COVID-19 is a respiratory viral contagious disease caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) [1,2]. Since its first identification in Wuhan, China in December 2019 [3], more than 177 million cases have been confirmed with 3.8 million confirmed deaths [4], making COVID-19 one of the deadliest pandemics in history. The disease was declared a global pandemic by the World Health Organization on 11 March 2020.

In public health, social distancing generally refers to a set of non-pharmaceutical measures that are intended to halt the spread of a contagious disease by imposing physical distancing among a population group (the physical distance may vary from one country to another and may change with time) and reducing the frequency of interaction/contact among the population [5,6]. In an attempt to ‘flatten the curve [7], during the early stages of the pandemic, social distancing guidelines such as self-isolation, quarantine were enforced as preventive measures. Prior to the development of an effective vaccine, such preventive measures played a pivotal role in checking the rapid spreading of the disease and reducing the infection rate [8,9]. However, social distancing guidelines have also paved the way to adverse effects on the mental status and lifestyle of people belonging to different age [10,11], gender [12-14], profession [15,16], socio-economic background [17,18], race and ethnicity [19,20]. Generally characterized as a developing nation, Bangladesh has emerged as one of the fastest growing economies in the last decade which is largely attributed to its demographic dividend, stable macroeconomic conditions, and exports in the garments sector [21]. Being one of the world’s densest populations, the government of Bangladesh has faced significant challenges in imposing social distancing measures [22,23]. Alongside socio-economic hurdles of social distancing guidelines associated to the COVID-19 pandemic, several studies have reported severe adverse impact on the mental health and psychological status [24-28] of Bangladeshi people.

In this study, we aim to elucidate the perception of social distancing guidelines among Bangladeshis living in two geographic regions – Bangladesh and The United States of America.

Study Design and Participants

A web-based cross-sectional study was conducted among people of Bangladeshi origin living in their home country and abroad. Participants were divided into two groups -- primarily residing in their native country and currently living in the United States either due to permanent migration, or job, or higher education. Participants living outside of these two countries were not included in this study due to relatively smaller sample size and demographic heterogeneity.

Data Collection

The data for this study was collected in the period between June 1st and July 31st, 2020. A structured questionnaire was developed and distributed through social media platforms. In the first page of the data collection instrument, the purpose of the study was stated and written informed consent was sought from the participants. Participation was voluntary and anonymity was preserved. The entire questionnaire including the cover page was developed in English with Bengali translation provided within parenthesis. The questionnaire was developed focusing on collecting information in three major sections. The first section included questions about sociodemographic characteristics i.e., age, gender, country of primary residence, length of residence, area of residence, educational status, income, and marital status. In the second section, participants were asked several questions about their knowledge and perception of social distancing regulations during the COVID-19 pandemic. In the third section of the questionnaires, participants were asked to choose reasons they believe are keeping them from complying with the regulations of social distancing e.g., employment issues such as inability to work from home, overcrowded living space, excessive boredom from staying at home, lack of proper information regarding the social distancing regulations, etc.

Measures

The main outcome of interest in this study was the knowledge and perception of the participants about the COVID-19 related social distancing regulations which was measured by a scoring system with the range of possible scores from 0 to 9. Participants were asked what they understand by social distancing and to choose as many responses as they think are correct from a list of options e.g., staying at least 3-6 feet from other people when going outside, using facemask when going out, avoiding unnecessary travels outside the city or country, etc. One point was assigned for choosing each of the seven correct responses. They were also asked if they think during the COVID-19 pandemic it is okay to “go out and socialize if someone is healthy” and “continue normal socializing wearing a face mask”. One point was assigned for answering no to each of the questions. Finally, the Perception of Social Distancing Regulation (PSDR) score was calculated by summing up all the assigned points.

Data Cleaning

The total number of respondents were 3008. We excluded 45 participants who did not primarily reside in the US or Bangladesh and 240 participants who reported primarily residing in both countries. We also excluded 54 participants who were below 18 years old, 319 participants who looked up answers during the survey, and 12 participants for contradictory answers to some questions. The final number of total respondents after cleaning the data was 2338.

Handling of Missing Data

Around 38% of the participants declined to report their income in the survey response. A univariate t -test comparing the mean PSDR score between the missing and non-missing income categories confirmed a Missing Completely at Random (MCAR) mechanism. We used Multiple Imputation (MI) process to impute the income information for these participants. MI is a state-of-the-art technique to handle missingness of the data that generates several copies of the dataset and fills in each copy with different estimates of the missing values. Finally, it pools all the imputed datasets to combine the parameter estimates and standard errors into a single set of results.

Statistical Analysis

Descriptive statistics of the sample demographic characteristics were calculated separately for participants residing in the United States and Bangladesh. Additionally, the frequency and percentage of responses to the social distancing regulation questions were calculated and reported by the country of primary residence of the participants. Bivariate analysis was performed to assess the association between the 3 categories of PSDR score (0-3, 4-6, and 7-9) and sociodemographic characteristics of the participants according to their primary country of residence. Finally, the imputed dataset was used to conduct multiple logistic regression analyses to investigate the predictability of PSDR score by the sociodemographic characteristics of participants from each country. All analyses were performed by SAS 9.4.

