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Maciej F Boni

Maciej F Boni

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Associate Professor of Biology

Millennium Science Complex W-252
University Park, PA 16802
Phone: (814) 867-4651


  1. Ph.D., Stanford University, 2006
  2. M.S., Stanford University, 2004
  3. A.B., Princeton University, 1999

Postdoc Training

  1. 2008-2011 University of Oxford and Oxford University Clinical Research Unit (Ho Chi Minh City, Vietnam)
  2. 2007-2008 Resources for the Future (Washington DC) and Princeton University

Honors and Awards

  1. Wellcome Trust Sir Henry Dale Fellowship, 2012
  2. British Medical Association H.C. Roscoe Award, 2011

Research Interests

Epidemiology of influenza in the tropics.  Tropical disease epidemiology.  Treatment strategies and antimalarial drug resistance.  mHealth and participatory epidemiology.  Theory of infectious disease dynamics.  Pathogen evolution, population genetics, phylogenetics, recombination.

From 2008 to 2016, I ran a research group in Ho Chi Minh City, Vietnam, focused on influenza epidemiology in the tropics and treatment strategies to delay or slow antimalarial drug resistance.  My PhD students and other team members have been mathematical modelers, bioinformaticians, field site coordinators, and laboratory research assistants.  

We have been running a large seroepidemiology study in southern Vietnam, aimed at reconstructing the disease dynamics of influenza virus including both symptomatic and asymptomatic influenza.  This work has expanded to dengue virus, and we are also using the project to look at incidence of a number of other diseases, most recently Tetanus and Hepatitis B and E.

Since 2009, we have been running a community-based mHealth study on influenza-like illness (ILI) in Ho Chi Minh City.  The study has collected over 40,000 data points and is currently used as a real-time epidemiology tool for Ho Chi Minh City.  You can read about the study here .

Our malaria work is focused on designing and calibrating individual-based microsimulations.  The microsimulations are used to compare different long-term drug distribution strategies to see which ones are most effective at delaying drug resistance.  You can read about the most recent modeling results here and here.  Our next goal is to perform health-economic analyses to determine if deploying multiple first-line therapies is an economically feasible strategy.


Selected Publications


Improved algorithmic complexity for the 3SEQ recombination detection algorithm.
Lam HM, Ratmann O, Boni MF.
Mol Biol Evol, advance access, 2017.   open-access link

Structure of general-population antibody titer distributions to influenza A virus.

Nhat NTD, Todd S, de Bruin E, Thao TTN, Vy NHT, Quan TM, Vinh DN, van Beek J, Anh PH, Lam HM, Hung NT, Thanh NTL, Huy HLH, Dong N, Baker S, Thwaites GE, Lien NTN, Hong TTK, Farrar J, Simmons CP, Chau NVV, Koopmans M, Boni MF.
Nat Sci Rep, 7:6060, 2017.      open-access link 

The community as the patient in malaria-endemic areas: preempting drug resistance with multiple first-line therapies.
Boni MF, White NJ, Baird JK.
PLoS Med, 13(3):e1001984, 2016.      pdf 

Optimum population-level use of artemisinin combination therapies: a modelling study.
Nguyen TD, Olliaro P, Dondorp A, Baird JK, Lam HM, Farrar J, Thwaites GE, White NJ, Boni MF.
Lancet Global Health, 3(12):e758-e766, 2015.      pdf       supp       podcast 

Statistical identifiability and sample size calculations for serial seroepidemiology.
Vinh DN, Boni MF.
Epidemics, 12:30-39, 2015.      pdf       supp 

Measuring the impact of artemisinin-based case management on malaria incidence in southern Vietnam, 1991-2010.
Peak C, Thuan PD, Britton A, Nguyen TD, Wolbers M, Thanh NV, Buckee CO, Boni MF.
Am J Trop Med Hyg, 92(4):811-817, 2015.      pdf+supp