10/01/2025, 23:31 Information technology solutions, challenges, and suggestions for tackling the COVID-19 pandemic - ScienceDirect

International Journal of Information

Management
Volume 57, April 2021, 102287

Opinion Paper

Information technology solutions,

challenges, and suggestions for tackling the
COVID-19 pandemic
Wu He a , Zuopeng (Justin) Zhang b , Wenzhuo Li a

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https://doi.org/10.1016/j.ijinfomgt.2020.102287
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Abstract
Various technology innovations and applications have been developed to fight the
coronavirus pandemic. The pandemic also has implications for the design, development,
and use of technologies. There is an urgent need for a greater understanding of what
roles information systems and technology researchers can play in this global pandemic.
This paper examines emerging technologies used to mitigate the threats of COVID-19 and
relevant challenges related to technology design, development, and use. It also provides
insights and suggestions into how information systems and technology scholars can help
fight the COVID-19 pandemic. This paper helps promote future research and technology
development to produce better solutions for tackling the COVID-19 pandemic and future
pandemics.

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Keywords

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10/01/2025, 23:31 Information technology solutions, challenges, and suggestions for tackling the COVID-19 pandemic - ScienceDirect

COVID-19; Artificial intelligence; Big data; Blockchain; Information systems; Human

behavior; Digital divide; System integration

1. Introduction
The COVID-19 pandemic has caused an immense impact on hospital systems, businesses,
schools, and the economy. Telemedicine, telework, and online education become
essential to help society slow down the spread of the coronavirus (Chavez & Kounang,
2020; Loh & Fishbane, 2020; Young, 2020). The pandemic has generated a rapid demand
for efforts to use innovative technologies to cope with damage from COVID-19 on our life
(O’Leary, 2020).

The pandemic has not only raised opportunities to advance technology-based solutions
but also provided a rare opportunity to study the research and practice of technology,
including information management, work practices, and design and use of technologies
(Sein, 2020). The quick transition to telehealth, telework, and online education in
response to the coronavirus threat is a reminder that digital technology brings many
benefits and can play an essential role in managing and reducing the risks caused by the
lockdown during the pandemic and even after the pandemic (Richter, 2020). It is well
known that information systems and information technology (IS/IT) play an important
role in healthcare, clinical decision support, emergency/crisis response, and risk
management (Angst & Agarwal, 2009; Ben-Assuli & Padman, 2020; Chen, Sharman,
Chakravarti, Rao, & Upadhyaya, 2008; Thompson, Whitaker, Kohli, & Jones, 2019). Many
IS/IT professionals are working in various ways to help fight the pandemic, including
developing products to combat the virus, tracking and predicting its spread, and
protecting hospitals from cyberattacks (Mingis, 2020). Information systems and
technology scholars should contribute to this global effort to fight the COVID-19 and
future pandemics (Ågerfalk, Conboy, & Myers, 2020) by leveraging their previous
experience and knowledge on responding to crises, decision making, remote working,
managing virtual teams, analyzing large data sets, etc. There is currently a shortage of
research contributions in the areas of information systems (IS) to help fight the COVID-
19.

The pandemic has implications for the design, development, and use of information
systems and technologies (Sein, 2020). Information systems and technology researchers
and practitioners can help conduct an analysis of the COVID-19 pandemic data and
engage in potential emerging research topics, such as facilitating work while social
distancing, contactless commerce, face recognition when wearing masks or in other
crises, COVID-19 apps in terms of privacy, crowdsourcing, donating data, and tracking
cases, robotics and their impact on organizations, monitoring vulnerable vs. non-
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vulnerable for their impact on work, changing patterns of supply and demand for fragile
supply chains and autonomic systems, virtual communication tools, online education
breakthroughs, and separation of work and private life (O’Leary, 2020). Rai (2020) also
identified some opportunities for IS research to contribute toward building resilience to
pandemics and extreme events including (i) redesigning the public health system from
reactive to proactive through the use of real-time surveillance systems and contact
tracing tools to stem transmission, (ii) transforming organizations through enhancing
crisis-driven agility and reducing crisis-revealed fragility, and (iii) empowering
individuals and communities through adapting, coping, and stemming the infodemic.
Dwivedi et al. (2020) present an assessment of critical challenges of COVID-19 through
an information system and technological perspective and offer insights for research and
recommendations studying the impact of COVID-19 on information management
research and practice in transforming education, work, and life.

To reduce the overlap with O’Leary (2020) and Rai (2020), this paper primarily focuses
on technology integration from the data, system, and people perspectives to discuss how
information systems and technology scholars could contribute knowledge and insights to
help fight the pandemic. As information systems and technologies are becoming
foundational to society, information systems and technology scholars are in an excellent
position to leverage their experience and knowledge with information systems and
various technologies to improve existing systems and technology practice and help the
society become digitally resilient to future large-scale disruptions.

