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COVID-19 has been a sustained and global crisis with a strong continual impact on daily life. Staying accurately informed about COVID-19 has been key to personal and communal safety, especially for essential workers---individuals whose jobs have required them to go into work throughout the pandemic---as their employment has exposed them to higher risks of contracting the virus. Through 14 semi-structured interviews, we explore how essential workers across industries navigated the COVID-19 information landscape to get up-to-date information in the early months of the pandemic. We find that essential workers living through a sustained crisis have a broad set of information needs. We summarize these needs in a framework that centers 1) fulfilling job requirements, 2) assessing personal risk, and 3) keeping up with crisis news coverage. Our findings also show that the sustained nature of COVID-19 crisis coverage led essential workers to experience breaking points and develop coping strategies. Additionally, we show how workplace communications may act as a mediating force in this process: lack of adequate information in the workplace caused workers to struggle with navigating a contested information landscape, while consistent updates and information exchanges at work could ease the stress of information overload. Our findings extend the crisis informatics field by providing contextual knowledge about the information needs of essential workers during a sustained crisis.

Many policies allocate harms or benefits that are uncertain in nature: they produce distributions over the population in which individuals have different probabilities of incurring harm or benefit. Comparing different policies thus involves a comparison of their corresponding probability distributions, and we observe that in many instances the policies selected in practice are hard to explain by preferences based only on the expected value of the total harm or benefit they produce. In cases where the expected value analysis is not a sufficient explanatory framework, what would be a reasonable model for societal preferences over these distributions? Here we investigate explanations based on the framework of probability weighting from the behavioral sciences, which over several decades has identified systematic biases in how people perceive probabilities. We show that probability weighting can be used to make predictions about preferences over probabilistic distributions of harm and benefit that function quite differently from expected-value analysis, and in a number of cases provide potential explanations for policy preferences that appear hard to motivate by other means. In particular, we identify optimal policies for minimizing perceived total harm and maximizing perceived total benefit that take the distorting effects of probability weighting into account, and we discuss a number of real-world policies that resemble such allocational strategies. Our analysis does not provide specific recommendations for policy choices, but is instead interpretive in nature, seeking to describe observed phenomena in policy choices.

The increasing abundance of extended spectrum β-lactamase (ESBL) genes inE. coli, and other commensal and pathogenic bacteria, endangers the utility of third or more recent generation cephalosporins, which are major tools for fighting deadly infections. The role of domestic animals in the transmission of ESBL carrying bacteria has been recognized, especially in low- and middle-income countries, however the horizontal gene transfer of these genes is difficult to assess. Here we investigateblaCTX-Mgene diversity (and flanking nucleotide sequences) inE. colifrom chicken and humans, in an Ecuadorian rural community and from chickens in another location in Ecuador. TheblaCTX-Massociated sequences in isolates from humans and chickens in the same remote community showed greater similarity from those found inE. coliin a chicken industrial operation 200 km away. Our study may provide evidence ofblaCTX-Mtransfer between chickens and humans in the community.

Antibiotic resistance is a leading cause of hospitalization and death worldwide. Heavy metals such as arsenic have been shown to drive co-selection of antibiotic resistance, suggesting arsenic-contaminated drinking water is a risk factor for antibiotic resistance carriage. This study aimed to determine the prevalence and abundance of antibiotic-resistant Escherichia coli (AR-Ec) among people and drinking water in high (Hajiganj, >100 μg/L) and low arsenic-contaminated (Matlab, E. coli isolates from 10 households. Prevalence of AR-Ec was significantly higher in water in Hajiganj (48%) compared to water in Matlab (22%, p p E. coli isolates from Hajiganj were multidrug-resistant (83%) compared to isolates from Matlab (71%, p 0.2) was observed in a higher proportion of water (78%) and child stool (100%) isolates in Hajiganj than in water (57%) and children (89%) in Matlab (p p E. coli isolates did not reveal any clustering based on arsenic exposure and no significant difference in resistome was found among the isolates between the two areas. The positive association detected between arsenic exposure and antibiotic resistance carriage among children in arsenic-affected areas in Bangladesh is an important public health concern that warrants redoubling efforts to reduce arsenic exposure.

BackgroundAntibiotic resistance is a leading cause of death, with the highest burden in low-resource settings. There is limited evidence on the potential for water, sanitation, and hygiene (WASH) infrastructure to reduce the burden of antibiotic resistance in humans.MethodsWe used geospatially tagged human gut metagenomes and household survey datasets to determine the association between antibiotic resistance gene (ARG) abundance and community-level coverage of improved drinking water points and improved sanitation facilities. Adjusted general linearized models with robust standard errors were used to estimate the relationship between ARG abundance in the human gut and access to water and sanitation.FindingsWe identified 1589 publicly available metagenomes from 26 countries. The average abundance of ARGs, in units of log10 ARG reads per kilobase per million (RPKM) mapped reads classified as bacteria, was highest in Africa compared to other World Health Organization (WHO) regions (one-way ANOVA pInterpretationWhile additional studies to investigate casual effects are needed, increasing access to water and sanitation could be an effective strategy to curb the proliferation of antibiotic resistance in low- and middle-income countries.FundingBill & Melinda Gates FoundationResearch in ContextEvidence before this studyAntibiotic resistance is a growing global health threat that disproportionately affects low- and middle-income countries (LMICs). In 2019, an estimated 5 million deaths were associated with antibiotic resistance, with the highest death rate in western sub-Saharan Africa. Water, sanitation, and hygiene (WASH) interventions (e.g., household drinking water treatment, flush toilet, hand washing facilities with soap) can reduce diarrheal and respiratory infections, as reported in previous meta-analyses. Estimates, based on probability modeling, suggest improvements in water and sanitation could decrease antibiotic use for diarrheal disease treatment by 47-50% and 69-72%, respectively. Improving WASH infrastructure could theoretically contribute to the control of antibiotic resistance by preventing the release of antibiotics, resistant organisms, or antibiotic resistance genes (ARGs) into the environment, thus decreasing the burden of antibiotic-resistant infections. One global analysis across 73 countries suggested that improved infrastructure, including WASH services, was associated with reduced antibiotic resistance prevalence in isolates, however the independent effect of WASH access was not assessed.We searched PubMed for evidence on the impact of WASH interventions (excluding those related to animals and agriculture) on antibiotic resistance using the following keyword chain: (water OR sanitation OR hygiene OR WASH) AND (antimicrobial OR antibiotic) AND resistance) NOT (“OneHealth” OR “One Health” OR animal OR livestock). We selected reviews and systematic reviews (n=1420) to be screened for relevance to WASH and antibiotic resistance. The reference lists of included reviews were then searched for individual studies. We also consulted international agency guidelines and online resources from the Joint Programming Initiative on Antimicrobial Resistance, the International Scientific Forum on Hygiene, ReAct, Resistomap, and the London School of Hygiene and Tropical Medicine AMR Centre.Studies focusing on centralized water or wastewater treatment technologies in high income countries (HICs) reported variable removal of antibiotics (53 to >90%), antibiotic-resistant bacteria (90-99.9%) and ARGs (90-99.9%) from waste streams. Other studies were conducted on hand hygiene, which has proven effective at reducing human infections and antibiotic use. No studies were identified on the effect of on-site sanitation systems (e.g., pour-flush toilets, pit latrines), which serve an estimated 2.7 billion people globally, or fecal sludge management interventions on antibiotic resistance.Added value of this studyIn this study, we used 1589 publicly available human gut metagenomes from around the world to assess the abundance of ARGs as a function of access to improved drinking water and sanitation infrastructure. This analysis provides new evidence of differences in the abundance of antibiotic resistance in the human gut across the world and finds that decreased gut abundance of ARGs is associated with increased access to improved drinking water and sanitation.Implications of all the available evidenceCurrent approaches to controlling antibiotic resistance in humans predominantly focus on antibiotic stewardship; however, this approach is challenging in LMICs where infectious illnesses are generally more prevalent and unregulated antibiotic usage is common. Along with efforts to provide other known social benefits, such as reducing infectious disease and improving gender equality, improving access to safe drinking water and sanitation could contribute to reducing the burden of antibiotic resistance. This work highlights improving access to adequate water and sanitation as a potentially effective strategy, although additional studies designed to rigorously investigate the casual relationship between WASH and antibiotic resistance are needed.

