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Research article
COVID-19 pandemic, socioeconomic crisis and human stress in
resource-limited settings: A case from Bangladesh
Mashura Shammi
a
, Md. Bodrud-Doza
b
, Abu Reza Md. Towfiqul Islam
c
,
Md. Mostafizur Rahman
a
,
*
a
Department of Environmental Sciences, Jahangirnagar University, Dhaka-1342, Bangladesh
b
Climate Change Programme, BRAC, Bangladesh
c
Department of Disaster Management, Begum Rokeya University, Rangpur-5400, Bangladesh
ARTICLE INFO
Keywords:
Psychology
COVID-19
Perception-based questionnaire
Principal component analysis (PCA)
Linear regression model
Social panic
Social conflict
ABSTRACT
Considering the population density, healthcare capacity, limited resources and existing poverty, environmental
factors, social structure, cultural norms, and already more than 18,863 people infected, the community trans-
mission of COVID-19 is happening fast. These exacerbated a complex fear among the public. The aim of this
article is, therefore, to understand the public perception of socioeconomic crisis and human stress in resource-
limited settings of Bangladesh during the COVID-19 outbreak.
The sample comprised of 1066 Bangladeshi participants. Principal component analysis (PCA) was considered to
design a standardized scale to measure the mental stress and socioeconomic crisis, one-way ANOVA and t-test
were conducted to perceive different demographic risk groups; multiple linear regression was applied to estimate
the statistically significant association between each component, and classical test theory (CTT) analysis was
applied to examine the reliability of each item according to the components to develop a composite score.
Without safeguarding the fundamental needs for the vulnerable ultra-poor group can undeniably cause the
socioeconomic crisis and mental stress due to the COVID-19 lockdown. It has further created unemployment,
deprivation, hunger, and social conflicts. The weak governance in the fragile healthcare system exacerbates the
general public's anxiety as the COVID-19 testing facilities are centered around in the urban areas, a long serial to
be tested, minimum or no treatment facilities in the dedicated hospital units for COVID-19 patients are the chief
observations hampered along with the disruption of other critical healthcare services. One-way ANOVA and t-test
confirmed food and nutritional deficiency among the vulnerable poorest section due to loss of livelihood. Also,
different emergency service provider professions such as doctors, healthcare staff, police forces, volunteer or-
ganizations at the frontline, and bankers are at higher risk of infection and subsequently mentally stressed. Proper
risk assessment of the pandemic and dependable risk communications to risk groups, multi-sectoral management
taskforce development, transparency, and good governance with inter-ministerial coordination is required along
with strengthening healthcare capacity was suggested to reduce mental and social stress causing a socioeconomic
crisis of COVID-19 outbreak. Moreover, relief for the low-income population, proper biomedical waste man-
agement through incineration, and preparation for the possible natural disasters such as flood, cyclones, and
another infectious disease such as dengue was suggested. Finally, this assessment process could help the gov-
ernment and policymakers to judge the public perceptions to deal with COVID-19 pandemic in densely populated
lower-middle-income and limited-resource countries like Bangladesh.
1. Introduction
The World Health Organization (WHO) announced COVID-19 as a
global pandemic on March 11, 2020. The disease has advanced into a
pandemic, started with small chains of spreading, further culminating
into larger chains of spread in many countries resulting in the widespread
transmission consequently across the globe affecting all the continents
(Anderson et al., 2020). The fatality case of COVID-19 risk is around 1%
and that it can kill healthy adults, as well as the elderly people with,
existing health problems (Gates, 2020). According to Worldometers
* Corresponding author.
E-mail address: rahmanmm@juniv.edu (Md.M. Rahman).
Contents lists available at ScienceDirect
Heliyon
journal homepage: www.cell.com/heliyon
https://doi.org/10.1016/j.heliyon.2020.e04063
Received 6 April 2020; Received in revised form 15 May 2020; Accepted 20 May 2020
2405-8440/©2020 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-
nc-nd/4.0/).
Heliyon 6 (2020) e04063
(2020), 14 May 2020, with the total coronavirus cases rising to 4,490,
958, and total deaths 301,616, USA is the worst affected country from the
COVID-19 pandemic with 86,098 deaths. It took 67 days from the first
reported of COVID-19 to reach 100,000 cases, 11 days for the second
100,000, and just four days for the third 100,000 (WHO, 2020a,b). The
accelerating spread of the COVID-19 and its outcomes around the world
has led people to fear, panic, concern, and anxiety (Ahorsu et al., 2020),
panic buying of surgical masks (Wang et al., 2020), stigma, depression,
racism, and xenophobia. Besides, as there is no medication and vacci-
nation yet, wrong use of disinfectant liquids, methyl alcohols, garlic,
lemon tea is amongst the many misinformation to cure COVID-19.
Moreover, the fear of infection, quarantine, social isolation, a lack of
self-care even leads individuals to suicide. Predictably, any contagious
epidemic outbreak has deleterious effects on individuals and society
(Duan and Zhu, 2020).
Institute of Epidemiology, Disease Control and Research (IEDCR) is
the research institute under the Ministry of Health responsible for
COVID-19 surveillance in Bangladesh, first confirmed the COVID-19 case
on 7 March 2020, followed by a nationwide lockdown of all educational
institutes, government and private offices, and industries from 26 March.
The government of Bangladesh (GoB) deployed armed forces from 24
March to facilitate the social-distancing and prevention of the disease.
Emergency healthcare services and law enforcement services were
exempted from this announcement. Nevertheless, just after the
announcement of lockdown, more than 11 million people left Dhaka to
be in their home districts and commenced the risk of COVID-19 infection
to the entire 64 districts in Bangladesh. On 15 May 2020, with 20,065
confirmed cases, 298 deaths (Figure 1) Bangladesh is within the top 30
affected country. With only 41 labs located in the urban areas, it is not
easy to be tested for COVID-19 and often the tests are done after the
Figure 1. Map of the study area showing number of COVID-19 confirmed patient (Data source: IEDCR).
M. Shammi et al. Heliyon 6 (2020) e04063
2
patients had expired. Moreover, at present Bangladesh has 1,169 ICU
beds, totalling to 0.72 beds/100,000 citizens. Of these 432 beds are in
government hospitals and 737 in private hospitals. Likewise, there are
only 550 ventilators in the country (IEDCR, 2020).
