Complication Severity and Its Association with the COVID-19 Prevention, Management and the Place of Treatment of the COVID-19 Patients in Bangladesh: A Cross-Sectional Study

DOI: https://doi.org/10.21203/rs.3.rs-2332537/v1

Abstract

This study aimed to explore the extent of COVID-19 complications and its association with the pattern of COVID-19 management and prevention at hospital and home settings in urban Bangladesh. The study included 659 COVID-19 positive patients aged 18 and up who were treated at home or in hospitals and lived in Dhaka city from April to September 2021. Among the respondents, around 79% respondents suffering from mild infection believe that the risk of Covid-19 infection can be decreased by wearing mask, while 21% participants with severe infection had similar opinion and have significant association of wearing masks with infection level (p < .001). The predominant primary symptoms of COVID–19 infection was fever (80.9%), dry cough (60.4%), myalgia (56.6%), headache (50.5%), sneezing (38.2%), chest pain (25.9%), diarrhea (23.2%) and loss of smell/taste (21.5%). About 61.8% participants did not suffer from any co-morbidity. Others suffered mostly from diabetes (22.9%), cardiovascular disease (19.7%) and asthma/COPD (7.9%) as co-morbidities. 80.9% respondents having mild infection and 19.1% having severe infection always practiced all preventive measures as wearing masks, used alcohol-based hand rub and using PPE at workplace to avoid Covid-19 infection. The reported post-recovery symptoms are fatigue/muscle weakness (42.3%), headache (39.3%), loss of taste/smell (29.0%), depression (27.2%), cough (25.8%), breathing difficulty (21.1%), trouble in mobility (19.7%), chest pain (19.4%), loss of memory (18.1%), each of joint pain/arthralgia and fever (17.0%) and weight loss (16.4%). Recovery time was found to be significantly influenced by family income, the number of co-morbidities, and the location of therapy. Furthermore, age, the number of co-morbidities, and educational level were all strongly linked to the treatment location. Government needs to emphasize more on making sure the effective level of management at the hospitals and extensive level of awareness at the community level where concerted efforts is inevitable.

Introduction

SARS-CoV-2, a new coronavirus, was initially discovered in Wuhan, Hubei Province, China, in December 2019 (WHO, 2020). The new virus is relevant to the coronaviruses that cause Middle East Respiratory Syndrome (MERS) and severe acute respiratory syndrome (SARS), although it is distinct in its own right (Zaki N., 2020). According to WHO, older adults, as well as individuals with underlying medical disorders, are more likely to acquire severe COVID-19 disease (WHO, 2020). Patients with weak immune systems are often considered to be more exposed (Zhou F., 2020). The most prevalent means of human-to-human transmission are assumed to include direct touch, inhaled droplets, and fomites from an infected individual (WHO, 2019). The virus invades the upper respiratory system through mucosa and finally damaging the lungs (Lin L, 2020). The SARS-CoV-2 infection has been linked to a range of mild to severe clinical manifestations (Nicola M, 2020). Fever, dry cough, diarrhoea, shortness of breath, vomiting, stomach discomfort, generalized myalgia, headache, malaise, and bilateral interstitial pneumonia are the most common symptoms of COVID-19 (Zhang T, 2020).

The current COVID-19 outbreak has exacerbated social stigma and discrimination against people who have come into contact with the virus. Although COVID-19 is primarily a respiratory virus, it affects many tissues, some of which are distal to the respiratory system. COVID-19 may be asymptomatic with the ability to transmit the virus, and some are indistinguishable from regular flu. The current method for limiting the spread of instances is to take preventive measures & to stop COVID-19 from spreading further, early screening, diagnosis, isolation, and treatment are required (GÜNER et al., 2020). Face masks are suggested by the ECDC to prevent COVID-19 transmission from possibly asymptomatic or pre-symptomatic patients (ECDC, 2020). Purpose of social distancing is to decrease contacts between people in a greater community where individuals may be contagious but haven't been detected and hence haven't been separated (Wilder-Smith A, 2020). Patients should wash their hands for 20 seconds with soap and water or use an alcohol rub, work from home, stand 2 meters away from people, avoid contact their nose, eyes, and mouth, and avoid unnecessary travel (Fong MW, 2020). According to studies and leading health organizations, individuals must practice strict hand-washing and respiratory hygiene to prevent the spread of respiratory viruses, particularly COVID-19 (Fang L, 2020). Maintaining communication with friends, relatives and neighbors through telephone chats or using online contacts platforms can be helpful to decrease the effects of community isolation (WHO, 2020).