2. Existing IT solutions
This paper uses the data-people-system framework to examine technology solutions to
mitigate the impact of the COVID-19 pandemic. The data-people-system framework by
Bardhan, Chen, and Karahanna (2020) demonstrates a multidisciplinary roadmap for
controlling and managing chronic diseases by focusing on the following three
components: (1) extraction, integration, and delivery of health data; (2) interoperability
of systems; and (3) guidelines and interface to guide people’s behavior. It must be noted
that the original data-people-system framework was proposed for chronic disease
management, which needs further development to be proactive and take account of the
pandemic context.

The COVID-19 pandemic has revealed the urgent need to redesign the public health
system from reactive to proactive and develop innovations that will provide real-time
information for proactive decision-making at the local, state, and national levels of public
health systems (Rai, 2020). COVID-19 is different from chronic diseases as it is highly
contagious, can pass from people to people, and has a high mortality rate. Additionally,
as COVID-19 is a new disease, scientific understanding of the virus that causes it, medical

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response, and actions by governments and organizations continue to evolve. The impact
of COVID-19 on people and society is changing daily in ways that would have been
unthinkable. As the current pandemic situation and its consequence continue to remain
fluid, combating the COVID-19 pandemic requires strong coordination of various
resources.

In response to the threats and risks posed by COVID-19, this paper adopts the data-
people-system framework to examine the existing technology solutions for fighting
against the COVID-19 pandemic and identify their challenges and potential opportunities
for information systems and technology researchers. In particular, we have conducted an
extensive search using academic databases and web search engines with a variety of
queries related to technology, coronavirus, and COVID-19, synthesizing the related
discussions in newspapers, news websites, blogs, white papers, practitioner websites,
grey literature or academic literature to help understand the existing information
systems and technology solutions and the roles that they could play in this challenging
time of the pandemic.

Some new technology applications such as mobile COVID-19 contact tracing apps and
chatbots have been recently developed to fight this pandemic. Applying these
technologies can help reduce the impact of the coronavirus pandemic on people,
organizations, and society. Effective and innovative use of emerging technologies can
help identify community spread of the coronavirus, monitor the condition of the infected
patients, improve the treatment of COVID-19 infected patients, and help develop medical
treatments and vaccines (Johnstone, 2020). This section evaluates these technology
applications based on the data-people-system framework by Bardhan et al. (2020).

Technologies powered by artificial intelligence (AI) including machine learning, image

recognition, and deep learning algorithms can be used for early detection and diagnosis
of the infection, more rapid drug discovery for developing new treatments (Brohi,
Jhanjhi, Brohi, & Brohi, 2020). A few companies also repurposed existing AI systems that
were initially designed for other areas to assist in social distancing enforcement and
contract tracing (Sipior, 2020).

3D Printing Technology can help make face masks and other Personal Protective
Equipment (PPE) for healthcare workers. Markforged has partnered with
Neurophotometrics to produce 3D printed rayon wrapped nasopharyngeal (NP) swabs
for COVID-19 testing. The swabs take less than three minutes to make, can be much
quicker at collecting viral particles (Markforged, 2020).

Big Data Analytics can be used to identify people that need quarantine based on their
travel history, predict the COVID-19 curve, speed up the development of antiviral drugs
and vaccines, and advance the understanding of the COVID-19 spread across both time
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and space. In Taiwan, big data analytics has been successfully applied to help identify
COVID-19 cases and generate real-time alerts through analyzing clinical visits, travel
history, and clinical symptoms (Wang, Ng, & Brook, 2020; Wang, Zha, et al., 2020;
Watson, Ives, & Piccoli, 2020).

HPC infrastructures and supercomputers are needed to address complex scientific

problems and process big datasets in shorter time frames in order to develop new drugs
and vaccines. The COVID-19 High-Performance Computing Consortium was launched to
leverage the computing resources and supercomputers in the US. The consortium
includes 16 public and private entities such as the US Department of Energy (DoE), IBM,
and other academic and industry leaders (Woo, 2020).

