Optimisation of preparedness and response of health services in major crises using the IMPRESS platform

Nina Dobrinkova; Thomas Finnie; James Thompson; Ian Hall; Christos Dimopoulos; George Boustras; Yianna Danidou; Nectarios Efstathiou; Chrysostomos Psaroudakis; Nikolaos Koutras; George Eftichidis; Ilias Gkotsis; Marcel Heckel; Andrej Olunczek; Ralf Hedel; Antonis Kostaridis; Marios Moutzouris; Simona Panunzi; Geert Seynaeve; Sofia Tsekeridou; Danae Vergeti

doi:10.1007/978-3-319-99648-6_2

Optimisation of preparedness and response of health services in major crises using the IMPRESS platform

Nina Dobrinkova^*, Thomas Finnie, James Thompson, Ian Hall, Christos Dimopoulos, George Boustras, Yianna Danidou, Nectarios Efstathiou, Chrysostomos Psaroudakis, Nikolaos Koutras, George Eftichidis, Ilias Gkotsis, Marcel Heckel, Andrej Olunczek, Ralf Hedel, Antonis Kostaridis, Marios Moutzouris, Simona Panunzi, Geert Seynaeve, Sofia TsekeridouDanae Vergeti

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

We present the IMPRESS software system; a tool that can support the first responders in cases of disaster management and resources allocation and the optimisation of response to large-scale emergencies. This is a multi-level architecture system that has desktop and mobile interfaces, supporting the decision makers with different modules. Every module has been designed in a way that the data can be unified, no matter the source, and the related calculation engines are providing optimized information for both the users in the incident management centre and on the field. In this article IMPRESS system components are presented, among the validation and optimization activities during the demonstrations implemented in Palermo, Italy (field test exercise), Podgorica, Montenegro (field test exercise) and Sofia, Bulgaria (table top exercise).

Original language	English
Title of host publication	Studies in Computational Intelligence
Publisher	Springer Verlag
Pages	15-34
Number of pages	20
DOIs	https://doi.org/10.1007/978-3-319-99648-6_2
Publication status	Published - 2019

Publication series

Name	Studies in Computational Intelligence
Volume	795
ISSN (Print)	1860-949X

Bibliographical note

Funding Information:
Acknowledgements This work has been partially supported by the EC Research Executive Agency 7th Framework Programme, (SEC-2013.4.1-4) under grant number: FP7-SEC-2013-608078-IMproving Preparedness and Response of HEalth Services in major criseS (IMPRESS), the UK NIH Health Protection Research Unit in Emergency Preparedness and Response and the Bulgarian National Science Fund project number DN 12/5 called: Efficient Stochastic Methods and Algorithms for Large-Scale Computational Problems.

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Dobrinkova, N., Finnie, T., Thompson, J., Hall, I., Dimopoulos, C., Boustras, G., Danidou, Y., Efstathiou, N., Psaroudakis, C., Koutras, N., Eftichidis, G., Gkotsis, I., Heckel, M., Olunczek, A., Hedel, R., Kostaridis, A., Moutzouris, M., Panunzi, S., Seynaeve, G., ... Vergeti, D. (2019). Optimisation of preparedness and response of health services in major crises using the IMPRESS platform. In Studies in Computational Intelligence (pp. 15-34). (Studies in Computational Intelligence; Vol. 795). Springer Verlag. https://doi.org/10.1007/978-3-319-99648-6_2

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title = "Optimisation of preparedness and response of health services in major crises using the IMPRESS platform",

abstract = "We present the IMPRESS software system; a tool that can support the first responders in cases of disaster management and resources allocation and the optimisation of response to large-scale emergencies. This is a multi-level architecture system that has desktop and mobile interfaces, supporting the decision makers with different modules. Every module has been designed in a way that the data can be unified, no matter the source, and the related calculation engines are providing optimized information for both the users in the incident management centre and on the field. In this article IMPRESS system components are presented, among the validation and optimization activities during the demonstrations implemented in Palermo, Italy (field test exercise), Podgorica, Montenegro (field test exercise) and Sofia, Bulgaria (table top exercise).",

author = "Nina Dobrinkova and Thomas Finnie and James Thompson and Ian Hall and Christos Dimopoulos and George Boustras and Yianna Danidou and Nectarios Efstathiou and Chrysostomos Psaroudakis and Nikolaos Koutras and George Eftichidis and Ilias Gkotsis and Marcel Heckel and Andrej Olunczek and Ralf Hedel and Antonis Kostaridis and Marios Moutzouris and Simona Panunzi and Geert Seynaeve and Sofia Tsekeridou and Danae Vergeti",

