Design and Implementation of an Innovative, Rapid Data-Monitoring Strategy for Public Health Emergencies: Pilot of the United States School COVID-19 Mitigation Strategies Project.

During the COVID-19 pandemic, an urgent need existed for near-real-time data collection to better understand how individual beliefs and behaviors, state and local policies, and organizational practices influenced health outcomes. We describe the processes, methods, and lessons learned during the development and pilot testing of an innovative rapid data collection process we developed to inform decision-making during the COVID-19 public health emergency. We used a fully integrated mixed-methods approach to develop a structured process for triangulating quantitative and qualitative data from traditional (cross-sectional surveys, focus groups) and nontraditional (social media listening) sources. Respondents included students, parents, teachers, and key school personnel (eg, nurses, administrators, mental health providers). During the pilot phase (February-June 2021), data from 12 cross-sectional and sector-based surveys (n = 20 302 participants), 28 crowdsourced surveys (n = 26 820 participants), 10 focus groups (n = 64 participants), and 11 social media platforms (n = 432 754 503 responses) were triangulated with other data to support COVID-19 mitigation in schools. We disseminated findings through internal dashboards, triangulation reports, and policy briefs. This pilot demonstrated that triangulating traditional and nontraditional data sources can provide rapid data about barriers and facilitators to mitigation implementation during an evolving public health emergency. Such a rapid feedback and continuous improvement model can be tailored to strengthen response efforts. This approach emphasizes the value of nimble data modernization efforts to respond in real time to public health emergencies.

State-to-State Variation in Opioid Dispensing Changes Following the Release of the 2016 CDC Guideline for Prescribing Opioids for Chronic Pain.

Importance: Evidence suggests that opioid prescribing was reduced nationally following the 2016 release of the Guideline for Prescribing Opioids for Chronic Pain by the US Centers for Diseases Control and Prevention (CDC). State-to-state variability in postguideline changes has not been quantified and could point to further avenues for reducing opioid-related harms. Objective: To estimate state-level changes in opioid dispensing following the 2016 CDC Guideline release and explore state-to-state heterogeneity in those changes. Design, Setting, and Participants: This cross-sectional study included information on opioid prescriptions for US individuals between 2012 and 2018 from an administrative database. Serial cross-sections of monthly opioid dispensing trajectories in each US state and the District of Columbia were analyzed using segmented regression to characterize preguideline dispensing trajectories and to estimate how those trajectories changed following the 2016 guideline release. Data were analyzed January to March 2023. Exposure: The March 2016 CDC Guideline for Prescribing Opioids for Chronic Pain. Main Outcomes and Measures: Four measures of opioid dispensing: opioid dispensing rate per 100 000 persons, long-acting opioid dispensing rate per 100 000 persons, high-dose (90 or more morphine milligram equivalents [MME] per day) dispensing rate per 100 000 persons, and average per capita MME. All measures were calculated monthly, from January 2012 through December 2018. Results: Data from approximately 58 900 retail pharmacies were included in analysis, representing approximately 92% of US retail prescriptions. The overall monthly dispensing rate in the US in early 2012 was approximately 7000 per 100 000 population. Following the 2016 guideline release, the already-decreasing slope accelerated nationally for the overall dispensing rate (preguideline slope, -23.19; postguideline slope, -48.97; change in slope, 25.97 [95% CI, 18.67-32.95]), long-acting dispensing rate (preguideline slope, -1.03; postguideline slope, -5.94; change in slope, 4.90 [95% CI, 4.26-5.55]), high-dose dispensing (preguideline slope, -3.52; postguideline slope, -7.63; change in slope, 4.11 [95% CI, 3.49-4.73]), and per-capita MME (preguideline slope, -0.22; postguideline slope, -0.58; change in slope, 0.36 [95% CI, 0.30-0.42]). For all outcomes, nearly all states showed analogous acceleration of an already-decreasing slope, but there was substantial state-to-state heterogeneity. Slope changes (preguideline - postguideline slope) ranged from 9.15 (Massachusetts) to 74.75 (Mississippi) for overall dispensing, 1.88 (Rhode Island) to 13.41 (Maine) for long-acting dispensing, 0.71 (District of Columbia) to 13.68 (Maine) for high-dose dispensing, and 0.06 (Hawaii) to 0.91 (Arkansas) for per capita MME. Conclusions and Relevance: The 2016 CDC Guideline release was associated with broad reductions in prescription opioid dispensing, and those changes showed substantial geographic variability. Determining the factors associated with these state-level differences may inform further improvements to ensure safe prescribing practices.

