FRED (A Framework for Reconstructing Epidemic Dynamics): an open-source software system for modeling infectious diseases and control strategies using census-based populations

BMC Public Health

Donald S Burke²  Thomas Abraham¹  Hasan Guclu²  Anuroop Sriram¹  David D Galloway²  Alona Fyshe¹  William D Wheaton³  Phillip C Cooley³  Nathan TB Stone⁴  Jay DePasse⁴  Roni Rosenfeld¹  Shawn T Brown⁴  John J Grefenstette² 

[1] School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA;Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA;RTI International, Research Triangle Park, Durham, North Carolina, USA;Pittsburgh Supercomputing Center, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA

关键词: Influenza modeling;    Synthetic population;    Agent-based model;    Simulator;    Pandemic influenza;   

Others  :  1161682
DOI  :  10.1186/1471-2458-13-940

 received in 2013-06-11, accepted in 2013-09-25,  发布年份 2013

【 摘 要 】

Background

Mathematical and computational models provide valuable tools that help public health planners to evaluate competing health interventions, especially for novel circumstances that cannot be examined through observational or controlled studies, such as pandemic influenza. The spread of diseases like influenza depends on the mixing patterns within the population, and these mixing patterns depend in part on local factors including the spatial distribution and age structure of the population, the distribution of size and composition of households, employment status and commuting patterns of adults, and the size and age structure of schools. Finally, public health planners must take into account the health behavior patterns of the population, patterns that often vary according to socioeconomic factors such as race, household income, and education levels.

Results

FRED (a Framework for Reconstructing Epidemic Dynamics) is a freely available open-source agent-based modeling system based closely on models used in previously published studies of pandemic influenza. This version of FRED uses open-access census-based synthetic populations that capture the demographic and geographic heterogeneities of the population, including realistic household, school, and workplace social networks. FRED epidemic models are currently available for every state and county in the United States, and for selected international locations.

Conclusions

State and county public health planners can use FRED to explore the effects of possible influenza epidemics in specific geographic regions of interest and to help evaluate the effect of interventions such as vaccination programs and school closure policies. FRED is available under a free open source license in order to contribute to the development of better modeling tools and to encourage open discussion of modeling tools being used to evaluate public health policies. We also welcome participation by other researchers in the further development of FRED.

