Spatiotemporal Analysis Exploring the Effect of Law Enforcement Drug Market Disruptions on Overdose, Indianapolis, Indiana, 2020-2021.

Objectives. To test the hypothesis that law enforcement efforts to disrupt local drug markets by seizing opioids or stimulants are associated with increased spatiotemporal clustering of overdose events in the surrounding geographic area. Methods. We performed a retrospective (January 1, 2020 to December 31, 2021), population-based cohort study using administrative data from Marion County, Indiana. We compared frequency and characteristics of drug (i.e., opioids and stimulants) seizures with changes in fatal overdose, emergency medical services nonfatal overdose calls for service, and naloxone administration in the geographic area and time following the seizures. Results. Within 7, 14, and 21 days, opioid-related law enforcement drug seizures were significantly associated with increased spatiotemporal clustering of overdoses within radii of 100, 250, and 500 meters. For example, the observed number of fatal overdoses was two-fold higher than expected under the null distribution within 7 days and 500 meters following opioid-related seizures. To a lesser extent, stimulant-related drug seizures were associated with increased spatiotemporal clustering overdose. Conclusions. Supply-side enforcement interventions and drug policies should be further explored to determine whether they exacerbate an ongoing overdose epidemic and negatively affect the nation's life expectancy. (Am J Public Health. 2023;113(7):750-758. https://doi.org/10.2105/AJPH.2023.307291).

Association between race, shooting hot spots, and the surge in gun violence during the COVID-19 pandemic in Philadelphia, New York and Los Angeles.

Gun violence rates increased in U.S. cities in 2020 and into 2021. Gun violence rates in U.S. cities is typically concentrated in racially segregated neighborhoods with higher poverty levels. However, poverty levels and demographics alone do not explain the high concentration of violence or its relative change over time. In this paper, we examine the extent to which the increase in shooting victimization in Philadelphia, New York, and Los Angeles during the 2020-2021 pandemic was concentrated in gun violence hot spots, and how the increase impacted race and ethnic disparities in shooting victimization rates. We find that 36% (Philadelphia), 47% (New York), and 55% (Los Angeles) of the increase in shootings observed during the period 2020-2021 occurred in the top decile of census block groups, by aggregate number of shootings, and that the race/ethnicity of victims in these gun violence hot spots were disproportionately Black and Hispanic. We discuss the implications of these findings as they relate to racial disparities in victimization and place-based efforts to reduce gun violence.

Impact of Medicaid, Race/Ethnicity, and Criminal Justice Referral on Opioid Use Disorder Treatment.

We examined the impact of Medicaid expansion and of race/ethnicity on medication-assisted treatment (MAT) for opioid use disorder among those referred for treatment through the criminal justice system. Using a cross-sectional design, we combined data from the Substance Use and Mental Health Services Administration's Treatment Episode Data Set with data on Medicaid expansion and age-adjusted mortality for drug poisoning deaths. Logistic regression was performed within state panels from 2012 to 2016, with 2014 excluded due to this being the transitional Medicaid expansion year. We found that Medicaid expansion led to an increase in the use of MAT to treat those referred to substance treatment facilities through the criminal justice system. We also identified key racial disparities in the use of MAT for those referred from the criminal justice system, with Blacks and Hispanics less likely to receive MAT than non-Hispanic Whites.

Hawkes process modeling of COVID-19 with mobility leading indicators and spatial covariates.

Hawkes processes are used in statistical modeling for event clustering and causal inference, while they also can be viewed as stochastic versions of popular compartmental models used in epidemiology. Here we show how to develop accurate models of COVID-19 transmission using Hawkes processes with spatial-temporal covariates. We model the conditional intensity of new COVID-19 cases and deaths in the U.S. at the county level, estimating the dynamic reproduction number of the virus within an EM algorithm through a regression on Google mobility indices and demographic covariates in the maximization step. We validate the approach on both short-term and long-term forecasting tasks, showing that the Hawkes process outperforms several models currently used to track the pandemic, including an ensemble approach and an SEIR-variant. We also investigate which covariates and mobility indices are most important for building forecasts of COVID-19 in the U.S.

Changes in public-police cooperation following the murder of George Floyd.

The murder of George Floyd triggered a broad social response and noticeable shift in public opinion of policing. Since policing is dependent upon public cooperation, a question is whether the shift in opinion had an effect on police calls-for-service. Data from Los Angeles and New York City are evaluated using a regression discontinuity design. Violent crime, property crime, and quality-of-life disorder calls are analyzed to address differences in reporting norms. The role of racial-ethnic composition of local areas is assessed by examining census tracts where the majority of the residential population is Asian, Black, Hispanic, or White. Following the murder of George Floyd, in New York City violent crime, property crime, and quality-of-life calls all increased significantly. In Los Angeles, quality-of-life calls for service decreased significantly. The increase in violent crime calls observed in New York was greatest in areas where the majority of residents are Black, whereas the increase in property crime calls was the greatest in areas where a majority of residents are White. The decrease in quality-of-life calls observed in Los Angeles was in areas where the majority of residents are White. In both cases, the effect was relatively short-lived.

Gang-related crime in Los Angeles remained stable following COVID-19 social distancing orders.

Research Summary: The onset of extreme social distancing measures is expected to have a dramatic impact on crime. Here, we examine the impact of mandated, city-wide social distancing orders aimed at limiting the spread of COVID-19 on gang-related crime in Los Angeles. We hypothesize that the unique subcultural processes surrounding gangs may supersede calls to shelter in place and allow gang-related crime to persist. If the normal guardianship of people and property is also disrupted by social distancing, then we expect gang violence to increase. Using autoregressive time series models, we show that gang-related crime remained stable and crime hot spots largely stationary following the onset of shelter in place. Policy Implications: In responding to disruptions to social and economic life on the scale of the present pandemic, both police and civilian organizations need to anticipate continued demand, all while managing potential reductions to workforce. Police are faced with this challenge across a wide array of crime types. Civilian interventionists tasked with responding to gang-related crime need to be prepared for continued peacekeeping and violence interruption activities, but also an expansion of responsibilities to deal with "frontline" or "street-level" management of public health needs.