Amidst the lockdown of the COVID-19 pandemic, Bangladesh also has
been facing other epidemics of panic buying, social stigma, fear, and
hatred. The primary healthcare treatments in the hospitals and private
clinics were disrupted in the lockdown. Moreover, many emergency
service providers such as frontline doctors, healthcare staffs, caregivers,
police and armed forces, bankers and government authority were infec-
ted, isolated and even died. Private practitioners, clinics, and hospitals in
suburban and rural areas were shut down due to the fear of infection.
Moreover, the healthcare workers who have treated the patients and
infected have been socially hatred and stigmatized. Besides, the deceased
was even denied burial in the local graveyards which are basic human
rights and, in most cases, handled by the government authority (TBS,
2020a). The price hike of the daily necessities was observed due to low
supply and shopkeepers and suppliers stopped working fearing infection.
Middle-income, lower-income and daily-wedge earners fell into a severe
financial shortfall due to loss of jobs, incomes. With their last savings
spent, they are plunged to be ultra-poor.
Considering the population density, environmental factors, social
structure, cultural norms, healthcare capacity, and poverty in
Bangladesh, it is certainly hard to lockdown millions of people. Besides,
Bangladesh hosts the largest refugee camps in Cox's Bazar which is also
about to embrace the COVID-19 pandemic, where, it will have cata-
strophic outcomes (Hopman et al., 2020). Despite the precautions taken
by the government and other international aid bodies, on 14 May 2020,
the Coronavirus cases were detected in Cox's Bazar Rohingya camps
(TBS, 2020b). Moreover, miscommunication among the government
ministries, policymakers, advisers and the country's apex trade organi-
zations such as Federation of Bangladesh Chambers of Commerce and
Industries (FBCCI) and the trade organization of the ready-made garment
(RMG) manufacturers Bangladesh Garment Manufacturers and Exporters
Association (BGMEA) led industry workers to return to the industrial
districts due to the message of reopening at least two times first on 4
th
April and later on 11
th
April. To save their jobs, thousands of RMG
workers travelled back to Dhaka and its surrounding districts on foot, in a
truck, or covered vans without social distancing while ensuring further
transmission. The district of Dhaka and its Upazilas Savar and Ashulia,
Gazipur, Narayanganj, and Chittagong remained the highest infected
clusters of COVID-19 infection (IEDCR, 2020). The latest extension
period declared by the GoB is until 30 May 2020. Yet the RMG factories
and other industrial operations resumed from 26 April 2020. Moreover,
as the biggest Muslim festival Eid-Ul-Fitr approaches, mass people are
gathering in the shopping centres despite the risk of spreading human
transmission. It is utterly depicting the scenario of overlooking risks of
the pandemic by unaware citizens while social anxiety and fear of the
pandemic in concerned citizens. Both should be immediately dealt with
by the Government along with the alliance groups with proper risk
communication.
Moreover, the possibility of natural disasters such as tropical cy-
clones, flooding, and landslide preparedness, the rising of dengue fevers,
and other infections are potentially overlooked. Furthermore, the con-
sequences of disposal of used personal protective equipment (PPE)
without proper treatment in the landfill will just arise more disease
transmission and environmental disasters leaving the country at stake. In
these circumstances, this study was therefore designed to analyze so-
cioeconomic crisis and mental stress in resource-limited settings of
Bangladesh due to the COVID-19 outbreak. This assessment might be
useful for the government and policymakers of countries with a similar
socioeconomic and cultural structure like Bangladesh.
2. Methodology
2.1. Study procedure
Considering the impact of COVID-19 outbreak in Bangladesh, this
study identifies several relevant and possible items based on the country's
situation analysis based on the print and electronic media, and literature
review. We drafted the questionnaire considering demographic charac-
teristics, individual mental health condition (MH), the health system in
Bangladesh (HSB), governance and political issues (GPI), government
decisions and impacts (GDI), socioeconomic issues (SEI), immediate
emerging issues (IEI) and enduring emerging issues (EEI). A total of 49
items was considered in the drafted questionnaires to get people's
perception of the COVID-19 outbreak in Bangladesh. Furthermore, expert
consultation was considered to set and validate these 49 items.
Bangladesh has witnessed a boom in internet usage due to the fast-
growing mobile internet and the government's push for digitalization.
There are 99.428 million internet users in February 2020 according to
the Bangladesh Telecommunication Regulatory Commission (BTRC,
2020). Google Form based online questionnaire was prepared to conduct
the survey. An online database of target participants was prepared by
reviewing the relevant websites and online social platforms of different
groups in Bangladesh, considering their Bangladeshi citizenship, age
above 18 years, current activities, occupation, social responsibilities, and
engagement related to COVID19 response, socioeconomic sector,
country-level planning, and policymaking. The prepared questionnaire
with an introductory paragraph outlining the purpose of the study was
shared through Email, Facebook, LinkedIn, and WhatsApp with selective
and relevant people considering the purposive sampling method. The
questionnaire survey was conducted from 28 March to 30 March 2020.
The inclusion of the respondents was different social groups like
university faculty and scholars, Government officials, development
worker or practitioner, doctors, engineers and technologists, youth
leaders and students, businessmen and industry officials, banking and
finance corporates, researchers, and others. The answers to the survey
questionnaires are the voluntary basis. Data from 1082 respondents were
collected via a nationwide online survey method, but following the
removal of incomplete 16 questionnaires, 1066 were retained for this
study. A five-point (1–5) Likert scale was employed to test whether each
understands the statement descriptions that ranged from strongly
disagree to strongly agree with the statements (Table S1).
2.2. Data analysis
Employing the Statistical Package for the Social Science (SPSS) v.
25.0, datasets were analyzed for Principal component analysis (PCA),
one-way ANOVA and t-Test, multiple linear regression, and classical test
theory (CTT). PCA is considered in this study to design a standardized
scale to measure the socioeconomic crisis and mental stress in
Bangladesh due to the COVID-19 outbreak. PCA is one of the population
data reduction techniques that indicate each potentiality of variables and
their significance level in a huge sample size. Before conducting the PCA,
Kaiser-Maier -Olkin (KMO) and Bartlett's sphericity tests were applied to
confirm the necessity of this analysis. The results of the KMO >0.5 (the
KMO value was 0.903 in this research) and the significance of Bartlett's
sphericity test at p <0.01 verified our datasets to be fitted for the PCA
(Islam et al., 2020). The number of factors chosen was based on the
Kaiser's normalization principle, where the only factors with
eigenvalues>1.0 were regarded. PCA results were used to find how many
components are to be retained as well as how many items in each of those
components are to be retained.
