Discovery of a missing disease spreader
Abstract
This study presents a method to discover an outbreak of an infectious disease in a region for which data are missing, but which is at work as a disease spreader. Node discovery for the spread of an infectious disease is defined as discriminating between the nodes which are neighboring to a missing disease spreader node, and the rest, given a dataset on the number of cases. The spread is described by stochastic differential equations. A perturbation theory quantifies the impact of the missing spreader on the moments of the number of cases. Statistical discriminators examine the midbody or tailends of the probability density function, and search for the disturbance from the missing spreader. They are tested with computationally synthesized datasets, and applied to the SARS outbreak and flu pandemic.
 Publication:

Physica A Statistical Mechanics and its Applications
 Pub Date:
 October 2011
 DOI:
 10.1016/j.physa.2011.05.005
 arXiv:
 arXiv:1006.2322
 Bibcode:
 2011PhyA..390.3412M
 Keywords:

 Computer Science  Artificial Intelligence;
 Computer Science  Social and Information Networks;
 Physics  Biological Physics;
 Physics  Physics and Society;
 Quantitative Biology  Populations and Evolution
 EPrint:
 in press