Literature DB >> 35089917

Perceived COVID-19 vaccine effectiveness, acceptance, and drivers of vaccination decision-making among the general adult population: A global survey of 20 countries.

Roy Rillera Marzo1,2,3, Absar Ahmad4, Md Saiful Islam5,6, Mohammad Yasir Essar7, Petra Heidler8,9,10, Isabel King11,12, Arulmani Thiyagarajan13, Kittisak Jermsittiparsert14, Karnjana Songwathana15, Delan Ameen Younus16, Radwa Abdullah El-Abasiri17, Burcu Kucuk Bicer18, Nhat Tan Pham19,20, Titik Respati21, Susan Fitriyana22, Erwin Martinez Faller23, Aries Moralidad Baldonado24, Md Arif Billah25, Yadanar Aung26,27, Shehu Muhammad Hassan28, Muhammad Mujtaba Asad29, Kareem Ahmed El-Fass30, Sudip Bhattacharya31, Sunil Shrestha32, Nouran Ameen Elsayed Hamza33,34, Pascal Friedmann35, Michael Head36, Yulan Lin37, Siyan Yi38,39,40.   

Abstract

BACKGROUND: Mass vaccination campaigns have significantly reduced the COVID-19 burden. However, vaccine hesitancy has posed significant global concerns. The purpose of this study was to determine the characteristics that influence perceptions of COVID-19 vaccine efficacy, acceptability, hesitancy and decision making to take vaccine among general adult populations in a variety of socioeconomic and cultural contexts.
METHODS: Using a snowball sampling approach, we conducted an online cross-sectional study in 20 countries across four continents from February to May 2021.
RESULTS: A total of 10,477 participants were included in the analyses with a mean age of 36±14.3 years. The findings revealed the prevalence of perceptions towards COVID-19 vaccine's effectiveness (78.8%), acceptance (81.8%), hesitancy (47.2%), and drivers of vaccination decision-making (convenience [73.3%], health providers' advice [81.8%], and costs [57.0%]). The county-wise distribution included effectiveness (67.8-95.9%; 67.8% in Egypt to 95.9% in Malaysia), acceptance (64.7-96.0%; 64.7% in Australia to 96.0% in Malaysia), hesitancy (31.5-86.0%; 31.5% in Egypt to 86.0% in Vietnam), convenience (49.7-95.7%; 49.7% in Austria to 95.7% in Malaysia), advice (66.1-97.3%; 66.1% in Austria to 97.3% in Malaysia), and costs (16.0-91.3%; 16.0% in Vietnam to 91.3% in Malaysia). In multivariable regression analysis, several socio-demographic characteristics were identified as associated factors of outcome variables including, i) vaccine effectiveness: younger age, male, urban residence, higher education, and higher income; ii) acceptance: younger age, male, urban residence, higher education, married, and higher income; and iii) hesitancy: male, higher education, employed, unmarried, and lower income. Likewise, the factors associated with vaccination decision-making including i) convenience: younger age, urban residence, higher education, married, and lower income; ii) advice: younger age, urban residence, higher education, unemployed/student, married, and medium income; and iii) costs: younger age, higher education, unemployed/student, and lower income.
CONCLUSIONS: Most participants believed that vaccination would effectively control and prevent COVID-19, and they would take vaccinations upon availability. Determinant factors found in this study are critical and should be considered as essential elements in developing COVID-19 vaccination campaigns to boost vaccination uptake in the populations.

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Year:  2022        PMID: 35089917      PMCID: PMC8797205          DOI: 10.1371/journal.pntd.0010103

Source DB:  PubMed          Journal:  PLoS Negl Trop Dis        ISSN: 1935-2727


Introduction

The global COVID-19 pandemic has raised imminent public health threats to people across the globe. As it continues spreading, the burden of the cases has become more worrisome. As of September 4, 2021, over 219 million cases have been recorded globally [1]. The epidemic has hit low- and middle-income nations due to relatively weak health care systems in responding to such a public health emergency. The fight against COVID-19 has taken various trends in different parts of the world, with some countries bracing against the third wave of the pandemic [2-5]. South Asian countries like India have experienced colossal impacts of COVID-19, such as oxygen shortage and Delta variant that have exploded the healthcare system in the country [6,7]. Mass vaccination has started to beat the deadly pandemic, but more vaccines are required to supply the large population [8,9]. To prevent further spread, governments worldwide have adopted several prevention measures to contain the pandemic in its early days. However, lessons from the past have revealed that the best tool in preventing any viral epidemic and pandemic is safe and secure vaccines [10]. The World Health Organization (WHO) has approved several vaccines for emergency use against the COVID-19 pandemic. Mass vaccination campaigns across the globe have significantly reduced the burden of cases. However, along with the movements, adverse drug reactions of vaccines, acceptance of vaccines, and hesitancy in populations have raised severe concerns [11,12] and may pose a significant global health threat. Vaccine hesitancy is defined as an individual’s unwillingness to take the vaccines despite their availability [13]. Primary reasons for the willingness to accept vaccination include convenience, complacency, and confidence [14]. Convenience comprises the availability, affordability, and vaccines delivery in a comfortable context. Complacency underscores the low disease risk perception; thus, the need for immunization was deemed unnecessary. Confidence denotes the trust in vaccination safety, effectiveness, and healthcare systems competence [15]. The impact of vaccine hesitancy is threatening the world as it has been listed in the top ten global health threats in 2019 [16,17]. The past rises in measles cases have been linked to vaccine hesitancy as one of the known reasons [18]. To this day, vaccine hesitancy has remained a significant challenge to the world. The COVID-19 pandemic has further reignited the notion of vaccine hesitancy. The rapid vaccine development and media coverage of misinformation are among the reasons behind the rationale of hesitancy towards vaccination [11,19]. Amid the COVID-19 pandemic, the hesitancy in vaccination has taken a surge across the world. This plight has plagued many countries and slowed down the scale of vaccination coverage. To date, many studies have been conducted in different countries and populations to address these concerns [20-24]. Afghanistan, a low-income country with low vaccination coverage, has also witnessed a trend in the hesitancy towards vaccination. Nemat et al. have revealed that over 37% of the population from different provinces in Afghanistan expressed reluctance to get the COVID-19 vaccination [25]. Primary reasons for the unwillingness to get the vaccines were a perception of low vaccine quality and safety and a belief that they have sufficient immunity to combat COVID-19 [25]. A population-based survey in Nigeria during the pandemic peak indicated a high willingness to get the COVOD-19 vaccines among the general public [26]. However, 25% of the participants expressed their hesitancy [26]. The primary reasons behind the hesitancy included the perceived unreliability of clinical trials, a belief that they have strong immunity to fight against the disease, and a concern over vaccine safety [26]. These findings emphasize the need for more strategic interventions to understand the barriers better and increase vaccine acceptance across the world. However, there is a lack of multi-country population-based studies involving different socioeconomic and cultural contexts. A previous study conducted in nine lower- and middle-income countries (LIMCs) reported only COVID-19 prevalence and factors related to vaccine acceptance. Therefore, this large-scale multi-country study explored perceived COVID-19 vaccine effectiveness, acceptability, and hesitancy rates and their related factors among the general adult populations in different socioeconomic and cultural contexts. This study findings will help countries plan for better control of vaccination programs and better prepare for future pandemics.

