Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.
ADVANCED SEARCH
Log in
Top
BMC Medicine
Published in: BMC Medicine 1/2012

Open Access 01-12-2012 | Research article

Real-time numerical forecast of global epidemic spreading: case study of 2009 A/H1N1pdm

Authors: Michele Tizzoni, Paolo Bajardi, Chiara Poletto, José J Ramasco, Duygu Balcan, Bruno Gonçalves, Nicola Perra, Vittoria Colizza, Alessandro Vespignani

Published in: BMC Medicine | Issue 1/2012

Login to get access

Abstract

Background

Mathematical and computational models for infectious diseases are increasingly used to support public-health decisions; however, their reliability is currently under debate. Real-time forecasts of epidemic spread using data-driven models have been hindered by the technical challenges posed by parameter estimation and validation. Data gathered for the 2009 H1N1 influenza crisis represent an unprecedented opportunity to validate real-time model predictions and define the main success criteria for different approaches.

Methods

We used the Global Epidemic and Mobility Model to generate stochastic simulations of epidemic spread worldwide, yielding (among other measures) the incidence and seeding events at a daily resolution for 3,362 subpopulations in 220 countries. Using a Monte Carlo Maximum Likelihood analysis, the model provided an estimate of the seasonal transmission potential during the early phase of the H1N1 pandemic and generated ensemble forecasts for the activity peaks in the northern hemisphere in the fall/winter wave. These results were validated against the real-life surveillance data collected in 48 countries, and their robustness assessed by focusing on 1) the peak timing of the pandemic; 2) the level of spatial resolution allowed by the model; and 3) the clinical attack rate and the effectiveness of the vaccine. In addition, we studied the effect of data incompleteness on the prediction reliability.

Results

Real-time predictions of the peak timing are found to be in good agreement with the empirical data, showing strong robustness to data that may not be accessible in real time (such as pre-exposure immunity and adherence to vaccination campaigns), but that affect the predictions for the attack rates. The timing and spatial unfolding of the pandemic are critically sensitive to the level of mobility data integrated into the model.