Use of Medication for Opioid Use Disorder Among Adults With Past-Year Opioid Use Disorder in the US, 2021.

This cross-sectional study uses data from the 2021 National Survey on Drug Use and Health to estimate the receipt of medication for opioid use disorder among US adults with past-year opioid use disorder.

Trends and Characteristics of Buprenorphine-Involved Overdose Deaths Prior to and During the COVID-19 Pandemic.

Importance: Buprenorphine remains underused in treating opioid use disorder, despite its effectiveness. During the onset of the COVID-19 pandemic, the US government implemented prescribing flexibilities to support continued access. Objective: To determine whether buprenorphine-involved overdose deaths changed after implementing these policy changes and highlight characteristics and circumstances of these deaths. Design, Setting, and Participants: This cross-sectional study used data from the State Unintentional Drug Overdose Reporting System (SUDORS) to assess overdose deaths in 46 states and the District of Columbia occurring July 2019 to June 2021. Data were analyzed from March 7, 2022, to June 30, 2022. Main Outcomes and Measures: Buprenorphine-involved and other opioid-involved overdose deaths were examined. Monthly opioid-involved overdose deaths and the percentage involving buprenorphine were computed to assess trends. Proportions and exact 95% CIs of drug coinvolvement, demographics, and circumstances were calculated by group. Results: During July 2019 to June 2021, 32 jurisdictions reported 89 111 total overdose deaths and 74 474 opioid-involved overdose deaths, including 1955 buprenorphine-involved overdose deaths, accounting for 2.2% of all drug overdose deaths and 2.6% of opioid-involved overdose deaths. Median (IQR) age was similar for buprenorphine-involved overdose deaths (41 [34-55] years) and other opioid-involved overdose deaths (40 [31-52] years). A higher proportion of buprenorphine-involved overdose decedents, compared with other opioid-involved decedents, were female (36.1% [95% CI, 34.2%-38.2%] vs 29.1% [95% CI, 28.8%-29.4%]), non-Hispanic White (86.1% [95% CI, 84.6%-87.6%] vs 69.4% [95% CI, 69.1%-69.7%]), and residing in rural areas (20.8% [95% CI, 19.1%-22.5%] vs 11.4% [95% CI, 11.2%-11.7%]). Although monthly opioid-involved overdose deaths increased, the proportion involving buprenorphine fluctuated but did not increase during July 2019 to June 2021. Nearly all (92.7% [95% CI, 91.5%-93.7%]) buprenorphine-involved overdose deaths involved at least 1 other drug; higher proportions involved other prescription medications compared with other opioid-involved overdose deaths (eg, anticonvulsants: 18.6% [95% CI, 17.0%-20.3%] vs 5.4% [95% CI, 5.2%-5.5%]) and a lower proportion involved illicitly manufactured fentanyls (50.2% [95% CI, 48.1%-52.3%] vs 85.3% [95% CI, 85.1%-85.5%]). Buprenorphine decedents were more likely to be receiving mental health treatment than other opioid-involved overdose decedents (31.4% [95% CI, 29.3%-33.5%] vs 13.3% [95% CI, 13.1%-13.6%]). Conclusions and Relevance: The findings of this cross-sectional study suggest that actions to facilitate access to buprenorphine-based treatment for opioid use disorder during the COVID-19 pandemic were not associated with an increased proportion of overdose deaths involving buprenorphine. Efforts are needed to expand more equitable and culturally competent access to and provision of buprenorphine-based treatment.