COVID-19 patients are affected initially symptoms like fever, dry cough, sneezing etc. Among all the early symptoms fever is the most prevalent, which was reported in 88 among 100 of COVID-19 patients in Chinese research (Guan WJ, 2020). Some develop mild symptoms, while others develop severe complications such as respiratory distress and pneumonia, which lead to death. Around 20% COVID-19 patients need hospital admission who receives therapies ranging from oxygen to ventilator support. People with diabetes, according to existing research, are not more susceptible to SAR-CoV-2 infection (Fadini GP, 2020). In the current COVID-19 epidemic, Zhang et al. consider cancer patients to be particularly vulnerable (Zhang L., 2020). One of the most major disorders in chronic COVID-19 patients is hypertension (high blood pressure) (Guan W., 2020).Cheng et al. investigated the prevalence of renal disease (RD) in COVID-19 patients and the relationship between indications of impaired kidney function and death (Cheng Y., 2020). The main connections with severe disease in patients significantly impacted by COVID-19 were hypertension, diabetes, coronary artery disease, and cerebrovascular disease (Fadini GP, 2020). One-fifth to half of COVID-19 flu patients had diabetes, depending on the global territory, highlighting the association between COVID-19 and diabetes (Bornstein SR., 2020). Yang et al. discovered that one-fourth of the 32 non-survivors from a cohort of 52 COVID-19 patients had diabetes (Yang X., 2020). The presence of more than one co-morbidity and obesity among adult individuals also predict lower prognosis among COVID-19 patients (Dietz W, 2020).

Moreover, maintaining social distance, wearing musk, maintaining etiquette during sneezing, self-quarantine at home or institutional isolation are the recommended ways to manage mild or moderate cases, though there is a lack in practice of the guidelines. This study aimed to determine the pattern of COVID-19 management and prevention at hospital and home settings in urban Bangladesh. The study findings explored to what extent COVID-19 complications are related with the pattern of COVID-19 Prevention and Treatment Management.

Materials And Methods

This cross-sectional study was conducted utilizing a pre-tested semi-structured questionnaire addressing the WHO component in terms of prevention and management of Covid-19 at home and in hospitals. The study included 659 COVID-19 positive patients aged 18 and up who were treated at home or in hospitals and lived in Dhaka city From April to September 2021. Before the interview, respondents were asked to give their informed consent. Information on hospital-treated patients, 205 and 170 patients were drawn from hospitals in Dhaka North City Corporation and Dhaka South City Corporation, respectively. In the meantime, 164 patients from Dhaka North City Corporation's four wards and 120 patients from Dhaka South City Corporation's four wards were interviewed in order to obtain information on people treated at home. The list of Covid-19 positive cases was obtained from the ward counsellor's office. Data was gathered using an electronic survey on smartphones and, in some cases, face-to-face interviews, and was analyzed using SPSS-23. The study protocol was approved by the research ethics committee of the faculty of allied health sciences of Daffodil International University, Dhaka, Bangladesh.

Results

Respondents were 38.43 ± 13.90 years old on average, 60.2% of whom were female, and 46% held a bachelor's degree or higher (Table 1). The typical monthly household income was BDT 50,000, and slightly more than 42% were service holders. 4.42 ± 1.39 was the average (SD) family size. Around 10.3% of the individuals were overweight, whereas only 5.6% were underweight.

