The Effects of Race and Ethnicity on Admission, Graduation, and Recidivism in the Milwaukee County Adult Drug Treatment Court

Drug courts play a key role in the criminal justice system by diverting individuals from incarceration and providing them with resources to address substance use issues and reduce criminal recidivism. However, it is unclear whether drug courts reflect—or even exacerbate—preexisting racial/ethnic disparities in the criminal justice system. While prior literature has offered some insight into the influence of race and ethnicity on drug court success, much of the focus has been on outcomes (i.e., program completion and recidivism) rather than disparities at earlier stages (i.e., referral to admittance). The current study adds to this body of research by evaluating the Milwaukee County Adult Drug Treatment Court to examine whether racial/ethnic disparities exist at several stages of the drug court process: (1) referral to admittance, (2) likelihood of graduation, and (3) likelihood of recidivism. Results of the analyses determined racial/ethnic disparities in the likelihood of admission to the drug court, as well as the likelihood of graduation. There were no racial/ethnic disparities found in the likelihood of recidivism. The analyses also identified several additional variables that were influential in the likelihood of admission (risk score, prior record), likelihood of graduation (age, prior record, custody sanctions), and recidivism (drug court outcome).

Predicting SARS-CoV-2 Asymptomatic Infection Rate of Inpatients: A Time Series Analysis

Background: Asymptomatic SARS-CoV-2 infections play a crucial role in viral transmission. However, they are often difficult to identify given that widespread surveillance has not been the norm. We sought to determine whether COVID-19 rates reported at the county level could predict the positivity rates for SARS-CoV-2 among asymptomatic patients tested in a large academic health system. Methods: This observational study was conducted from April 23, 2020, to December 10, 2020, at Froedtert Health (FH) system, the largest academic health system in Wisconsin. On April 23, 2020, FH implemented SARS-CoV-2 surveillance among all consecutive admissions not suspected of COVID-19, all patients scheduled for elective procedures and deliveries, and all asymptomatic patients with known exposures. Samples were processed by the FH laboratory using molecular methods (RT-PCR). To obtain the daily number of newly confirmed COVID-19 cases in Milwaukee County, we accessed the Wisconsin Department of Health Services publicly available COVID-19 database. For the purpose of this study, COVID-19 rates were defined as the percentage of positive tests among all daily tests performed at the county level, while SARS-CoV-2 positivity rates were the percentage of positive tests among all daily surveillance tests performed at FH among asymptomatic patients. The association between COVID-19 rates in Milwaukee County and asymptomatic rates at FH were assessed using an autoregressive moving average time series analysis. To examine the association between these rates, we fitted a seventh-order autoregression for the residuals based on autocorrelation function and partial autocorrelation function plots of the residuals from linear regression. Results: From April 23, 2020, to December 10, 2020, there were 2,347 new asymptomatic infections detected at FH and 75,196 new COVID-19 cases reported in Milwaukee County. Figure 1 shows the time-series plot of asymptomatic SARS-CoV-2 positivity rates at FH and Figure 2 shows COVID-19 rates in Milwaukee County. As the COVID-19 rate in Milwaukee County increased by 1 unit, the asymptomatic infection rate in FH decreased by 0.024 unit (95% CI, −0.053 to 0.004; P = .095) after accounting for autocorrelation over time. Thus, there was no association between these rates. Conclusions: The positivity rates among asymptomatic patients at a large medical center were not predicted by the positivity rate at the county level. This finding suggests that the epidemiology at a county level may be determined by pockets in the population who may not interact, and thus not affect, the positivity rates among asymptomatic patients served by a hospital system within the county.Funding: NoDisclosures: None

A Multisite Evaluation of Prosecutor-Led Pretrial Diversion: Effects on Conviction, Incarceration, and Recidivism

Recent years have witnessed a resurgence of interest in prosecutor-led pretrial diversion programs, yet up-to-date research on the effectiveness of these programs is lacking. Participants in four prosecutor-led diversion programs, Cook County, IL (separate analyses for misdemeanor and felony participants), Milwaukee County, WI (two distinct programs varying in participant risk level and treatment intensity), and Chittenden County, VT, were propensity-score matched to comparison defendants (total n = 5,040). All programs yielded a significant decrease in instant case conviction (mean odds ratio = .12) and use of jail sentences (mean odds ratio = .33). There was also a trend toward reduced re-arrest at 2 years (mean odds ratio = .79). Three of four diversion programs significantly delayed onset of first re-arrest. Taken together, results support the effectiveness of a diverse set of prosecutor-led pretrial diversion programs that varied in charge severity, participant risk level, and program duration and intensity.

