Keywords
Bangladesh, COVID-19, Cost, Lifestyle.
Bangladesh, COVID-19, Cost, Lifestyle.
Coronavirus disease 2019 (COVID-19), an extremely infectious infection caused by severe acute respiratory syndrome coronavirus 2, is now sweeping the globe (SARS-CoV-2). This communicable disease has infected over 200 countries and regions around the world. It began in Wuhan, China, in December 2019 and easily expanded over the world, causing one of the worst health and economic disasters in human civilization. COVID-19 has touched around 248 million individuals worldwide, with around five million people dying as a result.1–3 On March 11, 2020, COVID-19 was proclaimed a pandemic.4 As an unusual multifunctional stressor, the pandemic crisis has wreaked havoc on health and the economy around the world, posing huge social, socioeconomic, and clinical issues as a result.5 Bangladesh is one of the largest and most populous nations, and as a result, it has been heavily impacted by the virus, putting a strain on its economy and public health system.6 Bangladesh’s economy expanded at one of the quickest rates in the world, with an average GDP growth rate of 7.41 percent over the last five years and 8.2 percent in 20197 Including an average annual growth rate of 16.42 percent, the per capita income increased to $1855.74 in 2019 from $702.26 in 2009. In 2019, the jobless rate was 4.15 percent, one of the lowest in the world.8 The global economy has dropped considerably, and COVID-19 has had a detrimental impact on practically every country.2 COVID-19 has somehow put people’s health in jeopardy, but it has also taken hold of the country’s social, economic, spiritual, and other aspects. Nonetheless, of all the spheres, the health and economic segments have experienced the most (Addressing economic and health challenges of COVID-19 in Bangladesh: preparation and response). Notwithstanding the health issues, the financial impact of the COVID-19 lightning has had a significant impact on the wealth of individuals and communities. For low-income households, a loss of income due to an incident can lead to unemployment, a lack of food security, and a reduction in access to medical treatment.9 According to experts, the ongoing COVID-19 event will have a huge impact on economic development. COVID-19 had a serious influence on the Bangladeshi economy because it appeared at a time when a few key indicators of the economy were on a downward trend. Financial researchers predict a 40.0 percent drop in Bangladesh’s $310.0 billion GDP, with 0.89 million jobs under jeopardy because to the epidemic.10,11 The state’s second-level prophylactic actions to protect its citizens against the new coronavirus include but are not strictly limited. Soap, hand sanitizers, surgical gloves, swab tests, and other items were made freely available by the government to make people aware of COVID-19. Mass gatherings were banned, schools and public transportation were shut down, and the city was put on partial lockdown and then full lockdown12. Personalized protective equipment, contact detectors, testing, and immunizations are among the direct health-care costs. They also consider the disease’s treatment expenses as well as its lengthy physical and emotional consequences.13 Hand washing for at least 20 seconds, as well as the use of hand sanitizers, facemasks, gloves, and other protective equipment, are all recommended to avoid contracting this pandemic condition. Lives of millions have been flipped upside down on a human level. Because of this, real economic effects are more varied and maybe even more extreme than those shown by economic factors alone.
In this article, we’ll look at the concerns surrounding COVID-19 and how it affects people from many walks of life. We will highlight the havoc and suffering it has inflicted in terms of economic, social, cultural, chronic disease and, most importantly, human aspects. There was no relevant study in Bangladesh that addressed the COVID-19-induced cost increases in the common people’s lifestyle; this will give an idea of the cost increases due to COVID-19 in the local lifestyle. Our findings show that these economic mechanisms are responsible for the majority of heterogeneity in COVID-19-induced cost increases in Bangladeshi households’ lifestyles. As a result, the study’s specific objective is to evaluate Bangladesh’s views on COVID-19, as well as the impact of the outbreak on their lifestyles and earnings.
