Within-City Variation in Ambient Carbon Monoxide Concentrations: Leveraging Low-Cost Monitors in a Spatiotemporal Modeling Framework.

BACKGROUND: Based on human and animal experimental studies, exposure to ambient carbon monoxide (CO) may be associated with cardiovascular disease outcomes, but epidemiological evidence of this link is limited. The number and distribution of ground-level regulatory agency monitors are insufficient to characterize fine-scale variations in CO concentrations. OBJECTIVES: To develop a daily, high-resolution ambient CO exposure prediction model at the city scale. METHODS: We developed a CO prediction model in Baltimore, Maryland, based on a spatiotemporal statistical algorithm with regulatory agency monitoring data and measurements from calibrated low-cost gas monitors. We also evaluated the contribution of three novel parameters to model performance: high-resolution meteorological data, satellite remote sensing data, and copollutant (PM2.5, NO2, and NOx) concentrations. RESULTS: The CO model had spatial cross-validation (CV) R2 and root-mean-square error (RMSE) of 0.70 and 0.02 parts per million (ppm), respectively; the model had temporal CV R2 and RMSE of 0.61 and 0.04 ppm, respectively. The predictions revealed spatially resolved CO hot spots associated with population, traffic, and other nonroad emission sources (e.g., railroads and airport), as well as sharp concentration decreases within short distances from primary roads. DISCUSSION: The three novel parameters did not substantially improve model performance, suggesting that, on its own, our spatiotemporal modeling framework based on geographic features was reliable and robust. As low-cost air monitors become increasingly available, this approach to CO concentration modeling can be generalized to resource-restricted environments to facilitate comprehensive epidemiological research. https://doi.org/10.1289/EHP10889.

Differences in Stress and Anxiety Among Women With and Without Children in the Household During the Early Months of the COVID-19 Pandemic.

The COVID-19 pandemic and resulting lockdowns have had a disproportionate impact on parents of children under 18, particularly women. Mandatory school closures and loss of childcare resulted in parents balancing work, teaching, and childcare needs. A number of studies have examined changes in mental health of parents, but to date no studies have compared the differences in stress and anxiety levels between women with and without children in the United States. Adult women from the Washington State Twin Registry (WSTR) (N = 1,014, pair N = 529) and mothers of twin children enrolled in the WSTR (N = 147) completed an online survey examining several health-related behaviors and outcomes and their self-reported changes due to COVID-19. We conducted two studies to examine the impact of children on stress and anxiety levels among women. In study 1, we assessed whether women living in households with children under the age of 18 have higher levels of stress and anxiety than those without children in their household. We found that perceived stress levels did not differ between women with and without children in the household, but anxiety levels were higher among women living with children than those without. In study 2, we assessed whether the correlation between children in the household and stress/anxiety is accounted for by non-random genetic and environmental selection effects, causal processes, or both using a sample of adult female twins. We found that the presence of children in the household was associated with higher levels of stress and anxiety. However, this association is confounded by genetic and shared environmental factors. Our findings highlight the need to provide supporting resources to women living with children in the household during and after the COVID-19 pandemic.

Quantifying the Distribution of Environmental Health Threats and Hazards in Washington State Using a Cumulative Environmental Inequality Index.

Background: Environmental racism, community stressors, and age-related susceptibility play a significant role in environmental inequality. The goal of this article was to use an inequality index (II) to assess the level of equality in environmental threats and hazards based on race, poverty, and age in Washington State. Methods: Using the Washington Environmental Health Disparities Map, we quantified the level of disproportionate burdens on communities with greater populations of people of color, people in poverty, children younger than 5, and people older than 65 using 3 cumulative environmental indices and 10 individual environmental indicators. Results: Census tracts with a higher proportion of people of color and those with people living below 185% federal poverty levels were found to be disproportionately burdened by environmental threats (II = -0.175 and II = -0.167, respectively, p < 0.001). Individual environmental indicators were found to disproportionately burden communities of color and low-income communities. Children younger than 5 were also disproportionately burdened by cumulative environmental indices (II = -0.076, p < 0.001) and individual indicators. Our analysis did not show disproportionate burden of environmental health threats based on the proportion of people older than 65 (II = 0.124, p < 0.001). Discussion: The disproportionate burden of the cumulative environmental threats on communities of color and low-income communities in this study corroborates similar analyses. These findings can be applied in policy and regulatory actions to correct the distributive environmental disparities. Conclusion: We found much higher burdens among historically marginalized communities and children who are more susceptible to environmental threats and hazards.

