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RESEARCH ARTICLE
Global survey-based assessment of lifestyle
changes during the COVID-19 pandemic
Poonam Agarwal
1☯
, Abhinav Kaushik
2☯
, Sutapa Sarkar
3¤
, Deepti Rao
1‡
,
Nilanjan Mukherjee
4‡
, Vinita Bharat
5
, Subhamoy Das
5
, Amit Kumar SahaID
6
*
1Department of Dermatology, Stanford University School of Medicine, Stanford, CA, United States of
America, 2Sean N. Parker Center for Allergy and Asthma Research at Stanford University, Stanford
University School of Medicine, Stanford, CA, United States of America, 3Gastroenterology and Hepatology,
Stanford University School of Medicine, VA Palo Alto, Palo Alto, CA, United States of America, 4Department
of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA, United States of
America, 5Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, United
States of America, 6Department of Biochemistry, Stanford University School of Medicine, Palo Alto, CA
United States of America
☯These authors contributed equally to this work.
¤Current address: Machaon Diagnostics, Inc., Oakland, CA, United States of America
‡ These authors also contributed equally to this work.
*amit.saha@stanford.edu
Abstract
Along with the major impact on public health, the COVID-19 outbreak has caused unprece-
dented concerns ranging from sudden loss of employment to mental stress and anxiety. We
implemented a survey-based data collection platform to characterize how the COVID-19
pandemic has affected the socio-economic, physical and mental health conditions of individ-
uals. We focused on three broad areas, namely, changes in social interaction during home
confinement, economic impact and their health status. We identified a substantial increase
in virtual interaction among individuals, which might be a way to alleviate the sudden unprec-
edented mental health burden, exacerbated by general awareness about viral infections or
other manifestations associated with them. The majority of participants (85%) lived with one
or more companions and unemployment issues did not affect 91% of the total survey takers,
which was one of the crucial consequences of the pandemic. Nevertheless, measures such
as an increased frequency of technology-aided distant social interaction, focus on physical
fitness and leisure activities were adopted as coping mechanisms during this period of
home isolation. Collectively, these metrics provide a succinct and informative summary of
the socio-economic and health impact of the COVID-19 pandemic on the individuals. Find-
ings from our study reflect that continuous surveillance of the psychological consequences
for outbreaks should become routine as part of preparedness efforts worldwide. Given the
limitations of analyzing the large number of variables, we have made the raw data publicly
available on the OMF ME/CFS Data Center server to facilitate further analyses (https://
igenomed.stanford.edu/dataset/survey-study-on-lifestyle-changes-during-covid-19-
pandemic).
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OPEN ACCESS
Citation: Agarwal P, Kaushik A, Sarkar S, Rao D,
Mukherjee N, Bharat V, et al. (2021) Global survey-
based assessment of lifestyle changes during the
COVID-19 pandemic. PLoS ONE 16(8): e0255399.
https://doi.org/10.1371/journal.pone.0255399
Editor: Jeffrey Shaman, Columbia University,
UNITED STATES
Received: February 4, 2021
Accepted: July 15, 2021
Published: August 13, 2021
Copyright: ©2021 Agarwal et al. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which
permits unrestricted use, distribution, and
reproduction in any medium, provided the original
author and source are credited.
Data Availability Statement: The raw data is
publicly available on the OMF ME/CFS Data Center
server to facilitate further analyses. https://
igenomed.stanford.edu/dataset/survey-study-on-
lifestyle-changes-during-covid-19-pandemic.
Funding: Financial support from Open Medicine
Foundation (OMF).
Competing interests: The authors have declared
that no competing interests exist.
Introduction
The novel coronavirus, SARS-CoV-2 emerged in Wuhan, China, in early December of 2019
and is known to cause mild to severe respiratory illness when transmitted to humans [1]. It
was previously considered to be droplet-borne and highly infectious due to several cases of
human- human transmission through coughing, sneezing and nasal mucosa [2]. However, sev-
eral recent studies have reported that SARS-CoV-2 virus particles are not only transmitted via
droplets but also through air (airborne transmission) and cause infections [3–5].
