SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), is thought to spread from person to person primarily by the respiratory route and mainly through close contact (1). Community mitigation strategies can lower the risk for disease transmission by limiting or preventing personto-person interactions (2). U.S. states and territories began implementing various community mitigation policies in March 2020. One widely implemented strategy was the issuance of orders requiring persons to stay home, resulting in decreased population movement in some jurisdictions (3). Each state or territory has authority to enact its own laws and policies to protect the public's health, and jurisdictions varied widely in the type and timing of orders issued related to stay-at-home requirements. To identify the broader impact of these stay-athome orders, using publicly accessible, anonymized location data from mobile devices, CDC and the Georgia Tech Research Institute analyzed changes in population movement relative to stay-at-home orders issued during March 1-May 31, 2020, by all 50 states, the District of Columbia, and five U.S. territories.* During this period, 42 states and territories issued mandatory stay-at-home orders. When counties subject to mandatory state-and territory-issued stay-at-home orders were stratified along rural-urban categories, movement decreased significantly relative to the preorder baseline in all strata. Mandatory stayat-home orders can help reduce activities associated with the spread of COVID-19, including population movement and close person-to-person contact outside the household. Data on state and territorial stay-at-home orders were obtained from government websites containing executive or administrative orders or press releases for each jurisdiction. Each order was analyzed and coded into one of five mutually exclusive categories: 1) mandatory for all persons; 2) mandatory only for persons in certain areas of the jurisdiction; 3) mandatory only for persons at increased risk in the jurisdiction; 4) mandatory only for persons at increased risk in certain areas of the jurisdiction; or 5) advisory or recommendation (i.e., nonmandatory). Jurisdictions that did not issue an order were coded as having no state-or territory-issued

On June 12, 2020, this report was posted as an MMWR Early Release on the MMWR website (https://www.cdc.gov/mmwr). SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), is thought to be transmitted mainly by person-toperson contact (1). Implementation of nationwide public health orders to limit person-to-person interaction and of guidance on personal protective practices can slow transmission (2,3). Such strategies can include stay-at-home orders, business closures, prohibitions against mass gatherings, use of cloth face coverings, and maintenance of a physical distance between persons (2,3). To assess and understand public attitudes, behaviors, and beliefs related to this guidance and COVID-19, representative panel surveys were conducted among adults aged ≥18 years in New York City (NYC) and Los Angeles, and broadly across the United States during May 5-12, 2020. Most respondents in the three cohorts supported stay-at-home orders and nonessential business closures* (United States, 79.5%; New York City, 86.7%; and Los Angeles, 81.5%), reported always or often wearing cloth face coverings in public areas (United States, 74.1%, New York City, 89.6%; and Los Angeles 89.8%), and believed that their state's restrictions were the right balance or not restrictive enough (United States, 84.3%; New York City, 89.7%; and Los Angeles, 79.7%). Periodic assessments of public attitudes, behaviors, and beliefs can guide evidence-based public health decision-making and related prevention messaging about mitigation strategies needed as the COVID-19 pandemic evolves. During May 5-12, 2020, a total of 4,042 adults aged ≥18 years in the United States were invited to complete a web-based survey administered by Qualtrics, LLC. † Surveys were conducted among residents of NYC and Los Angeles to enable comparison of the two most populous cities in the United States with each * Respondents were informed that, for the survey, stay-at-home orders mean that all nonessential services (e.g., dine-in restaurants, bars, social venues, gyms, fitness studios, and convention centers) are shut down. Essential services (e.g., groceries, pharmacies, gas stations, food banks, convenience stores, and delivery restaurants) remain open. Banks, local governments, and law enforcement agencies also remain open. Persons are still allowed to leave their homes but encouraged to observe social distancing guidelines. Public events and gatherings are not allowed. † Eligibility for the nationwide U.S. cohort was determined on the basis of informed consent, age, and residence within the United States. Therefore, consented adult potential respondents residing in NYC and Los Angeles metro areas were eligible to complete surveys as part of the nationwide U.S. or NYC and Los Angeles cohorts. * Nationwide cohort (n = 1,676) only unless otherwise specified. The six respondent characteristic categories shown in the table (gender, age, ethnicity, race, employment status, and essential worker status) account for 32 of 34 significant associations among the 108...

BACKGROUND: Colorectal cancer (CRC) is a leading cause of cancer death in the United States. Early detection through recommended screening has been shown to have favorable treatment outcomes, yet screening rates among the medically underserved and uninsured are low, particularly for rural and minority populations. This study evaluated the effectiveness of a patient navigation program that addresses individual and systemic barriers to CRC screening for patients at rural, federally qualified community health centers. METHODS: This quasiexperimental evaluation compared low-income patients at average risk for CRC (n 5 809) from 4 intervention clinics and 9 comparison clinics. We abstracted medical chart data on patient demographics, CRC history and risk factors, and CRC screening referrals and examinations. Outcomes of interest were colonoscopy referral and examination during the study period and being compliant with recommended screening guidelines at the end of the study period. We conducted multilevel logistic analyses to evaluate the program's effectiveness. RESULTS: Patients at intervention clinics were significantly more likely than patients at comparison clinics to undergo colonoscopy screening (35% versus 7%, odds ratio 5 7.9, P <.01) and be guideline-compliant on at least one CRC screening test (43% versus 11%, odds ratio 5 5.9, P <.001). CONCLUSIONS: Patient navigation, delivered through the Community Cancer Screening Program, can be an effective approach to ensure that lifesaving, preventive health screenings are provided to low-income adults in a rural setting. Cancer 2013;119:3059-66.

