COVID-19 transmission risk in Surabaya and Sidoarjo: an inhomogeneous marked Poisson point process approach
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Otros documentos de la autoría: Choiruddin, Achmad; Hannanu, Firdaus Fabrice; Mateu, Jorge; Fitriyanah, Vanda
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Título
COVID-19 transmission risk in Surabaya and Sidoarjo: an inhomogeneous marked Poisson point process approachFecha de publicación
2023Editor
SpringerISSN
1436-3240; 1436-3259Cita bibliográfica
CHOIRUDDIN, Achmad, et al. COVID-19 transmission risk in Surabaya and Sidoarjo: an inhomogeneous marked Poisson point process approach. Stochastic Environmental Research and Risk Assessment, 2023, p. 1-12Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
https://link.springer.com/article/10.1007/s00477-023-02393-5Versión
info:eu-repo/semantics/publishedVersionPalabras clave / Materias
Resumen
Understanding the spatio-temporal dynamics of COVID-19 transmission is necessary to plan better strategies for con-
trolling the spread of the disease. However, only a few studies explore the COVID-19 transmission ... [+]
Understanding the spatio-temporal dynamics of COVID-19 transmission is necessary to plan better strategies for con-
trolling the spread of the disease. However, only a few studies explore the COVID-19 transmission risk over a fine spatial
resolution while considering relevant spatial and temporal factors. To this aim, we consider an inhomogeneous marked
Poisson point process model to assess COVID-19 transmission risk using data of home addresses of confirmed cases, in
relation to locations of sources of crowd (enterprise, market, and place of worship) and population density in Surabaya and
Sidoarjo, Indonesia. Our marked model is able to analyze how the spatial covariates are varying with time, helping
authorities to evaluate the information of covariates depending on the period in which restrictions are taking place. Our
results show that enterprise, place of worship, and population densities have significant impact to the transmission risk in
Surabaya and Sidoarjo. We finally provide predicted risk maps which provide additional information based on the
demographic-based risk analysis to help conduct more efficient testing, tracing, and vaccination programs. [-]
Publicado en
Stochastic Environmental Research and Risk Assessment, 2023, p. 1-12Entidad financiadora
Institut Teknologi Sepuluh Nopember
Código del proyecto o subvención
967/PKS/ITS/2022
Derechos de acceso
© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023
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