Increases in methamphetamine injection among treatment admissions in the U.S.

BACKGROUND: Prior research indicates rising methamphetamine use and harms in the U.S., potentially related to increases in methamphetamine injection. To date, research on trends and correlates of methamphetamine injection is limited. METHODS: Analysis of trends and correlates of methamphetamine injection among treatment admissions among persons aged ≥ 12 whose primary substance of use at admission is methamphetamine. Data are from the Treatment Episode Data Set. Analyses includes descriptive statistics, trend analyses, and multilevel multivariable logistic regression. RESULTS: Primary methamphetamine treatment admissions increased from 138,379 in 2010 to 201,021 in 2019. Among primary methamphetamine admissions, injection as the usual route of use increased from 24,821 (18.0 % of admissions) in 2010 to 55,951 (28.2 % of admissions) in 2019. Characteristics associated with increased adjusted odds of reporting methamphetamine injection included: males (aOR = 1.13, 95 % CI = 1.10-1.15); admission age 25-34 years (aOR = 1.23, 95 % CI = 1.19-1.28) and 35-44 years (aOR = 1.12, 95 % CI = 1.08-1.17) compared to age 18-24; dependent living (aOR = 1.33, 95 % CI = 1.29-1.37) and homelessness (aOR = 1.58, 95 % CI = 1.54-1.63) compared to independent living; part-time employment (aOR = 1.08, 95 % CI = 1.02-1.14), unemployment (aOR = 1.39, 95 % CI = 1.34-1.44) and not in labor force (aOR = 1.43, 95 % CI = 1.37-1.49) compared to full-time employment; one to ≥ four prior treatment admissions (aORs ranging from 1.19 to 1.94) compared to no prior admissions; also reporting use of cocaine (aOR = 1.10, 95 % CI = 1.05-1.16), heroin (aOR = 3.52, 95 % CI = 3.40-3.66), prescription opioids (aOR = 1.61, 95 % CI = 1.54-1.67), or benzodiazepines (aOR = 1.42, 95 % CI = 1.32-1.52) at treatment admission. CONCLUSIONS: Findings lend further evidence to a resurgence of methamphetamine use that is intertwined with the ongoing opioid crisis in the U.S. Efforts to expand evidence-based prevention, treatment, and response efforts, particularly to populations at highest risk, are urgently needed.

CDC Clinical Practice Guideline for Prescribing Opioids for Pain - United States, 2022.

This guideline provides recommendations for clinicians providing pain care, including those prescribing opioids, for outpatients aged ≥18 years. It updates the CDC Guideline for Prescribing Opioids for Chronic Pain - United States, 2016 (MMWR Recomm Rep 2016;65[No. RR-1]:1-49) and includes recommendations for managing acute (duration of <1 month), subacute (duration of 1-3 months), and chronic (duration of >3 months) pain. The recommendations do not apply to pain related to sickle cell disease or cancer or to patients receiving palliative or end-of-life care. The guideline addresses the following four areas: 1) determining whether or not to initiate opioids for pain, 2) selecting opioids and determining opioid dosages, 3) deciding duration of initial opioid prescription and conducting follow-up, and 4) assessing risk and addressing potential harms of opioid use. CDC developed the guideline using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) framework. Recommendations are based on systematic reviews of the scientific evidence and reflect considerations of benefits and harms, patient and clinician values and preferences, and resource allocation. CDC obtained input from the Board of Scientific Counselors of the National Center for Injury Prevention and Control (a federally chartered advisory committee), the public, and peer reviewers. CDC recommends that persons with pain receive appropriate pain treatment, with careful consideration of the benefits and risks of all treatment options in the context of the patient's circumstances. Recommendations should not be applied as inflexible standards of care across patient populations. This clinical practice guideline is intended to improve communication between clinicians and patients about the benefits and risks of pain treatments, including opioid therapy; improve the effectiveness and safety of pain treatment; mitigate pain; improve function and quality of life for patients with pain; and reduce risks associated with opioid pain therapy, including opioid use disorder, overdose, and death.

