Avian influenza virus (H5N1) is a rapidly disseminating infection that affects poultry
and, potentially, humans. Because the avian virus has already adapted to several mammalian
species, decreasing the rate of avian-mammalian contacts is critical to diminish the chances
of a total adaptation of H5N1 to humans. To prevent the pandemic such adaptation could
facilitate, a biology-specific disease surveillance model is needed, which should also consider
geographical and socio-cultural factors. Here we conceptualized a surveillance model meant
to capture H5N1-related biological and cultural aspects, which included food processing,
trade, and cooking-related practices, as well as incentives (or disincentives) for desirable
behaviours. This proof-of-concept was tested with data collected from 378 Egyptian and
Nigerian sites (local [backyard] producers/ live bird markets /village abattoirs/ commercial
abattoirs and veterinary agencies).
Findings revealed numerous opportunities for pathogens to disseminate, as well as
lack of incentives to adopt preventive measures, and factors that promoted epidemic dissemination. Supporting such observations, the estimated risk for H5N1-related human
mortality was higher than previously reported.
The need for multi-dimensional disease surveillance models, which may detect risks
at higher levels than models that only measure one factor or outcome, was supported. To
develop efficient surveillance systems, interactions should be captured, which include but
exceed biological factors. This low-cost and easily implementable model, if conducted over
time, may identify focal instances where tailored policies may diminish both endemicity and
the total adaptation of H5N1 to the human species.