Association of a Housing Mobility Program With Childhood Asthma Symptoms and Exacerbations.

Importance: Structural racism has been implicated in the disproportionally high asthma morbidity experienced by children living in disadvantaged, urban neighborhoods. Current approaches designed to reduce asthma triggers have modest impact. Objective: To examine whether participation in a housing mobility program that provided housing vouchers and assistance moving to low-poverty neighborhoods was associated with reduced asthma morbidity among children and to explore potential mediating factors. Design, Setting, and Participants: Cohort study of 123 children aged 5 to 17 years with persistent asthma whose families participated in the Baltimore Regional Housing Partnership housing mobility program from 2016 to 2020. Children were matched to 115 children enrolled in the Urban Environment and Childhood Asthma (URECA) birth cohort using propensity scores. Exposure: Moving to a low-poverty neighborhood. Main Outcomes: Caregiver-reported asthma exacerbations and symptoms. Results: Among 123 children enrolled in the program, median age was 8.4 years, 58 (47.2%) were female, and 120 (97.6%) were Black. Prior to moving, 89 of 110 children (81%) lived in a high-poverty census tract (>20% of families below the poverty line); after moving, only 1 of 106 children with after-move data (0.9%) lived in a high-poverty tract. Among this cohort, 15.1% (SD, 35.8) had at least 1 exacerbation per 3-month period prior to moving vs 8.5% (SD, 28.0) after moving, an adjusted difference of -6.8 percentage points (95% CI, -11.9% to -1.7%; P = .009). Maximum symptom days in the past 2 weeks were 5.1 (SD, 5.0) before moving and 2.7 (SD, 3.8) after moving, an adjusted difference of -2.37 days (95% CI, -3.14 to -1.59; P < .001). Results remained significant in propensity score-matched analyses with URECA data. Measures of stress, including social cohesion, neighborhood safety, and urban stress, all improved with moving and were estimated to mediate between 29% and 35% of the association between moving and asthma exacerbations. Conclusions and Relevance: Children with asthma whose families participated in a program that helped them move into low-poverty neighborhoods experienced significant improvements in asthma symptom days and exacerbations. This study adds to the limited evidence suggesting that programs to counter housing discrimination can reduce childhood asthma morbidity.

Agreement in extreme precipitation exposure assessment is modified by race and social vulnerability.

Epidemiologic investigations of extreme precipitation events (EPEs) often rely on observations from the nearest weather station to represent individuals' exposures, and due to structural factors that determine the siting of weather stations, levels of measurement error and misclassification bias may differ by race, class, and other measures of social vulnerability. Gridded climate datasets provide higher spatial resolution that may improve measurement error and misclassification bias. However, similarities in the ability to identify EPEs among these types of datasets have not been explored. In this study, we characterize the overall and temporal patterns of agreement among three commonly used meteorological data sources in their identification of EPEs in all census tracts and counties in the conterminous United States over the 1991-2020 U.S. Climate Normals period and evaluate the association between sociodemographic characteristics with agreement in EPE identification. Daily precipitation measurements from weather stations in the Global Historical Climatology Network (GHCN) and gridded precipitation estimates from the Parameter-elevation Relationships on Independent Slopes Model (PRISM) and the North American Land Data Assimilation System (NLDAS) were compared in their ability to identify EPEs defined as the top 1% of precipitation events or daily precipitation >1 inch. Agreement among these datasets is fair to moderate from 1991 to 2020. There are spatial and temporal differences in the levels of agreement between ground stations and gridded climate datasets in their detection of EPEs in the United States from 1991 to 2020. Spatial variation in agreement is most strongly related to a location's proximity to the nearest ground station, with areas furthest from a ground station demonstrating the lowest levels of agreement. These areas have lower socioeconomic status, a higher proportion of Native American population, and higher social vulnerability index scores. The addition of ground stations in these areas may increase agreement, and future studies intending to use these or similar data sources should be aware of the limitations, biases, and potential for differential misclassification of exposure to EPEs. Most importantly, vulnerable populations should be engaged to determine their priorities for enhanced surveillance of climate-based threats so that community-identified needs are met by any future improvements in data quality.

Application of Markov models to predict changes in nasal carriage of Staphylococcus aureus among industrial hog operations workers.

Industrial hog operation (IHO) workers can be occupationally exposed to Staphylococcus aureus and may carry the bacteria in their nares. Workers may persistently carry S. aureus or transition between different states of nasal carriage over time: no nasal carriage, nasal carriage of a human-associated strain, and nasal carriage of a livestock-associated strain. We developed a mathematical model to predict the proportion of IHO workers in each nasal carriage state over time, accounting for IHO worker mask use. We also examined data sufficiency requirements to inform development of models that produce reliable predictions. We used nasal carriage data from a cohort of 101 IHO workers in North Carolina, sampled every 2 weeks for 4 months, to develop a three-state Markov model that describes the transition dynamics of IHO worker nasal carriage status over the study period and at steady state. We also stratified models by mask use to examine their impact on worker transition dynamics. If conditions remain the same, our models predicted that 49.1% of workers will have no nasal carriage of S. aureus, 28.2% will carry livestock-associated S. aureus, and 22.7% will carry human-associated S. aureus at steady state. In stratified models, at steady state, workers who reported only occasional mask (<80% of the time) use had a higher predicted proportion of individuals with livestock-associated S. aureus nasal carriage (39.2%) compared to workers who consistently (≥80% of the time) wore a mask (15.5%). We evaluated the amount of longitudinal data that is sufficient to create a Markov model that accurately predicts future nasal carriage states by creating multiple models that withheld portions of the collected data and compared the model predictions to observed data. Our data sufficiency analysis indicated that models created with a small subset of the dataset (approximately 1/3 of observed data) perform similarly to models created using all observed data points. Markov models may have utility in predicting worker health status over time, even when limited longitudinal data are available.

External Societal Costs of Antimicrobial Resistance in Humans Attributable to Antimicrobial Use in Livestock.

Antimicrobial use (AMU) in animal agriculture contributes to antimicrobial resistance (AMR) in humans, which imposes significant health and economic costs on society. Economists call these costs negative externalities, societal costs that are not properly reflected in market prices. We review the relevant literature and develop a model to quantify the external costs of AMU in animal agriculture on AMR in humans. Parameters required for this estimate include (a) the health and economic burden of AMR in humans,(b) the impact of AMU in animal agriculture on AMR in animals, (c) the fraction of AMR in humans attributable to animal agriculture, and (d) AMU in animals. We use a well-documented historic case to estimate an externality cost of about US$1,500 per kilogram of fluoroquinolones administered in US broiler chicken production. Enhanced data collection, particularly on the third and fourth parameters, is urgently needed to quantify more fully the externalities of AMU in animal agriculture.