Rationale: Avoiding excess health damages attributable to climate change is a primary motivator for policy interventions to reduce greenhouse gas emissions. However, the health benefits of climate mitigation, as included in the policy assessment process, have been estimated without much input from health experts. Objectives: In accordance with recommendations from the National Academies in a 2017 report on approaches to update the social cost of greenhouse gases (SC-GHG), an expert panel of 26 health researchers and climate economists gathered for a virtual technical workshop in May 2021 to conduct a systematic review and meta-analysis and recommend improvements to the estimation of health impacts in economic-climate models. Methods: Regionally resolved effect estimates of unit increases in temperature on net all-cause mortality risk were generated through random-effects pooling of studies identified through a systematic review. Results: Effect estimates and associated uncertainties varied by global region, but net increases in mortality risk associated with increased average annual temperatures (ranging from 0.1% to 1.1% per 1 degrees C) were estimated for all global regions. Key recommendations for the development and utilization of health damage modules were provided by the expert panel and included the following: not relying on individual methodologies in estimating health damages; incorporating a broader range of cause-specific mortality impacts; improving the climate parameters available in economic models; accounting for socioeconomic trajectories and adaptation factors when estimating health damages; and carefully considering how air pollution impacts should be incorporated in economic-climate models. Conclusions: This work provides an example of how subject-matter experts can work alongside climate economists in making continued improvements to SC-GHG estimates. U.S. Environmental Protection Agency; National Institute of Environmental Health Sciences; Centers for Disease Control and Prevention Published version Supported by the U.S. Environmental Protection Agency, Centers for Disease Control and Prevention, and National Institute of Environmental Health Sciences. The views expressed in this manuscript are solely those of the authors and do not necessarily represent those of their employers, including the U.S. Environmental Protection Agency, Centers for Disease Control and Prevention, and Health Canada, and no official endorsement should be inferred.

Infections with enteric pathogens impose a heavy disease burden, especially among young children in low-income countries. Recent findings from randomized controlled trials of water, sanitation, and hygiene interventions have raised questions about current methods for assessing environmental exposure to enteric pathogens. Approaches for estimating sources and doses of exposure suffer from a number of shortcomings, including reliance on imperfect indicators of fecal contamination instead of actual pathogens and estimating exposure indirectly from imprecise measurements of pathogens in the environment and human interaction therewith. These shortcomings limit the potential for effective surveillance of exposures, identification of important sources and modes of transmission, and evaluation of the effectiveness of interventions. In this review, we summarize current and emerging approaches used to characterize enteric pathogen hazards in different environmental media as well as human interaction with those media (external measures of exposure), and review methods that measure human infection with enteric pathogens as a proxy for past exposure (internal measures of exposure). We draw from lessons learned in other areas of environmental health to highlight how external and internal measures of exposure can be used to more comprehensively assess exposure. We conclude by recommending strategies for advancing enteric pathogen exposure assessments.

Purpose of review Several types of Escherichia coli cause acute diarrhea in humans and are responsible for a large burden of disease globally. The purpose of this review is to summarize diarrheagenic Escherichia coli (DEC) pathotype definitions and discuss existing and emerging molecular, genomic, and gut microbiome methods to detect, define, and study DEC pathotypes. Recent findings DEC pathotypes are currently diagnosed by molecular detection of unique virulence genes. However, some pathotypes have defied coherent molecular definitions because of imperfect gene targets, and pathotype categories are complicated by hybrid strains and isolation of pathotypes from asymptomatic individuals. Recent progress toward more efficient, sensitive, and multiplex DEC pathotype detection has been made using emerging PCR-based technologies. Genomics and gut microbiome detection methods continue to advance rapidly and are contributing to a better understanding of DEC pathotype diversity and functional potential. Summary DEC pathotype categorizations and detection methods are useful but imperfect. The implementation of molecular and sequence-based methods and well designed epidemiological studies will continue to advance understanding of DEC pathotypes. Additional emphasis is needed on sequencing DEC genomes from regions of the world where they cause the most disease and from the pathotypes that cause the greatest burden of disease globally.

BACKGROUND: We conducted a national impact evaluation of routine rotavirus vaccination on childhood diarrhea in Peru, accounting for potential modifying factors. METHODS: We utilized a dataset compiled from Peruvian governmental sources to fit negative binomial models investigating the impact of rotavirus vaccination, piped water access, sewerage access and poverty on the rate of diarrhea clinic visits in children under 5 years old in 194 Peruvian provinces. We considered the interaction between these factors to assess whether water access, sanitation access, or poverty modified the association between ongoing rotavirus vaccination and childhood diarrhea clinic visits. We compared the "pre-vaccine" (2005-2009) and "post-vaccine" (2010-2015) eras. RESULTS: The rate of childhood diarrhea clinic visits was 7% [95% confidence interval (CI): 3%-10%] lower in the post-vaccine era compared to the pre-vaccine era, controlling for long-term trend and El Niño seasons. No impact of rotavirus vaccination was identified in provinces with the lowest access to piped water (when