M. Shammi et al. Heliyon 6 (2020) e04063
3
Furthermore, the test of association between each principal compo-
nent and the demographic characteristic of the respondents were per-
formed to see how people of different demographic status to perceive
socioeconomic crisis and mental stress using the one-way ANOVA and t-
test. Moreover, multiple linear regression was applied to estimate the
statistically significant association between each component.
Classical Test Theory (CTT) analysis was applied to examine the
reliability of each item according to the components to develop a com-
posite score. Cronbach's alpha was employed to test the consistency and
reliability of the factor loadings in this study (DeVellis, 1991). Descrip-
tive statistics (e.g., Mean, Standard Deviation, Variance, Skewness, and
Kurtosis) of respondents perceived socioeconomic crisis and mental
stress was considered based on the developed composite score for the
entire scale. The hierarchical cluster analysis (HCA) and Pearson's cor-
relation coefficient was applied for identifying the relationships among
all-composite items.
2.3. Ethics statement
The consent of participants was taken, and they remained anony-
mous. We have applied for the ethical clearance to the ethical clearance
authority of Jahangirnagar University, Bangladesh. The studies involving
participants of this questionnaire was reviewed by the Department of
Public Health and Informatics and permit to conduct this study.
3. Results
3.1. Demographic information
According to the survey results, the ratio of male to female partici-
pants was 3:2, whereas the composition of age groups were 75.2%
(18–30 years old), 16.7% (31–40 years old), 6.7% (41–50 years old),
1.1% (51–60 years old) and 0.3% (>60 years old), respectively. The
young people responded more maybe because of their frequent access to
the internet depending on the socioeconomic structure of Bangladesh.
However, the average age of the participants (n ¼1066) was 27.80 years
(SD 10.05), and the participants had, on average, 12.5 years of formal
education (SD 8.1). More than half of the participants were males (n ¼
661; 61.5%) and remaining (n ¼405; 38.5%) females. Nearby, 60% of
the youth group was mostly students as Bangladesh is a youth dividend
country and they are the most dynamic groups of the society as well as
dynamic on online platforms. The rest of the 40% were from various
professions of doctors and health workers, civil service officials, non-
government officials, teachers and scholars, policymakers, researchers,
and businessmen (Table S1).
3.2. Relationships among demographic characteristics, socioeconomic
components, and mental stress
The scree plot (Figure 2) shows that a total of eight components can
be retained (determined by components with eigenvalues greater than
1). Items with factor loadings (items loading on a component) less than
0.5 were omitted from the analysis and analysis repeated on the
remaining items until a perfect scale was developed (Hair et al., 2014).
We inspected the loadings of the items on each component and omitted a
total of 12 items (have not met the 0.5-factor loading requirement) from
the questionnaire. The scores of the items that loaded well on each
component are represented in Table 1.
The loading scores were demarcated into three groups of weak
(0.50–0.30), moderate (0.75–0.51), and strong (>0.75) respectively (Liu
et al., 2003;Bodrud-Doza et al., 2016;Islam et al., 2017). The PC1 (First)
elucidated 8.85% of the variance as it encompassed a confidence level of
moderate positive loading, depicts the weakness of healthcare system in
Bangladesh including lack of trained doctors and health professionals to
deal with the COVID-19 (HSB1: 0.651); lack of health facilities to combat
the COVID-19 outbreak in Bangladesh (HSB2: 0.74); lack of health
infrastructure to deal with COVID-19 (HSB3:0.745); severe lack of
biomedical waste management facilities in Bangladesh (HSB4: 0.683);
lack of COVID-19 testing facility in Bangladesh (HSB5:0.69); and lack of
budget or financial support to respond to this outbreak (HSB6:0.536). All
the elements of the statement (HSB) showed moderate loading score
revealing the fragility of the healthcare system of Bangladesh in dealing
Figure 2. Scree plots of the eigenvalues of PCA.
M. Shammi et al. Heliyon 6 (2020) e04063
4
Table 1. Retained items after principle component analysis.
Sector Items PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8
Demographic
characteristics
Age 0.047 -0.033 -0.045 0.009 -0.056 0.042 -0.007 0.893
Occupation 0.019 -0.027 -0.001 0.057 0.031 0.027 -0.017 0.883
Individual Mental
health condition (MH)
I am most afraid
of coronavirus recent
outbreak in
Bangladesh (MH1)
0.112 -0.005 0.029 0.24 0.758 0.074 -0.057 0.034
I am afraid of getting
coronavirus (MH2)
0.033 0.04 0.062 0.148 0.838 0.032 -0.049 0.055
I am afraid of losing my
life or my relatives' life
due to this outbreak (MH3)
0.055 0.063 0.076 0.13 0.788 0.074 -0.091 -0.06
All the news and numbers
of COVID-19 in different
media increasing my
tension (MH4)
0.117 0.114 0.097 0.049 0.624 0.086 0.039 -0.046
Health system in
Bangladesh (HSB)
There is a lack of trained
doctors and health professional
to deal with the COVID-19 (HSB1)
0.651 0.03 0.099 0.011 0.034 -0.014 -0.022 -0.042
There is a lack of health
facilities to combat the COVID-19
outbreak in Bangladesh (HSB2)
0.74 0.079 0.103 0.214 0.092 0.215 -0.079 0.05
There is a lack of health
infrastructure to deal with
COVID-19 (HSB3)
0.745 0.068 0.144 0.202 0.099 0.111 -0.056 0.026
There is a severe lack of
bio-medical waste management
facilities in Bangladesh (HSB4)
0.683 0.11 0.138 0.21 0.055 0.229 -0.077 0.022
There is a lack of COVID-19
testing facility in Bangladesh (HSB5)
0.69 0.133 0.032 0.216 0.041 0.274 -0.038 -0.015
There is a lack of budget or
financial support to response
to this outbreak (HSB6)
0.536 0.255 0.137 -0.033 0.124 -0.217 0.004 0.104
Governance and
Political issues (GPI)
Bangladesh government can
deal with this outbreak (GPI1)
-0.164 0.003 -0.128 0.008 -0.028 0.114 0.563 -0.102
Government is taking this
outbreak seriously to deal with (GPI2)
-0.007 -0.036 -0.018 -0.13 -0.063 0.112 0.819 0.032
