Lessons from a decade of individual-based models for infectious disease transmission: a systematic review (2006-2015).
Identifieur interne : 000A87 ( Main/Merge ); précédent : 000A86; suivant : 000A88Lessons from a decade of individual-based models for infectious disease transmission: a systematic review (2006-2015).
Auteurs : Lander Willem [Belgique] ; Frederik Verelst [Belgique] ; Joke Bilcke [Belgique] ; Niel Hens [Belgique] ; Philippe Beutels [Belgique]Source :
- BMC infectious diseases [ 1471-2334 ] ; 2017.
Descripteurs français
- KwdFr :
- MESH :
- usage thérapeutique : Vaccins.
- économie : Transmission de maladie infectieuse.
- Humains, Modèles théoriques, Terminologie comme sujet, Transmission de maladie infectieuse, Épidémies.
English descriptors
- KwdEn :
- MESH :
- chemical , therapeutic use : Vaccines.
- economics : Disease Transmission, Infectious.
- prevention & control : Disease Transmission, Infectious.
- Epidemics, Humans, Models, Theoretical, Terminology as Topic.
Abstract
Individual-based models (IBMs) are useful to simulate events subject to stochasticity and/or heterogeneity, and have become well established to model the potential (re)emergence of pathogens (e.g., pandemic influenza, bioterrorism). Individual heterogeneity at the host and pathogen level is increasingly documented to influence transmission of endemic diseases and it is well understood that the final stages of elimination strategies for vaccine-preventable childhood diseases (e.g., polio, measles) are subject to stochasticity. Even so it appears IBMs for both these phenomena are not well established. We review a decade of IBM publications aiming to obtain insights in their advantages, pitfalls and rationale for use and to make recommendations facilitating knowledge transfer within and across disciplines.
DOI: 10.1186/s12879-017-2699-8
PubMed: 28893198
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pubmed:28893198Le document en format XML
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<front><div type="abstract" xml:lang="en">Individual-based models (IBMs) are useful to simulate events subject to stochasticity and/or heterogeneity, and have become well established to model the potential (re)emergence of pathogens (e.g., pandemic influenza, bioterrorism). Individual heterogeneity at the host and pathogen level is increasingly documented to influence transmission of endemic diseases and it is well understood that the final stages of elimination strategies for vaccine-preventable childhood diseases (e.g., polio, measles) are subject to stochasticity. Even so it appears IBMs for both these phenomena are not well established. We review a decade of IBM publications aiming to obtain insights in their advantages, pitfalls and rationale for use and to make recommendations facilitating knowledge transfer within and across disciplines.</div>
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