Patterns in Nonopioid Pain Medication Prescribing After the Release of the 2016 Guideline for Prescribing Opioids for Chronic Pain.

Importance: In 2016, the Centers for Disease Control and Prevention (CDC) released the evidence-based Guideline for Prescribing Opioids for Chronic Pain. How the release of this guideline coincided with changes in nonopioid pain medication prescribing rates remains unknown. Objective: To evaluate changes in nonopioid pain medication prescribing after the 2016 CDC guideline release and to assess the heterogeneity in these changes as a function of patient demographic and clinical characteristics. Design, Setting, and Participants: This cohort study constructed 7 (4 preguideline and 3 postguideline) annual cohorts using claims data from the national Optum Clinformatics Data Mart Database for the period January 1, 2011, through December 31, 2018. The cohorts included adults with commercial insurance, no cancer or palliative care claims, and 2 years of continuous insurance enrollment. Individuals could qualify for inclusion in multiple cohorts. Each cohort covered a 2-year period, with year 1 as the baseline period used to calculate opioid exposure and other clinical characteristics and year 2 as the follow-up period used to calculate prescribing outcomes. Data were analyzed in March 2022. Exposures: The CDC guideline, which was released in March 2016. Main Outcomes and Measures: The primary outcome was receipt of any nonopioid pain medication prescriptions (analgesics or antipyretics, anticonvulsants, antidepressants, and nonsteroidal anti-inflammatory drugs) during the follow-up period. This postguideline prescribing pattern was compared with estimates based on the preguideline prescribing pattern, and then the differences were stratified by patient clinical characteristics (chronic pain, recent opioid exposure, substance use disorder, anxiety disorder, and mood disorder). Results: A total of 15 879 241 individuals (2015 mean [SD] age, 50.2 [18.6] years; 8 298 271 female patients [52.3%]) qualified for inclusion in 1 or more cohorts. Logistic regression models showed that nonopioid pain medication prescribing odds were higher by 3.0% (95% CI, 2.6%-3.3%) in postguideline year 1, by 8.7% (95% CI, 8.3%-9.2%) in postguideline year 2, and by 9.7% (95% CI, 9.2%-10.3%) in postguideline year 3 than the preguideline pattern-based estimates. The magnitude of the postguideline departures from the preguideline pattern varied by several clinical characteristics (chronic pain, recent opioid exposure, anxiety disorder, and mood disorder). The largest departure was found among those with chronic pain, with postguideline prescribing being higher than estimated in postguideline year 2 (13.6%; 95% CI, 12.7%-14.6%) and postguideline year 3 (14.9%; 95% CI, 13.8%-16.0%). Conclusions and Relevance: Results of this study showed increases in nonopioid pain medication prescribing after the release of the 2016 CDC guideline, suggesting that the guideline may be associated with an increase in guideline-concordant care, but additional studies are needed to understand the role of other secular changes in the opioid policy landscape and other sources of nonopioid medication use.

Trends and characteristics of cannabis-associated emergency department visits in the United States, 2006-2018.

