A population of bang-bang switches of defective interfering particles makes within-host dynamics of dengue virus controllable.


Journal

PLoS computational biology
ISSN: 1553-7358
Titre abrégé: PLoS Comput Biol
Pays: United States
ID NLM: 101238922

Informations de publication

Date de publication:
11 2019
Historique:
received: 23 11 2018
accepted: 27 09 2019
revised: 21 11 2019
pubmed: 12 11 2019
medline: 15 2 2020
entrez: 12 11 2019
Statut: epublish

Résumé

The titre of virus in a dengue patient and the duration of this viraemia has a profound effect on whether or not a mosquito will become infected when it feeds on the patient and this, in turn, is a key driver of the magnitude of a dengue outbreak. The assessment of the heterogeneity of viral dynamics in dengue-infected patients and its precise treatment are still uncertain. Infection onset, patient physiology and immune response are thought to play major roles in the development of the viral load. Research has explored the interference and spontaneous generation of defective virus particles, but have not examined both the antibody and defective particles during natural infection. We explore the intrinsic variability in the within-host dynamics of viraemias for a population of patients using the method of population of models (POMs). A dataset from 208 patients is used to initially calibrate 20,000 models for the infection kinetics for each of the four dengue virus serotypes. The calibrated POMs suggests that naturally generated defective particles may interfere with the viraemia, but the generated defective virus particles are not adequate to reduce high fever and viraemia duration. The effect of adding excess defective dengue virus interfering particles to patients as a therapeutic is evaluated using the calibrated POMs in a bang-bang (on-off or two-step) optimal control setting. Bang-bang control is a class of binary feedback control that turns either 'ON' or 'OFF' at different time points, determined by the system feedback. Here, the bang-bang control estimates the mathematically optimal dose and duration of the intervention for each model in the POM set.

Identifiants

pubmed: 31710599
doi: 10.1371/journal.pcbi.1006668
pii: PCOMPBIOL-D-18-01981
pmc: PMC6872170
doi:

Types de publication

Journal Article Research Support, U.S. Gov't, Non-P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Pagination

e1006668

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

Références

Cell Syst. 2016 Jan 27;2(1):15-26
pubmed: 27136686
Nature. 1970 Apr 25;226(5243):325-7
pubmed: 5439728
Curr Opin Virol. 2018 Dec;33:74-80
pubmed: 30099321
PLoS One. 2016 Jan 26;11(1):e0147281
pubmed: 26812153
J R Soc Interface. 2014 Jul 6;11(96):
pubmed: 24829280
Math Biosci. 2014 Jan;247:1-12
pubmed: 24513243
J Theor Biol. 1995 Aug 21;175(4):567-76
pubmed: 7475092
Math Biosci. 2018 Oct;304:62-78
pubmed: 30055213
J Trop Med. 2012;2012:628475
pubmed: 22529868
PLoS Comput Biol. 2016 May 23;12(5):e1004951
pubmed: 27213681
Viruses. 2011 Feb;3(2):160-71
pubmed: 22049308
Proc Natl Acad Sci U S A. 1994 Aug 30;91(18):8685-9
pubmed: 8078942
Math Biosci. 2019 Mar;309:163-173
pubmed: 30149021
J Theor Biol. 2019 Jun 7;470:30-42
pubmed: 30853393
PLoS Pathog. 2013 Feb;9(2):e1003193
pubmed: 23468631
Lancet Infect Dis. 2015 Jul;15(7):862-6
pubmed: 26051887
Nature. 2013 Apr 25;496(7446):504-7
pubmed: 23563266
J Infect Dis. 2000 Jan;181(1):2-9
pubmed: 10608744
PLoS Negl Trop Dis. 2012;6(8):e1760
pubmed: 22880140
Bioinformatics. 2015 Nov 1;31(21):3558-60
pubmed: 26142188
Prog Biophys Mol Biol. 2016 Jan;120(1-3):115-27
pubmed: 26701222
Sci Adv. 2018 Jan 10;4(1):e1701676
pubmed: 29349296
Proc Natl Acad Sci U S A. 2013 Jun 4;110(23):E2098-105
pubmed: 23690584
Proc Natl Acad Sci U S A. 2013 May 28;110(22):9072-7
pubmed: 23674683
PLoS Negl Trop Dis. 2015 Sep 01;9(9):e0004052
pubmed: 26325059
Science. 2006 Jan 13;311(5758):236-8
pubmed: 16410525
Virus Res. 2016 Feb 2;213:90-99
pubmed: 26592173
Curr Top Microbiol Immunol. 1986;128:55-84
pubmed: 3533448
Adv Virus Res. 1954;2:59-79
pubmed: 13228257
PLoS Comput Biol. 2016 Nov 17;12(11):e1005194
pubmed: 27855153
Bull World Health Organ. 1966;35(1):3-15
pubmed: 5297536
J Theor Biol. 2000 Sep 21;206(2):279-90
pubmed: 10966764
PLoS One. 2011 Apr 29;6(4):e19447
pubmed: 21559384
Yale J Biol Med. 1970 Apr;42(5):311-28
pubmed: 5419206

Auteurs

Tarunendu Mapder (T)

School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia.
Australian Research Council Centre of Excellence for Mathematical and Statistical Frontiers, Queensland University of Technology, Brisbane, Queensland, Australia.

Sam Clifford (S)

Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom.

John Aaskov (J)

Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, Australia.

Kevin Burrage (K)

School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia.
Australian Research Council Centre of Excellence for Mathematical and Statistical Frontiers, Queensland University of Technology, Brisbane, Queensland, Australia.
Department of Computer Science, University of Oxford, Oxford, United Kingdom.

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH