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Background: The burden of diarrheal diseases remains high among children in low- income countries. Enteropathogens are challenging to control because they are transmitted via multiple pathways. Chickens are an important animal protein source, but live chickens and their products are often highly contaminated with enteropathogens. Objectives: We conducted this study to a) understand the contribution of multiple transmission pathways to the force of infection of Campylobacter spp. and nontyphoidal Salmonella spp., b) quantify the potential impact of reducing each pathway on human infection, and c) quantify hypothesized pathway reduction from the context of Maputo, Mozambique. Methods: We developed transmission models for Campylobacter and Salmonella that captured person-to-person, water- to- person, food-to-person, soil-to-person, animal-to-person, and all-other-sources-to-person in an urban, low-income setting in Mozambique. We calibrated these models using prevalence data from Maputo, Mozambique and estimates of attributable fraction of transmission pathways for the region. We simulated the prevalence of human infection after reducing transmission through each pathway. Results: Simulation results indicated that if foodborne transmission were reduced by 90%, the prevalence of Campylobacter and Salmonella infection would decline by [52.2%; 95% credible interval (CrI): 39.7, 63.8] and (46.9%; 95% CrI: 39, 55.4), respectively. Interruption of any other pathway did not have a substantial impact. Combined with survey and microbiology data, if contamination of broiler chicken meat at informal markets in Maputo could be reduced by 90%, the total infection of Campylobacter and Salmonella could be reduced by 21% (16-26%) and 12% (10- 13%), respectively. Discussion: Our transmission models showed that the foodborne transmission has to be reduced to control enteropathogen infections in our study site, and likely in other similar contexts, but mitigation of this transmission pathway has not received sufficient attention. Our model can serve as a tool to identify effective mitigation opportunities to control zoonotic enteropathogens. https://doi.org/10.1289/EHP12314, Introduction Diarrheal diseases are a substantial source of childhood morbidity and mortality. (1) In contexts where enteropathogen transmission is high, repeated asymptomatic infections also contributed to undernutrition and growth faltering [...]

Background: Small-scale poultry production is widespread and increasing in low- and middle-income countries (LMICs). Exposure to enteropathogens in poultry feces increases the hazard of human infection and related sequela, and the burden of disease due to enteric infection in children Objectives: To improve the understanding of potential exposures to enteropathogens carried by chickens, we used mixed methods to map and quantify microbial hazards along production value chains among broiler, layer, and indigenous chickens in Maputo, Mozambique. Methods: To map and describe the value chains, we conducted 77 interviews with key informants working in locations where chickens and related products are sold, raised, and butchered. To quantify microbial hazards, we collected chicken carcasses (n = 75) and fecal samples (n = 136) from chickens along the value chain and assayed them by qPCR for the chicken- associated bacterial enteropathogens C. jejuni/coli and Salmonella spp. Results: We identified critical hazard points along the chicken value chains and identified management and food hygiene practices that contribute to potential exposures to chicken-sourced enteropathogens. We detected C. jejuni/coli in 84 (76%) of fecal samples and 52 (84%) of carcass rinses and Salmonella spp. in 13 (11%) of fecal samples and 16 (21%) of carcass rinses. Prevalence and level of contamination increased as chickens progressed along the value chain, from no contamination of broiler chicken feces at the start of the value chain to 100% contamination of carcasses with C. jejuni/coli at informal markets. Few hazard mitigation strategies were found in the informal sector. Discussion: High prevalence and concentration of C. jejuni/coli and Salmonella spp. contamination along chicken value chains suggests a high potential for exposure to these enteropathogens associated with chicken production and marketing processes in the informal sector in our study setting. We identified critical control points, such as the carcass rinse step and storage of raw chicken meat, that could be intervened in to mitigate risk, but regulation and enforcement pose challenges. This mixed-methods approach can also provide a model to understand animal value chains, sanitary risks, and associated exposures in other settings. https://doi.org/10.1289/EHP11761, Introduction Foodborne illness results in an estimated 420,000 deaths annually, 30% of which occur in children Annual global production of feces from animals (primarily cattle, chickens, and sheep) is estimated [...]

'I have not failed. I've just found 10,000 ways that will not work.'--Thomas Edison Scientists and engineers often come up with brilliant ideas, but in the end technology is only [...]

Norovirus is the most common cause of outbreaks of acute gastroenteritis (AGE) in the United States (2,2). The Centers for Disease Control and Prevention (CDC) collects data on AGE outbreaks [...]

Abstract: This Article offers a comprehensive survey of privacy dependencies--the many ways that our privacy depends on the decisions and disclosures of other people. What we do and what we [...]

