JAMES O. LLOYD-SMITH, M.SC., PH.D.
Tools and Techniques: mathematical modeling, computer simulation, computational statistics, wildlife and human field epidemiology
Interests: infectious disease dynamics, zoonotic infections, emerging pathogens, virus evolution, host jumps, pathogen adaptation, population ecology, epidemiology
I study the ecology, evolution and epidemiology of infectious diseases, by using mathematical and computational tools to create models that help untangle the complex mechanisms that underlie disease spread and pathogen evolution. I am interested in the processes that give rise to emergence of novel pathogens, and particularly in the emergence of zoonotic pathogens from animal hosts into humans. For example, when a zoonotic virus like H5N1 avian influenza or monkeypox causes a cluster of cases among humans, what determines whether it adapts to become more transmissible and hence cause an epidemic? What determines its level of virulence in the short and long term?
My interests also include the evolutionary responses of pathogens to biomedical interventions, since the concepts and mechanisms involved in antibiotic resistance or vaccine escape are directly analogous to those involved in zoonotic emergence. I have worked on human, wildlife and livestock diseases including leptospirosis, monkeypox, HIV/AIDS, tuberculosis, SARS, influenza, dengue and many others. In all these activities, I collaborate with wildlife biologists, veterinarians, infectious disease specialists, epidemiologists, and microbiologists. I am excited about opportunities to build new collaborations with empirically and theoretically minded colleagues, to study how pathogen evolution impacts human and animal health, and how hosts evolultion is influenced by infectious disease.
I am chair of a working group on pathogen emergence for the NIH-RAPIDD program (Research and Policy for Infectious Disease Dynamics). In this capacity I have helped to organize numerous workshops that address themes in pathogen evolutionary ecology and molecular epidemiology.