BACKGROUND: Cannabis policies are rapidly changing in the United States, yet little is known about how this has affected cannabis-associated emergency department (ED) visits. METHODS: We studied trends in cannabis-associated ED visits and identified differences by visit characteristics. Cannabis-associated ED visits from 2006 to 2018 were identified from the Agency for Healthcare Research and Quality's Healthcare Cost and Utilization Project's (HCUP) Nationwide Emergency Department Sample (NEDS). JoinPoint analysis was used to identify trends from 2006 to 2014, prior to medical coding changes in 2015, and Z-tests were used to compare annual rate changes from 2016 to 2018. Changes in rates from 2017 to 2018 were examined by visit characteristics. RESULTS: From 2006-2014, the rate of cannabis-associated ED visits increased, on average, 12.1% annually (p < 0.05), from 12.3 to 34.7 visits per 100,000 population. The rate increased 17.3% from 2016 to 2017 (p < 0.05) and 11.1% from 2017 to 2018 (p < 0.05). From 2017-2018, rates of visits increased for both males (8.7%; p < 0.05) and females (15.9%; p < 0.05). Patients 0-14 years and 25 years and older had significant rate increases from 2017 to 2018 as did the Midwest region (36.8%; p < 0.05), the Northeast (9.2%; p < 0.05), and the South (4.5%; p < 0.05). CONCLUSIONS: Cannabis-associated ED visits are on the rise and subgroups are at increased risk. Some potential explanations for increases in cannabis-associated ED visits include increased availability of cannabis products, increased use, and diversity of products available in marketplaces. Strategies are needed to prevent youth initiation, limit potentially harmful use among adults, and ensure safe storage where cannabis use is legal.

Methamphetamine use in the United States: epidemiological update and implications for prevention, treatment, and harm reduction.

Recent attention has focused on the growing role of psychostimulants, such as methamphetamine in overdose deaths. Methamphetamine is an addictive and potent stimulant, and its use is associated with a range of physical and mental health harms, overdose, and mortality. Adding to the complexity of this resurgent methamphetamine threat is the reality that the increases in methamphetamine availability and harms are occurring in the midst of and intertwined with the ongoing opioid overdose crisis. Opioid involvement in psychostimulant-involved overdose deaths increased from 34.5% of overdose deaths in 2010 to 53.5% in 2019-an increase of more than 50%. This latest evolution of the nation's overdose epidemic poses novel challenges for prevention, treatment, and harm reduction. This narrative review synthesizes what is known about changing patterns of methamphetamine use with and without opioids in the United States, other characteristics associated with methamphetamine use, the contributions of the changing illicit drug supply to use patterns and overdose risk, motivations for couse of methamphetamine and opioids, and awareness of exposure to opioids via the illicit methamphetamine supply. Finally, the review summarizes illustrative community and health system strategies and research opportunities to advance prevention, treatment, and harm reduction policies, programs, and practices.

Cannabis sales increases during COVID-19: Findings from Alaska, Colorado, Oregon, and Washington.

BACKGROUND AND AIMS: Following emergency declarations related to COVID-19 in the United States, many states issued stay-at-home orders and designated essential business categories. Most states allowed medical and/or non-medical adult-use cannabis retailers to remain open. This study assesses changes in cannabis sales across Alaska, Colorado, Oregon, and Washington before and during the pandemic. METHODS: Pre-tax sales data from cannabis marketplaces in four states were analyzed to identify trends from January 2018-December 2020. Mean monthly sales and relative percent change in mean monthly sales were compared by state from April-December (coinciding with the pandemic) in 2018, 2019, and 2020. Differences were assessed using the nonparametric Mann-Whitney-U test. RESULTS: Mean monthly cannabis sales in all four states were higher during the pandemic period in 2020 compared to the same period in 2019. Sales reached a three-year peak in Washington in May 2020 and in Alaska, Colorado, and Oregon in July 2020. From April-December, the percent change in mean monthly sales from 2019 to 2020 was significantly higher than 2018-2019 in all four states, though Alaska saw similar increases between 2018-2019 and 2019-2020. CONCLUSION: To date, cannabis sales in Alaska, Colorado, Oregon, and Washington have increased more during the COVID-19 pandemic than in the previous two years. In light of these increases, data monitoring by states and CDC is warranted to understand how patterns of use are changing, which populations are demonstrating changes in use, and how such changes may affect substance use and related public health outcomes.

