IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v175y2023ip1s0960077923008408.html
   My bibliography  Save this article

A new population model for urban infestations

Author

Listed:
  • Calatayud, Julia
  • Jornet, Marc
  • Mateu, Jorge
  • Pinto, Carla M.A.

Abstract

The spread of rodents and insects in cities, in particular in summer periods, poses significant health, economic, social and environmental threats. The analysis of incidence and identification of seasonal and weather determinants are crucial for addressing intervention strategies. In this context, we investigate the occurrence of rats and cockroaches infestations in the city of Madrid, Spain, with differential equation models. Birth–death fluxes, sine–cosine waves and temperature conform the mechanistic nature of the models. Available data on citizen-reported sightings from 2010 until 2013 are fitted by parameter calibration and uncertain-error measurement. Numerical simulations show that the time series are adequately explained by the proposed models. This strongly suggests that the models can be used to predict future infestation dynamics, which can guide health policy measures.

Suggested Citation

  • Calatayud, Julia & Jornet, Marc & Mateu, Jorge & Pinto, Carla M.A., 2023. "A new population model for urban infestations," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).
    • Handle: RePEc:eee:chsofr:v:175:y:2023:i:p1:s0960077923008408
    DOI: 10.1016/j.chaos.2023.113939
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077923008408
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2023.113939?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. Wolfgang Härdle & Joel Horowitz & Jens‐Peter Kreiss, 2003. "Bootstrap Methods for Time Series," International Statistical Review, International Statistical Institute, vol. 71(2), pages 435-459, August.
    2. D’Ovidio, Mirko & Loreti, Paola & Sarv Ahrabi, Sima, 2018. "Modified fractional logistic equation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 818-824.
    3. Richard Bellman, 1957. "On a Dynamic Programming Approach to the Caterer Problem--I," Management Science, INFORMS, vol. 3(3), pages 270-278, April.
    4. Pelinovsky, Efim & Kurkin, Andrey & Kurkina, Oxana & Kokoulina, Maria & Epifanova, Anastasia, 2020. "Logistic equation and COVID-19," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    5. Roberto Cervelló & Juan- C. Cortés & Francisco- J. Santonja & Rafael- J. Villanueva, 2014. "The dynamics over the next few years of the Spanish mobile telecommunications market share: a mathematical modelling approach," Mathematical and Computer Modelling of Dynamical Systems, Taylor & Francis Journals, vol. 20(6), pages 557-565, November.
    6. A. Corberán-Vallet & F. J. Santonja & M. Jornet-Sanz & R.-J. Villanueva, 2018. "Modeling Chickenpox Dynamics with a Discrete Time Bayesian Stochastic Compartmental Model," Complexity, Hindawi, vol. 2018, pages 1-9, March.
    7. Green, Kesten C. & Armstrong, J. Scott, 2015. "Simple versus complex forecasting: The evidence," Journal of Business Research, Elsevier, vol. 68(8), pages 1678-1685.
    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. Area, I. & Nieto, J.J., 2021. "Power series solution of the fractional logistic equation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 573(C).
    2. Thomas George & Chuan-Yang Hwang & Tavy Ronen, 2010. "Bootstrap refinements in tests of microstructure frictions," Review of Quantitative Finance and Accounting, Springer, vol. 35(1), pages 47-70, July.
    3. Voelkel, Michael A. & Sachs, Anna-Lena & Thonemann, Ulrich W., 2020. "An aggregation-based approximate dynamic programming approach for the periodic review model with random yield," European Journal of Operational Research, Elsevier, vol. 281(2), pages 286-298.
    4. Armstrong, J. Scott & Green, Kesten C. & Graefe, Andreas, 2015. "Golden rule of forecasting: Be conservative," Journal of Business Research, Elsevier, vol. 68(8), pages 1717-1731.
    5. Tan, Madeleine Sui-Lay, 2016. "Policy coordination among the ASEAN-5: A global VAR analysis," Journal of Asian Economics, Elsevier, vol. 44(C), pages 20-40.
    6. D. W. K. Yeung, 2008. "Dynamically Consistent Solution For A Pollution Management Game In Collaborative Abatement With Uncertain Future Payoffs," International Game Theory Review (IGTR), World Scientific Publishing Co. Pte. Ltd., vol. 10(04), pages 517-538.
    7. Palm, Franz C. & Smeekes, Stephan & Urbain, Jean-Pierre, 2011. "Cross-sectional dependence robust block bootstrap panel unit root tests," Journal of Econometrics, Elsevier, vol. 163(1), pages 85-104, July.
    8. Litsiou, Konstantia & Polychronakis, Yiannis & Karami, Azhdar & Nikolopoulos, Konstantinos, 2022. "Relative performance of judgmental methods for forecasting the success of megaprojects," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1185-1196.
    9. Hanafi, Said & Freville, Arnaud, 1998. "An efficient tabu search approach for the 0-1 multidimensional knapsack problem," European Journal of Operational Research, Elsevier, vol. 106(2-3), pages 659-675, April.
    10. Renato Cordeiro Amorim, 2016. "A Survey on Feature Weighting Based K-Means Algorithms," Journal of Classification, Springer;The Classification Society, vol. 33(2), pages 210-242, July.
    11. Kydland, Finn & Rupert, Peter & Sustek, Roman, 2012. "Housing Dynamics over the Business Cycle," University of California at Santa Barbara, Economics Working Paper Series qt7bn5k73m, Department of Economics, UC Santa Barbara.
    12. Perrier, Frédéric & Girault, Frédéric, 2022. "Scaling and fine structure of superstable periodic orbits in the logistic map," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).
    13. Dmitri Blueschke & Ivan Savin, 2015. "No such thing like perfect hammer: comparing different objective function specifications for optimal control," Jena Economics Research Papers 2015-005, Friedrich-Schiller-University Jena.
    14. Changming Ji & Chuangang Li & Boquan Wang & Minghao Liu & Liping Wang, 2017. "Multi-Stage Dynamic Programming Method for Short-Term Cascade Reservoirs Optimal Operation with Flow Attenuation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(14), pages 4571-4586, November.
    15. Ghassan, Hassan B. & Al-Jefri, Essam H., 2015. "الحساب الجاري في المدى البعيد عبر نموذج داخلي الزمن [The Current Account in the Long Run through the Intertemporal Model]," MPRA Paper 66527, University Library of Munich, Germany.
    16. Alroomi, Azzam & Karamatzanis, Georgios & Nikolopoulos, Konstantinos & Tilba, Anna & Xiao, Shujun, 2022. "Fathoming empirical forecasting competitions’ winners," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1519-1525.
    17. John Stachurski, 2009. "Economic Dynamics: Theory and Computation," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262012774, April.
    18. Mercedes Esteban-Bravo & Jose M. Vidal-Sanz & Gökhan Yildirim, 2014. "Valuing Customer Portfolios with Endogenous Mass and Direct Marketing Interventions Using a Stochastic Dynamic Programming Decomposition," Marketing Science, INFORMS, vol. 33(5), pages 621-640, September.
    19. Ohno, Katsuhisa & Boh, Toshitaka & Nakade, Koichi & Tamura, Takayoshi, 2016. "New approximate dynamic programming algorithms for large-scale undiscounted Markov decision processes and their application to optimize a production and distribution system," European Journal of Operational Research, Elsevier, vol. 249(1), pages 22-31.
    20. Oleg Malafeyev & Achal Awasthi, 2015. "A Dynamic Model of Functioning of a Bank," Papers 1511.01529, arXiv.org.

    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:chsofr:v:175:y:2023:i:p1:s0960077923008408. 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: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    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.