Skip to main content
Erschienen in: BMC Infectious Diseases 1/2021

Open Access 01.12.2021 | COVID-19 | Research

Understanding the determinants of COVID-19 vaccination intention and willingness to pay: findings from a population-based survey in Bangladesh

verfasst von: Rajon Banik, Md. Saiful Islam, Mamun Ur Rashid Pranta, Quazi Maksudur Rahman, Mahmudur Rahman, Shahina Pardhan, Robin Driscoll, Sahadat Hossain, Md. Tajuddin Sikder

Erschienen in: BMC Infectious Diseases | Ausgabe 1/2021

Abstract

Background

Several coronavirus disease (COVID-19) vaccines have already been authorized and distributed in different countries all over the world, including Bangladesh. Understanding public acceptance of such a novel vaccine is vital, but little is known about the topic.

Objectives

This study aimed to investigate the determinants of intention to receive a COVID-19 vaccine and willingness to pay (WTP) among people in Bangladesh.

Methods

An anonymous and online-based survey of Bangladeshi people (mean age = 29.96 ± 9.15 years; age range = 18–60 years) was conducted using a self-reported questionnaire consisting of socio-demographics, COVID-19 experience, and vaccination-related information as well as the health belief model (HBM). Multivariable logistic regression was performed to determine the factors influencing COVID-19 vaccination intent and WTP.

Results

Of the 894 participants, 38.5% reported a definite intention to receive a COVID-19 vaccine, whereas 27% had a probable intention, and among this intent group, 42.8% wanted to get vaccinated as soon as possible. Older age, feeling optimistic about the effectiveness of COVID-19 vaccination, believing that vaccination decreases worries and risk of COVID-19 infection, and being less concerned about side effects and safety of COVID-19 vaccination under the HBM construct were found to be significant factors in COVID-19 vaccination intention. Most of the participants (72.9%) were willing to pay for a COVID-19 vaccine, with a median (interquartile range [IQR]) amount of BDT 400/US$ 4.72 (IQR; BDT 200–600/US$ 2.36–7.07) per dose. Factors associated with higher WTP were younger age, being male, having higher education, residing in an urban area, having good self-rated health status, positivity towards COVID-19 vaccination's effectiveness, and being worried about the likelihood of getting infected with COVID-19. Participants who were COVID-19 vaccination intent preferred an imported vaccine over a domestically-made vaccine (22.9% vs. 14.8%), while 28.2% preferred a routine immunization schedule.

Conclusion

The findings indicate a considerable proportion of Bangladeshi people intended to get vaccinated and had WTP for the COVID-19 vaccine. However, urgent education and awareness programs are warranted to alleviate public skepticism regarding the COVID-19 vaccination.
Begleitmaterial
Hinweise

Supplementary Information

The online version contains supplementary material available at https://​doi.​org/​10.​1186/​s12879-021-06406-y.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Abkürzungen
COVID-19
Coronavirus disease 2019
SARS-CoV-2
Severe Acute Respiratory Syndrome Coronavirus 2
WTP
Willingness to pay
HBM
Health belief model
WHO
World Health Organization
BDT
Bangladeshi Taka
US$
United States Dollar
aOR
Adjusted Odds Ratio
OR
Odds Ratio

Introduction

The coronavirus disease 2019 (COVID-19), which emerged in Wuhan, Hubei Province, China at the end of 2019, has caused a large global outbreak and has become a major public health crisis [1, 2]. COVID-19 is a highly transmittable viral infection caused by a novel strain of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) [3]. On March 11, 2020, the World Health Organization (WHO) declared the emergence of COVID-19 as a pandemic [4] which has affected more than 172 million people worldwide [5]. In Bangladesh, approximately 802,305 confirmed cases of COVID-19 were reported as of June 1, 2021, with a death toll of 12,660 [6]. This pandemic has severely affected people’s physical and psychological well-being [711], health system [12, 13] and also caused a major global economic recession [14].
Vaccines are the most effective strategy to protect the population from the devastating outcomes of COVID-19 [15, 16]. More than 287 potential vaccines are being developed and over 102 clinical trials have recently been released [16, 17]. Some have shown positive results, leading to a number of countries approving specific vaccines for implementation in vaccination programs. Meanwhile, by June 1, 2021, over 1.9 billion doses of the COVID-19 vaccine had been administered in 231 locations [18]. Bangladesh began mass vaccination on February 8, 2021 [19]. Despite considerable progress towards the vaccination program, there is some hesitancy about the COVID-19 vaccine [20]. Understanding public perception is crucial in order to achieve high vaccination coverage, especially for newly emerging infectious diseases such as COVID-19 [2123]. According to recent studies on public acceptance of COVID-19 vaccination, the intention to take the vaccine ranged from 67 to 91% across countries such as India, Saudi-Arabia, Canada, the United States, and China [2429]. There are multiple factors that may influence people’s vaccination intentions. Several demographic factors and perception of the disease risk have been found to be significantly associated with COVID-19 vaccination intent [2830]. The health belief model (HBM) is one of the most commonly used models to determine factors associated with vaccination intention [31, 32] and has been used in many previous studies [3335]. The HBM comprises several main constructs: perceived susceptibility, severity, benefits, barriers, self-efficacy to engage in a behavior, and cues to action [31]. Perceived stigma is also used for identifying determinants of vaccination intent [25]. In terms of HBM, perceived benefits (i.e. decreasing the chance of infection and making people less worried about infection) and barriers (i.e., being concerned about their efficacy) to vaccination were found to be significant in affecting vaccination intention [35, 36]. In addition, attitudes and experience regarding vaccination history, and convenience have been shown to be the major predictors of vaccination intention [29, 30].
Willingness-to-pay (WTP) refers to the maximum amount, in monetary terms, that an individual would be willing to allocate to obtain the benefits of a program [37]. The decision to vaccinate depends on the WTP of an individual in order to obtain increased health benefits [38]. HBM constructs have been used to explain WTP for influenza vaccination [34, 39]. In a previous study, the WTP for COVID-19 vaccination was found to be influenced by a variety of socioeconomic factors [36]. In addition, no-affordability barriers [35], as well as being aware of the perceived risks associated with higher WTP [38]. More evidence around public acceptance and WTP for the COVID-19 vaccine is essential to evaluate the success of vaccination programs, and to provide insights into future pricing considerations and demand forecasts.
To date, no research has been carried out in Bangladesh on people’s acceptance of the COVID-19 vaccine, the WTP, and the influencing factors and obstacles to vaccination coverage. The current study is aimed at determining the intention and WTP for a COVID-19 vaccine and other associated factors among people in Bangladesh.

