Marc Lipsitch

Professor of Epidemiology

Department of Epidemiology
Department of Immunology and Infectious Diseases

665 Huntington Ave
Kresge Building, Room 506G
Boston, Massachusetts 02115

I am Professor of Epidemiology and Director of the Center for Communicable Disease Dynamics, a center of excellence funded by the MIDAS program of NIH/NIGMS and located in the Department of Epidemiology.  I am also the Associate Director of the Interdisciplinary Concentration in Infectious Disease Epidemiology.  My laboratory work occurs in the Department of Immunology and Infectious Diseases.


My research concerns the effect of naturally acquired host immunity, vaccine-induced immunity and other public health interventions (e.g. antimicrobial use) on the population biology of pathogens and the consequences of changing pathogen populations for human health.  Some of this work is motivated mainly by practical questions in public health (such as vaccine design and intervention targeting), and some is motivated by classical questions in population biology, such as how to explain patterns of coexistence of pathogen strains in space and time.  Studies of Streptococcus pneumoniae combine the practical and the population-biological questions, as well as the experimental and quantitative approaches.

Streptococcus pneumoniae: immune responses and population biology.  Much of my work focuses on the bacterial pathogen Streptococcus pneumoniae, which colonizes the nasopharynx of 30-100% of children worldwide, and causes otitis media, septicemia, pneumonia and meningitis in a small fraction, but a large number of them, with an estimated 800,000+ child deaths a year attributed to pneumococcal disease.  Using experimental and epidemiologic approaches, our laboratory studies the biological determinants of genetic and antigenic diversity in this pathogen: why are there so many serotypes, what maintains the diversity of these serotypes in space and time, and how do our immune systems respond to various serotypes?  We have shown that while young children make effective serotype-specific immune responses to some pneumococcal serotypes (collaboration with Ron Dagan, Ben Gurion University, Israel), there is also evidence in humans for immune responses that are serotype-transcending (collaboration with Richard Malley, Children’s Hospital, Boston).  Also with the Malley laboratory, we have shown in mice that mucosal immunity to colonization occurs in an antigen-specific, antibody-independent, serotype-transcending fashion that is dependent on neutrophils and on TH17, CD4+ T cells.  This work continues, with an effort to understand additional biological differences among serotypes, in which we utilize sets of isogenic pneumococcal strains created in the laboratory that differ only in capsular serotype.  Dan Weinberger recently completed a PhD in the lab, in which he showed that simple measures of capsule biochemistry predict serotype-specific capsule size, resistance to phagocytosis, and prevalence of nasopharyngeal carriage.   An ongoing collaboration led by the Malley laboratory aims to create inexpensive, serotype-transcending vaccines for pneumococcal colonization and disease.  With collaborators incuding Jonathan Finkelstein in Boston and Kate O’Brien at Johns Hopkins, we are studying changes in the pneumococcal population following the introduction of pneumococcal conjugate vaccines, particularly the process of serotype replacement.  We are working with the Broad Institute to develop a population genomics project on S. pneumoniae.  Finally, we have a longstanding interest in epidemiologic and laboratory studies of the evolutionary dynamics of drug resistance in pneumococci, as well as the genetics of resistance.

Mathematical modeling and epidemiologic analysis.  The other part of our work focuses on mathematical modeling and epidemiologic analysis of infectious diseases.  Central themes of this work include:

