IDEAS home Printed from https://ideas.repec.org/a/kap/hcarem/v18y2015i2p205-217.html
   My bibliography  Save this article

Impact of combined vector-control and vaccination strategies on transmission dynamics of dengue fever: a model-based analysis

Author

Listed:
  • Gerhart Knerer
  • Christine Currie
  • Sally Brailsford

Abstract

Dengue fever is a vector-borne disease prevalent in tropical and subtropical regions. It is an important public health problem with a considerable and often under-valued disease burden in terms of frequency, cost and quality-of-life. Recent literature reviews have documented the development of mathematical models of dengue fever both to identify important characteristics for future model development as well as to assess the impact of dengue control interventions. Such reviews highlight the importance of short-term cross-protection; antibody-dependent enhancement; and seasonality (in terms of both favourable and unfavourable conditions for mosquitoes). The compartmental model extends work by Bartley (2002) and combines the following factors: seasonality, age-structure, consecutive infection by all four serotypes, cross-protection and immune enhancement, as well as combined vector-host transmission. The model is used to represent dengue transmission dynamics using parameters appropriate for Thailand and to assess the potential impact of combined vector-control and vaccination strategies including routine and catch-up vaccination strategies on disease dynamics. When seasonality and temporary cross-protection between serotypes are included, the model is able to approximate the observed incidence of dengue fever in Thailand. We find vaccination to be the most effective single intervention, albeit with imperfect efficacy (30.2 %) and limited duration of protection. However, in combination, control interventions and vaccination exhibit a marked impact on dengue fever transmission. This study shows that an imperfect vaccine can be a useful weapon in reducing disease spread within the community, although it will be most effective when promoted as one of several strategies for combating dengue fever transmission. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • Gerhart Knerer & Christine Currie & Sally Brailsford, 2015. "Impact of combined vector-control and vaccination strategies on transmission dynamics of dengue fever: a model-based analysis," Health Care Management Science, Springer, vol. 18(2), pages 205-217, June.
    • Handle: RePEc:kap:hcarem:v:18:y:2015:i:2:p:205-217
    DOI: 10.1007/s10729-013-9263-x
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10729-013-9263-x
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10729-013-9263-x?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. Sébastien Marcombe & Romain Blanc Mathieu & Nicolas Pocquet & Muhammad-Asam Riaz & Rodolphe Poupardin & Serge Sélior & Frédéric Darriet & Stéphane Reynaud & André Yébakima & Vincent Corbel & Jean-Phil, 2012. "Insecticide Resistance in the Dengue Vector Aedes aegypti from Martinique: Distribution, Mechanisms and Relations with Environmental Factors," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-11, February.
    3. Coutinho, F.A. B. & Burattini, M.N. & Lopez, L.F. & Massad, E., 2005. "An approximate threshold condition for non-autonomous system: An application to a vector-borne infection," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 70(3), pages 149-158.
    4. Hazhir Rahmandad & John Sterman, 2008. "Heterogeneity and Network Structure in the Dynamics of Diffusion: Comparing Agent-Based and Differential Equation Models," Management Science, INFORMS, vol. 54(5), pages 998-1014, May.
    5. Eduardo A Undurraga & Yara A Halasa & Donald S Shepard, 2013. "Use of Expansion Factors to Estimate the Burden of Dengue in Southeast Asia: A Systematic Analysis," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 7(2), pages 1-15, February.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Tay, Chai Jian & Fakhruddin, Muhammad & Fauzi, Ilham Saiful & Teh, Su Yean & Syamsuddin, Muhammad & Nuraini, Nuning & Soewono, Edy, 2022. "Dengue epidemiological characteristic in Kuala Lumpur and Selangor, Malaysia," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 194(C), pages 489-504.
    2. Abidemi, A. & Abd Aziz, M.I. & Ahmad, R., 2020. "Vaccination and vector control effect on dengue virus transmission dynamics: Modelling and simulation," Chaos, Solitons & Fractals, Elsevier, vol. 133(C).
    3. Gerhart Knerer & Christine S M Currie & Sally C Brailsford, 2020. "The economic impact and cost-effectiveness of combined vector-control and dengue vaccination strategies in Thailand: results from a dynamic transmission model," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 14(10), pages 1-32, October.
    4. Anggriani, N. & Tasman, H. & Ndii, M.Z. & Supriatna, A.K. & Soewono, E. & Siregar, E, 2019. "The effect of reinfection with the same serotype on dengue transmission dynamics," Applied Mathematics and Computation, Elsevier, vol. 349(C), pages 62-80.