Methods

Ethics statement

The study was designed and conducted in line with the declaration of Helsinki and was approved by the Asia Metropolitan University Ethics Committee in Malaysia (Ref. No: AMU/MREC/NF/28032020). Respondents were informed that their participation was voluntary, and written consent was implied on the completion of the questionnaire. All participants were aged 18 years or older.

Study design and sampling

An online cross-sectional study was conducted using a google form in Australia, Austria, Bangladesh, Denmark, Egypt, Germany, India, Indonesia, Iraq, Ireland, Malaysia, Myanmar, New Zealand, Nigeria, the Philippines, Scotland, Sri Lanka, Thailand, Turkey, and Vietnam. Data were collected between February 2021 and May 2021 using a snowball sampling approach.

Data collection procedures

We distributed the questionnaire using personal contacts by emails, web-based applications (e.g., WhatsApp, Telegram), and social media (e.g., Facebook, LinkedIn, Twitter, and Instagram). Participants must be aged 18 years or older. They were reminded to respond only once and use a unique identifier to create a single account by settings that allow one response per user. Finally, the confidentiality and privacy of participants’ responses were ensured to minimize potential bias caused by self-reported data. Data collected using google forms offered an excel format to survey output to analyze the raw data offline. All country’s data in excel were exported to IBM SPSS (version 25). De-identifications were done to secure the safety of respondents, which removed the identifiers like name, email ID, or mobile number that directly or indirectly point to a person.

Tool development and measures

We developed the questionnaire through participatory discussion within the research team of participating countries. The COVID-19 related questions were adapted from a previous study [27] conducted on 18 years and above. The questionnaire was completed in less than five minutes. The questionnaire was first designed in English and then translated into the participant countries native languages. It was created to alleviate responder fatigue and was face-validated by experts. Sociodemographic characteristics of the participants included age (continuous), sex (male/female), place of residence (rural/urban), education (secondary or less/post-secondary/tertiary), employment status (employed/student/unemployed), marital status (ever married/never married), and perceived family economic status (low/medium/high). Participants’ perception of vaccine effectiveness was assessed by asking whether they agreed that vaccination effectively prevents and controls COVID-19. COVID-19 vaccine acceptance was assessed by asking if the participant would like to get COVID-19 vaccines if they are successfully produced and authorized for use in the future. We also asked whether the participant agreed that convenience, health providers’ advice, and vaccine costs are important factors for deciding whether they should receive the vaccines. To measure vaccine hesitancy, participants were asked whether they would get the vaccine as soon as possible if it become available. The responses of all the questions were binary (yes/no).

Statistical analyses

For continuous variables, mean and standard deviation (SD) were calculated. Categorical variables were presented using percentages. In bivariate analyses, we used the Chi-square test to explore associations between categorical variables. Multivariable logistic regression models were constructed to explore factors associated with perceived vaccine effectiveness, acceptance, and drivers of COVID-19 vaccine uptake. The socio-demographic and economic characteristics of the participants were simultaneously included in each model. Adjusted odds ratio (AOR) with 95% confidence intervals (95% CI) were reported. Statistical significance was considered at p<0.05.

Results

A total of 11,024 participants responded to the survey including 547 incomplete responses. In the final analysis, 10,477 participants were included with a mean age 36 years (SD = 14.28). More than two-thirds (70.8%) were urban residents, 56.7% were female, 47.6% had tertiary education, 63.9% were employed, 53.5% were ever married, and 47.1% reported medium family economic status (Table 1). Thailand had the most significant number of participants (22.6%), followed by Austria (12.9%), Malaysia (12.2%), and Iraq (9.7%).
Table 1

Study sample characteristics according to residence country (n = 10,477).

AUATBDEGIDIQMYMMNGPHTHTRVNOtherTotal
Number156134735995752210211283301201313236582765117410477
Age
    <30 years22(14.1)188(14.0)259(72.1)723(75.5)329(63.0)311(30.5)964(75.1)98(32.6)102(50.7)228(72.8)791(33.4)261(31.6)395(60.7)42(24.1)4713(45.0)
    31–45 years51(32.7)500(37.1)48(13.4)186(19.4)120(23.0)327(32.0)229(17.8)174(57.8)90(44.8)57(18.2)939(39.7)140(16.9)237(36.4)75(43.1)3173(30.3)
    46–60 years42(26.9)521(38.7)36(10.0)40(4.2)63(12.1)242(23.7)71(5.5)21(7.0)7(3.5)22(7.0)579(24.5)232(28.1)19(2.9)50(28.7)1945(18.6)
    >60 years41(26.3)138(10.2)16(4.5)8(0.8)10(1.9)141(13.8)19(1.5)8(2.7)2(1.0)6(1.9)56(2.4)194(23.5)0(0.0)7(4.0)646(6.2)
Female92 (59.0)1106 (82.1)180 (50.1)598 (62.5)376 (72.0)530 (51.9)371 (28.9)176 (58.5)59 (29.4)247 (78.9)1288 (54.5)453 (54.8)340 (52.2)121 (69.5)5937 (56.7)
Urban resident94 (60.3)786 (58.4)213 (59.3)751 (78.5)310 (59.4)916 (89.7)1146 (89.3)269 (89.4)154 (76.6)166 (53.0)1602 (67.7)687 (83.1)199 (30.6)123 (70.7)7416 (70.8)
Education level
<Secondary58 (37.2)483 (35.9)33 (9.2)23 (2.4)278 (53.3)471 (46.1)67 (5.2)4 (1.3)8 (4.0)20 (6.4)492 (20.8)540 (65.3)105 (16.1)37 (21.3)2619 (25.0)
Secondary98 (62.8)169 (12.5)58 (16.2)500 (52.2)244 (46.7)424 (41.5)284 (22.1)42 (14.0)33 (16.4)0705 (29.8)0262 (40.2)51 (29.3)2870 (27.4)
>Secondary0695 (51.6)268 (74.7)434 (45.4)0126 (12.3)932 (72.6)255 (84.7)160 (79.6)293 (93.6)1168 (49.4)287 (34.7)284 (43.6)86 (49.4)4988 (47.6)
Currently employed134 (85.9)1239 (92.0)126 (35.1)682 (71.3)188 (36.0)566 (55.4)377 (29.4)261 (86.7)111 (55.2)126 (40.3)1924 (81.4)383 (46.3)433 (66.5)144 (82.8)6694 (63.9)
Ever married118 (75.6)1080 (80.2)154 (42.9)325 (34.0)269 (51.5)686 (67.2)328 (25.6)153 (50.8)95 (47.3)75 (24.0)1342 (56.7)511 (61.8)345 (53.0)124 (71.3)5605 (53.5)
Family economic status
Low27 (17.3)195 (14.5)92 (25.6)122 (12.7)286 (54.80290 (28.4)366 (28.5)44 (14.6)26 (12.9)119 (38.0)1045 (44.2)247 (29.9)137 (21.0)20 (11.5)3016 (28.8)
Medium68 (43.6)761 (56.5)138 (38.4)337 (35.2)221 (42.3)557 (54.6)831 (64.8)75 (24.9)18 (9.0)193 (61.7)905 (38.3)413 (49.9)335 (51.5)81 (46.6)4933 (47.1)
High61 (39.1)391 (29.0)129 (35.9)498 (52.0)15 (2.9)174 (17.0)86 (6.7)182 (60.5)157 (78.1)1 (0.3)415 (17.5)167 (20.2)179 (27.5)73 (42.0)2528 (24.1)