Background: 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. Objectives: 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. Methods: 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. Results: 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. Discussion: 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, Background Climate change is projected to induce increased frequency and intensity of precipitation in many regions throughout the United States under both low and high emissions scenarios. (1,2) The southeastern [...]

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, Introduction Climate change is expected to affect health conditions with known environmental determinants, including diarrheal disease (Ebi 2017). Diarrheal disease is already one of the leading causes of death in [...]

This Article examines the matrix of vulnerabilities that low-income people face as a result of the collection and aggregation of big data and the application of predictive analytics. On one hand, big data systems could reverse growing economic inequality by expanding access to opportunities for low-income people. On the other hand, big data could widen economic gaps by making it possible to prey on low-income people or to exclude them from opportunities due to biases entrenched in algorithmic decision-making tools. New kinds of 'networked privacy' harms, in which users are simultaneously held liable for their own behavior and the actions of those in their networks, may have particularly negative impacts on the poor. This Article reports on original empirical findings from a large, nationally-representative telephone survey with an oversample of low-income American adults, and highlights how these patterns make particular groups of low-status Internet users uniquely vulnerable to various forms of surveillance and networked privacy-related problems. In particular, a greater reliance on mobile connectivity, combined with lower usage of privacy-enhancing strategies, may contribute to various privacy and security-related harms. The Article then discusses three scenarios in which big data--including data gathered from social media inputs--is being aggregated to make predictions about individual behavior: employment screening, access to higher education, and predictive policing. Analysis of the legal frameworks surrounding these case studies reveals a lack of legal protections to counter digital discrimination against low-income people. In light of these legal gaps, the Article assesses leading proposals for enhancing digital privacy through the lens of class vulnerability, including comprehensive consumer privacy legislation, digital literacy, notice and choice regimes, and due process approaches. As policymakers consider reforms, the Article urges greater attention to impacts on low-income persons and communities., INTRODUCTION I. THE INTERSECTION OF PRIVACY AND POVERTY A. Brief History of Privacy-Related Vulnerabilities and Surveillance of the Poor B. The Evolving Nature of Privacy Harms Experienced by the Poor [...]

Background: The southeastern United States consistently has high salmonellosis incidence, but disease drivers remain unknown. Salmonella is regularly detected in this region's natural environment, leading to numerous exposure opportunities. Rainfall patterns may impact the survival/transport of environmental Salmonella in ways that can affect disease transmission. Objectives: This study investigated associations between short-term precipitation (extreme rainfall events) and longer- term precipitation (rainfall conditions antecedent to these extreme events) on salmonellosis counts in the state of Georgia in the United States. Methods: For the period 1997-2016, negative binomial models estimated associations between weekly county-level extreme rainfall events (>90th percentile of daily rainfall) and antecedent conditions (8-week precipitation sums, categorized into tertiles) and weekly county-level salmonellosis counts. Results: In Georgia's Coastal Plain counties, extreme and antecedent rainfall were associated with significant differences in salmonellosis counts. In these counties, extreme rainfall was associated with a 5% increase in salmonellosis risk (95% CI: 1%, 10%) compared with weeks with no extreme rainfall. Antecedent dry periods were associated with a 9% risk decrease (95% CI: 5%, 12%), whereas wet periods were associated with a 5% increase (95% CI: 1%, 9%), compared with periods of moderate rainfall. In models considering the interaction between extreme and antecedent rainfall conditions, wet periods were associated with a 13% risk increase (95% CI: 6%, 19%), whereas wet periods followed by extreme events were associated with an 11% increase (95% CI: 5%, 18%). Associations were substantially magnified when analyses were restricted to cases attributed to serovars commonly isolated from wildlife/environment (e.g., Javiana). For example, wet periods followed by extreme rainfall were associated with a 34% risk increase (95% CI: 20%, 49%) in environmental serovar infection. Conclusions: Given the associations of short-term extreme rainfall events and longer-term rainfall conditions on salmonellosis incidence, our findings suggest that avoiding contact with environmental reservoirs of Salmonella following heavy rainfall events, especially during the rainy season, may reduce the risk of salmonellosis. https://doi.org/10.1289/EHP4621, Introduction Every year, over 9 million cases of foodborne illness occur in the United States. Nontyphoidal Salmonella is estimated to cause 1 million of these cases (with 23,000 hospitalizations and [...]

The icsP promoter of Shigella spp. is repressed by H-NS and derepressed by VirB. Here, we show that an inverted repeat located between positions -1144 and -1130 relative to the icsP transcription start site is necessary for VirB-dependent derepression. The atypical location of this cis-acting site is discussed.