Government is taking proper
decisions in the right time (GPI3)
-0.07 -0.051 0.012 -0.138 -0.046 -0.04 0.811 0.055
Government is involving other
sector actors to combat the
COVID-19 outbreak (GPI4)
0.03 -0.024 0.009 -0.028 -0.006 0.025 0.748 -0.005
Government decisions
and impacts (GDI)
Government need support from the
people to reduce the impact
of COVID-19 (GDI1)
0.203 -0.006 0.092 0.254 0.033 0.627 0.216 -0.06
Government need to formulate
a policy and action plan and
implement it immediately (GDI2)
0.235 0.131 0.036 0.338 0.043 0.592 0.02 -0.064
Shut down or lockdown of
regular activities is a good
decision to reduce the chance of
infection of COVID-19 (GDI3)
0.064 0.042 0.051 0.079 0.191 0.585 0.067 0.08
Shut down or lockdown or social
distancing will have an economic
and social impact in future (GDI4)
0.051 0.362 0.333 0.005 0.04 0.513 0.082 0.094
The formal and informal business
will be hampered (GDI5)
0.075 0.376 0.387 0.003 0.023 0.543 -0.032 0.14
Socio-economic
issues (SEI)
Most of the poor people living
in urban areas have to leave
due to not having any options
for income (SEI1)
0.081 0.586 0.155 0.051 0.034 0.203 0.045 -0.01
Many people will lose their
livelihood/jobs at a time (SEI2)
0.016 0.681 0.192 0.171 0.056 0.163 -0.053 0.101
There will be less supply of basic
goods/products for daily use (SEI3)
0.096 0.734 0.154 0.084 0.044 -0.085 0 -0.134
Price of most of the basic products
will be higher than usual (SEI4)
0.11 0.665 0.116 0.073 0.006 0.11 -0.114 -0.048
Poor people will suffer food and
nutritional deficiency (SEI5)
0.128 0.576 0.211 0.127 0.002 0.365 -0.075 -0.088
There is a chance of social conflict
due to this outbreak (SEI6)
0.119 0.62 0.128 0.12 0.126 -0.103 0.016 0.051
(continued on next page)
M. Shammi et al. Heliyon 6 (2020) e04063
5
with COVID-19 pandemic, for instance very low ratio of intensive care
unit (ICU) beds to population, limited or centralized COVID-19 testing
facilities along with bias in selecting the test candidates, low test rate,
lack or a substandard quality of personal protective equipment (PPE) for
the caregivers, lack of institutional isolation units, and very poor coor-
dination in health management systems, etc.
Afterwards, the PC2 (Second) elucidated 8.82% of the total variance,
and it was moderately positive loaded with the socioeconomic issues
(SEI), including the risk of poor people from urban areas forced to tem-
porary migration while having no options for income along with the
chance of inducing social conflicts due to this outbreak; restriction of
basic supplies including foods; price hikes of commodities, losing jobs
(SEI1-6: 0.576–0.734). However, weak but positively loaded socioeco-
nomic issues such as shut down or lockdown or social distancing might
have an economic and social impact in the future (GDI4; 0.362) along
with the small formal and informal business will also be hampered. For
example, small business will lose their regular customers due to shutting
down their business (GDI5:0.376).
The PC3 (Third) explained 8.45% of the variance which was strong
positive loaded with enduring emerging issues (EEI: 0.548 to 0.805). The
major EEIs were stated here as occurring any further natural disasters
such as flood and tropical cyclone (EEI1: 0.548) and their burden on food
security (EEI2: 0.648), mounted economic loss (EEI3: 0.805) due to
damages of business and industrial chains both locally and globally, these
may put further stress as elevating poverty level (EEI4: 0.732) followed
by a chance of inducing severe socioeconomic and health crisis (EEI5:
0.699).
Furthermore, PC4 (Fourth) elucidated 8.14% of the variance and was
moderate positive loaded of immediate emerging issues (IEI: 0.581 to
0.701). This sector covered very important elements of COVID-19
pandemic in Bangladesh including the chance of community trans-
mission (IEI1: 0.688), huge infection potentials (IEI2: 0.701), but this
Table 2. Test of association between each component and the demographic characteristic using T-test.
t df Sig. (2-tailed) Mean Difference 95% Confidence Interval of the Difference
Lower Upper
PC1 4.926 36 0 0.18881 0.1111 0.2665
PC2 5.215 36 0 0.19492 0.1191 0.2707
PC3 5.066 36 0 0.18757 0.1125 0.2627
PC4 5.006 36 0 0.18278 0.1087 0.2568
PC5 3.622 36 0.001 0.13649 0.0601 0.2129
PC6 4.763 36 0 0.15951 0.0916 0.2274
PC7 1.326 36 0.193 0.05481 -0.029 0.1387
PC8 1.472 36 0.15 0.05159 -0.0195 0.1227
Table 1 (continued )
Sector Items PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8
Immediate emerging
issues (IEI)
There is a chance of community
transmission of COVID-19
in Bangladesh (IEI1)
0.099 0.141 0.12 0.688 0.15 0.054 -0.034 0.093
A huge number of people
will be infected (IEI2)
0.072 0.141 0.13 0.701 0.279 -0.014 -0.084 0.03
There is a chance of not
detecting most of the infected
patients due to lack of health
facilities leads to undermining
the actual infected case (IEI3)
0.218 0.13 0.144 0.661 0.066 0.23 -0.185 0.017
There is a chance to increase
in the number of death for not
having proper health facilities (IEI4)
0.233 0.105 0.244 0.694 0.125 0.228 -0.092 -0.027
Lack of bio-medical waste
management facilities in Bangladesh
will create more problem (IEI5)
0.234 0.111 0.269 0.581 0.162 0.201 -0.037 -0.048
Enduring emerging
issues (EEI)
If any disaster (flood, cyclone etc.) occur
after the COVID-19 situation then it
will create a double burden to
the country (EEI1)
0.199 0.123 0.548 0.299 0.056 0.215 -0.073 -0.013
There is a chance of severe food scarcity
due to these events (COVID-19 þ
Disasters) in the country (EEI2)
0.165 0.227 0.648 0.147 0.103 -0.119 0.028 -0.14
High possibility of huge
economical loss (EEI3)
0.127 0.187 0.805 0.099 0.094 0.159 -0.048 0.03
High possibility of increasing the
poverty level (EEI4)
0.091 0.296 0.732 0.169 0.088 0.123 -0.039 0.003
High possibility of severe socio-
economic and health crisis (EEI5)
0.153 0.265 0.699 0.254 0.044 0.168 -0.071 0.018
Varimax Rotation
Sums of Squared
Loadings
Eigenvalues 3.275 3.265 3.126 3.012 2.58 2.436 2.389 1.736
% of Variance 8.852 8.824 8.45 8.14 6.974 6.584 6.456 4.692
Cumulative % 8.852 17.676 26.125 34.265 41.239 47.823 54.28 58.971
Bold denotes significance at >0.5.