Values are the number (%) for categorical variables and mean (SD) for continuous variables. AU: Australia, AT: Austria, BD: Bangladesh, EG: Egypt, ID: Indonesia, IQ: Iraq, MY: Malaysia, MM: Myanmar, NG: Nigeria, PH: Philippines, TH: Thailand, TR: Turkey, VN: Vietnam. Other countries include Canada, China, Germany, India, Ireland, New Zeeland, Scotland, Sri-Lanka, and the United Kingdom.

Values are the number (%) for categorical variables and mean (SD) for continuous variables. AU: Australia, AT: Austria, BD: Bangladesh, EG: Egypt, ID: Indonesia, IQ: Iraq, MY: Malaysia, MM: Myanmar, NG: Nigeria, PH: Philippines, TH: Thailand, TR: Turkey, VN: Vietnam. Other countries include Canada, China, Germany, India, Ireland, New Zeeland, Scotland, Sri-Lanka, and the United Kingdom. As shown in Table 2, 78.8% of the participants agreed that vaccination would effectively control and prevent COVID-19, and 81.8% would get COVID-19 vaccines if they are successfully produced and authorized for use in the future. The participants believed that convenience (73.3%), health providers’ advice (81.8%), and costs of vaccines (57.0%) are important for people to decide whether to accept COVID-19 vaccines. About half (52.8%) expressed their hesitancy to receive the vaccines.
Table 2

Perceived effectiveness, acceptance, and drivers of COVID-19 vaccine uptake decision-making by country by socio-demographic characteristics (n = 10,477).

Socio-demographic characteristicsAgreed that vaccines are effective to prevent and control COVID-19Would accept COVID-19 vaccines when availableBelieved that convenience is important for people to decide whether to accept vaccinesBelieved that health providers’ advice is important for people to decide whether to accept vaccinesBelieved that cost of the vaccines is important for people to decide whether to accept vaccinesExpressed hesitancy to receive COVID-19 vaccines
Age group
<30 years3975 (84.3)4114 (87.3)3858 (81.9)4196 (89.0)3195 (67.8)2372 (50.3)
31 to 452392 (75.4)2505 (78.9)2109 (66.5)2441 (76.9)1587 (50.0)1680 (52.1)
46 to 601372 (70.5)1430 (73.5)1230 (63.2)1399 (71.9)881 (45.3)1064 (54.7)
60+514 (79.6)523 (81.0)479 (74.1)538 (83.3)313 (48.5)419 (64.9)
P < 0.001**P < 0.001**P < 0.001**P < 0.001**P < 0.001**P < 0.001**
Female4482 (75.5)4682 (78.9)4151 (69.9)4727 (79.6)3175 (53.5)3112 (52.4)
P < 0.001**P < 0.001**P < 0.001**P < 0.001**P < 0.001**P = 0.33
Urban residence6022 (81.2)6300 (85.0)5733 (77.3)6271 (84.6)4492 (60.6)3840 (51.8)
P < 0.001**P < 0.001**P < 0.001**P < 0.001**P < 0.001**P < 0.001**
Level of education
< Secondary1864 (71.2)1861 (71.1)1685 (64.3)1936 (73.9)1230 (47.0)1546 (59.0)
Secondary2239 (78.0)2281 (79.5)2107 (73.4)2265 (78.9)1611 (56.1)1471 (51.3)
> Secondary4150 (83.2)4430 (88.8)3884 (77.9)4373 (87.7)3135 (62.9)2518 (50.5)
P < 0.001**P < 0.001**P < 0.001**P < 0.001**P < 0.001**P < 0.001**
Currently employed5064 (75.6)5346 (79.9)4593 (68.6)5226 (78.1)3388 (50.6)3607 (53.9)
P < 0.001**P < 0.001**P < 0.001**P < 0.001**P < 0.001**P = 0.004**
Ever married4291 (76.6)4472 (79.8)3767 (67.2)4426 (79.0)2726 (48.6)3079 (54.9)
P < 0.001**P < 0.001**P < 0.001**P < 0.001**P < 0.001**P < 0.001**
Family economic status
Low2285 (75.8)2360 (78.2)2242 (74.3)2436 (80.8)1924 (63.8)1624 (53.8)
Medium3924 (79.5)4035 (81.8)3607 (73.1)4063 (82.4)2789 (56.5)2566 (52.0)
High2044 (80.9)2177 (86.1)1827 (72.3)2075 (82.1)1263 (50.0)1345 (53.2)
P < 0.001**P < 0.001**P < 0.001**P < 0.001**P < 0.001**P < 0.26
Total8253 (78.8)8572 (81.8)7676 (73.3)8574 (81.8)5976 (57.0)5535 (52.8)

