In the first chapter of this dissertation, I exploit the Covid-19 pandemic and associated government restrictions as a natural experiment in order to study the resilience of businesses in the United States. I use a border-county identification strategy with data on government restrictions, employment and open small businesses, in order to assess the resilience of small businesses in the United States. In my main results, I find negative impacts of stay-at-home orders on the number of open small merchants. In particular, shutdowns of businesses accelerated 8 weeks after imposition of a stay-at-home order, suggesting that many businesses were only resilient enough to handle adverse conditions for 8 weeks. On average, a county with a stay-at-home order experienced an additional 1.51 percentage points loss in the number of open small businesses, relative to January 2020, 8 weeks later compared to a neighboring county that did not have a stay-at-home order. Firms were quicker to resort to layoffs. On average a county with an active stay at home order in a month experienced an additional 1.19 percentage point loss in employment, relative to January 2020, the following month compared to a neighbor that did not have a stay-at-home order the previous month. My results suggest that in future scenarios where governments consider enacting similar restrictions further aid is needed for businesses in order to help them stay afloat. In particular, more assistance should be delivered to businesses within two months from the enacting of the order. In the second chapter of this dissertation, I study economic spillovers in the context of theCovid-19 associated government restrictions. I use a detailed geolocation dataset to construct data on the number of visitors per-capita between neighboring counties in the early stages of the pandemic, which I use as a proxy for economic spillovers. I employ a similar border-county identification strategy as in the first chapter to identify the causal effect of stay-at-home orders on inter-county movement. Additionally, I provide evidence for an assumption used in chapter one by examining if there are reduced spillovers in county-pairs that lie in the different commute zones. I find that stay-at-home orders caused reductions in inter-county visits in both directions in a county-pair. That is, I find a decrease in travel from the county without a stay-at-home order to the county with one, as well as a decrease in the opposite direction. On average, a county that does not have stay-at-home order will receive 408 fewer weekly visitors from their neighboring county that has a stay-at-home order. I also examine the effect of stay-at-home orders on the ratio of travel between the two directions in order to find evidence of a net spillover effect between the two counties and fail to find evidence of a net spillover effect. I also find that spillover effects are indeed reduced in neighbor county-pairs where the two counties are in different commute zones. The results of this paper imply that residents in counties with stay-at-home orders decreased travel to their neighboring counties even when those counties did not issue their own orders. In future situations where policy makers need to consider similar restrictions, they should focus on acting more quickly and not be concerned if neighboring counties are not cooperative. In the third chapter of this dissertation, I test the predictions of career concerns models by studying Major League Baseball umpires. Major League Baseball games can be dramatically shaped by minor lapses in judgement from the umpires officiating the game. Due to the indefinite length a game may have, this can include having the game shaped in a way that ends it faster. I study whether evidence for the career concerns model can be found in baseball umpires. A career concerns model would suggest that older umpires, whose careers and reputations are much more established than younger ones, would be more inclined to improperly make judgements that favor the end of the game in extra innings. I use data on MLB umpires and extra-innings games from the 2010-2018 seasons to conduct my empirical analysis and use a linear probability model to isolate the impact of the umpires’ tenure on the probability they make a “bad call.” I find evidence supporting the career concerns hypothesis and that the probability that an umpire makes a bad call that shortens the length of the game and allows them to go home increases with their tenure. I show that these results are likely driven by career concerns, rather than carelessness, by showing their error rate does not increase with tenure in situations where it would not reduce their workload.