Conclusions

Our results show that large-scale models can be used to provide valuable real-time forecasts of influenza spreading, but they require high-performance computing. The quality of the forecast depends on the level of data integration, thus stressing the need for high-quality data in population-based models, and of progressive updates of validated available empirical knowledge to inform these models.
Appendix
Available only for authorised users
Literature
1.
Riley S: Large-scale transmission models of infectious disease. Science. 2007, 316: 1298-1301. 10.1126/science.1134695.CrossRefPubMed
2.
Balcan D, Hu H, Gonçalves B, Bajardi P, Poletto C, Ramasco JJ, Paolotti D, Perra N, Tizzoni M, Van den Broeck W, Colizza V, Vespignani A: Seasonal transmission potential and activity peaks of the new influenza A/H1N1: a Monte Carlo likelihood analysis based on human mobility. BMC Med. 2009, 7: 45-10.1186/1741-7015-7-45.CrossRefPubMedPubMedCentral
3.
Balcan D, Colizza V, Gonçalves B, Hu H, Ramasco JJ, Vespignani A: Multiscale mobility networks and the large scale spreading of infectious diseases. Proc Natl Acad Sci USA. 2009, 106: 21484-21489. 10.1073/pnas.0906910106.CrossRefPubMedPubMedCentral
4.
Grais RF, Hugh Ellis J, Glass GE: Assessing the impact of airline travel on the geographic spread of pandemic influenza. Eur J Epidemiol. 2003, 18: 1065-1072. 10.1023/A:1026140019146.CrossRefPubMed
5.
Colizza V, Barrat A, Barthélemy M, Valleron A-J, Vespignani A: Modeling the World-wide spread of pandemic influenza: baseline case and containment interventions. PLoS Med. 2007, 4: e13-10.1371/journal.pmed.0040013.CrossRefPubMedPubMedCentral
6.
Hufnagel L, Brockmann D, Geisel T: Forecast and control of epidemics in a globalized world. Proc Natl Acad Sci USA. 2004, 101: 15124-15129. 10.1073/pnas.0308344101.CrossRefPubMedPubMedCentral
7.
Eubank S, Guclu H, Kumar VSA, Marathe MV, Srinivasan A, Toroczkai Z, Wang N: Modeling disease outbreaks in realistic urban social networks. Nature. 2004, 429: 180-4. 10.1038/nature02541.CrossRefPubMed
8.
9.
Cooper BS, Pitman RJ, Edmunds WJ, Gay N: Delaying the international spread of pandemic influenza. PLoS Med. 2006, 3: e12-10.1371/journal.pmed.0030012.CrossRef
10.
Ferguson NM, Keeling MJ, Edmunds WJ, Gani R, Grenfell BT, Anderson RM, Leach S: Planning for smallpox outbreaks. Nature. 2003, 425: 681-685. 10.1038/nature02007.CrossRefPubMed
11.
Ferguson NM, Cummings DAT, 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: 209-214. 10.1038/nature04017.CrossRefPubMed
12.
Ferguson NM, Cummings DAT, Fraser C, Cajka JC, Cooley PC, Burke DS: Strategies for mitigating an influenza pandemic. Nature. 2006, 442: 448-452. 10.1038/nature04795.CrossRefPubMed
13.
Germann TC, Kadau K, Longini IM, Macken CA: Mitigation strategies for pandemic influenza in the United States. Proc Natl Acad Sci USA. 2006, 103: 5935-5940. 10.1073/pnas.0601266103.CrossRefPubMedPubMedCentral
14.
Epstein J, Goedecke D, Yu F, Morris R, Wagener D, Bobashev G: Controlling pandemic flu: the value of international air travel restrictions. PLoS One. 2007, 2: 401-10.1371/journal.pone.0000401.CrossRef
15.
Ciofi degli Atti ML, Merler S, Rizzo C, Ajelli M, Massari M, Manfredi P, Furlanello C, Scalia-Tomba G, Iannelli M: Mitigation measures for pandemic influenza in italy: an individual based model considering different scenarios. PLoS One. 2008, 3: e1790-10.1371/journal.pone.0001790.CrossRefPubMedPubMedCentral
16.
Hejblum G, Setbon M, Temime L, Lesieur S, Valleron A-J: Modelers' perception of mathematical modeling in epidemiology: a web-based survey. PLoS One. 2011, 6: e16531-10.1371/journal.pone.0016531.CrossRefPubMedPubMedCentral
17.
