Our lab works with domestic and international organizations and institutions to strategize and address health policy and global health issues through mathematical modeling approaches, with highlights on infectious diseases such as HIV, TB, and malaria.
665 Huntington Avenue Building 1, Room 1105, Boston, MA 02115
3D close-up of Mycobacterium tuberculosis bacteria
Welcome
The Menzies Lab is based in the Department of Global Health and Population at the Harvard T.H. Chan School of Public Health. Our research focuses on major infectious diseases, tuberculosis (TB) and human immunodeficiency virus (HIV), in the United States and in low-resource settings.
The lab uses mechanistic and statistical modeling to undertake a range of research investigating the health impact and cost-effectiveness of infectious disease treatment and prevention programs.
Our work involves close collaboration with the Centers for Disease Control and Prevention for US-based TB research, as well as the Gates Foundation, the World Health Organization, and the Global Fund Against AIDS, TB, and Malaria. More recently, our team has been contributing their efforts and working with local health departments on the COVID-19 response.
Nick Menzies is Associate Professor of Global Health in the Department of Global Health and Population, and part of the core faculty of the Harvard Center for Health Decision Science. He uses decision science and quantitative research to understand the consequences of policies to combat major infectious diseases and help design effective disease control programs when resources are limited.
This project provides tailored TB risk evidence to optimize prevention services locally and globally. Prior work shows the feasibility of estimating TB risks for small population groups.
Evaluating the health impact, costs, and cost-effectiveness of infectious disease programs in the U.S., partnering with NCHHSTP at CDC to inform health policy and guide public health decis
TB MAC aims to improve TB care and prevention policy globally and locally, enhancing efficiency and understanding of the epidemiological and health system processes that drive TB outcomes.
