Abstract Details
Activity Number:
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493
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Type:
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Topic Contributed
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Date/Time:
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Wednesday, August 6, 2014 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistics in Epidemiology
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Abstract #311484
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View Presentation
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Title:
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Counting Process Models for Infectivity in Familial Disease Clusters
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Author(s):
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Forrest W. Crawford*+ and Daniel Zelterman
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Companies:
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Yale School of Public Health and Yale
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Keywords:
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Counting process ;
continuous-time Markov chain ;
dependent bernoulli ;
correlated outcomes ;
familial disease clustering
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Abstract:
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Epidemiological outcomes in family clusters are often dependent. Usually families are subject to two kinds of risk: one due to household- or cluster-level exposure and one due to contact with other affected family members. Untangling these sources of risk to find the per-unit disease risk is a vital task in epidemiology. In this talk, I derive a family of counting distributions for sums of dependent Bernoulli variables using principles from continuous-time Markov epidemic models. I derive efficient algorithms for regression with covariates. The approach allows estimation of relative risk, while controlling for dependency of responses due to infectivity or contagion within families.
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Authors who are presenting talks have a * after their name.
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