This research aims to improve public health policy and practice by incorporating social behavior into mathematical models of infectious disease spread and by providing a better understanding of how proposed health-related policies will work when put into practice.

Project Summary

The objective of this project is to incorporate social behavior into mathematical models of infectious disease transmission dynamics, with a focus on influenza like illness. The inferences of this project will improve our understanding of the impact of different control and prevention strategies for infectious disease epidemics in general and Influenza epidemics in particular. Our hypothesis is that individual behavior, disease dynamics, and interventions coevolve across multiple scales to create statistically and epidemiologically significant differences in the efficacy and social equity of public health policies such as infectious disease control strategies.

This project extends well studied computational simulations to include people's behaviors relevant to infectious disease epidemics and will be used to determine the consequences of feedback between population-level effects and individual-level behavior. In particular, we will determine the sensitivity of outcomes to particular behaviors. A survey designed to focus on those particular behaviors will be used to estimate variability across communities.

Team Members

  • Achla Marathe (Contact PI), Professor, Biocomplexity Institute of Virginia Tech and Agricultural and Applied Economics
  • Kaja Abbas (PI), Assistant Professor in Disease Modelling, London School of Hygieine and Tropical Medicine
  • Samarth Swarup, Research Assistant Professor, Biocomplexity Institute of Virginia Tech
  • Jiangzhuo Chen, Research Associate Professor, Biocomplexity Institute of Virginia Tech
  • Stephen Eubank, Professor, Biocomplexity Institute of Virginia Tech and Population Health Sciences
  • Bryan Lewis, Research Associate Professor, Biocomplexity Institute of Virginia Tech
  • Kevin Boyle, Professor, Agricultural and Applied Economics, Virginia Tech
  • Pamela Murray-Tuite, Associate Professor, Civil and Environmental Engineering, Clemson Univesity

Students


  • Gloria Kang, MPH (Infectious Disease)/PhD Biomedical and Veterinary Sciences
  • James Schlitt, PhD in Genetics, Bioinformatics & Computational Biology
  • Meghendra Singh, MCS, Computer Science and Appliction
  • Lijing Wang, PhD, Computer Science

