Using Automation, Prioritization, and Collaboration to Manage a COVID-19 Case Surge in Maricopa County, Arizona, 2020.

During summer 2020, the Maricopa County Department of Public Health (MCDPH) responded to a surge in COVID-19 cases. We used internet-based platforms to automate case notifications, prioritized investigation of cases more likely to have onward transmission or severe COVID-19 based on available preinvestigation information, and partnered with Arizona State University (ASU) to scale investigation capacity. We assessed the speed of automated case notifications and accuracy of our investigation prioritization criteria. Timeliness of case notification-the median time between receipt of a case report at MCDPH and first case contact-improved from 11 days to <1 day after implementation of automated case notification. We calculated the sensitivity and positive predictive value (PPV) of the investigation prioritization system by applying our high-risk prioritization criteria separately to data available pre- and postinvestigation to determine whether a case met these criteria preinvestigation, postinvestigation, or both. We calculated the sensitivity as the percentage of cases classified postinvestigation as high risk that had also been classified as high risk preinvestigation. We calculated PPV as the percentage of all cases deemed high risk preinvestigation that remained so postinvestigation. During June 30 to July 31, 2020, a total of 55 056 COVID-19 cases with an associated telephone number (94% of 58 570 total cases) were reported. Preinvestigation, 8799 (16%) cases met high-risk criteria. Postinvestigation, 17 037 (31%) cases met high-risk criteria. Sensitivity was 52% and PPV was 98%. Automating case notifications, prioritizing investigations, and collaborating with ASU improved the timeliness of case contact, focused public health resources toward high-priority cases, and increased investigation capacity. Establishing partnerships between health departments and academia might be a helpful strategy for future surge capacity planning.

Design and Implementation of a COVID-19 Case Investigation Program: An Academic-Public Health Partnership, Arizona, 2020.

From May through July 2020, Arizona was a global hotspot for new COVID-19 cases. In response to the surge of cases, local public health departments looked for innovative ways to form external partnerships to address their staffing needs. In collaboration with the Maricopa County Department of Public Health, the Arizona State University Student Outbreak Response Team (SORT) created and implemented a virtual call center to conduct public health case investigations for COVID-19. SORT officially launched a dedicated COVID-19 case investigation program after 3 weeks of program design and training. From June 29 through November 8, 2020, SORT recruited and trained 218 case investigators, completed 5000 case patient interviews, and closed 10 000 cases. Our team also developed process improvements to address disparities in case investigation timeliness. A strong infrastructure designed to accommodate remote case investigations, paired with a large workforce, enabled SORT to provide additional surge capacity for the county's high volume of cases. University-driven multidisciplinary case investigator teams working in partnership with state, tribal, and local public health staff members can be an effective tool for supporting a diverse and growing public health workforce. We discuss the essential design factors involved in building a university program to complement local COVID-19 response efforts, including workflows for case management, volunteer case investigator recruitment and training, secure technology platforms for conducting case investigations remotely, and robust data-tracking procedures for maintaining quality control and timely case reporting.

Changes in Health and Ability to Work Among Medicaid Expansion Enrollees: a Mixed Methods Study.

BACKGROUND: Michigan expanded Medicaid under the Affordable Care Act (Healthy Michigan Plan [HMP]) to improve the health of low-income residents and the state's economy. OBJECTIVE: To understand HMP's impact on enrollees' health, ability to work, and ability to seek employment DESIGN: Mixed methods study, including 67 qualitative interviews and 4090 computer-assisted telephone surveys (response rate 53.7%) PARTICIPANTS: Non-elderly adult HMP enrollees MAIN MEASURES: Changes in health status, ability to work, and ability to seek employment KEY RESULTS: Half (47.8%) of respondents reported better physical health, 38.2% better mental health, and 39.5% better dental health since HMP enrollment. Among employed respondents, 69.4% reported HMP helped them do a better job at work. Among out-of-work respondents, 54.5% agreed HMP made them better able to look for a job. Among respondents who changed jobs, 36.9% agreed HMP helped them get a better job. In adjusted analyses, improved health was associated with the ability to do a better job at work (aOR 4.08, 95% CI 3.11-5.35, p < 0.001), seek a job (aOR 2.82, 95% CI 1.93-4.10, p < 0.001), and get a better job (aOR 3.20, 95% CI 1.69-6.09, p < 0.001), but not with employment status (aOR 1.08, 95% CI 0.89-1.30, p = 0.44). In interviews, several HMP enrollees attributed their ability to get or maintain employment to improved physical, mental, and dental health because of services covered by HMP. Remaining barriers to work cited by enrollees included older age, disability, illness, and caregiving responsibilities. CONCLUSIONS: Many low-income HMP enrollees reported improved health, ability to work, and job seeking after obtaining health insurance through Medicaid expansion.