Stochastic modelling of infectious diseases for heterogeneous populations.

ABSTRACT:

Background

Infectious diseases such as SARS and H1N1 can significantly impact people's lives and cause severe social and economic damages. Recent outbreaks have stressed the urgency of effective research on the dynamics of infectious disease spread. However, it is difficult to predict when and where outbreaks may emerge and how infectious diseases spread because many factors affect their transmission, and some of them may be unknown.

Methods

One feasible means to promptly detect an outbreak and track the progress of disease spread is to implement surveillance systems in regional or national health and medical centres. The accumulated surveillance data, including temporal, spatial, clinical, and demographic information can provide valuable information that can be exploited to

SUBMITTER: Ming RX 

PROVIDER: S-EPMC5178099 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature