- Spatial Epidemiology Methods
The third approach used for the assessments included various spatial epidemiology methods. The most common form of spatial epidemiology used as part of opioid-related vulnerability was the choropleth map, which maps a variable using color intensity. ColorBrewer is a useful resource for identifying appropriate color schemes including sequential (for increasing rates), diverging (for comparing above and below a baseline), and qualitative (using no meaningful sort order for outcomes). Figure 6 illustrates per capita income from the American Community Survey using a sequential yellow-orange-red color scheme, mapped using R and Leaflet and uploaded to RPubs, a public website for visualizations created in R.
While most jurisdictions used county-level data, some jurisdictions focused on smaller geographic units, such as ZIP code-level data (ZIP code tabulation area) and formatted it for mapping purposes such that low population ZIP codes could be merged with adjacent ZIP codes to facilitate more stable rate calculations.
Additionally, jurisdictions introduced point layers including physical address-level data consisting of: buprenorphine-waivered physicians, syringe service programs, Naloxone providers, drug detox, outpatient and inpatient services, and other community-based resources. This type of approach added community health needs assessment-type content to the overall vulnerability assessment. Drive-time analyses were then conducted to estimate the proportion of a jurisdiction with access to the specific service type. [8,9]
A final risk and resource map could then be produced showing the intersection and availability of relevant community resource locations with the highest-risk communities for each indicator as well as overall vulnerability groups/ranks.
Combining GIS, spatial epidemiologic, and statistical modeling analyses allows for a more comprehensive review of the spatial pattern of risk, exploration of correlation, and the potential alignment of community health assets to help highlight the communities that face the highest risk and that may require additional resources.
Oregon Vulnerability Assessment Project
Information provided by Pickle, 2019. Viral Hepatitis Program Acute and Communicable Diseases.
Oregon’s County-Level JVA provided a thorough example of spatial epidemiology using a variety of choropleth map approaches, as introduced above. Oregon used multiple methodological approaches beginning with a high number of key indicator variables that were eventually reduced in a backward stepwise regression model until only significantly associated variables were included.
Illinois Vulnerability Assessment Project
Illinois undertook their JVA to inform work at the state level to conduct prevention activities, such as working with local health departments to develop jurisdictional response plans. The State leveraged national (e.g., Census Bureau) and local data sources (e.g., I-NEDSS; vital records) to derive 30 independent variables to test for association with the outcome of interest, HCV infections in individuals less than age 40.
Oregon Vulnerability Assessment Project Read More
Oregon Vulnerability Assessment Project
Oregon’s County-Level JVA provided a thorough example of spatial epidemiology using a variety of choropleth map approaches, as introduced above. Oregon used multiple methodological approaches beginning with a high number of key indicator variables that were eventually reduced in a backward stepwise regression model until only significantly associated variables were included. Their final model included four variables: high intensity drug trafficking area, premature deaths, risky opioid prescribing, and lack of transportation or vehicle availability. Using this final model, a vulnerability score was generated. Oregon proceeded to use ESRI software to generate a map showing the overall vulnerability scores using Jenks natural breaks to categorize into groups described as: lowest, low, mid-range, high, highest priority for intervention as shown in Figure 7.
Oregon also produced a similar stylized county-level map for each variable in the final model. Breaks in additional maps were chosen based on the statistical properties of each variable mapped, and additional geospatial layers were added for relevance. For example, Oregon layered interstate and highway data on top of the county map showcasing high intensity drug trafficking areas. Layering here helped demonstrate the reliance on interstate travel for drug movement.
Oregon faced limitations in the analysis due to the small number of counties in the state, which reduced their statistical power. Geographically, large sized rural counties made it difficult to discern risk arising in specific communities. Oregon was able to present the choropleth maps along with contextual information gathered from other projects, to provide further detail of potential risk to stakeholders interested in these areas of the State.
Illinois Vulnerability Assessment Project Read More
llinois Vulnerability Assessment Project
Illinois undertook their JVA to inform work at the state level to conduct prevention activities, such as working with local health departments to develop jurisdictional response plans. The State leveraged national (e.g., Census Bureau) and local data sources (e.g., I-NEDSS; vital records) to derive 30 independent variables to test for association with the outcome of interest, HCV infections in individuals less than age 40. Data at the ZIP code-level were obtained, and Illinois employed Negative Binomial regression methods after observing overdispersion in the outcome. For this analysis, Illinois used PROC GENMOD in SAS v.9.4 for regression modeling. Specifically, analysts ran bivariable regression models for each independent variable (approximately 30 models) with counts of HCV infections among individuals less than age 40 as the outcome, and population as the offset. Prior to regression modeling, Illinois combined data over two years (2017-2018), and all sampling units were treated as independent. Bivariable regression model results eliminated nine variables from consideration for the multivariable model due to statistically insignificant associations with the outcome at the 0.05 level. The remaining 21 variables were added to a multivariable model and backward selection was used to derive the final model containing eleven significant variables. Model assumptions and fits were checked and predicted person-rates were calculated for each ZIP code. These person-rates were used as the final vulnerability scores and ranked for reporting and mapping.
Illinois mapped both rates and counts of combined HCV incidence and drug overdose for 2017-2018 along with the final vulnerability scores, based on model-estimated rates. When working with local partners, Illinois found that ZIP code-level data gave far more detail than county-level maps, allowing local officials to focus on specific neighborhoods of high risk and high outcome. Partners found outcome rates (for relative comparisons), raw counts (for prioritizing resources) and vulnerability scores all to be useful. They further defined high risk as the bottom (i.e. most vulnerable) ranked 10% of counties and plotted that in a separate map.
Illinois used a number of software packages for mapping. Initial mapping was done in both R and GeoDa . Illinois also had an academic collaborator who was able to produce maps using Carto, an online package that produces interactive maps .
Despite the large number of ZIP codes in Cook County (2019 population of over five million people), there was only a single ZIP code that was in the top 10% for the vulnerability scores. Therefore, Illinois did not highlight Cook County in the statewide maps; they plan to produce ZIP code-level maps specifically for Cook County and Chicago partners during their regional meetings. Overall, the state found that ZIP code data worked well and provided an additional level of detailed information compared to just using the county level.
The state has used the assessment findings to inform work at the state level and to undertake prevention activities. They are working with two local health departments to develop jurisdictional response plans and had invited all local health departments to review their findings and provide feedback. Local health departments have said that the assessment has been a great tool for them to affirm areas they already knew are vulnerable and have begun conversations about how to turn the assessment findings into a tool for policy-making.