Marc Lipsitch studies 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. For some of the work, particularly the work on Streptococcus pneumoniae, the practical and the population-biological questions, as well as the experimental and quantitative approaches, are closely intertwined.
Streptococcus pneumoniae: immune responses and population biology. Much of the effort of the Lipsitch laboratory 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, we are studying 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. An ongoing collaboration with 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. 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 half 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. Ongoing work focuses on an effort 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.
- 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.
- 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. Ongoing work is focused on methods for analyzing data that emerges during an epidemic of a new disease.
Other areas of ongoing interest include infectious disease seasonality, its causes and consequences; the role of host genetics in controlling infectious diseases, and development of methods for detecting selection in samples from multiple pathogen populations.