Combined sewer overflows (CSOs) discharge untreated sewage into surface and recreational water, often following heavy precipitation. Given projected increases in frequency and intensity of precipitation due to climate change, it is important to understand the health impacts of CSOs and mediating effects of sewerage systems.In this study we estimate associations of CSO events and emergency department (ED) visits for gastrointestinal (GI) illness among City of Atlanta, Georgia, residents and explore how these associations vary with sewerage improvements.We estimate associations using Poisson generalized linear models, controlling for time trends. We categorized CSOs by overflow volume and assessed effects of CSO events prior to ED visits with 1-, 2- and 3-wk lags. Similarly, we evaluated effects of weekly cumulative precipitation greater than the 90th percentile at the same lags. We also evaluated effect modification by ZIP Code Tabulation Area (ZCTA)-level poverty and infrastructure improvement period using interaction terms.Occurrence of a large volume CSO in the previous week was associated with a 9% increase in daily ED visits for GI illness. We identified significant interaction by ZCTA-level poverty, with stronger CSO-GI illness associations in low than high poverty areas. Among areas with low poverty, we observed associations at 1-wk and longer lags, following both large and lower volume CSO events. We did not observe significant interaction by infrastructure improvement period for CSO- nor precipitation-GI illness associations; however, the number of CSO events decreased from 2.31 per week before improvements to 0.49 after improvements.Our findings suggest that CSOs contribute to acute GI illness burden in Atlanta and that the magnitude of this risk may be higher among populations living in areas of low poverty. We did not find a protective effect of sewerage system improvements. Nonetheless, observed reductions in CSO frequency may lower the absolute burden of GI illness attributable to these events. https://doi.org/10.1289/EHP10399.

The relative importance of environmental pathways that results in enteropathogen transmission may vary by context. However, measurement of contact events between individuals and the environment remains a challenge, especially for infants and young children who may use their mouth and hands to explore their environment. Using a mixed-method approach, we combined 1) semistructured observations to characterize key behaviors associated with enteric pathogen exposure and 2) structured observations using Livetrak, a customized software application, to quantify the frequency and duration of contacts events among infants in rural Ecuador. After developing and iteratively piloting the structured observation instrument, we loaded the final list of prompts onto a LiveTrak pallet to assess environmental exposures of 6-month infants (N = 19) enrolled in a prospective cohort study of diarrheal disease. Here we provide a detailed account of the lessons learned. For example, in our field site, 1) most mothers reported washing their hands after diaper changes (14/18, 77.8%); however only a third (4/11, 36.4%) were observed washing their hands; 2) the observers noted that animal ownership differed from observed animal exposure because animals owned by neighboring households were reported during the observation; and 3) using Livetrak, we found that infants frequently mouthed their hands (median = 1.9 episodes/hour, median duration: 1.6 min) and mouthed surroundings objects (1.8 episodes/hour, 1.9 min). Structured observations that track events in real time, can complement environmental sampling, quantitative survey data and qualitative interviews. Customizing these observations enabled us to quantify enteric exposures most relevant to our rural Ecuadorian context.

Rapid urbanization, resulting in population growth within informal settlements, has worsened exclusion and inequality in access to water and sanitation (WASH) services in the poorest and most marginalized communities. In this study, we describe the heterogeneity in water service satisfaction and WASH access in low-income, peri-urban neighborhoods of Beira, Mozambique, and examine whether this heterogeneity can be explained by distance to water distribution mains. Using spatial statistics and regression analyses, we identify spatial heterogeneity in household WASH access, as well as consumer-reported satisfaction with water services (services, pressure, quality, and sufficient quantity). We find that as distance from the water main increased, both access to an improved water source at the household and satisfaction with water pressure decreases, and water supply intermittency increases, controlling for household density and socioeconomic status. The odds of a household having access to a water source at the household or on the compound decreases with every 100-meter increase in distance from a water main pipe (odds ratio [OR] 0.87, 95% confidence interval [CI]: 0.82, 0.92). Satisfaction with water services also decreases with every 100-meter increase in distance from a water main pipe (OR: 0.80; 95% CI: 0.69, 0.94). Days of availability in the past week decreases by a factor of 0.22 for every 100-meter increase in distance from the water main (95% CI: -0.29, -0.15). Findings from this study highlight the unequal household access to water and sanitation in urban informal settlements, even within low-income neighborhoods. Describing this heterogeneity of access to water services, sanitation, and satisfaction—and the factors influencing them—can inform stakeholders and guide the development of infrastructural solutions to reduce water access inequities within urban settings.

IntroductionDespite clear linkages between provision of clean water and improvements in child health, limited information exists about the health impacts of large water infrastructure improvements in low-income settings. Billions of dollars are spent annually to improve urban water supply, and rigorous evaluation of these improvements, especially targeting informal settlements, is critical to guide policy and investment strategies. Objective measures of infection and exposure to pathogens, and measures of gut function, are needed to understand the effectiveness and impact of water supply improvements.Methods and analysisIn the PAASIM study, we examine the impact of water system improvements on acute and chronic health outcomes in children in a low-income urban area of Beira, Mozambique, comprising 62 sub-neighborhoods and ∼26,300 households. This prospective matched cohort study follows 548 mother-child dyads from late pregnancy through 12 months of age. Primary outcomes include measures of enteric pathogen infections, gut microbiome composition, and source drinking water microbiological quality, measured at the child’s 12 month visit. Additional outcomes include diarrhea prevalence, child growth, previous enteric pathogen exposure, child mortality, and various measures of water access and quality. Our analyses will compare a) subjects living in sub-neighborhoods with the improved water to those living in sub-neighborhoods without these improvements; and b) subjects with household water connections on their premises to those without such a connection. This study will provide critical information to understand how to optimize investments for improving child health, filling the information gap about the impact of piped water provision to low-income urban households, using novel gastrointestinal disease outcomes.Ethics and disseminationThe study was approved by the Emory University Institutional Review Board and the National Bio-Ethics Committee for Health in Mozambique. The pre-analysis is published on the Open Science Framework platform (https://osf.io/4rkn6/). Results will be shared with relevant stakeholders locally, and through publications.STRENGTHS AND LIMITATIONS OF THE STUDYThis matched cohort study of an urban water supply improvement project will provide critical information about the health impacts of providing piped water and household connections to low-income households.We employ rigorous measures of exposure and novel and objective outcome measures, including gut microbiome composition and molecular detection of enteric pathogens.The study design allows for examination of both neighborhood and household-level effects of water supply improvements.As a natural experiment, we are unable to randomize the intervention, leading to potential residual confounding.We are unable to examine the impacts of all aspects of the city-wide water improvement project, due to lack of comparable populations, and instead focus only on the low income neighborhoods.