Mobile apps via smartphones and video-conferencing tools can be used to track the
movements of individuals, alert people from visiting COVID-19 hotspots, help doctors to
diagnose patients through video services and telemedicine/telehealth, support people
with online shopping, e-learning, online meetings, and telework (Marr B., 2020). Various
phone and network-powered apps have been developed to help healthcare workers and
ordinary people in this crisis. For example, the U.S. National Science Foundation funded
an award to support researchers at Princeton University in developing a system to deploy
a firmware update to mobile phones to provide proximity tracking ability for health
officials. To preserve users’ privacy, the key to the proximity data would be stored on the
phone itself and could only be unlocked when the phone’s owner voluntarily provided it
to health officials. Suppose a person tests positive for a disease such as COVID-19. In that
case, health officials could then use the system to automatically identify all other
cellphone users who were within a certain distance of the infected person for a certain
time. The time and distance could be determined by health officials based on knowledge
of the disease. Healthcare departments can contact those potentially infected people,
advise them of the exposure, and instruct them to get tested for the disease and self-
quarantine as needed (WHO, 2020).

Robots have been applied to fight the coronavirus outbreak. For example, hospitals use
robots as support systems to deliver food and medicine, disinfect rooms, and other
hotspots without direct human interaction with patients. A CNN news report shows that
doctors in Seattle have used a telepresence robot to treat the first confirmed patient who
tests positive for coronavirus in the United States (Chavez & Kounang, 2020). Drones also
are used to deliver medical supplies, patrol public areas, track non-compliance to
quarantine mandates, and so on (Marr B., 2020; Marr N., 2020).

The Internet of Things (IoT) can be used for the surveillance of people infected by
coronavirus to reduce the spread of the coronavirus (Kumar, Kumar, & Shah, 2020). IoT
consists of several functional components: data collection, transfer, analytics, and

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storage. IoT sensors installed on mobile phones, robots, or health monitors can be used to
collect data. Next, sensor data would be sent to the cloud server for processing, analytics,
and decision-making. As an example, IoT helps check whether patients follow quarantine
requirements. IoT can also be used to take the remote patients’ temperatures and then
transmit the data through mobile devices to the doctors to monitor, track, and alert while
reducing the chance for coronavirus inflections (He, 2020). Additional roles of IoT
technologies include the use of smart wearable devices in response to COVID-19 in early
diagnosis, quarantine time, and after recovery (Nasajpour et al., 2020).

Blockchain is a distributed ledger technology that records online transactions. It is

regulated through a consensus mechanism and is secured with cryptography (Chong,
Lim, Hua, Zheng, & Tan, 2019). As an example, a smartphone app that leverages
blockchain technology and AI was developed to help fight the coronavirus pandemic.
Blockchain technology enables the app to give each participant a "digital identity"
controlled by a private key that brings access to a digital version of paper certificates
issued by the government. These allow the confirmed healthy people to leave home to
buy food or to work (Sinclair, 2020). Blockchain has also been used to prevent the
information from being manipulated by unauthorized parties. During the outbreak, a
Chinese payment processor and financial services company used blockchain technology
to monitor the process of processing claims and making payouts in a more secure and
trustworthy way (News Staff, 2020). Blockchain technology has been applied to resolve
the tension and trust issues between maintaining privacy and addressing public health
needs, such as tracking infected patients in the fight against COVID-19 (Khurshid, 2020).

All the above technologies require the integration of data, people, and systems. Based on
their primary focus and original design intention for use in practice, we broadly classify
them into three categories. The data-centric technologies for combating COVID-19
include machine learning/deep learning, big data analytics, and HPC infrastructure. The
people-centric technologies include robots and 3D printing technology; they are used to
serve patients better and protect healthy people from infections with the support of
specific systems. The system-centric technologies include digital contact tracing apps,
the Internet of Things, and Blockchain; they are developed based on system concepts to
monitor patients and prevent healthy people from contracting coronavirus. Some of
these technologies are interrelated and may transcend multiple categories as they are
being used in dealing with the pandemic, depending on how creative people are using
them in varying contexts. For example, big data analytics that identify people who need
quarantine could have system-centric or people-centric aspects depending on the
specific purposes and use by different government agencies, health authorities, hospitals,
and organizations. Table 1 summarizes the three categories of technologies and their
required support from data, people, and systems.

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Table 1. Summary of technology solutions for COVID-19.

Technologies COVID-19 Solutions Data System People

Analyze epidemic real-time

situations (Punn, information
Sonbhadra, & from the
Agarwal, 2020)

Diagnostic and computed fully automatic deep 5372 patients

prognostic analysis tomography learning system
(Wang, Ng, et al., images
2020; Wang, Zha, et
al., 2020; Watson, Ives,

Machine et al., 2020)

Learning/Deep Automatically raw chest X-ray 125 patients

Learning detection of COVID-19 images
cases (Ozturk et al.,
2020)

Early triage of medical records 1590 patients,

critically ill COVID-19 from of which 131
patients (Liang et al., laboratory- developed
2020) confirmed critical
hospitalized illness, from
cases 575 medical
centers

Big Data Early detection and smart contact 627,386

Analytics diagnosis (Chen et al., tracing–based potential
2020) mobile sensor contact-
data and other persons in
big sensor Taiwan
surveillance
data

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Technologies COVID-19 Solutions Data System People

Tracking movements 26.76 million Baidu Migration Map 115,000

of people, sleep and people in
understanding resting heart Hubei
epidemic trends, and rate data points province and
control and regulate from users’ the nearby
pharmaceutical smart bracelets Anhui
supplies (Liu., 2020; and watches province
Ting, Carin, Dzau, &
Wong, 2020)

New drug and vaccine screening 2201

development (Wang, approved drugs

HPC 2020)

Infrastructures Target exploration Alibaba’s super-

and drug selection computing power
(Liu, 2020)

Robots Deliver food and Robot-controlled Patients;

medicine; Disinfect noncontact ultraviolet Healthcare
rooms; Treat patients (UV) surface workers
(Yang et al., 2020) disinfection;
Mobile robots for
temperature
measurement;
Automated or robot-
assisted
nasopharyngeal and
oropharyngeal
swabbing; Autonomous
drones or ground
vehicles; Automated
camera systems;
Social Robots

3D Printing Produce protective Personal protection Patients;

Technology masks; Make test systems; Healthcare
swabs (Choong et al., Practice system for workers
2020) COVID-19 swab testing
procedures;

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Technologies COVID-19 Solutions Data System People

Temporary emergency
dwelling

Digital Contact Track movements of Mobile data; Smartphone tracing Patients;

Tracing individuals; Alert Social media apps Healthcare
Technology people from visiting data workers;
COVID-19 hotspots Public
(Budd et al., 2020)

Internet of Ensure patient Mobile data; IoT based smart disease Patients;
Things compliance with Sensor data surveillance systems Public
quarantine
requirements; Monitor
patients remotely
(Rahman et al., 2020)

Blockchain Develop "digital COVID-19 Immunity certificate Public

identity" for healthy related health system
people; Process Claims data
and make buyouts
(Bansal, Garg, &
Padappayil, 2020)

3. Challenges
The COVID-19 pandemic has exposed the weaknesses of existing public health systems.
The use of technologies to combat the pandemic raises challenges in many aspects. The
specific nature of the COVID-19 pandemic requires strong coordination of connected
data, people, and systems (Bardhan et al., 2020) to facilitate worldwide collaboration in
fighting against it. Traditionally, public health agencies and healthcare stakeholders have
not used the same systems, data formats, or standards, hampering the ability to identify
trends and develop interventions against the pandemic. Public health researchers,
epidemiologists, and government officials need to be connected via integrated systems
with connected data to understand the evolving pandemic better and make collective
decisions on addressing this crisis. As people play a crucial role in this fight against the
COVID-19, it is essential to connect, coordinate, and support various stakeholders
through innovative and integrated technologies.

3.1. Connecting systems to integrate technologies

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Emerging technologies including the IoT, big-data analytics, AI, and blockchain can be
integrated to develop smart strategies for addressing immediate challenges caused by
the coronavirus. For example, Facebook has used artificial intelligence and big data
technologies to tap into satellite imagery and census data to generate maps that display
population density, demographics, and travel patterns in order to help decide where to
send supplies or how to reduce the spread (Holt, 2020). Big data analysis of geographic
information systems (GIS) and IoT sensor data collected from infected patients can assist
epidemiologists to trace patient zero and help identify close contacts of the infected
patients (He, 2020). The U.S. National Science Foundation recently funded a RAPID award
that explores the capabilities and potential of integrating social media big data,
geospatial data, and AI technologies to enable and transform spatial epidemiology
research and risk communication. The emerging convergence of blockchain, the IoT, and
AI holds great promise for addressing the issues of trust and security in public health
(Gurgu, Andronie, Andronie, & Dijmarescu, 2019; Singh, Rathore, & Park, 2020). For
example, medical device data and non-personal sensor data collected by IoT can be
stored and shared on the blockchains. Patients’ personal data can still be stored in the
hospitals’ enterprise systems due to privacy regulations such as the GDPR (Agbo,
Mahmoud, & Eklund, 2019; Onik, Aich, Yang, Kim, & Kim, 2019). AI and big data
technologies can be leveraged to analyze and visualize both on-chain and off-chain data
and provide near real-time analytics and recommendations to relevant stakeholders
through customized dashboards.

Currently, most systems and apps that have been used to deal with the pandemic are
poorly inter-connected since they are developed by different government agencies,
health authorities, and organizations. There is a lack of systematic frameworks and tools
to accomplish systematic integration across various technologies in the global response
against pandemic challenges.