Is COVID-19 Keeping us Up at Night? Stress, Anxiety, and Sleep Among Adult Twins.

In response to the COVID-19 pandemic, a variety of social distancing measures to mitigate the virus outbreak have been implemented. These measures may have unintended consequences on individuals' well-being, such as increased stress, anxiety, and sleep disruptions. We investigated the extent to which individuals' mental health status is associated with perceived changes in sleep amount and sleep quality among a sample of adult twin pairs (N = 909 pairs; 77% MZ, 23% DZ), less than a month after the outbreak was declared a pandemic by the World Health Organization. About half of participants reported no change in sleep amount (50.1%) or sleep quality (55.6%). Approximately one-third of the participants had increased amount of sleep (29.8%), and 32.9% reported a decrease in sleep quality. We found that stress and anxiety levels were associated with sleep reduction (ORs = 2.36 and 3.12 for stress and anxiety, respectively) and poorer sleep quality (ORs = 2.45 and 3.73 for stress and anxiety, respectively), even after taking into account between-family confounds. A much smaller association was observed between levels of stress and anxiety and increased sleep amount (ORs = 1.42 and 1.60 for stress and anxiety, respectively) and sleep quality (OR = 1.21 and 1.29 for stress and anxiety, respectively), which was no longer significant after controlling for between-family confounds. Our results demonstrate that stress and anxiety associated with the COVID-19 pandemic and social distancing measures may be linked to reduced sleep amount and quality.

Does surrounding greenness moderate the relationship between apparent temperature and physical activity? Findings from the PHENOTYPE project.

BACKGROUND: Physical activity can be affected by both meteorological conditions and surrounding greenness, but few studies have evaluated the effects of these environmental factors on physical activity simultaneously. This multi-city comparative study aimed to assess the synergetic effects of apparent temperature and surrounding greenness on physical activity in four European cities. Specifically, we aimed to identify an interaction between surrounding greenness and apparent temperature in the effects on physical activity. METHODS: Data were collected from 352 adult residents of Barcelona (Spain), Stoke-on-Trent (United Kingdom), Doetinchem (The Netherlands), and Kaunas (Lithuania) as part of the PHENOTYPE study. Participants wore a smartphone for seven consecutive days between May-December 2013 and provided additional sociodemographic survey data. Hourly average physical activity (Metabolic Equivalent of Task (MET)) and surrounding greenness (NDVI) were derived from the Calfit mobile application collecting accelerometer and location data. Hourly apparent temperature was calculated from temperature and relative humidity, which were obtained from local meteorological stations along with other meteorological covariates (rainfall, windspeed, and sky darkness). We assessed the interaction effects of apparent temperature and surrounding greenness on hourly physical activity for each city using linear mixed models, while adjusting for meteorological, demographic, and time-related variables. RESULTS: We found significant interactions between apparent temperature and surrounding greenness on hourly physical activity in three of four cities, aside from the coastal city of Barcelona. Significant quadratic effects of apparent temperature were found in the highest level of surrounding greenness for Stoke-on-Trent and Doetinchem, with 4% decrease in median MET observed for a 10°C departure from optimal temperature (15.2°C and 14.6°C, respectively). Significant linear effects were found for higher levels of surrounding greenness in Kaunas, whereby an increase of 10°C was associated with ∼4% increase in median MET. CONCLUSION: Apparent temperature and surrounding greenness interacted in the effect on hourly physical activity across three of four European cities, with varying effect between cities. While quadratic effects of temperature suggest diminishing levels of physical activity in the highest greenness levels in cities of temperate climates, the variation in surrounding greenness between cities could be further explored, particularly by looking at indoor-outdoor locations. The study findings support the need for evidence-based physical activity promotion and urban design.

Stress, Anxiety, and Change in Alcohol Use During the COVID-19 Pandemic: Findings Among Adult Twin Pairs.

