Generic selectors
Exact matches only
Search in title
Search in content
Post Type Selectors
Filter by Categories
Academy Activities- ADI Comments
Academy Activities- ADI Convocations
Academy Activities- ADI Cover story
Academy Activities- ADI International projects
Case Report
Editorial
Guest Editorial
Letter to Editor
Letter to the Editor
Opinion Corner
Opinion Piece Article
Opinion Piece Articles
Original Research Article
Policy Papers
Research Article
Review Article
Systematic Reviews and Meta-analysis
Generic selectors
Exact matches only
Search in title
Search in content
Post Type Selectors
Filter by Categories
Academy Activities- ADI Comments
Academy Activities- ADI Convocations
Academy Activities- ADI Cover story
Academy Activities- ADI International projects
Case Report
Editorial
Guest Editorial
Letter to Editor
Letter to the Editor
Opinion Corner
Opinion Piece Article
Opinion Piece Articles
Original Research Article
Policy Papers
Research Article
Review Article
Systematic Reviews and Meta-analysis
View/Download PDF

Translate this page into:

Research Article
3 (
2
); 94-100
doi:
10.25259/JGOH_29_2020

Myths regarding COVID-19 among Indian population – An online survey

Department of Conservative Dentistry and Endodontics, Hyderabad, Telangana, India.
Department of Public Health Dentistry, Government Dental College, Hyderabad, Telangana, India.
Department of Periodontics, Army College of Dental Sciences, Chennapur, Secunderabad, Telangana, India.
Department of Conservative Dentistry and Endodontics, G Pulla Reddy Dental College and Hospital, Kurnool, Andhra Pradesh, India.
Author image

*Corresponding author: V. B. P. Suryakumari, Department of Conservative Dentistry and Endodontics, Government Dental College and Hospital, Afzalgunj, Hyderabad, Telangana, India. drsuryavbp@gmail.com

Licence
This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-Share Alike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms.

How to cite this article: Reddy P, Suryakumari VBP, Yadav SS, Doshi D, Palle AR, Gopikrishna M. Myths regarding COVID-19 among Indian population – An online survey. J Global Oral Health 2020;3(2):94-100.

Abstract

Objectives:

The coronavirus disease (COVID-19) has been recognized as one of the fast spreading infectious outbreaks of the recent times. In such situations, assessing the knowledge concerning the myths of the disease is crucial. Hence, this study employs a rapid online survey methodology to check the prevalence of myths concerning COVID-19 among a convenient sample of Indian population.

Materials and Methods:

A total of 1016 respondents participated in the study. Demographic details along with the data regarding the myths of COVID-19 were collected and evaluated using 19 questions in a yes/no format. Mean score and overall mean score for the incorrect responses were calculated and compared based on demographic variables using t-test for two variables and analysis of variance (ANOVA) for three or more variables.

Results:

The mean score for myths among the study population was 7.17 + 3.27 that displayed significant difference for educational level with postgraduation degree holders having lower score (P = 0.007). Multiple logistic regression analysis indicated younger age group (18–30 years) (P = 0.01) and middle age groups (41–60 years) (P = 0.04) which were at higher odds of myths related to COVID-19 as compared to older age group (61+ years).

Conclusion:

On the whole, 44.69% of the population had high levels of myths. Such kind of population should be included as part of the disease surveillance and campaigns by the public health authorities that might facilitate to alleviate the fear and anxiety among the general population.

Keywords

COVID-19
Myths
Prevalence
Knowledge
Pandemic
General population

INTRODUCTION

Coronavirus disease (COVID-19) caused by novel coronavirus has emerged as a global pandemic in the past few months.[1] The contagious nature of this virus has led to a public health crisis, with the World Health Organization (WHO) declaring it a Public Health Emergency of International Concern on January 30, 2020.[2]

The pandemic hit India in the month of March and since then the Government of India along with health authorities is strategizing countermeasures to contain the disease and to stem the devastating effects. To begin with a nationwide lockdown was enforced from 25 of March to interrupt the chain and “flatten the curve” of COVID-19 infection. Introduction of Aarogya Setu mobile application to educate citizens about novel coronavirus facilitates them in making informed decisions amid the crisis.[3] Social media campaigns to educate public on physical distancing, hand hygiene, personal protection, etc., are some of the implementation measures undertaken by Government of India.