To integrate these different technologies, guidelines and systematic efforts are required
to coordinate the collection of large amounts of quality data related to coronavirus cases.
The design of effective big data analytics and AI algorithms requires public health
departments and hospitals to provide a large amount of reliable and high-quality data.
Due to a lack of standards, the integration of multiple data sources for promoting
interoperability is challenging. Some data sources may be well structured, while others
are not (Pham, Nguyen, Huynh-The, Hwang, & Pathirana, 2020). There is also a need to
generate standardized protocols to facilitate communication across systems without
compromising data security. Governments, leading tech firms, health organizations, and
other relevant stakeholders need to collaborate efficiently and effectively to define the
standard, protocols, data formats and types, etc.

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Information systems and technology scholars have been examining system integration in
enterprise or organizational environments over the past several decades (Henningsson,
Yetton, & Wynne, 2018; Ravichandran & Rai, 2000; Xu, 2011). Information systems and
technology scholars also studied the role of information systems in crisis, disaster, and
emergency response (Chen et al., 2008; Pan, Pan, & Leidner, 2012; Valecha, Rao,
Upadhyaya, & Sharman, 2019). Information systems and technology researchers should
take the opportunity to offer their expertise in system integration and experience with
emergency or crisis response systems to provide recommendations and strategies to help
developers with various systems and technology integration efforts.

3.2. Connecting data to share best practices

As the World Health Organization (2020) suggests, new collaboration and knowledge
sharing are needed to deliver targeted solutions through a coordinated effort to support
countries facing stages of this epidemic in different ways and at different times. Faced
with a global pandemic, countries need to work together to share data, information,
resources, effective practices, and strategies to combat the coronavirus. In addition,
global collaboration among relevant stakeholders between organizations and
governments will be crucial to coordinating the sharing and use of data and knowledge
to solve the problems we encountered during this pandemic. For example, China took
extraordinary measures for the shutdown of Wuhan, a large city with millions of people,
to control the spread of the coronavirus (Lin et al., 2020). Useful experience and lessons
related to its efficacy as a containment measure could be valuable for other countries
who are considering similar measures. Data integration and knowledge management
(KM) technologies such as web portals, knowledge repositories, and online communities
of practice can be used to empower data connections to leverage resources more
effectively and efficiently at a lower cost (Bardhan et al., 2020; Pan, Cui, & Qian, 2020).

Knowledge-based systems such as expert systems and intelligent decision technologies

have been used to support health workers in detecting and diagnosing patients, and
providing decision-making support for relevant healthcare stakeholders and decision-
makers in a pandemic crisis (O’Leary, 2020; Rehfuess et al., 2019). Data mining and
visualization technologies have been used to discover and visualize knowledge evolution
across time and locations as the coronavirus outbreak continues to evolve. Online health
communities have been established to help healthcare workers, patients, and other
stakeholders learn about COVID-19, symptoms, and the effectiveness of treatments (Yan
& Tan, 2014; Ziebland et al., 2004). However, these systems often operate in a silo, and
the data, information, and knowledge stored in their systems are not widely shared. To
allow various systems and stakeholders in different communities of practice to share
knowledge within and across their individual areas, we need to create an environment to
encourage people across countries to share knowledge instead of keeping or holding the
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knowledge. In the context of a coronavirus outbreak, strategies could be developed to

assess the quality of the knowledge and help systems break down silos that hinder
communication and sharing data more efficiently.

Besides, behavioral issues need to be addressed to facilitate the sharing of data and best
practices among stakeholders. Over the years, there have been a number of calls for
information systems and technology researchers to consider the unintended or negative
consequences of technologies (Chiasson, Davidson, & Winter, 2018). IT professionals have
been rushing to build apps, services, and systems for contact tracing, tracking, and
quarantine monitoring. Some of these technologies are lightweight for short-term use,
while others are pervasive and invasive (O’Neill, Ryan-Mosley, & Johnson, 2020). For
example, many researchers have advocated the use of digital contact tracing and health
code apps (Oxford Analytica, 2020) to reduce the spread of the disease. Some people are
concerned that short-term fixes such as monitoring of infected people via an app could
lead to a permanent state of surveillance by the government (Lin & Martin, 2020). Digital
contact tracing can be effective but is controversial because it could have disastrous
consequences if not implemented with proper privacy checks and encryption (Huang,
Sun, & Sui, 2020). For example, some experts are questioning how anonymous the data is
and whether it can be easily de-anonymized to identify or infer the personal identity of
infected persons (Lee & Roberts, 2020). Healthy authorities may misuse or abuse the data
they collected from digital tracing mobile apps for long-term and other purposes. Many
people are concerned about whether these coronavirus-fighting apps are secure to use,
how these apps will preserve privacy, and what policies are needed to prevent the abuse
(O’Neill et al., 2020). These concerns are likely to undermine public trust and affect
people’s adoption of emerging technologies. There is also a need for further research to
investigate security, privacy, and ethics issues related to technologies developed for
fighting this pandemic.