Table 1

Background characteristics of study subjects (n = 659)

Background characteristics

Number

Percent

Gender

   
 

Male

262

39.8

Female

397

60.2

Age (in years)

   
 

Up to 29

195

29.6

30–49

312

47.3

50 and above

152

23.1

Mean ± SD

38.43 ± 13.90

Level of education

   
 

Up to Secondary

168

25.5

Higher Secondary

188

28.5

Bachelor & above

303

46.0

Marital status

   
 

Single

136

20.6

Married

523

79.4

Occupation

   
 

Health service provider

154

23.4

Service

278

42.2

Business

79

12.0

Housewife

124

18.8

Student

24

3.6

Monthly family income (Bangladeshi Taka)

 
 

Up to 50000

379

57.5

> 50000

280

42.5

Mean, Median

54633, 50000

Family size

 
 

Mean ± SD

4.42 ± 1.39

BMI category

   
 

Underweight

37

5.6

Normal weight

423

64.2

Overweight

131

19.9

Obese

68

10.3

79.5% of the 659 participants had severe COVID − 19 infection, with the remaining 20.5% having a mild infection (Fig. 1). Participants were asked if they believe they are taking all possible precautions to avoid becoming infected with the Coronavirus (Fig. 2). In the mild infection group, it was discovered that 76.2% never used all preventative measures, 80% used them seldom, 76.7% used them occasionally, and 80.9% used them always to avoid COVID-19 infection. While, the corresponding figures were 23.1%, 20.0%, 23.3%, and 19.1%, respectively among the severely infected participants.

About 407 (61.8%) respondents did not suffer from any co-morbidity (Table 2). While others with co-morbidities were mostly suffered from diabetes (22.9%), cardiovascular disease (19.7%), asthma/COPD (7.9%), rheumatoid arthritis (3.8%) and CKD (1.7%).

Table 2

Co-morbid conditions by severity (n = 659, Multiple response)

Co-morbid conditions

Number

Percent

 

None

407

61.8

Diabetes

151

22.9

Cardiovascular disease

130

19.7

Asthma/COPD

52

7.9

Rheumatoid Arthritis

25

3.8

CKD

11

1.7

Others

19

2.9

More than half (353, 53.6%) of the 659 participants said they used PPE at work, and nearly three-quarters (77.6%) of them had a moderate infection. 550 (83.5%) of the respondents always wore a mask when stepping outside, and 82.4% of them had a minor infection, according to the survey. Wearing masks was found to have a statistically significant relationship with infection levels (p < 0.001). The severity level is unaffected by wearing the mask in front of family/friends or washing/changing the mask. Another crucial component for COVID-19 prevention was found to be substantially linked (p < 0.001) with infection severity. 73.3% of respondents with mild infections used soap to wash their hands, 69.2% used an alcohol-based hand rub, and 87.2% used both. The corresponding proportion of the participants who had severe infections was 26.7%, 30.8%, and 12.8%, respectively.

Table 3

Use of PPE at workplace and Mask in going outside by Severity (n = 659)

Use of PPE

Mild

Number (%)

Severe Number (%)

Total

Chi-square value

p-value

Use Personal Protective Equipment (PPE) at work place

 
 

No

250 (81.7)

56 (18.3)

306

1.674

0.196

Yes

274 (77.6)

79 (22.4)

353

Always wear a mask when going outside

 
 

Sometimes

71 (65.1)

38 (34.9)

109

16.572

0.000

Always

453 (82.4)

97 (17.6)

550

Wear a mask in front of family, friends, colleagues when outside home

 
 

No

46 (76.7)

14 (23.3)

60

0.329

0.566

Yes

478 (79.8)

121 (20.2)

599

How often mask is changed/washed

 
 

Rarely

20 (76.9)

6 (23.1)

26

0.257

0.880

Sometimes

89 (80.9)

21 (19.1)

110

Always

405 (79.3)

106 (20.7)

511

What do you used for Hand Washing

 

Soap

244 (73.3)

89 (26.7)

333

20.153

0.000

 

Alcohol-based hand Rub

18 (69.2)

8 (30.8)

26

 

Both Soap and Alcohol-based Hand Rub

253 (87.2)

37 (12.8)

290

The most common primary sign of COVID–19 infection was fever, according to reports for 533 (80.9%) respondents, followed by dry cough in case of 398 (60.4%), myalgia for 373 (56.6%), headache for 333 (50.5%), sneezing for 252 (38.2%), chest pain for 171 (25.9%), diarrhoea for 153 (23.2%) and loss of smell/taste for 142 (21.5%) respondents.

