A Lattice Model for Influenza Spreading

PLoS ONE

Volumn 8, Issue 5, 2013, Pages

  Liccardo, Antonella ^a,b   Fierro, Annalisa ^a,c  

^a UNIVERSITY OF NAPLES FEDERICO II   (Italy)

^b INFN SEZIONE DI NAPOLI   (Italy)

^c CNR   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

2009 H1N1 INFLUENZA; ADAPTATION; ADOLESCENT; ADULT; AGE DISTRIBUTION; AGED; ARTICLE; CHILD; CONTROLLED STUDY; DISEASE TRANSMISSION; EPIDEMIOLOGICAL DATA; GENETIC HETEROGENEITY; HUMAN; INFANT; MAJOR CLINICAL STUDY; MATHEMATICAL ANALYSIS; MATHEMATICAL MODEL; MOLECULAR DYNAMICS; POPULATION STRUCTURE; PRESCHOOL CHILD; PROBABILITY; SCHOOL CHILD; SOCIAL BEHAVIOR; VIRUS TRANSMISSION;

ADOLESCENT; ADULT; AGE DISTRIBUTION; AGED; CHILD; CHILD, PRESCHOOL; CLUSTER ANALYSIS; COMMUNICABLE DISEASES; EPIDEMICS; HUMANS; INFANT; INFANT, NEWBORN; INFLUENZA A VIRUS, H1N1 SUBTYPE; INFLUENZA, HUMAN; ITALY; MIDDLE AGED; MODELS, THEORETICAL; SEASONS; YOUNG ADULT;

EID: 84878060968     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0063935     Document Type: Article

References (47)