Knowing about coronavirus exposures is important for containing the spread of COVID-
19. Governments around the world are introducing technologies such as mobile apps to
help health officials trace contacts of people newly infected with the coronavirus. These
mobile apps work by recording whom a person comes close to—then alerting those
people if a person contracts COVID-19. Out of precaution to protect people’s privacy and
reduce people’s concern on increased surveillance, Australia made it illegal for non-
health officials to access data collected on smartphone software to trace the spread of
the coronavirus. The European Data Protection Board (EDPB) has published guidance for
the use of location data and contact tracing tools in order to mitigate privacy and security
concerns. Apple and Google disclosed a series of changes including stronger privacy
protections and accuracy to their COVID-19 contact tracing initiative.

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On the other hand, some researchers think that it is justified to temporarily relax privacy
measures for such technologies in the hopes of possibly saving lives, serving the public
good, and protecting public health under pandemic circumstances. Many people have
been engaged in self-disclosure on social media to share personal information such as
health status and preventive behaviors (e.g., wearing masks and buying sanitizing
products) because sharing such information contributes to the public good (Nabity-
Grover, Cheung, & Thatcher, 2020). Some researchers hold that privacy concerns should
not decrease the usefulness of technology to protect public health (Cho, Ippolito, & Yu,
2020). They do not think such technologies were designed to make a permanent change
to society (Ferretti et al., 2020). The lack of a consensus on privacy protection in
technologies against COVID-19 indicates a strong need for establishing best practice
guidelines to reassure citizens on data collection (Fahey & Hino, 2020).

Public trust and confidence are necessary to people’s adoption of various technologies
including sharing their data to address the challenges caused by this pandemic (Ferretti
et al., 2020). Currently, the adoption of digital contact tracing apps is voluntary in
western countries. It has been recognized that these issues cause more controversy in
Western countries with a culture of individualism such as Europe and the U.S. than in
countries with a culture of collectivism. However, at least 60 percent of people with
smartphones would need to opt-in for such apps to be effective (Scott, 2020). How to
incentivize mass user adoption of these apps is a challenge. In the context of this
coronavirus pandemic with a lot of loss of life, information systems and technology
scholars can help evaluate the use of digital data and technologies including AI-related
algorithms in a responsible manner, provide oversight for user-related data, develop
ways to incentivize users to share relevant data as needed, help develop mechanisms to
ensure that technology design and use are guided by ethical principles in order to ensure
transparency, equity, and security and increase public trust and confidence (Ienca &
Vayena, 2020; Lee & Roberts, 2020). Information systems and technology scholars can
also help identify best practices to implement responsible data-collection and data-
processing, and achieve a balance between privacy and utility of the proposed
technologies.

3.3. Connecting people with enhanced collaborative tools and IT

infrastructures
The COVID-19 outbreak is rapidly changing the workplace. Millions of people are moving
their workspaces to their homes through teleworking. Many industries benefit as
knowledge workers learn to operate virtually, work from home, and use cloud services to
process and store files. We are witnessing wider acceptance of online services by people
and diverse types of industries during this pandemic. The importance of IT infrastructure
in enabling teleworking, online learning, e-government, e-commerce, and other online
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activities has been widely recognized. The pandemic is forcing a record number of
employees to work remotely for an extended duration, which results in heavy traffic on
remote connectivity networks. There are vital needs for society to continue investing in
IT infrastructure and accelerate digital transformation efforts to deal with the impact of
COVID-19 and future public health crises (Watson, Ives, et al., 2020). Companies need to
enhance their investments in tools such as video conferencing and group decision-
making support systems (Xu, Du, & Chen, 2015) to enable personnel and distributed
teams to work remotely and collaborate virtually. On the other hand, costs for IT
infrastructure are exploding as employees practice teleworking and students take online
classes in light of the COVID-19 outbreak. It is necessary to understand the rise in hard
costs of IT infrastructure associated with meeting spiking demand. As the pandemic
continues to evolve, IT infrastructures need to be enhanced for workers to perform their
duties safely and healthily (CISA, 2020). Some critical tasks may not be executable from
home, and workarounds need to be identified. It is particularly necessary to identify the
factors that drive the cost of serving the increased demand due to teleworking, such as
cloud server costs, video conferencing costs, additional licenses for support products.
Cloud services should be further leveraged through existing infrastructures such as
Google Cloud, Azure, AWS, or Salesforce. Strategies need to be developed to keep
essential functions and services up and running. CIOs need to think about retrofitting the
present for the new needs or creating new systems for new situations (Watson, Ives, et
al., 2020). Finally, digital infrastructure readiness and resilience are also important areas
to explore (Papagiannidis, Harris, & Morton, 2020).

