Florida Courts Opioids amp Stimulant RESPONSE September 3 2021 2020 OD Death Data Facts Provisional What drove the OD Death Data in 2020 March 15 2020 COVID Source Ahmad FB Rossen LM Sutton P Provisional drug overdose death counts National Center for Health Statistics 2021 ID: 1044081
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1. New Drug Threats: Latest on the Stimulant Crisis Florida Courts Opioids & Stimulant RESPONSESeptember 3, 2021
2. 2020 OD Death Data Facts (Provisional)
3. What drove the OD Death Data in 2020?
4. March 15, 2020COVIDSource: Ahmad FB, Rossen LM, Sutton P. Provisional drug overdose death counts. National Center for Health Statistics. 2021.12 Month-ending Provisional Number of Drug Overdose Deaths
5. Top Five State OD Death Increases by Count
6. Drug Threat Analysis
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9. Heroin Adjustment
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12. Cocaine Adjustment
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15. Methamphetamine Adjustment
16. Fentanyl Facts
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19. Fentanyl Adjustment
20. Where do we go from here?
21. NETI Rural Areas Project – Feasibility Study
22. Rural Areas Teams
23. Study Areas
24. Is it possible to identify emerging drug threats for rural areas?
25. Ohio: Heroin Rates of Seizure Incidents & Overdose Deaths per 100,000 Population
26. Ohio: Methamphetamine Rates of Seizures Incidents & Psychostimulant Overdose Deaths per 100,000 Population
27. Oregon - Four Rural Counties: Heroin Rates of Seizures in kg & Overdose Deaths per 100,000 Population
28. Intel Gap:Constraints in some areas did limit analysis. Public Health agencies provided insufficient drug overdose death data to three of the six HIDTAs. Because of the limited population, there is not enough data to project a meaningful result in some rural areas. In certain states, this was overcome by combining multiple counties into a larger area to reach a conclusion.
29. Kentucky – 17 Rural Counties: Cocaine Rates of Seizures in kg & Overdose Deaths*Per 100,000 Population, 2012 - 2019
30. If it is possible (to identify emerging drug threats in rural areas, even with limitations), can NETI develop a methodology to identify emerging threats for rural counties?
31. Kentucky - 2020 - All Rx Opioid Controlled Substances Dosages Per 1,000 Patients
32. Methamphetamine and Cocaine Seizure Incidents by Year and Region of Ohio, 2010 - 2019
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36. Examples of Current Projects
37. HIDTAs and Respective StatesNortheast Region HIDTA PDMPLiberty Mid-Atlantic PANew England MANew York - New Jersey NYWashington – Baltimore MD, DC & VASoutheast RegionAppalachia KY & TNAtlanta – Carolinas NCCentral Florida FLGulf Coast ARNorth Florida FLSouth Florida FLMidwest Region HIDTA PDMPChicago ILIndiana INIowa IAMichigan MINorth Central MNOhio OHRocky Mountain COTerritory & Distant StatesAlaska AKHawaii HIPuerto Rico - U. S. VI PR
38. HIDTAs and Respective StatesSouthwest Region HIDTA PDMPHouston TXArizona AZNew Mexico NMSouth Texas TXWest Texas TXTexoma OK & TXWest Region HIDTA PDMPCentral Valley California CALos Angeles CANevada NVNorthern California CANorthwest WAOregon – Idaho ORSan Diego/Imperial County CA
39. Opioid PrescriptionsState Drug Monitoring Program (PDMP) Data
40. Opioid Prescription Rates - Representative States
41. Opioid Prescription Rates - Representative States
42. Stimulant PrescriptionsState Drug Monitoring Program (PDMP) Data
43. Stimulant Prescription Rates - Representative States
44. Stimulant Prescription Rates - Representative States
45. Arizona Overdose & Addiction Data
46. U.S.Overdose Deaths 2019Deaths represent age adjusted overdose death rates per 100,000 Population. Source: CDC/NCHS National Vital Statistics System
47. Bayesian Overdose Death Estimates for 2003County-level estimates were generated using Hierarchical Bayesian models with spatial and temporal random effects using the INLA package for R (3,10–11). These models borrow strength over time and across neighboring counties to produce stable estimates of drug overdose death rates by county and year. Source: NCHS, National Vital Statistics System, mortality data (see http://www.cdc.gov/nchs/death s.htm).
48. County-level estimates were generated using Hierarchical Bayesian models with spatial and temporal random effects using the INLA package for R (3,10–11). These models borrow strength over time and across neighboring counties to produce stable estimates of drug overdose death rates by county and year. Source: NCHS, National Vital Statistics System, mortality data (see http://www.cdc.gov/nchs/death s.htm).Bayesian Overdose Death Estimates for 2008
49. County-level estimates were generated using Hierarchical Bayesian models with spatial and temporal random effects using the INLA package for R (3,10–11). These models borrow strength over time and across neighboring counties to produce stable estimates of drug overdose death rates by county and year. Source: NCHS, National Vital Statistics System, mortality data (see http://www.cdc.gov/nchs/death s.htm).Bayesian Overdose Death Estimates for 2013
50. County-level estimates were generated using Hierarchical Bayesian models with spatial and temporal random effects using the INLA package for R (3,10–11). These models borrow strength over time and across neighboring counties to produce stable estimates of drug overdose death rates by county and year. Source: NCHS, National Vital Statistics System, mortality data (see http://www.cdc.gov/nchs/death s.htm).Bayesian Overdose Death Estimates for 2018
51. Estimated Annual Prevalence of Marijuana Use: ArizonaSource: 2016-2018 NSDUH Substate Region EstimatesThe NSDUH Survey conducted by SAMHSA, includes persons aged 12 and over and is considered representative of the non- institutionalized population of the united states. Since the survey excludes homeless persons that are not present in shelters as well as other institutionalized persons such as residents of jails, nursing homes and mental institutions, the estimates may represent an under-estimation of actual prevalence.
52. Estimated Annual Prevalence of Methamphetamine Use: ArizonaSource: 2016-2018 NSDUH Substate Region EstimatesThe NSDUH Survey conducted by SAMHSA, includes persons aged 12 and over and is considered representative of the non- institutionalized population of the united states. Since the survey excludes homeless persons that are not present in shelters as well as other institutionalized persons such as residents of jails, nursing homes and mental institutions, the estimates may represent an under-estimation of actual prevalence.
53. Percent of Treatment Admissions By Type of Drugfor Arizona andU.S. - 2018Source: 2018 TreatmentEpisode Data SetThe Treatment Episode Data Set (TEDS) is based on clinical records collected by addiction treatment agencies and submitted to the Substance Abuse and Mental Health Services Administration (SAMHSA) through state treatment authorities. The TEDS system routinely collects data for more than a million treatment episodes every year. All data are maintained and summarized by the Center for Behavioral Health Statistics and Quality.
54. John L Eadie jeadie@pdmpneti.org (518) 529-6397 National Emerging Threats Initiative (NETI)