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Introduction Life expectancy is a public health metric used to assess mortality. We describe life expectancy calculations for US counties and present methodologic considerations compared with years of potential life lost before age 75 (YPLL-75) and premature age-adjusted mortality (PAAM), 2 commonly used length-of-life metrics. Methods We used death data from the National Center for Health Statistics for 2015-2017 and other health measures from the 2019 County Health Rankings & Roadmaps. We calculated life expectancy from birth at the county level using an abridged life table and the Chiang method of variance. Studentized residuals identified counties with discordant life expectancy and YPLL-75 or PAAM values. Correlations tested associations of life expectancy with key health measures (eg, smoking, child poverty, uninsured). Results Among 3073 US counties, life expectancy ranged from 62.4 to 98.0 years, with a mean of 77.4 years. Life expectancy was strongly and negatively correlated with YPLL-75 ( r = −0.91) and PAAM ( r = −0.95) at the county level. Life expectancy was also associated with other key health metrics, such as smoking, employment, and education rates, where an improvement in the health factor indicated improvement in the respective length-of-life measure. Counties with discordant life expectancy and YPLL-75 or PAAM values had differing age structures. Practice Implications Commonly used length-of-life metrics in population health settings are differentiated by methodological matters, such as computation complexity, data availability, and differential risk among age groups, especially among the very old or very young. The choice of metric should consider these factors, in addition to practical concerns, such as the communication needs of the audience.

Both the Occupational Safety and Health Administration and Washington State require safety and health protections for workers exposed to respirable crystalline silica, including tuberculosis (TB) screening as part of occupational medical surveillance. We describe the creation of a TB screening tool for silica-exposed workers receiving regulated medical surveillance examinations in Washington State. The tool provides relevant clinical recommendations to assist health care providers and public health practitioners who choose to use the tool when performing such examinations. A cross-disciplinary team at the Washington State Department of Labor and Industries created the TB screening tool to help health care providers identify silica-exposed workers who should receive a comprehensive evaluation for active TB disease and workers who should or must receive testing for latent TB infection. The Washington State Adult Tuberculosis Screening Tool for Workers Exposed to Respirable Crystalline Silica benefits occupational and respiratory clinicians and public health practitioners by aiding both the individual- and population-level delivery of occupational health and TB screening services to silica-exposed workers receiving required medical surveillance examinations.

Introduction Linking emergency medical services (EMS) data to emergency department (ED) data enables assessing the continuum of care and evaluating patient outcomes. We developed novel methods to enhance linkage performance and analysis of EMS and ED data for opioid overdose surveillance in North Carolina. Methods We identified data on all EMS encounters in North Carolina during January 1–November 30, 2017, with documented naloxone administration and transportation to the ED. We linked these data with ED visit data in the North Carolina Disease Event Tracking and Epidemiologic Collection Tool. We manually reviewed a subset of data from 12 counties to create a gold standard that informed developing iterative linkage methods using demographic, time, and destination variables. We calculated the proportion of suspected opioid overdose EMS cases that received International Classification of Diseases, Tenth Revision, Clinical Modification diagnosis codes for opioid overdose in the ED. Results We identified 12 088 EMS encounters of patients treated with naloxone and transported to the ED. The 12-county subset included 1781 linkage-eligible EMS encounters, with historical linkage of 65.4% (1165 of 1781) and 1.6% false linkages. Through iterative linkage methods, performance improved to 91.0% (1620 of 1781) with 0.1% false linkages. Among statewide EMS encounters with naloxone administration, the linkage improved from 47.1% to 91.1%. We found diagnosis codes for opioid overdose in the ED among 27.2% of statewide linked records. Practice Implications Through an iterative linkage approach, EMS–ED data linkage performance improved greatly while reducing the number of false linkages. Improved EMS–ED data linkage quality can enhance surveillance activities, inform emergency response practices, and improve quality of care through evaluating initial patient presentations, field interventions, and ultimate diagnoses.

Objectives We assessed the differences between the first version of the Centers for Disease Control and Prevention (CDC) opioid surveillance definition for suspected nonfatal opioid overdoses (hereinafter, CDC definition) and the North Carolina Disease Event Tracking and Epidemiologic Collection Tool (NC DETECT) surveillance definition to determine whether the North Carolina definition should include additional International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes and/or chief complaint keywords. Methods Two independent reviewers retrospectively reviewed data on North Carolina emergency department (ED) visits generated by components of the CDC definition not included in the NC DETECT definition from January 1 through July 31, 2018. Clinical reviewers identified false positives as any ED visit in which available evidence supported an alternative explanation for patient presentation deemed more likely than an opioid overdose. After individual assessment, reviewers reconciled disagreements. Results We identified 2296 ED visits under the CDC definition that were not identified under the NC DETECT definition during the study period. False-positive rates ranged from 2.6% to 41.4% for codes and keywords uniquely identifying ≥10 ED visits. Based on uniquely identifying ≥10 ED visits and a false-positive rate ≤10.0%, 4 of 16 ICD-10-CM codes evaluated were identified for NC DETECT definition inclusion. Only 2 of 25 keywords evaluated, “OD” and “overdose,” met inclusion criteria to be considered a meaningful addition to the NC DETECT definition. Practice Implications Quantitative and qualitative trends in coding and keyword use identified in this analysis may prove helpful for future evaluations of surveillance definitions.