Between the ages of 18 and 80, a cross-sectional and confidential online community survey was undertaken. From August 27 to October 10, 2020, the research was administered. The Google questionnaire method (Google Forms) was used to create a semi-structured form, and the associated link was shared with the public on social networks (i.e., Facebook, WhatsApp) using a snowball sampling. The link was also sent to the investigations’ and research assistants’ respective contact lists. The choice to gather information utilizing online methods was based on the investigators’ need to promote social distance during the critical circumstances in Bangladesh. Bangladesh imposed limitations like home confinement during the pandemic’s later waves. But social segregation measures were strengthened, a curfew was introduced, mask use was required, and movement between territories was restricted. At first, 400 potential responders gave their written informed consent via the internet. After getting rid of responses that didn’t meet the exclusion criteria, like living abroad, giving the same answer twice, or not giving enough information, the final data set had 320 participants. After that, a total of 320 individuals answered all of the questions on the questionnaire. Being a Bangladeshi citizen above 18 years, obtaining internet access, and volunteering were the only requirements for participation in the research. The sample size was determined using a single sample proportion test. The test determines the smallest sample size (n) necessary to assess a percentage in a source population based on the intended level of significance (Z), a margin of error (d), and the predicted level of the proportion (p). The calculations considered the following presumptions1: Due to a lack of prior research on cost upraises in lifestyle in common people in Bangladesh, a 50% anticipated incidence among local people in Bangladesh was chosen (p=50%). The level of 95% confidence (Z=1.96), and3 The level of 5% error (d=0.05). the following is the formula:
384 participants were included in our sample size, but only 320 completed the questionnaire because the response rate was around 80%. The electronic questionnaire was piloted with a random selection of user’s collection of primary data to find errors and provide clarification. The online questionnaire had a short summary of the background, goal, and steps, as well as comments about how participants could work on their own and remain anonymous, and extra notes to help fill it out. The questionnaire was provided in supplementary files.
Microsoft Excel 2019 and SPSS version 25.0 (Chicago, IL, USA) were used to analyze the data. Regarding modifying, organizing, and formatting, Microsoft Excel was used. After that, the Excel file was uploaded into the SPSS software. We used descriptive statistics (frequency, percentages, means, and standard deviations) as well as first-order analyses (chi-square tests). To find important correlations between categorical dependent and independent variables, binary logistic regression was used with a 95% confidence range.
The investigation was carried out in compliance with the Helsinki Declaration and Institutional Research Ethics. This experiment received authorization from North-South University’s Institutional Review Board/Ethical Review Committee (2020/OR-NSU/IRB/0402). The user was immediately led to the research description and verbal informed consent section by clicking a button after having read all relevant information, which was due to COVID-19’s limited movement at that time by the government and also to promote social distancing during the critical circumstances in Bangladesh. After completing the survey, eligible individuals were prompted to fill out a demographic profile. The research followed the CHERRIES (Checklist for Reporting Results of Internet ESurveys) principles.
Samples were collected from 320 participants during the study period. In all, 220 (69%) were male, the majority (32%) were between the ages of 31 and 40, the overwhelming (71%) lived in urban areas, 279 (87%) identified as Muslims, and 120 (38%) worked in the private sector. The mass of those who responded were in classes 13–16 (55%), were married (80%), had a family4–5 (76%), earned more than 40,000 Taka (46%) and also between 20,000 and 40,000 Taka (35%) each month. 200 of the persons who responded did not suffer from any kind of chronic illness, whereas the remaining 62 did. 311 out of 312 individuals who participated in the questionnaire wore masks at the commencement of COVID-19. This started with the very first COVID-19 case that was discovered in Bangladesh. Sanitizer was the method of choice used 95% of the time, whereas soap was used 36% of the time. During this same period, 22% of people had a decrease in their income, and 7% of people were fired from their work.
