IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v290y2016icp1-8.html
   My bibliography  Save this article

Analysis of the vectorial capacity of vector-borne diseases using moment-generating functions

Author

Listed:
  • Villela, Daniel A.M.

Abstract

The vectorial capacity of a mosquito species that is a disease-vector indicates the expected number of infectious bites given by all mosquitoes infected from biting a single infected human individual, assuming perfect transmissions between humans and vectors. Assessing this number for different transmitting species of the same disease, such as dengue or malaria, expresses how capable these species are of spreading the disease. We describe the vectorial capacity as a random process and present a model for analyzing its probability distribution. Our stochastic model permits us to obtain the moment-generating function for the distribution of the vectorial capacity and, under reasonable assumptions, the probability distribution itself. A stochastic modeling framework is helpful for analyzing the dynamics of disease spreading, such as when performing sensitivity analysis.

Suggested Citation

  • Villela, Daniel A.M., 2016. "Analysis of the vectorial capacity of vector-borne diseases using moment-generating functions," Applied Mathematics and Computation, Elsevier, vol. 290(C), pages 1-8.
    • Handle: RePEc:eee:apmaco:v:290:y:2016:i:c:p:1-8
    DOI: 10.1016/j.amc.2016.05.026
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300316303356
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.amc.2016.05.026?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. Miranda Chan & Michael A Johansson, 2012. "The Incubation Periods of Dengue Viruses," PLOS ONE, Public Library of Science, vol. 7(11), pages 1-7, November.
    2. Ball, Frank & Donnelly, Peter, 1995. "Strong approximations for epidemic models," Stochastic Processes and their Applications, Elsevier, vol. 55(1), pages 1-21, January.
    3. Daniel A M Villela & Claudia T Codeço & Felipe Figueiredo & Gabriela A Garcia & Rafael Maciel-de-Freitas & Claudio J Struchiner, 2015. "A Bayesian Hierarchical Model for Estimation of Abundance and Spatial Density of Aedes aegypti," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-17, April.
    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. Zan, Yongli, 2018. "DSIR double-rumors spreading model in complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 110(C), pages 191-202.

    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. Víctor Hugo Peña-García & Omar Triana-Chávez & Ana María Mejía-Jaramillo & Francisco J. Díaz & Andrés Gómez-Palacio & Sair Arboleda-Sánchez, 2016. "Infection Rates by Dengue Virus in Mosquitoes and the Influence of Temperature May Be Related to Different Endemicity Patterns in Three Colombian Cities," IJERPH, MDPI, vol. 13(7), pages 1-16, July.
    2. Simon, Matthieu, 2020. "SIR epidemics with stochastic infectious periods," Stochastic Processes and their Applications, Elsevier, vol. 130(7), pages 4252-4274.
    3. Barbour, A. D. & Utev, Sergey, 2004. "Approximating the Reed-Frost epidemic process," Stochastic Processes and their Applications, Elsevier, vol. 113(2), pages 173-197, October.
    4. Abdalgader, Tarteel & Banerjee, Malay & Zhang, Lai, 2022. "Spatially weak syncronization of spreading pattern between Aedes Albopictus and dengue fever," Ecological Modelling, Elsevier, vol. 473(C).
    5. Terrazas-Santamaria Diana & Mendoza-Palacios Saul & Berasaluce-Iza Julen, 2023. "An Alternative Approach to Frequency of Patent Technology Codes: The Case of Renewable Energy Generation," Economics - The Open-Access, Open-Assessment Journal, De Gruyter, vol. 17(1), pages 1-14, January.
    6. Ball, Frank & Neal, Peter, 2003. "The great circle epidemic model," Stochastic Processes and their Applications, Elsevier, vol. 107(2), pages 233-268, October.
    7. Kazi Mizanur Rahman & Yushuf Sharker & Reza Ali Rumi & Mahboob-Ul Islam Khan & Mohammad Sohel Shomik & Muhammad Waliur Rahman & Sk Masum Billah & Mahmudur Rahman & Peter Kim Streatfield & David Harley, 2020. "An Association between Rainy Days with Clinical Dengue Fever in Dhaka, Bangladesh: Findings from a Hospital Based Study," IJERPH, MDPI, vol. 17(24), pages 1-9, December.
    8. Mateus C, Rafael & Zuluaga, Susana Alvarez & Orozco, Mariajose Franco & Marín, Paula Alejandra Escudero, 2021. "Modeling the propagation of the Dengue, Zika and Chikungunya virus in the city of Bello using Agent-Based Modeling and Simulation," OSF Preprints wmxzd, Center for Open Science.
    9. Hao Gui & Sylvia Gwee & Jiayun Koh & Junxiong Pang, 2021. "Weather Factors Associated with Reduced Risk of Dengue Transmission in an Urbanized Tropical City," IJERPH, MDPI, vol. 19(1), pages 1-17, December.
    10. Bao-Linh Tran & Wei-Chun Tseng & Chi-Chung Chen & Shu-Yi Liao, 2020. "Estimating the Threshold Effects of Climate on Dengue: A Case Study of Taiwan," IJERPH, MDPI, vol. 17(4), pages 1-17, February.
    11. Lingcai Kong & Jinfeng Wang & Zhongjie Li & Shengjie Lai & Qiyong Liu & Haixia Wu & Weizhong Yang, 2018. "Modeling the Heterogeneity of Dengue Transmission in a City," IJERPH, MDPI, vol. 15(6), pages 1-21, May.
    12. Virgillito, Chiara & Manica, Mattia & Marini, Giovanni & Caputo, Beniamino & Torre, Alessandra della & Rosà, Roberto, 2021. "Modelling arthropod active dispersal using Partial differential equations: the case of the mosquito Aedes albopictus," Ecological Modelling, Elsevier, vol. 456(C).
    13. Santos, Eslaine S. & Miranda, José G.V. & Saba, Hugo & Skalinski, Lacita M. & Araújo, Marcio L.V. & Veiga, Rafael V. & Costa, Maria da Conceição N. & Cardim, Luciana L. & Paixão, Enny S. & Teixeira, M, 2023. "Complex network analysis of arboviruses in the same geographic domain: Differences and similarities," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    14. Wierman, John C. & Marchette, David J., 2004. "Modeling computer virus prevalence with a susceptible-infected-susceptible model with reintroduction," Computational Statistics & Data Analysis, Elsevier, vol. 45(1), pages 3-23, February.
    15. Dantas, Eber & Tosin, Michel & Cunha Jr, Americo, 2018. "Calibration of a SEIR–SEI epidemic model to describe the Zika virus outbreak in Brazil," Applied Mathematics and Computation, Elsevier, vol. 338(C), pages 249-259.
    16. Benito Chen-Charpentier, 2023. "Delays and Exposed Populations in Infection Models," Mathematics, MDPI, vol. 11(8), pages 1-22, April.
    17. Paul C. Fenema & A. Georges L. Romme, 2020. "Latent organizing for responding to emergencies: foundations for research," Journal of Organization Design, Springer;Organizational Design Community, vol. 9(1), pages 1-16, December.
    18. 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.
    19. 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).
    20. Brito da Cruz, Artur M.C. & Rodrigues, Helena Sofia, 2021. "Personal protective strategies for dengue disease: Simulations in two coexisting virus serotypes scenarios," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 188(C), pages 254-267.

    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:eee:apmaco:v:290:y:2016:i:c:p:1-8. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/applied-mathematics-and-computation .

    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.