Table 4

Primary symptoms of COVID-19 infections experienced by severity (n = 659, Multiple response)

Primary symptoms

Mild Number (%)

Severe Number (%)

Total Number

 

None

58 (93.5)

4 (6.5)

62 (9.4)

Fever

416 (78.0)

117 (22.0)

533 (80.9)

Dry cough

302 (75.9)

96 (24.1)

398 (60.4)

Myalgia

286 (76.7)

87 (23.3)

373 (56.6)

Headache

263 (79.0)

70 (21.0)

333 (50.5)

Sneezing

186 (73.8)

66 (26.2)

252 (38.2)

Chest pain

110 (64.3)

61 (35.7)

171 (25.9)

Diarrhea

106 (69.3)

47 (30.7)

153 (23.2)

No smell/taste of food

117 (82.4)

25 (17.6)

142 (21.5)

Others

16 (88.9)

2 (11.1)

18 (2.7)

The researchers additionally look at the study subjects' selected characteristics of interest by treatment location in order to analyze how the general public reacts to such diseases (Table 5). It took into account age, BMI, education level, tobacco usage, co-morbidity information, physical activity, preventive measures, religion, COVID–19 severity, recovery time, post-COVID sequelae, and daily sunlight exposure. All of the examined variables were discovered to have a significant relationship with the treatment location.

Table 5

Distribution of the participants by place of treatment by characteristics of interest (n = 659)

Distribution of the participants

Place of treatment

     

Home

Home to Hospital

Hospital

Total

Number

Chi-square Test

Number (%)

Number (%)

Number (%)

Value

p-value

Age

     
 

Up to 29

101 (51.8)

63 (32.3)

31 (15.9)

195

31.956

< 0.001

30–49

132 (42.3)

113 (36.2)

67 (21.5)

312

50 & above

34 (22.4)

77 (50.7)

41 (27.0)

152

BMI Category

     
 

Underweight

14 (37.8)

12 (32.4)

11 (29.7)

37

15.720

0.015

Normal weight

167 (39.5)

152 (35.9)

104 (24.6)

423

Overweight

54 (41.2)

60 (45.8)

17 (13.0)

131

Obese

32 (47.1)

29 (42.6)

7 (10.3)

68

Level of education

     
 

Up to Secondary

61 (36.3)

80 (47.6)

27 (16.1)

168

29.785

< 0.001

Higher Secondary

62 (33.0)

64 (34.0)

62 (33.0)

188

Bachelor & above

144 (47.5)

109 (36.0)

50 (16.5)

303

Use any form of tobacco

     
 

No

227 (39.9)

209 (36.7)

133 (23.4)

569

13.673

0.001

Yes

40 (44.4)

44 (48.9)

6 (6.7)

90

Number of co-morbidities

     
 

None

197 (48.4)

156 (38.3)

54 (13.3)

407

85.848

< 0.001

One

56 (38.9)

58 (40.3)

30 (20.8)

144

At least two

10 (12.2)

28 (34.1)

44 (53.7)

82

Three or more

4 (15.4)

11 (42.3)

11 (42.3)

26

Do any form of physical exercise

     
 

No

114 (34.5)

111 (33.6)

105 (31.8)

330

45.760

< 0.001

Yes

153 (46.5)

142 (43.2)

34 (10.3)

329

Preventive Measures taken

     
 

Never

12 (57.1)

5 (23.8)

4 (19.0)

21

22.442

< 0.001

Sometimes

64 (29.1)

93 (42.3)

63 (28.6)

220

Always

191 (45.7)

155 (37.1)

72 (17.2)

418

Religiosity

     
 

Low

12 (57.1)

9 (42.9)

0(.0)

21

28.761

< 0.001

Moderate

105 (52.0)

52 (25.7)

45 (22.3)

202

High

150 (34.4)

192 (44.0)

94 (21.6)

436

Severity of COVID – 19 infection

     
 

Mild

230 (43.9)

187 (35.7)

107 (20.4)

524

12.623

0.002

Severe

37 (27.4)

66 (48.9)

32 (23.7)

135

Recovery time

     
 

Up to 14 days

184 (49.2)

136 (36.4)

54 (14.4)

374

35.168

0.000

More than 14 days

83 (29.1)