【 授权许可】

   
2013 Grefenstette et al.; licensee BioMed Central Ltd.

【 图 表 】

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【 参考文献 】

• [1]Eubank S, Guclu H, Kumar VS, Marathe MV, Srinivasan A, Toroczkai Z, Wang N: Modelling disease outbreaks in realistic urban social networks. Nature 2004, 429(6988):180-184.
• [2]Ferguson NM, Cummings DA, Cauchemez S, Fraser C, Riley S, Meeyai A, Iamsirithaworn S, Burke DS: Strategies for containing an emerging influenza pandemic in Southeast Asia. Nature 2005, 437(7056):209-214.
• [3]Ferguson NM, Cummings DA, Fraser C, Cajka JC, Cooley PC, Burke DS: Strategies for mitigating an influenza pandemic. Nature 2006, 442(7101):448-452.
• [4]Halloran ME, Ferguson NM, Eubank S, Longini IM Jr, Cummings DA, Lewis B, Xu S, Fraser C, Vullikanti A, Germann TC, Wagener D, Beckman R, Kadau K, Barrett C, Macken CA, Burke DS, Cooley P: Modeling targeted layered containment of an influenza pandemic in the United States. Proc Natl Acad Sci U S A 2008, 105(12):4639-4644.
• [5]Lee BY, Brown ST, Cooley P, Grefenstette JJ, Zimmerman RK, Zimmer SM, Potter MA, Rosenfeld R, Wheaton WD, Wiringa AE, Bacon KM, Burke DS: Vaccination deep into a pandemic wave potential mechanisms for a “third wave” and the impact of vaccination. Am J Prev Med 2010, 39(5):e21-e29.
• [6]Lee BY, Brown ST, Cooley P, Potter MA, Wheaton WD, Voorhees RE, Stebbins S, Grefenstette JJ, Zimmer SM, Zimmerman RK, Assi TM, Bailey RR, Wagener DK, Burke DS: Simulating school closure strategies to mitigate an influenza epidemic. J Public Health Manag Pract 2010, 16(3):252-261.
• [7]Lee BY, Brown ST, Cooley PC, Zimmerman RK, Wheaton WD, Zimmer SM, Grefenstette JJ, Assi TM, Furphy TJ, Wagener DK, Burke DS: A computer simulation of employee vaccination to mitigate an influenza epidemic. Am J Prev Med 2010, 38(3):247-257.
• [8]Lee BY, Brown ST, Korch GW, Cooley PC, Zimmerman RK, Wheaton WD, Zimmer SM, Grefenstette JJ, Bailey RR, Assi TM, Burke DS: A computer simulation of vaccine prioritization, allocation, and rationing during the 2009 H1N1 influenza pandemic. Vaccine 2010, 28(31):4875-4879.
• [9]Lee BY, Brown ST, Bailey RR, Zimmerman RK, Potter MA, McGlone SM, Cooley PC, Grefenstette JJ, Zimmer SM, Wheaton WD, Quinn SC, Voorhees RE, Burke DS: The benefits to all of ensuring equal and timely access to influenza vaccines in poor communities. Health affairs 2011, 30(6):1141-1150.
• [10]Brown ST, Tai JH, Bailey RR, Cooley PC, Wheaton WD, Potter MA, Voorhees RE, LeJeune M, Grefenstette JJ, Burke DS, McGlone SM, Lee BY: Would school closure for the 2009 H1N1 influenza epidemic have been worth the cost?: a computational simulation of Pennsylvania. BMC Public Health 2011, 11:353. BioMed Central Full Text
• [11]Cooley P, Lee BY, Brown S, Cajka J, Chasteen B, Ganapathi L, Stark JH, Wheaton WD, Wagener DK, Burke DS: Protecting health care workers: a pandemic simulation based on Allegheny county. Influenza Other Respi Viruses 2010, 4(2):61-72.
• [12]Cooley P, Brown S, Cajka J, Chasteen B, Ganapathi L, Grefenstette J, Hollingsworth CR, Lee BY, Levine B, Wheaton WD, Wagener DK: The role of subway travel in an influenza epidemic: a New York City simulation. J Urban Health 2011, 88(5):982-995.
• [13]Burke DS, Epstein JM, Cummings DA, Parker JI, Cline KC, Singa RM, Chakravarty S: Individual-based computational modeling of smallpox epidemic control strategies. Acad Emerg Med 2006, 13(11):1142-1149.
• [14]Longini IM Jr, Halloran ME, Nizam A, Yang Y, Xu S, Burke DS, Cummings DA, Epstein JM: Containing a large bioterrorist smallpox attack: a computer simulation approach. Int J Infect Dis 2007, 11(2):98-108.
• [15]Burke DS, Grefenstette JJ: Towards an integrated meta-model of public health dynamics for preparedness decision support. J Public Health Manag Pract 2013, 19(Suppl 2):S12-5.
• [16]Keeling M, Rohani P: Modeling Infectious Diseases in Humans and Animals. Princeton: Princeton University Press; 2007.
• [17]Merler S, Ajelli M, Pugliese A, Ferguson NM: Determinants of the spatiotemporal dynamics of the 2009 H1N1 pandemic in Europe: implications for real-time modelling. PLoS Comput Biol 2011, 7(9):e1002205.
• [18]Suryaprasad A, Redd JT, Hancock K, Branch A, Steward-Clark E, Katz JM, Fry AM, Cheek JE: Severe acute respiratory infections caused by 2009 pandemic influenza A (H1N1) among American Indians-southwestern United States, May 1-July 21, 2009. Influenza Other Respi Viruses 2013. 10.1111/irv.12123. [Epub ahead of print]
• [19]Yu H, Feng L, Viboud CG, Shay DK, Jiang Y, Zhou H, Zhou M, Xu Z, Hu N, Yang W, Nie S: Regional variation in mortality impact of the 2009 A(H1N1) influenza pandemic in China. Influenza Other Respi Viruses 2013. 10.1111/irv.12121. [Epub ahead of print]
• [20]Stark JH, Sharma R, Ostroff S, Cummings DA, Ermentrout B, Stebbins S, Burke DS, Wisniewski SR: Local spatial and temporal processes of influenza in Pennsylvania, USA: 2003–2009. PloS one 2012, 7(3):e34245.