Objectives Studies describing linkage of ambulance trips and emergency department (ED) visits of patients with opioid-related overdose (ORO) are limited. We linked records of patients experiencing ORO from ambulance trip and ED visit records in Massachusetts during April 1–June 30, 2017. Methods We estimated the positive predictive value of ORO-capturing definitions by examining the narratives and triage notes of a sample of OROs from each data source. Because of a lack of common unique identifiers, we deterministically linked OROs to records in the counter data set on date of birth, incident date, facility, and sex. To validate the linkage strategy, we compared ambulance trip narratives with ED triage notes and chief complaints for a sample of pairs. Results Of 3203 ambulance trips for ORO and 3046 ED visits for ORO, 82% and 63%, respectively, matched a record in the counter data set on date of birth, incident date, facility, and sex. In 200 randomly selected linked pairs from a final linked data set of 3006 paired records, only 5 (3%) appeared to be false matches. Practice Implications This exercise demonstrated the feasibility of linking ORO records between 2 data sets without a unique identifier. Future analyses of the linked data could produce insights not available from analyzing either data set alone. Linkage using 2 rapidly available data sets can actively inform the state’s public health opioid overdose response and allow for de-duplicating counts of OROs treated by ambulance, in an ED, or both.

Objectives: Federal open data initiatives that promote increased sharing of federally collected data are important for transparency, data quality, trust, and relationships with the public and state, tribal, local, and territorial (STLT) partners. These initiatives advance understanding of health conditions and diseases by providing data to more researchers, scientists, and policymakers for analysis, collaboration, and valuable use outside CDC responders. This is particularly true for emerging conditions such as COVID-19 where we have much to learn and have evolving data needs. Since the beginning of the outbreak, CDC has collected person-level, de-identified data from jurisdictions and currently has over 8 million records, increasing each day. This paper describes how CDC designed and produces two de-identified public datasets from these collected data. Materials and Methods: Data elements were included based on the usefulness, public request, and privacy implications; specific field values were suppressed to reduce risk of reidentification and exposure of confidential information. Datasets were created and verified for privacy and confidentiality using data management platform analytic tools as well as R scripts. Results: Unrestricted data are available to the public through Data.CDC.gov and restricted data, with additional fields, are available with a data use agreement through a private repository on GitHub.com. Practice Implications: Enriched understanding of the available public data, the methods used to create these data, and the algorithms used to protect privacy of de-identified individuals allow for improved data use. Automating data generation procedures allows greater and more timely sharing of data., Comment: 19 pages, 4 figures, 1 table, 5 supplements

Introduction From the onset of the COVID-19 pandemic, public health officials have sought to develop evidence-based messages to reduce COVID-19 transmission by communicating key information to media outlets and the public. We describe the development of an interdisciplinary rapid message testing model to quickly create, test, and share messages with public health officials for use in health campaigns and policy briefings. Methods An interdisciplinary research team from the University of North Carolina at Chapel Hill assembled in March 2020 to assist the state health department in developing evidence-based messages to influence social distancing behaviors in the state. We developed and iteratively executed a rapid message testing model; the components of the 4-step model were message creation, survey development, survey administration, and analysis and presentation to health department officials. The model was executed 4 times, each during a 7-day period in April and May, and each subsequent survey included new phrasing and/or messaging informed by the previous week’s survey. A total of 917 adults from North Carolina participated in the 4 surveys. Results Survey participants rated messages focused on protecting oneself and others higher than messages focused on norms and fear-based approaches. Pairing behaviors with motivations increased participants’ desire to social distance across all themes and subgroups. For example, adding “Protect your grandmother, your neighbor with cancer, and your best friend with asthma,” to messaging received a 0.9-point higher score than the base message, “Stay 6 feet apart from others when out in public.” Practice Implications Our model to promote social distancing in North Carolina during the COVID-19 pandemic can be used for rapid, iterative message testing during public health emergencies.

Objective Data-informed decision making is valued among school districts, but challenges remain for local health departments to provide data, especially during a pandemic. We describe the rapid planning and deployment of a school-based COVID-19 surveillance system in a metropolitan US county. Methods In 2020, we used several data sources to construct disease- and school-based indicators for COVID-19 surveillance in Franklin County, an urban county in central Ohio. We collected, processed, analyzed, and visualized data in the COVID-19 Analytics and Targeted Surveillance System for Schools (CATS). CATS included web-based applications (public and secure versions), automated alerts, and weekly reports for the general public and decision makers, including school administrators, school boards, and local health departments. Results We deployed a pilot version of CATS in less than 2 months (August–September 2020) and added 21 school districts in central Ohio (15 in Franklin County and 6 outside the county) into CATS during the subsequent months. Public-facing web-based applications provided parents and students with local information for data-informed decision making. We created an algorithm to enable local health departments to precisely identify school districts and school buildings at high risk of an outbreak and active SARS-CoV-2 transmission in school settings. Practice Implications Piloting a surveillance system with diverse school districts helps scale up to other districts. Leveraging past relationships and identifying emerging partner needs were critical to rapid and sustainable collaboration. Valuing diverse skill sets is key to rapid deployment of proactive and innovative public health practices during a global pandemic.