Changes in Initial Opioid Prescribing Practices After the 2016 Release of the CDC Guideline for Prescribing Opioids for Chronic Pain.

Importance: The Centers for Disease Control and Prevention (CDC) released the "Guideline For Prescribing Opioids For Chronic Pain" (hereafter, CDC guideline) in 2016, but its association with prescribing practices for patients who are opioid naive is unknown. Objective: To estimate changes in initial prescribing rates, duration, and dosage practices to patients who are opioid naive after the release of the CDC guideline. Design, Setting, and Participants: This cohort study used 6 sequential cohorts to estimate preguideline trends in prescribing among patients who were opioid naive, project that trend forward, and compare it with postguideline prescribing practices. Participants included commercially insured adults without current cancer or hospice care diagnoses and with no past-year opioid claims in the US from 2011 to 2017. All adjusted models were controlled for patient demographics and state-fixed effects. Data were analyzed from January 2020 to May 2021. Exposures: The release of the CDC guideline. Main Outcomes and Measures: Indicators of any opioid prescription fills during a 9-month period, the number of days' supply of the initial prescription, and the binary indicator of whether the initial prescription was for 50 or more morphine milligram equivalents (MMEs) per day. Results: There were 12 870 612 eligible unique patients across cohorts (mean [SD] age in 2016, 51.2 [18.7] years; 6 553 458 [50.9%] women); and the mean (SD) age of the cohorts increased annually, from 48.7 (17.9) years in the April 2011 to December 2012 cohort to 51.9 (19.2) years in the April 2016 to December 2017 cohort. The postguideline prescribing prevalence was 532 962 of 5 834 088 individuals (9.1%), which exceeded that projected from the preguideline trend, estimated at 9.0% (95% CI, 9.0%-9.1%). Among patients receiving prescriptions during follow-up, adjusted mean days' supply was 4.7% (95% CI, 4.3%-5.1%) lower in the first year after release of the guideline and 9.8% (95% CI, 9.3%-10.3%) lower in the second year after release, compared with the expected rate from the preguideline trend. The adjusted odds of receiving a high-dose (ie, ≥50 MME/d) initial prescription were lower in the first year (odds ratio, 0.97; 95% CI, 0.96-0.98) and in the second year (odds ratio, 0.94; 95% CI, 0.93-0.96) after the release of the CDC guideline compared with the odds expected from the preguideline trend. Conclusions and Relevance: This cohort study found that patients who were opioid naive continued to initiate opioid therapy after the release of opioid prescribing guidelines by the CDC, but trends in prescribing duration reversed and decreased, after increasing in each of 4 preguideline cohorts examined. High-dose prescribing rates were already decreasing, but those trends accelerated after the CDC guideline release. These results suggest that nonmandatory, evidence-based guidelines from trusted sources were associated with prescribing practices. Guideline-concordant care has potential to improve pain management and reduce opioid-related harms.

E-cigarette, or Vaping, Product Use-Associated Lung Injury: Looking Back, Moving Forward.

Implications In this commentary, we describe the evidence-based approach used to identify the primary cause of EVALI and to curb the 2019 outbreak. We also discuss future research opportunities and public health practice considerations to prevent a resurgence of EVALI.

Implementing Mitigation Strategies in Early Care and Education Settings for Prevention of SARS-CoV-2 Transmission - Eight States, September-October 2020.