** Significant at P <0.01

** Significant at P <0.01 Table 3 shows that 95.9% of the participants from Malaysia thought that vaccination would effectively prevent and control COVID-19, followed by those from the Philippines (88.8%) and Vietnam (88.3%). Countries where majority of respondents responded that they would accept COVID-19 vaccination included Malaysia (96.0%), Bangladesh (93.6%), and Iraq (91.8%). Regarding perceived drivers of vaccine uptake decision-making, 95.7% of the participants from Malaysia, 93.0% from the Philippines, and 90.8% from Bangladesh agreed that convenience is an important factor for deciding whether they would receive the vaccines. Majority of the participants from Malaysia (97.3%), the Philippines (93.9%), and Indonesia (93.5%) agreed that health providers’ advice is important in people’s decision-making to get the COVID-19 vaccines. Vaccine costs were also believed to be an important factor among the participants from Malaysia (91.3%), the Philippines (81.5%), and Turkey (78.4%). Majority of the participants from Vietnam (86.0%) and Turkey (74.7%) expressed hesitance to receive COVID-19 vaccines.
Table 3

Perceived COVID-19 vaccine effectiveness, acceptance, and determinants of the uptake decision-making by country (n = 10,477).

CountryAgreed that vaccines are effective to prevent and control COVID-19,% (95%CI)Would accept COVID-19 vaccines when available, % (95%CI)Believed that convenience is important for people to decide whether to accept vaccines, % (95%CI)Believed that health providers’ advice is important for people to decide whether to accept vaccines, % (95%CI)Believed that cost of the vaccines is important for people to decide whether to accept vaccines, % (95%CI)Expressed hesitancy to receive COVID-19 vaccines, % (95%CI)
Australia84.0 (78.0–90.0)64.7 (57.2–72.2)71.8 (64.7–78.9)78.8 (72.4–85.2)55.8 (48.0–63.5)53.2 (45.4–61.0)
Austria70.4 (67.9–72.8)71.0 (68.6–73.5)49.7 (47.0–52.3)66.1 (63.5–68.6)22.6 (20.4–24.9)65.3 (62.7–67.8)
Bangladesh83.0 (79.1–86.9)93.6 (91.0–96.1)90.8 (87.8–93.8)92.5 (89.7–95.2)73.3 (68.7–77.8)52.9 (47.8–58.1)
Egypt67.8 (64.9–70.8)80.8 (78.3–83.3)85.7 (83.5–87.9)87.0 (84.9–89.2)75.3 (72.6–78.1)31.5 (28.5–34.4)
Indonesia86.0 (83.0–89.0)68.6 (64.6–72.6)64.6 (60.4–68.7)93.5 (91.4–95.6)42.7 (38.5–47.0)68.6 (64.6–72.6)
Iraq84.4 (82.2–86.6)91.8 (90.1–93.5)79.5 (77.0–82.0)87.7 (85.6–89.7)36.0 (33.1–39.0)61.2 (58.2–64.2)
Malaysia95.9 (94.9–97.0)96.0 (95.0–97.1)95.7 (94.6–96.8)97.3 (96.5–98.2)91.3 (89.7–92.8)38.3 (35.6–41.0)
Myanmar85.0 (81.0–89.1)90.4 (87.0–93.7)86.7 (82.9–90.1)86.4 (82.5–90.2)70.4 (65.3–75.6)62.1 (56.6–67.6)
Nigeria85.1 (80.1–90.0)84.1 (79.0–89.1)88.6 (84.7–93.0)89.6 (85.3–93.8)79.6 (74.0–85.2)35.3 (28.7–41.9)
Philippines88.8 (85.3–92.3)81.5 (77.2–85.8)93.0 (90.1–95.8)93.9 (91.3–96.6)81.5 (77.2–85.8)34.2 (28.9–39.4)
Thailand68.6 (66.7–70.4)76.3 (74.6–78.0)65.5 (63.5–67.4)75.9 (74.2–77.6)58.5 (56.5–60.5)41.2 (39.2–43.2)
Turkey80.2 (77.4–82.9)81.3 (78.6–83.9)82.2 (79.6–84.8)79.7 (76.9–82.4)78.4 (75.5–81.2)74.7 (71.8–77.7)
Vietnam88.3 (85.9–90.8)89.9 (87.5–92.2)48.2 (44.4–52.1)69.3 (65.7–72.8)16.0 (13.2–18.8)86.0 (83.4–88.7)
Other69.0 (62.1–75.8)69.5 (62.7–76.4)57.5 (50.1–64.8)71.8 (65.2–78.5)43.1 (35.7–50.5)52.3 (44.9–59.7)

Other countries include Canada, China, Germany, India, Ireland, New Zeeland, Scotland, Sri-Lanka, and the United Kingdom.

Other countries include Canada, China, Germany, India, Ireland, New Zeeland, Scotland, Sri-Lanka, and the United Kingdom. As shown in Table 4, the levels of perceived COVID-19 vaccine effectiveness, acceptance, drivers of vaccine uptake decision-making, and vaccine uptake hesitancy remained significantly associated with the country of residence after controlling for socio-demographic and economic characteristics. For example, participants from Australia, Bangladesh, Indonesia, Iraq, Malaysia, Myanmar, the Philippines, Turkey, and Vietnam were significantly more likely to agree that vaccination would effectively control and prevent COVID-19 than participants from other countries. Compared to participants from other countries, participants from Bangladesh, Iraq, Malaysia, Myanmar, Thailand, Turkey, and Vietnam were significantly more likely to get the COVID-19 vaccines. Regarding hesitancy in vaccine uptake, participants from Austria, Indonesia, Iraq, Turkey, and Vietnam were significantly more likely to express their hesitancy to receive COVID-19 vaccines than participants from other countries.
Table 4

Factors related to perceived COVID-19 vaccine effectiveness, acceptance, and drivers of the uptake decision-making (n = 10477).