Group decision-making is often needed for complicated situations involving much

uncertainty and time constraints. Information systems and technology scholars can share
their experience with group decision support systems to support collective decision
making regarding the evolving pandemic, help connect stakeholders at different levels to
build consensus, and support governments, health authorities, organizations, and the
public to make culturally appropriate and sensitive decisions regarding the infection
detection, infection prediction, and infection avoidance and when to reopen the
economy. Information systems and technology scholars can also help build collaborative
information systems, community-based information systems, talent, and volunteer
networks to leverage the expertise and time of various stakeholders. As an example, an
innovative application is a wastewater COVID-19 early warning detection system.
Wastewater detection of COVID-19 could act not only as a supplement to medical testing
but as an early warning system for community monitoring and prevention. Continued
wastewater-based monitoring could alert public health officials whether the coronavirus
is still circulating in a community (Chakradhar, 2020). A lot of volunteers are needed to
make the wastewater COVID-19 early warning detection system successful. Information
systems and technology scholars can contribute by providing expertise to help the

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government, authorities, and local communities to design and develop a volunteer

network to engage and organize a large number of volunteers, and help build a
collaborative information system to deliver a national program in this area (Thomas &
Bertsch, 2020). As Rai (2020) points out, swift deployment of grassroots innovation could
develop rapid solutions to meet urgent needs.

3.4. Studying human behavior with technologies and digital divide

It is important to study human behavior when designing, building, and using
technologies as more COVID-19 related technologies are being developed, integrated, and
used by governments, organizations, and people. Lots of efforts to combat the pandemic
incorporate new technological advances and approaches in integrating various systems
and innovations. However, we need to acknowledge that people’s misbehavior with
technologies may reduce the eff ;ectiveness of the technology-related interventions or
countermeasures on containing the coronavirus break. Information systems and
technology scholars can contribute by incorporating their understanding of human
behavior into the technology design and development process, leading to more effective
technology (Pfleeger & Caputo, 2012). A large number of theories and models such as the
technology acceptance model, innovation diffusion theory, the theory of reasoned action,
health belief models and theory of planned behavior, social cognitive theory, and
motivation theory can be used to explore the acceptance and use of COVID-19 related
technologies such as telehealth technologies, study the strategic role of various
technologies in dealing with the COVID-19 pandemic, and also examine unintended
consequences of using technologies. For example, information systems and technology
scholars can examine online users’ information sharing behavior, study how online
patient communities should be engaged and incentivized to share information and
support COVID-19 patients and caregivers, and how to analyze data to reveal new
insights to support policy-making for health departments and medical knowledge
discovery (Bardhan et al., 2020).

We have also witnessed a digital divide during the pandemic. The digital divide broadly
refers to the uneven access to digital content and connection because of some people
who do not own or have easy access to technology. People's ability to use technologies
effectively remains inequitable (Newman, Browne‐Yung, Raghavendra, Wood, & Grace,
2017). As emerging technologies such as mobile apps, AI, IoT, and big data analytics are
increasingly used to fight the pandemic, existing disparities, inequality, and biases are
further reinforced (Park & Humphry, 2019). As people spent more time working, learning,
socializing, and shopping online at home, this pandemic provides a chance to assess the
issues and challenges faced by the rapid digital transformation of organizations and how
the digital divide impacts people (e.g., underprivileged populations, women, workers in
healthcare, elderly and those at-risk) (Venkatesh, 2020). Therefore, information systems
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and technology scholars need to help develop strategies and approaches to addressing
digital inequality and disparity, especially when the governments need to flatten the
curve of infection.

