State prisons nationwide house approximately 1,306,000 inmates, which is more than half (57%) of the total population of incarcerated individuals on any given day in the United States. Program evaluation is essential to ensuring that state prison systems adopt effective programs and policies. The gold standard methodology for evaluating outcomes of programs and policies is the randomized controlled trial (RCT). This paper presents an overview of the RCT design as a program evaluation method, describes examples of RCT evaluations in both criminal justice generally and a state prison context specifically, and also discusses considerations and challenges to be addressed when seeking to conduct an RCT evaluation in a state prison. The takeaway from this paper is that, while conducting RCT evaluations can be met with skepticism and challenges in a state prison environment, it is possible to overcome these challenges and to conduct RCT evaluations in state prisons in order to best determine the impact of state prison policies and programs.

This study uses quasi-experimental analyses to estimate the effectiveness of police-operated CCTV cameras in Milwaukee, Wisconsin. Most studies have focused on how cameras can deter crime. But, like many other agencies, the Milwaukee Police Department strategically deployed their cameras in high-crime, high-traffic intersections to aid criminal investigations. Thus, this study examines the impact of CCTV cameras on crimes and crime clearances. The authors also examined the differential impacts of CCTV in three treatment groups: all intersections that received a new camera, intersections where new cameras were installed alongside existing cameras, and intersections where only new cameras were installed. The authors used propensity score matching to create comparison groups of camera-free intersections, then employed difference-in-differences estimation with negative binomial and Poisson panel regression models to determine whether CCTV cameras have an impact on various categories of crimes and clearances. Despite overall crime declines in Milwaukee during the study period, the authors found that treatment intersections experienced more crimes post-intervention than comparison areas, likely because camera operators were using them to detect incidents that would have otherwise gone unreported. They also found limited evidence that CCTV cameras improve crime clearances.

Jails and prisons are major sites of novel coronavirus (SARS-CoV-2) infection. Many jurisdictions in the United States have therefore accelerated release of low-risk offenders. Early release, however, does not address how arrest and pre-trial detention practices may be contributing to disease spread. Using data from Cook County Jail, in Chicago, Illinois, one of the largest known nodes of SARS-CoV-2 spread, the authors analyze the relationship between jailing practices and community infections at the zip-code level. The authors find that jail cycling (i.e., cycling in and out of jail) is a significant predictor of SARS-CoV-2 infection, accounting for 55% of the variance in case rates across zip codes in Chicago and 37% in Illinois. By comparison, jail cycling far exceeds race, poverty, public transit utilization, and population density as a predictor of variance. The data suggest that cycling through Cook County Jail alone is associated with 15.7% of all documented novel coronavirus disease (COVID-19) cases in Illinois and 15.9% in Chicago as of April 19, 2020.

In the 2015–16 school year, 52% of undergraduates were enrolled in sub-baccalaureate programs, and 69% of these sub-baccalaureate students were enrolled in occupational education programs. Among these occupational education students, health sciences was the most common field of study, followed by business and marketing. These sub-baccalaureate health sciences students more commonly enrolled in public 2-year institutions than in other types of institutions, as did sub-baccalaureate students in general. Both sub-baccalaureate health sciences students and sub-baccalaureate students in general more often sought an associate’s degree than a certificate. However, a smaller proportion of health sciences students than sub-baccalaureate students in general sought an associate’s degree, and a higher proportion sought a certificate. Compared with all undergraduate students, higher proportions of sub-baccalaureate students are women, older adults, and Black and Hispanic. These findings are accentuated within health sciences for women, older adults, and Black students. Although 58% of all sub-baccalaureate students were female, this number increased to 83% within the health sciences. In addition, a larger proportion of health sciences students were age 25 or older compared with sub-baccalaureate students in general. Finally, the proportion of students in health sciences who were Black was larger than the proportion among all sub-baccalaureate students.