Agreed that vaccines are effective to prevent and control COVID-19Would accept COVID-19 vaccines when availableBelieved that convenience is important for people to decide whether to accept vaccinesBelieved that healthcare providers’ advice is important for people to decide whether to accept vaccinesBelieved that cost of the vaccines is important for people to decide whether to accept vaccinesExpressed hesitancy to receive COVID-19 vaccines
Country
Australia2.83 (1.64–4.88)**1.16 (0.72–1.86)2.12 (1.32–3.38)**2.05 (1.22–3.44)**1.93 (1.23–3.03)**1.01 (0.65–1.57)
Austria1.31 (0.92–1.85)1.30 (0.91–1.86)0.80 (0.58–1.11)0.81 (0.56–1.16)0.40 (0.28–0.56)**1.78 (1.29–2.45)**
Bangladesh1.67 (1.08–2.58)*4.81 (2.78–8.31)**5.52 (3.43–8.89)**3.02 (1.78–5.11)**2.64 (1.78–3.91)**0.98 (0.68–1.42)
Egypt0.67 (0.47–0.96)*1.34 (.92–1.95)3.27 (2.29–4.69)**2.06 (1.39–3.05)**3.37 (2.39–4.76)**0.38 (0.27–0.53)**
Indonesia3.58 (2.35–5.45)**1.47 (0.99–2.17)1.26 (0.87–1.81)6.61 (4.04–10.83)**0.65 (0.45–0.94)*2.17 (1.51–3.11)**
Iraq2.74 (1.88–3.99)**6.65 (4.42–10.02)**2.83 (2.00–4.00)**3.19 (2.15–4.73)**0.64 (0.46–0.90)**1.48 (1.06–2.06)*
Malaysia7.57 (4.88–11.74)**7.62 (4.88–11.89)**10.68 (7.04–16.19)**8.99 (5.51–14.66)**8.25 (5.69–11.97)**0.52 (0.37–0.72)**
Myanmar1.91 (1.20–3.02)**2.67 (1.60–4.45)**4.05 (2.57–6.38)**1.82 (1.13–2.93)*3.10 (2.08–4.63)**1.32 (0.90–1.94)
Nigeria1.66 (0.99–2.78)1.37 (0.82–2.30)4.69 (2.74–8.01)**2.21 (1.25–3.93)**5.09 (3.19–8.13)**0.44 (0.29–0.67)**
Philippines3.11 (1.90–5.09)**1.40 (0.89–2.21)6.77 (3.95–11.61)**3.33 (1.85–5.98)**3.35 (2.18–5.15)**0.46 (0.32–0.69)**
Thailand1.05 (0.75–1.48)1.62 (1.14–2.30)**1.26 (0.92–1.74)1.31 (0.92–1.87)1.49 (1.08–2.05)*0.58 (0.43–0.80)**
Turkey2.16 (1.48–3.17)**2.54 (1.72–3.75)**3.45 (2.40–4.96)**1.49 (1.00–2.20)*4.58 (3.21–6.55)**2.82 (1.99–3.98)**
Vietnam3.33 (2.21–5.02)**4.03 (2.64–6.17)**0.60 (0.43–0.85)**0.77 (0.52–1.13)0.19 (0.13–0.28)**5.54 (3.80–8.07)**
Other countriesRRRRRR
Age group
<30 yearsRRRRRR
31 to 45 years0.66 (0.57–0.76)**0.58 (0.50–0.68)**0.66 (0.57–0.75)**0.54 (0.46–0.63)**0.77 (0.68–0.88)**0.93 (0.82–1.04)
46 to 60 years0.61 (0.51–0.71)**0.54 (0.45–0.64)**0.66 (0.57–0.77)**0.49 (0.41–0.59)**0.71 (0.61–0.82)**0.95 (0.82–1.09)
60+ years0.82 (0.65–1.03)0.74 (0.57–0.94)*0.85 (0.68–1.06)0.86 (0.66–1.11)0.62 (0.50–0.76)**1.15 (0.94–1.40)
Sex
FemaleRRRRRR
Male1.28 (1.15–1.43)**1.16 (1.03–1.30)*1.09 (0.99–1.21)1.09 (0.97–1.22)0.99 (0.90–1.09)1.21 (1.11–1.32)**
Residential area
RuralRRRRRR
Urban1.35 (1.21–1.51)**1.40 (1.25–1.57)**1.25 (1.12–1.39)**1.17 (1.04–1.32)**1.05 (0.95–1.17)1.04 (0.95–1.15)
Education level
< SecondaryRRRRRR
Secondary1.53 (1.33–1.76)**1.42 (1.23–1.64)**1.37 (1.20–1.56)**1.08 (0.93–1.25)1.35 (1.19–1.54)**1.12 (0.99–1.27)
> Secondary1.85 (1.61–2.13)**2.68 (2.31–3.11)**1.55 (1.36–1.77)**2.31 (2.00–2.67)**1.41 (1.23–1.61)**1.18 (1.04–1.33)**
Employment status
EmployedRRRRRR
Unemployed/student1.06 (0.92–1.21)0.96 (0.83–1.11)1.00 (0.88–1.14)1.23 (1.06–1.42)**1.25 (1.10–1.40)**0.81 (0.72–0.90)**
Marital status
Ever marriedRRRRRR
Never married0.92 (0.82–1.03)0.87 (0.77–0.99)*1.14 (1.01–1.28)*0.81 (0.72–0.93)**1.05 (0.94–1.17)1.12 (1.01–1.24)*
Perceived family economic status
LowRRRRRR
Medium1.17 (1.04–1.32)*1.12 (0.99–1.27)0.93 (0.83–1.05)1.18 (1.04–1.35)*0.76 (0.68–0.85)**0.82 (0.74–0.90)**
High1.46 (1.25–1.70)**1.48 (1.25–1.75)**0.81 (0.70–0.94)**1.09 (0.93–1.28)0.47 (0.41–0.54)**0.90 (0.79–1.02)

Other countries include Canada, China, Germany, India, Ireland, New Zealand, Scotland, Sri-Lanka, and the United Kingdom. Data were presents as adjusted odds ratio (confidence interval). R: Reference

