William D. Wheaton
RTI International
Network
Latest external collaboration on country level. Dive into details by clicking on the dots.
Publication
Featured researches published by William D. Wheaton.
Proceedings of the National Academy of Sciences of the United States of America | 2010
Stephen B. Beres; Ronan K. Carroll; Patrick R. Shea; Izabela Sitkiewicz; Juan Carlos Martinez-Gutierrez; Donald E. Low; Allison McGeer; Barbara M. Willey; Karen Green; Gregory J. Tyrrell; Thomas Goldman; Michael Feldgarden; Bruce W. Birren; Yuriy Fofanov; John Boos; William D. Wheaton; Christiane Honisch; James M. Musser
Understanding the fine-structure molecular architecture of bacterial epidemics has been a long-sought goal of infectious disease research. We used short-read-length DNA sequencing coupled with mass spectroscopy analysis of SNPs to study the molecular pathogenomics of three successive epidemics of invasive infections involving 344 serotype M3 group A Streptococcus in Ontario, Canada. Sequencing the genome of 95 strains from the three epidemics, coupled with analysis of 280 biallelic SNPs in all 344 strains, revealed an unexpectedly complex population structure composed of a dynamic mixture of distinct clonally related complexes. We discovered that each epidemic is dominated by micro- and macrobursts of multiple emergent clones, some with distinct strain genotype–patient phenotype relationships. On average, strains were differentiated from one another by only 49 SNPs and 11 insertion-deletion events (indels) in the core genome. Ten percent of SNPs are strain specific; that is, each strain has a unique genome sequence. We identified nonrandom temporal–spatial patterns of strain distribution within and between the epidemic peaks. The extensive full-genome data permitted us to identify genes with significantly increased rates of nonsynonymous (amino acid-altering) nucleotide polymorphisms, thereby providing clues about selective forces operative in the host. Comparative expression microarray analysis revealed that closely related strains differentiated by seemingly modest genetic changes can have significantly divergent transcriptomes. We conclude that enhanced understanding of bacterial epidemics requires a deep-sequencing, geographically centric, comparative pathogenomics strategy.
Journal of Public Health Management and Practice | 2010
Bruce Y. Lee; Shawn T. Brown; Philip C. Cooley; Maggie A. Potter; William D. Wheaton; Ronald E. Voorhees; Samuel Stebbins; John J. Grefenstette; Shanta M. Zimmer; Richard K. Zimmerman; Tina Marie Assi; Rachel R. Bailey; Diane K. Wagener; Donald S. Burke
BACKGROUND There remains substantial debate over the impact of school closure as a mitigation strategy during an influenza pandemic. The ongoing 2009 H1N1 influenza pandemic has provided an unparalleled opportunity to test interventions with the most up-to-date simulations. METHODS To assist the Allegheny County Health Department during the 2009 H1N1 influenza pandemic, the University of Pittsburgh Models of Infectious Disease Agents Study group employed an agent-based computer simulation model (ABM) of Allegheny County, Pennsylvania, to explore the effects of various school closure strategies on mitigating influenza epidemics of different reproductive rates (R0). RESULTS Entire school system closures were not more effective than individual school closures. Any type of school closure may need to be maintained throughout most of the epidemic (ie, at least 8 weeks) to have any significant effect on the overall serologic attack rate. In fact, relatively short school closures (ie, 2 weeks or less) may actually slightly increase the overall attack rate by returning susceptible students back into schools in the middle of the epidemic. Varying the illness threshold at which school closures are triggered did not seem to have substantial impact on the effectiveness of school closures, suggesting that short delays in closing schools should not cause concern. CONCLUSIONS School closures alone may not be able to quell an epidemic but, when maintained for at least 8 weeks, could delay the epidemic peak for up to a week, providing additional time to implement a second more effective intervention such as vaccination.
