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.

Methodology: We compared reports of bird outbreaks of HPAI H5N1 in Egypt for 2006–2011 compiled by the World Organization 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.

Principal Findings: 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.

Background: Influenza A H5N1 has killed millions of birds and raises serious public health concern because of its potential to spread to humans and cause a global pandemic. While the early focus was in Asia, recent evidence suggests that Egypt is a new epicenter for the disease. This includes characterization of a variant clade 2.2.1.1, which has been found almost exclusively in Egypt.
We analyzed 226 HA and 92 NA sequences with an emphasis on the H5N1 2.2.1.1 strains in Egypt using a Bayesian discrete phylogeography approach. This allowed modeling of virus dispersion between Egyptian governorates including the most likely origin.

Results: Phylogeography models of hemagglutinin (HA) and neuraminidase (NA) suggest Ash Sharqiyah as the origin of virus spread, however the support is weak based on Kullback–Leibler values of 0.09 for HA and 0.01 for NA. Association Index (AI) values and Parsimony Scores (PS) were significant (p-value < 0.05), indicating that dispersion of H5N1 in Egypt was geographically structured. In addition, the Ash Sharqiyah to Al Gharbiyah and Al Fayyum to Al Qalyubiyah routes had the strongest statistical support.

Conclusion: We found that the majority of routes with strong statistical support were in the heavily populated Delta region. In particular, the Al Qalyubiyah governorate appears to represent a popular location for virus transition as it represented a large portion of branches in both trees. However, there remains uncertainty about virus dispersion to and from this location and thus more research needs to be conducted in order to examine this. Phylogeography can highlight the drivers of H5N1 emergence and spread. This knowledge can be used to target public health efforts to reduce morbidity and mortality. For Egypt, future work should focus on using data about vaccination and live bird markets in phylogeography models to study their impact on H5N1 diffusion within the country.