Quantitatively evaluating interventions in the influenza A (H1N1) epidemic on China campus grounded on individual-based simulations.
van de Vijver, David A. M. C.
Sloot, Peter M. A.
Date of Issue2012
School of Computer Engineering
The novel Influenza A (H1N1) virus is attacking the world in 2009. Among others, campuses in China, particularly most university/college campuses for bachelor students, are at-risk areas where many susceptible youngsters live. They most likely interact with each other quite often in dormitories, classrooms and refectories. We model the pandemic influenza A (H1N1) transmission through campus contacts and then forecast the effectiveness of interventions, based on a previously presented Complex Agent Network model for simulating infectious diseases . Our results suggest that pandemic influenza A (H1N1) on campus will die out even with no intervention taken; the most effective intervention is still quarantining confirmed cases as early as possible and, in addition, vaccinating susceptible people can further decrease the maximum daily number of the infected. This study can support quantitative experimentation and prediction of infectious diseases within predefined areas, and assessment of intervention strategies.
Procedia computer science
© 2012 Published by Elsevier B.V.