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*ACM Transactions on Management Information Systems*
*Special Issue on Using AI and Data Science to Handle Pandemics
and Related
Disruptions*
*Co-editors:*
Kang Zhao
<kang-zhao@uiowa.edu>, The University of Iowa
Qingpeng Zhang
<qingpeng.zhang@cityu.edu.hk>, City
University of Hong Kong
Kelvin Tsoi
<kelvintsoi@cuhk.edu.hk>, The Chinese University
of Hong Kong
Sean Yuan
<sean.yuan@cityu.edu.hk>, City University of Hong
Kong
Human beings have fought against pandemics for centuries. With
millions of
infections, the ongoing pandemic of COVID-19 has seriously
disrupted many
aspects of people's life and caused hundreds of thousands of
deaths around
the world. Many researchers are studying the novel coronavirus and
its
impacts around the clock. In a short period of time, there have
been a
large number of studies published by various parts of the
biomedical and
health communities addressing the pandemic from the perspectives
of
biology, medicine, as well as epidemiology and public health.
The purpose of this special issue is to reach out to the broader
scientific
community, including those who come from management, social
science, policy
and/or MIS settings, as well as those who come from computer
science,
informatics, and other information technology-oriented settings.
We seek
your contributions that may help the world respond and adjust to
pandemics
and disruptions they cause. We are particularly interested in
research that
builds on recent rapid advancements in applying AI and Data
Science across
many application and domain areas.
The devastating COVID-19 pandemic has resulted in the creation of
a large
amount of related data, including case tracking data, hospital
admission
data, news and social media data, human mobility data, as well as
data
reported in scholarly articles. Many of these COVID-19 related
datasets
include important relational, temporal and/or geographical
features. The
availability of such rich datasets provides enormous opportunities
for
researchers to better understand, monitor and forecast the
pandemic.
This special issue seeks articles that *leverage AI and Data
Science* to
better manage risks and disruptions caused by pandemics.
Submissions that
analyze how pandemics impact business organizations, industry
sectors, as
well as the economy and society overall are also welcomed. We
especially
encourage researchers to put forth innovative and sound ways to
plan for or
adapt to future pandemics as a result of COVID-19 beyond the
immediate
near-term horizon.
Topics of interests include, but are not limited to:
- Disease diagnosis and tracking
- Predictive models for disease spread
- Simulations of disease transmissions and interventions
- Disease forecasting and surveillance
- Awareness of the disease and of personal protections
- AI and data science infrastructures for disease surveillance and
control
- Discovery and management of knowledge about pandemics or
infectious
diseases
- Supply chain management during and/or after a pandemic
- The impact of pandemic-related disruptions on business
operations and
processes
- Decision support for enforcing and lifting quarantine measures
- Risk assessment and management for the resumption of economic
and
social activities
*Submission Guidelines:*
All submissions will follow ACM TMIS guidelines (
dl.acm.org/journal/tmis/author-guidelines
<https://orange.hosting.lsoft.com/trk/click?ref=znwrbbrs9_6-25f01x3232fbx045007&>)
and submitted through the TMIS portal
(mc.manuscriptcentral.com/tmis
<https://orange.hosting.lsoft.com/trk/click?ref=znwrbbrs9_6-25f01x31ba15x045007&>)
with clear indications for the special issue.
*Important Dates:*
- Initial submissions due: Sept 30, 2020
- First round of notifications: Nov 30, 2020
- Second submissions due: Jan 15, 2021
- Final decisions: Feb 15, 2021
For questions and further information, please write to
kang-zhao@uiowa.edu.
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