The novel coronavirus (COVID-19) has impacted the lives of people worldwide since being declared a pandemic on March 11, 2020. Social restrictions aimed at flattening the curve may be associated with an increase in stress and anxiety, which may increase the use of alcohol as a coping mechanism. The objective of this study was to examine if stress and anxiety were associated with changes in alcohol use in a sample of adult twins. Twins allowed us to control for genetic and shared environmental factors that would confound the alcohol - mental health relationship. Twins (N = 3,971; 909 same-sex pairs) from the Washington State Twin Registry (WSTR) completed an online survey examining several health-related behaviors and outcomes and their self-reported changes due to COVID-19. About 14% of the respondents reported an increase in alcohol use. We found an association between both stress and anxiety and increased alcohol use, where twins with higher levels of stress and anxiety were more likely to report an increase in alcohol consumption. The associations were small and confounded by between-family factors and demographic characteristics. However, there was no significant difference in stress or anxiety levels between non-drinkers and those who reported no change in alcohol use. Our findings suggest that individuals' mental health may be associated with changes in alcohol use during the COVID-19 pandemic.

Developing a Low-Cost Passive Method for Long-Term Average Levels of Light-Absorbing Carbon Air Pollution in Polluted Indoor Environments.

We propose a low-cost passive method for monitoring long-term average levels of light-absorbing carbon air pollution in polluted indoor environments. Building on prior work, the method here estimates the change in reflectance of a passively exposed surface through analysis of digital images. To determine reproducibility and limits of detection, we tested low-cost passive samplers with exposure to kerosene smoke in the laboratory and to environmental pollution in 20 indoor locations. Preliminary results suggest robust reproducibility (r = 0.99) and limits of detection appropriate for longer-term (~1-3 months) monitoring in households that use solid fuels. The results here suggest high precision; further testing involving "gold standard" measurements is needed to investigate accuracy.

Contribution of low-cost sensor measurements to the prediction of PM2.5 levels: A case study in Imperial County, California, USA.

Regulatory monitoring networks are often too sparse to support community-scale PM2.5 exposure assessment while emerging low-cost sensors have the potential to fill in the gaps. To date, limited studies, if any, have been conducted to utilize low-cost sensor measurements to improve PM2.5 prediction with high spatiotemporal resolutions based on statistical models. Imperial County in California is an exemplary region with sparse Air Quality System (AQS) monitors and a community-operated low-cost network entitled Identifying Violations Affecting Neighborhoods (IVAN). This study aims to evaluate the contribution of IVAN measurements to the quality of PM2.5 prediction. We adopted the Random Forest algorithm to estimate daily PM2.5 concentrations at a 1-km spatial resolution using three different PM2.5 datasets (AQS-only, IVAN-only, and AQS/IVAN combined). The results show that the integration of low-cost sensor measurements is an effective way to significantly improve the quality of PM2.5 prediction with an increase of cross-validation (CV) R2 by ~0.2. The IVAN measurements also contributed to the increased importance of emission source-related covariates and more reasonable spatial patterns of PM2.5. The remaining uncertainty in the calibrated IVAN measurements could still cause apparent outliers in the prediction model, highlighting the need for more effective calibration or integration methods to relieve its negative impact.

Spray Drift from Three Airblast Sprayer Technologies in a Modern Orchard Work Environment.

