Detecting New Sources of Childhood Environmental Lead Exposure Using a Statistical Surveillance System, 2015–2019

Bibliographic Data

ID11028008
AuthorsPaul S Romer Present (All authors are with the Toxicology and Environmental Epidemiology Office, Colorado Department of Public Health and Environment, Denver.), Kevin Berg (All authors are with the Toxicology and Environmental Epidemiology Office, Colorado Department of Public Health and Environment, Denver.), Kevin C de Berg (0000-0001-9349-1408, Colorado Department of Public Health and Environment), Megan Snow (All authors are with the Toxicology and Environmental Epidemiology Office, Colorado Department of Public Health and Environment, Denver.), Kristy Richardson (All authors are with the Toxicology and Environmental Epidemiology Office, Colorado Department of Public Health and Environment, Denver.)
Year2022
Volume112
IssueS7
PagesS715-S722
Publication date2022-09-01
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueAmerican Journal of Public Health (JOURNAL)
Journal identifiersISSN: 0090-0036 • E-ISSN: 1541-0048
PublisherAmerican Public Health Association (PUBLISHER • US)
DOI10.2105/ajph.2022.307009
PMID36179295
OpenAlexW4298111984
LanguageEN
Citations received1
References cited21

Objectives. To design and implement a statistical surveillance system to prospectively identify potential clusters of elevated blood lead levels (EBLLs) in children younger than 6 years in the Denver, Colorado, metro area. Methods. We evaluated the ability of 2 independent statistical surveillance methods to detect synthetic clusters of EBLLs in Denver between 2015 and 2019. Results. Together, the statistical surveillance methods took an average of 9 months to detect the synthetic clusters. This is faster than similar real-world clusters that have been reported in the past. The system was relatively unaffected by changes in the testing rate and to the blood lead reference value. Conclusions. The adequate design of a statistical surveillance system can help increase the rate at which clusters of EBLLs are detected in Denver, but doing so requires an accurate model of the spatial distribution of EBLLs. Earlier detection of clusters can help guide more effective public health interventions at the local level. (Am J Public Health. 2022;112(S7):S715–S722. https://doi.org/10.2105/AJPH.2022.307009 )

Environmental health · Lead (geology) · Lead exposure · Pathology · Population · Public health · Public health interventions · Public health surveillance · Statistical analysis · Statistics · Data-Driven Disease Surveillance · Environmental Justice and Health Disparities · Heavy Metal Exposure and Toxicity · Mathematics · Medicine

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