Associations between neighborhood socioeconomic status, parental education, and executive system activation in youth.

Socioeconomic status (SES) can impact cognitive performance, including working memory (WM). As executive systems that support WM undergo functional neurodevelopment during adolescence, environmental stressors at both individual and community levels may influence cognitive outcomes. Here, we sought to examine how SES at the neighborhood and family level impacts task-related activation of the executive system during adolescence and determine whether this effect mediates the relationship between SES and WM performance. To address these questions, we studied 1,150 youths (age 8-23) that completed a fractal n-back WM task during functional magnetic resonance imaging at 3T as part of the Philadelphia Neurodevelopmental Cohort. We found that both higher neighborhood SES and parental education were associated with greater activation of the executive system to WM load, including the bilateral dorsolateral prefrontal cortex, posterior parietal cortex, and precuneus. The association of neighborhood SES remained significant when controlling for task performance, or related factors like exposure to traumatic events. Furthermore, high-dimensional multivariate mediation analysis identified distinct patterns of brain activity within the executive system that significantly mediated the relationship between measures of SES and task performance. These findings underscore the importance of multilevel environmental factors in shaping executive system function and WM in youth.

Correction: Short-term leprosy forecasting from an expert opinion survey.

[This corrects the article DOI: 10.1371/journal.pone.0182245.].

Short-term leprosy forecasting from an expert opinion survey.

We conducted an expert survey of leprosy (Hansen's Disease) and neglected tropical disease experts in February 2016. Experts were asked to forecast the next year of reported cases for the world, for the top three countries, and for selected states and territories of India. A total of 103 respondents answered at least one forecasting question. We elicited lower and upper confidence bounds. Comparing these results to regression and exponential smoothing, we found no evidence that any forecasting method outperformed the others. We found evidence that experts who believed it was more likely to achieve global interruption of transmission goals and disability reduction goals had higher error scores for India and Indonesia, but lower for Brazil. Even for a disease whose epidemiology changes on a slow time scale, forecasting exercises such as we conducted are simple and practical. We believe they can be used on a routine basis in public health.

Correction: Cost Resulting from Anti-Tuberculosis Drug Shortages in the United States: A Hypothetical Cohort Study.

[This corrects the article DOI: 10.1371/journal.pone.0134597.].

Cost Resulting from Anti-Tuberculosis Drug Shortages in the United States: A Hypothetical Cohort Study.

BACKGROUND: From 2012 through 2014, the United States experienced acute shortages and price escalations of several first-line anti-tuberculosis (TB) medications. Because secondary TB drug regimens are longer and adverse events occur more frequently with them, we sought to conservatively estimate the cost, to patients and the health care system, of TB treatment and medication adverse events from alternative regimens during drug shortages. METHODS: We assessed the cost of treatment for TB disease in the absence of isoniazid (INH), rifampin (RIF), or pyrazinamide (PZA), or both INH and RIF. We simulated adverse events based on published probabilities using a monthly discrete-time stochastic model. For total costs, we summed costs of medications, routine testing, and treatment of adverse events using procedural terminology codes. We report average cost ratios of TB treatment during drug shortages to standard TB treatment. RESULTS: The cost ratio of TB treatment without INH, RIF, or PZA to standard treatment was 1.7 (Range: 1.2, 2.3), 4.9 (Range: 3.2, 7.3), and 1.1 (Range: 0.7, 1.7) times higher, respectively. Without both INH and RIF, the cost ratio was 18.6 (Range: 10.0, 39.0) times higher. When the prices for INH, RIF and PZA were increased, the cost for standard treatment increased by a factor of 2.7 (Range: 1.9, 3.0). The percentage of patients experiencing at least one adverse event while taking standard therapy was 3.9% (Range: 1.3%, 11.8%). This percentage increased to 51.5% (Range: 20.1%, 83.8%) when RIF was unavailable, and increased to 82.5% (Range: 41.2%, 98.5%) when both INH and RIF were unavailable. CONCLUSIONS: Our conservative model illustrates that an interruption in first-line anti-TB medications leads to appreciable additional costs and adverse events for patients. The availability of these drugs in the United States should be ensured. Models that incorporate the effectiveness of alternative regimens, delays in treatment initiation, and TB transmission can provide broader perspectives on the impact of drug shortages.

When does overuse of antibiotics become a tragedy of the commons?

BACKGROUND: Over-prescribing of antibiotics is considered to result in increased morbidity and mortality from drug-resistant organisms. A resulting common wisdom is that it would be better for society if physicians would restrain their prescription of antibiotics. In this view, self-interest and societal interest are at odds, making antibiotic use a classic "tragedy of the commons". METHODS AND FINDINGS: We developed two mathematical models of transmission of antibiotic resistance, featuring de novo development of resistance and transmission of resistant organisms. We analyzed the decision to prescribe antibiotics as a mathematical game, by analyzing individual incentives and community outcomes. CONCLUSIONS: A conflict of interest may indeed result, though not in all cases. Increased use of antibiotics by individuals benefits society under certain circumstances, despite the amplification of drug-resistant strains or organisms. In situations where increased use of antibiotics leads to less favorable outcomes for society, antibiotics may be harmful for the individual as well. For other scenarios, where a conflict between self-interest and society exists, restricting antibody use would benefit society. Thus, a case-by-case assessment of appropriate use of antibiotics may be warranted.