Publications

Article

  • Rife L. Med Beat: On the hunt for contagious diseases. The Roanoke Times . 2018. http://www.roanoke.com/business/columns_and_blogs/blogs/med_beat....
  • Rosplock D. Vaccine access for nation's poorest residents has massive impact on effective flu planning, new Virginia Tech study suggests. VT News. 2018. https://vtnews.vt.edu/articles/2018/03/bi-fluseasonplanning.html....
  • Dorratoltaj N, O'Dell ML, Bordwine P, Kerkering TM, Redican KJ, Abbas K. Epidemiological Effectiveness and Cost of a Fungal Meningitis Outbreak Response in New River Valley, Virginia: Local Health Department and Clinical Perspectives. Disaster Medicine and Public Health Preparedness . 2018;12(1):38-46. https://doi.org/. 10.1017/dmp.2017.32.
  • Adiga A, Chu S, Eubank SG, et al. Disparities in Spread and Control of Influenza in Slums of Delhi. BMJ Open. 2018;8(1):e017353. https://doi.org/10.1136/bmjopen-2017-017353. .
  • Adiga A, Chu S, Eubank S, et al. Disparities in spread and control of influenza in slums of Delhi: findings from an agent-based modelling study. BMJ. 2018.
  • Nath M, Ren Y, Khorramzadeh Y, Eubank S. Determining whether a class of random graphs is consistent with an observed contact network. Journal of Theoretical Biology. 2017;440:121-132. https://doi.org/10.1016/j.jtbi.2017.12.021.
  • Brownstein JS, Chu S, Marathe A, et al. Combining Participatory Influenza Surveillance with Modeling and Forecasting: Three Alternative Approaches. JMIR public health and surveillance. 2017;3(4):e83. https://doi.org/10.2196/publichealth.7344.
  • Tabataba FS, Chakraborty P, Ramakrishnan N, et al. A framework for evaluating epidemic forecasts. BMC Infectious Diseases. 2017. https://doi.org/10.1186/s12879-017-2365-1.
  • Dorrataltaj N, Marathe A, Lewis BL, Swarup S, Eubank SG, Abbas KM. Epidemiological and Economic Impact of Pandemic Influenza in Chicago: Priorities for Vaccine Interventions. PLoS Computational Biology. 2017;13(6). https://doi.org/10.1371/journal.pcbi.1005521.
  • Kang GJ, Ewing-Nelson SR, Mackey L, et al. Semantic Network Analysis of Vaccine Sentiment in Online Social Media. Vaccine. 2017;35(29):3621-3638. https://doi.org/10.1016/j.vaccine.2017.05.052.
  • Venkatramanan S, Lewis BL, Chen J, Higdon D, Kumar VSA, Marathe MV. Using data-driven agent-based models for forecasting emerging infectious diseases. Epidemics - Special Issue on Ebola Challenge. 2017. https://doi.org/10.1016/j.epidem.2017.02.010.
  • Marathe A, Chen J, Chu S, et al. Effect of Modeling Slum Populations on Influenza Spread Delhi. BMJ Open. 2016;6(9):e011699. https://doi.org/10.1136/bmjopen-2016-011699.
  • Biggerstaff M, Alper D, Dredze M, et al. Results from the centers for disease control and prevention's predict the 2013-2014 Influenza Season Challenge. BMC infectious diseases. 2016;16(357):1-10. https://doi.org/10.1186/s12879-016-1669-x.
  • Parikh NK, Hayatnagarkar HG, Beckman RJ, Marathe MV, Swarup S. A comparison of multiple behavior models in a simulation of the aftermath of an improvised nuclear detonation. Autonomous Agents and Multi-Agent Systems. 2016:1-27. https://doi.org/10.1007/s10458-016-9331-y.
  • Abbas K, Dorratoltaj N, O'Dell M, Bordwine P, Kerkering TM, Redican KJ. Clinical Response, Outbreak Investigation, and Epidemiology of the Fungal Meningitis Epidemic in the United States: Systematic Review. Disaster Med Public Health Prep. 2016;10(1):145-151. https://doi.org/10.1056/NEJMoa1215460.
  • Althouse BM, Scarpino SV, Meyers LA, et al. Enhancing disease surveillance with novel data streams: challenges and opportunities. EPJ Data Science. 2015;4(17). https://doi.org/10.1140/epjds/s13688-015-0054-0.
  • Schlitt J, Lewis BL, Eubank SG. ChatterGrabber: A Lightweight Easy to Use Social Media Surveillance Toolkit. Online Journal of Public Health Informatics. 2015;7(1). https://doi.org/10.5210/ojphi.v7i1.5717.
  • Abbas K, Dorratoltaj N, O'Dell ML, Bordwine P, Kerkering TM, Redican KJ. Economic Evaluation of a Fungal Meningitis Outbreak Response in New River Valley: Local Health Department Perspective. Front Public Health Serv Syst Res. 2015;4(4):21-28. https://doi.org/10.13023/FPHSSR.0404.04.
  • Lau E, Zheng J, Tsang T, et al. Epidemiological inferences using public information, influenza H7N9 epidemic in China. Online J Public Health Inform. 2015;7(1):e143. https://doi.org/10.5210/ojphi.v7i1.5809.
  • Yi M, Marathe A. Fairness versus Efficiency of Vaccine Allocation Strategies. Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research. 2015;18(2):278-283. http://www.sciencedirect.com/science/article/pii/S10983015140477....
  • Khorramzadeh Y, Youssef M, Eubank SG, Mowlaei S. Analyzing network reliability using structural motifs. Phys Rev E. 2015;91(4):042814.
  • Xia H, Nagaraj KS, Chen J, Marathe MV. Synthesis of a High Resolution Social Contact Network for Delhi With Application to Pandemic Planning. Journal of Artificial Intelligence in Medicine. 2015;65(2):113-130. https://doi.org/10.1016/j.artmed.2015.06.003.
  • Alexander KA, Sanderson CE, Marathe MV, et al. What factors might have led to the emergence of Ebola in West Africa? PLOS Neglected Tropical Diseases. 2014:1418-1425. http://blogs.plos.org/speakingofmedicine/2014/11/11/factors-migh....