M. Shammi et al. Heliyon 6 (2020) e04063
6
huge number of infection might not be reported due to lack of health
facilities which ultimately undermine the actual cases (IEI3: 0.661), the
lack of health facilities further trigger the chance of a high number of
deaths due to infection (IEI4: 0.694), and the poor facility of biomedical
waste management might be a risk factor for further virus transmission
(IEI5: 0.581) through an unconventional pathway in Bangladesh.
While, PC5 (Fifth) explained 6.97% of the total variances, and it
showed strong positive loadings with mental health issues (MH: 0.624 to
0.838) such as people are afraid of coronavirus recent outbreak in
Bangladesh (MH1), fear of getting coronavirus infection (MH2), and
afraid of losing life or relatives' life due to this outbreak (MH3) (MHI1-
3:0.758-0.838); and a moderate positive loading of all the news and
numbers of COVID-19 in different media increasing tension and anxiety
(MH4: 0.624). This result indicates the mental health burden in
Bangladesh due to COVID-19. Thus the question arises: What should be
the role of the GoB during the global pandemic to safeguard its citizens?
The following PC6 (Sixth) might produce some indication regarding
the question, which accounted for 6.58% of the variance. The PC6 was
Table 3. Estimated model of multiple regression.
Model-1: Dependent Variable: MH1 (R ¼0.991, R Square ¼0.975)
Unstandardized Coefficients Standardized Coefficients t Sig. 95.0% Confidence Interval for B
B Std. Error Beta Lower Bound Upper Bound
(Constant) -0.009 0.02 -0.453 0.669 -0.06 0.042
MH2 0.897 0.055 0.976 16.179 0 0.754 1.039
IEI3 0.17 0.065 0.157 2.597 0.048 0.002 0.338
Model-2: Dependent Variable: HSB6 (R¼1, R Square¼1)
(Constant) 0.085 0 3087.118 0 0.084 0.085
HSB1 0.86 0 0.893 2436.454 0 0.856 0.865
GDI1 -0.401 0 -0.392 -1583.19 0 -0.404 -0.397
SEI1 0.73 0.001 0.633 1256.524 0.001 0.723 0.738
SEI5 -0.497 0.001 -0.51 -863.253 0.001 -0.504 -0.489
GPI3 -0.06 0 -0.082 -324.713 0.002 -0.062 -0.057
HSB2 -0.037 0 -0.041 -96.705 0.007 -0.042 -0.032
Model-3: Dependent Variable: GDI1 (R¼1, R Square¼1)
(Constant) 0.087 0 364.433 0.002 0.084 0.09
GDI2 0.712 0 0.707 2025.783 0 0.707 0.716
GPI2 0.153 0 0.214 560.211 0.001 0.149 0.156
SEI6 -0.903 0.002 -0.883 -500.629 0.001 -0.926 -0.88
SEI3 0.503 0.001 0.625 376.743 0.002 0.486 0.52
GDI3 0.081 0 0.069 313.709 0.002 0.077 0.084
EEI5 0.023 0 0.025 74.962 0.008 0.019 0.026
Modle-4: Dependent Variable: SEI5 (R¼0.997, R Square¼0.993)
(Constant) -0.076 0.014 -5.529 0.005 -0.114 -0.038
SEI1 0.997 0.049 0.841 20.43 0 0.862 1.133
GDI2 0.304 0.045 0.287 6.731 0.003 0.178 0.429
EEI1 0.225 0.049 0.195 4.585 0.01 0.089 0.361
Model-5: Dependent Variable: IEI2 (R¼1, R Square¼1)
(Constant) -0.05 0 -1261.6 0.001 -0.05 -0.049
IEI1 1.07 0 0.956 10993.03 0 1.068 1.071
MH4 0.274 0 0.229 600.686 0.001 0.269 0.28
GDI3 -0.089 0 -0.066 -1241.36 0.001 -0.09 -0.088
EEI4 0.042 0 0.042 887.841 0.001 0.041 0.043
HSB1 -0.023 0 -0.021 -422.45 0.002 -0.024 -0.022
MH3 0.014 0 0.016 41.82 0.015 0.01 0.019
Model-6: Dependent Variable: EEI5 (R¼0.996, R Square¼0.993)
(Constant) -0.001 0.011 -0.045 0.966 -0.03 0.029
EEI4 0.623 0.076 0.645 8.23 0 0.428 0.818
EEI1 0.46 0.094 0.383 4.889 0.005 0.218 0.702
Table 4. Cronbach's alpha value for composite score development.
Cronbach's Alpha N of Items
Individual Mental health condition (MH) 0.79 4
Health system in Bangladesh (HSB) 0.783 6
Governance and Political issues (GPI) 0.742 4
Government decisions and impacts (GDI) 0.719 5
Socio-economic issues (SEI) 0.78 6
Immediate emerging issues (IEI) 0.821 5
Enduring emerging issues (EEI) 0.839 5
M. Shammi et al. Heliyon 6 (2020) e04063
7
moderate but positively loaded of the government decision and impacts
issues (GDI: 0.513 to 0.627), including the government need supports
from the people to reduce the impact of COVID-19 (GDI1: 0.627) and also
need to formulate a strong policy and action plan, and implement it
immediately (GDI2: 0.592); also moderate positively loaded of the gov-
ernment decision and impact issues (GDI3-5: 0.513–0.585). These de-
cisions were declared without a proper strategy of implementation and
exit plan that might lead to huge mismanagement during the partial
lockdown period in Bangladesh. This lack of coordination in policy
formulation further linked with the PC7 (Seventh), elucidated 6.46% of
the total variances and were strong positive loading of the government
and political issues (GPI: 0.563 to 0.819). The loading elements were as
follows: the capacity of dealing with the pandemic (GPI1: 0.563); seri-
ousness in dealing with it (GPI2: 0.819); timely decision taking (GPI3:
0.811); involvement of other stakeholders properly (GPI4: 0.748). These
are very crucial elements in terms of COVID-19 pandemic management,
therefore failing to address this issue might produce huge aftermath.
Finally, the PC8 (eighth) elucidated 4.692% of the total variances and
strongly loaded with demographic characteristics such as age (0.893) and
occupation (0.883).