Introduction The number of congenital syphilis (CS) cases in Arizona quadrupled from an average of 14 cases annually before 2017 to 61 cases in 2018, and a statewide outbreak was declared. The Arizona Department of Health Services (ADHS) analyzed statewide surveillance data to identify missed opportunities for prevention and collaborated with the Arizona Health Care Cost Containment System (AHCCCS) to inform response activities. Methods ADHS developed a metric to identify missed opportunities for CS prevention during pregnancy by using medical records, vital records, and case investigation notes for all mothers of infants born with CS from January 1, 2017, through June 30, 2018. AHCCCS conducted a cost-effectiveness analysis to calculate the effect of increasing perinatal syphilis screening. Results Arizona had 57 cases of CS during the study period, of which 17 (29.8%) could have been prevented through third-trimester screening for women who were in prenatal care but screened late (n = 9), were infected after their first prenatal visit screen (n = 7), or were reinfected after an initial reactive syphilis test and appropriate treatment and not rescreened (n = 1). The estimated net cost of combining the additional primary (screening) and secondary (treatment) costs of a third-trimester screen for all pregnant AHCCCS members and the estimated total per-year savings of all newborn hospitalizations was $527. Practice Implications Third-trimester syphilis screening could prevent CS in regions where syphilis transmission is high. Partnering with health insurance agencies to evaluate the cost effectiveness of screening recommendations may improve the accuracy of the estimate of the potential cost savings by using insurance agency–specific data for the population at risk for CS.

Background Public health surveillance requires historical baselines to identify unusual activity. However, these baselines require adjustment after public health interventions. We describe an example of such an adjustment after the introduction of rotavirus vaccine in England in July 2013. Methods We retrospectively measured the magnitude of differences between baselines and observed counts (residuals) before and after the introduction of a public health intervention, the introduction of a rotavirus vaccine in July 2013. We considered gastroenteritis, diarrhea, and vomiting to be indicators for national syndromic surveillance, including telephone calls to a telehealth system, emergency department visits, and unscheduled consultations with general practitioners. The start of the preintervention period varied depending on the availability of surveillance data: June 2005 for telehealth, November 2009 for emergency departments, and July 2010 for general practitioner data. The postintervention period was July 2013 to the second quarter of 2016. We then determined whether baselines incorporating a step-change reduction or a change in seasonality resulted in more accurate models of activity. Results Residuals in the unadjusted baseline models increased by 42%-198% from preintervention to postintervention. Increases in residuals for vomiting indicators were 19%-44% higher than for diarrhea. Both step-change and seasonality adjustments improved the surveillance models; we found the greatest reduction in residuals in seasonally adjusted models (4%-75%). Conclusion Our results demonstrated the importance of adjusting surveillance baselines after public health interventions, particularly accounting for changes in seasonality. Adjusted baselines produced more representative expected values than did unadjusted baselines, resulting in fewer false alarms and a greater likelihood of detecting public health threats.

Objectives: Violence due to firearms is a substantial public health problem. Death data from medical examiner and vital records were linked to evaluate the use of medical examiner data to augment routine surveillance and determine any differences in sex, age, manner of death, or race and ethnicity between the 2 data systems. Materials and Methods: Medical examiner data were searched for keywords of interest, and vital records data were obtained and linked for deaths occurring in Multnomah County, Oregon, from January 1, 2010, through December 31, 2016. Both data sets were compared for the number and proportion of firearm-related deaths by sex, age, manner of death, and race/ethnicity. Sensitivity and positive predictive values were calculated for variables that had discordant results. Results: A total of 568 firearm-related deaths were identified in the medical examiner data. After matching with manual review, the 2 data systems had 100% case agreement. A reverse match showed that most cases not found in medical examiner data were due to transfer of case jurisdiction. The 2 systems matched nearly perfectly in sex, age, and manner of death but differed in characterization of race and ethnicity. Sensitivity was 62% for Hispanic ethnicity but 93% for white and black race. Practice Implications: Using medical examiner data was a useful way to augment routine surveillance of firearm-related deaths in our jurisdiction in close to real time. However, caution is needed when analyzing data by subgroups because of discordant classifications of race between the data systems.

