A workflow for software development within computational epidemiology

Journal of Computational Science

Volumn 2, Issue 3, 2011, Pages 216-222

  Cakici, Baki ^a,b   Boman, Magnus ^a,c  

^a ROYAL INSTITUTE OF TECHNOLOGY   (Sweden)

^b SWEDISH INSTITUTE FOR INFECTIOUS DISEASE CONTROL   (Sweden)

^c SWEDISH INSTITUTE OF COMPUTER SCIENCE   (Sweden)

Author keywords

Computational epidemiology; Individual based simulation; Policy making; Workflow

Indexed keywords

CHECK-LISTS; COMMUNICABLE DISEASE; COMPUTATIONAL MODEL; INDIVIDUAL-BASED SIMULATION; POLICY MAKERS; POLICY MAKING; SOFTWARE DEVELOPMENT PROJECTS; SPATIALLY EXPLICIT; WORKFLOW;

COMPUTER SIMULATION; DECISION MAKING; DISEASES; POPULATION STATISTICS;

SOFTWARE DESIGN;

EID: 80052883032     PISSN: 18777503     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jocs.2011.05.004     Document Type: Article

References (27)

1. Ross R. An application of the theory of probabilities to the study of a priori pathometry. Part I. Proceedings of the Royal Society of London. Series A, Containing Papers of a Mathematical and Physical Character 1916, 92:204-230.
2. Kermack W.O., McKendrick A.G. A contribution to the mathematical theory of epidemics. Proceedings of the Royal Society of London. Series A, Containing Papers of a Mathematical and Physical Character 1927, 115:700-721.
3. Boman M., Holm E. Multi-agent systems, time geography, and microsimulations. Systems Approaches and their Application 2004, 95-118. Springer. M.-O. Olsson, G. Sjöstedt (Eds.).
4. Eubank S., Guclu H., Kumar V., Marathe M., Srinivasan A., Toroczkai Zand Wang N. Modelling disease outbreaks in realistic urban social networks. Nature 2004, 429:180-184.
5. Ferguson N.M., Cummings D.A.T., Cauchemez S., Fraser C., Riley S., Meeyai A., Iamsirithaworn S., Burke D.S. Strategies for containing an emerging influenza pandemic in Southeast Asia. Nature 2005, 437:209-214.
6. Longini I.M., Nizam A., Xu S., Ungchusak K., Hanshaoworakul W., Cummings D.A.T., Halloran M.E. Containing pandemic influenza at the source. Science (New York, N.Y.) 2005, 309:1083-1087.
7. Balcan D., Goncalves B., Hu H., Ramasco J.J., Colizza V., Vespignani A. Modeling the spatial spread of infectious diseases: the global epidemic and mobility computational model. Journal of Computational Science 2010, 1:132-145.
8. Epstein J.M. Agent-based computational models and generative social science. Complexity 1999, 4:41-60.
9. Swedish Institute for Communicable Disease Control, Microsim Source Code, 2010. https://smisvn.smi.se/sim/.
10. Brouwers L., Boman M., Camitz M., Mäkilä K., Tegnell A. Micro-simulation of a smallpox outbreak using official register data. Eurosurveillance 2010, 15:17-24. pii: 19651.
11. Coelho F., Cruz O., Codeco C. Epigrass: a tool to study disease spread in complex networks. Source Code for Biology and Medicine 2008, 3.
12. Statistics Sweden, 2010. http://www.scb.se.
13. Popper K. Philosophy of a science: A personal report. British philosophy in the mid-century 1957, 155-191. Allen and Unwin, London. C.A. Mace (Ed.).
14. I. Lakatos, Science and pseudoscience, in: Philosophical Papers, vol. 1, Cambridge University Press, 1977, pp. 1-7.
15. Thom R. Structural Stability and Morphogenesis: An Outline of a General Theory of Models 1993, Addison-Wesley.
16. Axtell R., Axelrod R., Epstein J.M., Cohen M.D. Aligning simulation models: a case study and results. Computational & Mathematical Organization Theory 1996, 1:123-141.
17. Roche B., Guegan J.-F., Bousquet F. Multi-agent systems in epidemiology: a first step for computational biology in the study of vector-borne disease transmission. BMC Bioinformatics 2008, 9:435.
18. Micro, Meso, Macro: Addressing Complex Systems Couplings 2005, World Scientific. H. Liljenström, U. Svedin (Eds.).
19. Espino J., Wagner M., Szczepaniak C., Tsui F., Su H., Olszewski R., Liu Z., Chapman W., Zeng X., Ma L., Lu Z., Dara J. Removing a barrier to computer-based outbreak and disease surveillance - the RODS Open Source Project. MMWR. Morbidity and Mortality Weekly Report 2004, 53(Suppl.):32-39.
20. Crubezy M., O'Connor M., Pincus Z., Musen M., Buckeridge D. Ontology-centered syndromic surveillance for bioterrorism,. Intelligent Systems, IEEE 2005, 20:26-35.
21. Abramson D., Bethwaite B., Enticott C., Garic S., Peachey T., Michailova A., Amirriazi S. Embedding optimization in computational science workflows. Journal of Computational Science 2010, 1:41-47.
22. Cakici B., Hebing K., Saretok G.M.P., Hulth A. CASE: a framework for computer supported outbreak detection. BMC Medical Informatics and Decision Making 2010, 10.
23. Halloran M.E., Ferguson N.M., Eubank S., Longini I.M., Cummings D.A.T., Lewis B., Xu S., Fraser C., Vullikanti A., Germann T.C., Wagener D., Beckman R., Kadau K., Barrett C., Macken C.A., Burke D.S., Cooley P. Modeling targeted layered containment of an influenza pandemic in the United States. PNAS 2008, 105:4639-4644.
24. Chao D.L., Halloran M.E., Obenchain V.J., Longini I.M. FluTE, a publicly available stochastic influenza epidemic simulation model. PLoS Computational Biology 2010, 6:e1000656.
25. Youssef M., Kooij R., Scoglio C. Viral conductance: quantifying the robustness of networks with respect to spread of epidemics. Journal of Computational Science 2011, 2:286-298.
26. Newman M.E.J. The structure and function of complex networks. SIAM Review 2003, 45:167-256.
27. Bonabeau E., Toubiana L., Flahault A. The geographical spread of influenza. Proceedings of the Royal Society B 1998, 265:2421-2425.