Materials and methods

Study design, participants, and sampling

A cross-sectional online-based survey was carried out between 10 December 2020 and 10 January 2021. The inclusion criteria for participating were age ≥ 18 years, social media users (Facebook, WhatsApp, etc.), and currently living in Bangladesh. Incomplete surveys, individuals below 18 years old, and those who did not consent to the survey were excluded. Participants were not awarded any incentives or remuneration for taking part, and all responses were anonymous.

Study procedure

The study used an online survey tool (Google Forms) to collect data, which was advertised and disseminated across different social media platforms (Facebook, WhatsApp, etc.). Participants were asked, “Are you willing to participate in this study voluntarily?” with “yes/no” responses. If the response was positive, they were given access to the full questionnaire. Otherwise, a blank survey form was submitted automatically. The questionnaire was translated into Bangla (the native language of participants) and then translated back to English and pre-tested with 40 individuals before starting the final data collection for acceptability and clarity. A total of 1032 participants completed the online survey form where 894 participants were included in the final analysis, following quality control and manual check procedures to exclude incomplete and invalid surveys.

Sampling method

The sample size was calculated using the following equation:
$$ n=\frac{z^2 pq}{d^2};n=\frac{1.96^2\times 0.5\times \left(1-0.5\right)}{0.05^2}=384.16\approx 384 $$
Here,
n = number of samples
z = 1.96 (95% confidence level)
p = prevalence estimate (0.5)
q = (1-p)
d = precision limit or proportion of sampling error (0.05)
Assuming a 10% non-response rate, a total of 423.5 ≈ 424 sample size was estimated. However, the final sample exceeded this estimate.

Survey instruments

A self-reported semi-structured questionnaire was developed after reviewing previous studies on COVID-19 vaccine uptake [25, 29, 36]. The survey consisted of questions about (1) socio-demographic information, health status, COVID-19 experience, and vaccination-related information; (2) beliefs about COVID-19 infection and COVID-19 vaccination; (3) intention to receive the COVID-19 vaccine; (4) WTP for the COVID-19 vaccine; and (5) participant’s vaccine preference.

Socio-demographic, health status, COVID-19 experience, and vaccination-related information

Participants’ details, including age, sex, marital status, education level, monthly family income, number of children in the family, and area of residence were recorded. Participants were also asked to rate their overall health status, and whether or not they had any existing chronic diseases. Participants responded to their experience regarding COVID-19, whether or not they perceived COVID-19 vaccination as an effective way to prevent and control COVID-19 and whether or not they perceived a doctor’s recommendation as an important factor for COVID-19 vaccination decision. Information about the history of any vaccine hesitancy was also obtained.

Beliefs about COVID-19 infection and COVID-19 vaccination

Participants’ beliefs about COVID-19 infection and COVID-19 vaccination were measured using HBM [40]. The questions probed perceived stigma of COVID-19 (four items), perceived susceptibility to COVID-19 (three items), perceived severity of COVID-19 (three items), perceived benefits of COVID-19 vaccination (two items), perceived barriers to getting a vaccination against COVID-19 (five items), and cues to action (two items). All construct questions of the health belief model were measured on a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree) [35, 41]. For simplification, the responses were recoded as “agree” (strongly agree/agree) and “disagree” (strongly disagree/disagree/not sure) during the final analysis.

Intention to receive a COVID-19 vaccine and willingness to pay

Participant’s intention to receive a COVID-19 vaccine was measured by asking “If a vaccine against COVID-19 infection was available, would you be willing to take it?” Response options included “definitely not,” “probably not,” “not sure,” “probably yes,” and “definitely yes.” For our primary outcome, we dichotomized these responses into “yes” (definitely/probably yes) or “no” (all other responses). To assess the WTP for a COVID-19 vaccine, the question was “Would you be willing to pay out-of-pocket for a COVID-19 vaccine?” with “yes/no” responses. Participants who responded positively (yes) were asked “What is the maximum amount you are willing to pay for a dose of the COVID-19 vaccine?” The response options for price per dose were based on a 10-point scale and ranged from BDT 100 (≈ US$ 1.18) to BDT 1000 (≈ US$ 11.79). One United States Dollar (US$) is equivalent to 84.81 Bangladeshi Taka (BDT).

Participant’s vaccine preference

Participants were asked “How soon would you like to receive a COVID-19 vaccine when it becomes available?” with two response options: I will receive the vaccine as soon as possible” or “I will delay”. This was then followed by a question, “Which type of COVID-19 vaccine would you prefer?” with response options: “domestically-made vaccine”, “imported vaccine” or “both are acceptable”. Lastly, participants were asked "What kind of immunization schedule do you prefer for the COVID-19 vaccination?” with response options: “routine immunization”, “emergency vaccination” or “both are acceptable".

Statistical analysis

All statistical analyses were performed using IBM Statistical Package for the Social Sciences software (SPSS; version 25.0). Descriptive analyses, including frequencies, percentages, means, standard deviations, etc. were computed. Bivariate logistic regression analysis was performed on the unadjusted estimates. Variables that were significant (p < 0.05) in the bivariate logistic regression analysis were included in the adjusted multivariable logistic regression model. A p-value less than 0.05 was considered statistically significant.

Results

Socio-demographics

The sample comprised 894 survey responses. The participants’ age ranged from 18 to 60 years with a mean age of 29.96 (SD 9.15) years and approximately half of the participants were female (50.3%). About 57.2% of the participants were unmarried and 55.9% had a bachelor’s degree, 30.4% reported having a monthly family income of > 40,000 BDT and 78.3% resided in urban areas (Table 1).
Table 1
Distribution of all variables and their associations with the intention to receive a COVID-19 vaccine
Variables
Overall
N=894
Intention to receive a COVID-19 vaccine
Nob
Yesa
OR (95% CI)
p-value
aOR (95% CI)
p-value
n (%)
n (%)
n (%)
Socio-demographics
Age
  18-25 years
328 (36.7)
107 (34.7)
221 (37.7)
Reference
 
Reference
 
  26-35 years
339 (37.9)
151 (49)
188 (32.1)
0.603 (0.44-0.826)
0.002
0.735 (0.502-1.075)
0.112
  36-45 years
171 (19.1)
38 (12.3)
133 (22.7)
1.695 (1.104-2.6)
0.016
1.682 (1.032-2.742)
0.037
  > 45 years
56 (6.3)
12 (3.9)
44 (7.5)
1.775 (0.9-3.5)
0.097
2.123 (0.936-4.815)
0.072
Sex
  Male
444 (49.7)
151 (49)
293 (50)
1.04 (0.789-1.37)
0.782
  Female
450 (50.3)
157 (51)
293 (50)
Reference
   