Public school facilities primarily serve an educational role, and they also serve a civic role as voting places and emergency shelters. School districts collectively spend tens of billions of dollars each year on facilities construction needs at the nearly 100,000 K-12 public schools nationwide. This report examines (1) the common facility condition issues school districts identify in public schools and how they have done so and (2) school districts’ highest priorities for their school facility renovations and updates, and how districts and states fund them. The authors found that districts’ highest priorities for school facilities were improving security, expanding technology, and addressing health hazards; about half of districts needed to update or replace multiple systems like heating, ventilation, and air conditioning (HVAC) or plumbing; an estimated one-third of schools needed HVAC system updates; and funding for school facilities primarily came from local government sources.

Schools funded by the Bureau of Indian Education (BIE) are required under the federal Individuals with Disabilities Education Act (IDEA) to provide services for eligible students with disabilities, such as learning disabilities or health impairments. Services for these students are listed in individualized education programs (IEP). The authors found that BIE schools did not provide or did not account for 38% of special education and related service time for students with disabilities, according to analysis of school documentation for a 4-month review period. This included one school that did not provide any services to three students. While BIE has plans to improve documentation of such services, it has not established whether and when missed services should be made up, which has led to inconsistent practices among schools. Establishing consistent requirements for making up missed services could help students receive the special education and related services they need to make academic progress.

Student-centered learning describes various approaches that keep students' goals, interests, and needs central to the teaching and learning process. Despite the recent proliferation of student-centered learning approaches, researchers and practitioners are still learning about which strategies are most effective for supporting student achievement and how to measure them. This report summarizes a study on the validity, reliability, and usability of the Measuring and Improving Student-Centered Learning Toolkit, which was developed to help school systems measure, understand, and reflect on the extent of student-centered learning and equitable distribution of student-centered learning opportunities in high schools. Key findings are that the toolkit instruments measure student-centered learning constructs as intended and may be useful in differentiating among schools with differing levels of student-centered learning. Survey scales were generally internally consistent and could be used to distinguish among the responses of individual students, instructional staff, school leaders, and district leaders. Although users found that the toolkit process provided them with useful information, they also found the process burdensome and lengthy. User concerns about the burden of toolkit administration and its potential evaluative nature led to revisions of some toolkit content.

This report looks at the roughly 18 million Americans, or about 7% of the adult population, who were veterans of the U.S. Armed Forces in 2018. Ranging from 18 to over 100 years old, they served in conflicts as diverse as the Korean War and the Global War on Terrorism. This report provides an overview of these men and women, such as how many veterans alive today served in World War II, the characteristics of Vietnam veterans, and how many Gulf War veterans are disabled. Highlights from the report include: the number of veterans in the United States declined by a third, from 26.4 million to 18.0 million between 2000 and 2018; there are fewer than 500,000 World War II veterans alive today, down from 5.7 million in 2000; women make up a growing share of veterans – today, about 9% of veterans (or 1.7 million) are women and by 2040 that number is projected to rise to 17%; the largest cohort of veterans alive today served during the Vietnam Era (6.4 million), which lasted from 1964 to 1975; the second largest cohort of veterans served during peacetime only (4.0 million); and the median age of veterans today is 65 years. By service period, Post-9/11 veterans are the youngest with a median age of about 37, Vietnam Era veterans have a median age of about 71, and World War II veterans are the oldest with a median age of about 93.

This report focuses on the role (and aggregates the wisdom) of a specific set of intermediaries that are doing development differently in rural America. In the report they are called Rural Development Hubs (or Hubs for short). The report focuses on Rural Development Hubs because they are main players advancing an asset-based, wealth-building, approach to rural community and economic development in the United States. They are the most visible actors in rural America designing and implementing efforts that simultaneously (1) increase and improve the assets that are fundamental to current and future prosperity: individual, intellectual, social, cultural, built, natural, political and financial capital; (2) increase the local ownership and control of those assets; and (3) always include low-income people, places and firms in the design of their efforts — and in the benefits. In short, Hubs focus on all the critical ingredients in a region’s system that either advance or impede prosperity — the integrated range of social, economic, health and environmental conditions needed for people and places to thrive. The report recommends increased investments in rural America, increasing the nation’s rural cultural competency, learning from trust already developed in existing Hubs, eradicating government systems and structures that disadvantage rural areas, and designing policies and programs with rural implementation in mind.

