Ecological and evolutionary analysis of infectious diseases has proven invaluable for understanding and predicting contemporary patterns of disease emergence and spread. However, the two forms of analysis (ecological and evolutionary) have largely remained separated with different intellectual communities undertaking one or the other form of analysis, but rarely both. Often, the obstacle to combined analysis resides in an apparent large difference in the time-scale of operation of evolutionary and ecological processes (millennia versus months or years). Yet, for many host-pathogen systems, especially those associated with RNA viral pathogens, the time-scale of ecological dynamics and evolutionary change are identical. In this proposal, we undertake a synthesis of ecological and evolutionary dynamics using rabies virus (RABV) and Ebola virus (EBOV) as model systems. Following on the spatial dynamics models we have developed for predicting the spread of rabies across specific states (CT, NY, OH), we will construct population-based simulations of the spread of infection among subpopulations of raccoon hosts distributed over ecological landscapes. Transmission of virus will be tracked within """"""""transmission trees"""""""" and virus will evolve according to known evolutionary rates and mutation processes for RABV. We will examine the relationship between different types and phases of SEIR dynamics on the residual signature of demographic change within the molecular phylogeny, based on predicted variation in the structure of the coalescent. In principle, these types of signatures can also provide us with specific information about the underlying epidemiological processes. We will ascertain differences in the revealed coalescent under conditions of endemic steady state versus epidemic spread as well as under scenarios involving demographic and spatial heterogeneity within these two different states. Over the past eight years we have been working closely with state and federal agencies in the US and Canada to compile an unprecedented database and sample library for the historical and contemporary expansion of rabies virus. We will use this database, coupled with targeted sample acquisition, to test the integrated model. We are also working with labs in Africa to construct models for the most likely transmission dynamics of Ebola among candidate hosts, calibrated against geo-referenced molecular sequence data from both human and candidate host (Gorilla, chimpanzee, bat) infections. We believe that the work executed on rabies will be extendable and useful in predicting patterns of emergence and spread in this alarming human pathogen. Project Narrative: We are constructing integrated models for the ecology and evolution of rabies and Ebola viruses, two of the most important viral zoonotic diseases worldwide. These models will be instrumental in understanding patterns of emergence and spread, as well as targeting mechanisms for control and eradication.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Project (R01)
Project #
5R01AI047498-10
Application #
8065930
Study Section
Genetic Variation and Evolution Study Section (GVE)
Program Officer
Gezmu, Misrak
Project Start
1999-09-15
Project End
2015-04-30
Budget Start
2011-05-01
Budget End
2012-04-30
Support Year
10
Fiscal Year
2011
Total Cost
$352,152
Indirect Cost
Name
Emory University
Department
Biology
Type
Schools of Arts and Sciences
DUNS #
066469933
City
Atlanta
State
GA
Country
United States
Zip Code
30322
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Nadin-Davis, Susan A; Colville, Adam; Trewby, Hannah et al. (2017) Application of high-throughput sequencing to whole rabies viral genome characterisation and its use for phylogenetic re-evaluation of a raccoon strain incursion into the province of Ontario. Virus Res 232:123-133
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Duke-Sylvester, Scott M; Biek, Roman; Real, Leslie A (2013) Molecular evolutionary signatures reveal the role of host ecological dynamics in viral disease emergence and spread. Philos Trans R Soc Lond B Biol Sci 368:20120194

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