117 (41.1)

85 (29.8)

285

Post COVID-19 Complication

     
 

None

76 (39.2)

41 (21.1)

77 (39.7)

194

71.365

< 0.001

At least 1

22 (39.3)

25 (44.6)

9 (16.1)

56

At least 2

24 (32.0)

42 (56.0)

9 (12.0)

75

Three or more

145 (43.4)

145 (43.4)

44 (13.2)

334

Had 15–20 minutes of sun light every day

     
 

No

131 (39.9)

144 (43.9)

53 (16.2)

328

12.752

0.002

 

Yes

136 (41.1)

109 (32.9)

86 (26.0)

331

Age, family income, BMI, number of co-morbidities, level of education, usage of any kind of tobacco, treatment location, and post-COVID complications were all used as factors in a logistic regression (Table 6). COVID-19 Suffering is classified as having a recovery time of up to 14 days or more than 14 days. The recovery time was found to be associated with the factors of family income, number of co-morbidities, tobacco use, treatment location, and post-COVID-19 complications.

Table 6

Recovery time of Covid-19 infected patients: A logistic regression analysis.

Covariates

B

p-value

Odds Ratio (OR)

95% C.I. for OR

Lower

Upper

Age

 

.454

     
 

Up to 29

.102

.726

1.107

.627

1.954

 

30–49

.273

.265

1.313

.813

2.121

 

50 and above (rc)

         

Family income

         
 

Up to 50000 (rc)

         
 

More than 50000

.373

.047

1.453

1.005

2.099

BMI

 

.233

     
 

Normal weight (rc)

         
 

Underweight

− .762

.073

.467

.203

1.075

 

Over weight

.114

.611

1.121

.722

1.739

 

Obese

.215

.451

1.239

.709

2.165

No. of comorbidity

 

.000

     
 

None (rc)

         
 

At least one

.766

.001

2.151

1.378

3.358

 

At least two

1.139

.000

3.122

1.701

5.730

 

Three or more

.732

.112

2.080

.843

5.131

Level of education

 

.985

     
 

Up to Secondary

.042

.861

1.043

.651

1.670

 

Higher Secondary

.016

.940

1.016

.672

1.537

 

Bachelor or above (rc)

         

Use any form of tobacco

         
 

No (rc)

         
 

Yes

− .621

.021

.537

.317

.911

Place of treatment

 

.000

     
 

Home (rc)

         
 

Home to hospital

.493

.013

1.637

1.110

2.415

 

Hospital

1.274

.000

3.575

2.130

6.002

Post COVID complications

.000

     
 

None (rc)

         
 

At least one

.843

.016

2.322

1.170

4.611

 

At least two

1.555

.000

4.737

2.498

8.983

 

Three or more

.822

.000

2.275

1.441

3.592

In comparison to respondents with family income higher than 50,000 BDT, those with total family income from all sources up to 50,000 BDT were 1.45 (CI: 1.05–2.1) times more likely to have a lengthier recovery period. Respondents with one co-morbidity were found to have 2.15 (CI: 1.38–3.36) times more recovery time, while those with up to two co-morbidities were found to have 3.12 (CI: 1.70–5.73) times more recovery time. In compared to those treated at home before moving to hospital, those treated at home-to-hospital were 1.64 (CI: 1.10–2.42) times more likely to have a longer recovery time, while those treated directly at hospital were 3.58 (CI: 2.13-6.00) times more likely to have a longer recovery time. That seems to be, patients who are treated at home from the outset of their COVID-19 infection may not need to go to the hospital or, if they do, they are less likely to stay in the hospital longer than patients who go to the hospital without receiving any home treatment. In comparison to patients who recovered in less than 14 days, those with a longer recovery time are 2.28 (CI: 1.44–3.59) times more likely to experience three or more post-COVID complications, 4.74 (CI: 2.50–8.98) times more likely to experience two post-COVID complications, and 2.32 (CI: 1.17–4.61) times more likely to experience one post COVID-19 complication.

Discussion

SARS Covid-19 is said to be quite contagious. The COVID-19 epidemic has been a major shock to our societies and economies, highlighting society's reliance on humans on the front lines and at home, while also exposing systemic inequities in every domain, from health to the economy (UN WOMEN, 2021). The primary goal of this study was to assess the frequency of COVID-19 complications and their relationship to the care and preventative methods for COVID-19.