Background: Throughout the COVID-19 pandemic, women carried, birthed, and cared for infants in a drastically changed world. For perinatal women, the sudden increase in stressors compounded an already vulnerable time where they are at an elevated risk of developing symptoms of psychopathology. Moreover, the pandemic exacerbated pre-existing racial health disparities and disproportionately impacted Black, Indigenous, and People of Color (BIPOC)— particularly perinatal BIPOC women, due to the intersection of their race and perinatal status. This study investigated the relationships between COVID-19-related stressors and postpartum psychopathology using network analysis. Network analysis is used as an alternative technique for investigating the activation and maintenance of psychopathology and is increasingly used to examine the influence of external variables (e.g., stressors) on network dynamics. The relationship between psychological symptoms and stressors is typically examined in a unilinear manner—that is, stress causes psychopathology or vice versa. By using network analysis, we were able to investigate the bidirectional relationship between COVID-19-related stressors and postpartum psychopathology to reveal new insights into the individual stressor-symptom interactions that may underlie the emergence of psychological disorders for the perinatal population during the pandemic. Methods: Participants (N=630) were recruited via social media and listservs and completed an online Qualtrics survey. Data quality measures were used to identify repeated, incomplete, and potentially fraudulent responses, which were removed prior to data analysis. Goldbricker, inter-item correlations, and variance inflation factor analyses were used to address topological overlap and identify statistically unique items to be included in the networks. A comorbidity symptom network was estimated to investigate the relationship between postpartum depression and anxiety symptoms in all participants. Bridge symptoms between the two conditions were identified using bridge analysis and clique percolation analysis. Next, an expanded model was estimated to investigate the relationship between postpartum symptoms and COVID-19-related stressors. Node-wise predictability and moderation analyses were used to investigate the effects of adding external variables (i.e., positive experiences, maternal functioning domains, and predictors of psychopathology) to the expanded model. Finally, moderated networks were estimated to investigate differences in the structure of the comorbidity network and the expanded network for mothers from different racial and ethnic groups. Results: Fear-based symptoms were central in both the comorbidity and expanded networks and bridged postpartum anxiety and depression symptoms in the comorbidity network. The Depressed Mood and two Home Stress domains were central in the expanded network. Additional bridge symptoms in the comorbidity network included feeling overwhelmed, concentration difficulties, and feeling disliked by others, and in the expanded network included the Postpartum Stress, Emotional Stress, and Difficulty Adjusting domains. Moderation analyses revealed that the more mothers felt competent and the less challenging they perceived their infant’s temperament, the weaker the node connections were in their expanded networks. Furthermore, mothers with a history of prenatal depression, prenatal anxiety, or baby blues had denser expanded networks (i.e., stronger and more unique edges) compared to mothers with no history of these conditions. Contrary to expectations, moderation analyses revealed that: 1) social support and engaging in positive experiences during the pandemic strengthened connections between stressors and symptoms; 2) middle-income mothers had denser networks compared to low- and high-income mothers. Finally, racial network comparisons revealed that Black mothers' comorbidity and expanded networks were denser compared to all other racial groups. Conclusions: Our findings highlight the influence of major contextual changes, such as the COVID-19 pandemic, on network dynamics—that is, previously established peripheral network nodes (e.g., fear) may shift to the center during large-scale events. Therefore, researchers cannot assume that previously identified central nodes will remain as the main drivers of psychopathology irrespective of changes in context, as this may lead to a misdirection of prevention and intervention efforts. Further, our findings underscore that people with multiple intersecting vulnerabilities may be disproportionately impacted by these major events.

COVID-19 exacerbated a pre-existing and well-documented mental health crisis on college campuses in the United States. During COVID-19, more college students than ever before in recorded history reported feelings of anxiety and depression, among other mental health issues. There are myriad possible causes for the decline in mental health among college students. One clear cause is the introduction of the smartphone, its widespread adoption, and its frequent use by college-age people. Research also revealed that an unprecedented number of college students are completely disconnected from religion and spirituality. Studies demonstrated that cultivating a religious or spiritual life can be beneficial for one’s mental well-being. The efforts on college campuses to provide mental health resources for students would benefit from additional support. This care should be accessible to more students and should combat the unfortunate stigma around receiving help for mental health. Undergraduate introductory philosophy courses taken as a requirement by various majors can serve as responses to this call for additional care. These classes are inherently accessible and can offer students an engaging experience with self-care by implementing exercises inspired by philosophy as the art of living. Although philosophy as the art of living does not necessarily have to replace religion or other forms of mental health care, it can offer an experience that is of therapeutic value in the classroom. This tradition has a rich, ancient history of intending to serve this purpose. The objective of this research was to present and examine self-care exercises from philosophy as the art of living and to evaluate how these can be taught in the college classroom in response to the mental health crisis on college campuses. It also aimed to render the experience of teaching these exercises. The research was executed through a hermeneutical and phenomenological approach. The phenomenological methodology was performed by a teacher in the form of a self-study. It was also conducted with the teacher as a witness to what transpired in introductory philosophy classes with thousands of students in dozens of individual classes in a diverse metropolis. A college introductory philosophy course in this epoch of mental health crisis on campuses should abide by philosophy as the art of living’s imperative to decrease suffering. There is a vital need for additional resources to respond to the decline in mental wellness among students. The results of this research demonstrated that philosophy as the art of living and its emphasis on exercises can be successfully applied to the college classroom. In this research, students were given time on a regular basis during class to be in silence, confront Socratic-style questions that encouraged them to examine and care for themselves, practice self-writing to heighten their ability to think and pursue the aim of self-care, and then read to engage with philosophical texts to support their self-care. Students consistently and rigorously engaged with these exercises. Their time spent in silent practice provided an opportunity for therapeutic, meditative, and peaceful reflection. Educators should consider implementing these exercises in introductory philosophy classes and beyond as ways to offer self-care to students who may be struggling with their mental health, as so many are.