Objectives: Public health accreditation is a 7-step process that starts with a period of preapplication during which a health department assesses its readiness for accreditation. However, no tools with established reliability and validity that quantitatively measure a local health department’s (LHD’s) capacity for accreditation are available to complete this initial step. We developed and validated a survey to measure accreditation capacity for LHDs. Methods: From January through April 2015, we administered a cross-sectional electronic survey instrument with 15 questions that tapped into domains of capacity for public health accreditation. We analyzed and grouped responses by using a confirmatory maximum likelihood factor analysis with oblique rotations. We assessed reliability by using Cronbach α, and we assessed validity by comparing responses with previously established instruments. We administered the survey to 174 LHD directors in Colorado, Kansas, and Nebraska, 153 (88%) of whom responded. Results: The factor analysis produced a 3-factor model of accreditation capacity, suggesting that accreditation capacity depends on 3 distinct latent constructs: support for accreditation, preparation, and planning and approach. The model had good scale reliability (average Cronbach α = 0.7) and validity (average factor correlation = 0.43). Conclusions: The survey developed and scored in this analysis can be used by LHDs to inform the feasibility of initiating the time-intensive and costly process of accreditation.

Objectives: Supplemental federal funding is allocated to state and local tuberculosis (TB) programs using a formula that considers only countable cases reported to the National Tuberculosis Surveillance System (NTSS). Health departments submit reports of cases, which are countable unless another (US or international) jurisdiction has already counted the case or the case represents a recurrence of TB diagnosed ≤12 months after completion of treatment for a previous TB episode. Noncountable cases are a resource burden, so in 2009, NTSS began accepting noncountable case reports as an indicator of program burden. We sought to describe the volume and completeness of noncountable case reports. Methods: We analyzed 2010-2014 NTSS data to determine the number and distribution of noncountable cases reported. We also surveyed jurisdictions to determine the completeness of noncountable case reporting and obtain information on jurisdictions’ experience in reporting noncountable cases. In addition, we prepared a hypothetical recalculation of the funding formula to evaluate the effect of including noncountable cases on funding allocations. Results: Of 54 067 TB case reports analyzed, 1720 (3.2%) were noncountable; 47 of 60 (78.3%) jurisdictions reported ≥1 noncountable case. Of 60 programs surveyed, 34 (56.7%) responded. Of the 34 programs that responded, 24 (70.6%) had not reported all their noncountable cases to NTSS, and 11 (32.4%) stated that reporting noncountable cases was overly burdensome, considering the cases were not funded. Conclusions: Complete data on noncountable TB cases help support estimates of programmatic burden. Ongoing training and a streamlined reporting system to NTSS can facilitate noncountable case reporting.

Objective No case definition exists that allows public health authorities to accurately identify opioid overdoses using emergency medical services (EMS) data. We developed and evaluated a case definition for suspected nonfatal opioid overdoses in EMS data. Methods To identify suspected opioid overdose–related EMS runs, in 2019 the Rhode Island Department of Health (RIDOH) developed a case definition using the primary impression, secondary impression, selection of naloxone in the dropdown field for medication given, indication of medication response in a dropdown field, and keyword search of the report narrative. We developed the case definition with input from EMS personnel and validated it using an iterative process of random medical record review. We used naloxone administration in consideration with other factors to avoid misclassification of opioid overdoses. Results In 2018, naloxone was administered during 2513 EMS runs in Rhode Island, of which 1501 met our case definition of a nonfatal opioid overdose. Based on a review of 400 randomly selected EMS runs in which naloxone was administered, the RIDOH case definition accurately identified 90.0% of opioid overdoses and accurately excluded 83.3% of non–opioid overdose–related EMS runs. Use of the case definition enabled analyses that identified key patterns in overdose locations, people who experienced repeat overdoses, and the creation of hotspot maps to inform outbreak detection and response. Practice Implications EMS data can be an effective tool for monitoring overdoses in real time and informing public health practice. To accurately identify opioid overdose–related EMS runs, the use of a comprehensive case definition is essential.

Introduction: We describe the California Healthy Places Index (HPI) and its performance relative to other indexes for measuring community well-being at the census-tract level. The HPI arose from a need identified by health departments and community organizations for an index rooted in the social determinants of health for place-based policy making and program targeting. The index was geographically granular, validated against life expectancy at birth, and linked to policy actions. Materials and Methods: Guided by literature, public health experts, and a positive asset frame, we developed a composite index of community well-being for California from publicly available census-tract data on place-based factors linked to health. The 25 HPI indicators spanned 8 domains; weights were derived from their empirical association with tract-level life expectancy using weighted quantile sums methods. Results: The HPI’s domains were aligned with the social determinants of health and policy action areas of economic resources, education, housing, transportation, clean environment, neighborhood conditions, social resources, and health care access. The overall HPI score was the sum of weighted domain scores, of which economy and education were highly influential (50% of total weights). The HPI was strongly associated with life expectancy at birth ( r = 0.58). Compared with the HPI, a pollution-oriented index did not capture one-third of the most disadvantaged quartile of census tracts (representing 3 million Californians). Overlap of the HPI’s most disadvantaged quartile of census tracts was greater for indexes of economic deprivation. We visualized the HPI percentile ranking as a web-based mapping tool that presented the HPI at multiple geographies and that linked indicators to an action-oriented policy guide. Practice Implications: The framing of indexes and specifications such as domain weighting have substantial consequences for prioritizing disadvantaged populations. The HPI provides a model for tools and new methods that help prioritize investments and identify multisectoral opportunities for policy action.