• [21]Cauchemez S, Donnelly CA, Reed C, Ghani AC, Fraser C, Kent CK, Finelli L, Ferguson NM: Household transmission of 2009 pandemic influenza A (H1N1) virus in the United States. N Engl J Med 2009, 361(27):2619-2627.
• [22]Cauchemez S, Valleron AJ, Boelle PY, Flahault A, Ferguson NM: Estimating the impact of school closure on influenza transmission from Sentinel data. Nature 2008, 452(7188):750-754.
• [23]Chao DL, Halloran ME, Longini IM Jr: School opening dates predict pandemic influenza A(H1N1) outbreaks in the United States. J Infect Dis 2010, 202(6):877-880.
• [24]Araz OM, Damien P, Paltiel DA, Burke S, van de Geijn B, Galvani A, Meyers LA: Simulating school closure policies for cost effective pandemic decision making. BMC public health 2012, 12:449. BioMed Central Full Text
• [25]Zimmerman RK, Lauderdale DS, Tan SM, Wagener DK: Prevalence of high-risk indications for influenza vaccine varies by age, race, and income. Vaccine 2010, 28(39):6470-6477.
• [26]Davila-Payan C, Swann J, Wortley PM: System factors to explain H1N1 state vaccination rates for adults in US emergency response to pandemic. Vaccine 2013. S0264-410X(13)00684-1. doi: 10.1016/j.vaccine.2013.05.069. [Epub ahead of print]
• [27]Kumar S, Grefenstette JJ, Galloway D, Albert SM, Burke DS: Policies to reduce influenza in the workplace: impact assessments using an agent-based model. Am J Public Health 2013, 103(8):1406-1411.
• [28]Stark JH, Cummings DA, Ermentrout B, Ostroff S, Sharma R, Stebbins S, Burke DS, Wisniewski SR: Local variations in spatial synchrony of influenza epidemics. PloS one 2012, 7(8):e43528.
• [29]Shim E, Grefenstette JJ, Albert SM, Cakouros BE, Burke DS: A game dynamic model for vaccine skeptics and vaccine believers: measles as an example. J Theor Biol 2012, 295:194-203.
• [30]Stebbins S, Cummings DA, Stark JH, Vukotich C, Mitruka K, Thompson W, Rinaldo C, Roth L, Wagner M, Wisniewski SR, Dato V, Eng H, Burke DS: Reduction in the incidence of influenza A but not influenza B associated with use of hand sanitizer and cough hygiene in schools: a randomized controlled trial. Pediatr Infect Dis J 2011, 30(11):921-926.
• [31]Wheaton WD: 2005–2009 U.S. Synthetic Population Ver. 2. RTI International; 2012. http://www.epimodels.org/midas/Rpubsyntdata1.do webcite
• [32]Wheaton WD: U.S. Synthetic Population Database 2005–2009: Quick Start Guide. RTI International; 2012. http://portaldev.rti.org/10_Midas_Docs/SynthPop/2005-2009_synth_pop_ver2_quickstart.pdf webcite
• [33]Beckman RJ, Baggerly KA, McKay MD: Creating synthetic baseline populations. Transp Res A Policy Pract 1996, 30(6):415-429.
• [34]Wheaton WD, Cajka JC, Chasteen BM, Wagener DK, Cooley PC, Ganapathi L, Roberts DJ, Allpress JL: Synthesized population databases: A US geospatial database for agent-based models. RTI Press; 2009. [Research Triangle Park, NC] http://www.rti.org/pubs/mr-0010-0905-wheaton.pdf webcite
• [35]Cajka JC, Cooley PC, Wheaton WD: Attribute Assignment to a Synthetic Population in Support of Agent-Based Disease Modeling. Methods Rep 2010, 19(1009):1-14. RTI
• [36]Durham DP, Casman EA, Albert SM: Deriving behavior model parameters from survey data: self-protective behavior adoption during the 2009–2010 influenza A(H1N1) pandemic. Risk Anal 2012, 32(12):2020-2031.
• [37]Durham DP, Casman EA: Incorporating individual health-protective decisions into disease transmission models: a mathematical framework. J R Soc Interface 2012, 9(68):562-570.
• [38]U.S. Bureau: of Labor Statistics: Employee Benefits in the United States – March 2010.
• [39]Palmer LA, Rousculp MD, Johnston SS, Mahadevia PJ, Nichol KL: Effect of influenza-like illness and other wintertime respiratory illnesses on worker productivity: the child and household influenza-illness and employee function (CHIEF) study. Vaccine 2010, 28(31):5049-5056.
• [40]Chao DL, Halloran ME, Obenchain VJ, Longini IM Jr: FluTE, a publicly available stochastic influenza epidemic simulation model. PLoS Comput Biol 2010, 6(1):e1000656.
• [41]Hladish T, Melamud E, Barrera LA, Galvani A, Meyers LA: EpiFire: an open source C++ library and application for contact network epidemiology. BMC Bioinformatics 2012, 13:76. BioMed Central Full Text
• [42]Epstein JM, Goedecke DM, Yu F, Morris RJ, Wagener DK, Bobashev GV: Controlling pandemic flu: the value of international air travel restrictions. PloS one 2007, 2(5):e401.
• [43]Parker J, Epstein JM: A distributed platform for global-scale agent-based models of disease transmission. ACM Trans Model Comput Simul 2011, 22(1):25.
• [44]Nsoesie EO, Beckman RJ, Marathe MV: Sensitivity analysis of an individual-based model for simulation of influenza epidemics. PloS one 2012, 7(10):e45414.
• [45]Paparian J, Brown S, Burke D, Grefenstette J: FRED Navigator: An interactive system for visualizing results from large-scale epidemic simulations. In Proceedings of the 8th International Conference on e-Science (e-Science 2012): 8-12 Oct 2012. Chicago: IEEE; 2012:1-5.