Predictive Modeling of Influenza Shows the Promise of Applied Evolutionary Biology.
Trends Microbiol
; 26(2): 102-118, 2018 02.
Article
in En
| MEDLINE
| ID: mdl-29097090
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.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Influenza Vaccines
/
Influenza, Human
/
Biological Evolution
/
Forecasting
Type of study:
Prognostic_studies
/
Risk_factors_studies
Limits:
Humans
Language:
En
Journal:
Trends Microbiol
Journal subject:
MICROBIOLOGIA
Year:
2018
Document type:
Article