The symptoms of the disease include high fever, cough, fatigue and shortness of breath
[6], and is often accompanied by abdominal pain, diarrhea and nausea. Due to its similarity in
the symptoms with Severe Acute Respiratory Syndrome (SARS), this novel infectious virus
was named as SARS-CoV-2 and the disease was named as Coronavirus Disease 2019 or
COVID-19 [7].
COVID-19 outbreak started in the Hubei Province of Wuhan and took the shape of an epi-
demic in China by late January where numerous cases emerged at an alarming rate. There was
a marked increase in new cases in USA, Europe and South Asian countries by late February,
which prompted the World Health Organization (WHO) to declare it as a ‘Pandemic’. By
mid-April 2020, at least 200 or more countries were affected with the virus, owing to its very
high transmission rate. One of the major concerns of this disease is the asymptomatic trans-
mission among individuals. Several infected individuals may show very mild to no symptoms
for COVID-19 disease, but are still capable of spreading it to other individuals [8,9]. Prelimi-
nary studies and several data reports suggest that this virus infects people with comorbidities
(one or more chronic diseases) and old people more aggressively, than people of younger age
[10]. A study in Nature Medicine showed that the number of cases in children was low as com-
pared to the adults from the data collected from China, Italy, Japan, Singapore, Canada and
South Korea [11]. Even though COVID-19 hospitalizations and death can occur in young and
middle-aged adults, people of age 60 years or older are subject to higher risk [12]. Also, several
reports suggest that adults and old people with pre-existing medical conditions like diabetes,
kidney disease, cardiovascular disease, chronic obstructive pulmonary disease, hypertension
and several other chronic illnesses are more severely affected [13–16]. With the progression
of this pandemic since over an year, emerging studies suggest that the novel variants of
SARS-CoV2 virus including the B.1.1.7 variant may be significantly more transmissible and
infectious outcompeting the preexisting variants [17].
The consequences of the COVID-19 pandemic has not only incurred a worldwide negative
impact on the socio-economic status but also threatened people’s lives and caused high mortal-
ity rates in an unanticipated manner [18]. The prevalence of infection, patient surges and
death rates eventually led to situations of lockdown or shelter-in-place practices in different
countries, thereby introducing an unforeseen challenge in the daily lives of people across the
globe [19,20]. As a safety measure to prevent the spread of COVID-19, social distancing and
home isolation strategies including closing schools, offices, factories and other public places
had been adopted globally. These strategies have proven to reduce cross-infection effectively
[21]. However, as humans have evolved to be socially connected, these long periods of confine-
ment have influenced an individual’s life in different ways based on one’s situations and the
dwelling environment. For instance, the effect of lockdown/shelter-in-place has caused not
only mental health burden in common people worldwide, but also has affected some of them
financially. Due to the lockdown policies, the government of respective countries had to close
schools and colleges, lay off individuals from jobs or overwork healthcare workers for treat-
ment of the infection surge. These unprecedented actions have led to an inevitable change in
social practices and norms. In this era of globalization, an abrupt change in the fast-paced
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lifestyle to a sedentary lifestyle has created both positive and negative effects on the common
population. While a few people have discovered new hobbies, habits, several others have been
a victim of anxiety and depression, especially for young adults. While there have been substan-
tial investigation into understanding the physiological aspects to develop diagnostics [22] and
vaccines [23], the socio-psychological impacts of the pandemic remain understudied. Here we
present the findings from our study to investigate how the global lifestyle changes have affected
the socio-economic, physical and mental well-being during the ongoing COVID-19 pandemic.
Given the limitations of analyzing the large number of parameters, we have made the raw data
publicly available on the OMF ME/CFS Data Center server. (https://igenomed.stanford.edu/
dataset/survey-study-on-lifestyle-changes-during-covid-19-pandemic).