Humans’ social relationships determine to a large degree their trajectories in life. Despite strong evidence for the impact of interpersonal relations on wellbeing, the causal links between the two are not yet fully understood. This dissertation offers a new perspective on the mechanisms through which social ties influence negative (excessive drinking) and positive (participation in recreational activities) health behaviors. In three studies employing a unique combination of social network, fMRI, and experience-sampling methods, we propose that health decisions are the result of complex computations involving prior social experiences, perceived social norms, social comparison processes, and current feelings of connections. Each chapter of this dissertation discusses one of these three studies. Chapter 1 provides evidence that past social experiences shape valuations of new information by showing that pairs of students that drink often together tend to have more similar neural responses to novel alcohol cues in regions associated with affective self-generated thought. In addition, this Chapter suggests that researchers must consider the intricate interplay between individuals’ personal goals and their communities’ norms to understand the influence of social environments on neural representations. The degree to which students aligned their neural response patterns to alcohol with those of their peers depended on interactions between their individual motives for drinking and their group’s approval of this behavior. Chapter 2 presents novel findings that people spontaneously represent social information from multiple networks (e.g., popularity and leadership) at a neural level in social cognition (right TPJ, dmPFC) and valuation (vmPFC) regions. Importantly, individuals who display higher neural sensitivity to status differences are also more likely to align their drinking behavior with their group norms in daily life. Together, our results provide insight into the neural mechanisms through which social comparison processes shape conformity and suggest social cognition and valuation regions as important hubs orchestrating this process. While Chapter 1 and Chapter 2 focus on the influence of social ties on drinking, Chapter 3 discusses the protective role of close relations during difficult times. We provide evidence that close college friendships, even if afar, helped young adults cope with the stress of the COVID-19 pandemic. Follow-up between- and within-individual analyses reveal that this buffering effect could be explained by differences in the quality of online interactions (e.g., via phone, text messaging), instances of personal disclosure, and participation in enjoyable activities. All in all, this dissertation advances our understanding of why measures of social wellbeing are the best predictor of health trajectories in life, by highlighting the important role social ties play in shaping valuation of new information, guiding behavior to meet social goals, and protecting against stress by allowing people to engage in recreational activities.

The COVID-19 pandemic elucidated geographical disparities in COVID-19 burden on a globalscale. Geographical disparities in adverse COVID-19 outcomes may suggest population-level drivers of disease, such as environmental exposures. Epidemiological literature provides strong evidence that greater exposure to ambient air pollution, an environmental exposure, is associated with a greater risk of COVID-19 hospitalization and fatality. The pathways by which ambient air pollution exposure influences adverse COVID-19 outcomes are currently unknown. I propose that cardiovascular morbidity is relevant in this pathway, given that cardiovascular morbidity is a predominant risk factor of adverse COVID-19 outcomes, and there are strong and consistent associations between air pollution and cardiovascular morbidity. I suggest that the role of cardiovascular morbidity will be different for historical air pollution (period > 30 days) and short-term air pollution (period < 30 days). By proposing clear causal structures for the relationship between air pollution and adverse COVID-19 outcomes, we can explicate how air pollution leads to greater COVID-19 burden and address the larger goal of reducing