DOI: https://doi.org/10.21203/rs.3.rs-2332537/v2
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.
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.
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.
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.
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%).
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.
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.
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.
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.
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.
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.
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.
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.