Materials and methods
Sample and Study Design: This study was based on a series of survey-based questions con-
ducted in the period between June 10 and August 5, 2020. A 3-months online questionnaire
survey was conducted on the REDCap software, a secure and widely used platform for creating
custom modules to post online questionnaires and collect data worldwide. The online survey
link was circulated through a standard study invitation message within known acquaintances,
social media and communication platforms such as email, Linkedin, Facebook, Instagram,
Twitter and WhatsApp. Only individuals above the age of 18 years were allowed to participate
in the study. There were no other exclusion criteria.
We applied the principle of maximum diversity to recruit a representative sample for this
study. The survey was eligible for participants who are 18 years old or above. As an effort to
sustain maximum representativeness and in order to keep the survey unbiased, the partici-
pants could belong to any geographical location. A total of 3253 responses were collected
across 47 countries using the RedCap survey link (Table 1). After excluding responses that met
the exclusion criteria (age <18 years), duplicates and invalid entries, the final data included
2683 participants.
The questionnaire included three domains/sections: demographic information (such as
age, sex, living areas, education and occupation), hobbies and habits, effect on socio-economic
lives and mental health/disease awareness. All analyses were performed using R software with
gg plot package. A majority of the final plots were made using GraphPad Prism. This was pri-
marily an observational study, and hence detailed statistical analyses were outside the scope of
this manuscript.
The study was approved by the Stanford University Institutional Review Board (Protocol
56465; Exempt). Only participants over the age of 18 were considered for the study. Informed
consent was obtained for study participation from all the participants. Written consent was
obtained electronically prior to the start of the survey. The survey can be found here: https://is.
gd/COVIDSocialSurvey.
All the raw data are available on the OMF ME/CFS Data Center server, including data col-
lected after August 5, 2020 (https://igenomed.stanford.edu/dataset/survey-study-on-lifestyle-
changes-during-covid-19-pandemic). Readers can perform subsequent analyses on the avail-
able data, to shed further light on the different parameters. The survey link is still active, but
there has been no active promotion of the study beyond the mentioned date range.
Results and discussion
As of August 5, 2020, there were 2683 valid, questionnaire entries which comprised 82.4% of
the total participants who initiated the survey (Table 1). The online survey method of
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nonprobability sampling was used to recruit participants via social media posts that targeted
the general adult population (aged >18 years old).
This sample population was composed by anonymous denizens of 47 countries, with the
highest number of participants from the United States, India, New Zealand and Australia
(Table 1). Age-wise profiling of the survey takers show that 22.7% of the participants belonged
to the age group between 56–65 years alone, followed by 26–35 years (20.6%) age group. Indi-
viduals under the age groups of 36–45 years and 46–55 years also formed a significant portion
(36%) of the survey participants (Fig 1A). The rest were either adults younger than 25 years
old (7.6%) or senior citizens above 65 years old (13.1%). The majority of participants were
female (1967/2683) and approximately one- fourth of the total participants were male (680
participants). There were also a small number of participants who identified as transgenders (6
people), other (8), and 22 participants chose not to disclose their gender. Since the number of
participants who identified as male or female was much larger, our analyses only consider
these two categories. The educational status for most of these participants ranged from an
undergraduate to graduate degree as their highest qualification with 88.9% of the people
Table 1. List of countries where the survey participants were located, with the corresponding number of participants per country.