Van Kerkhove MD, Asikainen T, Becker NG, Bjorge S, Desenclos JC, dos Santos T, Fraser C, Leung GM, Lipsitch M, Longini IM, McBryde ES, Roth CE, Shay DK, Smith DJ, Wallinga J, White PJ, Ferguson NM, Riley S: Studies needed to address the public health challenges of the 2009 H1N1 influenza pandemic: insights from modeling. PLoS Med. 2010, 7: e1000275-10.1371/journal.pmed.1000275.CrossRefPubMedPubMedCentral
18.
19.
Medlock J, Galvani A: Optimizing influenza vaccine distribution. Science. 2009, 325: 1705-1708. 10.1126/science.1175570.CrossRefPubMed
20.
Hollingsworth TD, Ferguson NM, Anderson RM: Will travel restrictions control the International spread of pandemic influenza?. Nature Med. 2006, 12: 497-499. 10.1038/nm0506-497.CrossRefPubMed
21.
Halloran ME, Ferguson NM, Eubank S, Longini IM, Cummings DAT, Lewis B, Xu S, Fraser C, Vullikanti A, Germann TC, Wagener D, Beckman R, Kadau K, Macken C, Burke DS, Cooley P: Modeling targeted layered containment of an influenza pandemic in the United States. Proc Natl Acad Sci USA. 2008, 105: 4639-44. 10.1073/pnas.0706849105.CrossRefPubMedPubMedCentral
22.
Flahault A, Vergu E, Coudeville L, Grais R: Strategies for containing a global influenza pandemic. Vaccine. 2006, 24: 6751-6755. 10.1016/j.vaccine.2006.05.079.CrossRefPubMed
23.
Longini IM, Halloran ME, Nizam A, Yang Y: Containing pandemic influenza with antiviral agents. Am J Epidemiol. 2004, 159: 623-633. 10.1093/aje/kwh092.CrossRefPubMed
24.
Longini IM, Nizam A, S X, Ungchusak K, Hanshaoworakul W, Cummings D, Halloran M: Containing pandemic influenza at the source. Science. 2005, 309: 1083-1087. 10.1126/science.1115717.CrossRefPubMed
25.
Bauch CT, Lloyd-Smith JO, Coffee MP, Galvani AP: Dynamically modeling SARS and other newly emerging respiratory illnesses: past, present, and future. Epidemiology. 2005, 16: 791-801. 10.1097/01.ede.0000181633.80269.4c.CrossRefPubMed
26.
Hall IM, Gani R, Hughes HE, Leach S: Real-time epidemic forecasting for pandemic influenza. Epidemiol Infect. 2007, 135: 372-385. 10.1017/S0950268806007084.CrossRefPubMed
27.
Fraser C, Donnelly C, Cauchemez S, Hanage W, Van Kerkhove M, Hollingsworth T, Griffin J, Baggaley R, Jenkins H, Lyons E, Jombart T, Hinsley W, Grassly N, Balloux F, Ghani A, Ferguson NM: Pandemic potential of a strain of influenza A/H1N1: early findings. Science. 2009, 324: 1557-1561. 10.1126/science.1176062.CrossRefPubMedPubMedCentral
28.
Yang Y, Sugimoto JD, Halloran ME, Basta NE, Chao DL, Matrajt L, Potter G, Kenah E, Longini IM: The transmissibility and control of pandemic influenza A/H1N1 virus. Science. 2009, 326: 729-733. 10.1126/science.1177373.CrossRefPubMedPubMedCentral
29.
30.
Boëlle PY, Bernillon P, Desenclos JC: A preliminary estimation of the reproduction ratio for new influenza A(H1N1) from the outbreak in Mexico, March-April 2009. Euro Surveill. 2009, 14: 19205.PubMed
31.
Lipsitch M, Lajous M, O'Hagan J, Cohen T, Miller J, Goldstein E, Danon L, Wallinga J, Riley S, Dowell S, Reed C, McCarron M: Use of cumulative incidence of novel influenza A/H1N1 in foreign travelers to estimate lower bounds on cumulative incidence in Mexico. PLoS One. 2009, 4: e6895-10.1371/journal.pone.0006895.CrossRefPubMedPubMedCentral
32.
White LF, Wallinga J, Finelli L, Reed C, Riley S, Lipsitch M, Pagano M: Estimation of the reproductive number and the serial interval in early phase of the 2009 influenza A/H1N1 pandemic in the USA. Influenza Other Respi Viruses. 2009, 3: 267-276. 10.1111/j.1750-2659.2009.00106.x.CrossRef
33.
Nishiura H, Castillo-Chavez C, Safan M, Chowell G: Transmission potential of the new influenza A(H1N1) virus and its age-specificity in Japan. Euro Surveill. 2009, 14: 19227.PubMed
34.
