IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0141147.html
   My bibliography  Save this article

Modeling the Impact of Alternative Immunization Strategies: Using Matrices as Memory Lanes

Author

Listed:
  • Wladimir J Alonso
  • Maia A Rabaa
  • Ricardo Giglio
  • Mark A Miller
  • Cynthia Schuck-Paim

Abstract

Existing modeling approaches are divided between a focus on the constitutive (micro) elements of systems or on higher (macro) organization levels. Micro-level models enable consideration of individual histories and interactions, but can be unstable and subject to cumulative errors. Macro-level models focus on average population properties, but may hide relevant heterogeneity at the micro-scale. We present a framework that integrates both approaches through the use of temporally structured matrices that can take large numbers of variables into account. Matrices are composed of several bidimensional (time×age) grids, each representing a state (e.g. physiological, immunological, socio-demographic). Time and age are primary indices linking grids. These matrices preserve the entire history of all population strata and enable the use of historical events, parameters and states dynamically in the modeling process. This framework is applicable across fields, but particularly suitable to simulate the impact of alternative immunization policies. We demonstrate the framework by examining alternative strategies to accelerate measles elimination in 15 developing countries. The model recaptured long-endorsed policies in measles control, showing that where a single routine measles-containing vaccine is employed with low coverage, any improvement in coverage is more effective than a second dose. It also identified an opportunity to save thousands of lives in India at attractively low costs through the implementation of supplementary immunization campaigns. The flexibility of the approach presented enables estimating the effectiveness of different immunization policies in highly complex contexts involving multiple and historical influences from different hierarchical levels.

Suggested Citation

  • Wladimir J Alonso & Maia A Rabaa & Ricardo Giglio & Mark A Miller & Cynthia Schuck-Paim, 2015. "Modeling the Impact of Alternative Immunization Strategies: Using Matrices as Memory Lanes," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-11, October.
  • Handle: RePEc:plo:pone00:0141147
    DOI: 10.1371/journal.pone.0141147
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0141147
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0141147&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0141147?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Robert E. Hall & Charles I. Jones, 2007. "The Value of Life and the Rise in Health Spending," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 122(1), pages 39-72.
    2. B. T. Grenfell & O. N. Bjørnstad & J. Kappey, 2001. "Travelling waves and spatial hierarchies in measles epidemics," Nature, Nature, vol. 414(6865), pages 716-723, December.
    3. Carol Y. Lin, 2008. "Modeling Infectious Diseases in Humans and Animals by KEELING, M. J. and ROHANI, P," Biometrics, The International Biometric Society, vol. 64(3), pages 993-993, September.
    4. Keith Task & Maria Jaramillo & Ipsita Banerjee, 2012. "Population Based Model of Human Embryonic Stem Cell (hESC) Differentiation during Endoderm Induction," PLOS ONE, Public Library of Science, vol. 7(3), pages 1-10, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wan Yang & Liang Wen & Shen-Long Li & Kai Chen & Wen-Yi Zhang & Jeffrey Shaman, 2017. "Geospatial characteristics of measles transmission in China during 2005−2014," PLOS Computational Biology, Public Library of Science, vol. 13(4), pages 1-21, April.
    2. Gonzalez-Eiras, Martín & Niepelt, Dirk, 2012. "Ageing, government budgets, retirement, and growth," European Economic Review, Elsevier, vol. 56(1), pages 97-115.
    3. Ho, Sy-Hoa & OUEGHLISSI, Rim & EL FERKTAJI, Riadh, 2019. "The dynamic causality between ESG and economic growth: Evidence from panel causality analysis," MPRA Paper 95390, University Library of Munich, Germany.
    4. Volker Grossmann & Johannes Schünemann & Holger Strulik, 2024. "Fair Pension Policies with Occupation-Specific Ageing," The Economic Journal, Royal Economic Society, vol. 134(663), pages 2835-2875.
    5. Steve Newbold & Charles Griffiths & Christopher C. Moore & Ann Wolverton & Elizabeth Kopits, 2010. "The "Social Cost of Carbon" Made Simple," NCEE Working Paper Series 201007, National Center for Environmental Economics, U.S. Environmental Protection Agency, revised Aug 2010.
    6. Herrendorf, Berthold & Rogerson, Richard & Valentinyi, Ákos, 2014. "Growth and Structural Transformation," Handbook of Economic Growth, in: Philippe Aghion & Steven Durlauf (ed.), Handbook of Economic Growth, edition 1, volume 2, chapter 6, pages 855-941, Elsevier.
    7. Johan Gustafsson, 2021. "Age-Targeted Income Taxation, Labor Supply, and Retirement," CESifo Working Paper Series 8988, CESifo.
    8. Wei Zhong, 2017. "Simulating influenza pandemic dynamics with public risk communication and individual responsive behavior," Computational and Mathematical Organization Theory, Springer, vol. 23(4), pages 475-495, December.
    9. De Martino, Giuseppe & Spina, Serena, 2015. "Exploiting the time-dynamics of news diffusion on the Internet through a generalized Susceptible–Infected model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 634-644.
    10. D. Dragone & H. Strulik, 2017. "Human Health and Aging over an Infinite Time Horizon," Working Papers wp1104, Dipartimento Scienze Economiche, Universita' di Bologna.
    11. FUKAI Taiyo & ICHIMURA Hidehiko & KANAZAWA Kyogo, 2018. "Quantifying Health Shocks over the Life Cycle," Discussion papers 18014, Research Institute of Economy, Trade and Industry (RIETI).
    12. Groneck, Max & Ludwig, Alexander & Zimper, Alexander, 2016. "A life-cycle model with ambiguous survival beliefs," Journal of Economic Theory, Elsevier, vol. 162(C), pages 137-180.
    13. Alex R. Horenstein & Manuel S. Santos, 2012. "A Cross-Country Analysis of Health Care Expenditures," Working Papers 2013-05, University of Miami, Department of Economics.
    14. Guido M. Kuersteiner & Ingmar R. Prucha, 2020. "Dynamic Spatial Panel Models: Networks, Common Shocks, and Sequential Exogeneity," Econometrica, Econometric Society, vol. 88(5), pages 2109-2146, September.
    15. Strulik, Holger, 2018. "The return to education in terms of wealth and health," The Journal of the Economics of Ageing, Elsevier, vol. 12(C), pages 1-14.
    16. Tomasz Rokicki & Aleksandra Perkowska & Marcin Ratajczak, 2020. "Differentiation in Healthcare Financing in EU Countries," Sustainability, MDPI, vol. 13(1), pages 1-17, December.
    17. Jeremy Greenwood & Nezih Guner & Karen A. Kopecky, 2022. "The Downward Spiral," NBER Working Papers 29764, National Bureau of Economic Research, Inc.
    18. Maria Jaramillo & Shibin Mathew & Keith Task & Sierra Barner & Ipsita Banerjee, 2014. "Potential for Pancreatic Maturation of Differentiating Human Embryonic Stem Cells Is Sensitive to the Specific Pathway of Definitive Endoderm Commitment," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-14, April.
    19. Jagrič, Timotej & Brown, Christine & Boyce, Tammy & Jagrič, Vita, 2021. "The impact of the health-care sector on national economies in selected European countries," Health Policy, Elsevier, vol. 125(1), pages 90-97.
    20. Ofosuhene O Apenteng & Noor Azina Ismail, 2014. "The Impact of the Wavelet Propagation Distribution on SEIRS Modeling with Delay," PLOS ONE, Public Library of Science, vol. 9(6), pages 1-9, June.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0141147. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.