Pesticide spray drift represents an important exposure pathway that may cause illness among orchard workers. To strike a balance between improving spray coverage and reducing drift, new sprayer technologies are being marketed for use in modern tree canopies to replace conventional axial fan airblast (AFA) sprayers that have been used widely since the 1950s. We designed a series of spray trials that used mixed-effects modeling to compare tracer-based drift volume levels for old and new sprayer technologies in an orchard work environment. Building on a smaller study of 6 trials (168 tree rows) that collected polyester line drift samples (n = 270 measurements) suspended on 15 vertical masts downwind of an AFA sprayer application, this study included 9 additional comparison trials (252 tree rows; n = 405 measurements) for 2 airblast tower sprayers: the directed air tower (DAT) and the multi-headed fan tower (MFT). Field-based measurements at mid (26 m) and far (52 m) distances showed that the DAT and MFT sprayers had 4-15 and 35-37% less drift than the AFA. After controlling for downwind distance, sampling height, and wind speed, model results indicated that the MFT [-35%; 95% confidence interval (CI): -22 and -49%; P < 0.001] significantly reduced drift levels compared to the AFA, but the DAT did not (-7%; 95% CI: -19 and 6%; P = 0.29). Tower sprayers appear to be a promising means by which to decrease drift levels through shorter nozzle-to-tree canopy distances and more horizontally directed aerosols that escape the tree canopy to a lesser extent. Substitution of these new technologies for AFA sprayers is likely to reduce the frequency and magnitude of pesticide drift exposures and associated illnesses. These findings, especially for the MFT, may fit United States Environmental Protection Agency's Drift Reduction Technology (DRT) one-star rating of 25-50% reduction. An 'AFA buyback' incentive program could be developed to stimulate wider adoption of new drift-reducing spray technologies. However, improved sprayer technologies alone do not eliminate drift. Applicator training, including proper sprayer calibration and maintenance, and application exclusion zones (AEZs) can also contribute to minimizing the risks of drift exposure. With regard to testing DRTs and establishing AEZs, our study findings demonstrate the need to define the impact of airblast sprayer type, orchard architecture, sampling height, and wind speed.

The Washington State Environmental Health Disparities Map: Development of a Community-Responsive Cumulative Impacts Assessment Tool.

Communities across Washington State have expressed the need for neighborhood-level information on the cumulative impact of environmental hazards and social conditions to illuminate disparities and address environmental justice issues. Many existing mapping tools have not explicitly integrated community voice and lived experience as an integral part of their development. The goals of this project were to create a new community-academic-government partnership to collect and summarize community concerns and to develop a publicly available mapping tool that ranks relative environmental health disparities for populations across Washington State. Using a community-driven framework, we developed the Washington Environmental Health Disparities Map, a cumulative environmental health impacts assessment tool. Nineteen regularly updated environmental and population indicators were integrated into the geospatial tool that allows for comparisons of the cumulative impacts between census tracts. This interactive map provides critical information for the public, agencies, policymakers, and community-based organizations to make informed decisions. The unique community-academic-government partnership and the community-driven framework can be used as a template for other environmental and social justice mapping endeavors.

Spray Drift from a Conventional Axial Fan Airblast Sprayer in a Modern Orchard Work Environment.

Pesticide spray drift represents an important cause of crop damage and farmworker illness, especially among orchard workers. We drew upon exposure characteristics from known human illness cases to design a series of six spray trials that measured drift from a conventional axial fan airblast sprayer operating in a modern orchard work environment. Polyester line drift samples (n = 270; 45 per trial) were suspended on 15 vertical masts downwind of foliar applications of zinc, molybdenum, and copper micronutrient tracers. Samples were analyzed using inductively coupled plasma mass spectrometry and resulting masses were normalized by sprayer tank mix concentration to create tracer-based drift volume levels. Mixed-effects modeling described these levels in the context of spatial variability and buffers designed to protect workers from drift exposure. Field-based measurements showed evidence of drift up to 52 m downwind, which is approximately 1.7 times greater than the 30 m (100 ft) 'Application Exclusion Zone' defined for airblast sprayers by the United States Environmental Protection Agency Worker Protection Standard. When stratified by near (5 m), mid (26 m), and far (52 m) distances, geometric means and standard deviations for drift levels were 257 (1.8), 52 (2.0), and 20 (2.3) µl, respectively. Fixed effect model coefficients showed that higher wind speed [0.53; 95% confidence interval (CI): 0.35, 0.70] and sampling height (0.16; 95% CI: 0.11, 0.20) were positively associated with drift; increasing downwind distance (-0.05; 95% CI: -0.06, -0.04) was negatively associated with drift. Random effects showed large within-location variability, but relatively few systematic changes for individual locations across spray trials after accounting for wind speed, height, and distance. Our study findings demonstrate that buffers may offer drift exposure protection to orchard workers from airblast spraying. Variables such as orchard architecture, sampling height, and wind speed should be included in the evaluation and mitigation of risks from drift exposure. Data from our study may prove useful for estimating potential exposure and validating orchard-based bystander exposure models.