How to make epidemiological training infectious.

Modern infectious disease epidemiology builds on two independently developed fields: classical epidemiology and dynamical epidemiology. Over the past decade, integration of the two fields has increased in research practice, but training options within the fields remain distinct with few opportunities for integration in the classroom. The annual Clinic on the Meaningful Modeling of Epidemiological Data (MMED) at the African Institute for Mathematical Sciences has begun to address this gap. MMED offers participants exposure to a broad range of concepts and techniques from both epidemiological traditions. During MMED 2010 we developed a pedagogical approach that bridges the traditional distinction between classical and dynamical epidemiology and can be used at multiple educational levels, from high school to graduate level courses. The approach is hands-on, consisting of a real-time simulation of a stochastic outbreak in course participants, including realistic data reporting, followed by a variety of mathematical and statistical analyses, stemming from both epidemiological traditions. During the exercise, dynamical epidemiologists developed empirical skills such as study design and learned concepts of bias while classical epidemiologists were trained in systems thinking and began to understand epidemics as dynamic nonlinear processes. We believe this type of integrated educational tool will prove extremely valuable in the training of future infectious disease epidemiologists. We also believe that such interdisciplinary training will be critical for local capacity building in analytical epidemiology as Africa continues to produce new cohorts of well-trained mathematicians, statisticians, and scientists. And because the lessons draw on skills and concepts from many fields in biology--from pathogen biology, evolutionary dynamics of host--pathogen interactions, and the ecology of infectious disease to bioinformatics, computational biology, and statistics--this exercise can be incorporated into a broad array of life sciences courses.

Environmental determinants of infectious disease: a framework for tracking causal links and guiding public health research.

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 much-needed construct for furthering our understanding of both specific and general relationships between environmental change and infectious disease.

Integrating disease control strategies: balancing water sanitation and hygiene interventions to reduce diarrheal disease burden.

OBJECTIVES: Although the burden of diarrheal disease resulting from inadequate water quality, sanitation practices, and hygiene remains high, there is little understanding of the integration of these environmental control strategies. We tested a modeling framework designed to capture the interdependent transmission pathways of enteric pathogens. METHODS: We developed a household-level stochastic model accounting for 5 different transmission pathways. We estimated disease preventable through water treatment by comparing 2 scenarios: all households fully exposed to contaminated drinking water and all households receiving the water quality intervention. RESULTS: We found that the benefits of a water quality intervention depend on sanitation and hygiene conditions. When sanitation conditions are poor, water quality improvements may have minimal impact regardless of amount of water contamination. If each transmission pathway alone is sufficient to maintain diarrheal disease, single-pathway interventions will have minimal benefit, and ultimately an intervention will be successful only if all sufficient pathways are eliminated. However, when 1 pathway is critical to maintaining the disease, public health efforts should focus on this critical pathway. CONCLUSIONS: Our findings provide guidance in understanding how to best reduce and eliminate diarrheal disease through integrated control strategies.

Environmental change and infectious disease: how new roads affect the transmission of diarrheal pathogens in rural Ecuador.

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, Borbón, 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 Borbón 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.

Temporal instability of auditory and visual event-related potentials in posttraumatic stress disorder.

BACKGROUND: We examined P300 measures in patients with posttraumatic stress disorder (PTSD) and control subjects at two different time points to determine event-related potential (ERP) stability over time and the relationship of changes in ERPs to changes in symptom levels. METHODS: Auditory and visual P300 was recorded in a three-condition novelty oddball task in 25 male subjects with combat-related PTSD and 15 male combat-exposed normal control subjects at two time points separated by 6-12 months. Regression analyses were conducted to compare the temporal stability of ERP measures in PTSD and control subjects. Variability in ERP measures over time within PTSD subjects was examined for association with changes in symptom levels. RESULTS: There were no significant differences in P300 amplitude or latency in PTSD versus control subjects at either time point, regardless of stimulus type (target, novel) or modality (auditory, visual). Nine of 24 P300 measures were significantly less predictable over time in the PTSD group compared to control subjects. Variability of P300 measures over time was not associated with fluctuations in symptoms of depression or PTSD. CONCLUSIONS: P300 ERPs are more variable cross-sectionally and over time in PTSD subjects compared to trauma exposed control subjects. Measures of variability about the group mean appear to be more informative about the cognitive electrophysiology of PTSD than measures of central tendency.