Facilitating outbreak management of COVID-19 urges a need to understand the public’s awareness of COVID-19. Prevention of such outbreaks largely depends on how the population accepts it and behaves that successively is influenced by what individuals apprehend and believe about the disease.[4] Since the course of this disease, its outcome, and long term effects are unclear, it has created a state of panic among the general population with social media providing easy access to information concerning this disease.

A particular concern in this regard is the spread of misinformation about COVID-19 among general population which would further add to fear and anxiety. Midst this situation, the World Health Organization (WHO) has addressed the topic, that is, “Myth Busters” on its website to avoid the spread of false information.[5]

Hence, understanding general population awareness and myths about COVID-19 may prove important for improving emergency responses, enhancing sentiment awareness and support decision-making.[6] It additionally may help the public health authorities in designing effective campaigns.

Since this disease is swiftly spreading across the globe, it calls for a rapid testing methodology to assess the populations knowledge and perception of the infection.[7] Thus, this study employs a rapid online survey methodology to assess the prevalence of myth’s concerning COVID-19 among a convenient sample of Indian population.

MATERIALS AND METHODS

Ethical clearance was obtained from the Review Board. This cross-sectional online questionnaire survey utilized a convenient sampling technique.

The sample size was determined based on a pilot survey. A minimum sample of 1003 participants was arrived at based on the pilot survey and calculation using the formula n = Z2pq/d2. Where, Z = Standard normal variate value (Z-value) = 2.58 at 99% confidence, P = Prevalence = 59.47%, q = 100–p, (i.e.) 100–59.47, d = precision = 4%.

The questionnaire gathering demographic data and the myth’s relating to COVID-19 was designed using an online survey administration app, Google Forms (Google LLC) for easy access and understanding and circulated through WhatsApp (WhatsApp Inc., USA). Participation was voluntary and informed consent was obtained through the questionnaire. People aged 18 years and above, with smartphone and WhatsApp application, ability to understand and read English , residing in the State of Telangana, India, were included for the study.

Age, gender, and educational qualifications were the demographic details recorded and the various myths relating to COVID-19 were evaluated using nineteen questions in a yes/no format. The correct response was yes for all the questions except Q2, for which the response was no.

For each incorrect response, a score of 1 was assigned. Mean score for each question and overall mean score for the incorrect responses were calculated to categorize into low and high levels of incorrect knowledge, lower score signifying lesser incorrect knowledge. Data were analyzed using SPSS software. Descriptive statistics in the form of number and percentages were calculated and compared based on demographic variables using t-test for two variables and analysis of variance (ANOVA) for three or more variables. Comparison of low level and high level of incorrect knowledge was done for demographic variables. Multiple logistic regression analysis of levels of incorrect knowledge with demographic variables was evaluated. P ≤ 0.05 was considered statistically significant.

RESULTS

A total of 1016 respondents participated in the study. Of which 50.10% (509) were female 49.9% (507), male with around 46.26% (470) belonging to the age group of 18–30 years, and the rest belonging to the other age group categories. Majority of the study population were either undergraduates (44.09%) or postgraduates (42.52%).

[Table 1] demonstrates the demographic details of the study population in number and percentage. [Table 2] illustrates the distribution of responses for every question in percentages of correct and incorrect knowledge. It was observed that only Q no. Q3, Q6, Q7, Q10, and Q19 had majority incorrect responses.