A total of 2338 participants were selected for this study with around 80% (n = 1879) primarily residing in Bangladesh and 19% (n = 459) living in the United States. For participants living in Bangladesh most were 18-34 years old (n=1475; 78%); female (n=964; 51%); living in urban area (n=1326; 70%) with a graduate or professional degree (n=1448; 77%). Similarly, for participants living in the United States most were 18-34 years old (n=304; 66%); female (n=248; 54%); living in urban area (n=291; 63%) with a graduate or professional degree either from Bangladesh (n=190; 41%) or the United States (n=209; 45%). Majority of the participants from Bangladesh has a high annual household income of 84,000 BDT or more (n=607; 53%). On the other hand, majority of the participants from the United States has a low annual household income of income of $31,000 or less (n=123; 39%) (Table 1). Mean PSDR score is slightly higher among the U.S. participants (7.58, ± 1.90) than the participants from Bangladesh (6.27, ± 2.48). Most of the participants from the United States correctly identified the 9 survey responses that were used to create the PSDR score. On the other hand, only 55% (n=1043) participants from Bangladesh identified food and grocery deliveries as a part of the social distancing. Overall, 46% (n=1,116) participants think it is okay to continue normal socializing while wearing a face mask during the COVID-19 pandemic (Table 2). Bivariate analysis showed significant association of the 3 PSDR score categories with gender (p-value = 0.01) and highest level of education (p-value = 0.002) for the participants primarily living in the United States. For participants living in Bangladesh, PSDR score was significantly associated with age (p-value = 0.002), highest level of education (p-value

Table 1: Demographic characteristics of participants by their primary country of residence

Table 2: Comparison of knowledge and perception of social distancing among the participants by their primary country of residence

Table 3: Bivariate analysis: association between PSDR score categories and sociodemographic factors by the country of primary residence of the participants

Table 4: Results of multiple imputation with 50 iterations for the annual household income variable

Table 5: Logistic regression analysis: association between PSDR score and sociodemographic characteristics by country of primary residence

Maintaining social distancing has been a fundamental public health measure during the initial fight against the COVID-19 pandemic. The effectiveness of various social distancing measures depends more on the compliance of general population than on central decision making by the government. The aim of this study was to assess the knowledge and perception of social distancing regulations among Bangladeshis and explore if sociodemographic factors predict their level of knowledge. We compared the findings with the knowledge level and the impact of sociodemographic factors on a sample of participants of same ethnic origin but living in a developed country. To date, no research has been conducted to explore this viewpoint. The most notable difference in the sociodemographic factors between these two groups of participants was in the distribution pattern of their household income. Although, in terms of the highest level of education, both groups have similar percentage of participants who completed university education, most of the participants from Bangladesh reported being in the highest category of the household income while the majority of the participants from the U.S. belonged to the lowest income groups. In bivariate analysis, household income was found to be significantly associated with the 3 categories of PSDR score for participants living in Bangladesh, but ordinal logistic regression with imputed dataset did not reveal any significant role of household income in predicting PSDR score for neither of the countries’ participants. The overall PSDR score was 6.53 with a standard deviation of 2.43. U.S. participants, despite having similar education level distribution and comparatively being in the lower income category, have higher mean PSDR score than Bangladeshi participants. Clearly the annual household income did not play much role in predicting the PSDR score in neither group of the participants. Rather, for participants from both countries people who have completed university level education were found to score significantly higher compared to the persons who completed elementary level education only. These findings indicate the possible paucity among the low educated group of people regarding interpreting the directions issued by the government for maintaining social distance during the COVID-19 pandemic.

There are some limitations of our study that impacts the generalizability of the findings. Firstly, the data was collected through a web-based questionnaire circulated in the social media which heavily represent the younger, wealthier, urban population with higher education. Secondly, the instrument used in measuring the PSDR score was not validated previously. However, a high Cronbach’s alpha value (0.87) indicates the reliability of the questionnaire.

While governments worldwide had introduced social distancing measures to mitigate the burden of COVID-19 pandemic, the compliance of public heavily depended on the effective conveying of the message to the diverse group of population. Findings from the study underscores the importance of tailoring the message according to the sociodemographic characteristics of the target population, especially level of education. Future research with higher statistical rigor is needed to further advance the knowledge regarding effective message delivery for taming the pandemic.