3.3. Professional risk groups of socioeconomic crisis and mental stress
Results of t-Test and one-way ANOVA showed that all PCs exhibited a
strong association among them except for PC7 (Governance and Political
issues) and PC8 (demographic characteristics) (Table 2). However, a
One-way ANOVA test between 35 items and the age and occupation of
the participants were conducted which is presented in Table S2 and S3. A
strong association between age and MH3, MH4, and EEI2 were found
which represents that different age groups are afraid of getting corona-
virus and losing their lives due to this outbreak. Also, climate change
vulnerability and possible dengue outbreak in the country are creating
mental stress among different age groups. Furthermore, a strong associ-
ation between occupation and HSB1, SEI3, SEI5, and EEI2 represents that
there is lack of trained health professional in the country, a supply of
basic products will be reduced due to lockdown and fewer supplies, and
poor people will suffer food and nutritional deficiency due to loss of
livelihood. Also, different professions such as doctors, police, and banker
are at higher risk of infection.
3.4. Strategy, actions and individual role in public wellbeing and
socioeconomic crisis
The multiple linear regression model was applied to estimate the
individual mental health condition (MH) performance in model 1
(Table 3). The results indicate that the independent variable MH2 and
IEI3 was statistically significant and had a positive influence on MH1
(dependent Variable). From this model, it was found that coronavirus
outbreak, lack of testing capacity undermining the actual cases with a
lack of health facilities are inducing individual mental stress.
For model 2, the results indicate that HSB1 and SEI1 had a positive
impact whereas GDI1, SEI5, GPI3, HSB2 had a negative impact on HSB6.
From this model, it is found that lack of budget or financial support has
created constrained to COVID-19 response and created a scarcity of
trained health professionals, which enforced to shut down the regular
activities in the urban areas and poor people lose their income options.
Due to this, people are suffering food and nutritional deficiency and the
government is not getting proper support from the people to reduce the
impact of the COVID-19 outbreak. Not having a proper response plan
with the budget was not a good decision of the government, which
created a lack of health facilities to combat this outbreak in Bangladesh.
For model 3, GDI2, GPI2, SEI6, SEI3, GDI3, and EEI5 were statistically
significant and had a significant effect on GDI1. This model depicts the
role of general people to assist the implementation of government actions
against COVID-19 in Bangladesh such as the implementation of proper
lockdown and social distancing, relief supports to the poor people, pre-
venting potential socioeconomic burden, and ensuring the safeguard of
the country.
For model 4, GDI2 and EEI1 were statistically significant and had a
significant effect on SEI5. This means a strong coordinated strategy is
warranted to tackle such unprecedented events as Bangladesh is one of
the vulnerable countries in the world. Especially, the months from April
to September is especially important in terms of natural disaster
vulnerability in Bangladesh.
For model 5, IEI1, MH4, GDI3, EEI4, HSB1, MH3 were statistically
significant and had a substantial effect on IEI2. This model can be suit-
able to explain the most potential risk factors for the negative impacts of
COVID-19 pandemic in Bangladesh including mental health and poverty.
For model 6, EEI4 and EEI1 were statistically significant and had a
significant effect on EEI5. This unprecedented chain of events could be a
Table 5. Descriptive overview of respondents on psychosocial, and socio-economic crisis due to COVID-19 pandemic in Bangladesh.
Mean Std. Error of Mean Median Mode Std. Deviation Variance Skewness Kurtosis Minimum Maximum
Individual Mental health condition (MH) 4.04 0.03 4.25 5 0.83 0.69 -1.04 0.94 1 5
Health system in Bangladesh (HSB) 4.47 0.02 4.67 5 0.61 0.37 -2.28 7.93 1 5
Governance and Political issues (GPI) 2.63 0.03 2.50 2.25 0.91 0.83 0.29 -0.38 1 5
Government decisions and impacts (GDI) 4.56 0.02 4.60 5 0.51 0.26 -2.70 12.53 1 5
Socio-economic issues (SEI) 4.28 0.02 4.33 5 0.62 0.39 -1.30 2.93 1 5
Immediate emerging issues (IEI) 4.44 0.02 4.60 5 0.61 0.37 -1.75 5.11 1 5
Enduring emerging issues (EEI) 4.49 0.02 4.60 5 0.58 0.33 -1.49 3.28 1 5
Table 6. Correlation matrix of people's perception.
MH HSB GPI GDI SEI IEI EEI
MH 1
HSB .254** 1
GPI -.117** -.148** 1
GDI .235** .384** .083** 1
SEI .205** .349** -.100** .447** 1
IEI .426** .465** -.225** .475** .390** 1
EEI .267** .417** -.124** .482** .561** .527** 1
**
Correlation is significant at the 0.01 level (2-tailed).
M. Shammi et al. Heliyon 6 (2020) e04063
8
potential threat to the COVID-19 response and rehabilitation efforts by
the GoB. However, there was significant evidence (R
2
¼>0.97) that the
independent variables in the proposed models adequately described in
the influence of dependent variables (Table 3).
3.5. Descriptive overview of governance, perceived socioeconomic crisis
and mental stress
CTT analysis was applied to examine the reliability of each item ac-
cording to the components to develop a composite score. The Cronbach's
alpha values varied from 0.719 to 0.839 (>0.70), indicating that a
composite score for the entire scale can be generated to have a descrip-
tive overview of respondents' perceived mental stress, and socioeconomic
crisis (Table 4). On the scale of 1–5 (strongly disagree to strongly agree),
for an individual mental health condition (MH), it was found that the
composite mean is 4.04 0.03 which represents that the participants are
mentally stressed and afraid of COVID-19 outbreak in Bangladesh
(Table 5). The source of such stresses and fears might be linked to factors
such as fragile healthcare systems with poor management, low test rates,
weak medical infrastructures, weakness in planning, and implementation
of the COVID-19 response strategy by the GoB. The following further
sectors results indicate the correctness of the claims as to the case of the
health system in Bangladesh, with a mean of 4.47 0.02 represents that
the health systems in Bangladesh are very fragile to combat the COVID-
19 spread in Bangladesh. The weak coordination is consenting to gov-
ernment political issues (GPI), with a mean of 2.63 0.03 represents that
the government is not taking a proper decision at the right time to reduce
the effect of this pandemic. In summary, respondents had negative
viewpoints about the government is taking a proper decision in the
pandemic.
For government decisions and impacts (GDI), with a mean of 4.56
0.02 represent that the government's decision to lock down the activities
was right. Also, the lockdown of activities created economic impacts.