note = "Funding Information: Acknowledgements This work has been partially supported by the EC Research Executive Agency 7th Framework Programme, (SEC-2013.4.1-4) under grant number: FP7-SEC-2013-608078-IMproving Preparedness and Response of HEalth Services in major criseS (IMPRESS), the UK NIH Health Protection Research Unit in Emergency Preparedness and Response and the Bulgarian National Science Fund project number DN 12/5 called: Efficient Stochastic Methods and Algorithms for Large-Scale Computational Problems.",

year = "2019",

doi = "10.1007/978-3-319-99648-6_2",

language = "English",

series = "Studies in Computational Intelligence",

publisher = "Springer Verlag",

pages = "15--34",

booktitle = "Studies in Computational Intelligence",

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Dobrinkova, N, Finnie, T, Thompson, J, Hall, I, Dimopoulos, C, Boustras, G, Danidou, Y, Efstathiou, N, Psaroudakis, C, Koutras, N, Eftichidis, G, Gkotsis, I, Heckel, M, Olunczek, A, Hedel, R, Kostaridis, A, Moutzouris, M, Panunzi, S, Seynaeve, G, Tsekeridou, S & Vergeti, D 2019, Optimisation of preparedness and response of health services in major crises using the IMPRESS platform. in Studies in Computational Intelligence. Studies in Computational Intelligence, vol. 795, Springer Verlag, pp. 15-34. https://doi.org/10.1007/978-3-319-99648-6_2

Optimisation of preparedness and response of health services in major crises using the IMPRESS platform. / Dobrinkova, Nina; Finnie, Thomas; Thompson, James et al.

Studies in Computational Intelligence. Springer Verlag, 2019. p. 15-34 (Studies in Computational Intelligence; Vol. 795).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

TY - CHAP

T1 - Optimisation of preparedness and response of health services in major crises using the IMPRESS platform

AU - Dobrinkova, Nina

AU - Finnie, Thomas

AU - Thompson, James

AU - Hall, Ian

AU - Dimopoulos, Christos

AU - Boustras, George

AU - Danidou, Yianna

AU - Efstathiou, Nectarios

AU - Psaroudakis, Chrysostomos

AU - Koutras, Nikolaos

AU - Eftichidis, George

AU - Gkotsis, Ilias

AU - Heckel, Marcel

AU - Olunczek, Andrej

AU - Hedel, Ralf

AU - Kostaridis, Antonis

AU - Moutzouris, Marios

AU - Panunzi, Simona

AU - Seynaeve, Geert

AU - Tsekeridou, Sofia

AU - Vergeti, Danae

N1 - Funding Information: Acknowledgements This work has been partially supported by the EC Research Executive Agency 7th Framework Programme, (SEC-2013.4.1-4) under grant number: FP7-SEC-2013-608078-IMproving Preparedness and Response of HEalth Services in major criseS (IMPRESS), the UK NIH Health Protection Research Unit in Emergency Preparedness and Response and the Bulgarian National Science Fund project number DN 12/5 called: Efficient Stochastic Methods and Algorithms for Large-Scale Computational Problems.

PY - 2019

Y1 - 2019

N2 - We present the IMPRESS software system; a tool that can support the first responders in cases of disaster management and resources allocation and the optimisation of response to large-scale emergencies. This is a multi-level architecture system that has desktop and mobile interfaces, supporting the decision makers with different modules. Every module has been designed in a way that the data can be unified, no matter the source, and the related calculation engines are providing optimized information for both the users in the incident management centre and on the field. In this article IMPRESS system components are presented, among the validation and optimization activities during the demonstrations implemented in Palermo, Italy (field test exercise), Podgorica, Montenegro (field test exercise) and Sofia, Bulgaria (table top exercise).

AB - We present the IMPRESS software system; a tool that can support the first responders in cases of disaster management and resources allocation and the optimisation of response to large-scale emergencies. This is a multi-level architecture system that has desktop and mobile interfaces, supporting the decision makers with different modules. Every module has been designed in a way that the data can be unified, no matter the source, and the related calculation engines are providing optimized information for both the users in the incident management centre and on the field. In this article IMPRESS system components are presented, among the validation and optimization activities during the demonstrations implemented in Palermo, Italy (field test exercise), Podgorica, Montenegro (field test exercise) and Sofia, Bulgaria (table top exercise).

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U2 - 10.1007/978-3-319-99648-6_2

DO - 10.1007/978-3-319-99648-6_2

M3 - Chapter

AN - SCOPUS:85053528795

T3 - Studies in Computational Intelligence

SP - 15

EP - 34

BT - Studies in Computational Intelligence

PB - Springer Verlag

ER -

Optimisation of preparedness and response of health services in major crises using the IMPRESS platform

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