dc.contributor.author
Duwal, Sulav
dc.contributor.author
Winkelmann, Stefanie
dc.contributor.author
Schütte, Christof
dc.contributor.author
Kleist, Max von
dc.date.accessioned
2018-06-08T03:27:53Z
dc.date.available
2015-07-02T21:26:41.790Z
dc.identifier.uri
https://refubium.fu-berlin.de/handle/fub188/15238
dc.identifier.uri
http://dx.doi.org/10.17169/refubium-19426
dc.description.abstract
An estimated 2.7 million new HIV-1 infections occurred in 2010. `Treatment-
for-prevention’ may strongly prevent HIV-1 transmission. The basic idea is
that immediate treatment initiation rapidly decreases virus burden, which
reduces the number of transmittable viruses and thereby the probability of
infection. However, HIV inevitably develops drug resistance, which leads to
virus rebound and nullifies the effect of `treatment-for-prevention’ for the
time it remains unrecognized. While timely conducted treatment changes may
avert periods of viral rebound, necessary treatment options and diagnostics
may be lacking in resource-constrained settings. Within this work, we provide
a mathematical platform for comparing different treatment paradigms that can
be applied to many medical phenomena. We use this platform to optimize two
distinct approaches for the treatment of HIV-1: (i) a diagnostic-guided
treatment strategy, based on infrequent and patient-specific diagnostic
schedules and (ii) a pro-active strategy that allows treatment adaptation
prior to diagnostic ascertainment. Both strategies are compared to current
clinical protocols (standard of care and the HPTN052 protocol) in terms of
patient health, economic means and reduction in HIV-1 onward transmission
exemplarily for South Africa. All therapeutic strategies are assessed using a
coarse-grained stochastic model of within-host HIV dynamics and pseudo-codes
for solving the respective optimal control problems are provided. Our
mathematical model suggests that both optimal strategies (i)-(ii) perform
better than the current clinical protocols and no treatment in terms of
economic means, life prolongation and reduction of HIV-transmission. The
optimal diagnostic-guided strategy suggests rare diagnostics and performs
similar to the optimal pro-active strategy. Our results suggest that
‘treatment-for-prevention’ may be further improved using either of the two
analyzed treatment paradigms.
en
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.subject.ddc
600 Technik, Medizin, angewandte Wissenschaften::610 Medizin und Gesundheit::616 Krankheiten
dc.title
Optimal Treatment Strategies in the Context of ‘Treatment for Prevention’
against HIV-1 in Resource-Poor Settings
dc.type
Wissenschaftlicher Artikel
dcterms.bibliographicCitation
PLoS Comput Biol. - 11 (2015), 4, Artikel Nr. e1004200.
dcterms.bibliographicCitation.doi
10.1371/journal.pcbi.1004200
dcterms.bibliographicCitation.url
http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004200
refubium.affiliation
Mathematik und Informatik
de
refubium.funding
Deutsche Forschungsgemeinschaft (DFG)
refubium.mycore.fudocsId
FUDOCS_document_000000022515
refubium.note.author
Gefördert durch die DFG und den Open Access Publikationsfonds der Freien
Universität Berlin.
refubium.resourceType.isindependentpub
no
refubium.mycore.derivateId
FUDOCS_derivate_000000004968
dcterms.accessRights.openaire
open access