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Modelling Health In...
Modelling Health Information during Catastrophic Events - A Disaster Management System for Sudan
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Abd-Alrahman, Ahmed Mustafa (author)
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- Ekenberg, Love (author)
- Stockholms universitet,Institutionen för data- och systemvetenskap
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(creator_code:org_t)
- International Information Management Corporation Limited, 2017
- 2017
- English.
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In: IST-Africa 2017. - : International Information Management Corporation Limited. - 9781905824571 ; , s. 1-9
- Related links:
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https://urn.kb.se/re...
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https://doi.org/10.2...
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Abstract
Subject headings
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- There is an increasing trend of disastrous events during past decade with significant damage in terms of lives, infrastructure, economics and environment. Disastrous events are affecting communities worldwide and, apart for the actual and personal suffering involved, can fundamentally disrupt societal functions for many years. This is particularly the case in already vulnerable regions, which often require external assistance of various kinds. In order to reduce catastrophic effects of disasters, disaster mitigation measures and crisis reduction must be systematically planned and managed. This includes correct damage assessment, fast, efficient and prepared responses, adequate resource allocation and organisation of the relief processes. Obviously, the conditions and abilities to implement such measures are very different in various locations, where regions have particularly severe conditions. In this paper, we discuss crisis management in Sudan and highlight the need for national and regional disaster management processes and activities as well as general framework for the design of an efficient disaster management program in Sudan.
Subject headings
- NATURVETENSKAP -- Data- och informationsvetenskap -- Systemvetenskap, informationssystem och informatik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Information Systems (hsv//eng)
Keyword
- Disaster management
- Information system
- Decision support
- Decision making
- Computer and Systems Sciences
- data- och systemvetenskap
Publication and Content Type
- ref (subject category)
- kon (subject category)
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