Country Total entries Completed entries Country Total entries Completed entries
United State of America 2283 1991 Netherlands 5 3
India 372 266 Spain 4 3
New Zealand 93 79 Slovakia 3 3
Australia 78 65 China 5 2
Canada 61 40 Saudi Arabia 3 2
Italy 52 34 Israel 2 2
France 31 25 Singapore 2 2
Nepal 37 21 United Arab Emirates 2 2
United Kingdom 22 19 South Africa 3 1
Indonesia 22 16 Ukraine 3 1
Pakistan 21 14 Papua New Guinea 2 1
Hungary 15 12 Poland 2 1
Germany 12 11 Slovenia 2 1
Croatia 14 10 Switzerland 2 1
Mexico 10 10 Turkey 2 1
Malaysia 8 7 Algeria 1 1
Brazil 8 6 Austria 1 1
Bosnia and Herzegovina 7 6 Bangladesh 1 1
Sri Lanka 6 4 Egypt 1 1
Luxembourg 5 4 Liberia 1 1
Greece 4 4 Monaco 1 1
Taiwan 7 3 Romania 1 1
Uganda 1 1 Sweden 1 1
Afghanistan 17 0 Tanzania 1 1
Angola 3 0 Burundi 1 0
El Salvador 2 0 Christmas Island 1 0
Akrotiri 1 0 Ireland 1 0
American Samoa 1 0 Japan 1 0
Antarctica 1 0 Portugal 1 0
Belgium 1 0 South Korea 1 0
Burundi 1 0 Zimbabwe 1 0
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having a bachelor’s degree or higher (Fig 1B). The survey takers had the following racial/ethnic
identities: White, Asian, Hispanic or Latino, Black or African American and “others” such as
Native Americans, Hawaiians, Pacific Highlanders, Alaskan Native, or some with more than
Fig 1. Graphical representation of demographics of the study participants. Age-distribution of the participants. B. Educational status of the participants.
C. Racial/ethnic background of the participants. All the plots are further subdivided by gender.
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one racial identity. The majority of the participants were either White (60.4%) or Asian (23.6%),
whereas 16% participants fell under the above mentioned “other” categories (Fig 1C). For each
of these categories, distribution for male vs. female participants is represented in the plots.
To gain insights on the impact of the COVID-19 pandemic on professional lives, we asked
the occupational background of the survey takers by listing a range of employment categories
or occupational groups including art and entertainment, finance, research, first responders,
healthcare, news and media, transportation, civil and military services and other relevant staff.
The highest percentage of our survey takers belonged to the healthcare sector (31.2%). About
26% of the survey takers opted not to disclose their occupational category. The next three high-
est representations were from education (9.5%), science and technology (8.1%) and research
sectors (6.4%) (Fig 2A). Furthermore, to analyze how their occupational lives were influenced
by the unprecedented changes in the routine, we asked what best reflected the survey takers
current professional status. Fig 2B is a heat map looking into the current employment status,
taking into account potential overlaps between different professional statuses. The colored
grids represent overlaps between any two given categories. For the non-overlapping popula-
tion, represented along the diagonal, we have specified the exact number of participants in the
figure. For the participants who have two professions, we represented the numbers using a
color scale. The numerical values in the diagonal grids represent the total number of partici-
pants in individual categories. Even though there was a rapid shift to remote working options,
most of the participants were employed full-time followed by a second highest group of retired
personnel who took our survey. A smaller subset of the participants belonged to part-time or
self-employment status followed by students, unemployed members and homemakers (Fig
2B). Thus, compared to other occupational groups, more than 50% of the survey takers
belonged to full-time research and healthcare segments. Moreover, we found some overlap
between the different categories. For instance, most of the full-time workers were students or
self-employed individuals (Fig 2B). A critical separation of the workforce during the time of a
pandemic generated crisis is classifying the essential and non-essential workers. Responses for
this survey question revealed that there were 1659 essential workers present in our study
cohort (61.8%) and 972 workers (36.2%) belonged to the non-essential workers category, with
a few participants (n = 52, 1.9%) who opted not to answer this question (Fig 2C). To under-
stand whether this study group experienced unique challenges such as risk of financial stability
during the COVID-19 crisis through loss of employment we asked the participants their cur-
rent occupational status. Most of the candidates (91%) who took the survey were not affected
by loss of employment except for a small subgroup (6.85%) who lost their jobs (Fig 2D). Thus,
data from this section of the study suggests that there was a mixed distribution of candidates
with regard to their occupational status and a major fraction of them did not lose
employment.