IntroductionThe functional consequences of the bacterial gut microbiome for child health are not well understood. Characteristics of the early child gut microbiome may influence the course of enteric infections, and enteric infections may change the composition of the gut microbiome, all of which may have long-term implications for child growth and development.Methods and analysisWe are conducting a community-based birth cohort study to examine interactions between gut microbiome conditions and enteric infections, and how environmental conditions affect the development of the gut microbiome. We will follow 360 newborns from 3 sites along a rural–urban gradient in northern coastal Ecuador, characterising enteric infections and gut microbial communities in the children every 3 to 6 months over their first 2 years of life. We will use longitudinal regression models to assess the correlation between environmental conditions and gut microbiome diversity and presence of specific taxa, controlling for factors that are known to be associated with the gut microbiome, such as diet. From 6 to 12 months of age, we will collect weekly stool samples to compare microbiome conditions in diarrhoea stools versus stools from healthy children prior to, during and after acute enteric infections, using principal-coordinate analysis and other multivariate statistical methods.Ethics and disseminationEthics approvals have been obtained from Emory University and the Universidad San Francisco de Quito institutional review boards. The findings will be disseminated through conference presentations and peer-reviewed journals.

“Algorithmic audits” have been embraced as tools to investigate the functioning and consequences of sociotechnical systems. Though the term is used somewhat loosely in the algorithmic context and encompasses a variety of methods, it maintains a close connection to audit studies in the social sciences—which have, for decades, used experimental methods to measure the prevalence of discrimination across domains like housing and employment. In the social sciences, audit studies originated in a strong tradition of social justice and participatory action, often involving collaboration between researchers and communities; but scholars have argued that, over time, social science audits have become somewhat distanced from these original goals and priorities. We draw from this history in order to highlight difficult tensions that have shaped the development of social science audits, and to assess their implications in the context of algorithmic auditing. In doing so, we put forth considerations to assist in the development of robust and engaged assessments of sociotechnical systems that draw from auditing’s roots in racial equity and social justice.

We define Artificial Intelligence-Mediated Communication (AI-MC) as interpersonal communication in which an intelligent agent operates on behalf of a communicator by modifying, augmenting, or generating messages to accomplish communication goals. The recent advent of AI-MC raises new questions about how technology may shape human communication and requires re-evaluation – and potentially expansion – of many of Computer-Mediated Communication’s (CMC) key theories, frameworks, and findings. A research agenda around AI-MC should consider the design of these technologies and the psychological, linguistic, relational, policy and ethical implications of introducing AI into human–human communication. This article aims to articulate such an agenda.

Опосредованная искусственным интеллектом коммуникация (Artificial Intelligence -Mediated Communication, AI-MC) определяется как межличностная коммуникация, в которой интеллектуальный агент действует от лица коммуниканта путем изменения, расширения или создания сообщений с тем, чтобы достичь коммуникационных целей. Недавнее появление AI-MC ставит новые вопросы относительно того, как технология может преобразовать коммуникацию, и требует переоценки и даже расширения многих базовых теорий, подходов и наблюдений о компьютерно-опосредованной коммуникации (computer-mediated communication, CMC). Повестка исследований относительно AI-MC должна рассматривать разработку этих технологий, а также психологические, лингвистические, относительные, политические и этические аспекты введения искусственного интеллекта в коммуникации между людьми. Статья нацелена на четкую формулировку подобной повестки.

Nearly one-half of foodborne illnesses in the United States can be attributed to fresh produce consumption. The preharvest stage of production presents a critical opportunity to prevent produce contamination in the field from contaminating postharvest operations and exposing consumers to foodborne pathogens. One produce-contamination route that is not often explored is the transfer of pathogens in the soil to edible portions of crops via splash water. We report here on the results from multiple field and microcosm experiments examining the potential for Salmonella contamination of produce crops via splash water, and the effect of soil moisture content on Salmonella survival in soil and concentration in splash water. In field and microcosm experiments, we detected Salmonella for up to 8 to 10 days after inoculation in soil and on produce. Salmonella and suspended solids were detected in splash water at heights of up to 80 cm from the soil surface. Soil-moisture conditions before the splash event influenced the detection of Salmonella on crops after the splash events-Salmonella concentrations on produce after rainfall were significantly higher in wet plots than in dry plots (geometric mean difference = 0.43 CFU/g; P = 0.03). Similarly, concentrations of Salmonella in splash water in wet plots trended higher than concentrations from dry plots (geometric mean difference = 0.67 CFU/100 mL; P = 0.04). These results indicate that splash transfer of Salmonella from soil onto crops can occur and that antecedent soil-moisture content may mediate the efficiency of microbial transfer. Splash transfer of Salmonella may, therefore, pose a hazard to produce safety. The potential for the risk of splash should be further explored in agricultural regions in which Salmonella and other pathogens are present in soil. These results will help inform the assessment of produce safety risk and the development of management practices for the mitigation of produce contamination.

Birth stories have become increasingly common on the internet, but they have received little attention as a computational dataset. These unsolicited, publicly posted stories provide rich descriptions of decisions, emotions, and relationships during a common but sometimes traumatic medical experience. These personal details can be illuminating for medical practitioners, and due to their shared structures, birth stories are also an ideal testing ground for narrative analysis techniques. We present an analysis of 2,847 birth stories from an online forum and demonstrate the utility of these stories for computational work. We discover clear sentiment, topic and persona-based patterns that both model the expected narrative event sequences of birth stories and highlight diverging pathways and exceptions to narrative norms. The authors' motivation to publicly post these personal stories can be a way to regain power after a surveilled and disempowering experience, and we explore power relationships between the personas in the stories, showing that these dynamics can vary with the type of birth (e.g., medicated vs unmedicated). Finally, birth stories exist in a space that is both public and deeply personal. This liminality poses a challenge for analysis and presentation, and we discuss tradeoffs and ethical practices for this collection. WARNING: This paper includes detailed narratives of pregnancy and birth.

Scholars have recently drawn attention to a range of controversial issues posed by the use of computer vision for automatically generating descriptions of people in images. Despite these concerns, automated image description has become an important tool to ensure equitable access to information for blind and low vision people. In this paper, we investigate the ethical dilemmas faced by companies that have adopted the use of computer vision for producing alt text: textual descriptions of images for blind and low vision people, We use Facebook's automatic alt text tool as our primary case study. First, we analyze the policies that Facebook has adopted with respect to identity categories, such as race, gender, age, etc., and the company's decisions about whether to present these terms in alt text. We then describe an alternative -- and manual -- approach practiced in the museum community, focusing on how museums determine what to include in alt text descriptions of cultural artifacts. We compare these policies, using notable points of contrast to develop an analytic framework that characterizes the particular apprehensions behind these policy choices. We conclude by considering two strategies that seem to sidestep some of these concerns, finding that there are no easy ways to avoid the normative dilemmas posed by the use of computer vision to automate alt text.