Objectives: The Care and Prevention in the United States Demonstration Project included implementation of a Data to Care strategy using surveillance and other data to (1) identify people with HIV infection in need of HIV medical care or other services and (2) facilitate linkages to those services to improve health outcomes. We present the experiences of 4 state health departments: Illinois, Louisiana, Tennessee, and Virginia. Methods: The 4 state health departments used multiple databases to generate listings of people with diagnosed HIV infection (PWH) who were presumed not to be in HIV medical care or who had difficulty maintaining viral suppression from October 1, 2013, through September 29, 2016. Each health department prioritized the listings (eg, by length of time not in care, by viral load), reviewed them for accuracy, and then disseminated the listings to staff members to link PWH to HIV care and services. Results: Of 16 391 PWH presumed not to be in HIV medical care, 9852 (60.1%) were selected for follow-up; of those, 4164 (42.3%) were contacted, and of those, 1479 (35.5%) were confirmed to be not in care. Of 794 (53.7%) PWH who accepted services, 694 (87.4%) were linked to HIV medical care. The Louisiana Department of Health also identified 1559 PWH as not virally suppressed, 764 (49.0%) of whom were eligible for follow-up. Of the 764 PWH who were eligible for follow-up, 434 (56.8%) were contacted, of whom 269 (62.0%) had treatment adherence issues. Of 153 PWH who received treatment adherence services, 104 (68.0%) showed substantial improvement in viral suppression. Conclusions: The 4 health departments established procedures for using surveillance and other data to improve linkage to HIV medical care and health outcomes for PWH. To be effective, health departments had to enhance coordination among surveillance, care programs, and providers; develop mechanisms to share data; and address limitations in data systems and data quality.

COVID-19 pandemic is ongoing for more than a year and has changed priorities and boosted some WBE studies. The aim of this work is to contributed to our knowledge sharing the methodology developed for SARS-CoV-2 detection in wastewater of Madrid region of over six million and a half inhabitants, where the sewer system is a combined system. At first, a pilot test in a small metropolitan area was carried out in order to define the criteria for the selection of the sampling points to be applied to the entire region. Methodologys for laboratory analysis and statistical analysis and interpretation of data are also presented. This work relies highly on fieldwork, so sewer network safe accessibility is paramount. A total of 289 sampling points were weekly characterised. Each sampling point represents a sewershed, some of them in a cascade distribution. Samples are tested for SARS-CoV-2 concentration (gc/L, genome copies per litre) and physicochemical parameters are also analysed to validate or discard what at first could be an unusual virus presence. Field results are correlated with health indicators such as incidence rates and hospitalisation data. This information is daily shared with regional health authorities, disaggregated by municipalities, or aggregated for the entire Madrid region. Results have proved to anticipate health indicators. The tool is used as an early warning indicator for COVID-19 pandemic. Further work is planned to apply the current scheme for a permanent epidemiological surveillance system of 87 sampling points to pinpoint infection hotspots and activate the linked sewersheds in the event of an outbreak.

Background: An antibiogram is a summary of antibiotic susceptibility patterns for selected bacterial pathogens and antibiotics. The New Hampshire Department of Health and Human Services’ Division of Public Health Services (DPHS) sought to create an annual state antibiogram to monitor statewide antibiotic resistance trends, guide appropriate empiric antibiotic prescribing, and inform future statewide antibiotic stewardship. Methods: Through legislative authority, DPHS required hospital laboratories to report antibiogram data annually. DPHS convened an advisory group of infectious disease and pharmacy stakeholders and experts to develop a standardized reporting form for bacteria and antibiotic susceptibility, which was disseminated to all 26 hospitals in New Hampshire. We combined the reported data into a statewide antibiogram, and we created clinical messaging to highlight findings and promote rational antibiotic prescribing among health care providers. Results: All hospital laboratories in New Hampshire submitted annual antibiogram data for 2016 and 2017, including more than 30 000 and 20 000 bacterial isolates recovered from urine and nonurine cultures, respectively, each year. The advisory group created clinical messages for appropriate treatment of common infectious syndromes, including uncomplicated urinary tract infections, community-acquired pneumonia, skin and soft-tissue infections, intra-abdominal infections, and health care–associated gram-negative aerobic infections. The statewide antibiograms and clinical messaging were widely disseminated. Conclusions: The small size of New Hampshire, a centralized public health structure, and close working relationships with hospitals and clinical partners allowed for efficient creation and dissemination of an annual statewide antibiogram, which has fostered public health–clinical partnerships and built a foundation for future state-coordinated antibiotic stewardship. This process serves as a model for other jurisdictions that are considering antibiogram development.