We then assessed whether the study participants were tested for COVID-19 and found that
a little more than one-fourth of the total participants, i.e., n = 777 or 29% took the COVID-19
detection test and the majority 1890 or 70.4% of total participants did not test for an infection
until the time of filling the survey (Fig 3A). In order to estimate whether it was mandatory for
this subset of COVID-19 test takers to be tested, we analyzed if they were essential or non-
essential workers. The results showed that a large number of the tested individuals were essen-
tial workers (511 out of 777 i.e., 65.7%) and a few of them (244 out of 777 i.e., 31.4%) belonged
to the non-essential workers category while 1.5% preferred not to answer (Fig 3B). This result
suggests that along with the essential workers for whom COVID-19 testing was expected to be
mandatory as a safety precaution, there was an alarming health concern among the general
public /non-essential workers to obtain the COVID-19 test and thereby assure that they have
not been exposed to an infection. Furthermore, a comparative analysis also informed what
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fraction of the total essential and non-essential workers in our study group took the COVID-
19 test. A little more than half of the total essential workers, 511/972 i.e., 52.5% took the test
while working as frontline taskforce which accounts for 511/2683 or 19% of the total survey
participants. As expected, this fraction was lower in the non-essential workers group where
only 252/1659 i.e., 15.1% were tested (S1 Fig). We then assessed whether the sub-population
who opted for taking the COVID-19 detection test belonged to a few of the specific occupa-
tions or were evenly distributed among all categories. Upon analyzing which occupational cat-
egories these COVID-19 test takers belonged to, we found that the majority of them (67.3%)
were healthcare workers followed by employees from the research and education sector (9.5%)
(Fig 3C). To measure how people from different employment backgrounds were impacted by
the unexpected and abrupt restrictions such as lower density of occupants in the office and
business spaces we asked whether their jobs could be performed remotely. A vast majority of
the tested individuals did not have the flexibility of working from home since most of our
study cohort were employed by healthcare or research/education organizations. About 40.1%
of the participants had to be onsite at their workplaces and 28% people reported that their
work could only be partially done from home. Only 24.2% of the total participants could work
entirely remotely with having any adverse effect on their work (Fig 3D). Overall, these studies
show that regular monitoring through periodic testing for workers in healthcare and related
sectors could help circumvent the spread of COVID-19 disease allowing smooth functioning
of the healthcare delivery systems when working remotely is not an option.
Previous studies have shown that even under normal circumstances our overall well-being
is influenced by the people we surround ourselves with [24]. During the COVID-19 pandemic
lockdown when everyone experienced either shorter or longer periods of home isolation, the
people we live with is an important determinant of our social and mental wellbeing. Therefore,
we designed our survey questionnaire to assess the immediate household cohabitants of the
study participants and to explore how it impacted their daily routines. Our results show that
the majority, ~65% (1730/2683) of the survey participants lived with their spouses while others
had roommates, siblings or relatives as companions, and a few lived by themselves. Single indi-
viduals formed the second highest category (14.7%). There was almost an equal distribution of
individuals living either with their sibling(s), other relatives or roommates (~6%) while 1% of
the entries preferred not to answer this question (Fig 4A). Based on further analysis of partici-
pants who lived with their spouse, we found that 45% among them (781/1730) had children in
their household (Fig 4B). A comparison of the overlapping categories revealed that most of
our study participants lived with one or more companions during this challenging time and
only a small percentage lived by themselves (14%). In terms of how people felt about spending
more time indoors with other household members during the pandemic, there were mixed
reactions ranging from fluctuation in their opinion to feeling great or neutral (Fig 4C). The
COVID-19 pandemic altered social interactions among people around the world. In particu-
lar, more than 2/3
rd
of the participants experienced a significant change in the extent of social
interaction with people not living in their common household (Fig 4D). There was a pro-
nounced increase (87.1%) in the level of social interaction during the isolation phase and only
a few individuals (10.8%) responded to have no change in their interactions with other people.
