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Modeling of Infectious Diseases: A Core Research Topic for the Next Hundred Years

In: Regional Research Frontiers - Vol. 2

Author

Listed:
  • I Gede Nyoman Mindra Jaya

    (Universitas Padjadjaran)

  • Henk Folmer

    (University of Groningen)

  • Budi Nurani Ruchjana

    (Universitas Padjadjaran)

  • Farah Kristiani

    (Parahyangan Catholic University)

  • Yudhie Andriyana

    (Universitas Padjadjaran)

Abstract

Incidence of infectious diseases is an under-researched topic in regional science. This situation is unfortunate because the occurrence of these types of diseases frequently has far-reaching welfare impacts at household, regional, national, and even international levels. Given its welfare impacts and soaring incidence, inter alia, because of climate change, increasing population density, higher mobility, and increasing immunity to several common medicines, the occurrence and spread of infectious diseases should become a regular research topic in regional science. There are also methodological reasons why regional scientists should pay (more) attention to the incidence of infectious diseases. Although both regional science and epidemiology deal with the spatial distributions of their research topics and apply spatial analytical techniques, important methodological differences between them open possibilities for cross-fertilization. This study presents an overview of the main models and estimators of infectious disease incidence. We first discuss maximum likelihood (ML), which is the most common estimator. It is unbiased but imprecise and unreliable for small regions. Next we discuss several methods that have been proposed to improve ML estimation by smoothing (i.e., Bayesian smoothing techniques and nonparametric estimators). From the review, we conclude that none of the models used so far adequately considers the most basic characteristic of infectious diseases, namely, spatial spillover. We argue that the development and application of infectious disease models that allow for spatial spillover is a core research topic for the years to come. We conclude the chapter with suggestions for future regional science research themes in the area of infectious diseases.

Suggested Citation

  • I Gede Nyoman Mindra Jaya & Henk Folmer & Budi Nurani Ruchjana & Farah Kristiani & Yudhie Andriyana, 2017. "Modeling of Infectious Diseases: A Core Research Topic for the Next Hundred Years," Advances in Spatial Science, in: Randall Jackson & Peter Schaeffer (ed.), Regional Research Frontiers - Vol. 2, chapter 0, pages 239-255, Springer.
    • Handle: RePEc:spr:adspcp:978-3-319-50590-9_15
    DOI: 10.1007/978-3-319-50590-9_15
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    Citations

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    Cited by:

    1. Amitrajeet A. Batabyal & Henk Folmer, 2019. "Space and the environment: an introduction to the topical collection," Letters in Spatial and Resource Sciences, Springer, vol. 12(1), pages 1-7, April.
    2. Batabyal, Amitrajeet & Folmer, Henk, 2018. "Space and the Environment: An Introduction to the Special Issue," MPRA Paper 90526, University Library of Munich, Germany, revised 13 Dec 2018.
    3. I. Gede Nyoman Mindra Jaya & Henk Folmer, 2022. "Spatiotemporal high-resolution prediction and mapping: methodology and application to dengue disease," Journal of Geographical Systems, Springer, vol. 24(4), pages 527-581, October.
    4. Amitrajeet A. Batabyal & Henk Folmer, 2020. "Spatial economic aspects of climate change," Spatial Economic Analysis, Taylor & Francis Journals, vol. 15(3), pages 209-218, July.
    5. I. Gede Nyoman M. Jaya & Henk Folmer, 2021. "Bayesian spatiotemporal forecasting and mapping of COVID‐19 risk with application to West Java Province, Indonesia," Journal of Regional Science, Wiley Blackwell, vol. 61(4), pages 849-881, September.
    6. I. Gede Nyoman Mindra Jaya & Henk Folmer, 2020. "Bayesian spatiotemporal mapping of relative dengue disease risk in Bandung, Indonesia," Journal of Geographical Systems, Springer, vol. 22(1), pages 105-142, January.

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