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.

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.

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]:1­49) and includes recommendations for managing acute (duration of <1 month), subacute (duration of 1­3 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.

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.

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.

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.

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.

Hospitalizations and Deaths Associated with EVALI.

BACKGROUND: As of January 7, 2020, a total of 2558 hospitalized patients with nonfatal cases and 60 patients with fatal cases of e-cigarette, or vaping, product use-associated lung injury (EVALI) had been reported to the Centers for Disease Control and Prevention (CDC). METHODS: In a national study, we compared the characteristics of patients with fatal cases of EVALI with those of patients with nonfatal cases to improve the ability of clinicians to identify patients at increased risk for death from the condition. Health departments reported cases of EVALI to the CDC and included, when available, data from medical-record abstractions and patient interviews. Analyses included all the patients with fatal or nonfatal cases of EVALI that were reported to the CDC as of January 7, 2020. We also present three case reports of patients who died from EVALI to illustrate the clinical characteristics common among such patients. RESULTS: Most of the patients with fatal or nonfatal cases of EVALI were male (32 of 60 [53%] and 1666 of 2498 [67%], respectively). The proportion of patients with fatal or nonfatal cases was higher among those who were non-Hispanic white (39 of 49 [80%] and 1104 of 1818 [61%], respectively) than among those in other race or ethnic groups. The proportion of patients with fatal cases was higher among those 35 years of age or older (44 of 60 [73%]) than among those younger than 35 years, but the proportion with nonfatal cases was lower among those 35 years of age or older (551 of 2514 [22%]). Among the patients who had an available medical history, a higher proportion of those with fatal cases than those with nonfatal cases had a history of asthma (13 of 57 [23%] vs. 102 of 1297 [8%]), cardiac disease (26 of 55 [47%] vs. 115 of 1169 [10%]), or a mental health condition (32 of 49 [65%] vs. 575 of 1398 [41%]). A total of 26 of 50 patients (52%) with fatal cases had obesity. Half the patients with fatal cases (25 of 54 [46%]) were seen in an outpatient setting before hospitalization or death. CONCLUSIONS: Chronic conditions, including cardiac and respiratory diseases and mental health conditions, were common among hospitalized patients with EVALI.

Vitamin E Acetate in Bronchoalveolar-Lavage Fluid Associated with EVALI.

BACKGROUND: The causative agents for the current national outbreak of electronic-cigarette, or vaping, product use-associated lung injury (EVALI) have not been established. Detection of toxicants in bronchoalveolar-lavage (BAL) fluid from patients with EVALI can provide direct information on exposure within the lung. METHODS: BAL fluids were collected from 51 patients with EVALI in 16 states and from 99 healthy participants who were part of an ongoing study of smoking involving nonsmokers, exclusive users of e-cigarettes or vaping products, and exclusive cigarette smokers that was initiated in 2015. Using the BAL fluid, we performed isotope dilution mass spectrometry to measure several priority toxicants: vitamin E acetate, plant oils, medium-chain triglyceride oil, coconut oil, petroleum distillates, and diluent terpenes. RESULTS: State and local health departments assigned EVALI case status as confirmed for 25 patients and as probable for 26 patients. Vitamin E acetate was identified in BAL fluid obtained from 48 of 51 case patients (94%) in 16 states but not in such fluid obtained from the healthy comparator group. No other priority toxicants were found in BAL fluid from the case patients or the comparator group, except for coconut oil and limonene, which were found in 1 patient each. Among the case patients for whom laboratory or epidemiologic data were available, 47 of 50 (94%) had detectable tetrahydrocannabinol (THC) or its metabolites in BAL fluid or had reported vaping THC products in the 90 days before the onset of illness. Nicotine or its metabolites were detected in 30 of 47 of the case patients (64%). CONCLUSIONS: Vitamin E acetate was associated with EVALI in a convenience sample of 51 patients in 16 states across the United States. (Funded by the National Cancer Institute and others.).

Evaluation of Bronchoalveolar Lavage Fluid from Patients in an Outbreak of E-cigarette, or Vaping, Product Use-Associated Lung Injury - 10 States, August-October 2019.

CDC, the Food and Drug Administration (FDA), state and local health departments, and multiple public health and clinical partners are investigating a national outbreak of e-cigarette, or vaping, product use-associated lung injury (EVALI). Based on data collected as of October 15, 2019, 86% of 867 EVALI patients reported using tetrahydrocannabinol (THC)-containing products in the 3 months preceding symptom onset (1). Analyses of THC-containing product samples by FDA and state public health laboratories have identified potentially harmful constituents in these products, such as vitamin E acetate, medium chain triglyceride oil (MCT oil), and other lipids (2,3) (personal communication, D.T. Heitkemper, FDA Forensic Chemistry Center, November 2019). Vitamin E acetate, in particular, might be used as an additive in the production of e-cigarette, or vaping, products; it also can be used as a thickening agent in THC products (4). Inhalation of vitamin E acetate might impair lung function (5-7).

Update: Interim Guidance for Health Care Providers for Managing Patients with Suspected E-cigarette, or Vaping, Product Use-Associated Lung Injury - United States, November 2019.

CDC, the Food and Drug Administration (FDA), state and local health departments, and public health and clinical stakeholders are investigating a nationwide outbreak of e-cigarette, or vaping, product use-associated lung injury (EVALI) (1). CDC has published recommendations for health care providers regarding EVALI (2-4). Recently, researchers from Utah and New York published proposed diagnosis and treatment algorithms for EVALI (5,6). EVALI remains a diagnosis of exclusion because, at present, no specific test or marker exists for its diagnosis, and evaluation should be guided by clinical judgment. Because patients with EVALI can experience symptoms similar to those associated with influenza or other respiratory infections (e.g., fever, cough, headache, myalgias, or fatigue), it might be difficult to differentiate EVALI from influenza or community-acquired pneumonia on initial assessment; EVALI might also co-occur with respiratory infections. This report summarizes recommendations for health care providers managing patients with suspected or known EVALI when respiratory infections such as influenza are more prevalent in the community than they have been in recent months (7). Recommendations include 1) asking patients with respiratory, gastrointestinal, or constitutional symptoms about the use of e-cigarette, or vaping, products; 2) evaluating those suspected to have EVALI with pulse oximetry and obtaining chest imaging, as clinically indicated; 3) considering outpatient management for clinically stable EVALI patients who meet certain criteria; 4) testing patients for influenza, particularly during influenza season, and administering antimicrobials, including antivirals, in accordance with established guidelines; 5) using caution when considering prescribing corticosteroids for outpatients, because this treatment modality has not been well studied among outpatients, and corticosteroids could worsen respiratory infections; 6) recommending evidence-based treatment strategies, including behavioral counseling, to help patients discontinue using e-cigarette, or vaping, products; and 7) emphasizing the importance of annual influenza vaccination for all persons aged ≥6 months, including patients who use e-cigarette, or vaping products.