Geospatial and Spatio-Temporal Models

Authors

Daniel Joseph Benito, Ateneo de Manila UniversityFollow
Lean Franzl Yao, Nara Institute of Science and Technology
Joshua Uyheng, Carnegie Mellon University
Elvira De Lara-TuprioFollow
Christian E. Pulmano, Ateneo de Manila UniversityFollow
Ma. Regina Justina Estuar, Ateneo de Manila UniversityFollow

Document Type

Article

Publication Date

8-8-2023

Abstract

One of the main functions of the FASSSTER platform is to provide Spatio-Temporal approach in understanding disease spread. In fact; the name of the platform when spelled out explicitly indicates Spatio-Temporal analysis. Specifically; the original version of FASSSTER made use of Spatio-Temporal Epidemiological Modeler (STEM) to visualize the spread of dengue; measles; and typhoid that is derived from the SEIR projections. Given the limitations in using STEM for spatial and spatio-temporal analysis for COVID-19 cases in the Philippines; more appropriate models were developed to accommodate the need for better visualization as well as a better prediction on the spread of the disease.

Recommended Citation

Benito, D. J., Yao, L. F., Uyheng, J., de Lara-Tuprio, E., Pulmano, C., Estuar, M. R. (2023). Geospatial and Spatio-Temporal Models. In: Estuar, M. R. J., De Lara-Tuprio, E. (eds) COVID-19 Experience in the Philippines. Disaster Risk Reduction. Springer, Singapore. https://doi.org/10.1007/978-981-99-3153-8_7.