IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v16y1969i4pb190-b211.html
   My bibliography  Save this article

An Optimization Model of Tuberculosis Epidemiology

Author

Listed:
  • Charles Reveller

    (Department of Environmental Systems Engineering, Cornell University)

  • Walter Lynn

    (Department of Environmental Systems Engineering, Cornell University)

  • Floyd Feldmann

    (Department of Public Health, Cornell Medical College)

Abstract

The problems of management of tuberculosis in developing nations are studied utilizing the tools of systems analysis. The tuberculosis system consists of interacting components which are the "states of nature" of the disease. The interaction of these components determine the future state of the disease. Controls in the form of therapy, vaccinations or prophylaxis may be superimposed on the natural processes, thus altering the future course of the disease. A descriptive mathematical model describing the flows between the various categories is used to predict the trends both with and without intervention. An optimization model is derived from the descriptive model under the assumption that a program of reduction of active cases has been specified. The optimization model selects the forms of control which achieve the specified reduction program at least cost. Optimization is accomplished via linear programming. The model is general in that the parameters, costs and initial conditions may be varied for different situations. The descriptive mathematical model and the optimization model which determines the most efficient controls are intended to improve decision-making in public health management of tuberculosis.

Suggested Citation

  • Charles Reveller & Walter Lynn & Floyd Feldmann, 1969. "An Optimization Model of Tuberculosis Epidemiology," Management Science, INFORMS, vol. 16(4), pages 190-211, December.
    • Handle: RePEc:inm:ormnsc:v:16:y:1969:i:4:p:b190-b211
    DOI: 10.1287/mnsc.16.4.B190
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.16.4.B190
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mnsc.16.4.B190?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
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Anke Richter & Margaret L. Brandeau & Douglas K. Owens, 1999. "An Analysis of Optimal Resource Allocation for Prevention of Infection with Human Immunodeficiency Virus (HIV) in Injection Drug Users and Non-Users," Medical Decision Making, , vol. 19(2), pages 167-179, April.
    2. Linus Nyiwul, 2021. "Epidemic Control and Resource Allocation: Approaches and Implications for the Management of COVID-19," Studies in Microeconomics, , vol. 9(2), pages 283-305, December.
    3. Benjamin Armbruster & Margaret Brandeau, 2007. "Contact tracing to control infectious disease: when enough is enough," Health Care Management Science, Springer, vol. 10(4), pages 341-355, December.
    4. Flessa, Steffen, 2003. "Priorities and allocation of health care resources in developing countries: A case-study from the Mtwara region, Tanzania," European Journal of Operational Research, Elsevier, vol. 150(1), pages 67-80, October.
    5. Duijzer, Lotty Evertje & van Jaarsveld, Willem & Dekker, Rommert, 2018. "Literature review: The vaccine supply chain," European Journal of Operational Research, Elsevier, vol. 268(1), pages 174-192.
    6. Biswas, Debajyoti & Alfandari, Laurent, 2022. "Designing an optimal sequence of non‐pharmaceutical interventions for controlling COVID-19," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1372-1391.
    7. Brandeau, Margaret L. & Zaric, Gregory S. & Richter, Anke, 2003. "Resource allocation for control of infectious diseases in multiple independent populations: beyond cost-effectiveness analysis," Journal of Health Economics, Elsevier, vol. 22(4), pages 575-598, July.
    8. Choudhury, Nishat Alam & Ramkumar, M. & Schoenherr, Tobias & Singh, Shalabh, 2023. "The role of operations and supply chain management during epidemics and pandemics: Potential and future research opportunities," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).

    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:inm:ormnsc:v:16:y:1969:i:4:p:b190-b211. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.