Prediction of province-level outbreaks of foot-and-mouth disease in Iran using a zero-inflated negative binomial model.

To identify events that could predict province-level frequency of foot-and-mouth disease (FMD) outbreaks in Iran, 5707 outbreaks reported from April 1995 to March 2002 were studied. A zero-inflated negative binomial model was used to estimate the probability of a 'no-outbreak' status and the number of outbreaks in a province, using the number of previous occurrences of FMD for the same or adjacent provinces and season as covariates. For each province, the probability of observing no outbreak was negatively associated with the number of outbreaks in the same province in the previous month (odds ratio [OR]=0.

Factors associated with spatial clustering of foot-and-mouth disease in Nepal.

The purpose of this study was to quantify associations between hypothesized epidemiological factors and the spatial distribution of foot-and-mouth disease (FMD) in Nepal. Spatial clustering of reports of at least one FMD case by Village Development Committee (VDC) in 2004 was examined by use of the spatial scan statistic. A Bayesian Poisson multivariate regression model was used to quantify the association between the number of reports and 25 factors hypothesized to be associated with FMD risk.

Visualization and analysis of the Danish 2006 highly pathogenic avian influenza virus H5N1 wild bird surveillance data by a prototype avian influenza BioPortal.

Infection with highly pathogenic avian influenza virus H5N1 occurred for the first time in Denmark in 2006 during the last part of the European epidemic that mainly affected migrating wild birds. The total number of Danish wild bird cases was 45, of which only one was found through active surveillance using fecal sampling from resting areas for migrating species, whereas passive surveillance of dead wild birds provided 44 cases. One backyard, mixed poultry flock also became infected late in the epidemic.

Automatic online news monitoring and classification for syndromic surveillance.

Syndromic surveillance can play an important role in protecting the public's health against infectious diseases. Infectious disease outbreaks can have a devastating effect on society as well as the economy, and global awareness is therefore critical to protecting against major outbreaks. By monitoring online news sources and developing an accurate news classification system for syndromic surveillance, public health personnel can be apprised of outbreaks and potential outbreak situations.