An open source tool to infer epidemiological and immunological dynamics from serological data: serosolver.
Journal
PLoS computational biology
ISSN: 1553-7358
Titre abrégé: PLoS Comput Biol
Pays: United States
ID NLM: 101238922
Informations de publication
Date de publication:
05 2020
05 2020
Historique:
received:
10
01
2020
accepted:
01
04
2020
revised:
21
05
2020
pubmed:
5
5
2020
medline:
29
8
2020
entrez:
5
5
2020
Statut:
epublish
Résumé
We present a flexible, open source R package designed to obtain biological and epidemiological insights from serological datasets. Characterising past exposures for multi-strain pathogens poses a specific statistical challenge: observed antibody responses measured in serological assays depend on multiple unobserved prior infections that produce cross-reactive antibody responses. We provide a general modelling framework to jointly infer infection histories and describe immune responses generated by these infections using antibody titres against current and historical strains. We do this by linking latent infection dynamics with a mechanistic model of antibody kinetics that generates expected antibody titres over time. Our aim is to provide a flexible package to identify infection histories that can be applied to a range of pathogens. We present two case studies to illustrate how our model can infer key immunological parameters, such as antibody titre boosting, waning and cross-reaction, as well as latent epidemiological processes such as attack rates and age-stratified infection risk.
Identifiants
pubmed: 32365062
doi: 10.1371/journal.pcbi.1007840
pii: PCOMPBIOL-D-20-00058
pmc: PMC7241836
doi:
Substances chimiques
Antibodies
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e1007840Subventions
Organisme : Medical Research Council
ID : MC_PC_19012
Pays : United Kingdom
Organisme : NIA NIH HHS
ID : R56 AG048075
Pays : United States
Organisme : Department of Health
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 200187/Z/15/Z
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/J008761/1
Pays : United Kingdom
Organisme : NIGMS NIH HHS
ID : U01 GM110721
Pays : United States
Organisme : Wellcome Trust
ID : 200861/Z/16/Z
Pays : United Kingdom
Organisme : NIAID NIH HHS
ID : R01 AI114703
Pays : United States
Organisme : Wellcome Trust
ID : 206250/Z/17/Z
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/R015600/1
Pays : United Kingdom
Déclaration de conflit d'intérêts
The authors have declared that no competing interests exist.
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