Evidence map›Paper›PMID 35691649›Full record

ArticleSpatial and spatio-temporal epidemiology2022

Aggregated spatial intensity as a method for estimating point-level exposures within area-level units: The case of tobacco retailer exposure in census tracts.

Madeline M Brooks, Scott D Siegel, Anne E Corrigan, Frank C Curriero

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In one paragraph

Article in Spatial and spatio-temporal epidemiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors.

Madeline M BrooksInstitute for Research on Equity and Community Health (iREACH), Christiana Care Health System, 4000 Nexus Drive, Newark, DE 19803, United States. Electronic address: madeline.m.brooks@christianacare.org.
Scott D SiegelInstitute for Research on Equity and Community Health (iREACH), Christiana Care Health System, 4000 Nexus Drive, Newark, DE 19803, United States; Helen F. Graham Cancer Center & Research Institute, Christiana Care Health System, Newark, DE, United States.
Anne E CorriganDepartment of Epidemiology, Johns Hopkins Spatial Science for Public Health Center, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.
Frank C CurrieroDepartment of Epidemiology, Johns Hopkins Spatial Science for Public Health Center, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.

Funding

Predictive Modeling & Optimal Control Framework for Model-Based Epidemic Response in DelawareP20GM103446 · NIGMS · UNIVERSITY OF DELAWARE · PI Anjana Narayan Bhat · 2012 to 2026
$67.2M
NIGMS NIH HHS P20 GM103446
6 · The paper itself

Abstract

backgroundAggregating point-level events to area-level units can produce misleading interpretations when displayed via choropleth maps. We developed the aggregated intensity method to share point-level location information across unit boundaries prior to aggregation. This method was applied to tobacco retailers among census tracts in New Castle County, DE.

methodsAggregated intensity uses kernel density estimation to generate spatially continuous expected counts of events per unit area, then aggregates these results to area-level units. We calculated a relative difference measure to compare aggregated intensity to observed counts.

resultsAggregated intensity produces estimates of event exposure unconstrained by boundaries. The relative difference between aggregated intensity and counts is greater for units with many events proximal to their borders. The appropriateness of aggregated intensity depends on events' spatial influence and proximity to unit boundaries, as well as computational inputs.

conclusionsAggregated intensity may facilitate more spatially realistic estimates of exposure to point-level events.

Indexed as

Tobacco ProductsCensus TractCommerceHumansSpatial AnalysisChoropleth mapExposureKernel density estimationSpatial intensityTobacco retail

Identifiers

PMID35691649
PMCPMC9193981

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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.