A total of 659 samples were studied, with 39.8% being male and 60.2% being female, which contradicts the male and female ratio of the Covid-19 infection report released by DGHS. Approximately one-third of the targeted male samples could not be reached due to a lack of interest or work/job outside the home during data collection. In terms of hospitalization of Covid-19 patients, this study discovered that more than half of the participants (59.5%) had been admitted to hospitals. A previous study found that 69.3% of people were isolated at home, while 27.9% and 2.8% were admitted to COVID-19 specialized hospitals and non-COVID-19 hospitals, respectively (Ali et al., 2021). The second wave of Covid-19 infection was occurring at the time of data collection for this study, which can be attributed to the reason for treating more patients in the hospital rather than at home.

According to the data, the majority of patients with co-morbidities had diabetes (22.9%), cardiovascular disease (19.7%), and asthma/COPD (7.9%). This finding is consistent with a previous study conducted in Bangladesh, which discovered that the majority of Covid-19 patients (34.6%) had diabetes as a comorbidity (Hossain et al., 2021). In contrast, hypertension (30%), diabetes (36%), and coronary heart disease (15%) were identified as the associated medical condition of Covid-19 patients in a hospital-based survey in China (Zhou et al., 2020). This indicates that non-communicable diseases vary greatly from country to country. Furthermore, people with any medical condition are susceptible to this infectious disease.

Every day, healthcare workers rely on personal protective equipment (PPE) to keep themselves and their patients safe from pathogens and contagious diseases. With the coronavirus epidemic spreading like wildfire, PPE is more important than ever. According to the current study, approximately 53.6% of respondents used PPE at work and 83.5% always wore masks when going outside. It was discovered that 77.6% and 82.4% of respondents who used PPE and masks, respectively, showed mild infection. A meta-analysis attempted to investigate the effects of face masks on virus transmission in healthcare and non-healthcare (e.g., community) settings and discovered that face masks were associated with an 82% lower risk of SARS, Middle East respiratory disease, and COVID-19 (Chu et al., 2020).

Similarly, Wang et al. recently reported on the potential role of PPE use in COVID-19 protection using a cohort of HCWs assigned to work in Wuhan (Wang et al., 2020). Using throat swab samples for SARS-CoV-2 real-time reverse transcription polymerase chain reaction (RT-PCR) and specific antibody levels evaluated with immunoglobulin M, immunoglobulin G, and immunoglobulin A by chemiluminescent kits, they discovered that none of the HCWs were infected with COVID-19 as a result of using PPE. Similarly to a previous study (Kim et al., 2021), the current study discovered a strong relationship between mask use and Covid-19 infection level. Furthermore, evidence suggests that people who have received the Covid-19 vaccine have fewer symptoms than unvaccinated people (CDC, 2021), which is consistent with the current study findings. Thus, this study demonstrates the importance of appropriate PPE, face masks, and vaccination in preventing Covid-19 infection among healthcare workers and the general population.

Covid-19 affects different people in different ways. The vast majority of infected people have mild to severe symptoms. The most common symptoms of this infectious disease, according to WHO, are fever, cough, fatigue, and loss of taste or smell (WHO, 2021b). It further states that infected persons may feel a sore throat, headaches, aches and pains, diarrhoea, skin rashes or discolouration of fingers or toes, red or irritated eyes, difficulties breathing or shortness of breath, speech or mobility loss, or dementia, as well as chest pain in extreme cases. The participants in this study exhibited nearly all of the Covid-19 symptoms listed by the World Health Organization. Fever (80.9%), dry cough (60.4%), myalgia (56.6%), headache (50.5%), sneezing (38.2%), chest pain (25.9%), and diarrhoea were among the most common symptoms reported by respondents (23.2%). During the early stages of Covid-19 infection, about 70% of respondents were treated at home by a certified physician. Antipyretics were prescribed to 86.7% of responders, antiallergics to 71.6%, antihistamines to 69.4%, antibiotics to 66.6%, vitamins to 53.5%, and oxygen therapy to 14.8%, implying that the participants were treated according to the Director General of Health Services of Bangladesh standards (DGHS 2021).