Even before the COVID-19 pandemic, millions of Americans lacked stable, affordable housing. Now, the crisis has highlighted the social and economic costs of this crucial gap in the safety net. People living in poor-quality, overcrowded, or unstable housing—or without any home at all—cannot follow public health directives to safely “shelter in place.” As a result, they are at far greater risk of contracting the virus, along with other chronic illness. Once the current public health crisis has been contained, policymakers should make more serious efforts to reduce the number of households who lack affordable, stable, decent-quality housing, and focus on three goals: (1) Increase the amount of long-term affordable rental housing, especially in high-opportunity communities; (2) protect existing affordable rental housing from physical deterioration and financial insecurity; (3) support affordable housing projects currently in the pipeline that face financial obstacles due to the pandemic. In this piece, the authors explain why each of these goals is critical to supporting affordable housing infrastructure across the U.S. They then explore strategies aimed at achieving the first goal, specifically through the acquisition of existing housing. Several policies used in recent decades offer lessons for the design of similar programs moving forward, providing both examples to emulate and pitfalls to avoid. Future work will explore policy models that support the second and third goals. Finally, they pose a series of policy design questions to help stakeholders tailor policies to local needs and capacities.

Infectious disease models can help guide policy decisions, such as how to allocate health care resources in response to COVID-19. Interpreting them requires understanding their purpose, limitations, and assumptions. For example, a model may project the need for hospital beds based on the assumption that past trends will continue. But if human behavior changes—for instance, if social distancing is relaxed—then the forecast is likely to be less accurate. A noted statistician once said, “All models are wrong, but some are useful.” In other words, all outbreak models simplify reality but can still help with decisions and to improve understanding. This report provides information on COVID-19 modeling, opportunities for using infections disease models, and challenges with using infectious disease models.

Governments around the world are responding to the novel coronavirus (COVID-19) pandemic with unprecedented policies designed to slow the growth rate of infections. Many actions, such as closing schools and restricting populations to their homes, impose large and visible costs on society, but their benefits cannot be directly observed and are currently understood only through process-based simulations. Here, the authors compile new data on 1,717 local, regional, and national non-pharmaceutical interventions deployed in the ongoing pandemic across localities in China, South Korea, Italy, Iran, France, and the United States. They then apply reduced-form econometric methods, commonly used to measure the effect of policies on economic growth, to empirically evaluate the effect that these anti-contagion policies have had on the growth rate of infections. In the absence of policy actions, they estimate that early infections of COVID-19 exhibit exponential growth rates of roughly 38% per day. The authors find that anti-contagion policies have significantly and substantially slowed this growth. Some policies have different impacts on different populations, but the authors obtain consistent evidence that the policy packages now deployed are achieving large, beneficial, and measurable health outcomes. They estimate that across these six countries, interventions prevented or delayed on the order of 62 million confirmed cases, corresponding to averting roughly 530 million total infections. These findings may help inform whether or when these policies should be deployed, intensified, or lifted, and they can support decision-making in the other 180+ countries where COVID-19 has been reported.

Many people have raised concerns about the accuracy of COVID-19 data from China. This report presents strong evidence that China's reported COVID-19 caseload was undercounted by a factor of nearly 40. The authors used a COVID-19 Air Traffic Visualization tool to estimate the likely number of infections in China in early 2020. The tool combines COVID-19 case data from Johns Hopkins University with detailed air travel data from the International Air Transport Association. From December 31, 2019, to January 22, 2020, China reported a daily average of 172 cases of COVID-19 among its residents. This number of confirmed cases was equivalent to just one per 8.2 million residents in the country per day. Using the detailed flight data over that same period of time, the authors determined that the five countries most at risk of importing COVID-19 from China were, in descending order of risk, Japan, Thailand, South Korea, the United States, and Taiwan. But far fewer than 8.2 million passengers flew from China to the five countries over that 23-day period. Just more than 1 million passengers flew from China to Japan and Thailand each, while slightly more than 750,000 flew to South Korea, 500,000 flew to the United States, and fewer than 400,000 flew to Taiwan. Thus, all of these passengers from China totaled fewer than 3.7 million, for an expected COVID-19 exportation rate of less than one case to all five of these countries combined. However, COVID-19 cases were already being reported in all five countries during this time. This trend would be exceedingly unlikely given the low reported case count in China.