Estimating velocities of infectious disease spread through spatio-temporal log-Gaussian Cox point processes Article Swipe
Fernando Rodriguez Avellaneda
,
Jorge Mateu
,
Paula Moraga
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2409.05036
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2409.05036
Understanding the spread of infectious diseases such as COVID-19 is crucial for informed decision-making and resource allocation. A critical component of disease behavior is the velocity with which disease spreads, defined as the rate of change between time and space. In this paper, we propose a spatio-temporal modeling approach to determine the velocities of infectious disease spread. Our approach assumes that the locations and times of people infected can be considered as a spatio-temporal point pattern that arises as a realization of a spatio-temporal log-Gaussian Cox process. The intensity of this process is estimated using fast Bayesian inference by employing the integrated nested Laplace approximation (INLA) and the Stochastic Partial Differential Equations (SPDE) approaches. The velocity is then calculated using finite differences that approximate the derivatives of the intensity function. Finally, the directions and magnitudes of the velocities can be mapped at specific times to examine better the spread of the disease throughout the region. We demonstrate our method by analyzing COVID-19 spread in Cali, Colombia, during the 2020-2021 pandemic.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2409.05036
- https://arxiv.org/pdf/2409.05036
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4403617361
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4403617361Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2409.05036Digital Object Identifier
- Title
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Estimating velocities of infectious disease spread through spatio-temporal log-Gaussian Cox point processesWork title
- Type
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preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-09-08Full publication date if available
- Authors
-
Fernando Rodriguez Avellaneda, Jorge Mateu, Paula MoragaList of authors in order
- Landing page
-
https://arxiv.org/abs/2409.05036Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2409.05036Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2409.05036Direct OA link when available
- Concepts
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Gaussian, Infectious disease (medical specialty), Statistical physics, Point process, Point (geometry), Econometrics, Mathematics, Statistics, Disease, Physics, Medicine, Internal medicine, Geometry, Quantum mechanicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- Related works (count)
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10Other works algorithmically related by OpenAlex
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