4.7 Article

Integrating genetic and epidemiological data to determine transmission pathways of foot-and-mouth disease virus

Journal

PROCEEDINGS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES
Volume 275, Issue 1637, Pages 887-895

Publisher

ROYAL SOC
DOI: 10.1098/rspb.2007.1442

Keywords

foot-and-mouth disease virus; transmission trees; contact tracing; complete genome sequencing

Funding

  1. Biotechnology and Biological Sciences Research Council [BB/F005733/1] Funding Source: Medline
  2. Biotechnology and Biological Sciences Research Council [BB/F005733/1] Funding Source: researchfish
  3. BBSRC [BB/F005733/1] Funding Source: UKRI

Ask authors/readers for more resources

Estimating detailed transmission trees that reflect the relationships between infected individuals or populations during a disease outbreak often provides valuable insights into both the nature of disease transmission and the overall dynamics of the underlying epidemiological process. These trees may be based on epidemiological data that relate to the timing of infection and infectiousness, or genetic data that show the genetic relatedness of pathogens isolated from infected individuals. Genetic data are becoming increasingly important in the estimation of transmission trees of viral pathogens due to their inherently high mutation rate. Here, we propose a maximum-likelihood approach that allows epidemiological and genetic data to be combined within the same analysis to infer probable transmission trees. We apply this approach to data from 20 farms infected during the 2001 UK foot-and-mouth disease outbreak, using complete viral genome sequences from each infected farm and information on when farms were first estimated to have developed clinical disease and when livestock on these farms were culled. Incorporating known infection links due to animal movement prior to imposition of the national movement ban results in the reduction of the number of trees from 41 472 that are consistent with the genetic data to 1728, of which just 4 represent more than 95% of the total likelihood calculated using a model that accounts for the epidemiological data. These trees differ in several ways from those constructed prior to the availability of genetic data.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available