Introduction Few US studies have examined the usefulness of participatory surveillance during the coronavirus disease 2019 (COVID-19) pandemic for enhancing local health response efforts, particularly in rural settings. We report on the development and implementation of an internet-based COVID-19 participatory surveillance tool in rural Appalachia. Methods A regional collaboration among public health partners culminated in the design and implementation of the COVID-19 Self-Checker, a local online symptom tracker. The tool collected data on participant demographic characteristics and health history. County residents were then invited to take part in an automated daily electronic follow-up to monitor symptom progression, assess barriers to care and testing, and collect data on COVID-19 test results and symptom resolution. Results Nearly 6500 county residents visited and 1755 residents completed the COVID-19 Self-Checker from April 30 through June 9, 2020. Of the 579 residents who reported severe or mild COVID-19 symptoms, COVID-19 symptoms were primarily reported among women (n = 408, 70.5%), adults with preexisting health conditions (n = 246, 70.5%), adults aged 18-44 (n = 301, 52.0%), and users who reported not having a health care provider (n = 131, 22.6%). Initial findings showed underrepresentation of some racial/ethnic and non–English-speaking groups. Practical Implications This low-cost internet-based platform provided a flexible means to collect participatory surveillance data on local changes in COVID-19 symptoms and adapt to guidance. Data from this tool can be used to monitor the efficacy of public health response measures at the local level in rural Appalachia.

INTRODUCTION: Pediatric tuberculosis (TB) cases are sentinel events for Mycobacterium tuberculosis transmission in communities because children, by definition, must have been infected relatively recently. However, these events are not consistently identified by genotype-dependent surveillance alerting methods because many pediatric TB cases are not culture-positive, a prerequisite for genotyping. METHODS: We developed 3 potential indicators of ongoing TB transmission based on identifying counties in the United States with relatively high pediatric (aged

Objectives In June 2020, Arizona had the fastest-growing number of cases of coronavirus disease 2019 (COVID-19) worldwide. As part of the growing public health response, the University of Arizona Student Aid for Field Epidemiology Response (SAFER) team was able to modify and increase case investigation efforts to assist local health departments. We outline the recommended logistical and management steps to include students in a public health response of this scope. Methods From April 1 through September 1, 2020, the SAFER team identified key components of a successful student team response: volunteer training, management that allows more senior students to manage newer students, adoption of case-management software, and use of an online survey platform for students to conduct interviews consistently and allow for data quality control and management. Results From April 1 through September 1, 2020, SAFER worked with 3 local health departments to complete 1910 COVID-19 case investigations through a virtual call center. A total of 233 volunteers and 46 hourly student workers and staff members were involved. As of September 2020, students were completing >150 interviews per week, including contact-tracing efforts. Practice Implications Developing relationships between applied public health and academic programs can relieve the burden of low-risk, high-volume case investigations at local and state health departments. Furthermore, by establishing a virtual call center, health sciences faculty and students can volunteer remotely during a pandemic with no additional risk of infection.

Objectives Indian Health Service (IHS) screening rates for Chlamydia trachomatis are lower than national rates of chlamydia screening in the Southwest. We describe and evaluate the effect of a public health intervention consisting of electronic health record (EHR) reminders to alert health care providers to screen for chlamydia at an IHS facility. We also conducted an awareness presentation among health care providers on chlamydia screening. Methods We conducted our intervention from November 1, 2013, through October 31, 2015, at an IHS facility in the Southwest. We implemented algorithms that queried database values to assess chlamydia screening performance in 6 clinical departments. We presented data on the screening performance of clinical departments and health care providers (de-identified) in the awareness presentations. We re-queried database values 1 and 2 years after implementation of the EHR reminder intervention to evaluate before-and-after screening rates, comparing data among all patients and among female patients only. Results We found small, sustained relative increases in chlamydia screening rates during the 2012-2015 evaluation period: 20.8% pre-intervention to 24.9% and 24.2% one and two years postintervention, respectively, across all patients; 32.3% preintervention to 36.6% and 35.6% one and two years postintervention, respectively, among female patients. Increases in clinical department–specific screening rates varied and were most prominent in internal medicine (35.8% preintervention to peak 65.8% postintervention). The 1 clinic (obstetrics–gynecology) that did not receive an awareness presentation showed a consistent downward trend in screening rates, although absolute rates were consistently higher in that clinic than in other clinics. Conclusions Awareness presentations that offer feedback to health care providers on screening performance, heighten provider awareness of the importance of chlamydia screening, and promote development of novel provider-initiated screening protocols may help to increase screening rates when combined with EHR reminders.

