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COVID-19 experience in the Philippin...

Estuar, Maria Regina Justina.

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COVID-19 experience in the Philippines = response, surveillance and monitoring using the FASSSTER platform /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	COVID-19 experience in the Philippines/ edited by Maria Regina Justina Estuar, Elvira De Lara-Tuprio.
其他題名:	response, surveillance and monitoring using the FASSSTER platform /
其他作者:	Estuar, Maria Regina Justina.
出版者:	Singapore :Springer Nature Singapore : : 2023.,
面頁冊數:	xx, 159 p. :ill., digital ;24 cm.
內容註:	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.
Contained By:	Springer Nature eBook
標題:	COVID-19 (Disease) - Epidemiology. - Philippines -
電子資源:	https://doi.org/10.1007/978-981-99-3153-8
ISBN:	9789819931538

COVID-19 experience in the Philippines = response, surveillance and monitoring using the FASSSTER platform /
COVID-19 experience in the Philippinesresponse, surveillance and monitoring using the FASSSTER platform /[electronic resource] :edited by Maria Regina Justina Estuar, Elvira De Lara-Tuprio. - Singapore :Springer Nature Singapore :2023. - xx, 159 p. :ill., digital ;24 cm. - Disaster risk reduction, methods, approaches and practices,2196-4114. - Disaster risk reduction, methods, approaches and practices..

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.

ISBN: 9789819931538

Standard No.: 10.1007/978-981-99-3153-8doiSubjects--Topical Terms:

3664737
COVID-19 (Disease)
--Epidemiology.--Philippines

LC Class. No.: RA644.C67 / C68 2023

Dewey Class. No.: 362.196241440954

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