Table 1: Demographic profile of respondents.
Demographic profile No. of respondents n(%)
Age groups
18–30 years 470 (46.26)
31–40 years 210 (20.67)
41–60 years 219 (21.56)
61+ years 117 (11.52)
Gender
Male 507 (49.9)
Female 509 (50.10)
Education
High school 136 (13.39)
Undergraduate degree 448 (44.09)
Postgraduate degree 432 (42.52)
Total 1016 (100.00)
Table 2: Distribution of responses for questions.
Q. No. Questions n(%)
Correct Incorrect
Q1 People who are infected with the common flu are likely to get infected with the COVID-19? 776 (76.38) 240 (23.62)
Q2 Are those with other health problems like diabetes, hypertension more likely to acquire the COVID-19 disease than those without any other health problems? 619 (60.93) 397 (39.07)
Q3 Would it be wise not to eat food from Chinese restaurants for the next few weeks to
reduce the risk of getting infected with the COVID-19?
449 (44.19) 567 (55.81)
Q4 Do you think pregnant women can transmit the virus to the baby inside? 712 (70.08) 304 (29.92)
Q5 Do you think the virus be transmitted from mother to child through breastfeeding? 688 (67.72) 328 (32.28)
Q6 Do you think multivitamins and immunoboosters help in protecting an individual from the COVID-19 virus? 246 (24.21) 770 (75.79)
Q7 Eating garlic, turmeric, ginger, or applying oil can help prevent COVID-19 disease? 466(45.87) 550 (54.13)
Q8 Exposing yourself to sun or higher temperatures can prevent the COVID-19 disease? 631 (62.11) 385 (37.89)
Q9 Do you think COVID-19 will go away on its own in warm weather? 807 (79.43) 209 (20.57)
Q10 Cold weather can increase the chance of catching the COVID-19 virus infection easily? 290 (28.54) 726 (71.46)
Q11 Do you think taking a hot bath prevents the new COVID-19 disease? 698 (68.70) 318 (31.30)
Q12 Do you think the COVID-19 virus can be transmitted through mosquito bites and pests 972 (95.67) 44 (4.33)
Q13 Do you think spraying alcohol or chlorine all over the body can prevent or kill the COVID-19 virus? 715 (70.37) 301 (29.63)
Q14 Do you think hand dryers are effective in killing the COVID-19 virus? 822 (80.91) 194 (19.09)
Q15 Ultraviolet disinfection lamps can kill the COVID-19 virus? 661 (65.06) 355(34.94)
Q16 Are antibiotics and antiviral effective against the COVID-19 virus? 770 (75.79) 246 (24.21)
Q17 Once infected with the COVID-19 virus there are chances that you are susceptible to
lung infections throughout your life?
807(79.43) 209(20.57)
Q18 Being able to hold your breath for 10 s or more without coughing or feeling discomfort
mean you are free from the COVID-19 disease or any other lung disease.
592 (58.27) 424 (41.73)
Q19 Do you think washing your vegetables and groceries with disinfectants would
prevent the COVID-19 disease.
295 (29.04) 721 (70.96)
Except for Q2 for all other questions the correct response is yes. For Q2, correct response is no

Comparison of incorrect responses (myths) based on demographic variables is shown in [Table 3]. Age group has shown significant difference with most of the questions except Q6, Q12, and Q17, wherein no particular age group showed significant incorrect responses to all the questions. Overall, gender had a significant influence on the responses to question numbers (Q1, Q2,Q3, Q7, Q11, and Q14) with females accounting more incorrect responses to Q1 (P = 0.05) and Q3 (P = 0.04), while male population had significantly more myths for Q2, Q7, Q11, and Q14. On the other hand, educational status played a significant role for majority of the questions (Q2, Q3, Q5, Q10, Q13, Q14–16, and Q 18–19).