The Head Start program, including Head Start for children aged 3-5 years and Early Head Start for infants, toddlers, and pregnant women, promotes early learning and healthy development among children aged 0-5 years whose families meet the annually adjusted Federal Poverty Guidelines* throughout the United States.† These programs are funded by grants administered by the U.S. Department of Health and Human Services' Administration for Children and Families (ACF). In March 2020, Congress passed the Coronavirus Aid, Relief, and Economic Security (CARES) Act,§ which appropriated $750 million for Head Start, equating to approximately $875 in CARES Act funds per enrolled child. In response to the coronavirus disease 2019 (COVID-19) pandemic, most states required all schools (K-12) to close or transition to virtual learning. The Office of Head Start gave its local programs that remained open the flexibility to use CARES Act funds to implement CDC-recommended guidance (1) and other ancillary measures to provide in-person services in the early phases of community transmission of SARS-CoV-2, the virus that causes COVID-19, in April and May 2020, when many similar programs remained closed. Guidance included information on masks, other personal protective equipment, physical setup, supplies necessary for maintaining healthy environments and operations, and the need for additional staff members to ensure small class sizes. Head Start programs successfully implemented CDC-recommended mitigation strategies and supported other practices that helped to prevent SARS-CoV-2 transmission among children and staff members. CDC conducted a mixed-methods analysis to document these approaches and inform implementation of mitigation strategies in other child care settings. Implementing and monitoring adherence to recommended mitigation strategies reduces risk for COVID-19 transmission in child care settings. These approaches could be applied to other early care and education settings that remain open for in-person learning and potentially reduce SARS-CoV-2 transmission.

Timing of State and Territorial COVID-19 Stay-at-Home Orders and Changes in Population Movement - United States, March 1-May 31, 2020.

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 person-to-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-at-home 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 stay-at-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.

Pathological findings in suspected cases of e-cigarette, or vaping, product use-associated lung injury (EVALI): a case series.

BACKGROUND: Since August, 2019, US public health officials have been investigating a national outbreak of e-cigarette, or vaping, product use-associated lung injury (EVALI). A spectrum of histological patterns consistent with acute to subacute lung injury has been seen in biopsies; however, autopsy findings have not been systematically characterised. We describe the pathological findings in autopsy and biopsy tissues submitted to the US Centers for Disease Control and Prevention (CDC) for the evaluation of suspected EVALI. METHODS: Between Aug 1, 2019, and Nov 30, 2019, we examined lung biopsy (n=10 individuals) and autopsy (n=13 individuals) tissue samples received by the CDC, submitted by 16 US states, from individuals with: a history of e-cigarette, or vaping, product use; respiratory, gastrointestinal, or constitutional symptoms; and either pulmonary infiltrates or opacities on chest imaging, or sudden death from an undetermined cause. We also reviewed medical records, evaluated histopathology, and performed infectious disease testing when indicated by histopathology and clinical history. FINDINGS: 21 cases met surveillance case definitions for EVALI, with a further two cases of clinically suspected EVALI evaluated. All ten lung biopsies showed histological evidence of acute to subacute lung injury, including diffuse alveolar damage or organising pneumonia. These patterns were also seen in nine of 13 (69%) autopsy cases, most frequently diffuse alveolar damage (eight autopsies), but also acute and organising fibrinous pneumonia (one autopsy). Additional pulmonary pathology not necessarily consistent with EVALI was seen in the remaining autopsies, including bronchopneumonia, bronchoaspiration, and chronic interstitial lung disease. Three of the five autopsy cases with no evidence of, or a plausible alternative cause for acute lung injury, had been classified as confirmed or probable EVALI according to surveillance case definitions. INTERPRETATION: Acute to subacute lung injury patterns were seen in all ten biopsies and most autopsy lung tissues from individuals with suspected EVALI. Acute to subacute lung injury can have numerous causes; however, if it is identified in an individual with a history of e-cigarette, or vaping, product use, and no alternative cause is apparent, a diagnosis of EVALI should be strongly considered. A review of autopsy tissue pathology in suspected EVALI deaths can also identify alternative diagnoses, which can enhance the specificity of public health surveillance efforts. FUNDING: US Centers for Disease Control and Prevention.

Public Attitudes, Behaviors, and Beliefs Related to COVID-19, Stay-at-Home Orders, Nonessential Business Closures, and Public Health Guidance - United States, New York City, and Los Angeles, May 5-12, 2020.

SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), is thought to be transmitted mainly by person-to-person 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.