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Reconstructing HIV Epidemics from HIV Phylogenetics

从 HIV 系统发育学重建 HIV 流行病

基本信息

批准号：
8921721
负责人：
Thomas K. Leitner
金额：
$ 50.18万
依托单位：
LOS ALAMOS NAT SECTY-LOS ALAMOS NAT LAB
依托单位国家：
美国
项目类别：
财政年份：
2010
资助国家：
美国
起止时间：
2010-06-15 至 2020-02-29
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8921721
关键词：
Accounting Address Affect Africa Clinical Communities Computer software Contact Tracing DNA Sequence DNA Sequence Alteration Data Data Set Databases Deltastab Disease Epidemic Epidemiology Europe Event Evolution General Population Genes Goals HIV HIV-1 Human Immune Incidence Infection Internet Intervention Methods Modeling Molecular Molecular Biology Molecular Epidemiology Monitor Mutation Pathogenesis Patients Pattern Performance Persons Phylogenetic Analysis Phylogeny Population Population Sizes Prevalence Prevention Process Public Health Quality Control Recording of previous events Records Research Research Personnel Research Support Resources Sampling Science Sequence Analysis Site Social Network Software Design Sorting - Cell Movement Statistical Methods Structure System Time Trees USSR United States Virus base clinical sequencing computerized tools deep sequencing epidemiological model experience improved intervention effect mathematical theory multi-scale modeling novel prevent programs public health relevance reconstruction statistics theories tool transmission process trend user-friendly

项目摘要

DESCRIPTION (provided by applicant): Despite ongoing prevention campaigns, the HIV epidemic persists on a global scale. To monitor the effects of intervention campaigns, and more generally, to estimate incidence and prevalence in human populations, patterns of disease spread must be accurately reconstructed. Our project brings together a team of experienced researchers from clinical, molecular biology, epidemiological, mathematical, and evolutionary fields. We will carefully examine phylogenetic limitations and develop statistical methods to address and quantify their effects on transmission reconstruction. We will build novel phylodynamic inference methods that adequately take these limitations into account, and incorporate recent statistical advances developed in social network and epidemiological sciences. We will use seven large datasets describing both HIV within-host and between-host evolution and transmission. These data comprise many thousands of HIV cases from the US, Europe, former Soviet Union, and Africa, described by HIV sequence, clinical and demographic data. The overarching hypothesis of this project is that the evolutionary process of HIV-1 records genetic mutations affected by its epidemiological history. Thus, in this project we aim to extract epidemiological information from phylogenetic analyses of HIV and integrate it with clinical, demographical, and geographical data to push the boundaries of current state-of-the-art epidemiological inference methods. Our specific aims are: 1) Develop a more realistic within-host model of HIV evolutionary dynamics; 2) Jointly infer the unobserved transmission history and virus phylogeny; and 3) Create public software resources that facilitate molecular epidemiology inferences.