A Simulation Model for Designing Effective Interventions in Early Childhood Caries
Published Date:Mar 01 2012
Source:Prev Chronic Dis. 2012; 9.
Pubmed Central ID:PMC3366771
Funding:H47MC08655/PHS HHS/United States
RFA-DP09-908/DP/NCCDPHP CDC HHS/United States
Early childhood caries (ECC) — tooth decay among children younger than 6 years — is prevalent and consequential, affecting nearly half of US 5-year-olds, despite being highly preventable. Various interventions have been explored to limit caries activity leading to cavities, but little is known about the long-term effects and costs of these interventions. We developed a system dynamics model to determine which interventions, singly and in combination, could have the greatest effect in reducing caries experience and cost in a population of children aged birth to 5 years.
System dynamics is a computer simulation technique useful to policy makers in choosing the most appropriate interventions for their populations. This study of Colorado preschool children models 6 categories of ECC intervention — applying fluorides, limiting cariogenic bacterial transmission from mothers to children, using xylitol directly with children, clinical treatment, motivational interviewing, and combinations of these — to compare their relative effect and cost.
The model projects 10-year intervention costs ranging from $6 million to $245 million and relative reductions in cavity prevalence ranging from none to 79.1% from the baseline. Interventions targeting the youngest children take 2 to 4 years longer to affect the entire population of preschool-age children but ultimately exert a greater benefit in reducing ECC; interventions targeting the highest-risk children provide the greatest return on investment, and combined interventions that target ECC at several stages of its natural history have the greatest potential for cavity reduction. Some interventions save more in dental repair than their cost; all produce substantial reductions in repair cost.
By using data relevant to any geographic area, this system model can provide policy makers with information to maximize the return on public health and clinical care investments.
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