Marital status
  Unmarried
511 (57.2)
175 (56.8)
336 (57.3)
1.016 (0.764-1.351)
0.914
  Married
357 (39.9)
121 (39.3)
236 (40.3)
0.608 (0.275-1.342)
0.218
  Divorced
26 (2.9)
12 (3.9)
14 (2.4)
Reference
   
Education level
  Bachelor
500 (55.9)
170 (55.2)
330 (56.3)
1.255 (0.913-1.723)
0.162
1.165 (0.787-1.726)
0.445
  Master's and above
152 (17)
43 (14)
109 (18.6)
1.638 (1.058-2.537)
0.027
1.539 (0.908-2.606)
0.109
  Intermediate or below
242 (27.1)
95 (30.8)
147 (25.1)
Reference
 
Reference
 
Monthly family income
  < 20000 BDT
191 (21.4)
60 (19.5)
131 (22.4)
1.269 (0.857-1.88)
0.234
  20000-30000 BDT
193 (21.6)
58 (18.8)
135 (23)
1.353 (0.912-2.007)
0.133
  30000-40000 BDT
238 (26.6)
90 (29.2)
148 (25.3)
0.956 (0.667-1.37)
0.807
  > 40000 BDT
272 (30.4)
100 (32.5)
172 (29.4)
Reference
   
Number of children in the family
  0
443 (49.6)
152 (49.4)
291 (49.7)
1.436 (1.033-1.996)
0.031
1.486 (0.989-2.234)
0.057
  1
227 (25.4)
60 (19.5)
167 (28.5)
2.087 (1.404-3.103)
<0.001
1.658 (1.046-2.627)
0.081
  ≥2
224 (25.1)
96 (31.2)
128 (21.8)
Reference
 
Reference
 
Place of residence
  Urban
700 (78.3)
238 (77.3)
462 (78.8)
1.096 (0.786-1.528)
0.589
 Rural
194 (21.7)
70 (22.7)
124 (21.2)
Reference
   
Health status, COVID-19 experience, and vaccination-related information
Self-rated health status
  Good
633 (70.8)
219 (71.1)
414 (70.6)
0.978 (0.722-1.325)
0.887
  Poor
261 (29.2)
89 (28.9)
172 (29.4)
Reference
   
History of chronic disease
  Yes
248 (27.7)
92 (29.9)
156 (26.6)
0.852 (0.628-1.156)
0.303
  No
646 (72.3)
216 (70.1)
430 (73.4)
Reference
   
Ever tested for COVID-19
  Yes
219 (24.5)
66 (21.4)
153 (26.1)
1.296 (0.933-1.8)
0.123
  No
675 (75.5)
242 (78.6)
433 (73.9)
Reference
   
Ever diagnosed with COVID-19
  Yes
167 (18.7)
56 (18.2)
111 (18.9)
1.052 (0.737-1.501)
0.782
  No
727 (81.3)
252 (81.8)
475 (81.1)
Reference
   
Family member/friend ever infected by COVID-19
  Yes
235 (26.3)
94 (30.5)
141 (24.1)
Reference
 
Reference
 
  No
659 (73.7)
214 (69.5)
445 (75.9)
1.386 (1.019-1.886)
0.037
1.21 (0.838-1.747)
0.309
Impact of COVID-19 on daily life
  Severec
353 (39.5)
102 (33.1)
251 (42.8)
1.513 (1.134-2.019)
0.005
0.914 (0.593-1.408)
0.684
  Littled
541 (60.5)
206 (66.9)
335 (57.2)
Reference
 
Reference
 
Impact of COVID-19 on studies/work
  Severec
470 (52.6)
136 (44.2)
334 (57)
1.676 (1.269-2.214)
<0.001
1.167 (0.762-1.787)
0.479
  Littled
424 (47.4)
172 (55.8)
252 (43)
Reference
 
Reference
 
Impact of COVID-19 on physical/mental health
  Severec
398 (44.5)
110 (35.7)
288 (49.1)
1.74 (1.31-2.311)
<0.001
0.968 (0.639-1.466)
0.879
  Littled
496 (55.5)
198 (64.3)
298 (50.9)
Reference
 
Reference
 
COVID-19 vaccination is an effective way to prevent and control COVID-19
  Yes
704 (78.7)
188 (61)
516 (88.1)
4.705 (3.353-6.602)
<0.001
2.709 (1.827-4.015)
<0.001
  No
190 (21.3)
120 (39)
70 (11.9)
Reference
 
Reference
 
Doctor’s recommendation is an important factor in vaccination decision-making
  Yes
797 (89.1)
253 (82.1)
544 (92.8)
2.816 (1.835-4.322)
<0.001
1.579 (0.935-2.664)
0.087
  No
97 (10.9)
55 (17.9)
42 (7.2)
Reference
 
Reference
 
Previous refusals to get any type of vaccination
  No
728 (81.4)
241 (78.2)
487 (83.1)
1.368 (0.967-1.934)
0.076
  Yes
166 (18.6)
67 (21.8)
99 (16.9)
Reference
   
Perceived stigma of COVID-19
If I had COVID-19, I would be embarrassed
  Agreee
232 (26)
63 (20.5)
169 (28.8)
1.576 (1.134-2.191)
0.007
1.117 (0.688-1.815)
0.654
  Disagreef
662 (74)
245 (79.5)
417 (71.2)
Reference
 
Reference
 
If I had COVID-19, people would think badly of me
  Agreee
230 (25.7)
63 (20.5)
167 (28.5)
1.55 (1.114-2.156)
0.009
0.695 (0.389-1.243)
0.220
  Disagreef
664 (74.3)
245 (79.5)
419 (71.5)
Reference
 
Reference
 
If I had COVID-19, people would treat me differently.
  Agreee
276 (30.9)
72 (23.4)
204 (34.8)
1.75 (1.279-2.396)
<0.001
1.561 (0.917-2.657)
0.101
  Disagreef
618 (69.1)
236 (76.6)
382 (65.2)
Reference
 
Reference
 
If I had COVID-19, I would not tell anyone
  Agreee
142 (15.9)
49 (15.9)
93 (15.9)
0.997 (0.684-1.454)
0.988
  Disagreef
752 (84.1)
259 (84.1)
493 (84.1)
Reference
   
Perceived susceptibility of contracting COVID-19
My chance of getting COVID-19 in the next few months is high
  Agreee
226 (25.3)
71 (23.1)
155 (26.5)
1.2 (0.87-1.657)
0.267
  Disagreef
668 (74.7)
237 (76.9)
431 (73.5)
Reference
   