    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. Lewe, J.-H. & Hivin, L.F. & Mavris, D.N., 2014. "A multi-paradigm approach to system dynamics modeling of intercity transportation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 71(C), pages 188-202.
    2. Peres, Renana & Muller, Eitan & Mahajan, Vijay, 2010. "Innovation diffusion and new product growth models: A critical review and research directions," International Journal of Research in Marketing, Elsevier, vol. 27(2), pages 91-106.
    3. 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.
    4. Ellinas, Christos & Allan, Neil & Johansson, Anders, 2016. "Project systemic risk: Application examples of a network model," International Journal of Production Economics, Elsevier, vol. 182(C), pages 50-62.
    5. Cowan, Kelly R. & Daim, Tugrul U., 2011. "Review of technology acquisition and adoption research in the energy sector," Technology in Society, Elsevier, vol. 33(3), pages 183-199.
    6. Joseph H. Cook, 2013. "Principles and standards for benefit–cost analysis of public health preparedness and pandemic mitigation programs," Chapters, in: Scott O. Farrow & Richard Zerbe, Jr. (ed.), Principles and Standards for Benefit–Cost Analysis, chapter 3, pages 110-152, Edward Elgar Publishing.
    7. Lu, Xuefei & Borgonovo, Emanuele, 2023. "Global sensitivity analysis in epidemiological modeling," European Journal of Operational Research, Elsevier, vol. 304(1), pages 9-24.
    8. Gerhart Knerer & Christine S M Currie & Sally C Brailsford, 2020. "The economic impact and cost-effectiveness of combined vector-control and dengue vaccination strategies in Thailand: results from a dynamic transmission model," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 14(10), pages 1-32, October.
    9. Nguyen, Le Khanh Ngan & Howick, Susan & Megiddo, Itamar, 2024. "A framework for conceptualising hybrid system dynamics and agent-based simulation models," European Journal of Operational Research, Elsevier, vol. 315(3), pages 1153-1166.
    10. McKenna, Claire & Chalabi, Zaid & Epstein, David & Claxton, Karl, 2010. "Budgetary policies and available actions: A generalisation of decision rules for allocation and research decisions," Journal of Health Economics, Elsevier, vol. 29(1), pages 170-181, January.
    11. Santos, Mário & Bastos, Rita & Cabral, João Alexandre, 2013. "Converting conventional ecological datasets in dynamic and dynamic spatially explicit simulations: Current advances and future applications of the Stochastic Dynamic Methodology (StDM)," Ecological Modelling, Elsevier, vol. 258(C), pages 91-100.
    12. Wouter Vermeer & Otto Koppius & Peter Vervest, 2018. "The Radiation-Transmission-Reception (RTR) model of propagation: Implications for the effectiveness of network interventions," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-21, December.
    13. Lei Xu & Ronggui Ding & Lei Wang, 2022. "How to facilitate knowledge diffusion in collaborative innovation projects by adjusting network density and project roles," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(3), pages 1353-1379, March.
    14. Joseph L Servadio & Gustavo Machado & Julio Alvarez & Francisco Edilson de Ferreira Lima Júnior & Renato Vieira Alves & Matteo Convertino, 2020. "Information differences across spatial resolutions and scales for disease surveillance and analysis: The case of Visceral Leishmaniasis in Brazil," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-17, July.
    15. Jan Kwakkel & Willem Auping, 2021. "Reaction: A commentary on Lustick and Tetlock (2021)," Futures & Foresight Science, John Wiley & Sons, vol. 3(2), June.
    16. Tesfatsion, Leigh, 2017. "Modeling Economic Systems as Locally-Constructive Sequential Games," ISU General Staff Papers 201704300700001022, Iowa State University, Department of Economics.
    17. Abedi, Vahideh Sadat, 2019. "Compartmental diffusion modeling: Describing customer heterogeneity & communication network to support decisions for new product introductions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    18. Lixin Zhou & Jie Lin & Yanfeng Li & Zhenyu Zhang, 2020. "Innovation Diffusion of Mobile Applications in Social Networks: A Multi-Agent System," Sustainability, MDPI, vol. 12(7), pages 1-17, April.
    19. Stephanie Earnshaw & Katherine Hicks & Anke Richter & Amanda Honeycutt, 2007. "A linear programming model for allocating HIV prevention funds with state agencies: a pilot study," Health Care Management Science, Springer, vol. 10(3), pages 239-252, September.
    20. Amini, Mehdi & Wakolbinger, Tina & Racer, Michael & Nejad, Mohammad G., 2012. "Alternative supply chain production–sales policies for new product diffusion: An agent-based modeling and simulation approach," European Journal of Operational Research, Elsevier, vol. 216(2), pages 301-311.

    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:kap:hcarem:v:18:y:2015:i:2:p:205-217. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.