SAFER model: Strategic allocation of fundamental epidemic resources

Background To describe the Strategic Allocation of Fundamental Epidemic Resources (SAFER) model as a method to inform equitable community distribution of critical resources and testing infrastructure. Methods The SAFER model incorporates a four-quadrant design to categorize a given community based on two scales: testing rate and positivity rate. Three models for stratifying testing rates and positivity rates were applied to census tracts in Milwaukee County, Wisconsin: using median values (MVs), cluster-based classification and goal-oriented values (GVs). Results Each of the three approaches had its strengths. MV stratification divided the categories most evenly across geography, aiding in assessing resource distribution in a fixed resource and testing capacity environment. The cluster-based stratification resulted in a less broad distribution but likely provides a truer distribution of communities. The GVs grouping displayed the least variation across communities, yet best highlighted our areas of need. Conclusions The SAFER model allowed the distribution of census tracts into categories to aid in informing resource and testing allocation. The MV stratification was found to be of most utility in our community for near real time resource allocation based on even distribution of census tracts. The GVs approach was found to better demonstrate areas of need.

Revealing fine-scale spatiotemporal differences in SARS-CoV-2 introduction and spread

Evidence-based public health approaches that minimize the introduction and spread of new SARS-CoV-2 transmission clusters are urgently needed in the United States and other countries struggling with expanding epidemics. Here we analyze 247 full-genome SARS-CoV-2 sequences from two nearby communities in Wisconsin, USA, and find surprisingly distinct patterns of viral spread. Dane County had the 12th known introduction of SARS-CoV-2 in the United States, but this did not lead to descendant community spread. Instead, the Dane County outbreak was seeded by multiple later introductions, followed by limited community spread. In contrast, relatively few introductions in Milwaukee County led to extensive community spread. We present evidence for reduced viral spread in both counties following the statewide “Safer at Home” order, which went into effect 25 March 2020. Our results suggest patterns of SARS-CoV-2 transmission may vary substantially even in nearby communities. Understanding these local patterns will enable better targeting of public health interventions.

461. Presentation and Demographics of Veterans Tested for COVID-19 Infection

Background COVID-19, caused by the Severe Acute Respiratory Syndrome-Related Coronavirus 2 (SARS-CoV-2), has been a major cause of morbidity and mortality in the United States since its emergence in Wuhan, China. As of June 2020, there are over 20,000 confirmed cases and nearly 700 deaths due to COVID-19 in Wisconsin, with the majority of COVID-19 related deaths occurring within Milwaukee County. COVID-19 infections are disproportionately affecting minority communities across the United States. Presentation and outcomes vary, with the elderly and those with underlying diseases having poorer outcomes. Methods This retrospective chart review of patients tested for COVID-19 infection from March 2020-May 2020 at the Zablocki VA Medical Center, Milwaukee, WI evaluated demographics, comorbidities, presenting symptoms, and duration of symptoms. The primary outcomes analyzed were whether there were significant differences in demographic data, comorbidities, and presentation between patients testing positive or not positive for COVID-19. Results A total of 173 patients tested for COVID-19 were included during the study period, 82 positive and 91 otherwise. Univariate analysis of patient demographics and presenting symptoms are summarized in Table 1. A multivariable logistic regression using stepwise selection (AUC=0.7188) determined patients that tested positive for COVID-19, when controlling for demographics and comorbidities, were more likely to be African-American than White (OR 3.455, CI 1.733–6.887), and more likely to have a diagnosis of diabetes (OR 2.698, CI 1.36–5.353). However, race and diabetes were not informative when symptoms were included in a subsequent model (AUC=0.8458); patients testing positive for COVID-19 were more likely to present with diarrhea (OR 6.926, CI 1.760–6.926) and a higher temperature (OR 2.651, CI 1.533–4.584), but less likely to present with vomiting (OR 0.007, CI < .001-0.161) when compared to patients testing otherwise for COVID-19. Table 1: Univariate Analysis of Variables Associated with Testing Positive for COVID-19 at Zablocki VA Medical Center 3/2020–5/2020 Conclusion Patients testing positive in Milwaukee County are more likely to be African-American and/or diabetic; further highlighting racial disparities in COVID-19. Symptomology at presentation is more related to positive COVID-19 test results than demographics and comorbidities. Disclosures All Authors: No reported disclosures

Prevalence of SARS-CoV-2 asymptomatic infections in two large academic health systems in Wisconsin

SARS-CoV-2 asymptomatic infections may play a critical role in disease transmission. We aim to determine the prevalence of asymptomatic SARS-CoV-2 infection at two hospital systems in two counties in Wisconsin. The SARS-CoV-2 prevalence was 1% or lower at both systems despite the higher incidence of COVID-19 in Milwaukee county

Distinct patterns of SARS-CoV-2 transmission in two nearby communities in Wisconsin, USA

Evidence-based public health approaches that minimize the introduction and spread of new SARS-CoV-2 transmission clusters are urgently needed in the United States and other countries struggling with expanding epidemics. Here we analyze 247 full-genome SARS-CoV-2 sequences from two nearby communities in Wisconsin, USA, and find surprisingly distinct patterns of viral spread. Dane County had the 12th known introduction of SARS-CoV-2 in the United States, but this did not lead to descendant community spread. Instead, the Dane County outbreak was seeded by multiple later introductions, followed by limited community spread. In contrast, relatively few introductions in Milwaukee County led to extensive community spread. We present evidence for reduced viral spread in both counties, and limited viral transmission between counties, following the statewide Safer-at-Home public health order, which went into effect 25 March 2020. Our results suggest that early containment efforts suppressed the spread of SARS-CoV-2 within Wisconsin.