I am worried about the likelihood of getting COVID 19
  Agreee
406 (45.4)
112 (36.4)
294 (50.2)
1.762 (1.328-2.338)
<0.001
1.643 (1.065-2.537)
0.025
  Disagreef
488 (54.6)
196 (63.6)
292 (49.8)
Reference
 
Reference
 
Getting COVID-19 is currently a possibility for me
  Agreee
297 (33.2)
93 (30.2)
204 (34.8)
1.235 (0.918-1.661)
0.164
  Disagreef
597 (66.8)
215 (69.8)
382 (65.2)
Reference
   
Perceived severity of COVID-19
Complications from COVID-19 are serious
  Agreee
412 (46.1)
120 (39)
292 (49.8)
1.556 (1.175-2.06)
0.002
0.997 (0.649-1.531)
0.987
  Disagreef
482 (53.9)
188 (61)
294 (50.2)
Reference
 
Reference
 
I will be very sick if I get infected with COVID-19
  Agreee
365 (40.8)
104 (33.8)
261 (44.5)
1.575 (1.182-2.099)
0.002
0.946 (0.606-1.478)
0.808
  Disagreef
529 (59.2)
204 (66.2)
325 (55.5)
Reference
 
Reference
 
I will be very afraid if I become infected with COVID-19
  Agreee
401 (44.9)
122 (39.6)
279 (47.6)
1.386 (1.047-1.833)
0.022
0.871 (0.555-1.366)
0.547
  Disagreef
493 (55.1)
186 (60.4)
307 (52.4)
Reference
 
Reference
 
Perceived benefits of COVID-19 vaccination
Vaccination is a good idea because I feel less worried about catching COVID-19
  Agreee
329 (36.8)
46 (14.9)
283 (48.3)
5.32 (3.738-7.57)
<0.001
2.351 (1.385-3.988)
0.002
  Disagreef
565 (63.2)
262 (85.1)
303 (51.7)
Reference
 
Reference
 
Vaccination decreases my chance of getting COVID-19 or its complications
  Agreee
378 (42.3)
59 (19.2)
319 (54.4)
5.042 (3.636-6.993)
<0.001
3.083 (1.829-5.198)
<0.001
  Disagreef
516 (57.7)
249 (80.8)
267 (45.6)
Reference
 
Reference
 
Perceived barriers of COVID-19 vaccination
I am worried about the possible side effects of COVID-19 vaccination would interfere with my usual activities
  Agreee
479 (53.6)
167 (54.2)
312 (53.2)
0.842 (0.689-1.072)
0.060
0.284 (0.216-0.561)
0.002
  Disagreef
415 (46.4)
141 (45.8)
274 (46.8)
Reference
 
Reference
 
I am concerned about the efficacy of the COVID-19 vaccination
  Agreee
470 (52.6)
164 (53.2)
306 (52.2)
0.96 (0.728-1.265)
0.770
  Disagreef
424 (47.4)
144 (46.8)
280 (47.8)
Reference
   
I am concerned about the safety of the COVID-19 vaccination
  Agreee
483 (54)
183 (59.4)
300 (51.2)
0.716 (0.542-0.947)
0.019
0.284 (0.187-0.429)
<0.001
  Disagreef
411 (46)
125 (40.6)
286 (48.8)
Reference
 
Reference
 
I am concerned about the affordability (high cost of the vaccine) of getting the COVID-19 vaccination
  Agreee
450 (50.3)
151 (49)
299 (51)
1.083 (0.822-1.427)
0.570
  Disagreef
444 (49.7)
157 (51)
287 (49)
Reference
   
I am concerned about faulty/fake COVID-19 vaccines
  Agreee
539 (60.3)
188 (61)
351 (59.9)
0.953 (0.719-1.264)
0.740
  Disagreef
355 (39.7)
120 (39)
235 (40.1)
Reference
   
Cues to action
I will only take the COVID-19 vaccine if I am given adequate information about it
  Agreee
601 (67.2)
176 (57.1)
425 (72.5)
1.98 (1.482-2.645)
<0.001
1.273 (0.787-2.058)
0.325
  Disagreef
293 (32.8)
132 (42.9)
161 (27.5)
Reference
 
Reference
 
I will only take the COVID-19 vaccine if the vaccine is taken by many in the public
  Agreee
505 (56.5)
144 (46.8)
361 (61.6)
1.827 (1.382-2.415)
<0.001
0.878 (0.571-1.35)
0.553
  Disagreef
389 (43.5)
164 (53.2)
225 (38.4)
Reference
 
Reference
 
OR Odds Ratio, CI Confidence Interval, aOR Adjusted Odds Ratios, BDT Bangladeshi Taka
aDefinitely yes/ probably yes
bDefinitely no/ probably no/ not sure
cVery severe/ severe
dVery little/ little/ fair
eStrongly agree/ agree
fStrongly disagree/ disagree/ not sure
While the majority of participants reported good health status (70.8%), 27.7% reported having chronic underlying diseases. 18.7% of participants reported having already been diagnosed with COVID-19. More than a quarter of participants (26.3%) responded that their family members had been infected with COVID-19. The majority (89.1%) of participants perceived the doctor’s recommendation as an important factor in their decision to have the COVID-19 vaccine. While 18.6% reported previous vaccine hesitancy (Table 1).

Health beliefs

The distribution of each item of the HBM is presented in Table 1. Approximately 15.9–30.9% agreed with regard to each construct-related stigma of COVID-19. With regards to the perceived susceptibility of contracting COVID-19, 74.7% of respondents disagreed that they had the possibility of contracting COVID-19 in the next few months; 45.4% were concerned about contracting COVID-19, and 33.2% thought that contracting COVID-19 was currently a possibility. Responses to questions about the perceived severity of COVID-19 demonstrate that less than half of respondents (46.1%) thought that complications of COVID-19 were serious and they would be very sick if they contracted COVID-19 (40.8%), or were afraid of contracting COVID-19 (44.9%). While the majority (78.7%) of participants perceived that vaccination was an effective way to prevent and control COVID-19, very few (36.8%) agreed that vaccination would make them feel less worried about contracting COVID-19, and vaccination would decrease their chance of contracting COVID-19 or its complications (42.3%). With regards to perceived barriers to COVID-19 vaccination, the majority of respondents (50.3–60.3%) had concerns about COVID-19 vaccination, including the impact of side-effects on usual activities (53.6%), efficacy (52.6%), safety (54%), affordability (50.3%), and validity (60.3%). In the cues to action section of the survey, over two-thirds of respondents confirmed that they would only take a vaccine if they were provided with adequate information (67.2%) and 43.5% disagreed with taking the COVID-19 vaccine if the vaccine was not taken by many in the public.