geographic disparities in adverse COVID-19 outcomes. This dissertation is comprised of three specific aims. For the first aim, I performed a systematic review of the literature that examined the relationship between ambient air pollution and individual-level adverse COVID-19 outcomes. I identified if and how researchers conceptualized the causal role of comorbidities, specifically cardiovascular morbidities, in the relationship between air pollution and adverse COVID-19 outcomes. For the second aim, I examined if cardiovascular morbidity mediates the relationship between historical air pollution and adverse COVID-19 outcomes. For the third aim, I examined if there was evidence of synergistic interaction between short-term air pollution and cardiovascular morbidity in influencing the risk of adverse COVID-19 outcomes, suggesting that the effect of both short-term air pollution and cardiovascular morbidity on adverse COVID-19 is greater than the sum of the individual effects. In conducting the first aim, I used Covidence, a software used to manage systematic reviewstudies, to identify studies that examined the relationship between ambient air pollution exposure and individual-level adverse COVID-19, using the Embase, MEDLINE, and Web of Science databases. In conducting the empirical aims, I used a retrospective cohort study design using INSIGHT-Clinical Research Network (CRN) data, a harmonized repository of inpatient electronic health records in New York City (NYC) across metropolitan healthcare systems (3/1/2020-2/28/2021). INSIGHT-CRN included data pertaining to sociodemographics, diagnoses, outcomes, and residential ZIP Code to link air pollution exposure. For the second aim, I used the New York City Community Air Survey (NYCCAS) to estimate historical air pollution exposure to particulate matter (PM2.5), black carbon (BC), nitrogen dioxide (NO₂), and ozone (O₃) on a ZIP Code level (2009-2019). For the third aim, I used the 2020 Environmental Protection Agency (EPA) Community Multiscale Air Quality (CMAQ) downscaler modeled data, which estimated 2020 daily exposure to PM2.5 and O3 on a census tract level. I aggregated the census tract data to ZIP Code using a spatial weighting approach and estimated short-term air pollution as a 7-day average of daily PM2.5 and O3 exposure prior to patient hospitalization. For the first aim, the systematic review included 42 studies that examined the relationship between ambient air pollution, such as exposures to PM2.5, NO₂, and O₃, and individual-level adverse COVID-19, such as hospitalization, intensive care unit (ICU) admission, intensive respiratory support (IRS), and fatality. The studies were primarily retrospective cohort study designs, and were conducted in the United States and Europe (2020 to 2021). The majority of studies adjusted for cardiovascular morbidity without causal role specification, whereas some studies identified cardiovascular morbidity as a mediator or an effect modifier. For the second aim, I found evidence of cardiovascular morbidity mediating the relationship between historical air pollution and risk of acute respiratory distress syndrome (ARDS), dialysis use, ventilation use, and COVID-19 fatality, but not risk of pneumonia from March to June 2020, within areas of greater hospital catchment. Indirect effects suggest that historical air pollution increases the risk of atrial fibrillation and myocardial infarction, which increases risk of adverse COVID-19. For the third aim, I found evidence of synergistic interaction between short-term PM2.5 and presence of cardiovascular morbidities for only risk of COVID-19 pneumonia, in the latter half of 2020. Overall, there was evidence that cardiovascular morbidity mediates the relationship betweenhistorical air pollution and more severe COVID-19 outcomes, while cardiovascular morbidity synergistically interacts with short-term air pollution for risk of acute respiratory infections, such as pneumonia. This dissertation assesses the pathways by which air pollution may influence risk of adverse COVID-19, in better examining the causal role of cardiovascular morbidity. Knowledge gained could be used to mitigate population-level vulnerabilities to air pollution, and encourage population-level pandemic preparedness in the future.

