ReviewBiomedical informatics insights2017
Using Spatial Analysis to Inform Community Immunization Strategies.
Review in Biomedical informatics insights, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- Trial
- Spatiotemporal distribution and determinants of immunization among children aged 12-23 months in Ethiopia: Using EDHS 2000, 2005, 2011, and 2016.Human vaccines & immunotherapeutics · 2026Article
- Finding the Gaps: Integrated Serosurveillance and Spatial Clustering of Vaccine Preventable Diseases in Samoa, 2018-2019.Tropical medicine and infectious disease · 2025Article
- Overcoming Health Inequities: Spatial Analysis of Seroprevalence and Vaccination Against COVID-19 in Chile.Health equity · 2024Article
- Spatial analysis of vaccine coverage in children under the age of 1 year by mesoregions in Paraíba a northeastern Brazilian state.PloS one · 2023Article
- Article
- Spatial Epidemiological Analysis of Keshan Disease in China.Annals of global health · 2022Article
- Spatial distribution of incomplete immunization among under-five children in Ethiopia: evidence from 2005, 2011, and 2016 Ethiopian Demographic and health survey data.BMC public health · 2020Article
- Public and Population Health Informatics: The Bridging of Big Data to Benefit Communities.Yearbook of medical informatics · 2018Review
- Development, Implementation, and Evaluation of Three Outreach Events to Improve COVID-19 Vaccine Uptake Among Racial and Ethnic Minority Communities in Houston, Texas, 2022.Public health reports (Washington, D.C. : 1974)Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
introductionRecent pertussis outbreaks in the United States suggest our response to local disease outbreaks (eg, vaccine-preventable
methodsA 2012 study on Denver, CO, residents less than 19 years of age confirmed pertussis cases and immunization information system records were geocoded and aggregated to the census tract (CT) level. An algorithm assessed whether individuals were up-to-date (UTD) for pertussis vaccines. Pearson, Spearman, and Kendall correlations assessed relations between disease incidence and pertussis vaccine coverage. Using spatial analysis software, disease incidence and UTD rates were spatially weighted, and smoothed. Global and local autocorrelations based on univariate Moran's I spatial autocorrelation statistics evaluated whether a CT's rate belong to a cluster based on incidence or UTD measures.
resultsOverall disease incidence rate was 116.8/100 000. Assessment of pertussis vaccination coverage was available for 90% of the population. Among 134 672 Denver residents less than 19 years old, 103 496 (77%) were UTD for pertussis vaccines. Raw correlation coefficients showed weak relationships between incidence and immunization rates due to the presence of outliers. With geospatial and clustering analysis, estimates and correlation coefficients were improved with statistically significant Moran's I values for global and local autocorrelations rejecting the null hypothesis that incidence or UTD rates were randomly distributed. With evidence indicating the presence of clusters, smoothed and weighted disease incidence and UTD rates in 144 CTs identified 21 CTs (15%) for potential public health intervention.
conclusionsCorrelation of raw disease incidence and vaccine UTD rates in subcounty regions showed limited association, providing limited information for decision making. By assessing for clusters using spatial analysis methods, we identified CTs with higher incidence and lower immunization coverage for targeted public health interventions.
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