According to Table 1, the mean age of the participants was 39.77, with ages ranging from 18 to 80 years, and age is significantly associated (P value <0.001*) with the development of chronic diseases. People over the age of 51 had approximately 41.5% of chronic diseases, and approximately 41.9% had one chronic disease. More than two chronic diseases were present in the age groups 41–50 years, 31–40 years, and 18–30 years, with 17.7%, 25.8%, and 17.4%, respectively, and approximately 29%, 17.7%, and 11.3% having at least one of the chronic diseases. The male-to-female ratio was 2.2:1. Among the 320 participants, 228 (71.3%) were from urban areas, with at least two chronic diseases (74.2%) and at least one chronic disease (71%), and 92 (28.0%) were from rural areas, with more than two chronic diseases and at least one chronic disease (71% and 29%, respectively). In terms of education, post-graduate participants were 95 (29.7%), graduate participants were 175 (54.7%), and below-undergraduate level participants were 50 (15.6%). People who were post-graduated and had more than two of the chronic diseases or at least one of the chronic diseases were 33.2% and 32.3%, respectively. People with more than two chronic diseases and at least one chronic disease who were graduates or at the graduate level were 47.6% and 51.6%, respectively. People below graduate level had more than two of the chronic diseases, and at least one of the chronic diseases affected 13.2% and 16.1%, respectively. In terms of profession, the percentages of people who were medical doctors having more than two chronic diseases and at least one chronic disease were 17.3% and 17.7%, respectively. People in private employment who had more than two chronic diseases or at least one chronic disease were 18.5% and 30.6%. People who were in government jobs and had more than two of the chronic diseases or at least one of the chronic diseases were 6.6% and 14.5%, respectively. People who were unemployed and had more than two chronic diseases or at least one chronic disease were 11.3% and 14.5%, respectively. Marital status is significantly associated (p value <0.001*) with chronic diseases. People who were married and had more than two of the chronic diseases or at least one of the chronic diseases were 81.6% and 88.7%, respectively. People whose monthly income was more than 40,000 Taka and who had more than two chronic diseases or at least one of them were 45.2% and 46.8%, respectively. People with a monthly income of 20,000 to 40,000 Taka who had more than two chronic diseases or at least one chronic disease were 17% and 17.7%, respectively. People whose monthly income was below 20,000 Taka and who had more than two of chronic diseases or at least one of them were 37.8% and 35.5%, respectively. Participants with a growing number of family members were significantly (p = 0.033*) with chronic diseases.
Variables | Frequency (%) | Chronic Diseases | p-value | ||
---|---|---|---|---|---|
None | 1 | ≥2 | |||
(n=200) | (n=62) | (n=58) | |||
Age groups, years | |||||
18-30 | 70 (21.9) | 53 (26.5) | 7 (11.3) | 10 (17.4) | |
31-40 | 103 (32.2) | 77 (38.5) | 11 (17.7) | 15 (25.8) | <0.001* |
41-50 | 80 (25.0) | 51 (25.5) | 18 (29.0) | 11 (17.7) | |
51+ | 67 (20.9) | 19 (9.5) | 26 (41.9) | 22 (41.5) | |
Mean (SD) | 39.77 (10.72) | ||||
Gender | |||||
Male | 220 (68.8) | 134 (67.0) | 45 (72.6) | 41 (63.6) | 0.298 |
Female | 100 (31.3) | 66 (33.0) | 17 (27.4) | 17 (27.4) | |
Religion | |||||
Islam | 279 (87.2) | 171 (85.5) | 57 (91.9) | 51 (86.8) | |
Hinduism | 35 (10.9) | 25 (12.5) | 4 (6.5) | 6 (11.3) | 0.331 |
Buddhist | 2 (0.6) | 1 (0.5) | 0 (0.0) | 1 (1.9) | |