*P<0.05

**P<0.01.

Other countries include Canada, China, Germany, India, Ireland, New Zealand, Scotland, Sri-Lanka, and the United Kingdom. Data were presents as adjusted odds ratio (confidence interval). R: Reference *P<0.05 **P<0.01. The levels of perceived COVID-19 vaccine effectiveness, acceptance, drivers of vaccine uptake decision-making, and vaccine uptake hesitancy also remained significantly associated with socio-demographic and economic characteristics. For example, participants in the age groups of 31–45 years and 46–60 years were significantly less likely to agree that vaccination would effectively control and prevent COVID-19, accept the vaccines, and agree that convenience, health providers’ advice, and vaccine costs are important for deciding whether they would receive the vaccines relative to those who were 30 years or younger. Male participants were significantly more likely to agree that vaccination would effectively prevent and control COVID-19, accept the vaccines, and express their hesitancy to receive COVID-19 vaccines than female participants. Urban participants were significantly more likely to agree that vaccination would effectively prevent and control COVID-19, accept the vaccines, and agree that convenience and health providers’ advice is important for deciding whether they would receive the vaccines. Compared to participants with education lower than secondary, participants with education higher than secondary level were significantly more likely to agree that vaccination would effectively prevent and control COVID-19; accept the vaccines; agree that convenience, health providers’ advice, and vaccine costs are important for deciding whether they would receive the vaccines; and express their hesitancy to receive COVID-19 vaccines. Employed and never married participants were significantly more likely to express their hesitancy to receive COVID-19 vaccines than employed and ever married participants, respectively. Compared to low-economic families, participants from medium- and high-economic families were significantly more likely to agree that vaccination would effectively prevent and control COVID-19, vaccine acceptance, health providers’ advice is important, and less likely to agree that vaccine convenience, and costs are important for deciding whether they would receive the vaccines.

Discussion

This multi-country study assessed the prevalence and related factors of perceived effectiveness, acceptance, and potential drivers of people’s decision-making in COVID-19 vaccine uptake among a large-scale population recruited from 20 countries across four continents involving different socioeconomic and cultural contexts. We found that 78.8% of the participants agreed that vaccination would effectively control and prevent COVID-19, and 81.8% would get the vaccines if they would become available in the future. The participants believed that convenience (73.3%), health providers’ advice (81.8%), and costs of vaccines (57.0%) are important for deciding whether they would receive the vaccines. Almost half (47.2%) expressed their hesitancy to be vaccinated. Levels of perceived effectiveness ranged from 67.8% in Egypt to 95.9% in Malaysia and acceptance from 64.7% in Australia to 96.0% in Malaysia. Perceived drivers of vaccination decision-making also varied by country, ranging from 49.7% in Austria to 95.7% in Malaysia for convenience, 16.0% in Vietnam to 91.3% in Malaysia for costs of vaccines, and 31.5% in Egypt to 86.0% in Vietnam for hesitancy in vaccine uptake. The findings are comparable with other existing studies. China showed the highest level of tendency to take COVID-19 vaccines (91.3%), whereas the lowest level was found in Congo (27.7%) [28-30]. A survey conducted in nine LIMCs reported COVID-19 vaccine acceptance rates of 76.4% to 88.8% [31]. The rapid dissemination of COVID-19 related information and increased infections and deaths worldwide can explain the high rates of perceived COVID-19 vaccine effectiveness and acceptance. These evolvements may raise the consciousness and lead to positive attitudes regarding the COVID-19 vaccines. A recent study conducted in LIMCs found that COVID-19 vaccine acceptance was positively related to COVID-19 knowledge and worries and fears of the pandemic [32]. In this study, regression analyses showed that the levels of perceived COVID-19 vaccine effectiveness, acceptance, drivers of vaccine uptake decision-making, and vaccine uptake hesitancy are significantly associated with the country of residence and several other socio-demographic and economic characteristics. Individuals in the age groups of 31 to 45 and 46 to 60 were significantly less likely to agree that vaccination would successfully control and prevent COVID-19 and get the vaccine, compared to those aged 30 years or younger. They were also significantly more likely to agree that convenience, health providers’ advice, and vaccine costs are essential for deciding whether they would receive the vaccines. The existing literature also suggests that age was negatively correlated with the COVID-19 vaccine acceptance [33,34]. Similarly, youngers exhibited greater odds of COVID-19 vaccine acceptance compared to participants with older age in nine LIMCs [31]. This is conceivable because younger people are more exposed to information and engaged on online platforms such as the internet and social media. Therefore, they are more likely to stay updated on the latest information about the COVID-19 [35]. In contrast, most previous studies reported that older adults were more likely to get the COVID-19 vaccines than those in younger age groups [36-45]. A few other studies did not find significant relationships between age and COVID-19 vaccine acceptance [30,46,47]. Males had greater odds of perceived COVID-19 vaccine effectiveness and acceptance than females. Males were also more likely to agree that vaccination convenience and health providers’ advice were essential drivers of decision-making in COVID-19 vaccine uptake. These findings affirm previous studies that also reported a similar direction of association in terms of COVID-19 vaccine acceptance [30,36,37,39,40,42,44,45,47-53]. In addition, lower odds of willingness to be vaccinated were reported in females compared to males in a multi-country study conducted in nine LMICs [31]. Likewise, a previous study found an inverse association that females were more likely to express acceptance of COVID-19 vaccine than males [41]. However, multiple studies exhibited no relationships between sex and COVID-19 vaccine acceptance [33,38,43,54]. Perceived COVID-19 vaccine effectiveness and acceptance rates were higher among participants residing in urban areas than rural residents. Urbans were also significantly more likely to agree that vaccination convenience and health providers’ advice were essential drivers of decision-making in COVID-19 vaccine uptake. These findings corroborate previous studies that revealed the relationship between the increased willingness to take or accept COVID-19 vaccines among urban residents [39,42,51]. This association may be because urbans have a better COVID-19 prevention awareness than rural [55]. In contrast, another study found that participants from rural areas were more likely to express their tendency to receive COVID-19 vaccines than those in urban areas [31,33]. However, other studies did not find significant relationships [30,40,45]. Highly educated participants were more likely to perceive that COVID-19 vaccines would effectively control and prevent COVID-19 and accept them once available than those with lower education. In addition, they were more likely to believe that convenience, health providers’ advice, and vaccination costs are important drivers of people’s decision-making to receive the COVID-19 vaccines and express less hesitancy in its uptake. The findings are in line with previous studies showing that higher education is related to increased COVID-19 vaccine acceptance [33,42,56]. Similarly, another study in multiple LIMCs reported a positive relationship between education and COVID-19 vaccine acceptance [32]. Raising COVID-19 knowledge, particularly among lower-educated people, can effectively increase vaccine uptake [31]. However, this association was not detected in other studies [30,40,41,43,53,54]. Student or unemployed participants were more likely to believe that health providers’ advice and vaccination costs are important drivers of people’s decision-making to get the COVID-19 vaccines than employed participants. However, student or unemployed participants were less likely to express their hesitancy in the vaccine uptake. A study in England reported a positive association between employment and COVID-19 vaccine acceptance [46]. The relationship between education level and employment status can explain this finding. Employed people are more likely to have higher education and be aware of the COVID-19 pandemic and its prevention measures, including vaccination [57,58]. In contrast, a study in Israel found that unemployment was positively related to willingness to get COVID-19 vaccines and negatively associated with inoculation [59]. Other studies did not find relation between employment status and acceptance of COVID-19 vaccine [30,40,41,43,54]. In this study, never married respondents were more likely to believe that convenience is a crucial determinant of people’s decision-making to get the COVID-19 vaccines; whereas, ever married participants believed the healthcare workers’ advice. Never-married respondents were less likely to have vaccine acceptance, and more likely to have hesitancy in the vaccine uptake than ever-married respondents. This finding may indicate greater concern about COVID-19 among unmarried people. It may also be explained by the higher exposure to COVID-19 related information among younger groups as they tend to be more active in accessing information and social media [35]. This direction of the relation is in line with a previous study in Uganda [47] but inconsistent with other studies that reported married participants were more likely to express their intention to get the COVID-19 vaccines [30,38,54]. Some other studies did not find relation between marital status and acceptance of COVID-19 vaccine [40,53] Participants from medium- and high-economic families were significantly more likely to agree that vaccination would effectively prevent and control COVID-19than participants from low-economic families. They were less likely to agree that vaccine costs are important for deciding whether to receive the vaccines. The reduced COVID-19 vaccines acceptance rates among the low-income group may be due to scarcity of high-quality information and limited health literacy among lower-income individuals [60]. The present findings are partially supported by other studies that reported that income was positively related to the acceptance of the COVID-19 vaccines [40,42,46]. In contrast, a study in China did not find this relationship [30,40]. This multi-country survey is among a few studies exploring factors that may contribute to COVID-19 vaccine uptake improvement using extensive data collected from populations in countries with different socioeconomic and cultural contexts. However, this study has several limitations. Response biases could be one of the significant limitations because data were self-reported and collected through online platforms. The snowball technique used to recruit respondents could hamper the heterogeneity in the study sample. Another significant limitation is the study population representativeness that included a higher proportion of highly educated and urban samples more likely to access the online surveys. Moreover, the present study included the limited measures as it didn’t investigate any health literacy-related information. In conclusion, most of the general adult population in this multi-country study believed vaccination would effectively control and prevent COVID-19. They would accept the vaccines when they become available. Perceived drivers of people’s vaccination decision-making included convenience, health providers’ advice, and vaccination costs. About half had been vaccinated or would accept the vaccination when the vaccines become available, while the other half expressed their hesitancy to be vaccinated. Several economic and socio-demographic factors are related to the perceived COVID-19 vaccine effectiveness, acceptance, and hesitancy in the populations. These factors are critical and should be considered as essential elements in developing COVID-19 vaccination programs to boost the vaccine uptake in the populations.
  55 in total

