What do surrogate safety metrics measure? Understanding driving safety as a continuum.

Road safety is an important public health issue; technology, policy, and educational interventions to prevent crashes are of significant interest to researchers and policymakers. In particular, there is significant ongoing research to proactively evaluate the safety of new technologies, including autonomous vehicles, before enough crashes occur to directly measure their impact. We analyze the distributional form of five diverse datasets that approximate motor vehicle safety incident severity, including one dataset of hard braking events that characterizes the severity of non-crash incidents. Our empirical analysis finds that all five datasets closely fit a lognormal distribution (Kolmogorov-Smirnov distance < 0.013; significance of loglikelihood ratio with other distributions < 0.000029). We demonstrate a linkage between two well-known but largely qualitative safety frameworks and the severity distributions observed in the data. We create a formal model of the Swiss Cheese Model (SCM) and show through analysis and simulations that this formalization leads to a lognormal distribution of the severity continuum of safety-critical incidents. This finding is not only consistent with the empirical data we examine, but represents a quantitative restatement of Heinrich's Triangle, another heretofore largely qualitative framework that hypothesizes that safety events of increasing severity have decreasing frequency. Our results support the use of more frequent, low-severity events to rapidly assess safety in the absence of less frequent, high-severity events for any system consistent with our formalization of SCM. This includes any complex system designed for robustness to single-point failures, including autonomous vehicles.

Demographic and travel characteristics and self-reported predeparture SARS-CoV-2 testing behavior in air passengers entering the United States from foreign destinations from July to September 2021.

INTRODUCTION: From January 2021 to June 2022, the United States Centers for Disease Control and Prevention required predeparture SARS-CoV-2 testing for all air passengers arriving into the United States from a foreign country. METHODS: Using data collected during a surveillance project, we described predeparture testing behavior among a convenience sample of international air passengers entering the United States from July to September 2021 at six US ports of entry. We analyzed pairwise relationships between self-reported test type, test timing, demographic and travel characteristics, and COVID-19 vaccination status using chi-square and Fisher's exact tests. RESULTS: Participants were more likely to get a NAAT versus antigen test if they identified as non-Hispanic Asian or Pacific Islander (68.2%, n = 173), non-Hispanic Black (62.6%, n = 147), or if they preferred not to report race and ethnicity (60.8%, n = 209) when compared to those who identified as non-Hispanic White (47.1%, n = 1086, all p < 0.05). Those who identified as Hispanic or Latino (n = 671) were less likely to get a NAAT than the non-Hispanic White group (39.5% vs. 47.1%, p < 0.05). Participants arriving in the US from the Americas were less likely to get a NAAT (38.5%, n = 871) compared to those arriving from Europe (45.5%, n = 1165, p < 0.05). Participants who reported receiving their predeparture test 2 days or 3 or more days before departure were more likely to report receiving a NAAT (52.2%, n = 879, and 60.2%, n = 410, respectively) than those who reported testing within 1 day (41.4%, n = 1040, all p < 0.001) of departure. DISCUSSION: Test type was significantly associated with race and ethnicity, departure region, and test timing. Differences likely reflected regional disparities in the availability of tests at the time of the activity. Discrepancies in predeparture test timing and type worldwide may have consequences for the effectiveness and equity of travel requirements in future pandemics.

A mixed-methods, population-based study of a syndemic in Soweto, South Africa.

A syndemic has been theorized as a cluster of epidemics driven by harmful social and structural conditions wherein the interactions between the constitutive epidemics drive excess morbidity and mortality. We conducted a mixed-methods study to investigate a syndemic in Soweto, South Africa, consisting of a population-based quantitative survey (N = 783) and in-depth, qualitative interviews (N = 88). We used ethnographic methods to design a locally relevant measure of stress. Here we show that multimorbidity and stress interacted with each other to reduce quality of life. The paired qualitative analysis further explored how the quality-of-life impacts of multimorbidity were conditioned by study participants' illness experiences. Together, these findings underscore the importance of recognizing the social and structural drivers of stress and how they affect the experience of chronic illness and well-being.

Healthcare seeking for chronic illness among adult slum dwellers in Bangladesh: A descriptive cross-sectional study in two urban settings.

INTRODUCTION: Accompanying rapid urbanization in Bangladesh are inequities in health and healthcare which are most visibly manifested in slums or low-income settlements. This study examines socioeconomic, demographic and geographic patterns of self-reported chronic illness and healthcare seeking among adult slum dwellers in Bangladesh. Understanding these patterns is critical in designing more equitable urban health systems and in enabling the country's goal of Universal Health Coverage by 2030. METHODS: This descriptive cross-sectional study compares survey data from slum settlements located in two urban sites in Bangladesh, Tongi and Sylhet. Reported chronic illness symptoms and associated healthcare-seeking strategies are compared, and the catastrophic impact of household healthcare expenditures are assessed. RESULTS: Significant differences in healthcare-seeking for chronic illness were apparent both within and between slum settlements related to sex, wealth score (PPI), and location. Women were more likely to use private clinics than men. Compared to poorer residents, those from wealthier households sought care to a greater extent in private clinics, while poorer households relied more on drug shops and public hospitals. Chronic symptoms also differed. A greater prevalence of musculoskeletal, respiratory, digestive and neurological symptoms was reported among those with lower PPIs. In both slum sites, reliance on the private healthcare market was widespread, but greater in industrialized Tongi. Tongi also experienced a higher probability of catastrophic expenditure than Sylhet. CONCLUSIONS: Study results point to the value of understanding context-specific health-seeking patterns for chronic illness when designing delivery strategies to address the growing burden of NCDs in slum environments. Slums are complex social and geographic entities and cannot be generalized. Priority attention should be focused on developing chronic care services that meet the needs of the working poor in terms of proximity, opening hours, quality, and cost.

Community Gun Violence as a Social Determinant of Elementary School Achievement.

The association of indirect exposure to firearm-related violence and standardized test scores among third grade elementary school children were analyzed using geospatial mapping of police department data for all gunshots in Syracuse, NY (n = 2, 127) and state standardized test scores from 2009-2015. Confirmed gunshots were geocoded and mapped across the city and neighborhood school catchment areas. Third grade standardized New York State test scores for English Language Arts (ELA) and math were coded as dichotomous variables of proficient and below proficient scores. State standardized test scores for ELA and math were found to be 50% lower in the elementary schools located within higher concentration gunshot areas, than in elementary schools in lower gunshot areas. Higher levels of gun violence within school catchment areas were significantly associated with higher rates of ELA and math failure (p ≤ .05). These findings suggest that community violence may be an important, though under recognized, social determinant of poor school performance.