SummaryBackgroundChildhood exposure to enteric pathogens associated with poor sanitation contributes to undernutrition, associated with adverse effects later in life. This trial assessed the independent and combined effects of nutrition and sanitation interventions on child growth outcomes and enteric pathogen infection in rural Cambodia, where the prevalence of childhood stunting remains high.MethodsWe conducted a factorial cluster-randomised controlled trial of 4,015 households with 4,124 children (1-28 months of age at endline) across three rural provinces in Cambodia. Fifty-five communes (clusters) were randomly assigned to a control arm or one of three treatments: a nutrition-only arm, a sanitation-only arm, and a combined nutrition and sanitation arm receiving both treatments. The primary outcome was length-for-age Z-score (LAZ); other outcomes included weight-for-age Z-score (WAZ), weight-for-length Z-score (WLZ), stunting, wasting, underweight, and caregiver-reported diarrhoea. We assayed stool specimens from a subset of all children (n = 1,620) for 27 enteric pathogens (14 bacteria, 6 viruses, 3 protozoa, and 4 soil-transmitted helminths) and estimated effects of interventions on enteric pathogen detection and density. Analysis was by intention-to-treat. The trial was pre-registered with ISRCTN Registry (ISRCTN77820875).FindingsSelf-reported adherence was high for the nutrition intervention but uptake was low for sanitation. Compared with a mean LAZ of -1.04 (SD 1.2) in the control arm, children in the nutrition-only arm (LAZ +0.08, 95% CI -0.01-0.18) and combined nutrition and sanitation arm (LAZ +0.10, 95% CI 0.01-0.20) experienced greater linear growth; there were no measurable differences in LAZ in the sanitation-only arm (LAZ -0.05, 95% CI -0.16-0.05). We found no effect of any intervention (delivered independently or combined) on either enteric pathogen frequency or pathogen load in stool. Compared with a mean WAZ of -1.05 (SD 1.1) in the control arm, children in the nutrition-only arm (WAZ +0.10, 95% CI 0.00-0.19) and combined intervention arm (WAZ +0.11, 95% CI 0.03-0.20) were heavier for their age; there was no difference in WAZ in the sanitation-only arm. There were no differences between arms in prevalence of stunting, wasting, underweight status, one-week period prevalence of diarrhoea, pathogen prevalence, or pathogen density in stool.InterpretationImprovements in child growth in nutrition and combined nutrition and sanitation arms are consistent with previous efficacy trials of combined nutrition and sanitation interventions. We found no evidence that the sanitation intervention alone improved child growth or reduced enteric pathogen detection, having achieved only modest changes in access and use.FundingUnited States Agency for International Development (USAID), contracts AID-OAA-M-13-00017 and AID-OAA-TO-16-00016. The contents of this publication are the sole responsibility of the authors and do not necessarily reflect the views of USAID or the United States Government.

Representativeness is a foundational yet slippery concept. Though familiar at first blush, it lacks a single precise meaning. Instead, meanings range from typical or characteristic, to a proportionate match between sample and population, to a more general sense of accuracy, generalizability, coverage, or inclusiveness. Moreover, the concept has long been contested. In statistics, debates about the merits and methods of selecting a representative sample date back to the late 19th century; in politics, debates about the value of likeness as a logic of political representation are older still. Today, as the concept crops up in the study of fairness and accountability in machine learning, we need to carefully consider the term's meanings in order to communicate clearly and account for their normative implications. In this paper, we ask what representativeness means, how it is mobilized socially, and what values and ideals it communicates or confronts. We trace the concept's history in statistics and discuss normative tensions concerning its relationship to likeness, exclusion, authority, and aspiration. We draw on these analyses to think through how representativeness is used in FAccT debates, with emphasis on data, shift, participation, and power., Comment: Accepted to ACM FAccT 2021 https://facctconference.org/2021/acceptedpapers.html

Radiation therapy is the most effective cytotoxic therapy for localized tumors. However, normal tissue toxicity limits the radiation dose and the curative potential of radiation therapy when treating larger target volumes. In particular, the highly radiosensitive intestine limits the use of radiation for patients with intra-abdominal tumors. In metastatic ovarian cancer, total abdominal irradiation (TAI) was used as an effective postsurgical adjuvant therapy in the management of abdominal metastases. However, TAI fell out of favor due to high toxicity of the intestine. Here we utilized an innovative preclinical irradiation platform to compare the safety and efficacy of TAI ultra-high dose rate FLASH irradiation to conventional dose rate (CONV) irradiation in mice. We demonstrate that single high dose TAI-FLASH produced less mortality from gastrointestinal syndrome, spared gut function and epithelial integrity, and spared cell death in crypt base columnar cells compared to TAI-CONV irradiation. Importantly, TAI-FLASH and TAI-CONV irradiation had similar efficacy in reducing tumor burden while improving intestinal function in a preclinical model of ovarian cancer metastasis. These findings suggest that FLASH irradiation may be an effective strategy to enhance the therapeutic index of abdominal radiotherapy, with potential application to metastatic ovarian cancer.

Background: Projected increases in extreme weather may change relationships between rain-related climate exposures and diarrheal disease. Whether rainfall increases or decreases diarrhea rates is unclear based on prior literature. The concentration-dilution hypothesis suggests that these conflicting results are explained by the background level of rain: Rainfall following dry periods can flush pathogens into surface water, increasing diarrhea incidence, whereas rainfall following wet periods can dilute pathogen concentrations in surface water, thereby decreasing diarrhea incidence. Objectives: In this analysis, we explored the extent to which the concentration-dilution hypothesis is supported by published literature. Methods: To this end, we conducted a systematic search for articles assessing the relationship between rain, extreme rain, flood, drought, and season (rainy vs. dry) and diarrheal illness. Results: A total of 111 articles met our inclusion criteria. Overall, the literature largely supports the concentration-dilution hypothesis. In particular, extreme rain was associated with increased diarrhea when it followed a dry period [incidence rate ratio (IRR)=1.26; 95% confidence interval (CI): 1.05, 1.51], with a tendency toward an inverse association for extreme rain following wet periods, albeit nonsignificant, with one of four relevant studies showing a significant inverse association (IRR=0.911; 95% CI: 0.771, 1.08). Incidences of bacterial and parasitic diarrhea were more common during rainy seasons, providing pathogen-specific support for a concentration mechanism, but rotavirus diarrhea showed the opposite association. Information on timing of cases within the rainy season (e.g., early vs. late) was lacking, limiting further analysis. We did not find a linear association between nonextreme rain exposures and diarrheal disease, but several studies found a nonlinear association with low and high rain both being associated with diarrhea. Discussion: Our meta-analysis suggests that the effect of rainfall depends on the antecedent conditions. Future studies should use standard, clearly defined exposure variables to strengthen understanding of the relationship between rainfall and diarrheal illness. https://doi.org/10.1289/EHP6181