Book or Book Section

  • Chen J, Lewis BL, Marathe A, Marathe MV, Swarup S, Kumar VSA. Individual and Collective Behavior in Public Health Epidemiology. In: HS 36 Disease Modelling and Public Health. 1st ed. Elsevier; 2017.
  • Alam MM, Abedi V, Bassaganya-Riera J, et al. Agent-Based Modeling and High Performance Computing. In: Computational Immunology: Models and Tools. Elsevier; 2015:79-112. http://store.elsevier.com/product.jsp?isbn=9780128036976.
  • Barrett CL, Eubank SG, Marathe A, Marathe MV, Swarup S. Synthetic Information Environments for Policy Informatics: A Distributed Cognition Perspective. Routledge Press; 2015:pp. 267-284. eds. Erik Johnston. http://www.routledge.com/books/details/9781138832084/.

Conference

  • Abbas K. Modeling epidemiological and economic impact of vaccines. Presented at the International Symposium on Health Analytics and Disease Modeling (HADM 2018), New Delhi, India ; 2018.
  • Kuhlman C, Ren Y, Lewis B, Schlitt J. Hybrid Agent-Based Modeling of Zika in the United States. In: Proceedings of the Winter Simulation Conference 2017. 2017:1085-1096. https://doi.org/10.1109/WSC.2017.8247857.
  • Kang G, Ewing-Nelson SR, Mackey L, et al. Vaccine sentiment on social media: A semantic network analysis. Presented at the 145th American Public Health Association (APHA) Annual Meeting and Exposition, Atlanta, GA; 2017.
  • Venkatramanan S, Wu S, Shi B, et al. Towards Robust Models of Food Flows and Their Role in Invasive Species Spread. Presented at the IEEE Big Data 2017, Boston, MA, USA; 2017.
  • Abbas K. Systems thinking to improve effectiveness, efficiency, and equity in health. Presented at the 3rd Systems and Complexity Science for Healthcare Conference, Ashburn, VA; 2017.
  • Ghosh S, Chakraborty P, Lewis BL, et al. GELL: Automatic Extraction of Epidemiological Line Lists from Open Sources. In: Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM; 2017:1477-1485. https://doi.org/10.1145/3097983.3098073.
  • Chu S, Kuhlman C, Marathe A. Disparities in Slum Health and Its Impact on Larger Urban Regions. Presented at the North American Social Networks Conference NASN2017, Washington, DC; 2017.
  • Wang L, Chen J, Marathe A. Framework for Learning Health Disparities Among Cohorts in An Influenza Epidemic. Presented at the North American Social Networks Conference NASN2017, Washington, DC; 2017.
  • Tabataba FS, Hosseinipour M, Lewis BL, et al. Epidemic Forecasting by Combining Agent-Based Models and Smart Beam-Particle Filtering Framework. In: Proceedings of the IEEE International Conference on Data Mining 2017. 2017.
  • Parikh NK, Marathe MV, Swarup S. Contextual Ranking of Behaviors for Large-scale Multiagent Simulations. In: Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems. 2017:1676-1678. http://www.aamas2017.org/proceedings/pdfs/p1676.pdf.
  • Venkatramanan S, Chen J, Gupta S, et al. Spatio-temporal optimization of seasonal vaccination using a metapopulation model of influenza. In: IEEE International Conference on Healthcare Informatics (ICHI). IEEE; 2017.
  • Swarup S, Gohlke J, Bohland J. A Multi-agent Model of Population Heat Exposure. Presented at the 2nd International Workshop on Agent-based modeling of urban systems (ABMUS), Sao Paulo, Brazil ; 2017.
  • Lewis B. Disease Simulation Extensions - Zika Hybrid & and National Influenza. Presented at the MIDAS Annual Conference, Atlanta, GA; 2017.
  • Venkatramanan S, Wu S, Adiga A, Marathe A, Eubank SG, Marathe MV. Hybrid models for ecological and anthropogenic drivers of pest invasion: Case study of Tuta Absoluta in Nepal. Presented at the ICBCL 2017; 2017.
  • Wang L, Cho J-H, Chen I-R, Chen J. PDGM: Percolation-based Directed Graph Matching in Social Networks. In: Proceedings of The IEEE International Conference on Communications (ICC). 2017.
  • Chu S, Swarup S, Chen J, Marathe A. A Comparison of Targeted Layered Containment Strategies for a Flu Pandemic in Three US Cities. In: Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS). 2017.
