Predictive Modeling of Influenza Shows the Promise of Applied Evolutionary Biology.

Abstract:

:Seasonal influenza is controlled through vaccination campaigns. Evolution of influenza virus antigens means that vaccines must be updated to match novel strains, and vaccine effectiveness depends on the ability of scientists to predict nearly a year in advance which influenza variants will dominate in upcoming seasons. In this review, we highlight a promising new surveillance tool: predictive models. Based on data-sharing and close collaboration between the World Health Organization and academic scientists, these models use surveillance data to make quantitative predictions regarding influenza evolution. Predictive models demonstrate the potential of applied evolutionary biology to improve public health and disease control. We review the state of influenza predictive modeling and discuss next steps and recommendations to ensure that these models deliver upon their considerable biomedical promise.

journal_name

Trends Microbiol

journal_title

Trends in microbiology

authors

Morris DH,Gostic KM,Pompei S,Bedford T,Łuksza M,Neher RA,Grenfell BT,Lässig M,McCauley JW

doi

10.1016/j.tim.2017.09.004

subject

Has Abstract

pub_date

2018-02-01 00:00:00

pages

102-118

issue

2

eissn

0966-842X

issn

1878-4380

pii

S0966-842X(17)30209-3

journal_volume

26

pub_type

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