title: Comparison of human and animal surveillance data for H5N1 influenza A in Egypt 2006-2011.
abstract: BACKGROUND
  The majority of emerging infectious diseases are zoonotic (transmissible between animals and humans) in origin, and therefore integrated surveillance of disease events in humans and animals has been recommended to support effective global response to disease emergence. While in the past decade there has been extensive global surveillance for highly pathogenic avian influenza (HPAI) infection in both animals and humans, there have been few attempts to compare these data streams and evaluate the utility of such integration.
  
  
  METHODS
  We compared reports of bird outbreaks of HPAI H5N1 in Egypt for 2006-2011 compiled by the World Organisation for Animal Health (OIE) and the UN Food and Agriculture Organization (FAO) EMPRESi reporting system with confirmed human H5N1 cases reported to the World Health Organization (WHO) for Egypt during the same time period.
  
  
  RESULTS
  Both human cases and bird outbreaks showed a cyclic pattern for the country as a whole, and there was a statistically significant temporal correlation between the data streams. At the governorate level, the first outbreak in birds in a season usually but not always preceded the first human case, and the time lag between events varied widely, suggesting regional differences in zoonotic risk and/or surveillance effectiveness. In a multivariate risk model, lower temperature, lower urbanization, higher poultry density, and the recent occurrence of a bird outbreak were associated with increased risk of a human case of HPAI in the same governorate, although the positive predictive value of a bird outbreak was low.
  
  
  CONCLUSIONS
  Integrating data streams of surveillance for human and animal cases of zoonotic disease holds promise for better prediction of disease risk and identification of environmental and regional factors that can affect risk. Such efforts can also point out gaps in human and animal surveillance systems and generate hypotheses regarding disease transmission.
authors.affiliation: Yale Occupational and Environmental Medicine Program, Yale University, New Haven, Connecticut, United States of America. peter.rabinowitz@yale.edu
authors.forename: Peter M
authors.initials: PM
authors.lastname: Rabinowitz
authors.forename: Deron
authors.initials: D
authors.lastname: Galusha
authors.forename: Sally
authors.initials: S
authors.lastname: Vegso
authors.forename: Jennifer
authors.initials: J
authors.lastname: Michalove
authors.forename: Seppo
authors.initials: S
authors.lastname: Rinne
authors.forename: Matthew
authors.initials: M
authors.lastname: Scotch
authors.forename: Michael
authors.initials: M
authors.lastname: Kane
mesh_terms: D000818:Animals; D004196:Disease Outbreaks; D004534:Egypt / Q000453:epidemiology; D062665:Epidemiological Monitoring; D006801:Humans; D053124:Influenza A Virus, H5N1 Subtype; D005585:Influenza in Birds / Q000453:epidemiology* / Q000635:transmission; D007251:Influenza, Human / Q000453:epidemiology* / Q000635:transmission; D011200:Poultry; D062486:Public Health Surveillance; D012307:Risk Factors