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Data Science Advancements in Pandemic and Outbreak Management (Hardcover)
Loot Price: R6,682
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Data Science Advancements in Pandemic and Outbreak Management (Hardcover)
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Pandemics are disruptive. Thus, there is a need to prepare and plan
actions in advance for identifying, assessing, and responding to
such events to manage uncertainty and support sustainable
livelihood and wellbeing. A detailed assessment of a continuously
evolving situation needs to take place, and several aspects must be
brought together and examined before the declaration of a pandemic
even happens. Various health organizations; crisis management
bodies; and authorities at local, national, and international
levels are involved in the management of pandemics. There is no
better time to revisit current approaches to cope with these new
and unforeseen threats. As countries must strike a fine balance
between protecting health, minimizing economic and social
disruption, and respecting human rights, there has been an emerging
interest in lessons learned and specifically in revisiting past and
current pandemic approaches. Such approaches involve strategies and
practices from several disciplines and fields including healthcare,
management, IT, mathematical modeling, and data science. Using data
science to advance in-situ practices and prompt future directions
could help alleviate or even prevent human, financial, and
environmental compromise, and loss and social interruption via
state-of-the-art technologies and frameworks. Data Science
Advancements in Pandemic and Outbreak Management demonstrates how
strategies and state-of-the-art IT have and/or could be applied to
serve as the vehicle to advance pandemic and outbreak management.
The chapters will introduce both technical and non-technical
details of management strategies and advanced IT, data science, and
mathematical modelling and demonstrate their applications and their
potential utilization within the identification and management of
pandemics and outbreaks. It also prompts revisiting and critically
reviewing past and current approaches, identifying good and bad
practices, and further developing the area for future adaptation.
This book is ideal for data scientists, data analysts, infectious
disease experts, researchers studying pandemics and outbreaks, IT,
crisis and disaster management, academics, practitioners,
government officials, and students interested in applicable
theories and practices in data science to mitigate, prepare for,
respond to, and recover from future pandemics and outbreaks.
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