The recovery of metagenome-assembled genomes (MAGs) from metagenomic data has recently become a common task for microbial studies. The strengths and limitations of the underlying bioinformatics algorithms are well appreciated by now based on performance tests with mock data sets of known composition. However, these mock data sets do not capture the complexity and diversity often observed within natural populations, since their construction typically relies on only a single genome of a given organism. Further, it remains unclear if MAGs can recover population-variable genes (those shared by >10% but 90% of the members). To address these issues, we compared the gene variabilities of pathogenic Escherichia coli isolates from eight diarrheal samples, for which the isolate was the causative agent, against their corresponding MAGs recovered from the companion metagenomic data set. Our analysis revealed that MAGs with completeness estimates near 95% captured only 77% of the population core genes and 50% of the variable genes, on average. Further, about 5% of the genes of these MAGs were conservatively identified as missing in the isolate and were of different (non-Enterobacteriaceae) taxonomic origin, suggesting errors at the genome-binning step, even though contamination estimates based on commonly used pipelines were only 1.5%. Therefore, the quality of MAGs may often be worse than estimated, and we offer examples of how to recognize and improve such MAGs to sufficient quality by (for instance) employing only contigs longer than 1,000 bp for binning. IMPORTANCE Metagenome assembly and the recovery of metagenome-assembled genomes (MAGs) have recently become common tasks for microbiome studies across environmental and clinical settings. However, the extent to which MAGs can capture the genes of the population they represent remains speculative. Current approaches to evaluating MAG quality are limited to the recovery and copy number of universal housekeeping genes, which represent a small fraction of the total genome, leaving the majority of the genome essentially inaccessible. If MAG quality in reality is lower than these approaches would estimate, this could have dramatic consequences for all downstream analyses and interpretations. In this study, we evaluated this issue using an approach that employed comparisons of the gene contents of MAGs to the gene contents of isolate genomes derived from the same sample. Further, our samples originated from a diarrhea case-control study, and thus, our results are relevant for recovering the virulence factors of pathogens from metagenomic data sets.

Norovirus is the leading cause of acute gastroenteritis outbreaks in the United States. We estimated the basic (R0) and effective (Re) reproduction numbers for 7,094 norovirus outbreaks reported to the National Outbreak Reporting System (NORS) during 2009–2017 and used regression models to assess whether transmission varied by outbreak setting. The median R0 was 2.75 (interquartile range [IQR] 2.38–3.65), and median Re was 1.29 (IQR 1.12–1.74). Long-term care and assisted living facilities had an R0 of 3.35 (95% CI 3.26–3.45), but R0 did not differ substantially for outbreaks in other settings, except for outbreaks in schools, colleges, and universities, which had an R0 of 2.92 (95% CI 2.82–3.03). Seasonally, R0 was lowest (3.11 [95% CI 2.97–3.25]) in summer and peaked in fall and winter. Overall, we saw little variability in transmission across different outbreaks settings in the United States.

This chapter examines the effects of artificial intelligence (AI) on work and workers. As AI-driven technologies are increasingly integrated into workplaces and labor processes, many have expressed worry about the widespread displacement of human workers. The chapter presents a more nuanced view of the common rhetoric that robots will take over people’s jobs. We contend that economic forecasts of massive AI-induced job loss are of limited practical utility, as they tend to focus solely on technical aspects of task execution, while neglecting broader contextual inquiry about the social components of work, organizational structures, and cross-industry effects. The chapter then considers how AI might impact workers through modes other than displacement. We highlight four mechanisms through which firms are beginning to use AI-driven tools to reallocate risks from themselves to workers: algorithmic scheduling, task redefinition, loss and fraud prediction, and incentivization of productivity. We then explore potential policy responses to both displacement and risk-shifting concerns.

Surveillance cameras are increasingly being deployed in nursing homes and assisted living facilities, with insufficient attention to what is ethically fraught about this way of assuaging concerns about abuse and other personnel challenges. With seven state laws now regulating camera monitoring and more on the way, it is urgent for us to consider the ethical implications of how we use technology to keep older adults safe. Drawing on findings from the first facility survey on this topic, we address three ethical issues: the risk that in-room cameras pose to residents' privacy and dignity, the risk of undermining care workers' sense of being fiduciaries for residents, and the probable extension of camera use by facilities to monitor staff and residents. We argue that with an aging population, intensifying strain on the care workforce, and ease of access to Web-connected cameras, this is a critical moment to address these ethical challenges.

We argue that modern technical and social infrastructures of surveillance have brought a novel subject position to prominence: the surveillant consumer. Surveillance has become a normalized mode of interpersonal relation that urges the person as consumer to manage others around her using surveillant products and services. We explore two configurations of this model: the consumer as observer, effectuated through products for use in the supervision of intimate relations as a component of a normalized duty of care; and the consumer as manager, effectuated through capacities for the customer to manage the labor of workers providing services to her. These models frequently intersect and hybridize as market logics overlap with intimate spheres: the surveillant consumer thus acts as an emotional manager of the experience of everyday surveillance. In turn, this managerial role reifies the equation of financial wealth with moral weight in a hierarchy of oversight, giving the wealthiest the most control and least accountability.

PURPOSE: Climate change threatens progress achieved in global reductions of infectious disease rates over recent decades. This review summarizes literature on potential impacts of climate change on waterborne diseases, organized around a framework of questions that can be addressed depending on available data. RECENT FINDINGS: A growing body of evidence suggests that climate change may alter the incidence of waterborne diseases, and diarrheal diseases in particular. Much of the existing work examines historical relationships between weather and diarrhea incidence, with a limited number of studies projecting future disease rates. Some studies take social and ecological factors into account in considerations of historical relationships, but few have done so in projecting future conditions. SUMMARY: The field is at a point of transition, toward incorporating social and ecological factors into understanding the relationships between climatic factors and diarrheal diseases and using this information for future projections. The integration of these components helps identify vulnerable populations and prioritize adaptation strategies.

Visual data are transforming the documentation of activities across many legal domains. Visual data can incriminate or exonerate; they can shape and reshape public opinion. Visual evidence can legitimize certain accounts of events while calling others into question. The proliferation of visual data creates challenges for the law at multiple points of entry: recording, distribution or disclosure, redaction or deletion, or use as evidence. This symposium outlines and analyzes legal challenges posed by recent developments in visual data technologies and practices. This introductory essay and the articles that follow highlight legal issues that arise when state actors collect visual data and when visual data are used in legal disputes. Technological development is outpacing empirical research on, and legal regulation of, visual data within society and inside the courtroom. This symposium provides a much-needed opportunity to highlight new legal and empirical research at the intersection of visual data and law.

Digital technologies, including mobile devices, cloud computing services, and social networks, play a nuanced role in intimate partner violence (IPV) settings, including domestic abuse, stalking, and surveillance of victims by abusive partners. However, the interactions among victims of IPV, abusers, law enforcement, counselors, and others --- and the roles that digital technologies play in these interactions --- are poorly understood. We present a qualitative study that analyzes the role of digital technologies in the IPV ecosystem in New York City. Findings from semi-structured interviews with 40 IPV professionals and nine focus groups with 32 survivors of IPV reveal a complex set of socio-technical challenges that stem from the intimate nature of the relationships involved and the complexities of managing shared social circles. Both IPV professionals and survivors feel that they do not possess adequate expertise to be able to identify or cope with technology-enabled IPV, and there are currently insufficient best practices to help them deal with abuse via technology. We also reveal a number of tensions and trade-offs in negotiating technology's role in social support and legal procedures. Taken together, our findings contribute a nuanced understanding of technology's role in the IPV ecosystem and yield recommendations for HCI and technology experts interested in aiding victims of abuse.