Christian | 4 (1.3) | 3 (1.5) | 1 (1.6) | 0 (0.0) | |
Area of residence | |||||
Urban | 228 (71.3) | 141 (70.5) | 44 (71.0) | 43 (74.2) | 0.758 |
Rural | 92 (28.7) | 59 (29.5) | 18 (29.0) | 15 (25.8) | |
Education | |||||
Up to Class 12 | 50 (15.6) | 33 (16.5) | 10 (16.1) | 7 (13.2) | |
Class 13-16 | 175 (54.7) | 113 (56.5) | 32 (51.6) | 30 (47.6) | 0.272 |
Class 17 and above | 95 (29.7) | 54 (27.0) | 20 (32.3) | 21 (33.2) | |
Profession | |||||
Unemployed | 27 (8.4) | 12 (6.0) | 9 (14.5) | 6 (11.3) | |
Govt. service | 39 (12.2) | 25 (12.5) | 9 (14.5) | 5 (6.6) | 0.441 |
Private job | 120 (37.5) | 83 (41.5) | 19 (30.6) | 18 (18.5) | |
Medical Doctor | 67 (20.9) | 39 (19.5) | 11 (17.7) | 17 (17.3) | |
Others | 67 (20.9) | 41 (20.5) | 14 (22.6) | 12 (22.6) | |
Marital status | |||||
Married | 257 (80.3) | 149 (74.5) | 55 (88.7) | 53 (81.6) | |
Single | 58 (18.1) | 46 (23.0) | 7 (11.3) | 5 (9.4) | <0.001* |
Others | 5 (1.6) | 5 (2.5) | 0 (0.0) | 0 (0.0) | |
Monthly income (bdt) | |||||
Below 20000 | 60 (18.8) | 70 (35.0) | 22 (35.5) | 20 (37.8) | 0.736 |
20000 – 40000 | 112 (35.0) | 40 (20.0) | 11 (17.7) | 9 (17.0) | |
Above 40000 | 148 (46.3) | 90 (45.0) | 29 (46.8) | 29 (45.2) | |
No of family members | |||||
1-3 | 42 (13.1) | 34 (17.0) | 5 (8.1) | 3 (5.7) | |
4-5 | 244 (76.3) | 146 (73.0) | 51 (82.3) | 47 (74.1) | 0.033* |
> 5 | 34 (10.6) | 20 (10.0) | 6 (9.7) | 8 (12.3) | |
Smoking history | |||||
Never smoked | 227 (70.9) | 147 (73.5) | 45 (72.6) | 35 (58.3) | |
Former smoker | 35 (10.9) | 18 (9.0) | 8 (12.9) | 9 (17.0) | 0.313 |
Current smoker | 58 (18.1) | 35 (17.5) | 9 (14.5) | 14 (24.7) | |
Alcohol use | |||||
No | 292 (91.3) | 180 (90.0) | 60 (96.8) | 52 (90.6) | 0.325 |
Yes | 28 (8.8) | 20 (10.0) | 2 (3.2) | 6 (10.4) | |
Drug abuse | |||||
No | 318 (99.4) | 198 (99.0) | 62 (100.0) | 58 (100.0) | 0.276 |
Yes | 2 (0.6) | 2 (1.0) | 0 (0.0) | 0 (0.0) |
According to Table 2, 97.2% of the 320 participants used a mask, with 26.6%, 21.6%, and 0.3% of them using cloth masks, surgical masks, and K95/N95 masks, respectively. In this study, we discovered that 21.9% of people had lower pay during the COVID-19 epidemic, whereas 7% of people did lose their jobs.
The general public’s estimate of the sum added from July 2020 to July 2021, as compared to the typical time frame. About 48% of consumers spent between 5,000 and 20,000 Tk during the COVID-19 period, compared to 39% and 13%, respectively, who spent between 20,000 and 50,000 Tk and above 50000 Taka (Figure 1). During the COVID-19 pandemic, people’s discretionary spending increased most noticeably in the areas of face mask cost and hand sanitizer cost (around, 49%, among 20001-50000 Taka group), transportation cost (around 45%, among 5000-20000 Taka spent people), and electronic device cost (around 25%, likely above 50000 Taka part people). The remaining costs fell below 15% of people’s budgets (Figure 2). The majority of patients suffered from systemic hypertension (HTN), followed by a significant number with both HTN and diabetes mellitus (DM), as well as those who were solely affected by DM Diabetes mellitus (DM) (Figure 3). If we observed from the World Bank data that in 2019, Bangladesh’s GDP per capita growth (annual%) scale (precision) was seven units, but in the pandemic year 2020 it suddenly fell to 1.4 units, If we include other South Asian countries, GDP per capita growth will fall in 2020 compared to last year (2019) (Figure 4).14 Bangladesh’s total GDP growth (annual rate) slows down in 2020 compared to 2019, with declines in agriculture, industry, and services. The decline in industry is particularly severe, falling from 12.7 to 1.3. (Figure 5).