Despite the huge future economic burden, the GoB took the challenge to
implement partial lockdown in the country. However, this lockdown for a
long time might not be carried out rather it become loosen day by day
due to many socioeconomic factors and pressure from the industrial
sectors in Bangladesh. With a mean value of 4.28 0.02 for the socio-
economic issues (SEI) that represents the poor and marginalized people
will suffer a lot due to the COVID-19 outbreak in Bangladesh. Besides,
with a mean value of 4.44 0.02 for the immediate emerging issues
(IEI), it can be summarized as: the number of infections and death will
increase due to the fragile heal care system and improper biowaste
management. Some mismanagement in the industrial stakeholders and
lack of coordination among the responsible national COVID-19 response
committee already happened in Bangladesh. Furthermore, with a mean
value of 4.49 0.02 for enduring emerging issues (EEI), there is a change
of sever health and socioeconomic crisis if climate change-induced di-
sasters and dengue outbreak happen in the same year. For instance, the
early flash flood might bring sufferings for the poor people and farmers of
Bangladesh. Which in turn, puts excessive stress on the food security
issue of the country.
The individual mental health (MH) had a statistically positive sig-
nificant correlation with other issues (MH vs HSB, SEI, IEI, GDI, EEI) and
their correlation values ranged from 0.205 to 426 while MH had a sta-
tistically negative significant correlation with GPI (r ¼-0.117, p <0.01)
(Table 6). The GPI had a statistically negative relationship with other
issues (GPI vs SEI, IEI, EEI, MH) and their correlation values varied from
-0.10 to -0.225 whereas the GPI had a significant positive relationship
with GDI (r ¼0.083, p <0.01). The moderate significant correlation was
observed between pairs e.g., SEI vs EEI (r ¼0.561, p <0.01), and EEI vs
IEI (r ¼0.527, p <0.01). The weak positive significant correlation was
identified between pairs such as HSB vs GDI (r ¼0.384, p <0.01), EEI vs
GDI (r ¼0.482, p <0.01), and SEI vs HSB (r ¼0.349, p <0.01). These
results indicate a diversified nature of the peoples' perception regarding
the COVID-19 management and response in Bangladesh.
Further, the cluster analysis detected the total status of regional
variations, and how socioeconomic and environmental crises influence
Figure 3. Dendrogram showing the clustering of people's perceptions on COVID-19 outbreak in Bangladesh.
M. Shammi et al. Heliyon 6 (2020) e04063
9
further mental stress development (Figure 3). All the parameters were
classified into two major groups: cluster-1(C1), and cluster-2 (C2). C1
composed of socioeconomic issues (SEI), enduring emergency issues
(EEI), government decision and impact issue (GDI), immediate emer-
gency issue (IEI), the health system in Bangladesh (HSB) and individual
mental health (MH). C2 consisted of government political issues (GPI). It
can be concluded that all the issues depend on governance and political
aspects in Bangladesh.
4. Discussion
4.1. Strengthening healthcare system
The remarkable interferences and ventures in public health by the
governmental authority can control a pandemic where good governance
and good functional policy in the healthcare system exists. Tight lock-
down, mass people quarantine, increased testing facilities, government
stimulus packages, faster policy intervention and implementation have
prevented COVID-19 virus from spreading transmission between humans
in China, Hong Kong, South Korea, Vietnam, Taiwan, Singapore well to
date, despite initial cases (Anderson et al., 2020;Zhang et al., 2020). The
experiences gathered from across the globe, indicates that the
patient-management decisions, early diagnosis, and rapid testing and
detection are urgent in COVID-19 pandemic management (Binnicker,
2020). There is no doubt that the number of infections and death from
COVID-19 increases where a fragile and corrupt healthcare system exists.
So far, the fatality rate due to the COVID-19 is 1.52% in Bangladesh
(WHO, 2020a,b). However, the reported case numbers are given by the
Bangladesh Government certainly underestimates the actual number of
infected persons given the shortages or unavailability of test kits (Ebra-
him et al., 2020). The laboratory facilities for testing are only accessible
in the urban areas and 33 testing laboratories are still a few numbers in a
country of 165 million population. The fear of getting the virus-infected
along with the administrative procedure of testing and reluctance of
other private clinics and hospitals to admit patients is a sign of weak
governance in the healthcare of Bangladesh. In this scenario, other crit-
ical care patients are denied admittances, negligence, and often left to die
without treatments. After the detection of the first COVID-19 case in
Bangladesh, at least 929 þdeath cases having COVID-19 like symptoms
were reported in the different national daily newspapers until 10 May
2020, which is 3 times higher than the reported deaths by the GoB. This
indicates a serious level of community transmission is occurring in
Bangladesh.
Decentralization of testing and strengthening treatment facilities are
therefore required for the healthcare systems to combat the pandemic
and the treatment should reach in rural areas. The urban-rural disparity
in the facilities should be reduced as the rural practitioners and health-
care workers are equally at the risk of the pandemic. Moreover, the
administrative procedure of the deceased to burial put another confusion
and religious fear in the minds of the common people as the victims to
COVID-19 are buried without Muslim funeral procedures of baths and the
presence of family members and relatives. In this scenario, it is impera-
tive to deal with the peoples' fear and anxiety by the government. Proper
information should be circulated to get the people out of confusion.
Media partnerships should be created to prevent societal fear (Hopman
et al., 2020).
4.2. Taking intervention in mental stress and social conflict counselling
By quick administrative action and raising awareness in individuals
for social-distancing and stringent steps were taken to manage the spread
of disease by cancelling thousands of activities of social gatherings in
offices, clubs, classrooms, reception centres, transport services, travel
restrictions, contact tracing leaving the countries in complete lockdown
(Hopman et al., 2020;Cohen and Kupferschmidt, 2020). Yet weeks of
being in isolation, quarantine, physical trauma creates further loneliness
and anxiety and issues of a mental health crisis that have been mostly
overlooked. At the individual level and the government level, proper risk
communication is required. Special attention should be given to combat
child and women abuse. Necessary action should be proposed for the
post-recovery phase, suicide prevention, and mental health management
(Duan and Zhu, 2020;Gunnell et al., 2020;Mamun et al., 2020). Several
cases of suicide were reported due to the fear and stress of COVID-19
infection symptoms, job-loss, sudden fall to extreme poverty, economic
crisis, hunger, and unable to cope with social hatred. This kind of trau-
matic situation should be dealt with immediately by the government
through proper community counselling.
