ArticlePreventing chronic disease2020
A Bivariate Mapping Tutorial for Cancer Control Resource Allocation Decisions and Interventions.
Article in Preventing chronic disease, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
14 citing papers in PubMed.
- Spatiotemporal co-occurrence patterns and related risk factors of esophageal and lip and oral cavity cancers among older adults across 203 countries and territories: a machine learning-driven systematic analysis.Annals of medicine · 2026Article
- Application of Spatial Methods in Rural Cancer Control Research in the United States.Current epidemiology reports · 2026Review
- Mapping the Availability of Rehabilitation Providers Using Public Licensure and Population Data for a Geographic Information System-Based Approach to Workforce Planning: Cross-Sectional Feasibility Study.JMIR formative research · 2025Article
- Spatiotemporal analysis of the re-emerging foot and mouth disease outbreak in Central Java, Indonesia.Open veterinary journal · 2025Article
- Assessing disparities in cancer resources distribution in Mexico.BMC health services research · 2025Article
- Human Papillomavirus Vaccination and Human Papillomavirus-Related Cancer Rates.JAMA network open · 2024Article
- Examining the existing usage gap of electronic health records in the United States: A study of National Health Survey.SSM - population health · 2024Article
- Examining rehabilitation access disparities: an integrated analysis of electronic health record data and population characteristics through bivariate choropleth mapping.BMC health services research · 2024Article
- Linking Local-Level Chronic Disease and Social Vulnerability Measures to Inform Planning Efforts: A COPD Example.Preventing chronic disease · 2023Article
- LionVu: A Data-Driven Geographical Web-GIS Tool for Community Health and Decision-Making in a Catchment Area.Geographies · 2023Article
- Population-Based, Spatial Analysis of Specialised Ambulatory Palliative Care in Mecklenburg-Western Pomerania, Germany, on the Basis of Reimbursement Data.International journal of environmental research and public health · 2023Article
- Disparities in Internet Access and COVID-19 Vaccination in New York City.Preventing chronic disease · 2021Article
- Trends in Adolescent Treatment Admissions for Marijuana in the United States, 2008-2017.Preventing chronic disease · 2020Article
- Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Bivariate choropleth mapping is a straightforward but underused method for displaying geographic health information to use in public health decision making. Previous studies have recommended this approach for state comprehensive cancer control planning and similar efforts. In this method, 2 area-level variables of interest are mapped simultaneously, often as overlapping quantiles or by using other classification methods. Variables to be mapped may include area-level (eg, county level) measures of disease burden, health care use, access to health care services, and sociodemographic characteristics. We demonstrate how geographic information systems software, specifically ArcGIS, can be used to develop bivariate choropleth maps to inform resource allocation and public health interventions. We used 2 types of county-level public health data: South Carolina's Behavioral Risk Factor Surveillance System estimates of ever having received cervical cancer screening, and a measure of availability of cervical cancer screening providers that are part of South Carolina's Breast and Cervical Cancer Early Detection Program. Identification of counties with low screening rates and low access to care may help inform where additional resources should be allocated to improve access and subsequently improve screening rates. Similarly, identifying counties with low screening rates and high access to care may help inform where educational and behavioral interventions should be targeted to improve screening in areas of high access.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.