This paper is in the following e-collection/theme issue:

GIS (Geographic Information Systems) Applications in Public Health and Spatial Epidemiology (95) Addiction Medicine (20) Descriptive Epidemiology and Population Size Estimates (87) Substance Abuse (383)

Published on in Vol 5, No 2 (2019): Apr-Jun

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/12110, first published .
Detection of Spatiotemporal Prescription Opioid Hot Spots With Network Scan Statistics: Multistate Analysis

Detection of Spatiotemporal Prescription Opioid Hot Spots With Network Scan Statistics: Multistate Analysis

Detection of Spatiotemporal Prescription Opioid Hot Spots With Network Scan Statistics: Multistate Analysis

Authors of this article:

Arinjoy Basak1 Author Orcid Image ;   Jose Cadena2 Author Orcid Image ;   Achla Marathe3, 4 Author Orcid Image ;   Anil Vullikanti3, 5 Author Orcid Image
Article Authors Cited by (10) Tweetations (3) Metrics

Journals

  1. Thurston H, Freisthler B. The spatio-temporal distribution of naloxone administration events in rural Ohio 2010–16. Drug and Alcohol Dependence 2020;209:107950 View
  2. Balsamo D, Bajardi P, Salomone A, Schifanella R. Patterns of Routes of Administration and Drug Tampering for Nonmedical Opioid Consumption: Data Mining and Content Analysis of Reddit Discussions. Journal of Medical Internet Research 2021;23(1):e21212 View
  3. Marks C, Carrasco-Escobar G, Carrasco-Hernández R, Johnson D, Ciccarone D, Strathdee S, Smith D, Bórquez A. Methodological approaches for the prediction of opioid use-related epidemics in the United States: a narrative review and cross-disciplinary call to action. Translational Research 2021;234:88 View
  4. Pan J, Ren S, Huang X, Peng K, Chen Z. Evaluation of Policy Effectiveness by Mathematical Modeling for the Opioid Crisis with Spatial Study and Trend Analysis. Healthcare 2021;9(5):585 View
  5. Bauer C, Zhang K, Li W, Bernson D, Dammann O, LaRochelle M, Stopka T. Small Area Forecasting of Opioid-Related Mortality: Bayesian Spatiotemporal Dynamic Modeling Approach. JMIR Public Health and Surveillance 2023;9:e41450 View
  6. Blanco C, Wall M, Olfson M. Data needs and models for the opioid epidemic. Molecular Psychiatry 2022;27(2):787 View
  7. Borquez A, Martin N. Fatal overdose: Predicting to prevent. International Journal of Drug Policy 2022;104:103677 View
  8. Stewart K, Kendler K, Westholm A, Ohlsson H, Sundquist J, Sundquist K. Spatiotemporal patterns of drug use disorder in Sweden assessed using population-based registries. BMC Public Health 2023;23(1) View
  9. Böttcher L, Chou T, D’Orsogna M, Galea S. Forecasting drug-overdose mortality by age in the United States at the national and county levels. PNAS Nexus 2024;3(2) View

Books/Policy Documents

  1. Shrestha S, Stopka T. Geospatial Technology for Human Well-Being and Health. View