Impact of COVID-19 Pandemic on Drug Overdoses in Indianapolis.

We described the change in drug overdoses during the COVID-19 pandemic in one urban emergency medical services (EMS) system. Data was collected from Marion County, Indiana (Indianapolis), including EMS calls for service (CFS) for suspected overdose, CFS in which naloxone was administered, and fatal overdose data from the County Coroner's Office. With two sample t tests and ARIMA time series forecasting, we showed changes in the daily rates of calls (all EMS CFS, overdose CFS, and CFS in which naloxone was administered) before and after the stay-at-home order in Indianapolis. We further showed differences in the weekly rate of overdose deaths. Overdose CFS and EMS naloxone administration showed an increase with the social isolation of the Indiana stay-at-home order, but a continued increase after the stay-at-home order was terminated. Despite a mild 4% increase in all EMS CFS, overdose CFS increased 43% and CFS with naloxone administration increased 61% after the stay-at-home order. Deaths from drug overdoses increased by 47%. There was no change in distribution of age, race/ethnicity, or zip code of those who overdosed after the stay-at-home order was issued. We hope this data informs policy-makers preparing for future COVID-19 responses and other disaster responses.

The challenges of modeling and forecasting the spread of COVID-19.

The coronavirus disease 2019 (COVID-19) pandemic has placed epidemic modeling at the forefront of worldwide public policy making. Nonetheless, modeling and forecasting the spread of COVID-19 remains a challenge. Here, we detail three regional-scale models for forecasting and assessing the course of the pandemic. This work demonstrates the utility of parsimonious models for early-time data and provides an accessible framework for generating policy-relevant insights into its course. We show how these models can be connected to each other and to time series data for a particular region. Capable of measuring and forecasting the impacts of social distancing, these models highlight the dangers of relaxing nonpharmaceutical public health interventions in the absence of a vaccine or antiviral therapies.

Impact of social distancing during COVID-19 pandemic on crime in Los Angeles and Indianapolis.

Governments have implemented social distancing measures to address the ongoing COVID-19 pandemic. The measures include instructions that individuals maintain social distance when in public, school closures, limitations on gatherings and business operations, and instructions to remain at home. Social distancing may have an impact on the volume and distribution of crime. Crimes such as residential burglary may decrease as a byproduct of increased guardianship over personal space and property. Crimes such as domestic violence may increase because of extended periods of contact between potential offenders and victims. Understanding the impact of social distancing on crime is critical for ensuring the safety of police and government capacity to deal with the evolving crisis. Understanding how social distancing policies impact crime may also provide insights into whether people are complying with public health measures. Examination of the most recently available data from both Los Angeles, CA, and Indianapolis, IN, shows that social distancing has had a statistically significant impact on a few specific crime types. However, the overall effect is notably less than might be expected given the scale of the disruption to social and economic life.

Eliminating malaria in the American South: an analysis of the decline of malaria in 1930s Alabama.

Until the 1930s, malaria was endemic throughout large swaths of the American South. We used a Poisson mixture model to analyze the decline of malaria at the county level in Alabama (an archetypical Deep South cotton state) during the 1930s. Employing a novel data set, we argue that, contrary to a leading theory, the decline of malaria in the American South was not caused by population movement away from malarial areas or the decline of Southern tenant farming. We elaborate and provide evidence for an alternate explanation that emphasizes the role of targeted New Deal-era public health interventions and the development of local-level public health infrastructure. We show that, rather than disappearing as a consequence of social change or economic improvements, malaria was eliminated in the Southern United States in the face of economic dislocation and widespread and deep-seated poverty.

Effect of localization, length and orientation of chondrocytic primary cilium on murine growth plate organization.

The research investigates the role of the immotile chondrocytic primary cilium in the growth plate. This study was motivated by (i) the recent evidence of the mechano-sensorial function of the primary cilium in kidney tubule epithelial cells and (ii) the distinct three-dimensional orientation patterns that the chondrocytic primary cilium forms in articular cartilage in the presence or the absence of loading. For our investigation, we used the Smad1/5(CKO) mutant mouse, whose disorganized growth plate is due to the conditional deletion of Smad 1 and 5 proteins that also affect the so-called Indian Hedgehog pathway, whose physical and functional topography has been shown to be partially controlled by the primary cilium. Fluorescence and confocal microscopy on stained sections visualized ciliated chondrocytes. Morphometric data regarding position, orientation and eccentricity of chondrocytes, and ciliary localization on cell membrane, length and orientation, were collected and reconstructed from images. We established that both localization and orientation of the cilium are definite, and differently so, in the Smad1/5(CKO) and control mice. The orientation of the primary cilium, relative to the major axis of the chondrocyte, clusters at 80° with respect to the anterior-posterior direction for the Smad1/5(CKO) mice, showing loss of the additional clustering present in the control mice at 10°. We therefore hypothesized that the clustering at 10° contains information of columnar organization. To test our hypothesis, we prepared a mathematical model of relative positioning of the proliferative chondrocytic population based on ciliary orientation. Our model belongs to the category of "interactive particle system models for self-organization with birth". The model qualitatively reproduced the experimentally observed chondrocytic arrangements in growth plate of each of the Smad1/5(CKO) and control mice. Our mathematically predicted cell division process will need to be observed experimentally to advance the identification of ciliary function in the growth plate.