The unprecedented COVID-19 disease outbreak, which led to serious health concerns,
uncertainty and havoc in the global community, could be overwhelming and cause strong
Fig 2. Professional background of the participants. A. Classification of employment categories. B. Employment status of the participants during the
study period. C. Distribution of individuals on the basis of essential or non-essential workers. D. Participants’ employment retention status during the
study period.
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emotions in people of all ages [25–27]. Although preventive measures adopted through public
health actions such as social distancing are necessary to reduce the spread of the disease, these
are associated with fear, loneliness and anxiety in the people. We wondered how people were
adjusting to the changing environment with the sudden reduction in out-of-home activity and
how it affected their mental health. Therefore, in our global survey, we chose to ask about peo-
ple’s outlook towards the coronavirus crisis by creating different categories to gauge the extent
of mental health changes ranging from none to moderately or extremely affected. There were
mixed responses and opinions for how the participants felt under these changing circum-
stances. While around 30% of the participants stated that they were moderately affected, 13.5%
people faced extreme and overwhelming mental health challenges (Fig 5A(i)). Moreover, sev-
eral recent studies suggest that the current pandemic has impacted the physical and mental
health of men and women differently [28]. This is consistent with our analysis of the psycho-
logical and behavioral reactions to the COVID-19 pandemic in the male and female sub-
groups, where females were found to be more affected than their male counterparts and a
larger proportion considered these effects to be mood dependent (Fig 5A (ii, iii)).
We also found that both the essential and non-essential workers groups had similar effects
of social isolation on their mental health. Our current findings and similar recent studies [29,
30] have shown that the unprecedented disease outbreak and the lockdown phase has induced
higher chronic stress and psychological distress in the human community at large. We there-
fore aimed to assess the stress management strategies adopted by our study participants and
how well they coped with their mental health burden. We focused on a few options that are
considered as the prime coping strategies used by individuals facing stressful situations [31].
These include pursuing hobbies, physical activity such as yoga, online therapies, religious prac-
tices and speaking to friends and family. As a way to cope with the accumulating stress and
anxiety, there was a marked increase in the frequency of interactions with friends and family
members (63.8%) as well as exercising or pursuing individual hobbies (58.5%). Moreover, we
observed a correlation that the individuals who pursued hobbies were also engaged in social
interactions more than others. There were a very few people, at least in this study cohort, who
used online therapies (8%) or religious practices (13.9%) (Fig 5B(i)). While being required to
isolate themselves at home and prohibit physical social gatherings, we found that individuals
actively discovered alternate socializing ways through virtual interactions. We then categorized
the male and female participants separately and found slight differences in the response strate-
gies between these subgroups. For instance, activities like practicing yoga and pursuing hob-
bies were more prevalent in the females as compared to the male participants (Fig 5B (ii, iii)).
Thus, data from this section of the study suggest that an individual’s level of virtual interaction
with family, friends and acquaintances increased while going through this phase of severe
infectious disease prevalence. Overall, the majority of the survey takers were employed and liv-
ing with one or more companions and yet chose social interaction, in part, as a coping mecha-
nism to relieve their stress and anxiety during the COVID-19 pandemic.
Since the COVID-19 pandemic presents a major threat to public health, it is necessary for
the human population to acquaint ourselves with some awareness of viral infections and the
diseases associated with it. Viral infections can cause a series of disorders affecting multiple
organs in the body including the lungs, liver, gut, brain, heart, pancreas and kidneys [32]. In
order to estimate, as well as raise general awareness about viral infections or other
Fig 3. COVID-19 testing status and professional background of the test takers. A. Distribution of participants based on COVID-19 testing. B.
Classification of COVID-19 test takers into essential and non-essential workers. C. Occupational categories of COVID-19 test takers. D. Classification
of tested individuals on the nature of work based on physical location.