Pourbohloul B, Ahued A, Davoudi B, Meza R, Meyers LA, Skowronski DM, Villaseñor I, Galván F, Cravioto P, Earn DJD, Dushoff J, Fisman D, Edmunds WJ, Hupert N, Scarpino SV, Trujillo J, Lutzow M, Morales J, Contreras A, Chávez C, Patrick DM, Brunham RC: Initial human transmission dynamics of the pandemic (H1N1) 2009 virus in North America. Influenza Other Respi Viruses. 2009, 3: 215-222. 10.1111/j.1750-2659.2009.00100.x.CrossRef
35.
Boni MF, Manh BH, Thai PQ, Farrar J, Hien TT, Hien NT, Van Kinh N, Horby P: Modelling the progression of pandemic influenza A (H1N1) in Vietnam and the opportunities for reassortment with other influenza viruses. BMC Med. 2009, 7: 43-10.1186/1741-7015-7-43.CrossRefPubMedPubMedCentral
36.
Nishiura H: Real-time forecasting of an epidemic using a discrete time stochastic model: a case study of pandemic influenza (H1N1-2009). Biomed Eng Online. 2011, 10: 15-10.1186/1475-925X-10-15.CrossRefPubMedPubMedCentral
37.
Ong JBS, Chen MI-C, Cook AR, Lee HC, Lee VJ, Pin Lin RT, Tambyah PA, Gan Goh L: Real-time epidemic monitoring and forecasting of H1N1-2009 using influenza-like illness from general practice and family doctor clinics in Singapore. PLoS One. 2010, 5: e10036-10.1371/journal.pone.0010036.CrossRefPubMedPubMedCentral
38.
Baguelin M, van Hoeck AJ, Jit M, Flasche S, White PJ, Edmunds WJ: Vaccination against pandemic influenza A/H1N1v in England: A real-time economic evaluation. Vaccine. 2010, 28: 2370-2384. 10.1016/j.vaccine.2010.01.002.CrossRefPubMed
39.
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: e1002205-10.1371/journal.pcbi.1002205.CrossRefPubMedPubMedCentral
40.
Kenah E, Chao DL, Matrajt L, Halloran ME, Longini IM: The global transmission and control of influenza. PLoS One. 2011, 6: e19515-10.1371/journal.pone.0019515.CrossRefPubMedPubMedCentral
41.
Bobashev G, Morris RJ, Goedecke M: Sampling for global epidemic models and the topology of an international airport network. PLoS One. 2008, 3: e3154-10.1371/journal.pone.0003154.CrossRefPubMedPubMedCentral
42.
Ajelli M, Gonçalves B, Balcan D, Colizza V, Hu H, Ramasco JJ, Merler S, Vespignani A: Comparing large-scale computational approaches to epidemic modeling: agent-based versus structured metapopulation models. BMC Infect Dis. 2010, 10: 190-10.1186/1471-2334-10-190.CrossRefPubMedPubMedCentral
43.
Rvachev LA, Longini IM: A mathematical model for the global spread of influenza. Math Biosci. 1985, 75: 3-22. 10.1016/0025-5564(85)90064-1.CrossRef
44.
Viboud C, Bjornstad O, Smith D, Simonsen L, Miller M, Grenfell BT: Synchrony, waves, and spatial hierarchies in the spread of influenza. Science. 2006, 312: 447-451. 10.1126/science.1125237.CrossRefPubMed
45.
Flahault A, Valleron A-J: A Method for assessing the global spread of HIV-1 infection based on air travel. Math Popul Stud. 1991, 3: 1-11. 10.1080/08898489109525319.CrossRef
46.
Colizza V, Barrat A, Barthélemy M, Vespignani A: The role of airline transportation network in the prediction and predictability of global epidemics. Proc Natl Acad Sci USA. 2006, 103: 2015-2020. 10.1073/pnas.0510525103.CrossRefPubMedPubMedCentral
47.
Colizza V, Barrat A, Barthélemy M, Vespignani A: Predictability and epidemic pathways in global outbreaks of infectious diseases: the SARS case study. BMC Med. 2007, 5: 34-10.1186/1741-7015-5-34.CrossRefPubMedPubMedCentral
48.
Coburn BJ, Bradley G, Wagner BG, Blower S: Modeling influenza epidemics and pandemics: insights into the future of swine flu (H1N1). BMC Med. 2009, 7: 30-10.1186/1741-7015-7-30.CrossRefPubMedPubMedCentral
49.
Balcan D, Gonçalves B, Hu H, Ramasco JJ, Colizza V, Vespignani A: Modeling the spatial spread of infectious diseases: The Global Epidemic and Mobility computational model. J Computl Sci. 2010, 1: 132-145. 10.1016/j.jocs.2010.07.002.CrossRef
