Location inference on social media data for agile monitoring of public health crises: An application to opioid use and abuse during the Covid-19 pandemic
The Covid-19 pandemic has intersected with the opioid epidemic to create a unique public health crisis, with the health and economic consequences of the virus and associated lockdowns compounding pre-existing social and economic stressors associated with rising opioid and heroin use and abuse. In or...
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| Main Authors: | , |
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| Format: | Journal Article |
| Language: | English |
| Published: |
02-11-2021
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| Subjects: | |
| Online Access: | Get full text |
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| Summary: | The Covid-19 pandemic has intersected with the opioid epidemic to create a
unique public health crisis, with the health and economic consequences of the
virus and associated lockdowns compounding pre-existing social and economic
stressors associated with rising opioid and heroin use and abuse. In order to
better understand these interlocking crises, we use social media data to
extract qualitative and quantitative insights on the experiences of opioid
users during the Covid-19 pandemic. In particular, we use an unsupervised
learning approach to create a rich geolocated data source for public health
surveillance and analysis. To do this we first infer the location of 26,000
Reddit users that participate in opiate-related sub-communities (subreddits) by
combining named entity recognition, geocoding, density-based clustering, and
heuristic methods. Our strategy achieves 63 percent accuracy at state-level
location inference on a manually-annotated reference dataset. We then leverage
the geospatial nature of our user cohort to answer policy-relevant questions
about the impact of varying state-level policy approaches that balance economic
versus health concerns during Covid-19. We find that state government
strategies that prioritized economic reopening over curtailing the spread of
the virus created a markedly different environment and outcomes for opioid
users. Our results demonstrate that geospatial social media data can be used
for agile monitoring of complex public health crises. |
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| DOI: | 10.48550/arxiv.2111.01778 |