According to the findings, 60% of the participants were admitted to the hospital either directly or via home-to-hospital transportation. Antipyretic drugs were given to control fever, painkillers were given to relieve pain, oxygen was given to control respiratory distress, and saline was given to maintain proper hydration in a hospital-based study in Bangladesh (Bhuiyan et al., 2020). In addition, hydroxychloroquine and azithromycin was given to all patients to subside the associated medical conditions. The present study also showed that antipyretic (91.6%), anti-histamin (84.4%), antiallergic (83.4%), antibiotics (73.0%), vitamins (62.0%), antiviral (31.6%) and oxygen therapy (41.8%) was used for the treatment of hospitalized Covid-19 patients.

A logistic regression was performed with recovery time as the dependent variable and age, family income, BMI, number of co-morbidities, level of education, use of any form of tobacco, place of treatment, and post-COVID complications as covariates. The covariates family income, number of co-morbidities, tobacco use, place of treatment, and post-COVID complications were found to be related to recovery time. To date, no studies focusing on COVID-19 complications and their association with the pattern of COVID-19 prevention and treatment management have been conducted in Bangladesh; thus, it is presumed that the study findings will deliver as a threshold for additional studies.

Conclusion

This is, as far as we know, the first study in Bangladesh to provide data on Covid-19 management and prevention patterns. This study focused on the WHO component of Covid-19 prevention and management at home and in hospitals. A quarter of the people in the research had a mild Covid-19 infection, according to the findings. Recovery time was found to be significantly influenced by family income, the number of co-morbidities, and the location of therapy. Furthermore, age, the number of co-morbidities, and educational level were all strongly linked to the treatment location. Government needs to emphasize more on making sure effective level of management at the hospitals and extensive level of awareness at the community level.

Declarations

CONFLICT OF INTEREST: There is no conflict of interest.

DATA AVAILABILITY STATEMENT: The data of the study are available by the corresponding author upon reasonable request.

TRANSPARENCY STATEMENT: The authors affirm that this manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned (and, if relevant, registered) have been explained.

ETHICS STATEMENT: This study was approved by the ethics committee of the faculty of allied health sciences of Daffodil International University, Dhaka, Bangladesh. Importantly, informed consent was obtained for those eligible to enter the study.

