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

Statistical Methods for Surveillance and Population Health (156) Surveillance Systems (462) Clinical Information and Decision Making (1407) Clinical Informatics (1022)

Published on in Vol 9 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/41450, first published .
Small Area Forecasting of Opioid-Related Mortality: Bayesian Spatiotemporal Dynamic Modeling Approach

Small Area Forecasting of Opioid-Related Mortality: Bayesian Spatiotemporal Dynamic Modeling Approach

Small Area Forecasting of Opioid-Related Mortality: Bayesian Spatiotemporal Dynamic Modeling Approach

Authors of this article:

Cici Bauer1 Author Orcid Image ;   Kehe Zhang1 Author Orcid Image ;   Wenjun Li2 Author Orcid Image ;   Dana Bernson3 Author Orcid Image ;   Olaf Dammann4, 5 Author Orcid Image ;   Marc R LaRochelle6, 7 Author Orcid Image ;   Thomas J Stopka4, 8, 9 Author Orcid Image
Article Authors Cited by (3) Tweetations (2) Metrics

Journals

  1. Gezer F, Howard K, Litwin A, Martin N, Rennert L. Identification of factors associated with opioid-related and hepatitis C virus-related hospitalisations at the ZIP code area level in the USA: an ecological and modelling study. The Lancet Public Health 2024;9(6):e354 View
  2. Srinivasan S, Pustz J, Marsh E, Young L, Stopka T. Risk factors for persistent fatal opioid-involved overdose clusters in Massachusetts 2011–2021: a spatial statistical analysis with socio-economic, accessibility, and prescription factors. BMC Public Health 2024;24(1) View
  3. Rennert L, Gezer F, Jayawardena I, Howard K, Bennett K, Litwin A, Sease K. Mobile health clinics for distribution of vaccinations to underserved communities during health emergencies: A COVID-19 case study. Public Health in Practice 2024;8:100550 View