1. Germann TC, Kadau K, Longini IM, Macken CA, (2006) Mitigation strategies for pandemic in-uenza in the united states. Proceedings of the National Academy of Sciences 103: 5935-5940.
2. Ferguson NM, Cummings DAT, Cauchemez S, Fraser C, Riley S, et al. (2005) Strategies for containing an emerging inuenza pandemic in southeast asia. Nature 437: 209-214.
3. Merler S, Ajelli M (2009) The role of population heterogeneity and human mobility in the spread of pandemic inuenza. Proceedings of the Royal Society B: Biological Sciences.
4. Ciofi degli Atti ML, Merler S, Rizzo C, Ajelli M, Massari M, et al. (2008) Mitigation measures for pandemic inuenza in italy: An individual based model considering different scenarios. PLoS ONE 3: e1790.
5. Rvachev LA, Longini IM Jr, (1985) A mathematical model for the global spread of inuenza. Mathematical Biosciences 75: 3-22.
6. Watts DJ, Muhamad R, Medina DC, Dodds PS, (2005) Multiscale, resurgent epidemics in a hier-archical metapopulation model. Proceedings of the National Academy of Sciences of the United States of America 102: 11157-11162.
7. Hufnagel L, Brockmann D, Geisel T, (2004) Forecast and control of epidemics in a globalized world. Proceedings of the National Academy of Sciences of the United States of America 101: 15124-15129.
8. Colizza V, Barrat A, Barthelemy M, Valleron AJ, Vespignani A, (2007) Modeling the worldwide spread of pandemic inuenza: Baseline case and containment interventions. PLoS Med 4: e13.
9. Cooper BS, Pitman RJ, Edmunds WJ, Gay NJ, (2006) Delaying the international spread of pan-demic inuenza. PLoS Med 3: e212.
10. Epstein JM, Goedecke DM, Yu F, Morris RJ, Wagener DK, et al. (2007) Controlling pandemic u: The value of international air travel restrictions. PLoS ONE 2: e401.
11. Colizza V, Barrat A, Barthlemy M, Vespignani A, (2006) The role of the airline transportation network in the prediction and predictability of global epidemics. Proceedings of the National Academy of Sciences of the United States of America 103: 2015-2020.
12. Broeck WVd, Gioannini C, Gonalves B, Quaggiotto M, Colizza V, et al. (2011) The gleamviz computational tool, a publicly available software to explore realistic epidemic spreading scenarios at the global scale. BMC Infectious Diseases 11, 37 (2011).
13. Ajelli M, Gonalves B, Balcan D, Colizza V, Hu H, et al. (2010) Comparing large-scale computational approaches to epidemic modeling: agent-based versus structured metapopulation models. BMC Infectious Diseases 10, 190 (2010).
14. Valle SD, Hyman J, Hethcote H, Eubank S, (2007) Mixing patterns between age groups in social networks. Social Networks 29: 539-554.
15. Khiabanian H, Farrell GM, St George K, Rabadan R, (2009) Differences in patient age distribution between inuenza a subtypes. PLoS ONE 4: e6832.
16. Watts DJ, Strogatz SH, (1998) Collective dynamics of 'small-world' networks. Nature 393: 440-442.
17. Moore C, Newman MEJ, (2000) Epidemics and percolation in small-world networks. Phys Rev E 61: 5678-5682.
18. Newman MEJ, Watts DJ, (1999) Scaling and percolation in the small-world network model. Phys Rev E 60: 7332-7342.
19. Newman MEJ, (2002) Spread of epidemic disease on networks. Phys Rev E 66: 016128.
20. Pastor-Satorras R, Vespignani A, (2001) Epidemic dynamics and endemic states in complex networks. Phys Rev E 63: 066117.
21. Eames KTD, Keeling MJ, (2002) Modeling dynamic and network heterogeneities in the spread of sexually transmitted diseases. Proceedings of the National Academy of Sciences 99: 13330-13335.
22. Meyers L, Newman M, Pourbohloul B, (2006) Predicting epidemics on directed contact networks. Journal of theoretical biology 240: 400-418.
23. Volz E, Meyers LA, (2007) Susceptible infected recovered epidemics in dynamic contact networks. Proceedings of the Royal Society B: Biological Sciences 274: 2925-2934.
24. Gross T, D'Lima CJD, Blasius B, (2006) Epidemic dynamics on an adaptive network. Phys Rev Lett 96: 208701.
25. Masuda N, Konno N, Aihara K, (2004) Transmission of severe acute respiratory syndrome in dynamical small-world networks. Phys Rev E 69: 031917.
26. Zhu CP, Xiong SJ, Tian YJ, Li N, Jiang KS, (2004) Scaling of directed dynamical small-world networks with random responses. Phys Rev Lett 92: 218702.
27. Saramki J, Kaski K, (2005) Modelling development of epidemics with dynamic small-world networks. Journal of Theoretical Biology 234: 413-421.
28. Ochab J, Gra P, (2011) Shift of percolation thresholds for epidemic spread between static and dynamic small-world networks. The European Physical Journal B- Condensed Matter and Complex Systems 81: 373-379.
29. de Souza DR, Tomé T, (2010) Stochastic lattice gas model describing the dynamics of the sirs epidemic process. Physica A: Statistical Mechanics and its Applications 389: 1142-1150.
30. Wallinga J, Teunis P, Kretzschmar M (15 November 2006) Using data on social contacts to estimate age-specific transmission parameters for respiratory-spread infectious agents. American Journal of Epidemiology 164: 936-944.
31. Mossong J, Hens N, Jit M, Beutels P, Auranen K, et al. (2008) Social contacts and mixing patterns relevant to the spread of infectious diseases. PLoS Med 5: e74.
32. Iozzi F, Trusiano F, Chinazzi M, Billari FC, Zagheni E, et al. (2010) Little italy: An agent-based approach to the estimation of contact patterns-fitting predicted matrices to serological data. PLoS Computational Biology 6.
33. Melegaro A, Jit M, Gay N, Zagheni E, Edmunds WJ, (2011) What types of contacts are important for the spread of infections? using contact survey data to explore european mixing patterns. Epidemics 3: 143-151.
34. Zagheni E, Billari FC, Manfredi P, Melegaro A, Mossong J, et al. (2008) Using time-use data to parameterize models for the spread of close-contact infectious diseases. American Journal of Epidemiology 168: 1082-1090.
35. Funk S, Salath M, Jansen VAA, (2010) Modelling the inuence of human behaviour on the spread of infectious diseases: a review. J R Soc Interface 7: 1247-1256.
36. Perra N, Balcan D, Gonalves B, Vespignani A, (2011) Towards a characterization of behavior-disease models. PLoS ONE 6: e23084.
37. Fierro A, Liccardo A, (2011) A simple stochastic lattice gas model for h1n1 pandemic. Application to the italian epidemiological data. The European Physical Journal E 34: 1-6.
38. Cugliandolo LF, (2010) Topics in coarsening phenomena. Physica A: Statistical Mechanics and its Applications 389: 4360-4373.
39. Wu FY, (1982) The potts model. Reviews of Modern Physics 54: 235-268.
40. Swendsen RH, Wang JS, (1987) Nonuniversal critical dynamics in monte carlo simulations. Phys Rev Lett 58: 86-88.
41. Berg BA, Neuhaus T, (1992) Multicanonical ensemble: A new approach to simulate first-order phase transitions. Phys Rev Lett 68: 9-12.
42. Kermack WO, McKendrick AG, (1927) A contribution to the mathematical theory of epidemics. Proceedings of the Royal Society of London Series A 115: 700-721.
43. Lloyd AL, (2001) Realistic distributions of infectious periods in epidemic models: Changing patterns of persistence and dynamics. Theoretical Population Biology 60: 59-71.
44. Miller E, Hoschler K, Hardelid P, Stanford E, Andrews N, et al. (2010) Incidence of 2009 pandemic inuenza a h1n1 infection in england: a cross-sectional serological study. The Lancet 375: 1100-1108.
45. Wallinga J, Lipsitch M, (2007) How generation intervals shape the relationship between growth rates and reproductive numbers. Proceedings of the Royal Society B: Biological Sciences 274: 599-604.
46. Yang Y, Sugimoto JD, Halloran ME, Basta NE, Chao DL, et al. (2009) The transmissibility and control of pandemic inuenza a (h1n1) virus. Science 326: 729-733.
47. Fraser C, Donnelly CA, Cauchemez S, Hanage WP, Van Kerkhove MD, et al. (2009) Pandemic potential of a strain of inuenza a (h1n1): Early findings. Science 324: 1557-1561.