References

  1. Bornstein, S. R., Rubino, F., Khunti, K., Mingrone, G., Hopkins, D., Birkenfeld, A. L., … Ludwig, B. (2020). Practical recommendations for the management of diabetes in patients with COVID-19. The lancet Diabetes & endocrinology, 8(6), 546–550.
  2. Bhuiyan, A. K. M., Sakib, N., Pakpour, A. H., Griffiths, M. D., & Mamun, M. A. (2021). COVID-19-related suicides in Bangladesh due to lockdown and economic factors: case study evidence from media reports. International journal of mental health and addiction, 19(6), 2110–2115.
  3. Centre for Disease Control and Prevention (2021). Reducing Stigma. Available from: https://www.cdc.gov/mentalhealth/stress-coping/reduce-stigma/index.html
  4. Cheng, Y., Luo, R., Wang, K., Zhang, M., Wang, Z., Dong, L., … Xu, G. (2020). Kidney disease is associated with in-hospital death of patients with COVID-19. Kidney international, 97(5), 829–838.
  5. Dietz, W., & Santos-Burgoa, C. (2020). Obesity and its implications for COVID-19 mortality. Obesity, 28(6), 1005.
  6. European Centers for Disease Control (ECDC) (2020). Using face masks in the community reducing COVID-19 transmission from potentially asymptomatic or presymptomatic people through the use of face masks ECDC Technical Report (online). Available on: https://www.ecdc.europa.eu/en/publications-data/using-face-masks-communityreducing-covid-19-transmission (accessed 8 April 2020).
  7. Fadini, P. impact of diabetes among people infected with SARS-CoV-2. J Endocrinol Invest, (43). https://doi.org/10.1007/s40618-020-01236-2.
  8. Fang, L., & Karakiulakis, G. (2020). Roth MAre patients with hypertension and diabetes mellitus at increased risk for COVID-19 infection. Lancet Respir Med, 8, e21. Available on: https://doi.org/10.1016/S2213- 2600(20)30116-8
  9. Fong, M. W., Gao, H., Wong, J. Y., Xiao, J., Shiu, E. Y., Ryu, S., & Cowling, B. J. (2020). Nonpharmaceutical measures for pandemic influenza in nonhealthcare settings—social distancing measures. Emerging infectious diseases, 26(5), 976.
  10. Guan, W. J., Ni, Z. Y., Hu, Y., Liang, W. H., Ou, C. Q., He, J. X., … Zhong, N. S. (2020). Clinical characteristics of coronavirus disease 2019 in China. New England journal of medicine, 382(18), 1708–1720.
  11. Güner, H. R., Hasanoğlu, İ., & Aktaş, F. (2020). COVID-19: Prevention and control measures in community. Turkish Journal of medical sciences, 50(9), 571–577.
  12. Ghebreyesus, T. A. World Health Organization. WHO Director-General’s opening remarks at the media briefing on COVID-19-25 May 2020.
  13. Gomes, C. (2020). Report of the WHO-China joint mission on coronavirus disease 2019 (COVID-19). Brazilian Journal of Implantology and Health Sciences, 2(3).
  14. Lin, L., Lu, L., Cao, W., & Li, T. (2020). Hypothesis for potential pathogenesis of SARS-CoV-2 infection–a review of immune changes in patients with viral pneumonia. Emerging microbes & infections, 9(1), 727–732.
  15. Nicola, M., O’Neill, N., Sohrabi, C., Khan, M., Agha, M., & Agha, R. (1920). Evidence Based Management Guideline for the COVID-19 Pandemic-Review. https://doi.org/10.1016/j.ijsu.2020.04.001
  16. Wilder-Smith, A., & Freedman, D. O. (2020). Isolation, quarantine, social distancing and community containment: pivotal role for old-style public health measures in the novel coronavirus (2019-nCoV) outbreak. Journal of travel medicine.
  17. World Health Organization. Coronavirus disease (COVID-19) pandemic: World Health Organization; 2020.
  18. World Health Organization. (2020). Mental health and psychosocial considerations during the COVID-19 outbreak, 18 March 2020 (No. WHO/2019-nCoV/MentalHealth/2020.1). World Health Organization.
  19. World Health Organization (2021). The effects of virus variants on COVID-19 vaccines. Available from: https://www.who.int/news-room/feature-stories/detail/the-effects-of-virus-variants-on-covid-19-vaccines
  20. Yang, X., Yu, Y., Xu, J., Shu, H., Liu, H., Wu, Y., … Shang, Y. (2020). Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study. The Lancet Respiratory Medicine, 8(5), 475–481. https://doi.org/10.1183/13993003.00547-2020
  21. Yang, X., Yu, Y., Xu, J., Shu, H., Liu, H., Wu, Y., … Shang, Y. (2020). Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study. The Lancet Respiratory Medicine, 8(5), 475–481.
  22. Zaki, N., & Mohamed, E. A. (2020). The estimations of the COVID-19 incubation period: a systematic review of the literature.
  23. Zhang, T., Wu, Q., & Zhang, Z. (2020). Probable pangolin origin of SARS-CoV-2 associated with the COVID-19 outbreak. Current biology, 30(7), 1346–1351.
  24. Zhang, L., Zhu, F., Xie, L., Wang, C., Wang, J., Chen, R., … Zhou, M. (2020). Clinical characteristics of COVID-19-infected cancer patients: a retrospective case study in three hospitals within Wuhan, China. Annals of oncology, 31(7), 894–901.
  25. Zhou, F., Yu, T., Du, R., Fan, G., Liu, Y., Liu, Z., … Cao, B. (2020). Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. The lancet, 395(10229), 1054–1062.
  26. Zou, L., Ruan, F., Huang, M., Liang, L., Huang, H., Hong, Z., … Wu, J. (2020). SARS-CoV-2 viral load in upper respiratory specimens of infected patients. New England journal of medicine, 382(12), 1177–1179. https://www.nejm.org/doi/10.1056/NEJMc2001737