Objectives In response to a declared statewide public health emergency due to opioid-related overdose deaths, the Arizona Department of Health Services guided the creation of a modern, statewide, evidence-based curriculum on pain and addiction that would be relevant for all health care provider types. Methods The Arizona Department of Health Services convened and facilitated 4 meetings during 4 months with a workgroup comprising the deans and curriculum representatives of all 18 medical, osteopathic, physician assistant, nurse practitioner, dental, podiatry, and naturopathic programs in Arizona. During this collaborative and iterative process, the workgroup reviewed existing curricula, established a philosophical framework, and developed a flexible and practical structure for a curriculum that would suit the needs of all program types. Results The Arizona Pain and Addiction Curriculum was finalized in June 2018. The curriculum aims to redefine pain and addiction as multidimensional public health issues and is structured as 10 core components, each supported by a detailed set of evidence-based objectives. The curriculum includes a set of annual metrics to collect from both programs (focused on implementation progress and barriers) and learners (focused on knowledge, attitudes, and practice plans). Conclusions To our knowledge, this is the first example of a statewide collaboration among diverse health professional education programs to create a single, standard curriculum. This collaborative process and the nonproprietary Arizona Pain and Addiction Curriculum may serve as a useful template for other states to enhance pain and addiction education.

Objectives Rural communities in the United States are increasingly becoming epicenters of substance use and related harms. However, best practices for recruiting rural people who use drugs (PWUD) for epidemiologic research are unknown, because such strategies were developed in cities. This study explores the feasibility of web- and community-based strategies to recruit rural, young adult PWUD into epidemiologic research. Materials and Methods We recruited PWUD from rural Kentucky to participate in a web-based survey about opioid use using web-based peer referral and community-based strategies, including cookouts, flyers, street outreach, and invitations to PWUD enrolled in a concurrent substance use study. Staff members labeled recruitment materials with unique codes to enable tracking. We assessed eligibility and fraud through online eligibility screening and a fraud detection algorithm, respectively. Eligibility criteria included being aged 18-35, recently using opioids to get high, and residing in the study area. Results Recruitment yielded 410 complete screening entries, of which 234 were eligible and 151 provided complete, nonfraudulent surveys (ie, surveys that passed a fraud-detection algorithm designed to identify duplicate, nonlocal, and/or bot-generated entries). Cookouts and subsequent web-based peer referrals accounted for the highest proportion of screening entries (37.1%, n = 152), but only 29.6% (n = 45) of entries from cookouts and subsequent web-based peer referrals resulted in eligible, nonfraudulent surveys. Recruitment and subsequent web-based peer referral from the concurrent study yielded the second most screening entries (27.8%, n = 114), 77.2% (n = 88) of which resulted in valid surveys. Other recruitment strategies combined to yield 35.1% (n = 144) of screening entries and 11.9% (n = 18) of valid surveys. Conclusions Web-based methods need to be complemented by context-tailored, street-outreach activities to recruit rural PWUD.

Objectives Correctional settings (prisons, jails, detention facilities) provide a unique opportunity to screen for sexually transmitted infections (STIs) among correctional populations with a high prevalence of infection. Immigrant detainees are a distinct and poorly described correctional population. The main objective of this study was to determine the feasibility of a national STI screening program for immigrant detainees. Methods and Materials We developed an opt-out STI testing program that included electronic health record integration, patient education, and staff member training. We piloted this program from June 22 through August 19, 2018, at 2 detention facilities with different operational requirements and detainee demographic characteristics. We assessed STI test positivity rates, treatment outcomes, estimated cost to conduct testing and counseling, and staff member perceptions of program value and challenges to implementation. Results Of 1041 immigrant detainees approached for testing, 526 (50.5%) declined. Of 494 detainees who were tested, 42 (8.5%) tested positive for at least 1 STI; the percentage positivity rates were 6.7% (n = 33) for chlamydia, 0.8% (n = 4) for syphilis, 0.8% (n = 4) for gonorrhea, 0.6% (n = 3) for hepatitis B, and 0.2% (n = 1) for HIV. The estimated cost to detect any STI ranged from $500 to $961; the estimated cost to identify 1 person infected with HIV ranged from $22 497 to $43 244. Forty of 42 persons who tested positive began treatment before release from custody. Medical staff members had positive views of the program but had concerns about workload. Practice Implications STIs are prevalent among immigrant detainees. A routine screening program is feasible if operational aspects are carefully considered and would provide counseling, education, and treatment for this vulnerable population.