Vaccine | 2010
Bruce Y. Lee; Shawn T. Brown; George W. Korch; Philip C. Cooley; Richard K. Zimmerman; William D. Wheaton; Shanta M. Zimmer; John J. Grefenstette; Rachel R. Bailey; Tina Marie Assi; Donald S. Burke
In the fall 2009, the University of Pittsburgh Models of Infectious Disease Agent Study (MIDAS) team employed an agent-based computer simulation model (ABM) of the greater Washington, DC, metropolitan region to assist the Office of the Assistant Secretary of Public Preparedness and Response, Department of Health and Human Services, to address several key questions regarding vaccine allocation during the 2009 H1N1 influenza pandemic, including comparing a vaccinating children (i.e., highest transmitters)-first policy versus the Advisory Committee on Immunization Practices (ACIP)-recommended vaccinating at-risk individuals-first policy. Our study supported adherence to the ACIP (instead of a children-first policy) prioritization recommendations for the H1N1 influenza vaccine when vaccine is in limited supply and that within the ACIP groups, children should receive highest priority.
BMC Public Health | 2011
Shawn T. Brown; Julie H.Y. Tai; Rachel R. Bailey; Philip C. Cooley; William D. Wheaton; Margaret A. Potter; Ronald E. Voorhees; Megan LeJeune; John J. Grefenstette; Donald S. Burke; Sarah M. McGlone; Bruce Y. Lee
BackgroundDuring the 2009 H1N1 influenza epidemic, policy makers debated over whether, when, and how long to close schools. While closing schools could have reduced influenza transmission thereby preventing cases, deaths, and health care costs, it may also have incurred substantial costs from increased childcare needs and lost productivity by teachers and other school employees.MethodsA combination of agent-based and Monte Carlo economic simulation modeling was used to determine the cost-benefit of closing schools (vs. not closing schools) for different durations (range: 1 to 8 weeks) and symptomatic case incidence triggers (range: 1 to 30) for the state of Pennsylvania during the 2009 H1N1 epidemic. Different scenarios varied the basic reproductive rate (R0) from 1.2, 1.6, to 2.0 and used case-hospitalization and case-fatality rates from the 2009 epidemic. Additional analyses determined the cost per influenza case averted of implementing school closure.ResultsFor all scenarios explored, closing schools resulted in substantially higher net costs than not closing schools. For R0 = 1.2, 1.6, and 2.0 epidemics, closing schools for 8 weeks would have resulted in median net costs of
BMC Public Health | 2013
John J. Grefenstette; Shawn T. Brown; Roni Rosenfeld; Jay V. DePasse; Nathan Stone; Phillip Cooley; William D. Wheaton; Alona Fyshe; David Galloway; Anuroop Sriram; Hasan Guclu; Thomas Abraham; Donald S. Burke
21.0 billion (95% Range:
Natural Product Research | 2007
Feras Q. Alali; Khaled Tawaha; Tamam El-Elimat; Maha Syouf; Mosa El-Fayad; Khaled Abulaila; Samara Joy Nielsen; William D. Wheaton; Joseph O. Falkinham; Nicholas H. Oberlies
8.0 -
Influenza and Other Respiratory Viruses | 2010
Philip C. Cooley; Bruce Y. Lee; Shawn T. Brown; James Cajka; Bernadette Chasteen; Laxminarayana Ganapathi; James H. Stark; William D. Wheaton; Diane K. Wagener; Donald S. Burke
45.3 billion). The median cost per influenza case averted would have been
Health Affairs | 2011
Bruce Y. Lee; Shawn T. Brown; Rachel R. Bailey; Richard K. Zimmerman; Margaret A. Potter; Sarah M. McGlone; Philip C. Cooley; John J. Grefenstette; Shanta M. Zimmer; William D. Wheaton; Sandra Crouse Quinn; Ronald E. Voorhees; Donald S. Burke
14,185 (
Journal of Urban Health-bulletin of The New York Academy of Medicine | 2011
Philip C. Cooley; Shawn T. Brown; James Cajka; Bernadette M. Chasteen; Laxminarayana Ganapathi; John J. Grefenstette; Craig R. Hollingsworth; Bruce Y. Lee; Burton Levine; William D. Wheaton; Diane K. Wagener
5,423 -
Mathematical and Computer Modelling | 2008
Philip C. Cooley; Laxminarayana Ganapathi; George S. Ghneim; Scott D. Holmberg; William D. Wheaton; Craig R. Hollingsworth
30,565) for R0 = 1.2,