Information systems and technology can play a significant role in improving the visibility
of digital inequality and disparity at organizations and communities (Bardhan et al.,
2020). Data shows Black and Hispanic populations face higher exposure to coronavirus
and more significant hurdles for medical treatment and level of care (Nemo, 2020).
People of color communities tend to have relatively lower public health literacy and less
experience in finding and evaluating healthcare information. Information systems and
technology scholars can investigate to what extent the marginalized, women, elderly,
and people of color are engaged, included, and impacted by these COVID-19 technology-
related applications and systems, including health information seeking tools, mobile
contact tracing, and tracking apps, COVID-19 self-checking chatbots, quarantine
monitors, and telemedicine in a sustainable manner. It would be valuable to understand
the short, medium, and long-term impacts of the digital divide during the COVID-19
pandemic response on marginalized groups, women, the elderly, people of color and
people in rural settings. Information systems and technology scholars can do their part to
improve technology design and processes to promote digital inclusion, assist with
efficient development and sustainable implementation of the proposed technology,
particularly in underserved populations. For example, Goh, Gao, and Agarwal (2016))
showed that technology-mediated online health communities could share information
and alleviate rural-urban health disparities. Online health communities can also support
the most vulnerable family caregivers (Friedman, Trail, Vaughan, & Tanielian, 2018).
Information systems and technology scholars can explore factors affecting underserved
populations and communities to adopt and effectively use emerging technologies,
encourage information sharing behavior during this crisis, and identify strategies to
incentivize the mass adoption of relevant coronavirus-fighting technologies by
underserved populations. Understanding the underserved population's unique
perspectives in this coronavirus outbreak can provide guidelines for future IT systems
and applications design, development, and potentially improve the adoption and use of
novel IT systems.

4. Conclusion
The COVID-19 pandemic has produced significant impacts on people, businesses, and
society. The pandemic also has implications for the design, development, and use of
technologies (Sein, 2020). Technologies can be useful for reducing the severity of the
coronavirus pandemic’s impact on people, organizations, and society. However, the use
of technologies to combat the pandemic raises challenges such as security, privacy,
biases, ethics, and the digital divide. This paper evaluates the technology applications
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based on the data-people-system framework and suggests that the specific nature of the
COVID-19 pandemic requires strong coordination for connected data, people, and
systems to facilitate worldwide collaboration.

Future pandemics are likely to come. While information systems and technology scholars
might not be able to help with the scientific aspect of developing vaccination and
treatment directly, we can contribute knowledge, experiences, and time to help society
better prepare for future pandemics. To mitigate future pandemics’ costs and improve
data sharing during global public health crises, Chin and Chin (2020) called for
establishing a global common data space for highly infectious diseases. While it is very
challenging to establish a global common data space for public health data sharing due
to various reasons such as technical, geopolitical, and ethical barriers, we support this
call for its promising benefits and broader social good. At this stage, information systems
and technology scholars can at least help advocate and build a national common data
space or health information systems for public health data sharing.

Solving grand challenges facing society requires significant financial and human
resources. To increase the importance and relevance of information systems and
technology research, we encourage scholars to actively apply for various government and
industry grants, including various COVID-19 funding opportunities, to get financial
support to put some of their research ideas into practice. For example, the U.S. National
Science Foundation and National Institutes of Health have grants programs that support
technology-related research to develop solutions to addressing challenges caused by the
coronavirus. Information systems and technology scholars should get involved by leading
or joining an interdisciplinary team to write grant proposals and get funding to directly
work on some of these research ideas. Furthermore, many students including
undergraduate and graduate students in information systems and technology are looking
for internship opportunities. Since many small businesses in industries such as tourism,
food service, and retail are being hit hardest by the pandemic, information systems and
technology faculty could collect student resumes, put them on a Google drive or a
website, and share the resumes with interested small business owners. This would help
match information systems and technology students with interested small businesses or
non-profit organizations to solve the technology and other issues they may have during
the pandemic. We are glad that some of the information systems and technology faculty
are doing this and mentoring small business owners on deploying digital technologies to
deal with the challenges of business continuity (Papadopoulos, Baltas, & Balta, 2020).
Some professors were involved in digital solution development projects (e.g., tackling
misinformation) and helped to organize events such as online hackathons to gather
people with diverse skills to work on solutions to help society fight COVID-19 (Bacq,
Geoghegan, Josefy, Stevenson, & Williams, 2020; Pan & Zhang, 2020). We hope to see
more information systems and technology scholars involved in building and expanding
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technology volunteer networks and mobilizing community resources and services to

fight COVID-19. At last, some of the developed technologies and application for this
pandemic may cease to be useful after the pandemic ends, but many will likely be
retained, enhanced, or repurposed for other uses (Oxford Analytica, 2020), in which
information systems and technology scholars can continue to play a role after the
pandemic. For example, will data collected from mobile contact tracing be destroyed
after this pandemic? What data management policies are needed to prevent the abuse of
the user data and guide the improved design, development, and use of future mobile
contact tracing and tracking tools?

CRediT authorship contribution statement

Wu He: Conceptualization, Investigation, Writing - original draft, Writing - review &
editing. Zuopeng (Justin) Zhang: Writing - original draft, Writing - review & editing.
Wenzhuo Li: Writing - original draft, Writing - review & editing.

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