50.
51.
52.
53.
Keeling MJ, Rohani P: Estimating spatial coupling in epidemiological systems: a mechanistic approach. Ecol Lett. 2002, 5: 20-29. 10.1046/j.1461-0248.2002.00268.x.CrossRef
54.
Sattenspiel L, Dietz K: A structured epidemic model incorporating geographic mobility among regions. Math Biosci. 1995, 128: 71-91. 10.1016/0025-5564(94)00068-B.CrossRefPubMed
55.
Anderson RM, May RM: Infectious Diseases of Humans: Dynamics and Control. 1992, Oxford University Press
56.
Carrat F, Vergu E, Ferguson NM, Lemaitre M, Cauchemez S, Leach S, Valleron A-J: Time lines of infection and disease in human influenza: a review of volunteer challenge studies. Am J Epidemiol. 2008, 167: 775-785. 10.1093/aje/kwm375.CrossRefPubMed
57.
Gani J, D Jerwood D: Markov chain methods in chain binomial epidemic models. Biometrics. 1971, 27: 591-603. 10.2307/2528598.CrossRefPubMed
58.
Halloran ME, Longini IM, Struchiner CJ: Binomial and stochastic transmission models. In. Design and Analysis of Vaccine Studies, Statistics for Biology and Health. 2010, Springer, New York, 63-84.CrossRef
59.
60.
Van den Broeck W, Gioannini C, Goncalves B, Quaggiotto M, Colizza V, Vespignani A: The GLEAMviz computational tool, a publicly available software to explore realistic epidemic spreading scenarios at the global scale. BMC Infect Dis. 2011, 11: 37-10.1186/1471-2334-11-37.CrossRefPubMed
61.
Basta NE, Halloran ME, Matrajt L, Longini IM: Estimating influenza vaccine efficacy from challenge and community-based study data. Am J Epidemiol. 2008, 168: 1343-1352. 10.1093/aje/kwn259.CrossRefPubMedPubMedCentral
62.
Flahault A, de Lamballerie X, Hanslik T, Salez N: Symptomatic infections less frequent with H1N1pdm than with seasonal strains. PLoS Curr Influenza. 2009, 1: RRN1140.
63.
64.
65.
Lipsitch M, Hayden FG, Cowling BJ, Leung GM: How to maintain surveillance for novel influenza A H1N1 when there are too many cases to count. Lancet. 2009, 374: 1209-1211. 10.1016/S0140-6736(09)61377-5.CrossRefPubMed
66.
Colizza V, Vespignani A, Perra N, Poletto C, Goncalves B, Hu H, Balcan D, Paolotti D, Van den Broeck W, Tizzoni M, Bajardi P, Ramasco JJ: Estimate of novel influenza A/H1N1 cases in Mexico at the early stage of the pandemic with a spatially structured epidemic model. PLoS Curr Influenza. 2009, 1: RRN1129-doi:10.1371/currents.RRN1129CrossRef
67.
68.
Bajardi P, Poletto C, Balcan D, Hu H, Gonçalves B, Ramasco JJ, Paolotti D, Perra N, Tizzoni M, Van den Broeck W, Colizza V, Vespignani A: Modeling vaccination campaigns and the Fall/Winter 2009 activity of the new A/H1N1 influenza in the Northern Hemisphere. EHT Journal. 2009, 2: e11.
69.
Girard MP, Tam JS, Assossou OM, Kieny MP: The 2009 A (H1N1) influenza virus pandemic: A review. Vaccines. 2010, 28: 4895-4902. 10.1016/j.vaccine.2010.05.031.CrossRef
70.
Ghani AC, Donnelly CA, Cox DR, Griffin JT, Fraser C, Lam TH, Ho LM, Chan WS, Anderson RM, Hedley AJ, Leung GM: Methods for estimating the case fatality ratio for a novel, emerging infectious disease. Am J Epidemiol. 2005, 1162: 479-86.CrossRef
71.
Arinaminpathy N, McLean AR: Antiviral treatment for the control of pandemic influenza: some logistical constraints. J R Soc Interface. 2008, 5: 545-53. 10.1098/rsif.2007.1152.CrossRefPubMed
72.
Wu JT, Riley S, Fraser C, Leung GM: Reducing the impact of the next influenza pandemic using household-based public health interventions. PLoS Med. 2006, 3: e361-10.1371/journal.pmed.0030361.CrossRefPubMedPubMedCentral
73.
Jefferson T, Jones MA, Doshi P, Del Mar CB, Heneghan CJ, Hama R, Thompson MJ: Neuraminidase inhibitors for preventing and treating influenza in healthy adults and children. Cochrane Database Syst Rev. 2012, 1: CD008965.PubMed
