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Wilbert Van Panhuis, MD PhD

Assistant Professor, Epidemiology

Assistant Professor, Biomedical Informatics

Affiliated Faculty, Public Health Dynamics Lab

Contact

715 Parran Hall
R-znvy: jni65@cvgg.rqh
Primary Phone: 967-179-2148
Web site:


Personal Statement

I am an infectious disease epidemiologist with training in Medicine (Amsterdam) and Global Disease Epidemiology (Johns Hopkins). My research in the fields of computational epidemiology and population health informatics aims to improve the efficient use of information for public health action. In particular, I use large-scale public health data to study the spatial spread of infectious diseases, using statistical and agent-based simulation models. Currently, my main focus is on vector borne diseases (dengue and Chikungunya) in Latin America and Southeast Asia, and on vaccine preventable diseases in the US and EU (NEJM, PNAS, NIH Director's Blog). I am the lead scientist of Project Tycho that provides open access to integrated global disease data (NEJM, New York Times, Wall Street Journal). In addition, I am funded by the US NIH Big Data to Knowledge (BD2K) program to use Big Data approaches to improve access and integration of public health data for research and policy. I am also co-PI of the NIH funded Models of Infectious Disease Agents Study (MIDAS), a co-investigator of the Bill & Melinda Gates Foundation Vaccine Modeling Initiative (VMI), and I coordinate an outreach program on data and computational epidemiology funded by the Benter Foundation in Pittsburgh and various industry sponsors.

 

I lecture on infectious disease epidemiology, global health, and teach a graduate class in vaccine epidemiology. I am also involved in developing a Data Science curriculum at the at the University of Pittsburgh Graduate School of Public Health.


Education

2004 | Free University Medical Center, Amsterdam, Netherlands| MD
2009 | Johns Hopkins Bloomberg School of Public Health, Baltimore, MD | PhD
2010 | Phi Beta Kappa


Teaching

I lecture on the use of data in public health, in particular for vector-borne and vaccine preventable diseases. A few examples of invited lectures are listed below:


“Integrating data for science and decision making”. Global Health Equity Lecture, University of Pittsburgh School of Medicine, Nov 2014

 

“Data needs for dengue epidemic prediction”. Office of Science Technology Policy, Washington DC, Sep 2014

 

“Open access to newly digitized US weekly Notifiable Disease Surveillance data 1888-Present”, International Society of Disease Surveillance, Webinar, Apr 2014

 

“Contagious diseases in the United States from 1888 to the present”, Infectious Diseases Grand Rounds, Pittsburgh PA, Apr 2014

 

“Data Sharing in Disease Surveillance”, Chatham House London, Feb 2014

 

“Barriers to Public Health Data Sharing”, Bill & Melinda Gates Foundation  Conference on modeling, Seattle WA, Jul 2013

 

“Open access to a century of infectious disease surveillance in the United States”, University of Pittsburgh Senior Vice Chancellor’s Lecture Series, Apr 2013


Currently Funded Projects

2015-Present: NIH Big Data to Knowledge Career Development Award (PI). Data integration for global population health through dynamic models. Standardizing and integrating heterogeneous public health data through epidemic simulators.

 

2014-Present: Models of Infectious Disease Agent Study National Center of Excellence (co-PI). Study of surveillance data systems and decision making for disease control through computer modeling and simulation.

2014-Present: Public Health Dynamics Laboratory International Fellows Program (co-investigator). Building partnerships with academic institutions and health agencies in low- and middle income countries to advance the use of public health data for modeling and decision making.

 

2009 – Present: Bill & Melinda Gates Foundation Vaccine Modeling Initiative (co-investigator). Using disease data and computational modeling to study the public health impact of vaccination strategies.


Selected Publications

Region-wide synchrony and traveling waves of dengue across eight countries in Southeast Asia.van Panhuis WG, Choisy M, Xiong X, Chok NS, Akarasewi P, Iamsirithaworn S, Lam SK, Chong CK, Lam FC, Phommasak B, Vongphrachanh P, Bouaphanh K, Rekol H, Hien NT, Thai PQ, Duong TN, Chuang JH, Liu YL, Ng LC, Shi Y, Tayag EA, Roque VG Jr, Lee Suy LL, Jarman RG, Gibbons RV, Velasco JM, Yoon IK, Burke DS, Cummings DA. Proc Natl Acad Sci U S A. 2015 Oct 20;112(42):13069-74.

The availability and consistency of dengue surveillance data provided online by the World Health Organization.Ruberto I, Marques E, Burke DS, Van Panhuis WG. PLoS Negl Trop Dis. 2015 Apr 14;9(4):e0003511.


A systematic review of barriers to data sharing in public health.van Panhuis WG, Paul P, Emerson C, Grefenstette J, Wilder R, Herbst AJ, Heymann D, Burke DS. BMC Public Health. 2014 Nov 5;14:1144

Willem G. van Panhuis, John Grefenstette, Su Yon Jung, Nian Shong Chok, Anne Cross, Heather Eng, Bruce Y Lee, Vladimir Zadorozhny, Shawn Brown, Derek Cummings, Donald S. Burke. Contagious diseases in the United States from 1888 to the present. NEJM 2013:369(22):2152-2158.

Willem G. van Panhuis, Sangwon Hyun, Kayleigh Blaney, Ernesto T.A. Marques Jr, Giovanini E. Coelho, João Bosco Siqueira Jr., Ryan Tibshirani, Ph.D, Jarbas B. da Silva Jr., Roni Rosenfeld. Risk of dengue for tourists and teams during the World Cup 2014 in Brazil. PLOS NTD 2014;8(7): e3063.

Yasuko Matsubara, Yasushi, Sakurai, Willem G. van Panhuis, Christos Faloutsos. FUNNEL: Automatic Mining of Spatially Coevolving Epidemics. Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining, August 24–27, 2014, New York, NY, USA: 105-114.

Van Panhuis WG, Luxemburger C, Pengsaa K, Limkittikul K, Sabchareon A, Lang J, Durbin AP, Cummings DA. Decay and persistence of maternal dengue antibodies among infants in Bangkok. Am J Trop Med Hyg. 2011 Aug;85(2):355-62

Van Panhuis WG, Gibbons RV, Endy TP, Rothman AL, Srikiatkhachorn A, Nisalak A, Burke DS, Cummings DA. Inferring the serotype associated with dengue virus infections on the basis of pre- and postinfection neutralizing antibody titers. J Infect Dis. 2010 Oct 1;202(7):1002-10.

Wilbert  Van Panhuis
© 2017 by University of Pittsburgh Graduate School of Public Health

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