BackgroundCommunity coalitions are rooted in complex and dynamic community systems. Despite recognition that environmental factors affect coalition behavior, few studies have examined how community context impacts coalition formation. Using the Community Coalition Action theory as an organizing framework, the current study employs multiple case study methodology to examine how five domains of community context affect coalitions in the formation stage of coalition development. Domains are history of collaboration, geography, community demographics and economic conditions, community politics and history, and community norms and values.MethodsData were from 8 sites that participated in an evaluation of a healthy cities and communities initiative in California. Twenty-three focus groups were conducted with coalition members, and 76 semi-structured interviews were conducted with local coordinators and coalition leaders. Cross-site analyses were conducted to identify the ways contextual domains influenced selection of the lead agency, coalition membership, staffing and leadership, and coalition processes and structures.ResultsHistory of collaboration influenced all four coalition factors examined, from lead agency selection to coalition structure. Geography influenced coalition formation largely through membership and staffing, whereas the demographic and economic makeup of the community had an impact on coalition membership, staffing, and infrastructure for coalition processes. The influence of community politics, history, norms and values was most noticeable on coalition membership.ConclusionsFindings contribute to an ecologic and theory-based understanding of the range of ways community context influences coalitions in their formative stage.

IntroductionThe field of public health is increasingly implementing initiatives intended to make policies, systems, and environments (PSEs) more supportive of healthy behaviors, even though the evidence for many of these strategies is only emerging. Our objective was 3-fold: 1) to describe evaluations of PSE-change programs in which the evaluators followed the steps of the Centers for Disease Control and Prevention’s (CDC’s) Framework for Program Evaluation in Public Health, 2) to share the resulting lessons learned, and 3) to assist future evaluators of PSE-change programs with their evaluation design decisions.MethodsSeven Prevention Research Centers (PRCs) applied CDC’s framework to evaluate their own PSE-change initiatives. The PRCs followed each step of the framework: 1) engage stakeholders, 2) describe program, 3) focus evaluation design, 4) gather credible evidence, 5) justify conclusions, and 6) ensure use and share lessons learned.ResultsEvaluation stakeholders represented a range of sectors, including public health departments, partner organizations, and community members. Public health departments were the primary stakeholders for 4 of the 7 evaluations. Four PRCs used logic models to describe the initiatives being evaluated. Their evaluations typically included both process and outcome questions and used mixed methods. Evaluation findings most commonly focused on contextual factors influencing change (process) and the adoption or implementation of PSE-change strategies (outcome). Evaluators shared lessons learned through various channels to reach local stakeholders and broader public health audiences.Conclusion Framework for Program Evaluation in Public Health is applicable to evaluations of PSE-change initiatives. Using this framework to guide such evaluations builds practice-based evidence for strategies that are increasingly being used to promote healthful behaviors.

The types of adaptations and reasons described in this evaluation support the idea that adaptation is a natural element of implementing evidence-based interventions. Building this understanding into dissemination strategies may help researchers and funders better reach communities with evidence-based interventions that are a relevant fit, while striving for fidelity.

BackgroundEcological models of health suggest that to effectively prevent chronic disease, community food environments must support healthy eating behaviors. However, disparities in access to healthy foods persist in the United States.Community ContextThe Farm Fresh Market (FFM) was a fruit and vegetable market that sold low-cost fresh produce in Cobb County, Georgia in 2014.MethodsThis case study describes the development of the FFM through a community engagement process and presents evaluation results from the project’s pilot implementation. Community engagement strategies included forming a community advisory board, conducting a needs assessment, and contracting with a community-based organization to implement the FFM. OutcomeIn the pilot year, the FFM served an average of 28.7 customers and generated an average of $140.20 in produce sales per market day. Most returning customers lived in the local community and reported a range of socioeconomic backgrounds. Most returning customers strongly agreed that the FFM made it easier (69.0%) and less expensive (79.0%) for them to buy fresh fruits and vegetables, reported that they ate more vegetables (65.0%) and fruit (55.0%) as a result of the FFM, and reported that they were very satisfied with the FFM overall (92.0%).InterpretationResults from this community case study underscore the importance of engaging communities in the development of community food environment interventions. Results also suggest that the FFM initiative was a feasible and acceptable way to respond to the community-identified public health priority of increasing access to healthy foods.

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