74.
Singer AC, Howard BM, Johnson AC, Knowles CJ, Jackman S, Accinelli C, Caracciolo AB, Bernard I, Bird S, Boucard T, Boxall A, Brian JV, Cartmell E, Chubb C, Churchley J, Costigan S, Crane M, Dempsey MJ, Dorrington B, Ellor B, Fick J, Holmes J, Hutchinson T, Karcher F, Kelleher SL, Marsden P, Noone G, Nunn MA, Oxford J, Rachwal T, et al: Meeting report: risk assessment of Tamiflu use under pandemic conditions. Environ Health Perspect. 2008, 116: 1563-1567. 10.1289/ehp.11310.CrossRefPubMedPubMedCentral
75.
76.
Bajardi P, Poletto C, Ramasco JJ, Tizzoni M, Colizza V, Vespignani A: Human mobility networks, travel restrictions and the global spread of 2009 H1N1 pandemic. PLoS One. 2011, 6: e16591-10.1371/journal.pone.0016591.CrossRefPubMedPubMedCentral
77.
Cruz-Pacheco G, Duran L, Esteva L, Minzoni A, López-Cervantes M, Panayotaros P, Ahued A, Villaseñor I: Modelling of the influenza A/H1N1v outbreak in Mexico City, April-May 2009, with control sanitary measures. Euro Surveill. 2009, 14: 19254.PubMed
78.
Miller E, Hoschler K, Hardelid P, Stanford E, Andrews N, Zambon M: Incidence of 2009 pandemic A H1N1 infection in England: a cross-serological study. Lancet. 2010, 375: 1100-1108. 10.1016/S0140-6736(09)62126-7.CrossRefPubMed
79.
Ikonen N, Strengell M, Kinnunen L, Osterlund P, Pirhonen J, Broman M, Davidkin I, Ziegler T, Julkunen I: High frequency of cross-reacting antibodies against 2009 pandemic influenza A(H1N1) virus among the elderly in Finland. Euro Surveill. 2010, 15: 19478.PubMed
80.
Hancock K, Veguilla V, Lu X, Zhong W, Butler EN, Sun H, Liu F, Dong L, DeVos JR, Gargiullo PM, Brammer TL, Cox NJ, Tumpey TM, Katz JM: Cross-reactive antibody responses to the 2009 pandemic H1N1 influenza virus. N Engl J Med. 2009, 361: 1945-1952. 10.1056/NEJMoa0906453.CrossRefPubMed
81.
Allwinn R, Geiler J, Berger A, Cinatl J, Doer HW: Determination of serum antibodies against swine-origin influenza A virus H1N1/09 by immunofluorescence, haemagglutination inhibition, and by neutralization tests: how is the prevalence rate of protecting antibodies in humans?. Med Microbiol Immunol. 2010, 199: 117-121. 10.1007/s00430-010-0143-4.CrossRefPubMed
82.
83.
84.
85.
86.
Aguilera JF, Paget WJ, Mosnier A, Heijnen ML, Uphoff H, van der Velden J, Vega T, Watson JM: Heterogeneous case definitions used for the surveillance of influenza in Europe. Euro J Epidemiol. 2003, 18: 751-754.CrossRef
87.
Paget J, Marquet R, Meijer A, van der Velden K: Influenza activity in Europe during eight seasons (1999-2007): an evaluation of the indicators used to measure activity and an assessment of the timing, length and course of peak activity (spread) across Europe. BMC Infect Dis. 2007, 7: 141-10.1186/1471-2334-7-141.CrossRefPubMedPubMedCentral
88.
89.
Brooks-Pollock E, Edmunds WJ, Eames KTD: Using an online survey of healthcare-seeking behaviour to estimate the magnitude and severity of the 2009 H1N1v influenza epidemic in England. BMC Infect Dis. 2011, 11: 68-10.1186/1471-2334-11-68.CrossRefPubMedPubMedCentral
90.
91.
92.
Scalia Tomba G, Wallinga J: A simple explanation for the low impact of border control as a countermeasure to the spread of an infectious disease. Math Biosci. 2008, 214: 70-72. 10.1016/j.mbs.2008.02.009.CrossRefPubMed
93.
Cowling BJ, Lau LL, Wu P, Wong HW, Fang VJ, Riley S, Nishiura H: Entry screening to delay local transmission of 2009 pandemic influenza A (H1N1). BMC Infect Dis. 2010, 10: 82-10.1186/1471-2334-10-82.CrossRefPubMedPubMedCentral
94.
Colizza V, Vespignani A: Epidemic modeling in metapopulation systems with heterogeneous coupling pattern: theory and simulations. J Theor Biol. 2008, 251: 450-467. 10.1016/j.jtbi.2007.11.028.CrossRefPubMed