Objectives The New York City (NYC) Department of Health and Mental Hygiene (DOHMH) depends on reporting by health care facilities and laboratories for disease surveillance. Our objective was to evaluate the completeness of DOHMH surveillance to identify births to hepatitis B virus (HBV)–positive women to prevent perinatal transmission. Methods We identified infants born to HBV-positive women by matching mothers of all infants born in NYC during May 1, 2013–May 1, 2014, identified from the Citywide Immunization Registry (CIR) to persons with HBV-positive laboratory reports in the Electronic Laboratory Reporting (ELR) system. We then matched infants born to mothers identified in the CIR/ELR match to infants born to HBV-positive women from the DOHMH perinatal HBV surveillance database. We performed capture–recapture analysis to evaluate completeness of DOHMH case identification. We compared the proportion of infants born to HBV-positive mothers reported to DOHMH with the proportion of infants identified only through the CIR/ELR match for receipt of postexposure prophylaxis (PEP) and completion of the HBV vaccination series and post-vaccination serology testing. Results Of 1662 infants identified from the CIR/ELR match and 1554 infants in the DOHMH database, 1493 infants matched. Of 169 infants only in the CIR/ELR data set, 55 were born to HBV-positive women residing in NYC. Sixty-one infants were only in the DOHMH database. An estimated 2 infants were not identified by either method. The CIR/ELR match increased infant identification by 3.5%, from 1554 to 1609 infants. The proportion of infants who received PEP was significantly higher among infants whose mothers were reported to DOHMH (vs not reported to DOHMH). Practical Implications Use of the CIR/ELR match may further improve DOHMH identification of infants born to HBV-positive women and receipt of infant PEP.

Introduction In April 2017, the Tennessee Department of Health (TDH) was notified of an increase in the number of persons newly diagnosed with HIV in eastern Tennessee in the same month. Two were identified as persons with a history of injection drug use (IDU) and named each other as syringe-sharing partners, prompting an investigation into a possible HIV cluster among persons with a history of IDU. Materials and Methods TDH and public health staff members in eastern Tennessee collaborated to implement procedures outlined in TDH’s HIV/hepatitis C virus (HCV) Outbreak Response Plan, including conducting enhanced interviewing and using a preestablished database for data collection and management. To complement contact tracing and enhanced interviewing, TDH partnered with the Centers for Disease Control and Prevention to conduct molecular HIV analyses. Results By June 27, 2017, the investigation had identified 31 persons newly diagnosed with HIV infection; 8 (26%) self-reported IDU, 4 of whom were also men who have sex with men (MSM). Of the remaining 23 persons newly diagnosed with HIV infection, 10 were MSM who did not report IDU, 9 reported high-risk heterosexual contact, and 4 had other or unknown risk factors. Molecular analysis of the 14 HIV-1 polymerase genes (including 7 of the 8 persons self-reporting IDU) revealed 3 distinct molecular clusters, one of which included 3 persons self-reporting IDU. Practice Implications This investigation highlights the importance of implementing an established Outbreak Response Plan and using HIV molecular analyses in the event of a transmission cluster or outbreak investigations. Future HIV outbreak surveillance will include using Global Hepatitis Outbreak Surveillance Technology to identify HCV gene sequences as a potential harbinger for HIV transmission networks.

Objectives: The Colorado BMI Monitoring System was developed to assess geographic (ie, census tract) patterns of obesity prevalence rates among children and adults in the Denver-metropolitan region. This project also sought to assess the feasibility of a surveillance system that integrates data across multiple health care and governmental organizations. Materials and Methods: We extracted data on height and weight measures, obtained through routine clinical care, from electronic health records (EHRs) at multiple health care sites. We selected sites from 5 Denver health care systems and collected data from visits that occurred between January 1, 2013, and December 31, 2015. We produced shaded maps showing observed obesity prevalence rates by census tract for various geographic regions across the Denver-metropolitan region. Results: We identified clearly distinguishable areas by higher rates of obesity among children than among adults, with several pockets of lower body mass index. Patterns for adults were similar to patterns for children: the highest obesity prevalence rates were concentrated around the central part of the metropolitan region. Obesity prevalence rates were moderately higher along the western and northern areas than in other parts of the study region. Practice Implications: The Colorado BMI Monitoring System demonstrates the feasibility of combining EHRs across multiple systems for public health and research. Challenges include ensuring de-duplication across organizations and ensuring that geocoding is performed in a consistent way that does not pose a risk for patient privacy.

Introduction: With the goal of eliminating hepatitis C virus (HCV) as a public health problem in Washington State, Public Health–Seattle & King County (PHSKC) designed a Hepatitis C Virus Test and Cure (HCV-TAC) data system to integrate surveillance, clinical, and laboratory data into a comprehensive database. The intent of the system was to promote identification, treatment, and cure of HCV-infected persons (ie, HCV care cascade) using a population health approach. Materials and Methods: The data system automatically integrated case reports received via telephone and fax from health care providers and laboratories, hepatitis test results reported via electronic laboratory reporting, and data on laboratory and clinic visits reported by 6 regional health care systems. PHSKC examined patient-level laboratory test results and established HCV case classification using Council of State and Territorial Epidemiologists criteria, classifying patients as confirmed if they had detectable HCV RNA. Results: The data enabled PHSKC to report the number of patients at various stages along the HCV care cascade. Of 7747 HCV RNA-positive patients seen by a partner site, 5377 (69%) were assessed for severity of liver fibrosis, 3932 (51%) were treated, and 2592 (33%) were cured. Practice Implications: Data supported local public heath surveillance and HCV program activities. The data system could serve as a foundation for monitoring future HCV prevention and control programs.