Note. GDP per capita growth (annual %); Scale (Precision)=Unit (0.0); Data from: World Bank, World Development Indicators.
Acute watery diarrhoea, dengue fever, influenza, malaria, niphavirus, Chikungunya, and other life-threatening diseases have all occurred in Bangladesh in the past, and the country has withstood the economic and social consequences of these outbreaks.15–17 In many nations, COVID-19 is a major public health hazard linked to severe morbidity and mortality as well as economic loss. While the cost of illness for various infectious diseases has been studied in Bangladesh understanding of the cost of diarrheal disease illness from a larger social viewpoint is scarce.18 The average societal cost of disease per episode was BDT 5274.02 (US $ 67.18), with hospital and outpatient costs of BDT 8675.09 (US $ 110.51) and BDT 1853.96 (US $ 23.62), respectively.18 Another study says that diseases caused by influenza cost Bangladesh an estimated US$169 million in 2010.19 Patients in need of medical attention in Bangladesh paid for it entirely out of pocket because no universal health care system existed. Socioeconomic factors necessitated a substantial outlay of resources for medical care. The entire cost of missed productivity due to the chikungunya epidemic is unknown at this time. However, we tried to provide a picture of the financial impact on victim families by utilizing responses to a rating scale.
Ever since the outbreak of COVID-19 in China, the whole economy has been in disarray. The world economy has been hit particularly hard by the COVID-19 pandemic, especially in Bangladesh. The lockdown has been so severe that nearly all activities have been suspended. There has been a worldwide drop in the prosperity of both nations and financial institutions. According to a study conducted in Greece, COVID-19 is linked to higher absence rates and duration among Healthcare personnel (HCP). Indirect expenses, especially absenteeism, are a primary driver of overall expenditures for HCP exposed to COVID-19 patients, according to two distinct structured questionnaires.20 Another study reported that the potential consequences resulted in a decline in socioeconomic activities and a decrease in community income. The correlation analysis revealed a strong link between pandemics that tested positive for COVID-19 and mortality rates associated with socioeconomic conditions, with an average correlation coefficient of 0.80.21 A study conducted on Nigerians suggested that the majority of the respondents knew enough about the COVID-19 illness, its prevention measures, and how it spread. Furthermore, more than half of those polled said the pandemic had harmed their social lives and financial situations.22
Bangladesh’s poverty rate is expected to quadruple to 40.9 percent from its pre-pandemic level. The informal sector, which employs almost 80–90 percent of the workforce, has been hit the hardest. Between March and May, the average family income fell by as much as 74% (same). 496 (89.3%) respondents said their knowledge of the viral epidemic had improved. A total of 350 people (63.6%) were impacted by professional work or experienced a financial loss in their firm. More than 42% of people are devoting time to personal development, online education, and other activities.3 Impact on COVID-19 infections, hospitalizations, healthcare spending (in US dollars), and incremental cost-effectiveness per case averted.23
A global study mentioned the number of factors that affect poverty incidence in a panel of 76 nations for the period 2010–2019. According to the dynamic panel GMM estimates, communicable diseases, chemical-induced carbon and fossil fuel combustion, and a lack of access to basic handwashing facilities all threaten to increase poverty headcounts, whereas an increase in healthcare expenditures reduces poverty headcounts significantly across countries.24 COVID-19’s GDP cost is significantly higher than its other components. The cost of the COVID-19 crisis in 2020–2021 is estimated to be 14% of 2019’s GDP (approximately $12,206 mm$). In the case of Spain, it equates to 24 percent of the country’s 2019 GDP, which is 397.3 million euros. Spain has been and will continue to be the European country most economically affected by the pandemic. The GDP cost accounts for 94.7 percent of the overall COVID-19 cost in Spain in 2020, while health-care direct expenditures account for only 2.14 percent. In Spain, TTQ is the most popular tactic. Only seven euros will be repaid for every euro spent on it in terms of saved healthcare resources.25
