Giuseppe
Emeritus
[Source: PLoS Pathogens, full text: (LINK). Abstract, edited.]
Genetic Assignment Methods for Gaining Insight into the Management of Infectious Disease by Understanding Pathogen, Vector, and Host Movement
Justin V. Remais<SUP>1</SUP><SUP>*</SUP>, Ning Xiao<SUP>2</SUP>, Adam Akullian<SUP>3</SUP>, Dongchuan Qiu<SUP>2</SUP>, David Blair<SUP>4</SUP>
1 Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America, 2 Institute of Parasitic Disease, Sichuan Provincial Center for Disease Control and Prevention, Chengdu, Sichuan, People's Republic of China, 3 Environmental Health Sciences, School of Public Health, University of California, Berkeley, Berkeley, California, United States of America, 4 School of Marine and Tropical Biology, James Cook University, Townsville, Queensland, Australia
Abstract
For many pathogens with environmental stages, or those carried by vectors or intermediate hosts, disease transmission is strongly influenced by pathogen, host, and vector movements across complex landscapes, and thus quantitative measures of movement rate and direction can reveal new opportunities for disease management and intervention. Genetic assignment methods are a set of powerful statistical approaches useful for establishing population membership of individuals. Recent theoretical improvements allow these techniques to be used to cost-effectively estimate the magnitude and direction of key movements in infectious disease systems, revealing important ecological and environmental features that facilitate or limit transmission. Here, we review the theory, statistical framework, and molecular markers that underlie assignment methods, and we critically examine recent applications of assignment tests in infectious disease epidemiology. Research directions that capitalize on use of the techniques are discussed, focusing on key parameters needing study for improved understanding of patterns of disease.
Citation: Remais JV, Xiao N, Akullian A, Qiu D, Blair D (2011) Genetic Assignment Methods for Gaining Insight into the Management of Infectious Disease by Understanding Pathogen, Vector, and Host Movement. PLoS Pathog 7(4): e1002013. doi:10.1371/journal.ppat.1002013
Editor: Marianne Manchester, University of California San Diego, United States of America
Published: April 28, 2011
Copyright: ? 2011 Remais et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work was supported in part by the Ecology of Infectious Disease program of the National Science Foundation under Grant No. 0622743, by the National Institute for Allergy and Infectious Disease (grant K01AI091864), and the Global Health Institute Faculty Distinction Fund at Emory University. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
* E-mail: justin.remais@emory.edu
- ------Justin V. Remais<SUP>1</SUP><SUP>*</SUP>, Ning Xiao<SUP>2</SUP>, Adam Akullian<SUP>3</SUP>, Dongchuan Qiu<SUP>2</SUP>, David Blair<SUP>4</SUP>
1 Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America, 2 Institute of Parasitic Disease, Sichuan Provincial Center for Disease Control and Prevention, Chengdu, Sichuan, People's Republic of China, 3 Environmental Health Sciences, School of Public Health, University of California, Berkeley, Berkeley, California, United States of America, 4 School of Marine and Tropical Biology, James Cook University, Townsville, Queensland, Australia
Abstract
For many pathogens with environmental stages, or those carried by vectors or intermediate hosts, disease transmission is strongly influenced by pathogen, host, and vector movements across complex landscapes, and thus quantitative measures of movement rate and direction can reveal new opportunities for disease management and intervention. Genetic assignment methods are a set of powerful statistical approaches useful for establishing population membership of individuals. Recent theoretical improvements allow these techniques to be used to cost-effectively estimate the magnitude and direction of key movements in infectious disease systems, revealing important ecological and environmental features that facilitate or limit transmission. Here, we review the theory, statistical framework, and molecular markers that underlie assignment methods, and we critically examine recent applications of assignment tests in infectious disease epidemiology. Research directions that capitalize on use of the techniques are discussed, focusing on key parameters needing study for improved understanding of patterns of disease.
Citation: Remais JV, Xiao N, Akullian A, Qiu D, Blair D (2011) Genetic Assignment Methods for Gaining Insight into the Management of Infectious Disease by Understanding Pathogen, Vector, and Host Movement. PLoS Pathog 7(4): e1002013. doi:10.1371/journal.ppat.1002013
Editor: Marianne Manchester, University of California San Diego, United States of America
Published: April 28, 2011
Copyright: ? 2011 Remais et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work was supported in part by the Ecology of Infectious Disease program of the National Science Foundation under Grant No. 0622743, by the National Institute for Allergy and Infectious Disease (grant K01AI091864), and the Global Health Institute Faculty Distinction Fund at Emory University. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
* E-mail: justin.remais@emory.edu