A Geographical Analysis of Emergency Medical Service Calls and Extreme Heat in King County, WA, USA (2007-2012).

This research analyzed the relationship between extreme heat and Emergency Medical Service (EMS) calls in King County, WA, USA between 2007 and 2012, including the effect of community-level characteristics. Extreme heat thresholds for the Basic Life Support (BLS) data and the Advanced Life Support (ALS) data were found using a piecewise generalized linear model with Akaike Information Criterion (AIC). The association between heat exposure and EMS call rates was investigated using a generalized estimating equations with Poisson mean model, while adjusting for community-level indicators of poverty, impervious surface, and elderly population (65+). In addition, we examined the effect modifications of these community-level factors. Extreme-heat thresholds of 31.1 °C and 33.5 °C humidex were determined for the BLS and ALS data, respectively. After adjusting for other variables in the model, increased BLS call volume was significantly associated with occurring on a heat day (relative rate (RR) = 1.080, p < 0.001), as well as in locations with higher percent poverty (RR = 1.066, p < 0.001). No significant effect modification was identified for the BLS data on a heat day. Controlling for other variables, higher ALS call volume was found to be significantly associated with a heat day (RR = 1.067, p < 0.001), as well as in locations with higher percent impervious surface (RR = 1.015, p = 0.039), higher percent of the population 65 years or older (RR = 1.057, p = 0.005), and higher percent poverty (RR = 1.041, p = 0.016). Furthermore, percent poverty and impervious surface were found to significantly modify the relative rate of ALS call volumes between a heat day and non-heat day. We conclude that EMS call volume increases significantly on a heat day compared to non-heat day for both call types. While this study shows that there is some effect modification between the community-level variables and call volume on a heat day, further research is necessary. Our findings also suggest that with adequate power, spatially refined analyses may not be necessary to accurately estimate the extreme-heat effect on health.

The unhealthy food environment does not modify the association between obesity and participation in the Supplemental Nutrition Assistance Program (SNAP) in Los Angeles County.

BACKGROUND: Participation in the Supplemental Nutrition Assistance Program (SNAP) has been linked to an increased risk of obesity, but not much is known about the mechanisms behind this association. The objective of this study was to determine if the neighborhood density of unhealthy food outlets modifies the association between obesity and participation in SNAP. METHODS: Data comes from the first wave of the Los Angeles Family and Neighborhood Survey; included are a subsample of adults (18+ years) who were SNAP participants or eligible non-participants (N = 1,176). We carried out multilevel analyses with obesity (BMI ≥ 30 Kg/m2), SNAP participation, and the neighborhood density of unhealthy food outlets as dependent, independent and modifying variables, respectively, controlling for age, gender, race/ethnicity, marital status, working status, mental health, and neighborhood poverty. RESULTS: SNAP participants had double the odds of obesity compared to eligible non-participants (OR = 2.02; 95%CI = 1.44-2.83). However, the neighborhood density of unhealthy food outlets did not modify this association. CONCLUSIONS: SNAP participation was associated with higher odds of obesity in our primarily Hispanic sample in Los Angeles County, with no effect modification found for the unhealthy portion of the food environment. More research is needed with additional food environment measures to confirm our null findings. Additional research is needed to elucidate the mechanisms linking SNAP participation and obesity as they remain unclear.

Measuring the food environment and its effects on obesity in the United States: a systematic review of methods and results.

We identified fifty-one peer-reviewed studies that geospatially analyzed the relationship between the community nutrition environment (CNE) and obesity. Eighty percent of studies found at least one significant association between the CNE and obesity. However we calculated the proportion of studies that found at least one significant association between the CNE and obesity in the expected direction for each food store type and measurement technique, and the proportion across the different store types and measurement techniques was just 32%. Different methods for classifying, locating, and analyzing food stores produced mixed results and challenged direct study level comparison.

Assessment of traffic-related noise in three cities in the United States.