1. Gorbalenya AE, Baker SC, Baric RS, de Groot RJ, Drosten C ,et al. (2020) The species severe acute respiratory syndrome-related coronavirus: classifying 2019-nCoV and naming it SARS-CoV-2. Nat Microbiol 5(4): 536-544.
2. Kumar A, Singh R, Kaur J, pandey S, sharma V, et al. (2021) Wuhan to World: The COVID-19 Pandemic. Front Cell Infect Microbiol 11: 596201.
3. (2021) In Hunt for Covid-19 Origin, Patient Zero Points to Second Wuhan Market - WSJ. Wall Street Journal, USA.
4. Coronavirus COVID-19 (2019-nCoV), Johns Hopkins University (JHU).
5. What is social distancing and how can it slow the spread of COVID-19?. Johns Hopkins university, USA.
6. (2022) Public Health Guidance for Potential COVID-19 Exposure Associated with Travel | CDC, USA.
7. (2020) Flattening the Curve for COVID-19: What Does It Mean and How Can You Help?. USA.
8. McGrail DJ, Dai J, McAndrews KM, Kalluri R (2020) Enacting national social distancing policies corresponds with dramatic reduction in COVID-19 infection rates. PLoS One 15: e0236619.
9. Thu TPB, Ngoc PNH, Hai NM, Tuan LA (2020) Effect of the social distancing measures on the spread of COVID-19 in 10 highly infected countries. Sci Total Environ 742: 140430.
10. Marques de Miranda D, da Silva Athanasio B, Sena Oliveira AC, Simoes-e-Silva AC (2020) How is COVID-19 pandemic impacting mental health of children and adolescents? Int J Disaster Risk Reduct 51: 101845.
11. Singh S, Roy D, Sinha K, Parveen S, Sharma G, et al. (2020) Impact of COVID-19 and lockdown on mental health of children and adolescents: A narrative review with recommendations. Psychiatry Res 293: 113429.
12. Sriharan A, Ratnapalan S, Tricco AC, Lupea D, Ayala A, et al. (2020) Occupational Stress, Burnout, and Depression in Women in Healthcare During COVID-19 Pandemic: Rapid Scoping Review. Front Glob Womens Health 1: 596690.
13. Galasso V, Pons V, Profeta P, Becher M, Brouard S (2020) Gender differences in COVID-19 attitudes and behavior: Panel evidence from eight countries. Proc Natl Acad Sci USA 117(44): 27285-27291.
14. Rodriguez-Seijas C, Fields EC, Bottary R, M kark S, R Goldstein M, et al. (2020) Comparing the Impact of COVID-19-Related Social Distancing on Mood and Psychiatric Indicators in Sexual and Gender Minority (SGM) and Non-SGM Individuals. Front Psychiatry 11: 590318.
15. Koren M, Pető R (2020) Business disruptions from social distancing. PLoS One 15(9): e0239113.
16. (2020) It’s retail stores and restaurants, not farms and fisheries, that suffer most from social distancing | VOX, CEPR Policy Portal, UK.
17. Nicola M, Alsafi Z, Sohrabi C, Kerwan A, Jabir A, et al. (2020) The socio-economic implications of the coronavirus pandemic (COVID-19): A review. Int J Surg 78: 185-193.
18. Garnier R, Benetka JR, Kraemer J, Bansal S (2021) Socioeconomic Disparities in Social Distancing during the COVID-19 Pandemic in the United States: Observational Study. J Med Internet Res 23(1): e24591.
19. Latkin CA, Dayton L, Yi G, Colon B, Kong X (2021) Mask usage, social distancing, racial, and gender correlates of COVID-19 vaccine intentions among adults in the US. PLoS One 16(2): e0246970.
20. Castex G, Dechter E, Lorca M (2021) COVID-19: The impact of social distancing policies, cross-country analysis. Econ Disasters Clim Chang 5(1): 135-159.
21. Bangladesh Overview. The World Bank, Bangladesh.
22. Jalais A (2021) Bangladesh in 2020:Debating Social Distancing, Digital Money, and Climate Change Migration. Asian Surv 61(1): 194-201.
23. Anwar S, Nasrullah M, Hosen MJ (2020) COVID-19 and Bangladesh: Challenges and How to Address Them. Front Public Heal 8: 154.
24. Akhtarul Islam M, Barna SD, Raihan H, Nafiul Alam Khan M, Tanvir Hossain M (2020) Depression and anxiety among university students during the COVID-19 pandemic in Bangladesh: A web-based cross-sectional survey. PLoS One 15(8): e0238162.
25. Bhuiyan AKMI, Sakib N, Pakpour AH, Griffiths MD, Mamun MA (2020) COVID-19-Related Suicides in Bangladesh Due to Lockdown and Economic Factors: Case Study Evidence from Media Reports. Int J Ment Health Addict 19(6): 2110-2115.
26. Yeasmin S, Banik R, Hossain S, Hossain MN , Mahumad R et al. (2020) Impact of COVID-19 pandemic on the mental health of children in Bangladesh: A cross-sectional study. Child Youth Serv Rev 117: 105277.
27. Bodrud-Doza M, Shammi M, Bahlman L, Islam ARMT, Rahman MM (2020) Psychosocial and Socio-Economic Crisis in Bangladesh Due to COVID-19 Pandemic: A Perception-Based Assessment. Front Public Health 8: 341.
28. Faisal RA, Jobe MC, Ahmed O, Sharker T (2021) Mental Health Status, Anxiety, and Depression Levels of Bangladeshi University Students During the COVID-19 Pandemic. Int J Ment Health Addict 20(3): 1500-1515.