COVID-19 vaccination intent

Overall, 65.5% of participants reported a positive intention to receive a COVID-19 vaccine (38.5% definitely yes, and 27.0% probably yes); whilst 34.5% were unwilling or hesitant to be vaccinated against COVID-19 (21.5% not sure, 8.6% probably not, and 4.4% definitely not; Fig. 1). The results of bivariate and multivariable logistic regression of the intention to receive the vaccine are presented in Table 1. Bivariate analysis showed that the intention to receive the vaccine was significantly (p < 0.05) associated with being older, having higher education, having fewer children, having family members not infected with COVID-19, the severe impact of COVID-19 on participant's daily lives, studies/work and physical/mental health, positivity towards COVID-19 vaccination's effectiveness, and perceiving the doctor's recommendation as an important factor in vaccination decision making (Table 1). Multiple logistic regression, using only those variables that were significant in bivariate analysis, retained older age, positivity towards the effectiveness of COVID-19 vaccination, worries about the likelihood of being infected, believing that vaccination will safeguard against catching COVID-19 and decrease the risk of being infected with COVID-19 or its complications, and being less aware of the side-effects and safety of the COVID-19 vaccine (Table 1).

Willingness to pay (WTP)

Almost three-quarters of participants (72.9%) were willing to pay for the COVID-19 vaccine. The median (interquartile range [IQR]) WTP of the willing group was BDT400/US$ 4.72 (IQR; BDT 200–600/US$ 2.35–7.07) per dose (Fig. 2). Bivariate analysis showed that WTP was significantly (p < 0.05) associated with being young, male, being single, having higher education, urban residency, having good self-rated health status, having no chronic underlying diseases, positivity towards the effectiveness of COVID-19 vaccination, perceiving the doctor's recommendation as an important factor in vaccination decision making, being worried about the likelihood of contracting COVID 19, believing that vaccination decreases the chance of contracting COVID-19 or if infected, its complications, and perception of being vaccinated if given enough information about the COVID-19 vaccine (Table 2). Figure 2 represents the amount of money participants WTP for the COVID-19 vaccine. Multiple logistic regression, using only those variables that were significant in bivariate analysis, retained younger age, male, higher education, urban resident, having good self-rated health status, positivity towards the effectiveness of COVID-19 vaccination, and being worried about the likelihood of contracting COVID-19 (Table 2).
Table 2
Distribution of all studied variables and their associations with the willingness to pay for a COVID-19 vaccine
Variables
Willingness to pay for a COVID-19 vaccine
No
n (%)
Yes
n (%)
OR (95% CI)
p-value
aOR (95% CI)
p-value
Socio-demographics
Age
  18-25 years
111 (45.9)
217 (33.3)
1.173 (0.652-2.11)
0.594
1.148 (0.596-2.211)
0.680
  26-35 years
73 (30.2)
266 (40.8)
2.186 (1.2-3.983)
0.011
2.068 (1.072-3.99)
0.030
  36-45 years
37 (15.3)
134 (20.6)
2.173 (1.132-4.171)
0.02
1.715 (0.847-3.472)
0.134
  > 45 years
21 (8.7)
35 (5.4)
Reference
 
Reference
 
Sex
  Male
107 (44.2)
337 (51.7)
1.35 (1.003-1.816)
0.047
1.439 (1.044-1.985)
0.026
  Female
135 (55.8)
315 (48.3)
Reference
 
Reference
 
Marital status
  Unmarried
126 (52.1)
385 (59)
3.565 (1.607-7.909)
0.002
2.057 (0.847-4.993)
0.111
  Married
102 (42.1)
255 (39.1)
2.917 (1.305-6.521)
0.159
2.299 (0.953-5.545)
0.064
  Divorced
14 (5.8)
12 (1.8)
Reference
 
Reference
 
Education level
  Bachelor
112 (46.3)
388 (59.5)
2.162 (1.549-3.018)
<0.001
1.701 (1.169-2.476)
0.006
  Master's and above
37 (15.3)
115 (17.6)
1.94 (1.234-3.049)
0.004
1.414 (0.859-2.327)
0.173
  Intermediate or below
93 (38.4)
149 (22.9)
Reference
 
Reference
 
Monthly family income
  < 20000
58 (24)
133 (20.4)
0.779 (0.516-1.177)
0.236
  20000-30000
53 (21.9)
140 (21.5)
0.898 (0.591-1.363)
0.613
  30000-40000
62 (25.6)
176 (27)
0.965 (0.648-1.437)
0.86
  > 40000
69 (28.5)
203 (31.1)
Reference
   
Number of children in the family
  0
124 (51.2)
319 (48.9)
1.029 (0.72-1.47)
0.875
  1
54 (22.3)
173 (26.5)
1.281 (0.841-1.953)
0.248
  ≥2
64 (26.4)
160 (24.5)
Reference
   
Place of residence
  Urban
168 (69.4)
532 (81.6)
1.953 (1.393-2.737)
<0.001
1.687 (1.16-2.454)
0.006
  Rural
74 (30.6)
120 (18.4)
Reference
 
Reference
 
Health status, COVID-19 experience, and vaccination-related information
Self-rated health status
  Good
146 (60.3)
487 (74.7)
1.941 (1.42-2.652)
<0.001
1.713 (1.215-2.417)
0.002
  Poor
96 (39.7)
165 (25.3)
Reference
 
Reference
 
History of chronic disease
  No
162 (66.9)
484 (74.2)
1.423 (1.033-1.96)
0.031
1.187 (0.817-1.724)
0.369
  Yes
80 (33.1)
168 (25.8)
Reference
 
Reference
 
Ever tested for COVID-19
  Yes
61 (25.2)
158 (24.2)
0.949 (0.675-1.335)
0.764
  No
181 (74.8)
494 (75.8)
Reference
   
Ever diagnosed with COVID-19
  Yes
46 (19)
121 (18.6)
0.971 (0.666-1.415)
0.878
  No
196 (81)
531 (81.4)
Reference
   
Family member/friend ever infected by COVID-19
  Yes
70 (28.9)
165 (25.3)
0.833 (0.599-1.157)
0.275
  No
172 (71.1)
487 (74.7)
Reference
   
Impact of COVID-19 on daily life
  Severea
90 (37.2)
263 (40.3)
1.142 (0.842-1.548)
0.392
  Littleb
152 (62.8)
389 (59.7)
Reference
   
