Spatial Methods to Enhance Public Health Surveillance and Resource Deployment in the Opioid Epidemic

Datos Bibliográficos

ID11036629
AutoresZan M Dodson (0000-0003-0839-0720, Zan M. Dodson is with the Public Health Dynamics Laboratory, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA. Eun-Hye Enki Yoo is with the Department of Geography, State University of New York at Buffalo. Christian Martin-Gill and Ronald Roth are with the Department of Emergency Medicine, University of Pittsburgh.), Eun-Hye Enki Yoo (Zan M. Dodson is with the Public Health Dynamics Laboratory, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA. Eun-Hye Enki Yoo is with the Department of Geography, State University of New York at Buffalo. Christian Martin-Gill and Ronald Roth are with the Department of Emergency Medicine, University of Pittsburgh.), Christian Martin-Gill (Zan M. Dodson is with the Public Health Dynamics Laboratory, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA. Eun-Hye Enki Yoo is with the Department of Geography, State University of New York at Buffalo. Christian Martin-Gill and Ronald Roth are with the Department of Emergency Medicine, University of Pittsburgh.), Christian Martin‐Gill (0000-0002-3522-2100, University of Pittsburgh), Ronald Roth (Zan M. Dodson is with the Public Health Dynamics Laboratory, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA. Eun-Hye Enki Yoo is with the Department of Geography, State University of New York at Buffalo. Christian Martin-Gill and Ronald Roth are with the Department of Emergency Medicine, University of Pittsburgh.), Ronald H Roth (University of Pittsburgh)
Año2018
Volumen108
Número9
Páginas1191-1196
Fecha de publicación2018-09-01
Peer ReviewedSí
Open AccessNo
TipoARTICLE
RevistaAmerican Journal of Public Health (JOURNAL)
Identificadores de la revistaISSN: 0090-0036 • E-ISSN: 1541-0048
EditorialAmerican Public Health Association (PUBLISHER • US)
DOI10.2105/ajph.2018.304524
PMID30024793
OpenAlexW2884712615
IdiomaEN
Citas recibidas7
Referencias citadas24

Objectives. To improve public health surveillance and response by using spatial optimization. Methods. We identified cases of suspected nonfatal opioid overdose events in which naloxone was administered from April 2013 through December 2016 treated by the city of Pittsburgh, Pennsylvania, Bureau of Emergency Medical Services. We used spatial modeling to identify areas hardest hit to spatially optimize naloxone distribution among pharmacies in Pittsburgh. Results. We identified 3182 opioid overdose events with our classification approach, which generated spatial patterns of opioid overdoses within Pittsburgh. We then used overdose location to spatially optimize accessibility to naloxone via pharmacies in the city. Only 24 pharmacies offered naloxone at the time, and only 3 matched with our optimized solution. Conclusions. Our methodology rapidly identified communities hardest hit by the opioid epidemic with standard public health data. Naloxone accessibility can be optimized with established location–allocation approaches. Public Health Implications. Our methodology can be easily implemented by public health departments for automated surveillance of the opioid epidemic and has the flexibility to optimize a variety of intervention strategies

(+)-Naloxone · Environmental health · Family medicine · Flexibility (engineering) · Medical emergency · Opioid · Opioid epidemic · Opioid overdose · Public health · Public health surveillance · Data-Driven Disease Surveillance · Emergency Medicine · HIV, Drug Use, Sexual Risk · Medicine · Nursing · Opioid Use Disorder Treatment · Pharmacy