Consumer-sourced rating systems are a dominant method of worker evaluation in platform-based work. These systems facilitate the semi-automated management of large, disaggregated workforces, and the rapid growth of service platforms—but may also represent a potential avenue for employment discrimination that negatively impacts members of legally protected groups. We analyze the Uber platform as a case study to explore how bias may creep into evaluations of drivers through consumer-sourced rating systems, and draw on social science research to demonstrate how such bias emerges in other types of rating and evaluation systems. While companies are legally prohibited from making employment decisions based on protected characteristics of workers, their reliance on potentially biased consumer ratings to make material determinations may nonetheless lead to a disparate impact in employment outcomes. We analyze the limitations of current civil rights law to address this issue, and outline a number of operational, legal, and design-based interventions that might assist in so doing.

There has been rapidly growing interest in the use of algorithms in hiring, especially as a means to address or mitigate bias. Yet, to date, little is known about how these methods are used in practice. How are algorithmic assessments built, validated, and examined for bias? In this work, we document and analyze the claims and practices of companies offering algorithms for employment assessment. In particular, we identify vendors of algorithmic pre-employment assessments (i.e., algorithms to screen candidates), document what they have disclosed about their development and validation procedures, and evaluate their practices, focusing particularly on efforts to detect and mitigate bias. Our analysis considers both technical and legal perspectives. Technically, we consider the various choices vendors make regarding data collection and prediction targets, and explore the risks and trade-offs that these choices pose. We also discuss how algorithmic de-biasing techniques interface with, and create challenges for, antidiscrimination law.

In this paper we discuss the trade-off between accuracy and efficiency in distributed machine learning (ML) systems and analyze its resulting policy considerations. This trade-off is in fact quite common in multiple disciplines, including law and medicine, and it applies to a wide variety of sub-fields within computer science. Accuracy and efficiency trade-offs have unique implications in ML algorithms because, being probabilistic in nature, such algorithms generally exhibit error tolerance. After describing how the trade-off takes shape in real-world distributed computing systems, we show the interplay between such systems and ML algorithms, explaining in detail how accuracy and efficiency interact particularly in distributed ML systems. We close by making specific calls to action for approaching regulatory policy for the emerging technology of real-time distributed ML systems.

This article provides an overview of intimate threats: a class of privacy threats that can arise within our families, romantic partnerships, close friendships, and caregiving relationships. Many common assumptions about privacy are upended in the context of these relationships, and many otherwise effective protective measures fail when applied to intimate threats. Those closest to us know the answers to our secret questions, have access to our devices, and can exercise coercive power over us. We survey a range of intimate relationships and describe their common features. Based on these features, we explore implications for both technical privacy design and policy, and offer design recommendations for ameliorating intimate privacy risks.

Peritoneal metastases are the leading cause of morbidity and mortality in ovarian cancer. Despite current surgery, chemotherapy and targeted therapies, the majority of patients diagnosed with advanced epithelial ovarian cancer develop recurrent disease and overall survival rates remain poor. It is known that ovarian cancer is a radiosensitive tumor. Historically, total abdominal irradiation (TAI) was used as an effective postsurgical adjuvant therapy in the management of chemotherapy sensitive and resistant ovarian cancer. However, TAI fell out of favor due to high toxicity, particularly of the gastrointestinal tract. We have developed a preclinical irradiation platform that allows for total abdominal ultrahigh dose rate FLASH irradiation. We demonstrate that TAI-FLASH reduces radiation-induced intestinal injury in both healthy and tumor-bearing mice compared to conventional dose rate (CONV) irradiation. Single high dose TAI-FLASH reduced mortality from gastrointestinal syndrome, spared gut function and epithelial integrity, and decreased cell death in crypt base columnar cells. Importantly, FLASH and CONV irradiation had similar efficacy in the reduction of ovarian cancer peritoneal metastases. These findings suggest that FLASH irradiation may be an effective strategy to enhance the therapeutic index of radiotherapy for the treatment of metastatic ovarian cancer in women.

Escherichia coli is a leading contributor to infectious diarrhea and child mortality worldwide, but it remains unknown how alterations in the gut microbiome vary for distinct E. coli pathotype infections and whether these signatures can be used for diagnostic purposes. Further, the majority of enteric diarrheal infections are not diagnosed with respect to their etiological agent(s) due to technical challenges. To address these issues, we devised a novel approach that combined traditional, isolate-based and molecular-biology techniques with metagenomics analysis of stool samples and epidemiological data. Application of this pipeline to children enrolled in a case-control study of diarrhea in Ecuador showed that, in about half of the cases where an E. coli pathotype was detected by culture and PCR, E. coli was likely not the causative agent based on the metagenome-derived low relative abundance, the level of clonality, and/or the virulence gene content. Our results also showed that diffuse adherent E. coli (DAEC), a pathotype that is generally underrepresented in previous studies of diarrhea and thus, thought not to be highly virulent, caused several small-scale diarrheal outbreaks across a rural to urban gradient in Ecuador. DAEC infections were uniquely accompanied by coelution of large amounts of human DNA and conferred significant shifts in the gut microbiome composition relative to controls or infections caused by other E. coli pathotypes. Our study shows that diarrheal infections can be efficiently diagnosed for their etiological agent and categorized based on their effects on the gut microbiome using metagenomic tools, which opens new possibilities for diagnostics and treatment. IMPORTANCEE. coli infectious diarrhea is an important contributor to child mortality worldwide. However, diagnosing and thus treating E. coli infections remain challenging due to technical and other reasons associated with the limitations of the traditional culture-based techniques and the requirement to apply Koch’s postulates. In this study, we integrated traditional microbiology techniques with metagenomics and epidemiological data in order to identify cases of diarrhea where E. coli was most likely the causative disease agent and evaluate specific signatures in the disease-state gut microbiome that distinguish between diffuse adherent, enterotoxigenic, and enteropathogenic E. coli pathotypes. Therefore, our methodology and results should be highly relevant for diagnosing and treating diarrheal infections and have important applications in public health.

