- Associação Brasileira de Divulgação Científica (ABRADIC)
- Centers for Disease Control and Prevention
- Public Library of Science
- BMJ Publishing Group
- SAGE Publications
- World Bank, Washington, DC
- Academic Press Ltd
- Marine Biological Association of the United Kingdom
- Universidade Nacional da Austrália
- Blackwell Publishing Ltd
- Universidade de Cambridge
- Universidade Duke
- John Wiley & Sons Inc
- Organización Panamericana de la Salud
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DETECTION OF INFECTIOUS-DISEASE AGENTS IN TISSUE BY IMMUNOCYTOCHEMISTRY
Emerging Trends in International Law Concerning Global Infectious Disease Control1
Fatal Infectious Disease Surveillance in a Medical Examiner Database1
Systematic Review and Meta-Analysis on the Association Between Outpatient Statins Use and Infectious Disease-Related Mortality
Differences in research funding for women scientists: a systematic comparison of UK investments in global infectious disease research during 1997–2010
Funding Infectious Disease Research: A Systematic Analysis of UK Research Investments by Funders 1997–2010
Systematic analysis of funding awarded to institutions in the United Kingdom for infectious disease research, 1997–2010
On SARS Type Economic Effects During Infectious Disease Outbreaks
Invasion of infectious diseases in finite homogeneous populations
Spatiotemporal Infectious Disease Modeling: A BME-SIR Approach
Beach sand and the potential for infectious disease transmission: observations and recommendations
Infectious diseases, urbanization and climate change: challenges in future China
Unhealthy landscapes: policy recommendations on land use change and infectious disease emergence
Factors Influencing Performance of Internet-Based Biosurveillance Systems Used in Epidemic Intelligence for Early Detection of Infectious Diseases Outbreaks
Taking sociology seriously: a new approach to the bioethical problems of infectious disease
Final CIDC Report to Defra; The Cambridge Infectious Diseases Consortium
Phylodynamic Methods for Infectious Disease Epidemiology
In this dissertation, I present a general statistical framework for phylodynamic inference that can be used to estimate epidemiological parameters and reconstruct disease dynamics from pathogen genealogies. This framework can be used to fit a broad class of epidemiological models, including nonlinear stochastic models, to genealogies by relating the population dynamics of a pathogen to its genealogy using coalescent theory. By combining Markov chain Monte Carlo and particle filtering methods, efficient Bayesian inference of all parameters and unobserved latent variables is possible even when analytical likelihood expressions are not available under the epidemiological model. Through extensive simulations, I show that this method can be used to reliably estimate epidemiological parameters of interest as well as reconstruct past disease dynamics from genealogies, or jointly from genealogies and other common sources of epidemiological data like time series. I then extend this basic framework to include different types of host population structure, including models with spatial structure, multiple-hosts or vectors, and different stages of infection. The later is demonstrated by using a multistage model of HIV infection to estimate stage-specific transmission rates and incidence from HIV sequence data collected in Detroit...