BACKGROUND: Traffic-related noise is a growing public health concern in developing and developed countries due to increasing vehicle traffic. Epidemiological studies have reported associations between noise exposure and high blood pressure, increased risk of hypertension and heart disease, and stress induced by sleep disturbance and annoyance. These findings motivate the need for regular noise assessments within urban areas. This paper assesses the relationships between traffic and noise in three US cities. METHODS: Noise measurements were conducted in downtown areas in three cities in the United States: Atlanta, Los Angeles, and New York City. For each city, we measured ambient noise levels, and assessed their correlation with simultaneously measured vehicle counts, and with traffic data provided by local Metropolitan Planning Organizations (MPO). Additionally, measured noise levels were compared to noise levels predicted by the Federal Highway Administration's Traffic Noise Model using (1) simultaneously measured traffic counts or (2) MPO traffic data sources as model input. RESULTS: We found substantial variations in traffic and noise within and between cities. Total number of vehicle counts explained a substantial amount of variation in measured ambient noise in Atlanta (78%), Los Angeles (58%), and New York City (62%). Modeled noise levels were moderately correlated with measured noise levels when observed traffic counts were used as model input. Weaker correlations were found when MPO traffic data was used as model input. CONCLUSIONS: Ambient noise levels measured in all three cities were correlated with traffic data, highlighting the importance of traffic planning in mitigating noise-related health effects. Model performance was sensitive to the traffic data used as input. Future noise studies that use modeled noise estimates should evaluate traffic data quality and should ideally include other factors, such as local roadway, building, and meteorological characteristics.

Semiparametric Estimation of the Impacts of Longitudinal Interventions on Adolescent Obesity using Targeted Maximum-Likelihood: Accessible Estimation with the ltmle Package.

While child and adolescent obesity is a serious public health concern, few studies have utilized parameters based on the causal inference literature to examine the potential impacts of early intervention. The purpose of this analysis was to estimate the causal effects of early interventions to improve physical activity and diet during adolescence on body mass index (BMI), a measure of adiposity, using improved techniques. The most widespread statistical method in studies of child and adolescent obesity is multi-variable regression, with the parameter of interest being the coefficient on the variable of interest. This approach does not appropriately adjust for time-dependent confounding, and the modeling assumptions may not always be met. An alternative parameter to estimate is one motivated by the causal inference literature, which can be interpreted as the mean change in the outcome under interventions to set the exposure of interest. The underlying data-generating distribution, upon which the estimator is based, can be estimated via a parametric or semi-parametric approach. Using data from the National Heart, Lung, and Blood Institute Growth and Health Study, a 10-year prospective cohort study of adolescent girls, we estimated the longitudinal impact of physical activity and diet interventions on 10-year BMI z-scores via a parameter motivated by the causal inference literature, using both parametric and semi-parametric estimation approaches. The parameters of interest were estimated with a recently released R package, ltmle, for estimating means based upon general longitudinal treatment regimes. We found that early, sustained intervention on total calories had a greater impact than a physical activity intervention or non-sustained interventions. Multivariable linear regression yielded inflated effect estimates compared to estimates based on targeted maximum-likelihood estimation and data-adaptive super learning. Our analysis demonstrates that sophisticated, optimal semiparametric estimation of longitudinal treatment-specific means via ltmle provides an incredibly powerful, yet easy-to-use tool, removing impediments for putting theory into practice.

Patterns of intestinal schistosomiasis among mothers and young children from Lake Albert, Uganda: water contact and social networks inferred from wearable global positioning system dataloggers.

The establishment of a national control programme (NCP) in Uganda has led to routine treatment of intestinal schistosomiasis with praziquantel in the communities along Lake Albert. However, because regular water contact remains a way of life for these populations, re-infection continues to mitigate the sustainability of the chemotherapy-based programme. A six-month longitudinal study was conducted in one Lake Albert community with the aim of characterizing water contact exposure and infection among mothers and their young preschool-aged children as the latter are not yet formally included within the NCP. At baseline the cohort of 37 mothers, 36 preschool-aged children had infection prevalences of 62% and 67%, respectively, which diminished to 20% and 29%, respectively, at the 6-month post-treatment follow-up. The subjects wore global positioning system (GPS) datalogging devices over a 3-day period shortly after baseline, allowing for the estimation of time spent at the lakeshore as an exposure metric, which was found to be associated with prevalence at follow-up (OR = 2.1, P = 0.01 for both mothers and young children and odds ratio (OR) = 4.4, P = 0.01 for young children alone). A social network of interpersonal interactions was also derived from the GPS data, and the exposures were positively associated both with the number and duration of peer interaction, suggesting the importance of socio-cultural factors associated with water contact behaviour. The findings illustrate reduction in both prevalence and intensity of infection in this community after treatment as well as remarkably high rates of water contact exposure and re-infection, particularly among younger children. We believe that this should now be formally considered within NCP, which may benefit from more in-depth ethnographic exploration of factors related to water contact as this should provide new opportunities for sustaining control.

