Mathematical modeling of infectious diseases is an important tool in the understanding and prediction of epidemics. Knowledge of social interactions is used to understand how infectious diseases spread through populations and how to control epidemics. New research published in BMC Medicine shows that a model, which included dynamic information about the heterogeneity of contact length and rate of making new contacts, was as effective as a more complex model which included the order of contacts.
Click "source" for entire article.
"Simulation of an SEIR infectious disease model on the dynamic contact network of conference attendees" (http://www.biomedcentral.com/1741-7015/9/87/abstract)
"The importance of including dynamic social networks when modeling epidemics of airborne infections: does increasing complexity increase accuracy?"
(http://www.biomedcentral.com/1741-7015/9/88/abstract)
Click "source" for entire article.
"Simulation of an SEIR infectious disease model on the dynamic contact network of conference attendees" (http://www.biomedcentral.com/1741-7015/9/87/abstract)
"The importance of including dynamic social networks when modeling epidemics of airborne infections: does increasing complexity increase accuracy?"
(http://www.biomedcentral.com/1741-7015/9/88/abstract)
