Joel C Miller

Summary

Publications

  1. pmc Spread of infectious disease through clustered populations
    Joel C Miller
    University of British Columbia Centre for Disease Control, Vancouver, British Columbia, V5Z 4R4, Canada
    J R Soc Interface 6:1121-34. 2009
  2. ncbi request reprint Percolation and epidemics in random clustered networks
    Joel C Miller
    Harvard School of Public Health, Boston, Massachusetts 02115, USA
    Phys Rev E Stat Nonlin Soft Matter Phys 80:020901. 2009
  3. pmc Student behavior during a school closure caused by pandemic influenza A/H1N1
    Joel C Miller
    Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America
    PLoS ONE 5:e10425. 2010
  4. pmc Model hierarchies in edge-based compartmental modeling for infectious disease spread
    Joel C Miller
    Departments of Mathematics and Biology, Penn State University, University Park, USA
    J Math Biol 67:869-99. 2013
  5. pmc A note on the derivation of epidemic final sizes
    Joel C Miller
    Depts of Mathematics and Biology, The Pennsylvania State University, University Park, PA 16802, USA
    Bull Math Biol 74:2125-41. 2012
  6. pmc Edge-based compartmental modelling for infectious disease spread
    Joel C Miller
    Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA
    J R Soc Interface 9:890-906. 2012
  7. doi request reprint A note on a paper by Erik Volz: SIR dynamics in random networks
    Joel C Miller
    Harvard School of Public Health, Boston, MA 02215, USA
    J Math Biol 62:349-58. 2011
  8. doi request reprint Epidemics with general generation interval distributions
    Joel C Miller
    Fogarty International Center, National Institutes of Health, Bethesda, MD, USA
    J Theor Biol 262:107-15. 2010
  9. pmc Use of cumulative incidence of novel influenza A/H1N1 in foreign travelers to estimate lower bounds on cumulative incidence in Mexico
    Marc Lipsitch
    Department of Immunology and Infectious Diseases, Harvard School of Public Health, Boston, Massachusetts, United States of America
    PLoS ONE 4:e6895. 2009
  10. pmc Pre-dispensing of antivirals to high-risk individuals in an influenza pandemic
    Edward Goldstein
    Center for Communicable Disease Dynamics, Harvard School of Public Health, Boston, MA, USA
    Influenza Other Respir Viruses 4:101-12. 2010

Detail Information

Publications15

  1. pmc Spread of infectious disease through clustered populations
    Joel C Miller
    University of British Columbia Centre for Disease Control, Vancouver, British Columbia, V5Z 4R4, Canada
    J R Soc Interface 6:1121-34. 2009
    ..Our most significant contribution is a systematic way to address clustering in infectious disease models, and our results have a number of implications for the design of interventions...
  2. ncbi request reprint Percolation and epidemics in random clustered networks
    Joel C Miller
    Harvard School of Public Health, Boston, Massachusetts 02115, USA
    Phys Rev E Stat Nonlin Soft Matter Phys 80:020901. 2009
    ..Percolation in the clustered networks reduces the component sizes and increases the epidemic threshold compared to the unclustered networks...
  3. pmc Student behavior during a school closure caused by pandemic influenza A/H1N1
    Joel C Miller
    Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America
    PLoS ONE 5:e10425. 2010
    ..The effectiveness of closing schools to reduce transmission depends largely on student/family behavior during the closure. We sought to improve our understanding of these behaviors...
  4. pmc Model hierarchies in edge-based compartmental modeling for infectious disease spread
    Joel C Miller
    Departments of Mathematics and Biology, Penn State University, University Park, USA
    J Math Biol 67:869-99. 2013
    ..Our result about the convergence of models to the mass action model gives clear, rigorous conditions under which the mass action model is accurate. ..
  5. pmc A note on the derivation of epidemic final sizes
    Joel C Miller
    Depts of Mathematics and Biology, The Pennsylvania State University, University Park, PA 16802, USA
    Bull Math Biol 74:2125-41. 2012
    ..Thus, the use of integro-differential equations to find a final size relation is unnecessary and a simpler, more general method can be applied...
  6. pmc Edge-based compartmental modelling for infectious disease spread
    Joel C Miller
    Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA
    J R Soc Interface 9:890-906. 2012
    ..We introduce a graphical interpretation allowing for easy derivation and communication of the model and focus on applying the technique under different assumptions about how contact rates are distributed and how long partnerships last...
  7. doi request reprint A note on a paper by Erik Volz: SIR dynamics in random networks
    Joel C Miller
    Harvard School of Public Health, Boston, MA 02215, USA
    J Math Biol 62:349-58. 2011
    ..Under appropriate assumptions these equations reduce to the standard SIR equations, and we are able to estimate the magnitude of the error introduced by assuming the SIR equations...
  8. doi request reprint Epidemics with general generation interval distributions
    Joel C Miller
    Fogarty International Center, National Institutes of Health, Bethesda, MD, USA
    J Theor Biol 262:107-15. 2010
    ..We introduce a "memoryless" ODE system which approximates the true solutions. Finally, we analyze the transition from the stochastic to the deterministic phase...
  9. pmc Use of cumulative incidence of novel influenza A/H1N1 in foreign travelers to estimate lower bounds on cumulative incidence in Mexico
    Marc Lipsitch
    Department of Immunology and Infectious Diseases, Harvard School of Public Health, Boston, Massachusetts, United States of America
    PLoS ONE 4:e6895. 2009
    ..Accordingly, the total number of cases will be underestimated and disease severity overestimated. This problem is manifest in the current epidemic of novel influenza A/H1N1...
  10. pmc Pre-dispensing of antivirals to high-risk individuals in an influenza pandemic
    Edward Goldstein
    Center for Communicable Disease Dynamics, Harvard School of Public Health, Boston, MA, USA
    Influenza Other Respir Viruses 4:101-12. 2010
    ....
  11. pmc Effects of heterogeneous and clustered contact patterns on infectious disease dynamics
    Erik M Volz
    Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States of America
    PLoS Comput Biol 7:e1002042. 2011
    ....
  12. pmc Predicting the epidemic sizes of influenza A/H1N1, A/H3N2, and B: a statistical method
    Edward Goldstein
    Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America
    PLoS Med 8:e1001051. 2011
    ..We use publicly available US Centers for Disease Control (CDC) influenza surveillance data between 1997 and 2009 to study the temporal dynamics of influenza over this period...
  13. pmc Oseltamivir for treatment and prevention of pandemic influenza A/H1N1 virus infection in households, Milwaukee, 2009
    Edward Goldstein
    Department of Epidemiology, Center for Communicable Disease Dynamics, Harvard School of Public Health, Boston, MA, USA
    BMC Infect Dis 10:211. 2010
    ....
  14. pmc Cholera modeling: challenges to quantitative analysis and predicting the impact of interventions
    Yonatan H Grad
    Division of Infectious Diseases, Brigham and Women s Hospital, Boston, MA, USA
    Epidemiology 23:523-30. 2012
    ..We specify sensitivity analyses that would be necessary to improve confidence in model-based quantitative prediction, and suggest types of monitoring in future epidemic settings that would improve analysis and prediction...
  15. pmc Incorporating disease and population structure into models of SIR disease in contact networks
    Joel C Miller
    Departments of Mathematics and Biology, Penn State University, University Park, Pennsylvania, United States of America
    PLoS ONE 8:e69162. 2013
    ..Our goal is twofold: to provide a number of examples generalizing the EBCM method for various different population or disease structures and to provide insight into how to derive such a model under new sets of assumptions...