The human immune system is made up of cells and molecules distributed across the body, which provide protection from acute viral infection and can be maintained in diverse tissue sites as memory to protect against repeat viral exposure. Vaccine technology has leveraged our understanding of human immunity to induce immune memory in humans without infection. However, we continue to encounter novel infections, as evidenced by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, which necessitates the development of new vaccines and formulations, including the mRNA vaccine platform. Vaccine development began with serendipitous discoveries and, even today, often relies on empirical approaches that prioritize clinical outcomes over immunologic ones. For the recently developed coronavirus disease of 2019 (COVID-19) mRNA vaccines, we know that they confer clinical protection that wanes over time but have a more limited understanding of the immune memory they induce. Specifically, we do not know the tissue distribution of vaccine memory, these vaccines’ capacity to induce tissue-resident memory or various functional programs, and the relative role of B and T cells in protection. Through a unique collaboration with the New York City area organ procurement organization, LiveOnNY, we collected blood, bone marrow, spleen, lung, and various lymph nodes (LN) from human organ donors who had received COVID-19 mRNA vaccines. Using these tissues, we employed multimodal, high-dimensional analysis tools to investigate the localization, phenotype, maintenance, and functions of COVID-19 vaccine-induced memory in the context of host factors such as age, time post-vaccination, and prior SARS-CoV-2 infection. In samples from 63 organ donors aged 23-86, we found that COVID-19 vaccine memory was distributed across tissues, especially in LN, and was more durable across time post-vaccination and age in tissues than in circulation. Vaccine-specific B cells were mostly class-switched resident memory, while vaccine-specific T cells were variably tissue-resident depending on infection history. Vaccine-specific T cell effector functions were diverse and site-specific with an enhanced regulatory profile in tissues compared to circulating populations. To investigate the interaction between T and B cells in immune memory generation and their relative roles in protection, we also compared the quantity and quality of circulating COVID-19 vaccine induced memory from patients with multiple sclerosis taking B cell depleting (BCD) therapies to those taking other immunomodulatory therapies (non-BCD). In 281 samples from 216 subjects aged 24-78 we found that COVID-19 vaccine induced humoral immunity was completely diminished in the context of B cell depletion, but that cellular immunity, especially CD8+T cells, were enhanced in this context and maintained over time. Further, BCD subjects experienced equivalent numbers of infections following vaccination as non-BCD subjects. Together, these findings demonstrate that T cell responses can develop independently from, and may even be limited by, B cell responses, and that T cells but not B cells are critical for vaccine-induced protection. Ultimately, these findings provide critical insights for future vaccine development; studies must assess LN responses and aim to generate a robust cellular response that includes both regulatory and effector functional profiles within tissues.

By the end of 2020, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), better known as COVID-19, had produced over 82,357,482 confirmed cases and 1,802,393 related deaths worldwide. The first pandemic many had ever experienced, the call of duty for public health professionals in the United States and globally was strong. While the contributions of doctors, nurses, and first responders are frequently acknowledged in the media and health-related publications, forgotten key players include health education specialists. Because of their critical role in public health preparedness and response, special attention should be given to their work during disasters and public health emergencies. As the Screening Manager of the New Jersey Department of Health (DOH) COVID-19 Testing Center located at Bergen Community College, I observed firsthand how COVID-19 made people suffer, but also the resilience among health education specialist responders. Using narrative inquiry to detail my response experience, this dissertation offers the world my story, while highlighting the onset of the pandemic in New Jersey from March to June 2020 and the practice of incorporating relevant health education competencies.

Thesis (LL.M. (Labour Law)) -- University of Limpopo, 2022 / The aim of this research is to determine the laws that regulate affirmative action in the workplace and the impact Covid-19 has on affirmative action. This research focuses on the history of affirmative action in South Africa and the United States of America. Both countries have a similar history of discrimination and racial segregation. The United States of America is one of the most progressive countries on the issue of affirmative action. The comparison of South Africa with the United States of America will enhance the applicability and effectiveness of affirmative action. Past discrimination is a huge contributing factor to the imbalances and inequalities experienced in the workplace. A measure in a form of affirmative action was established to redress past injustices, however, there are many controversies around the topic and its effectiveness. The Covid-19 pandemic has made matters worse in that many people have been laid off, resulting in the retrenchments and the regress of affirmative action and its purpose. The findings of this research conclude that Covid-19 has negatively affected the process of affirmative action. As such, employers during this trying time prefer only individuals who are fully qualified and experienced as the employees have been reduced. As long as affirmative action applies to individuals or a group of individuals with certain skin colour or sex regardless of their past privileges this racial tension might never be relieved. In order to effectively implement affirmative action, South Africa has to focus on the institutions that cause the problem rather than dealing with the final results

This dissertation consists of three essays in applied microeconomics.The first chapter investigates the effect of coroner partisanship on COVID-19 death reporting. The politicization of the COVID-19 pandemic in the United States has raised questions about the integrity and accuracy of death reporting, particularly in jurisdictions with elected, partisan coroners. Using mortality data from the CDC and manually collected data on county-level death certification systems and coroner party affiliation where applicable, I examine the parallel systems of appointed medical examiners and elected coroners and analyze the effect of partisanship on reported COVID-19 deaths. Cross-sectional comparisons do not seem to suggest counties with coroners report fewer deaths than those with medical examiners, and difference-in-differences specifications reveal limited evidence of a statistically significant but not economically meaningful effect of partisanship on reported COVID death counts. The second chapter examines the effect of new information on lead water pipes on housing prices. In 2016, the Water and Sewer Authority of Washington, DC released an online map that contains information on lead service lines (LSLs) for all properties in the district. Using the release as a natural experiment, I estimate the effect of the new information on prices of properties with and without LSLs. Recent literature has found that housing lead reduction policies such as remediation mandates have significant price effects. In DC, while the map’s release was followed by a marked increase in requests for water lead tests, neither a difference-in-differences model nor a repeat sales model captures a significant divergence between housing prices of the two types of properties after the release, implying the housing market response to the information was limited. The second chapter considers the effect of the marriage tax subsidy on the marriage decision of same-sex couples. The U.S. Supreme Court’s ruling on United States v. Windsor in June 2013 compelled the federal government to recognize state-sanctioned same-sex marriages, including for tax purposes. The switch in the income tax filing status for same-sex couples meant that the marriage penalty or subsidy as a result of joint filing became a relevant factor that may enter couples’ marriage decisions. I construct a sample of married and cohabiting same-sex couples in 2012 and 2014 from public-use data of the American Community Survey. Using a difference-in-differences methodology, I do not find evidence that same-sex couples who would earn a higher marriage subsidy became more likely to marry after the Supreme Court ruling.