Impact of COVID-19 on studies/work
  Severea
122 (50.4)
348 (53.4)
1.126 (0.838-1.513)
0.431
  Littleb
120 (49.6)
304 (46.6)
Reference
   
Impact of COVID-19 on physical/mental health
  Severea
100 (41.3)
298 (45.7)
1.195 (0.887-1.611)
0.242
  Littleb
142 (58.7)
354 (54.3)
Reference
   
COVID-19 vaccination is an effective way to prevent and control COVID-19
  Yes
161 (66.5)
543 (83.3)
2.506 (1.789-3.511)
<0.001
2.172 (1.486-3.176)
<0.001
  No
81 (33.5)
109 (16.7)
Reference
   
Doctor’s recommendation is an important factor in vaccination decision-making
  Yes
200 (82.6)
597 (91.6)
2.279 (1.479-3.512)
<0.001
1.549 (0.938-2.557)
0.087
  No
42 (17.4)
55 (8.4)
Reference
 
Reference
 
Previous refusals to get any type of vaccination
  No
192 (79.3)
536 (82.2)
1.203 (0.831-1.743)
0.327
  Yes
50 (20.7)
116 (17.8)
Reference
   
Perceived stigma of COVID-19
If I had COVID-19, I would be embarrassed
  Agreec
64 (26.4)
168 (25.8)
0.965 (0.69-1.35)
0.837
  Disagreed
178 (73.6)
484 (74.2)
Reference
   
If I had COVID-19, people would think badly of me
  Agreec
66 (27.3)
164 (25.2)
0.896 (0.642-1.251)
0.520
  Disagreed
176 (72.7)
488 (74.8)
Reference
   
If I had COVID-19, people would treat me differently.
  Agreec
80 (33.1)
196 (30.1)
0.87 (0.635-1.194)
0.389
  Disagreed
162 (66.9)
456 (69.9)
Reference
   
If I had COVID-19, I would not tell anyone
  Agreec
46 (19)
96 (14.7)
0.736 (0.499-1.084)
0.120
  Disagreed
196 (81)
556 (85.3)
Reference
   
Perceived susceptibility of contracting COVID-19
My chance of getting COVID-19 in the next few months is high
  Agreec
61 (25.2)
165 (25.3)
1.005 (0.716-1.412)
0.976
  Disagreed
181 (74.8)
487 (74.7)
Reference
   
I am worried about the likelihood of getting COVID 19
  Agreec
93 (38.4)
313 (48)
1.479 (1.095-1.999)
0.011
1.403 (1.001-1.967)
0.049
  Disagreed
149 (61.6)
339 (52)
Reference
 
Reference
 
Getting COVID-19 is currently a possibility for me
  Agreec
80 (33.1)
217 (33.3)
1.01 (0.738-1.382)
0.950
  Disagreed
162 (66.9)
435 (66.7)
Reference
   
Perceived severity of COVID-19
Complications from COVID-19 are serious
  Agreec
123 (50.8)
289 (44.3)
0.77 (0.573-1.035)
0.084
  Disagreed
119 (49.2)
363 (55.7)
Reference
   
I will be very sick if I get infected with COVID-19
  Agreec
104 (43)
261 (40)
0.886 (0.657-1.194)
0.426
  Disagreed
138 (57)
391 (60)
Reference
   
I will be very afraid if I become infected with COVID-19
  Agreec
107 (44.2)
294 (45.1)
1.036 (0.77-1.394)
0.815
  Disagreed
135 (55.8)
358 (54.9)
Reference
   
Perceived benefits of COVID-19 vaccination
Vaccination is a good idea because I feel less worried about catching COVID-19
  Agreec
78 (32.2)
251 (38.5)
1.316 (0.963-1.799)
0.085
  Disagreed
164 (67.8)
401 (61.5)
Reference
   
Vaccination decreases my chance of getting COVID-19 or its complications
  Agreec
85 (35.1)
293 (44.9)
1.507 (1.11-2.047)
0.009
1.15 (0.787-1.681)
0.47
  Disagreed
157 (64.9)
359 (55.1)
Reference
 
Reference
 
Perceived barriers of COVID-19 vaccination
I am worried the possible side-effects of COVID-19 vaccination would interfere with my usual activities
  Agreec
112 (46.3)
303 (46.5)
1.008 (0.75-1.355)
0.959
  Disagreed
130 (53.7)
349 (53.5)
Reference
   
I am concerned about the efficacy of the COVID-19 vaccination
  Agreec
124 (51.2)
346 (53.1)
1.076 (0.801-1.446)
0.627
  Disagreed
118 (48.8)
306 (46.9)
Reference
   
I am concerned about the safety of the COVID-19 vaccination
  Agreec
127 (52.5)
356 (54.6)
1.089 (0.81-1.464)
0.572
  Disagreed
115 (47.5)
296 (45.4)
Reference
   
I am concerned about the affordability (high cost of the vaccine) of getting the COVID-19 vaccination
  Agreec
131 (54.1)
319 (48.9)
0.812 (0.604-1.091)
0.167
  Disagreed
111 (45.9)
333 (51.1)
Reference
   
I am concerned about faulty/fake COVID-19 vaccines
  Agreec
147 (60.7)
392 (60.1)
0.974 (0.72-1.318)
0.866
  Disagreed
95 (39.3)
260 (39.9)
Reference
   
Cues to action
I will only take the COVID-19 vaccine if I am given adequate information about it
  Agreec
148 (61.2)
453 (69.5)
1.446 (1.063-1.966)
0.019
0.954 (0.643-1.415)
0.814
  Disagreed
94 (38.8)
199 (30.5)
Reference
 
Reference
 
I will only take the COVID-19 vaccine if the vaccine is taken by many in the public
  Agreec
125 (51.7)
380 (58.3)
1.308 (0.972-1.759)
0.076
  Disagreed
117 (48.3)
272 (41.7)
Reference
   
OR Odds Ratio, CI Confidence Interval, aOR Adjusted Odds Ratios, BDT Bangladeshi Taka
aVery severe/ severe
bVery little/ little/ fair
cStrongly agree/ agree
dStrongly disagree/ disagree/ not sure

Vaccine preference

Almost four in every ten participants who were COVID-19 vaccine intet reported that they would receive the vaccine as soon as possible (42.8%); whilst 57.2% reported that they would delay. 14.8% reported a domestically-made vaccine as their preference, 22.9% preferred an imported vaccine and 62.3% had no preference. In terms of immunization schedule, 28.2% preferred routine immunization, 21.5% an emergency vaccination schedule and 50.3% had no preference (Fig. 3).