Small children are highly vulnerable to abuse if parent(s)/caregivers
are quarantined. Moreover, with limited or no outdoor activities and no
schooling makes them mentally stressed. Moreover, to maintain family
hygiene in the pandemic, the burden just increases on the women along
with her regular household activities. Likewise, it escalated family con-
flicts between men and women arising from physical and mental assault
towards women. Students are also vulnerable to mental pressure as their
education life is extended and posing an uncertain future caused by the
pandemic. The Shutdown of all educational institutions may increase
hatred and mentally depressed young which should be dealt with proper
plans.
4.3. Backing up emergency service providers
In any successful governance, a competent early warning system and
efficient analysis of the situation, interpretation, sharing, and use of
relevant evidence and epidemiological knowledge is required (Gu and Li,
2020). In particular, epidemiological outcomes need to be informed on
time so that they can be accurately evaluated and explained to the gen-
eral people (Xiao and Torok, 2020). The low quality and an inadequate
number of personal protective equipment (PPE) along with insufficient
training to use PPE caused doctors and healthcare professionals infected
across the country. Already 11% of the doctors and healthcare workers
are infected with COVID-19. Moreover, members of Bangladesh police,
armed forces, and rapid action battalion (RAB) along with other security
agencies who have been jointly working to ensure social distancing
across the country are at high risk of being infected. Already 914 mem-
bers of security forces have been infected with several reported deaths.
Besides, bankers, RMG factory workers, businessmen, shop keepers, daily
wedge earners are at higher risk of infection.
4.4. Inclusive plan to protect the vulnerable communities amidst the
pandemic and upcoming environmental disasters
Societies where underserved communities exist, they strongly fear
government information and politics. The ultra-poor are often being left
out of the relief program during the disasters. Public risk communica-
tions are therefore needed to let people know about the mental and social
risk of elderly, children, people with special needs, disabled as they are
susceptible to mental stress, and other disasters.
It should be mentioned here that government plans on pandemic
control, risk alleviation, and social management must be as inclusive as
possible. An inclusive commitment means responding to COVID-19
pandemic in a way that is sensitive to the most vulnerable commu-
nities, including ultra-poor, daily wedge earners, homeless people, un-
employed, indigenous communities, immigrant communities, people
with disabilities, and certain frontline healthcare workers and emergency
responders. Prison centres, nursing homes, orphanages, homeless shel-
ters, and refugee camps can be a focus for disease outbreaks; people in
such settings often have inadequate access to basic healthcare and
comorbidities that increase the risk of serious illness (Berger et al., 2020).
Moreover, the government should take proper strategy to protect the
agricultural farmers and their crops amidst the pandemic to strengthen
the food security of the country and maintain the supply chain to
consumers.
M. Shammi et al. Heliyon 6 (2020) e04063
10
As a country of climate change vulnerability, there might be some
additional risk factors of occurring natural disasters such as tropical cy-
clones, flash floods which may add further tolls for the country. More-
over, the shutdown of all kinds of business centres except groceries,
pharmacies, and other daily necessities puts stress on the country's
economy and financial burden. With RMG factories and other industrial
production resumed from 26 April, another infectious outbreak of
dengue along with critical level community transmission of coronavirus
might have a cumulative/synergistic negative impact on the public
health systems in Bangladesh. In this situation factory operation should
be maintained with minimum social distancing; water, sanitation, and
hygiene (WASH) kit; occupational health and safety guideline, and good
healthcare management. BGMEA should be the monitoring body and
draw safety protocols to protect the workers while maintaining public
safety.
5. Concluding remarks
This perception-based study tried to visualize the mental stresses as
well as the socioeconomic crisis due to the COVID-19 pandemic in
Bangladesh. It can be undoubtedly established that mental stress due to
the COVID-19 is because of the lockdown without ensuring the funda-
mental needs of the vulnerable ones. The weak governance in the
healthcare systems and the facilities further exacerbates the general
public's anxiety. The urban COVID-19 testing facilities, long serial to be
tested, lowest facilities in the dedicated hospital units for COVID-19
patients hampered the other critical patients to get healthcare services.
It was a good decision by the government to recruit 6000 doctors and
nurses to combat this pandemic. The government needs to take decisions
to implement testing facilities for both public and private clinical labo-
ratories all over Bangladesh. As with the COVID-19 outbreak, other
critical care patients and infectious diseases such as dengue testing are
being affected and patients are being deprived. It is also timely steps that
the government starts measures on dengue testing as well to all the
COVID-19 patients.
However, numerous mental wellbeing and socioeconomic factors that
have been identified in the study are already threatening public with fear
and anxiety can be considered for the upcoming threat due to COVID-19
in Bangladesh are as follows; risk of community transmission, healthcare
capacity, governance coordination and transparency, relief for the low-
income population, proper biomedical waste management through
incineration, and preparation for the possible natural disasters. The
recommendations collected in the perception study can be summarized
as to increase COVID-test rate and medical facilities. The strengthening
and decentralization of the COVID-19 medical facilities and treatment
are especially important for all 64 districts as the disease spread to entire
Bangladesh. Besides, proper risk assessment and dependable risk com-
munications, multi-sectoral management taskforce development, take
care of biomedical waste, ensure basic supports to the people who need,
and good governance was suggested to reduce mental and social stress
causing a socioeconomic crisis of COVID-19 outbreak in Bangladesh.
Finally, this assessment process could help the government and policy-
makers to judge the public perceptions in an emergency situation to deal
with COVID-19 pandemic in densely populated lower-middle-income
countries like Bangladesh.
Declarations
Author contribution statement
M. Shammi: Conceived and designed the experiments; Analyzed and
interpreted the data; Wrote the paper.
M. Bodrud-Doza: Conceived and designed the experiments; Per-
formed the experiments; Analyzed and interpreted the data; Contributed
reagents, materials, analysis tools or data.
A. R. M. Towfiqul Islam: Performed the experiments; Analyzed and
interpreted the data; Contributed reagents, materials, analysis tools or
data.
M. Mostafizur Rahman: Conceived and designed the experiments;
Performed the experiments; Wrote the paper.
Funding statement
This research did not receive any specific grant from funding agencies
in the public, commercial, or not-for-profit sectors.
Competing interest statement
The authors declare no conflict of interest.
Additional information
Supplementary content related to this article has been published
online at https://doi.org/10.1016/j.heliyon.2020.e04063.
Acknowledgements
The authors would like to acknowledge all the frontline doctors
fighting this pandemic and all the researchers cited in the references.
Also, the authors are gratefull to all the participants in this study.
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