  • Pandemic preparedness and response.  With Megan Murray, James Robins and several other collaborators we made one of the earliest estimates of the reproductive number of the SARS virus during the spring of 2003, and later applied the same approaches to estimate the reproductive number of pandemic influenza in fall, 1918, showing it was around 2.  This suggested the possibility of effective control measures, despite the difficulties inherent in controlling an illness in which transmission could precede symptoms.  Working with Richard Hatchett and Carter Mecher, we showed that rapid, early nonpharmaceutical interventions in 1918 were associated with diminished spread of influenza.  Other work has focused on the risk that multiple introductions could compromise attempts to contain a pandemic at the sources, and on the potential for drug resistance following massive antiviral use in a pandemic.  Recent work focuses on how to define optimal targeting of scarce pandemic control measures, including antivirals and vaccines, by taking advantage of the data that may be available early in a pandemic (with Jacco Wallinga) or based on a transmission matrix (with Ed Goldstein, a Senior Research Scientist at CCDD, and Stephen Eubank‘s group at Virginia Tech).
  • Response to the 2009 influenza A/H1N1 pandemic.  With many collaborators, we were heavily involved in analyzing data and providing advice to public health authorities during the 2009 influenza pandemic.  I served as a member of the 2009 H1N1 working group of the President’s Council of Advisors on Science and Technology (PCAST), and a co-author of its August 2009 report.  I also served on “Team B” for the United States CDC, providing external advice during the pandemic.  Early on, we published articles with international collaborators on decision-making under uncertainty during the pandemic and on how to maintain surveillance when cases become uncountable.  With collaborators from the Center for Communicable Disease Dynamics (CCDD), which I direct, we estimated the number of cases in Mexico early on based on travel data, the transmissibility and serial interval of the pandemic strain in the early US epidemic (led by Laura White), and the case-fatality ratio and other measures of severity in the US (with Anne Presanis and others), among other studies.  We also performed an analysis of the benefits of pre-dispensing antiviral drugs that argued for more liberal use of pre-dispensing, a version of which is now in press.  Much of this work was published first on the new PLoS Currents Influenza site.
  • Antimicrobial resistance.  We have worked on a variety of topics related to drug resistance in bacteria and viruses, with Bruce Levin, Carl Bergstrom, Megan Murray, Ted Cohen, and Matthew Samore as recurring collaborators.   Because antimicrobial use affects not only the individual who uses it, but also the pathogen population, much of our effort has been to define the effects of antimicrobial use at the population level, focusing on S. pneumoniae drug resistance, resistance in hospital-acquired infections, among others.  A recurring theme (in general, and in examples such as influenza and tuberculosis) is that optimizing treatment success for the individual host may simultaneously intensify selection for resistance in the population.  We have shown (here and here) why efforts to cycle antibiotics to control resistance are unlikely to be effective.  Ongoing work aims to understand the mechanisms promoting coexistence of drug-sensitive and drug-resistant strains of pneumococci and other bacteria, and, in collaboration with CDC colleagues, to understand the spread of drug resistant gonorrhea.
  • Seasonality.  The seasonality of infectious diseases is one of the oldest observations in medicine, yet the mechanisms underlying seasonality are poorly understood.  Building on data re-analyses by Jeff Shaman, we have been working together with Jeff and other collaborators to test the hypothesis that absolute humidity variation is a key driver of the timing of seasonal and pandemic influenza in temperate regions.  Further work on seasonality of influenza and associated conditions is underway.
  • Development of new methods for infectious disease analysis.  The questions above, and others, have led to the need for new analytic methods to approach infectious disease data.  These have included MCMC methods for assessing serotype replacement vs. unmasking in pneumococci  and for analysis of household data to assess time-varying infectiousness with SARS (with Virginia Pitzer and Gabriel Leung); hidden Markov models for hospital-acquired infections (with Ben Cooper); and an approach to quantify the tradeoffs of sensitivity, specificity and timeliness in epidemic alerts, applied to highland malaria in Ethiopia (with Hailay Teklehaimanot).  Recently with Christophe Fraser and colleagues we defined a class of “neutral null models” to improve the study of multi-strain pathogens.

Other projects include collaboration with the CEPAC group on modeling HIV transmission and interventions, work with Susan Huang and colleagues on MRSA transmission, and efforts to improve the interpretation of surveillance data to track emerging diseases.


B.A., 1991, Philosophy, Yale University
D.Phil., 1995, Zoology, University of Oxford

Photo Credit: Stephanie Mitchell/Harvard University News Office