SOURCE REGION EFFECTS IN EPIDEMIC DISEASE MODELING: COMPARISONS BETWEEN INFLUENZA AND HIV
Identifieur interne : 001F01 ( Main/Exploration ); précédent : 001F00; suivant : 001F02SOURCE REGION EFFECTS IN EPIDEMIC DISEASE MODELING: COMPARISONS BETWEEN INFLUENZA AND HIV
Auteurs : Richard ThomasSource :
- Papers in Regional Science [ 1056-8190 ] ; 1993-07.
Abstract
ABSTRACT The research reported in this paper presents the preliminary findings obtained from applying a multiregion disease model to forecasting pandemics of infectious disease. The beginning section examines the structure of the modeling system together with various start region effects that are embedded in the framework. An appropriate form of the model is fitted to the known spread of the 1957 Asian influenza pandemic and then used to examine the distributions of warning times that are associated with varying the location of the source region. The disease parameters are adjusted to represent current knowledge about the host‐agent relationship for HIV, and used to make povisional forecast for the spread of the virus during the next half century. The discussion considers how this highly simplified simulation procedure might be improved upon in future work, particularly in relation to cross‐infection between the high risk groups.
Url:
DOI: 10.1111/j.1435-5597.1993.tb01876.x
Affiliations:
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<front><div type="abstract" xml:lang="en">ABSTRACT The research reported in this paper presents the preliminary findings obtained from applying a multiregion disease model to forecasting pandemics of infectious disease. The beginning section examines the structure of the modeling system together with various start region effects that are embedded in the framework. An appropriate form of the model is fitted to the known spread of the 1957 Asian influenza pandemic and then used to examine the distributions of warning times that are associated with varying the location of the source region. The disease parameters are adjusted to represent current knowledge about the host‐agent relationship for HIV, and used to make povisional forecast for the spread of the virus during the next half century. The discussion considers how this highly simplified simulation procedure might be improved upon in future work, particularly in relation to cross‐infection between the high risk groups.</div>
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