311 service requests as indicators of neighborhood distress and opioid use disorder

New paper: Li, Y., Hyder, A., Southerland, L.T., Hammond, G., Porr, A. and Miller, H.J. “311 service requests as indicators of neighborhood distress and opioid use disorder,” Scientific Reports, 10, 19579.

Abstract

Opioid use disorder and overdose deaths is a public health crisis in the United States, and there is increasing recognition that its etiology is rooted in part by social determinants such as poverty, isolation and social upheaval. Limiting research and policy interventions is the low temporal and spatial resolution of publicly available administrative data such as census data. We explore the use of municipal service requests (also known as “311” requests) as high resolution spatial and temporal indicators of neighborhood social distress and opioid misuse. We analyze the spatial associations between georeferenced opioid overdose event (OOE) data from emergency medical service responders and 311 service request data from the City of Columbus, OH, USA for the time period 2008–2017. We find 10 out of 21 types of 311 requests spatially associate with OOEs and also characterize neighborhoods with lower socio-economic status in the city, both consistently over time. We also demonstrate that the 311 indicators are capable of predicting OOE hotspots at the neighborhood-level: our results show code violation, public health, and street lighting were the top three accurate predictors with predictive accuracy as 0.92, 0.89 and 0.83, respectively. Since 311 requests are publicly available with high spatial and temporal resolution, they can be effective as opioid overdose surveillance indicators for basic research and applied policy.

Media

Gap between rich, poor neighborhoods growing and self-reinforcing

A study led by Jinhyung Lee from Ohio State’s Center for Urban and Regional Analysis (CURA) finds deepening and self-reinforcing polarization of neighborhood housing values in Columbus, Ohio.  Factors long thought to impact neighborhood values – distance to downtown, nearby highways, or attractions such as city parks – no longer matter as much as the neighborhoods themselves.

OSU News article: Gap between rich, poor neighborhoods growing in some cities

Geographic information observatories and opportunistic GIScience

The first of three GIS status update reports commissioned by PiHG:

Miller, H. J. (2017) “Geographic information science I: Geographic information observatories and opportunistic GIScience,” Progress in Human Geography.  Online publication date: May-15-2017.  DOI: 10.1177/0309132517710741

Abstract: Geographic information observatories (GIOs) extend the capabilities for observatory-based science to the broad geographic data associated with a place or region. GIOs are a form of scientific instrumentation that affords a holistic view of geographic data. This potentially could lead to new insights about geographic information, as well as the human and coupled human-natural systems described by this information. In this report, I discuss GIOs in light of a timely question – what new types of GIScience should we be doing with big geographic data? I argue that GIOs also allow for a new type of opportunistic geographic information science that leverages real-world events via ongoing observation, experimentation and decision-support.

Keywords: data science, geographic information observatory, natural experiments, opportunistic science, spatial decision support