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manifestations associated with it we asked our study participants from different demographic
and occupational backgrounds about their idea on the disorders that a viral infection might
cause. The majority of the survey takers were aware of the impact of viral infection of seasonal
flu. This information is particularly useful as we approach the annual flu season. Among our
survey takers, the awareness was least that viral infections can cause Type 1 Diabetes. About
40–60% survey takers were familiar that viral infections can cause skin warts, Liver Cirrhosis,
and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS; an unexplained,
chronic disease that affects millions worldwide [33,34]) (Fig 6A). Of note, there is an emerging
body of evidence indicating that a section of the COVID-19 patients, especially the long haul-
ers, will eventually develop ME/CFS [35,36]. To find whether the survey takers had other
underlying health conditions that might exacerbate the effects of COVID-19, we shortlisted a
few disorders that are believed to have that effect. About 6.6%, 9.54%, 17.35%, 19.53%, 16.42%,
14.47%, 9.39%, 2.45% and 4.19% of our respondents suffered from diabetes, cardiovascular
disorders, obesity, respiratory infections, other respiratory disorders, gastrointestinal disor-
ders, autoimmune diseases, Chronic kidney disorders, and ME/CFS, respectively. Overall, the
majority of our respondents did not have the stated underlying conditions that could exacer-
bate their COVID-19 risk (Fig 6B).
Limitations
Although our survey design encompasses various dimensions to estimate the impact of the
COVID-19 outbreak on the participants, we cannot provide an exhaustive analysis of all the
possible variables here, as that is beyond the scope of a single manuscript. To overcome these
shortcomings, we have made all the raw data available for the community to conduct further
analyses (https://igenomed.stanford.edu/dataset/survey-study-on-lifestyle-changes-during-
covid-19-pandemic). As an example of such analysis, we have provided a second-degree analy-
sis of some of the parameters for the survey-takers who experienced changes in their social
interaction (S3 Fig).
Conclusions
Our web-based study indicates that there was a moderate to severe effect on an individual’s
social, financial and mental health conditions during the COVID-19 disease outbreak. Our
data does not show that there is significant variance in peoples’ outlook and behaviors across
countries. Among the survey completers (n = 2683), 22.7% of the participants belonged to the
age group 56–65 years while 56.6% were 26–55 years old and 78.24% held a bachelor’s degree
or above. More than 50% of these survey takers belonged to full-time research and healthcare
segments. We identified that most of our study group members did not lose their jobs and one
reason that we do not observe significant loss of employment in our study could be the fact
that a greater fraction of the survey takers was from the healthcare sector and research area,
and a large percentage among them identified themselves as essential workers. The essential
workers comprised the most significant portion of the small population of COVID-19 test tak-
ers in our entire study. Since they were healthcare workers and essential, they were not remote
workers. Interestingly, despite retaining their jobs, the majority of our survey takers indicated
change in their social interaction. Participants were engaged in an increased frequency of tech-
nology-aided distant social interaction, focus on physical fitness and leisure activities were
Fig 4. Impact of home isolation strategies implemented during the study period. A. Cohabiting profile of the study participants. B. Overlap between
individuals who lived together with spouse and/or children. C. Effect of spending more time in the household as opposed to usual lifestyle on the
participants’ mindset. D. Changes in social interaction of the study participants during the study period.
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Fig 5. Effect on mental health of the study participants. A. Extent of mental health effect due to home isolation during the study period. (i: Total
number of participants; ii: Male participants; iii: Female participants). B. Stress management strategies adopted by individuals. (i: Total number of
participants; ii: Male participants; iii: Female participants).
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adopted to serve as a coping mechanism during this period of home isolation. Moreover, a
large portion of the study participants had a general awareness about viral infections or other
manifestations associated with it. Collectively, these metrics provide a succinct and informa-
tive summary of the socio-economic and health impact of the COVID-19 pandemic on the
individuals. In conclusion, our findings provide data support for understanding people’s state
of mind during an unexpected period of social isolation associated with such a pandemic.
Findings from our study reflects the fact that continuous surveillance of the psychological con-
sequences for outbreaks should become routine as part of preparedness efforts worldwide.
Supporting information
S1 Fig. Group wise distribution showing the fraction of total essential and non-essential
workers who took the COVID-19 test.