  • Nath M, Ren Y, Khorramzadeh Y, Eubank SG. Diffusive Dynamics on a Network. Presented at the 83rd Annual Meeting of the APS Southeastern Section, Charlottesville, VA; 2016. http://meetings.aps.org/Meeting/SES16/Session/K1.57.
  • Wang L, Chen J, Marathe A. Understanding Health Disparities in an Influenza Epidemic. In: Computational Social Science Society of the Americas Annual Conference (CSSSA). 2016.
  • Dorratoltaj N, Marathe A, Lewis BL, Eubank SG, Swarup S, Abbas KM. Economic Evaluation of Influenza Vaccine Intervention. In: Proceedings of the American Public Health Association Annual Meeting & Expo. 2016. https://apha.confex.com/apha/144am/meetingapp.cgi/Paper/366314.
  • Parikh N, Marathe MV, Swarup S. Integrating Behavior and Microsimulation Models. Presented at the AAMAS, Singapore; 2016.
  • Parikh N, Marathe M, Swarup S. Summarizing Simulation Results Using Causally-Relevant States. Presented at the Conference on Autonomous Agents and Multiagent Systems (AAMAS) Workshops, Singapore, SINGAPORE; 2016. https://doi.org/10.1007/978-3-319-46840-2_6.
  • Bisset KR, Cadena JE, Khan M, Kuhlman CJ, Lewis BL, Telionis P. An Integrated Agent-Based Approach for Modeling Disease Spread in Large Populations to Support Health Informatics. In: Proceedings of the 2016 IEEE International Conference on Biomedical and Health Informatics. IEEE; 2016:629-632.
  • Adiga A, Chu S, Marathe A, Kumar VSA. Can social distancing compensate for the unvaccinated? In: Proceedings of the Computational Social Science Society of the Americas Annual Conference. 2015. https://computationalsocialscience.org/.
  • Deodhar S, Chen J, Wilson AL, et al. EpiCaster: An Integrated Web Application For Situation Assessment and Forecasting of Global Epidemics. In: Proceedings of the 6th ACM Conference on Bioinformatics, Computational Biology and Health Informatics (ACM-BCB). ACM; 2015:156-165. https://doi.org/10.1145/2808719.2808735.
  • Deodhar S, Chen J, Wilson AL, et al. FluCaster: A Pervasive Web Application For High Resolution Situation Assessment and Forecasting of Flu Outbreaks. In: Proceedings of the 2nd IEEE International Conference on Healthcare Informatics. IEEE; 2015:105-114. https://doi.org/10.1109/ICHI.2015.20.
  • Zhao L, Chen J, Chen F, Wang W, Lu C-T, Ramakrishnan N. SimNest: Social Media Nested Epidemic Simulation via Online Semi-supervised Deep Learning. In: Proceedings of the IEEE International Conference on Data Mining. 2015. http://icdm2015.stonybrook.edu/.
  • Adiga A, Chu S, Marathe A, Kumar VSA. Vaccination or social distancing: A public health dilemma. Presented at the INFORMS Healthcare Conference, Nashville, TN; 2015.
  • Marathe A, Abbas KM, Swarup S. Understanding Feedback Between Behavioral Interventions and Disease Evolution. In: Proceedings of the 2015 INFORMS Annual Meeting. 2015.
  • Adiga A, Beckman RJ, Bisset KR, et al. Synthetic Populations for Epidemic Modeling. In: Proceedings of the International Conference on Computational Social Sciences (ICCSS). 2015. http://www.iccss2015.eu/.
  • Kang GJ, Culp R, Marathe A, Abbas KM. Parental Factors Associated with Influenza School Located Vaccination Program in the United States. Presented at the CUGH Global Health Conference, "Mobilizing Research for Global Health", Boston, Massachusetts; 2015.
  • Lopez D, Gunasekaran M, Murugan B, Harprett K, Abbas K. Spatial big data analytics of influenza epidemic in Vellore, India. In: 2014 IEEE International Conference on Big Data (Big Data). 2015:19-24. https://doi.org/10.1109/BigData.2014.7004422.
  • Swarup S, Ravi R, Mahmud MMH, Lum K, Ravi SS. Identifying Core Network Structure for Epidemic Simulations. In: Proceedings of the 12th International Workshop on Agents and Data-Mining Interaction. 2015.

Presentation

  • Marathe A. Systems analysis of social pathways of epidemics. 2018.
  • Marathe A. Vaccination or social distancing: A public health dilemma. 2015.
  • Marathe A, Gray J, Gray L, Fan S, Norton G. Projecting the Spread of Infectious Diseases. Ebola: Predicting it, Addressing it, and Food Security Impacts. 2015.

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