04389nam 22006615 450 991073698500332120230807065000.0981-9931-53-310.1007/978-981-99-3153-8(MiAaPQ)EBC30679944(Au-PeEL)EBL30679944(OCoLC)1393306579(DE-He213)978-981-99-3153-8(PPN)272263982(CKB)27942475000041(EXLCZ)992794247500004120230807d2023 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierCOVID-19 Experience in the Philippines Response, Surveillance and Monitoring Using the FASSSTER Platform /edited by Maria Regina Justina Estuar, Elvira De Lara-Tuprio1st ed. 2023.Singapore :Springer Nature Singapore :Imprint: Springer,2023.1 online resource (169 pages)Disaster Risk Reduction, Methods, Approaches and Practices,2196-4114Print version: Estuar, Maria Regina Justina COVID-19 Experience in the Philippines Singapore : Springer,c2023 9789819931521 Includes bibliographical references.Chapter 1. Origins of FASSSTER -- Chapter 2. Management of COVID-19 Data for the FASSSTER Platform -- Chapter 3. FASSSTER Data Pipeline and DevOps -- Chapter 4. Disease Surveillance Metrics and Statistics -- Chapter 5. Effective Reproduction Number Rt -- Chapter 6. The FASSSTER SEIR Model -- Chapter 7. Geospatial and Spatio-Temporal Models. .This book provides an overview of the extensive work that has been done on the design and implementation of the COVID-19 Philippines Local Government Unit Monitoring Platform, more commonly known as Feasibility Analysis of Syndromic Surveillance Using Spatio-Temporal Epidemiological Modeler for Early Detection of Diseases (FASSSTER). The project began in 2016 as a pilot study in developing a multidimensional approach in disease modeling requiring the development of an interoperable platform to accommodate input of data from various sources including electronic medical records, various disease surveillance systems, social media, online news, and weather data. In 2020, the FASSSTER platform was reconfigured for use in the COVID-19 pandemic. Using lessons learned from the previous design and implementation of the platform toward its full adoption by the Department of Health of the Philippines, this book narrates the story of FASSSTER in two main parts. Part I provides a historical perspective of the FASSSTER platform as a modeling and disease surveillance system for dengue, measles and typhoid, followed by the origins of the FASSSTER framework and how it was reconfigured for the management of COVID-19 information for the Philippines. Part I also explains the different technologies and system components of FASSSTER that paved the way to the operationalization of the FASSSTER model and allowed for seamless rendering of projections and analytics. Part II describes the FASSSTER analytics and models including the Susceptible-Exposed-Infected-Recovered (SEIR) model, the model for time-varying reproduction number, spatiotemporal models and contact tracing models, which became the basis for the imposition of restrictions in mobility translated into localized lockdowns.Disaster Risk Reduction, Methods, Approaches and Practices,2196-4114Natural disastersPublic healthElectronic data processing—ManagementDiseases—Animal modelsNatural HazardsPublic HealthIT OperationsDisease ModelsNatural disasters.Public health.Electronic data processing—Management.Diseases—Animal models.Natural Hazards.Public Health.IT Operations.Disease Models.362.1962414009599Estuar Maria Regina JustinaDe Lara-Tuprio ElviraMiAaPQMiAaPQMiAaPQBOOK9910736985003321COVID-19 Experience in the Philippines3424590UNINA