Scalable deep learning to identify brick kilns and aid regulatory capacity.

Improving compliance with environmental regulations is critical for promoting clean environments and healthy populations. In South Asia, brick manufacturing is a major source of pollution but is dominated by small-scale, informal producers who are difficult to monitor and regulate-a common challenge in low-income settings. We demonstrate a low-cost, scalable approach for locating brick kilns in high-resolution satellite imagery from Bangladesh. Our approach identifies kilns with 94.2% accuracy and 88.7% precision and extracts the precise GPS coordinates of every brick kiln across Bangladesh. Using these estimates, we show that at least 12% of the population of Bangladesh (>18 million people) live within 1 km of a kiln and that 77% and 9% of kilns are (illegally) within 1 km of schools and health facilities, respectively. Finally, we show how kilns contribute up to 20.4 µg/[Formula: see text] of [Formula: see text] (particulate matter of a diameter less than 2.5 µm) in Dhaka when the wind blows from an unfavorable direction. We document inaccuracies and potential bias with respect to local regulations in the government data. Our approach demonstrates how machine learning and Earth observation can be combined to better understand the extent and implications of regulatory compliance in informal industry.

Reproductive and Social Policies, Sociopolitical Stress, and Implications for Maternal and Child Health Equity.

PURPOSE OF REVIEW: Although many environmental exposures (e.g., air pollution) are geographically patterned and persist as a result of historic economic policies (e.g., redlining), the impact of reproductive and social policies on maternal and child health remains incompletely understood. Reproductive and social policies are increasingly important for maternal and child health equity, particularly following the 2022 US Supreme Court decision in Dobbs v Jackson Women's Health Organization ("Dobbs decision"), which restricted access to abortion. Here, we summarize the literature from original research studies examining influences of reproductive and social policy on maternal and child health, focusing on impacts on adverse birth outcomes and policies as sources of stress. RECENT FINDINGS: Several studies suggest that those most impacted by the Dobbs decision are younger, non-white, socioeconomically disadvantaged, and living in states with less access to government safety net programs, all of which are compounded by environmental injustices. Further, studies conducted in the wake of the Dobbs decision find elevated stress levels among women of reproductive age. This may represent one pathway leading to adverse birth outcomes, as epidemiologic studies demonstrate that preterm birth rates increased following the 2016 election, a period of heightened stress. Reproductive and social policies are understudied contributors to adverse outcomes for reproductive-aged women and their children. This has important implications for maternal and child health equity, as those who will be the most impacted by reproductive and social policies already experience the highest rates of adverse birth outcomes and environmental toxicant exposure.