(TIF)
S2 Fig. Comparative analyses of essential vs non-essential workers. A. Comparison with
regard to their employment status during the study period. B. Change in social interaction lev-
els. As anticipated and shown in S2 Fig. A, we found that the non-essential group lost more
jobs as opposed to the essential workers. Moreover. there was a bigger effect on social interac-
tion among the non-essential working group as compared to the essential workers (S2B Fig).
(TIF)
S3 Fig. Comparative analyses between the two groups of participants who experienced
changes in their social interaction and those who reported no changes in social interaction
during the study period. The comparisons were based on their: A. Employment status, house-
hold companion and COVID-19 test status. B. Mental health status of participants. C. Strate-
gies to cope with mental health issues. For all of the above metrics, there was similar
distribution in the two groups as depicted by the bar graphs (S3A Fig). We then evaluated
what effect these two groups of survey takers had on their mental health as a result of COVID-
19 and social isolation. In particular, we asked about the extent of impact on their mental
health by providing different levels or categories to choose from, such as, extremely, moder-
ately to overwhelming or no effect at all. Our analysis shows that a large portion of the social
interaction affected individuals had moderate effects on their mental health whereas the
majority of the participants who did not have an effect on their social interaction neither had
any kind of mental health impact (S3B Fig). Moreover, a substantial proportion of the partici-
pants who had changes in their social interaction felt that the overall quality of their mental
health could have been better whereas the other group had a neutral opinion. We also mea-
sured the differences with regard to stress coping mechanisms in these two groups of individu-
als. Our data reflects that both these groups had a similar trend of involvement in alternate
activities as a way to cope with stress and anxiety. For instance, in both the groups, the largest
fraction of people opted to communicate with their friends and family the most followed by
pursuing their hobbies (S3C Fig).
(TIF)
S1 File. Survey questionnaire used for this study. Also available online at https://is.gd/
COVIDSocialSurvey.
(DOCX)
Fig 6. Public health aspects of the study. A. Awareness of viral infection associated diseases among the study participants. B. Number of survey takers
who had underlying conditions before the COVID-19 outbreak.
https://doi.org/10.1371/journal.pone.0255399.g006
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COVID-19 lifestyle survey
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Acknowledgments
The authors thank Dr. Ronald W. Davis (Stanford University) for his guidance. The authors
thank Dr. Iti Kapoor and Dr. Esha Kaushal (Stanford University) for their inputs. The authors
thank the study participants who took the survey. The authors thank Open Medicine Founda-
tion (OMF) for providing space in the OMF ME/CFS Data Center server for data storage. The
authors thank Dr. Wenzhong Xiao (Harvard Medical School/Massachusetts General Hospital)
for his help in setting up the open source data protocol.
Author Contributions
Conceptualization: Amit Kumar Saha.
Data curation: Abhinav Kaushik, Deepti Rao, Nilanjan Mukherjee.
Formal analysis: Poonam Agarwal, Abhinav Kaushik, Amit Kumar Saha.
Investigation: Poonam Agarwal, Abhinav Kaushik, Sutapa Sarkar, Deepti Rao, Nilanjan
Mukherjee, Vinita Bharat, Amit Kumar Saha.
Methodology: Poonam Agarwal, Abhinav Kaushik, Sutapa Sarkar, Deepti Rao, Nilanjan
Mukherjee, Vinita Bharat, Subhamoy Das, Amit Kumar Saha.
Project administration: Amit Kumar Saha.
Software: Abhinav Kaushik, Deepti Rao, Nilanjan Mukherjee.
Supervision: Amit Kumar Saha.
Visualization: Poonam Agarwal, Abhinav Kaushik, Sutapa Sarkar, Vinita Bharat.
Writing – original draft: Poonam Agarwal, Sutapa Sarkar, Amit Kumar Saha.
Writing – review & editing: Poonam Agarwal, Sutapa Sarkar, Nilanjan Mukherjee, Vinita
Bharat, Subhamoy Das, Amit Kumar Saha.
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