A complex systems approach to infectious disease surveillance and response

Benyun SHI, Shang Xia, Jiming LIU*

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

4 Citations (Scopus)

Abstract

The transmission of infectious diseases can be affected by various interactive factors at or across different scales, such as environmental factors (e.g., temperature) and physiological factors (e.g., immunity). In view of this, to effectively and efficiently monitor and response to an infectious disease, it would be necessary for us to systematically model these factors and their impacts on disease transmission. In this paper, we propose a complex systems approach to infectious disease surveillance and response that puts a special emphasis on complex systems modeling and policy-level decision making with consideration of multi-scale interactive factors and/or surveillance data of disease prevalence. We demonstrate the implementation of our approach by presenting two real-world studies, one on the air-borne influenza epidemic in Hong Kong and the other on the vector-borne malaria endemic in Yunnan, China.

Original languageEnglish
Title of host publicationBrain and Health Informatics - International Conference, BHI 2013, Proceedings
Pages524-535
Number of pages12
DOIs
Publication statusPublished - 2013
EventInternational Conference on Brain and Health Informatics, BHI 2013 - Maebashi, Japan
Duration: 29 Oct 201331 Oct 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8211 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceInternational Conference on Brain and Health Informatics, BHI 2013
Country/TerritoryJapan
CityMaebashi
Period29/10/1331/10/13

Scopus Subject Areas

  • Theoretical Computer Science
  • Computer Science(all)

User-Defined Keywords

  • Complex systems modeling
  • Data-driven computational intelligence
  • Policy-level decision making

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