Linked Life Data

20943696

Source:http://linkedlifedata.com/resource/pubmed/id/20943696

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1710
pubmed:dateCreated
2011-3-24
pubmed:abstractText
Antibodies to the pre-erythrocytic antigens, circumsporozoite protein (CSP), thrombospondin-related adhesive protein (TRAP) and liver-stage antigen 1, have been measured in field studies of semi-immune adults and shown to correlate with protection from Plasmodium falciparum infection. A mathematical model is formulated to estimate the probability of sporozoite infection as a function of antibody titres to multiple pre-erythrocytic antigens. The variation in antibody titres from field data was used to estimate the relationship between the probability of P. falciparum infection per infectious mosquito bite and antibody titre. Using this relationship, we predict the effect of vaccinations that boost baseline CSP or TRAP antibody titres. Assuming the estimated relationship applies to vaccine-induced antibody titres, then single-component CSP or TRAP antibody-mediated pre-erythrocytic vaccines are likely to provide partial protection from infection, with vaccine efficacy of approximately 50 per cent depending on the magnitude of the vaccine-induced boost to antibody titres. It is possible that the addition of a TRAP component to a CSP-based vaccine such as RTS,S would provide an increase in infection-blocking efficacy of approximately 25 per cent should the problem of immunological interference between antigens be overcome.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
May
pubmed:issn
1471-2954
pubmed:author
pubmed:issnType
Electronic
pubmed:day
7
pubmed:volume
278
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1298-305
pubmed:meshHeading
pubmed:year
2011
pubmed:articleTitle
Efficacy model for antibody-mediated pre-erythrocytic malaria vaccines.
pubmed:affiliation
MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, UK. m.white08@imperial.ac.uk
pubmed:publicationType
Journal Article