Review 1.  Vaccine development for emerging infectious diseases.

Authors:  Jean-Louis Excler; Melanie Saville; Seth Berkley; Jerome H Kim
Journal:  Nat Med       Date:  2021-04-12       Impact factor: 53.440

2.  Acceptance of the coronavirus disease-2019 vaccine among medical students in Uganda.

Authors:  Andrew Marvin Kanyike; Ronald Olum; Jonathan Kajjimu; Daniel Ojilong; Gabriel Madut Akech; Dianah Rhoda Nassozi; Drake Agira; Nicholas Kisaakye Wamala; Asaph Asiimwe; Dissan Matovu; Ann Babra Nakimuli; Musilim Lyavala; Patricia Kulwenza; Joshua Kiwumulo; Felix Bongomin
Journal:  Trop Med Health       Date:  2021-05-13

3.  Willingness to Receive SARS-CoV-2 Vaccination and Associated Factors among Chinese Adults: A Cross Sectional Survey.

Authors:  Lin Gan; Yan Chen; Peipei Hu; Dawei Wu; Yajuan Zhu; Jinlin Tan; Yufen Li; Dingmei Zhang
Journal:  Int J Environ Res Public Health       Date:  2021-02-18       Impact factor: 3.390

4.  Current burden on healthcare systems in low- and middle-income countries: recommendations for emergency care of COVID-19.

Authors:  Husnain Hamid; Zubia Abid; Attiya Amir; Touseef Ur Rehman; Waqas Akram; Tooba Mehboob
Journal:  Drugs Ther Perspect       Date:  2020-08-09

5.  Knowledge, attitude, and practice regarding COVID-19 outbreak in Bangladesh: An online-based cross-sectional study.

Authors:  Most Zannatul Ferdous; Md Saiful Islam; Md Tajuddin Sikder; Abu Syed Md Mosaddek; J A Zegarra-Valdivia; David Gozal
Journal:  PLoS One       Date:  2020-10-09       Impact factor: 3.240

6.  COVID-19 Vaccine Acceptance Among Dental Professionals Based on Employment Status During the Pandemic.

Authors:  Asaf Zigron; Amiel A Dror; Nicole G Morozov; Tali Shani; Tharwat Haj Khalil; Netanel Eisenbach; Doaa Rayan; Amani Daoud; Fares Kablan; Hesham Marei; Eyal Sela; Samer Srouji
Journal:  Front Med (Lausanne)       Date:  2021-02-09

7.  Cross-sectional analysis of COVID-19 vaccine intention, perceptions and hesitancy across Latin America and the Caribbean.

Authors:  Diego Urrunaga-Pastor; Guido Bendezu-Quispe; Percy Herrera-Añazco; Angela Uyen-Cateriano; Carlos J Toro-Huamanchumo; Alfonso J Rodriguez-Morales; Adrian V Hernandez; Vicente A Benites-Zapata
Journal:  Travel Med Infect Dis       Date:  2021-04-16       Impact factor: 6.211

8.  COVID-19 vaccination intention in the UK: results from the COVID-19 vaccination acceptability study (CoVAccS), a nationally representative cross-sectional survey.

