Literature DB >> 36179295

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

Paul S Romer Present1, Kevin Berg1, Megan Snow1, Kristy Richardson1.   

Abstract

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).

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Year:  2022        PMID: 36179295      PMCID: PMC9528648          DOI: 10.2105/AJPH.2022.307009

Source DB:  PubMed          Journal:  Am J Public Health        ISSN: 0090-0036            Impact factor:   11.561


  16 in total

1.  Association between children's blood lead levels, lead service lines, and water disinfection, Washington, DC, 1998-2006.

Authors:  Mary Jean Brown; Jaime Raymond; David Homa; Chinaro Kennedy; Thomas Sinks
Journal:  Environ Res       Date:  2010-11-26       Impact factor: 6.498

2.  Control of Lead Sources in the United States, 1970-2017: Public Health Progress and Current Challenges to Eliminating Lead Exposure.

Authors:  Timothy Dignam; Rachel B Kaufmann; Lauren LeStourgeon; Mary Jean Brown
Journal:  J Public Health Manag Pract       Date:  2019 Jan/Feb

3.  Elevated blood lead in young children due to lead-contaminated drinking water: Washington, DC, 2001-2004.

Authors:  Marc Edwards; Simoni Triantafyllidou; Dana Best
Journal:  Environ Sci Technol       Date:  2009-03-01       Impact factor: 9.028

4.  Blood Lead Levels Among Children Aged <6 Years - Flint, Michigan, 2013-2016.

Authors:  Chinaro Kennedy; Ellen Yard; Timothy Dignam; Sharunda Buchanan; Suzanne Condon; Mary Jean Brown; Jaime Raymond; Helen Schurz Rogers; John Sarisky; Rey de Castro; Ileana Arias; Patrick Breysse
Journal:  MMWR Morb Mortal Wkly Rep       Date:  2016-07-01       Impact factor: 17.586

5.  Spatial Surveillance of Childhood Lead Exposure in a Targeted Screening State: An Application of Generalized Additive Models in Denver, Colorado.

Authors:  Kevin Berg; Stephanie Kuhn; Mike Van Dyke
Journal:  J Public Health Manag Pract       Date:  2017 Sep/Oct

6.  Effects of early childhood lead exposure on academic performance and behaviour of school age children.

Authors:  K Chandramouli; C D Steer; M Ellis; A M Emond
Journal:  Arch Dis Child       Date:  2009-09-21       Impact factor: 3.791

7.  Confirmation and extension of association of blood lead with attention-deficit/hyperactivity disorder (ADHD) and ADHD symptom domains at population-typical exposure levels.

Authors:  Joel T Nigg; Molly Nikolas; G Mark Knottnerus; Kevin Cavanagh; Karen Friderici
Journal:  J Child Psychol Psychiatry       Date:  2009-11-23       Impact factor: 8.982

8.  A novel experience in the use of control charts for the detection of nosocomial infection outbreaks.

Authors:  Isabel Cristina Gomes; Sueli Aparecida Mingoti; Cláudia Di Lorenzo Oliveira
Journal:  Clinics (Sao Paulo)       Date:  2011       Impact factor: 2.365

9.  Blood Lead Levels in U.S. Children Ages 1-11 Years, 1976-2016.

Authors:  Kathryn B Egan; Cheryl R Cornwell; Joseph G Courtney; Adrienne S Ettinger
Journal:  Environ Health Perspect       Date:  2021-03-17       Impact factor: 9.031

10.  An empirical comparison of spatial scan statistics for outbreak detection.

Authors:  Daniel B Neill
Journal:  Int J Health Geogr       Date:  2009-04-16       Impact factor: 3.918

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