Toward sustainable and comprehensive control of schistosomiasis in China: lessons from Sichuan.

Triggered by a fascinating publication in the New England Journal of Medicine detailing China's new multi-pronged strategy to control and eventually interrupt the transmission of Schistosoma japonicum, this PLoS Neglected Tropical Diseases Debate critically examines the generalizability and financial costs of the studies presented from the marshlands of the lake region. Edmund Seto from the University of California and colleagues emphasize that the epidemiology and control of schistosomiasis varies according to the social-ecological context. They conjecture that the successful intervention packages piloted in the lake region is not fully fit for the hilly and mountainous environments in Sichuan and Yunnan provinces, and hence call for more flexible, setting-specific, and less expensive control strategies. In response, Xiao-Nong Zhou from the National Institute of Parasitic Diseases at the Chinese Center of Disease Control and Prevention and colleagues explain the steps from designing pilot studies to the articulation and implementation of a new national control strategy through a careful process of scaling-up and adaptations. Finally, the two opponents converge. The need for integrated, intersectoral, and setting-specific control measures is stressed, supported by rigorous surveillance and continuous research. Experiences and lessons from China are important for shaping the schistosomiasis elimination agenda.

Closing the praziquantel treatment gap: new steps in epidemiological monitoring and control of schistosomiasis in African infants and preschool-aged children.

Where very young children come into contact with water containing schistosome cercariae, infections occur and schistosomiasis can be found. In high transmission environments, where mothers daily bathe their children with environmentally drawn water, many infants and preschool-aged children have schistosomiasis. This 'new' burden, inclusive of co-infections with Schistosoma haematobium and Schistosoma mansoni, is being formally explored as infected children are not presently targeted to receive praziquantel (PZQ) within current preventive chemotherapy campaigns. Thus an important PZQ treatment gap exists whereby infected children might wait up to 4-5 years before receiving first treatment in school. International treatment guidelines, set within national treatment platforms, are presently being modified to provide earlier access to medication(s). Although detailed pharmacokinetic studies are needed, to facilitate pragmatic dosing in the field, an extended 'dose pole' has been devised and epidemiological monitoring has shown that administration of PZQ (40 mg/kg), in either crushed tablet or liquid suspension, is both safe and effective in this younger age-class; drug efficacy, however, against S. mansoni appears to diminish after repeated rounds of treatment. Thus use of PZQ should be combined with appropriate health education/water hygiene improvements for both child and mother to bring forth a more enduring solution.

Human schistosomiasis resistance to praziquantel in China: should we be worried?

The efficacy of praziquantel for the treatment of Schistosoma japonicum in humans is reported from a cross-sectional survey conducted in 33 villages in Sichuan Province. Infection prevalence was found to be 5.7% (185 infected of 3,269 tested) in a region where 44-73% prevalence was found 9 years before. Collected miracidia were subjected to an in vitro test of praziquantel susceptibility. An effective concentration of praziquantel associated with 50% of miracidia changing shape was found between 10(-8) and 10(-7) M and 10(-7) and 10(-6) M for 10 and 5 minutes of exposure, respectively. After treating infected persons two times with 40-mg/kg doses of praziquantel, only one remained infected. Findings are reported from a 60-household questionnaire on attitudes and behaviors that may be associated with development of drug resistance. The low number of treatment failures and good compliance with treatment despite side effects and repeated annual treatments suggest that, in the near term, praziquantel remains effective in treating human S. japonicum infection in China.