title: Combinatorial decomposition of an outbreak signature.
abstract: We use mathematically rigorous definitions of epidemiological concepts in order to derive a sequential combinatorial model of disease outbreak decomposition. We define the idea of a population specific 'disease signature' and use this in order to decompose and further understand outbreaks as incidents of spatial and temporal spread of disease exposure both in, and across, populations. This allows us to differentiate between different disease spread scenarios with a level of sensitivity that previous models were unable to provide. This perspective leads us to propose a new practical definition for 'outbreak'. In addition, we are able to use this model to understand, estimate, and, in some cases, correct for, the likely instances of reporting error inherent in disease surveillance. We demonstrate our model first with a hypothetical outbreak scenario and then in an analysis of suspected outbreaks of waterborne diseases in Massachusetts (MA) in 1995.
authors.affiliation: Department of Public Health and Family Medicine, Tufts University School of Medicine, 136 Harrison Avenue, Boston, MA 02111, USA. feferman@math.princeton.edu <feferman@math.princeton.edu>
authors.forename: Nina H
authors.initials: NH
authors.lastname: Fefferman
authors.forename: Elena N
authors.initials: EN
authors.lastname: Naumova
mesh_terms: D000328:Adult; D000368:Aged; D000818:Animals; D002648:Child; D003457:Cryptosporidiosis / Q000453:epidemiology / Q000635:transmission; D004196:Disease Outbreaks; D004812:Epidemiologic Methods; D005873:Giardiasis / Q000453:epidemiology / Q000635:transmission; D006801:Humans; D008404:Massachusetts / Q000453:epidemiology; D008954:Models, Biological; D014867:Water / Q000469:parasitology
chemical_list: D014867:Water