Giuseppe
Emeritus
[Source: Proceedings of the National Academy of the Sciences of the United States of America, full page: (LINK). Abstract, edited.]
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Unifying the spatial epidemiology and molecular evolution of emerging epidemics
Oliver G. Pybus<SUP>a</SUP>,<SUP>1</SUP>,<SUP>2</SUP>, Marc A. Suchard<SUP>b</SUP>,<SUP>c</SUP>,<SUP>d</SUP>,<SUP>1</SUP>, Philippe Lemey<SUP>e</SUP>,<SUP>1</SUP>, Flavien J. Bernardin<SUP>f</SUP>,<SUP>g</SUP>, Andrew Rambaut<SUP>h</SUP>,<SUP>i</SUP>, Forrest W. Crawford<SUP>b</SUP>, Rebecca R. Gray<SUP>a</SUP>, Nimalan Arinaminpathy<SUP>j</SUP>, Susan L. Stramer<SUP>k</SUP>, Michael P. Busch<SUP>f</SUP>,<SUP>g</SUP>, and Eric L. Delwart<SUP>f</SUP>,<SUP>g</SUP>
Author Affiliations: <SUP>a</SUP>Department of Zoology, University of Oxford, Oxford OX1 3PS, United Kingdom; Departments of <SUP>b</SUP>Biomathematics, <SUP>c</SUP>Biostatistics, and <SUP>d</SUP>Human Genetics, University of California, Los Angeles, CA 90095; <SUP>e</SUP>Department of Microbiology and Immunology, Rega Institute, KU Leuven, 3000 Leuven, Belgium; <SUP>f</SUP>Blood Systems Research Institute, San Francisco, CA 94118; <SUP>g</SUP>Department of Laboratory Medicine, University of California, San Francisco, CA 94143; <SUP>h</SUP>Institute for Evolutionary Biology, Edinburgh University, Edinburgh EH9 3JT, United Kingdom; <SUP>i</SUP>Fogarty International Center, National Institutes of Health, Bethesda, MD 20892-2220; <SUP>j</SUP>Department of Ecology and Evolution, Princeton University, Princeton, NJ 08544-2016; and <SUP>k</SUP>Scientific Support Office, American Red Cross, Gaithersburg, MD 20877
Edited by David M. Hillis, University of Texas at Austin, Austin, TX, and approved July 27, 2012 (received for review April 19, 2012)
Abstract
We introduce a conceptual bridge between the previously unlinked fields of phylogenetics and mathematical spatial ecology, which enables the spatial parameters of an emerging epidemic to be directly estimated from sampled pathogen genome sequences. By using phylogenetic history to correct for spatial autocorrelation, we illustrate how a fundamental spatial variable, the diffusion coefficient, can be estimated using robust nonparametric statistics, and how heterogeneity in dispersal can be readily quantified. We apply this framework to the spread of the West Nile virus across North America, an important recent instance of spatial invasion by an emerging infectious disease. We demonstrate that the dispersal of West Nile virus is greater and far more variable than previously measured, such that its dissemination was critically determined by rare, long-range movements that are unlikely to be discerned during field observations. Our results indicate that, by ignoring this heterogeneity, previous models of the epidemic have substantially overestimated its basic reproductive number. More generally, our approach demonstrates that easily obtainable genetic data can be used to measure the spatial dynamics of natural populations that are otherwise difficult or costly to quantify.
<SUP>1</SUP>O.G.P., M.A.S., and P.L. contributed equally to this work.
<SUP>2</SUP>To whom correspondence should be addressed. E-mail: oliver.pybus@zoo.ox.ac.uk.
Author contributions: O.G.P. designed research; O.G.P., M.A.S., P.L., F.J.B., A.R., F.W.C., R.R.G., N.A., S.L.S., M.P.B., and E.L.D. performed research; M.A.S., P.L., S.L.S., M.P.B., and E.L.D. contributed new reagents/analytic tools; O.G.P., M.A.S., P.L., F.J.B., A.R., F.W.C., R.R.G., and N.A. analyzed data; and O.G.P., M.A.S., and P.L. wrote the paper.
The authors declare no conflict of interest.
This article is a PNAS Direct Submission.
Data deposition: The sequences reported in this paper have been deposited in the GenBank database, www.ncbi.nlm.nih.gov (accession nos. GQ507468?GQ507484).
This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1206598109/-/DCSupplemental.
-Author Affiliations: <SUP>a</SUP>Department of Zoology, University of Oxford, Oxford OX1 3PS, United Kingdom; Departments of <SUP>b</SUP>Biomathematics, <SUP>c</SUP>Biostatistics, and <SUP>d</SUP>Human Genetics, University of California, Los Angeles, CA 90095; <SUP>e</SUP>Department of Microbiology and Immunology, Rega Institute, KU Leuven, 3000 Leuven, Belgium; <SUP>f</SUP>Blood Systems Research Institute, San Francisco, CA 94118; <SUP>g</SUP>Department of Laboratory Medicine, University of California, San Francisco, CA 94143; <SUP>h</SUP>Institute for Evolutionary Biology, Edinburgh University, Edinburgh EH9 3JT, United Kingdom; <SUP>i</SUP>Fogarty International Center, National Institutes of Health, Bethesda, MD 20892-2220; <SUP>j</SUP>Department of Ecology and Evolution, Princeton University, Princeton, NJ 08544-2016; and <SUP>k</SUP>Scientific Support Office, American Red Cross, Gaithersburg, MD 20877
Edited by David M. Hillis, University of Texas at Austin, Austin, TX, and approved July 27, 2012 (received for review April 19, 2012)
Abstract
We introduce a conceptual bridge between the previously unlinked fields of phylogenetics and mathematical spatial ecology, which enables the spatial parameters of an emerging epidemic to be directly estimated from sampled pathogen genome sequences. By using phylogenetic history to correct for spatial autocorrelation, we illustrate how a fundamental spatial variable, the diffusion coefficient, can be estimated using robust nonparametric statistics, and how heterogeneity in dispersal can be readily quantified. We apply this framework to the spread of the West Nile virus across North America, an important recent instance of spatial invasion by an emerging infectious disease. We demonstrate that the dispersal of West Nile virus is greater and far more variable than previously measured, such that its dissemination was critically determined by rare, long-range movements that are unlikely to be discerned during field observations. Our results indicate that, by ignoring this heterogeneity, previous models of the epidemic have substantially overestimated its basic reproductive number. More generally, our approach demonstrates that easily obtainable genetic data can be used to measure the spatial dynamics of natural populations that are otherwise difficult or costly to quantify.
- phylogeny
- phylogeography
- transmission
<SUP>1</SUP>O.G.P., M.A.S., and P.L. contributed equally to this work.
<SUP>2</SUP>To whom correspondence should be addressed. E-mail: oliver.pybus@zoo.ox.ac.uk.
Author contributions: O.G.P. designed research; O.G.P., M.A.S., P.L., F.J.B., A.R., F.W.C., R.R.G., N.A., S.L.S., M.P.B., and E.L.D. performed research; M.A.S., P.L., S.L.S., M.P.B., and E.L.D. contributed new reagents/analytic tools; O.G.P., M.A.S., P.L., F.J.B., A.R., F.W.C., R.R.G., and N.A. analyzed data; and O.G.P., M.A.S., and P.L. wrote the paper.
The authors declare no conflict of interest.
This article is a PNAS Direct Submission.
Data deposition: The sequences reported in this paper have been deposited in the GenBank database, www.ncbi.nlm.nih.gov (accession nos. GQ507468?GQ507484).
This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1206598109/-/DCSupplemental.
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