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.

On October 6, 2020, this report was posted as an MMWR Early Release on the MMWR website (https://www.cdc.gov/mmwr). Mitigating the spread of SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), requires individual, community, and state public health actions to prevent person-to-person transmission. Community mitigation measures can help slow the spread of COVID-19; these measures include wearing masks, social distancing, reducing the number and size of large gatherings, pausing operation of businesses where maintaining social distancing is challenging, working from or staying at home, and implementing certain workplace and educational institution controls (1-4). The Arizona Department of Health Services' (ADHS) recommendations for mitigating exposure to SARS-CoV-2 were informed by continual monitoring of patient demographics, SARS-CoV-2 community spread, and the pandemic's impacts on hospitals. To assess the effect of mitigation strategies in Arizona, the numbers of daily COVID-19 cases and 7-day moving averages during January 22-August 7, 2020, relative to implementation of enhanced community mitigation measures, were examined. The average number of daily cases increased approximately 151%, from 808 on June 1, 2020 to 2,026 on June 15, 2020 (after stay-at-home order lifted), necessitating increased preventive measures. On June 17, local officials began implementing and enforcing mask wearing (via county and city mandates),* affecting approximately 85% of the state population. Statewide mitigation measures included limitation of public events; closures of bars, gyms, movie theaters, and water parks; reduced restaurant dine-in capacity; and voluntary resident action to stay at home and wear masks (when and where not mandated). The number of COVID-19 cases in Arizona peaked during June 29-July 2, stabilized during July 3-July 12, and further declined by approximately 75% during July 13-August 7. Widespread implementation and enforcement of sustained community mitigation measures informed by state and local officials' continual data monitoring and collaboration can help prevent transmission of SARS-CoV-2 and decrease the numbers of COVID-19 cases. * Mandates and ordinances varied and were county-and city-specific. Enforcement types included educating persons on the dangers of COVID-19 spread, issuing fines to persons and businesses who refused to comply with mandates, and loss of licenses for businesses not enforcing rules or mandates. Public pools (e.g., at hotels; limited capacity) Jun 29, Jul 23 Private pools in public areas (e.g., multihousing complexes; limited capacity) Jun 29, Jul 23 Public events (<50 persons) Mar 15, Jun 29, Jul 23 Wearing masks (mandatory) Local officials able to mandate and enforce wearing masks Jun 17

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The US health care system relies on highly resourced tertiary and quaternary hospitals receiving patients from hospitals that are unable to provide these levels of specialty care. These latter hospitals, often in sparsely populated rural areas or underresourced urban areas, are typically not equipped to provide the consultative, procedural, and surgical expertise found in larger systems.Substantial effort and expenditure have gone into developing complex systems for transferring patients with time-sensitive conditions, such as trauma, myocardial infarction, and stroke, largely relying on regional centers located in more populated areas.The recent surge in cases of COVID-19 has reinforced how rapidly hospitals within a broad geographic region can be overwhelmed. Widespread staffing shortages are exacerbating these conditions and substantially constraining health care surge capacity. These problems have been increasingly highlighted in the media as contributors to COVID-19 and non-COVID-19 mortality. 1 Hospital load-balancing initiatives have been developed in some states to ensure access to necessary inpatient care during the COVID-19 pandemic. As leaders in 3 of these statewide initiatives in Washington, Minnesota, and Arizona, our centers have facilitated the coordination and transfer of more than 15 000 patients from April 2020 through November 2021. In this Viewpoint, we present lessons learned from these centralized, regional, load-balancing services. To promote equitable and

Effective inter-organizational collaboration is essential to a community's ability to leverage social and material resources for community problem solving, particularly in the face of complex public health problems. This study used network analysis to document the evolution of collaboration among 21 organizations in the Tar Creek Superfund site in northeastern Oklahoma from 1997 to 2005. The Tar Creek Superfund site was part of a major lead and zinc mining operation and suffers from widespread heavy metal contamination. An organizational network of 21 organizations and a subset of eight tribes were assessed through interviews at three points in time for density and centrality. In addition to collaboration on any topic, we examined information exchange and joint planning related to lead. Density scores were consistently higher in 2005 than in 1997 for both the full and tribal networks. Centralization indices for information exchange showed a marked reduction in the hierarchical structure of information exchange over time. Of particular note is that tribal linkages with local, state and federal agencies increased over time, as did inter-tribal linkages to address the lead issue.

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IntroductionThe Arizona Surge Line was an emergent initiative during the COVID-19 pandemic to facilitate COVID-19 patient transfers and load-level hospitals on a statewide level. It was designed and implemented by the Arizona Department of Health Services in preparation for the first hospital surge due to COVID-19, recognizing the disproportionate impact that hospital surge would have on rural and tribal populations.MethodsWe analyzed the Arizona Surge Line transfer data for the state's first two COVID-19 surges (4/16/2020–3/6/2021). Transfer data included transfer request characteristics, patient demographics and participating hospital characteristics. When applicable, we compared this data with Arizona census data, COVID-19 case data, and the CDC/ATSDR Social Vulnerability Index. The primary outcomes studied were the proportion of COVID-19 patient requests being successfully transferred, the median transfer time, and the proportion of vulnerable populations impacted.ResultsDuring the period of study, 160 hospitals in Arizona made 6,732 requests for transfer of COVID-19 patients. The majority of these patients (84%, 95% CI: 83–85%) were placed successfully with a median transfer time of 59 min (inter-quartile range 33–116). Of all transfer requests, 58% originated from rural hospitals, 53% were for patients of American Indian/Alaska Native ethnicity, and 73% of patients originated from highly vulnerable areas. The majority (98%) of receiving facilities were in urban areas. The Arizona Surge Line matched the number of transfers with licensed market shares during the period of study.ConclusionsThe Arizona Surge Line is an equity-enhancing initiative that disproportionately benefited vulnerable populations. This statewide transfer infrastructure could become a standard public health mechanism to manage hospital surges and enhance access to care during a health emergency.