Discussion

Vaccines are a key solution to halting the escalation of pandemics such as COVID-19. The government of Bangladesh began the COVID-19 vaccination roll-out on February 8, 2021 [42]. As with any new vaccine, the COVID-19 vaccine raises concerns. The present study examined how likely people will be to take a COVID-19 vaccine and investigate whether people are willing to pay for it. Our finding represents one of the first estimates of the intention to receive the vaccine among Bangladeshi people and can be used to guide projections of future vaccine uptake and successful implementation of the COVID-19 vaccination program in Bangladesh.
In this study, the majority of participants (65.5%) reported a definite or probable intention to receive a COVID-19 vaccine, which is comparable with recent studies conducted in Saudi Arabia and the United States [25, 28]. A higher proportion of COVID-19 vaccine intention has been reported in similar studies conducted in China, India, Indonesia, and Malaysia, ranging from 83.5 to 94.3% [24, 27, 35, 36]. It may be possible that when the study was conducted, the outbreak of COVID-19 in Bangladesh was largely under control, and also there was a lack of adequate information about the vaccine. Participants in this study had a low level of perceived susceptibility to COVID-19, according to the HBM construct, which is consistent with previous studies [35, 36] and suggests that the Bangladeshi people were not aware of the possibility of the resurgence of COVID-19, making them feel less vulnerable. Our findings suggest that participants’ intention to receive a COVID-19 vaccine was dependent on various socio-demographic factors. In particular, older age was found to be a significant influential factor for the COVID-19 vaccine intention. This finding is justified by the fact that elderly people are at an increased risk of COVID-19 infection both in terms of its severity and also mortality [43]. Our findings highlight the need for education intervention focusing particularly on younger age groups. The participants’ education level was also found to be a significant factor in COVID-19 vaccine intention in the bivariate analysis, although it was not significant in the multivariate analysis. Similar results were shown in other earlier studies in Bangladesh, illustrating that individuals with a higher educational background had more knowledge and awareness regarding COVID-19 [44, 45].
The COVID-19 epidemic has had a significant impact on people all across the world, affecting work, income, and physical and mental health [4648]. The present study found that having family members who had been infected and the perception of COVID-19’s impact on daily life, studies/work, and physical/mental health were significant factors in the bivariate analysis, agreeing with a recent study among Chinese citizens [29]. Majority of the study participants agreed that vaccination is an effective way to prevent and control COVID-19, and this was a significant factor for participant’s intention to receive a vaccine, agreeing with 89.5% of Chinese residents who thought that vaccination is an effective way to prevent and control COVID-19 [29]. This positive attitude towards COVID-19 vaccination and the significant impact that it would have on their life explains the intention to receive a vaccine among people in Bangladesh. Multivariable analysis found that vaccination intention was associated with participant’s beliefs [e.g., Health Belief Model (HBM)] towards COVID-19, consistent with previous studies [34, 36, 49]. In particular, our findings suggest that perceived susceptibility to being infected with COVID-19 and the perceived benefits of and barriers to COVID-19 vaccination are the most important HBM constructs influencing participants’ intention to receive a COVID-19 vaccine. Participants with high perceived susceptibility to being infected with COVID-19 expressed increased vaccination intention, consistent with previous studies [25, 35]. While less than half of the participants (45.4%) were worried about the likelihood of contracting COVID-19, relatively few (25.3%) perceived themselves as at high risk of becoming infected. This indicates the need to increase public education and awareness about risk, in order that preventive actions can be taken to improve COVID-19 pandemic control [50].
The findings of this study also suggest participants' lower perceived benefits of COVID-19 vaccination and relatively higher perceived barriers to getting COVID-19 vaccination. In contrast, a similar study conducted in China showed high perceived benefits and low perceived barriers towards COVID-19 vaccination among the participants [36]. This may be the reason why Bangladeshi people showed a lower intention to receive a COVID-19 vaccine compared to Malaysian and Chinese people [29, 35]. Public health intervention programs that focus on increasing awareness of the benefits of COVID-19 vaccination and reducing the identified barriers are therefore essential. The multivariate analysis found concern about the safety of the COVID-19 vaccination as a significant barrier to vaccination intention, with similar findings reported in other studies related to the new vaccine [51], suggesting that information regarding the safety and efficacy standards should be made available to the general public. Another significant barrier was the worry about possible side effects of the COVID-19 vaccine. Bangladesh has experienced various negative events associated with vaccine malpractices and scandals, which have resulted in the public losing confidence in the COVID-19 vaccines [52], which may be implied in this study, as a considerable proportion of reported concerns regarding the possibility of side-effects of COVID-19 vaccines.
This study revealed that the majority of participants (72.9%) were willing to pay for a COVID-19 vaccine. This finding is comparable with a recent study in Indonesia, which found 78.3% of participants had WTP for a COVID-19 vaccine [38]. Multivariate analysis found that WTP for a vaccine was significantly influenced by socio-demographic factors such as younger age, male sex, higher education level, and residing in an urban area. Younger people reported higher WTP for a COVID-19 vaccine, consistent with a recent study in China [36]. A Malaysian study found higher education levels, professional and managerial occupations, and higher income groups were associated with higher WTP [35]. An Indonesian study found that higher income and high perceived risk among healthcare workers were associated with higher WTP [38]. Good self-rated health status and perceived effectiveness of the vaccine for prevention and control of COVID-19 were also found as significant factors for participants’ WTP for the COVID-19 vaccine. In addition, the perceived severity of the pandemic was also associated with a higher WTP. As HBM constructs were significantly associated with WTP, the HBM model should be used to inform the development of interventions to promote vaccination against COVID-19 as a priority for expenditure.
Over 40% of the participants who intended to receive a COVID-19 vaccine wanted to get vaccinated as soon as possible. Studies conducted in China and India found people’s intention to get prompt COVID-19 vaccination was 52.5 and 65.8% respectively [24, 29]. The majority of vaccine intent participants reported that both types of vaccine (domestically-made or imported) were acceptable, while the imported vaccine was more frequently preferred compared to the domestically-made (22.9% vs 14.8%) in contrast to a study in China which found that the majority of participants preferred a domestically-made vaccine over foreign-made (64.2% vs 11.9%) [36].
Our findings suggest that information about the safety and efficacy of the COVID-19 vaccines should be made public on a regular basis and timely health education and communications by public health and government sources such as healthcare professionals are critical to alleviating public concerns as well as improving confidence and compliance with the COVID-19 vaccine [23, 53].
There are some limitations to the current study that need to be considered when interpreting the results. Firstly, this study is a cross-sectional study design that cannot establish causal inferences. Secondly, the responses were based on self-reporting and may be subject to self-reporting bias and a tendency to report socially desirable responses. Thirdly, the use of an online survey and convenience sampling may result in sampling bias, so results may not apply to the wider community due to a lack of representative samples. Finally, the study was hypothetical in nature as it was conducted before the COVID-19 vaccine became available in Bangladesh, so results may now differ in practice. However, we believe that we have captured some really important information about the COVID-19 vaccine. Further research is needed to gather more data about the COVID-19 vaccine and WTP since over 9.9 million doses of the COVID-19 vaccine have been given in Bangladesh as of June 1, 2021 [18].

