The impact of school closures on pandemic influenza:Assessing potential repercussions using a seasonal SIR model

Sherry Towers; Katia Vogt Geisse; Chia-Chun Tsai; Qing Han; Zhilan Feng

doi:10.3934/mbe.2012.9.413

Article Contents

2012, Volume 9, Issue 2: 413-430. Doi: 10.3934/mbe.2012.9.413

This issue Previous Article Impact of heterogeneity on the dynamics of an SEIR epidemic model Next Article A mutualism-parasitism system modeling host and parasite with mutualism at low density

The impact of school closures on pandemic influenza: Assessing potential repercussions using a seasonal SIR model

1.
Department of Mathematics, Purdue University, West Lafayette, IN 47907
2.
Department of Forestry and Natural Resources, Purdue University, West Lafayette, IN 47907

Received: June 2011

Revised: November 2011

Published: February 2012

Abstract Related Papers Cited by

Abstract

When a new pandemic influenza strain has been identified, mass-production of vaccines can take several months, and antiviral drugs are expensive and usually in short supply. Social distancing measures, such as school closures, thus seem an attractive means to mitigate disease spread. However, the transmission of influenza is seasonal in nature, and as has been noted in previous studies, a decrease in the average transmission rate in a seasonal disease model may result in a larger final size. In the studies presented here, we analyze a hypothetical pandemic using a SIR epidemic model with time- and age-dependent transmission rates; using this model we assess and quantify, for the first time, the the effect of the timing and length of widespread school closures on influenza pandemic final size and average peak time.
We find that the effect on pandemic progression strongly depends on the timing of the start of the school closure. For instance, we determine that school closures during a late spring wave of an epidemic can cause a pandemic to become up to 20% larger, but have the advantage that the average time of the peak is shifted by up to two months, possibly allowing enough time for development of vaccines to mitigate the larger size of the epidemic. Our studies thus suggest that when heterogeneity in transmission is a significant factor, decisions of public health policy will be particularly important as to how control measures such as school closures should be implemented.

Keywords:

Mathematics Subject Classification: Primary: 92D30.

Citation:

Related Papers

Cited by

References

[1]	W. J. Alonso, C. Viboud, L. Simonsen, E. W. Hirano, L. Z. Daufenbach and M. A. Miller, Seasonality of influenza in Brazil: A traveling wave from the Amazon to the Subtropics, Am. J. Epidemiol., 165 (2007), 1434-1442.doi: 10.1093/aje/kwm012.
[2]	R. Anderson and R. M. May, "Infectious Diseases of Humans: Dynamics and Control," Oxford University Press, New York, 1991.
[3]	N. Bacaër and E. H. Ait Dads, Genealogy with seasonality, the basic reproduction number, and the influenza pandemic, J. Math. Biol., 62 (2011), 741-762.
[4]	N. Bacaër and M. G. M. Gomes, On the final size of epidemics with seasonality, Bulletin of Mathematical Biology, 71 (2009), 1954-1966.doi: 10.1007/s11538-009-9433-7.
[5]	N. Bacaër, Approximation of the basic reproduction number $R_0$ for vector-borne diseases with a periodic vector population, Bull. Math. Biol., 69 (2007), 1067-1091.doi: 10.1007/s11538-006-9166-9.
[6]	N. Bacaër and S. Guernaoui, The epidemic threshold of vector-borne diseases with seasonality, J. Math. Biol., 53 (2006), 421-436.doi: 10.1007/s00285-006-0015-0.
[7]	S. Cauchemez, N. M. Ferguson, C. Wachtel, A. Tegnell, G. Saour, B. Duncan and A. Nicoll, Closure of schools during an influenza pandemic, Lancet. Infect. Dis., 9 (2009), 473-481.doi: 10.1016/S1473-3099(09)70176-8.
[8]	S. Cauchemez, A.-J. Valleron, P.-Y. Boëlle, A. Flahault and N. M. Ferguson, Estimating the impact of school closure on influenza transmission from Sentinel data, Nature, 452 (2008), 750-754.doi: 10.1038/nature06732.
[9]	V. Colizza, A. Barrat, M. Barthelemy, A.-J. Valleron and A. Vespignani, Modeling the worldwide spread of pandemic influenza: Baseline case and containment interventions, PLoS Med., 4 (2007), e13.doi: 10.1371/journal.pmed.0040013.
[10]	S. Y. Del Valle, P. D. Stroud and S. M. Mniszewski, Dynamic contact patterns and social structure, in "Realistic Social Networks in Social Networks: Development, Evaluation, and Influence," Nova Science Publishers, (2009), 201-216.
[11]	S. F. Dowell, Seasonal variation in host susceptibility and cycles of certain infectious diseases, Emerg. Infec. Dis., 7 (2001), 369-374.
[12]	J. Dushoff, J. B. Plotkin, C. Viboud, D. J. Earn and L. Simonsen, Mortality due to influenza in the United States, American Journal of Epidemiology, 163 (2006), 181-187.
[13]	Z. Feng, S. Towers and Y. Yang, Modeling the effects of vaccination and treatment on pandemic influenza, American Association of Pharmaceutical Science Journal, 13 (2011), 427-437.
[14]	N. M. Ferguson, D. A. T. Cummings, C. Fraser, J. C. Cajka, P. C. Cooley and D. S. Burke, Strategies for mitigating an influenza pandemic, Nature, 442 (2006), 448-452.doi: 10.1038/nature04795.
[15]	N. M. Ferguson, A .P. Galvani and R. M. Bush, Ecological and immunological determinants of influenza evolution, Nature, 422 (2003), 428-433.doi: 10.1038/nature01509.
[16]	C. Fraser, et al., Pandemic potential of a strain of influenza A(H1N1): Early findings, Science, 324 (2009), 1557-1561.doi: 10.1126/science.1176062.
[17]	T. C. Germann, K. Kadau, I. M. Longini and C. A. Macken, Mitigation strategies for pandemic influenza in the United States, PNAS, 103 (2006), 5935-5940.doi: 10.1073/pnas.0601266103.
[18]	R. J. Glass, L. M. Glass, W. E. Beyeler and J. H. Min, Targeted social distancing design for pandemic influenza, Emerg. Infect. Dis., 12 (2006), 1671-1681.doi: 10.3201/eid1211.060255.
[19]	M. Z. Gojovic, B. Sander, D. Fisman, M. D. Krahn and C. T. Bauch, Modelling mitigation strategies for pandemic (H1N1) 2009, CMAJ, 181 (2009), 673-680.doi: 10.1503/cmaj.091641.
[20]	N. Halder, J. Kelso and G. Milne, Analysis of the effectiveness of interventions used during the 2009 A/H1N1 influenza pandemic, BMC Public Health, 10 (2010), 168.doi: 10.1186/1471-2458-10-168.
[21]	S. D. Holmberg, C. M. Layton, G. S. Ghneim and D. K. Wagener, State plans for containment of pandemic influenza, Emerg. Infect. Dis., 12 (2006), 1414-1417.doi: 10.3201/eid1209.060369.
[22]	L. Kahn, Pandemic influenza school closure policies, Emerg. Infect. Dis., 13 (2007), 344-345.doi: 10.3201/eid1302.061109.
[23]	J. K. Kelso, G. J. Milne and H. Kelly, Simulation suggests that rapid activation of social distancing can arrest epidemic development due to a novel strain of influenza, BMC Public Health, 9 (2009).
[24]	B. Y. Lee, S. T. Brown, P. Cooley, M. A. Potter, W. D. Wheaton, R. E. Voorhees, S. Stebbins, J. J. Grefenstette, S. M. Zimmer, R. K. Zimmerman, T. M. Assi, R. R. Bailey, D. K. Wagener and D. S. Burke, Simulating school closure strategies to mitigate an influenza epidemic, Journal of Public Health Management and Practice, 16 (2010), 252-261.
[25]	E. Lofgren, N.H . Fefferman, Y. N. Naumov, J. Gorski and E. N. Naumova, Influenza seasonality: Underlying causes and modeling theories, J. Virol., 81 (2007), 5429-5436.doi: 10.1128/JVI.01680-06.
[26]	A. C. Lowen, S. Mubareka, J. Steel and P. Palese, Influenza virus transmission is dependent on relative humidity and temperature, PLoS Pathogens, 4 (2007), 151-158.doi: 10.1371/journal.ppat.0030151.
[27]	J. Medlock and A. P. Galvani, Optimizing influenza vaccine distribution, Science, 325 (2009), 1705-1708.doi: 10.1126/science.1175570.
[28]	G. J. Milne, J. K. Kelso, H. A. Kelly, S. T. Huband and J. McVernon, A small community model for the transmission of infectious diseases: Comparison of school closure as an intervention in individual-based models of an influenza pandemic, PLoS ONE, 3 (2008), e4005.doi: 10.1371/journal.pone.0004005.
[29]	J. Mossong, N. Hens, M. Jit, P. Beutels, K. Auranen, R. Mikolajczyk, M. Massari, S. Salmaso, G. Scalia Tomba, J. Wallinga, J. Heijne, M. Sadkowska-Todys, M. Rosinska and W. J. Edmunds, Social contacts and mixing patterns relevant to the spread of infectious diseases, PLoS Med, 5 (2008), e74.doi: 10.1371/journal.pmed.0050074.
[30]	B. Sander, A. Nizam, L. P. Garrison, M. J. Postma, M. E. Halloran and I. M. Longini, Economic evaluation of influenza pandemic mitigation strategies in the United States using a stochastic microsimulation transmission model, Value in Health, 12 (2009), 226.doi: 10.1111/j.1524-4733.2008.00437.x.
[31]	S. Towers and Z. Feng, Pandemic H1N1 influenza: Predicting the course of pandemic and assessing the efficacy of the planned vaccination programme in the United States, Eurosurveillance, 14 (2009).
[32]	S. Towers, K. Vogt Geisse, Y. Zheng and Z. Feng, Antiviral treatment for pandemic influenza: Assessing potential repercussions using a seasonally forced SIR model, Journal of Theoretical Biology, 289 (2011), 259-268.doi: 10.1016/j.jtbi.2011.08.011.
[33]	U.S. 2000 Census. Available from: http://www.census.gov.
[34]	W. Wang and X.-Q. Zhang, Threshold dynamics for compartmental epidemic models in periodic environments, J. Dyn. Diff. Equat., 20 (2008), 699-717.doi: 10.1007/s10884-008-9111-8.
[35]	World Health Organization, Nonpharmaceutical interventions for pandemic influenza, national and community measures, Emerg. Infec. Dis., 12 (2006), 88-94.
[36]	Y. Yang, Jonathan D. Sugimoto, M. E. Halloran, N. E. Basta, D. L. Chao, L. Matrajt, G. Potter, E. Kenah and I. M. Longini Jr., The transmissibility and control of pandemic influenza A(H1N1) virus, Science, 326 (2009), 729-733.doi: 10.1126/science.1177373.