Escherichia coli is a leading contributor to infectious diarrhea and child mortality worldwide, but it remains unknown how alterations in the gut microbiome vary for distinct E. coli pathotype infections and whether these signatures can be used for diagnostic purposes. Further, the majority of enteric diarrheal infections are not diagnosed with respect to their etiological agent(s) due to technical challenges. To address these issues, we devised a novel approach that combined traditional, isolate-based and molecular-biology techniques with metagenomics analysis of stool samples and epidemiological data. Application of this pipeline to children enrolled in a case-control study of diarrhea in Ecuador showed that, in about half of the cases where an E. coli pathotype was detected by culture and PCR, E. coli was likely not the causative agent based on the metagenome-derived low relative abundance, the level of clonality, and/or the virulence gene content. Our results also showed that diffuse adherent E. coli (DAEC), a pathotype that is generally underrepresented in previous studies of diarrhea and thus, thought not to be highly virulent, caused several small-scale diarrheal outbreaks across a rural to urban gradient in Ecuador. DAEC infections were uniquely accompanied by coelution of large amounts of human DNA and conferred significant shifts in the gut microbiome composition relative to controls or infections caused by other E. coli pathotypes. Our study shows that diarrheal infections can be efficiently diagnosed for their etiological agent and categorized based on their effects on the gut microbiome using metagenomic tools, which opens new possibilities for diagnostics and treatment. IMPORTANCE E. coli infectious diarrhea is an important contributor to child mortality worldwide. However, diagnosing and thus treating E. coli infections remain challenging due to technical and other reasons associated with the limitations of the traditional culture-based techniques and the requirement to apply Koch’s postulates. In this study, we integrated traditional microbiology techniques with metagenomics and epidemiological data in order to identify cases of diarrhea where E. coli was most likely the causative disease agent and evaluate specific signatures in the disease-state gut microbiome that distinguish between diffuse adherent, enterotoxigenic, and enteropathogenic E. coli pathotypes. Therefore, our methodology and results should be highly relevant for diagnosing and treating diarrheal infections and have important applications in public health.

The Sustainable Development Goals recognize that the availability and quality of improved water sources affect how households use and benefit from these sources. Although unreliability in piped water supplies in low- and middle-income countries (LMICs) has been described, few studies have assessed household coping strategies in response to unreliable water supplies and associated health outcomes. We characterized unreliability in the piped water supply of the town of Borbon, Ecuador over the twelve years following a major upgrade, as well as household coping strategies and associations with diarrhea. We examined trends in primary and secondary drinking water sources, water storage, and water treatment using longitudinal data collected from 2005 to 2012. In 2017, a follow-up survey was administered (N = 202) and a subset of 84 household water samples were tested for chlorine residual levels and microbial contamination. From 2005 to 2017, access to a household water connection increased from 19.4% to 90.3%. However, reliability decreased over time, as in the latter half of 2009, households had access to piped water 79% of the time, compared to 63% by 2017. Piped water samples were highly contaminated with total coliforms (100% of samples) and Escherichia coli (89% of samples). From 2005 to 2017, households less likely to report drinking water treatment (50.6%–5.0%). And from 2009 to 2017, bottled water was increasingly consumed as the primary drinking water source (18.8%–62.4%). From 2005 to 2012, having a household connection was not statistically significantly associated with diarrhea case status (OR: 0.86 95%CI: 0.53, 1.39). Neither household water treatment nor bottled water consumption were negatively associated with diarrhea. Increased water storage was associated with diarrhea (OR: 1.33 per 10L of water stored, 95%CI: 1.05, 1.69). Household water treatment, and consumption of purchased bottled water, two coping strategies that households may have undertaken in response to an unreliable water supply, were not associated with a reduced likelihood of diarrhea. These data suggest a need to understand how impoverished rural households in LMICs respond to unreliable water supplies, and to develop heath messaging appropriate for this context.

Background Humans are susceptible to over 1400 pathogens. Co-infection by multiple pathogens is common, and can result in a range of neutral, facilitative, or antagonistic interactions within the host. Soil-transmitted helminths (STH) are powerful immunomodulators, but evidence of the effect of STH infection on the direction and magnitude of concurrent enteric microparasite infections is mixed. Methods We collected fecal samples from 891 randomly selected children and adults in rural Laos. Samples were analyzed for 5 STH species, 6 viruses, 9 bacteria, and 5 protozoa using a quantitative reverse transcription polymerase chain reaction (qRT-PCR) assay. We utilized logistic regression, controlling for demographics and household water, sanitation, and hygiene access, to examine the effect of STH infection on concurrent viral, bacterial, and protozoal infection. Results We found that STH infection was associated with lower odds of concurrent viral infection [odds ratio (OR): 0.48, 95% confidence interval (CI): 0.28–0.83], but higher odds of concurrent bacterial infections (OR: 1.81, 95% CI: 1.06–3.07) and concurrent protozoal infections (OR: 1.50, 95% CI: 0.95–2.37). Trends were consistent across STH species. Conclusions The impact of STH on odds of concurrent microparasite co-infection may differ by microparasite taxa, whereby STH infection was negatively associated with viral infections but positively associated with bacterial and protozoal infections. Results suggest that efforts to reduce STH through preventive chemotherapy could have a spillover effect on microparasite infections, though the extent of this impact requires additional study. The associations between STH and concurrent microparasite infection may reflect a reverse effect due to the cross-sectional study design. Additional research is needed to elucidate the exact mechanism of the immunomodulatory effects of STH on concurrent enteric microparasite infection. Electronic supplementary material The online version of this article (10.1186/s13071-019-3471-2) contains supplementary material, which is available to authorized users.

This paper critiques blockchain-based “smart contracts,” which aim to automatically and securely execute obligations without reliance on a centralized enforcement authority. Though smart contracts do have some features that might serve the goals of social justice and fairness, I suggest that they are based on a thin conception of what law does, and how it does it. Smart contracts focus on the technical form of contract to the exclusion of the social contexts within which contracts operate, and the complex ways in which people use them. In the real world, contractual obligations are enforced through all kinds of social mechanisms other than formal adjudication—and contracts serve many functions that are not explicitly legal in nature, or even designed to be formally enforced. I describe three categories of contracting practices in which people engage (the inclusion of facially unenforceable terms, the inclusion of purposefully underspecified terms, and willful nonenforcement of enforceable terms) to illustrate how contracts actually “work.” The technology of smart contracts neglects the fact that people use contracts as social resources to manage their relations. The inflexibility that they introduce, by design, might short-circuit a number of social uses to which law is routinely put. Therefore, I suggest that attention to the social and relational contexts of contracting are essential considerations for the discussion, development, and deployment of smart contracts.

The objective was to evaluate the characteristics of exposure to OP pesticides and health status in Chilean farm workers from the Maule Region. An occupational health questionnaire was administered in 207 agricultural and non-agricultural workers. For the group of agricultural workers, we asked about specific occupational exposure history and symptoms of OP pesticide poisoning. The main health problem of the exposed group was previous OP pesticide poisoning (p 0.001). Fifty-six percent of agricultural workers reported symptoms consistent with acute OP pesticide poisoning. The use of respiratory personal protective equipment and younger age were protective against these symptoms, and number of years of OP pesticide exposure was positively associated with reporting symptoms of poisoning. Of the pesticide applicators 47 % reported using chlorpyrifos. The regulations regarding use and application of pesticides should be strengthened, as should training and intervention with workers to improve the use of personal protective equipment.