Commentary: resolving pertussis resurgence and vaccine immunity using mathematical transmission models.


Journal

Human vaccines & immunotherapeutics
ISSN: 2164-554X
Titre abrégé: Hum Vaccin Immunother
Pays: United States
ID NLM: 101572652

Informations de publication

Date de publication:
2019
Historique:
pubmed: 21 11 2018
medline: 27 2 2020
entrez: 21 11 2018
Statut: ppublish

Résumé

The epidemiology of pertussis-a vaccine-preventable respiratory infection typically caused by the bacterium Bordetella pertussis-remains puzzling. Indeed, the disease seems nowhere close to eradication and has even re-emerged in certain countries-such as the US-that have maintained high vaccination coverage. Because the dynamics of pertussis are shaped by past vaccination and natural infection rates, with the relevant timescale spanning decades, the interpretation of such unexpected trends is not straightforward. In this commentary, we propose that mathematical transmission models play an essential role in helping to interpret the data and in closing knowledge gaps in pertussis epidemiology. We submit that recent advances in statistical inference methods now allow us to estimate key parameters, such as the nature and duration of vaccinal immunity, which have to date been difficult to quantify. We illustrate these points with the results of a recent study based on data from Massachusetts (Domenech de Cellès, Magpantay, King, and Rohani, Sci. Transl. Med. 2018;10: eaaj1748. doi:10.1126/scitranslmed.aaj1748), in which we used such methods to elucidate the mechanisms underlying the ongoing resurgence of pertussis. In addition, we list a number of safety checks that can be used to critically assess mathematical models. Finally, we discuss the remaining uncertainties surrounding pertussis vaccines, in particular the acellular vaccines used for teenage booster immunizations.

Identifiants

pubmed: 30457424
doi: 10.1080/21645515.2018.1549432
pmc: PMC6988877
doi:

Substances chimiques

Pertussis Vaccine 0

Types de publication

Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

683-686

Subventions

Organisme : NIAID NIH HHS
ID : R01 AI101155
Pays : United States
Organisme : NIGMS NIH HHS
ID : U54 GM111274
Pays : United States

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Auteurs

M Domenech de Cellès (M)

a Biostatistics, Biomathematics, Pharmacoepidemiology, and Infectious Diseases (B2PHI) Unit , Institut Pasteur, Inserm U1181, University of Versailles St-Quentin-en-Yvelines.

A A King (AA)

b Department of Ecology and Evolutionary Biology , University of Michigan , Ann Arbor , MI , USA.
c Department of Mathematics , University of Michigan , Ann Arbor , MI , USA.
d Center for the Study of Complex Systems , University of Michigan , Ann Arbor , MI , USA.

P Rohani (P)

e Odum School of Ecology , University of Georgia , Athens , GA , USA.
f Department of Infectious Diseases , University of Georgia , Athens , GA , USA.
g Center for the Ecology of Infectious Diseases , University of Georgia , Athens , GA , USA.

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Classifications MeSH