國立高雄大學圖資館 |

COVID-19 experience in the Philippinesresponse, surveillance and monitoring using the FASSSTER platform /

Record Type:	Electronic resources : Monograph/item
Title/Author:	COVID-19 experience in the Philippinesedited by Maria Regina Justina Estuar, Elvira De Lara-Tuprio.
Reminder of title:	response, surveillance and monitoring using the FASSSTER platform /
other author:	Estuar, Maria Regina Justina.
Published:	Singapore :Springer Nature Singapore :2023.
Description:	xx, 159 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	COVID-19 (Disease)Epidemiology.Philippines
Online resource:	https://doi.org/10.1007/978-981-99-3153-8
ISBN:	9789819931538$q(electronic bk.)

COVID-19 experience in the Philippinesresponse, 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$q(electronic bk.)

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

956883
COVID-19 (Disease)
--Epidemiology.--Philippines

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

Dewey Class. No.: 362.196241440954

COVID-19 experience in the Philippinesresponse, surveillance and monitoring using the FASSSTER platform /
LDR:03316nmm a2200337 a 4500 001 647534
003 DE-He213
005 20230807065000.0
006 m d
007 cr nn 008maaau
008 240116s2023 si s 0 eng d
020 $a 9789819931538$q(electronic bk.)
020 $a 9789819931521$q(paper)
024 7 $a 10.1007/978-981-99-3153-8 $2 doi
035 $a 978-981-99-3153-8
040 $a GP $c GP
041 0 $a eng
050 4 $a RA644.C67 $b C68 2023
072 7 $a RNR $2 bicssc
072 7 $a NAT023000 $2 bisacsh
072 7 $a RNR $2 thema
082 0 4 $a 362.196241440954 $2 23
090 $a RA644.C67 $b C873 2023
245 0 0 $a COVID-19 experience in the Philippines $h [electronic resource] : $b response, surveillance and monitoring using the FASSSTER platform / $c edited by Maria Regina Justina Estuar, Elvira De Lara-Tuprio.
260 $a Singapore : $b Springer Nature Singapore : $b Imprint: Springer, $c 2023.
300 $a xx, 159 p. : $b ill., digital ; $c 24 cm.
490 1 $a Disaster risk reduction, methods, approaches and practices, $x 2196-4114
505 0 $a 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.
520 $a 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.
650 0 $a COVID-19 (Disease) $z Philippines $x Epidemiology. $3 956883
650 0 $a COVID-19 (Disease) $x Transmission $x Mathematical models. $3 956884
650 0 $a Health planning $z Philippines. $3 956885
650 1 4 $a Natural Hazards. $3 348413
650 2 4 $a Public Health. $3 320661
650 2 4 $a IT Operations. $3 913145
650 2 4 $a Disease Models. $3 923738
700 1 $a Estuar, Maria Regina Justina. $3 956881
700 1 $a De Lara-Tuprio, Elvira. $3 956882
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
830 0 $a Disaster risk reduction, methods, approaches and practices. $3 711978
856 4 0 $u https://doi.org/10.1007/978-981-99-3153-8
950 $a Earth and Environmental Science (SpringerNature-11646)