Traffic is a problem across the globe, reaching perniciously into cities and communities nearly everywhere. The United States (US) has its share of traffic problems; of the ten cities with the highest traffic delay times in 2022, four were in the US. While nearly everyone living in the US has likely experienced traffic congestion of some kind, some cities are notoriously worse than others. In New York City (NYC), traffic congestion has been a problem as far back as 1913, when Fifth Avenue was so traffic-clogged it could take 40 minutes to go 23 blocks. Today, of the 25 most congested traffic corridors in the US, three are in NYC. One of these runs through the South Bronx, an environmental justice neighborhood we highlight in this dissertation. Traffic congestion is a source of air pollution (traffic-related air pollution, or TRAP) and noise, and it can result in property damage, injuries, and fatalities from collisions with other vehicles, pedestrians, or those using other forms of transportation. Both traffic congestion and TRAP have been associated with numerous negative health outcomes. For example, TRAP is associated with respiratory, cardiovascular, neurological, and pregnancy outcomes, including asthma exacerbation, incident childhood and adult asthma, reduced lung function, atherosclerosis, hypertension, stroke, myocardial infarction, cardiovascular-related mortality, cognitive decline, neurodevelopmental outcomes, pregnancy loss, term low birth weight, and small for gestational age birth. In general across the US, communities of color and higher-poverty neighborhoods face greater exposure and health burden from traffic. Throughout this dissertation, we study traffic congestion and TRAP through two lenses: (1) environmental justice; and (2) policy. Additionally, we assess the cardiovascular health impacts of TRAP. In Chapter 1, we provide background on the problem of traffic, focusing on NYC and the South Bronx. In Chapter 2, we present a case study from the South Bronx, where a new trucking-intensive warehouse was opened in 2018. In this study, we quantified the increase in vehicles and trucks following the opening of the warehouse and estimated the resulting increases in black carbon (BC) and noise. We discuss the injustice in the methods used to assess the environmental impact of the warehouse, the warehouse’s siting in a predominantly Black and Lantinx community already overburdened with trucking-intensive industries, and the desire of the community to instead use the land for a community park. In Chapter 3, we present a study quantifying how traffic congestion in NYC changed during the COVID-19 pandemic. We assess how NY on Pause, the state’s stay-at-home order, impacted traffic congestion by comparing the magnitude of traffic decreases in environmentally burdened or systematically disadvantaged neighborhoods to the magnitude of decreases in less burdened and more advantaged neighborhoods. We discuss the implications of these results for upcoming traffic policies in NYC, such as congestion pricing. In Chapter 4, we present a study evaluating diurnal changes in TRAP in NYC during NY on Pause. We discuss the implications of these results for congestion pricing, including the potential timing of TRAP decreases. In Chapter 5, we present an epidemiologic study of TRAP and myocardial infarction (MI) in New York State, identifying hazard windows of exposure in a study period where the mean nitrogen dioxide (NO₂) concentration was substantially lower than the hourly national standard. We discuss implications for the NO₂ National Ambient Air Quality Standards (NAAQS) and suggest that the current standard may be insufficient to protect population cardiovascular health. Finally, in Chapter 6, we conclude with a discussion of recommended research directions and policy considerations.