Authors:  Susan M Sherman; Louise E Smith; Julius Sim; Richard Amlôt; Megan Cutts; Hannah Dasch; G James Rubin; Nick Sevdalis
Journal:  Hum Vaccin Immunother       Date:  2020-11-26       Impact factor: 3.452

9.  COVID-19 vaccine acceptance and hesitancy in low- and middle-income countries.

Authors:  Julio S Solís Arce; Shana S Warren; Niccolò F Meriggi; Alexandra Scacco; Nina McMurry; Maarten Voors; Georgiy Syunyaev; Amyn Abdul Malik; Samya Aboutajdine; Opeyemi Adeojo; Deborah Anigo; Alex Armand; Saher Asad; Martin Atyera; Britta Augsburg; Manisha Awasthi; Gloria Eden Ayesiga; Antonella Bancalari; Martina Björkman Nyqvist; Ekaterina Borisova; Constantin Manuel Bosancianu; Magarita Rosa Cabra García; Ali Cheema; Elliott Collins; Filippo Cuccaro; Ahsan Zia Farooqi; Tatheer Fatima; Mattia Fracchia; Mery Len Galindo Soria; Andrea Guariso; Ali Hasanain; Sofía Jaramillo; Sellu Kallon; Anthony Kamwesigye; Arjun Kharel; Sarah Kreps; Madison Levine; Rebecca Littman; Mohammad Malik; Gisele Manirabaruta; Jean Léodomir Habarimana Mfura; Fatoma Momoh; Alberto Mucauque; Imamo Mussa; Jean Aime Nsabimana; Isaac Obara; María Juliana Otálora; Béchir Wendemi Ouédraogo; Touba Bakary Pare; Melina R Platas; Laura Polanco; Javaeria Ashraf Qureshi; Mariam Raheem; Vasudha Ramakrishna; Ismail Rendrá; Taimur Shah; Sarene Eyla Shaked; Jacob N Shapiro; Jakob Svensson; Ahsan Tariq; Achille Mignondo Tchibozo; Hamid Ali Tiwana; Bhartendu Trivedi; Corey Vernot; Pedro C Vicente; Laurin B Weissinger; Basit Zafar; Baobao Zhang; Dean Karlan; Michael Callen; Matthieu Teachout; Macartan Humphreys; Ahmed Mushfiq Mobarak; Saad B Omer
Journal:  Nat Med       Date:  2021-07-16       Impact factor: 87.241

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  11 in total

1.  Myth and Misinformation on COVID-19 Vaccine: The Possible Impact on Vaccination Refusal Among People of Northeast Ethiopia: A Community-Based Research.

Authors:  Mulugeta Hayelom Kalayou; Shekur Mohammed Awol
Journal:  Risk Manag Healthc Policy       Date:  2022-10-01

2.  COVID-19 Vaccination: An Exploratory Study of the Motivations and Concerns Detailed in the Medical Records of a Regional Australian Population.

Authors:  Elizabeth M Hamilton; Shannen Oversby; Angela Ratsch; Scott Kitchener
Journal:  Vaccines (Basel)       Date:  2022-04-21

3.  COVID-19 Vaccine Uptake in the Context of the First Delta Outbreak in China During the Early Summer of 2021: The Role of Geographical Distance and Vaccine Talk.

Authors:  Qionghan Zhang; Yanwei Shi; Alexander Scott English
Journal:  Risk Manag Healthc Policy       Date:  2022-06-10

Review 4.  Knowledge, Attitude and Practices Toward Coronavirus Disease (COVID- 19) in Southeast and South Asia: A Mixed Study Design Approach.

Authors:  Mohammad Meshbahur Rahman; Roy Rillera Marzo; Shanjida Chowdhury; Sikandar Ali Qalati; Mohammad Nayeem Hasan; Gowranga Kumar Paul; Khadijah Abid; Wegayehu Enbeyle Sheferaw; Angela Mariadass; Divitra Chandran; Shasvini Kanan; Ahmad Umar Shafie Bin Ahmad Firdaus; Fatimah Az Zahra' Binti Sabarin; Yulan Lin
Journal:  Front Public Health       Date:  2022-06-21

5.  COVID-19 vaccine adoption and hesitancy among older Veterans.

Authors:  Tamar Wyte-Lake; Cari Levy; Sona Hovsepian; Yvonne Mudoh; Cheryl Schmitz; Aram Dobalian
Journal:  BMC Public Health       Date:  2022-08-11       Impact factor: 4.135

6.  COVID-19 vaccine acceptance and perceived risk among pregnant and non-pregnant adults in Cameroon, Africa.

Authors:  Nuwan Gunawardhana; Kendall Baecher; Alexander Boutwell; Seraphine Pekwarake; Mirabelle Kifem; Mary Glory Ngong; Anthony Fondzeyuf; Gregory Halle-Ekane; Rahel Mbah; Pius Tih; Jodie Dionne-Odom; Denis M Tebit
Journal:  PLoS One       Date:  2022-09-13       Impact factor: 3.752

7.  COVID-19 vaccine acceptance and hesitancy among the general population of Pakistan: a population-based survey.

Authors:  Salman Muhammad Soomar; Sarmad Muhammad Soomar; Maria Khan; Ghazal Moin; Iqbal Azam
Journal:  BMJ Open       Date:  2022-09-17       Impact factor: 3.006

8.  Determinants of COVID-19 vaccine uptake among healthcare professionals and the general population in Cyprus: A web-based cross-sectional survey.

Authors:  Konstantinos Giannakou; Georgia Fakonti; Maria Kyprianidou
Journal:  J Eval Clin Pract       Date:  2022-09-17       Impact factor: 2.336

9.  Digital health literacy for COVID-19 vaccination and intention to be immunized: A cross sectional multi-country study among the general adult population.

Authors:  Roy Rillera Marzo; Tin Tin Su; Roshidi Ismail; Mila Nu Nu Htay; Mohammad Yasir Essar; Shekhar Chauhan; Mark E Patalinghug; Burcu Kucuk Bicer; Titik Respati; Susan Fitriyana; Wegdan Baniissa; Masoud Lotfizadeh; Farzana Rahman; Zahir Rayhan Salim; Edlaine Faria de Moura Villela; Kittisak Jermsittiparsert; Yadanar Aung; Nouran Ameen Elsayed Hamza; Petra Heidler; Michael G Head; Ken Brackstone; Yulan Lin
Journal:  Front Public Health       Date:  2022-09-16

10.  Adapted digital health literacy and health information seeking behavior among lower income groups in Malaysia during the COVID-19 pandemic.

Authors:  Roy Rillera Marzo; Hana W Jun Chen; Khadijah Abid; Shekhar Chauhan; Mark Mohan Kaggwa; Mohammad Yasir Essar; Jacynta Jayaram; Manah Chandra Changmai; Mohamad Khairuddin Bin Adbul Wahab; Indang Ariati Binti Ariffin; Muhammad Najib Bin Mohamad Alwi; Michael G Head; Yulan Lin
Journal:  Front Public Health       Date:  2022-09-14
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