64 years, and 0.55 (0.43, 0.70) among adults aged ≥65 years. CONCLUSIONS These early results following introduction of a combined pediatric and adult pneumococcal immunization program in Nicaragua show a probable impact of the program on the reduction of pneumonia-related deaths in older adults, but a less clear impact on the reduction of health facility visits for pneumonia.

In observational studies, treatments are typically not randomized and therefore estimated treatment effects may be subject to confounding bias. The instrumental variable (IV) design plays the role of a quasi-experimental handle since the IV is associated with the treatment and only affects the outcome through the treatment. In this paper, we present a novel framework for identification and inference using an IV for the marginal average treatment effect amongst the treated (ETT) in the presence of unmeasured confounding. For inference, we propose three different semiparametric approaches: (i) inverse probability weighting (IPW), (ii) outcome regression (OR), and (iii) doubly robust (DR) estimation, which is consistent if either (i) or (ii) is consistent, but not necessarily both. A closed-form locally semiparametric efficient estimator is obtained in the simple case of binary IV and outcome and the efficiency bound is derived for the more general case.

Copyright © 2015 Wolters Kluwer Health, Inc. The Public Health Workforce Interests and Needs Survey (PH WINS) has yielded the first-ever nationally representative sample of state health agency central office employees. The survey represents a step forward in rigorous, systematic data collection to inform the public health workforce development agenda in the United States. PH WINS is a Web-based survey and was developed with guidance from a panel of public health workforce experts including practitioners and researchers. It draws heavily from existing and validated items and focuses on 4 main areas: workforce perceptions about training needs, workplace environment and job satisfaction, perceptions about national trends, and demographics. This article outlines the conceptualization, development, and implementation of PH WINS, as well as considerations and limitations. It also describes the creation of 2 new data sets that will be available in public use for public health officials and researchers\-A nationally representative data set for permanently employed state health agency central office employees comprising over 10 000 responses, and a pilot data set with approximately 12 000 local and regional health department staff responses.