Our epidemiology simulations reveal that a one-week delay in implementing lockdown would have cost more than half a million lives across eight countries. Furthermore, countries that moved quickly saved significantly more lives than those that waited. We demonstrate the costs that national governments were implicitly willing to pay to safeguard their populations, as reflected in the economic activity forgone to save lives, by linking judgments about the time of lockdown and the resulting deaths to economic statistics. These “cost of living” estimates vary greatly between nations, ranging from roughly $100,000 (e.g., the United Kingdom, the United States, and Italy) to over $1 million (e.g., the United Kingdom, the United States, and Italy) (e.g., Denmark, Germany, New Zealand, and Korea). The lowest estimates are further reduced once we correct for under-reporting of COVID-19 deaths.26 The global economy has taken a hit, and COVID-19 has had a detrimental impact on practically every country. Global economic growth was badly harmed in the first half of 2020, and the global economic growth prediction for 2020 was 4.9 percent.13 The international economy may recover faster than projected because to the vaccine, but it will still confront hurdles in the near future.2
During the 45-day lockdown between March and May, Bangladesh’s farmers suffered a loss of 565.36 billion takas.27 Dairy and poultry farmers suffered significant losses during the outbreak. The price of everyday essential items increased as a result of the lockdown, causing the supply-chain system to break down.13 COVID-19 had a considerable impact on the respondents’ income, savings, and social position, according to the findings. The study is intended to aid policymakers in understanding the socioeconomic position of Bangladesh’s lower-middle and lower-income groups, since it covered their socioeconomic state during COVID-19 and the obstacles they encountered.28
There are a few flaws in this study. To begin, this study is multidisciplinary. As a result, observations may be impossible to specify. Secondly, personality has disadvantaged that pale in comparison to face-to-face questionnaire surveys, together with numerous biases. Third, to avoid potential propagation, this study used a digital survey method, which means the proportion demonstrates sampling biases because it was digitized and thus limited to only those with an internet connection, leading to speculation that it demonstrates an exact picture of the entire Bangladeshi population. Fourth, we just asked a few questions to assess COVID-19-induced lifestyle cost increases. These findings may only apply to Bangladeshi young adults with a higher level of education. As a result, they can indeed be applied to the entire community. The data’s external validity and ability to infer causality are constrained by the cross-sectional design and recruitment via non-probabilistic methods. Furthermore, the COVID-19 increased the cost of lifestyle evaluation, which should be established through focus group discussions and in-depth interviews and built as multidimensional assessments.
The objective of this perspective study was to conceptualize the expense as well as the socioeconomic catastrophe in Bangladesh as a result of the COVID-19 pandemic. Ultimately, in a COVID-19 outbreak scenario, this vetting process potentially aid the government and stakeholders in judging public opinions in thickly urbanized lower-middle-income nations such as Bangladesh.
MAA, DHH, NEM, ASB, SN, SA did the literature search. MAA and DHH conceived and designed the study, MAA, DHH, NEM, SA, ASB, and SN oversaw its implementation, analysis, and write-up. MAA and NEM planned the statistical analyses. MAA outlined the data collection procedure. MAA, SN and SA led the study & field implementation; MAA, NEM, ASB, SA and SN were responsible for data entry. MAA, NEM, SN, ASB and SA contributed to the study field implementation and did data entry. MAA and DHH verified the underlying data. MAA and NEM did the statistical analyses. MAA, NEM, DHH, SA, ASB and SN wrote the manuscript & first draft. The manuscript was reviewed and accepted by all contributors.
Mendeley Data. COVID-19 induced cost upraises in the lifestyle of common people in Bangladesh: a cross-sectional study. DOI: 10.17632/pnm6c9mwzs.1. 29
Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).
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