Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3
pubmed:dateCreated
1997-1-14
pubmed:abstractText
Progress in the development of schistosomiasis models for use in control programmes is limited by the considerable uncertainty in many of the biological parameters. In this paper, this problem is addressed by a comprehensive sensitivity analysis of a schistosomiasis model using the Latin Hypercube method. Fifty simulations with different parameter contributions are run for 50 years with treatment during the first 20 years and reinfection thereafter. The analysis shows only a relatively small divergence between simulations during the chemotherapy treatment programme but considerable divergence in reinfection levels after treatment is stopped. A skewed distribution of outcomes was seen with most simulations showing effective control and a few where control had less impact. The most important uncertainty source was due to the unknown levels of acquired immunity and also uncertainty in the true worm burden. In particular, the strength of the immune response was most important in determining whether control was effective with higher immunity leading to less effective control. Among those simulations in which control was not very effective, those in which the mean worm burden was high showed the least effective control. Since both these are areas of genuine uncertainty, it is proposed that uncertainty analysis should be an integral part of any projection of control programmes.
pubmed:commentsCorrections
http://linkedlifedata.com/resource/pubmed/commentcorrection/8972681-1428017, http://linkedlifedata.com/resource/pubmed/commentcorrection/8972681-1470476, http://linkedlifedata.com/resource/pubmed/commentcorrection/8972681-1641245, http://linkedlifedata.com/resource/pubmed/commentcorrection/8972681-1674152, http://linkedlifedata.com/resource/pubmed/commentcorrection/8972681-1684260, http://linkedlifedata.com/resource/pubmed/commentcorrection/8972681-1780171, http://linkedlifedata.com/resource/pubmed/commentcorrection/8972681-2311368, http://linkedlifedata.com/resource/pubmed/commentcorrection/8972681-3904343, http://linkedlifedata.com/resource/pubmed/commentcorrection/8972681-4000277, http://linkedlifedata.com/resource/pubmed/commentcorrection/8972681-5294264, http://linkedlifedata.com/resource/pubmed/commentcorrection/8972681-5637021, http://linkedlifedata.com/resource/pubmed/commentcorrection/8972681-5860312, http://linkedlifedata.com/resource/pubmed/commentcorrection/8972681-6879047, http://linkedlifedata.com/resource/pubmed/commentcorrection/8972681-7589272, http://linkedlifedata.com/resource/pubmed/commentcorrection/8972681-8413664, http://linkedlifedata.com/resource/pubmed/commentcorrection/8972681-8667377, http://linkedlifedata.com/resource/pubmed/commentcorrection/8972681-8702023
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Dec
pubmed:issn
0950-2688
pubmed:author
pubmed:issnType
Print
pubmed:volume
117
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
537-50
pubmed:dateRevised
2010-9-10
pubmed:meshHeading
pubmed:year
1996
pubmed:articleTitle
The consequences of uncertainty for the prediction of the effects of schistosomiasis control programmes.
pubmed:affiliation
Department of Zoology, Oxford, UK.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't