95.
96.
97.
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: 750-54. 10.1038/nature06732.CrossRefPubMed
98.
Chao DL, Halloran ME, Obenchain VJ, Longini IM: FluTE, a publicly available stochastic influenza epidemic simulation model. PloS Comput Biol. 2010, 6: e1000656-10.1371/journal.pcbi.1000656.CrossRefPubMedPubMedCentral
99.
World Health Organization: Seroepidemiological studies of pandemic influenza A(H1N1) 2009 virus. Wkly Epidemiol Rec 85. 2010, 24: 229-236.
100.
Carrat F, Pelat C, Levy-Bruhl D, Bonmarin I, Lapidus N: Planning for the next influenza H1N1 season: a modelling study. BMC Infecti Dis. 2010, 10: 301-10.1186/1471-2334-10-301.CrossRef
101.
102.
Baguelin M, Hoschler K, Stanford E, Waight P, Hardelid P, Andrews N, Miller E: Age-specific incidence of A/H1N1 2009 influenza infection in England from sequential antibody prevalence data using likelihood-based estimation. PLoS One. 2011, 6: e17074-10.1371/journal.pone.0017074.CrossRefPubMedPubMedCentral
103.
Ross T, Zimmer S, Burke D, Crevar C, Carter D, Stark J, Giles B, Zimmerman R, Ostroff S, Lee B: Seroprevalence Following the Second Wave of Pandemic 2009 H1N1 Influenza. PLoS Curr Influenza. 2010, 1: RRN1148.
104.
Wu JT, Ma ES, Lee CK, Chu DK, Ho PL, Shen AL, Ho A, Hung IF, Riley S, Ho LM, Lin CK, Tsang T, Lo SV, Lau YL, Leung GM, Cowling BJ, Malik Peiris JS: The infection attack rate and severity of 2009 pandemic H1N1 influenza in Hong Kong. Clin Infect Dis. 2010, 51: 1184-10.1086/656740.CrossRefPubMedPubMedCentral
105.
Chao DL, Matrajt L, Basta NE, Sugimoto JD, Dean B, Bagwell DA, Oiulfstad B, Halloran ME, Longini IM: Planning for the control of pandemic influenza A(H1N1) in Los Angeles County and the United States. Pract Epidemiol. 2011, doi:10.1093/aje/kwq497
106.
Ajelli M, Merler S, Pugliese A, Rizzo C: Model predictions and evaluation of possible control strategies for the 2009 A/H1N1v influenza pandemic in Italy. Epidemiol Infect. 2011, 139: 68-10.1017/S0950268810001317.CrossRefPubMed
107.
Nishiura H, Chowell G, Castillo-Chavez C: Did modeling overestimate the transmission potential of pandemic (H1N1-2009)? Sample size estimation for post-epidemic seroepidemiological studies. PLoS One. 2011, 6: e17908-10.1371/journal.pone.0017908.CrossRefPubMedPubMedCentral
108.
Grais RF, Eliis JH, Kress A, Glass GE: Modeling the spread of annual influenza epidemics in the U.S.: The potential role of air travel. Health Care Manag Sci. 2004, 7: 127.CrossRefPubMed
Metadata
Title
Real-time numerical forecast of global epidemic spreading: case study of 2009 A/H1N1pdm
Authors
Michele Tizzoni
Paolo Bajardi
Chiara Poletto
José J Ramasco
Duygu Balcan
Bruno Gonçalves
Nicola Perra
Vittoria Colizza
Alessandro Vespignani
Publication date
01-12-2012
Publisher
BioMed Central
Published in
BMC Medicine / Issue 1/2012
Electronic ISSN: 1741-7015
DOI
https://doi.org/10.1186/1741-7015-10-165

Other articles of this Issue 1/2012

BMC Medicine 1/2012 Go to the issue

Research article

Toll-like receptor 4 signaling promotes epithelial-mesenchymal transition in human hepatocellular carcinoma induced by lipopolysaccharide

Research article

Pinocembrin protects against β-amyloid-induced toxicity in neurons through inhibiting receptor for advanced glycation end products (RAGE)-independent signaling pathways and regulating mitochondrion-mediated apoptosis

Commentary

Location, location, location: the BRMS1 protein and melanoma progression

Minireview

Personalized medicine in multiple sclerosis: hope or reality?

Commentary

The regulation of mobile health applications

Research article

Pre-cooling for endurance exercise performance in the heat: a systematic review