Conclusion

This study reflected that a sizeable proportion of Bangladeshi people intended to receive a COVID-19 vaccine. Low perceived susceptibility to being infected with COVID-19, as well as concern about side effects, and the safety of any new vaccine were identified as key factors in people's unwillingness or hesitation to receive a vaccine. Furthermore, the majority of participants had a willingness to pay for a COVID-19 vaccine. This study has important implications for facilitating public health and government authorities to design and deliver targeted intervention programs to enhance public acceptance of the COVID-19 vaccination in Bangladesh.

Acknowledgments

The authors would like to express their gratitude to all of the respondents who participated in the study voluntarily and amicably. Furthermore, the authors are also grateful to the people who supported the collection of data online and would like to thank Arfina Akhter Keya, Jannatul Mawa, Jannat Shancharika Shuchi, Sayeda Alvi Khorshed, Anab Anwar, Noyon Chandra Das, Sabiha Naznin, Rion Ahmed Sakhor, Najnin Sultana Rima, Md. Rezwan Ahmed Mahedi, Bashudeb Talukder, Fahima Chowdhury Joya, Fatema Tuz Zohra, Arpita Chakrabarty, Nishrita Devnath Smrity, Safa Akter Ruma, Kifayat Sadmam Ishadi, Adiba for their contribution in data collection.

Declarations

This study maintained ethical standards to the highest possible extent and informed consent was obtained from participants. All procedures followed the 1964 Helsinki declaration. This research was approved by the Biosafety, Biosecurity, and Ethical review board of Jahangirnagar University, Savar, Dhaka-1342, Bangladesh [BBEC, JU/ M 2021/COVID-19/3(1)]. All responses were anonymous to ensure data confidentiality. All participants provided their informed consent to participate in the study after being informed about the purpose of the study.
Not applicable.

Competing interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the publication of this research output.
Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://​creativecommons.​org/​licenses/​by/​4.​0/​. The Creative Commons Public Domain Dedication waiver (http://​creativecommons.​org/​publicdomain/​zero/​1.​0/​) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Anhänge

Supplementary Information

Literatur
31.
Zurück zum Zitat Glanz K, Barbara K, Rimer KV. Health behavior and health education: theory, research, and practice. 4th ed. San Francisco: Wiley; 2008. Glanz K, Barbara K, Rimer KV. Health behavior and health education: theory, research, and practice. 4th ed. San Francisco: Wiley; 2008.
41.
Zurück zum Zitat Al-Metwali BZ, Al-Jumaili AA, Al-Alag ZA, Sorofman B. Exploring the acceptance of COVID-19 vaccine among healthcare workers and general population using health belief model. J Eval Clin Pract. 2021:1–11. https://doi.org/10.1111/jep.13581. Al-Metwali BZ, Al-Jumaili AA, Al-Alag ZA, Sorofman B. Exploring the acceptance of COVID-19 vaccine among healthcare workers and general population using health belief model. J Eval Clin Pract. 2021:1–11. https://​doi.​org/​10.​1111/​jep.​13581.
Metadaten
Titel
Understanding the determinants of COVID-19 vaccination intention and willingness to pay: findings from a population-based survey in Bangladesh
verfasst von
Rajon Banik
Md. Saiful Islam
Mamun Ur Rashid Pranta
Quazi Maksudur Rahman
Mahmudur Rahman
Shahina Pardhan
Robin Driscoll
Sahadat Hossain
Md. Tajuddin Sikder
Publikationsdatum
01.12.2021
Verlag
BioMed Central
Schlagwort
COVID-19
Erschienen in
BMC Infectious Diseases / Ausgabe 1/2021
Elektronische ISSN: 1471-2334
DOI
https://doi.org/10.1186/s12879-021-06406-y

Weitere Artikel der Ausgabe 1/2021

BMC Infectious Diseases 1/2021 Zur Ausgabe

Leitlinien kompakt für die Innere Medizin

Mit medbee Pocketcards sicher entscheiden.

Seit 2022 gehört die medbee GmbH zum Springer Medizin Verlag

Notfall-TEP der Hüfte ist auch bei 90-Jährigen machbar

26.04.2024 Hüft-TEP Nachrichten

Ob bei einer Notfalloperation nach Schenkelhalsfraktur eine Hemiarthroplastik oder eine totale Endoprothese (TEP) eingebaut wird, sollte nicht allein vom Alter der Patientinnen und Patienten abhängen. Auch über 90-Jährige können von der TEP profitieren.

Niedriger diastolischer Blutdruck erhöht Risiko für schwere kardiovaskuläre Komplikationen

25.04.2024 Hypotonie Nachrichten

Wenn unter einer medikamentösen Hochdrucktherapie der diastolische Blutdruck in den Keller geht, steigt das Risiko für schwere kardiovaskuläre Ereignisse: Darauf deutet eine Sekundäranalyse der SPRINT-Studie hin.

Bei schweren Reaktionen auf Insektenstiche empfiehlt sich eine spezifische Immuntherapie

Insektenstiche sind bei Erwachsenen die häufigsten Auslöser einer Anaphylaxie. Einen wirksamen Schutz vor schweren anaphylaktischen Reaktionen bietet die allergenspezifische Immuntherapie. Jedoch kommt sie noch viel zu selten zum Einsatz.

Therapiestart mit Blutdrucksenkern erhöht Frakturrisiko

25.04.2024 Hypertonie Nachrichten

Beginnen ältere Männer im Pflegeheim eine Antihypertensiva-Therapie, dann ist die Frakturrate in den folgenden 30 Tagen mehr als verdoppelt. Besonders häufig stürzen Demenzkranke und Männer, die erstmals Blutdrucksenker nehmen. Dafür spricht eine Analyse unter US-Veteranen.

Update Innere Medizin

Bestellen Sie unseren Fach-Newsletter und bleiben Sie gut informiert.