Although the efficacy of chlorine disinfection under controlled laboratory conditions is well known, the effectiveness of chlorine under field point-of-use (POU) conditions is still not clearly understood and may be impacted by a variety of factors. This study evaluated the effectiveness of POU chlorine disinfection in rural Ecuador under typical use conditions and compared this effectiveness with the efficacy in controlled laboratory conditions. While reductions of indicator organisms were slightly higher in households that used chlorination, no significant differences were seen between households employing POU chlorination and the households with no chlorination (1-1.5 [log.sub.10] median reductions for chlorinating households and 0.31-0.55 [log.sub.10] for nonchlorinating households, depending on the indicator organism). In contrast, significant reduction of all test organisms was found when simulating POU conditions in the laboratory. This study demonstrates that POU chlorination can be considerably less effective under actual field conditions than would be predicted based on its laboratory efficacy (3-5 [log.sub.10] median reductions for chlorinated and 0-0.3 [log.sub.10] for non-chlorinated samples). Human factors (including improper storage and chlorine dosing) and uncontrolled water quality effects are hypothesized to impact significantly the effectiveness of chlorine disinfection., Introduction Consumption of fecally contaminated water is a leading cause of death in rural regions of less-developed countries (Briscoe, 1986). According to the World Health Organization (WHO, 2004), 1.8 million [...]

BACKGROUND: To design the most appropriate interventions to improve water quality and supply, information is needed to assess water contamination in a variety of community settings, including those that rely [...]

BACKGROUND: Discoveries that emerging and re-emerging pathogens have their origin in environmental change has created an urgent need to understand how these environmental changes impact disease burden. In this article we present a framework that provides a context from which to examine the relationship between environmental changes and disease transmission and a structure from which to unite disparate pieces of information from a variety of disciplines. METHODS: The framework integrates three interrelated characteristics of environment-disease relationships: a) Environmental change manifests in a complex web of ecologic and social factors that may ultimately impact disease; these factors are represented as those more distally related and those more proximally related to disease. b) Transmission dynamics of infectious pathogens mediate the effects that environmental changes have on disease. c) Disease burden is the outcome of the interplay between environmental change and the transmission cycle of a pathogen. RESULTS: To put this framework into operation, we present a matrix formulation as a means to define important elements of this system and to summarize what is known and unknown about the these elements and their relationships. The framework explicitly expresses the problem at a systems level that goes beyond the traditional risk factor analysis used in public health, and the matrix provides a means to explicitly express the coupling of different system components. CONCLUSION: This coupling of environmental and disease transmission processes provides a muchneeded construct for furthering our understanding of both specific and general relationships between environmental change and infectious disease. KEY WORDS: environmental change, infectious disease, interdisciplinary, system theory, transmission dynamics. Environ Health Perspect 115:1216-1223 (2007). doi:10.1289/ehp.9806 available via http://dx.doi.org/ [Online 31 May 2007], Public health scientists are increasingly discovering that the recent emergence or re-emergence of infectious diseases has an origin in environmental change (McMichael and Martens 2002; Morse 1995; Patz et al. [...]

Environmental change plays a large role in the emergence of infectious disease. The construction of a new road in a previously roadless area of northern coastal Ecuador provides a valuable natural experiment to examine how changes in the social and natural environment, mediated by road construction, affect the epidemiology of diarrheal diseases. Twenty-one villages were randomly selected to capture the full distribution of village population size and distance from a main road (remoteness), and these were compared with the major population center of the region, Borbon, that lies on the road. Estimates of enteric pathogen infection rates were obtained from case-control studies at the village level. Higher rates of infection were found in nonremote vs. remote villages [pathogenic Escherichia coli: odds ratio (OR) = 8.4, confidence interval (CI) 1.6, 43.5; rotavirus: OR = 4.0, CI 1.3, 12.1; and Giardia: OR = 1.9, CI 1.3, 2.7]. Higher rates of all-cause diarrhea were found in Borbon compared with the 21 villages (RR = 2.0, CI 1.5, 2.8), as well as when comparing nonremote and remote villages (OR = 2.7, CI 1.5, 4.8). Social network data collected in parallel offered a causal link between remoteness and disease. The significant and consistent trends across viral, bacterial, and protozoan pathogens suggest the importance of considering a broad range of pathogens with differing epidemiological patterns when assessing the environmental impact of new roads. This study provides insight into the initial health impacts that roads have on communities and into the social and environmental processes that create these impacts. community study | developing country | diarrheal disease | environment | humans

A report by the National Academy of Sciences in 1985 concluded that traumatic injuries are epidemic in proportions, increasing in numbers every year, and represent the greatest health hazard in [...]