Table 3: Comparison of incorrect responses (myths) based on demographic variables.
Q. No. Age groups in years Gender Educational level
18–30 31–40 41–60 61+ p Male Female P-value High school Undergraduate degree Postgraduate degree P-value
Q1 126 (26.81) 51 (24.29) 44 (20.09) 19 (16.24) 0.05* 107 (21.10) 133 (26.13) 0.05 37 (27.21) 110 (24.55) 93 (21.53) 0.32
Q2 198 (42.13) 87 (41.43) 82 (37.44) 30 (25.64) 0.01* 222 (43.79) 175 (34.38) 0.002* 46 (33.82) 195 (43.53) 156 (36.11) 0.03*
Q3 259 (55.11) 119 (56.67) 122 (55.71) 67 (57.26) 0.96 267 (52.66) 300 (58.94) 0.04* 91 (66.91) 247 (55.13) 229 (53.01) 0.01*
Q4 141 (30.00) 59 (28.10) 57 (26.03) 47 (40.17) 0.05* 155 (30.57) 149 (29.27) 0.65 49 (36.03) 129 (28.79) 126 (29.17) 0.24
Q5 154 (32.77) 70 (33.33) 60 (27.40) 44 (37.61) 0.25 156 (30.77) 172 (33.79) 0.30 61 (44.85) 144 (32.14) 123 (28.47) 0.002*
Q6 349 (74.26) 165 (78.57) 162 (73.97) 94 (80.34) 0.36 384 (75.74) 386 (75.83) 0.97 107 (78.68) 349 (77.90) 314 (72.69) 0.13
Q7 209 (44.47) 128 (60.95) 130 (59.36) 83 (70.94) 0.0001* 298 (58.78) 252 (49.51) 0.003* 82 (60.29) 227 (50.67) 241 (55.79) 0.09
Q8 141 (30.00) 81 (38.57) 96 (43.84) 67 (57.26) 0.0001* 203 (40.04) 182 (35.76) 0.15 52 (38.24) 180 (40.18) 153 (35.42) 0.34
Q9 78 (16.60) 49 (23.33) 46 (21.00) 36 (30.77) 0.005* 103 (20.32) 106 (20.83) 0.84 31 (22.79) 102 (22.77) 76 (17.59) 0.13
Q10 345 (73.40) 154 (73.33) 155 (70.78) 72 (61.54) 0.07 350 (69.03) 376 (73.87) 0.08 78 (57.35) 335 (74.78) 313 (72.45) 0.0001*
Q11 118 (25.11) 68 (32.38) 86 (39.27) 46 (39.32) 0.0001* 179 (35.31) 139 (27.31) 0.006* 46 (33.82) 135 (30.13) 137 (31.71) 0.69
Q12 28 (5.96) 9 (4.29) 4 (1.83) 3 (2.56) 0.06 23 (4.54) 21 (4.13) 0.74 6 (4.41) 20 (4.46) 18 (4.17) 0.97
Q13 161 (34.26) 50 (23.81) 56 (25.57) 34 (29.06) 0.01* 157 (30.97) 144 (28.29) 0.35 56 (41.18) 136 (30.36) 109 (25.23) 0.002*
Q14 80 (17.02) 38 (18.10) 43 (19.63) 33 (28.21) 0.05* 118 (23.27) 76 (14.93) 0.001* 31 (22.79) 89 (19.87) 74 (17.13) 0.29
Q15 176 (37.45) 54 (25.71) 77 (35.16) 48 (41.03) 0.01* 182 (35.90) 173 (33.99) 0.52 66 (48.53) 154 (34.38) 135 (31.25) 0.001*
Q16 142 (30.21) 46 (21.90) 37 (16.89) 21 (17.95) 0.0001* 129 (25.44) 117 (22.99) 0.36 45 (33.09) 122 (27.23) 79 (18.29) 0.0001*
Q17 108 (22.98) 38 (18.10) 41 (18.72) 22 (18.80) 0.37 102 (20.12) 107 (21.02) 0.72 23 (16.91) 98 (21.88) 88 (20.37) 0.45
Q18 163 (34.68) 93 (44.29) 111 (50.68) 57 (48.72) 0.0001* 206 (40.63) 218 (42.83) 0.47 42 (30.88) 186 (41.52) 196 (45.37) 0.01*
Q19 346 (73.62) 137 (65.24) 143 (65.30) 95 (81.20) 0.003* 358 (70.61) 363 (71.32) 0.80 108 (79.41) 317 (70.76) 296 (68.52) 0.05*
P<0.05: Statistically significant

The mean score for myths for the entire study population was 7.17 + 3.27, which was significant for educational level with postgraduation degree holders having lower score (P = 0.007). Post hoc analysis reveals significance between high school and postgraduate educational level (P = 0.01) [Table 4].

Table 4: Comparison of demographic variables with mean knowledge scores.
Demographic variables Incorrect knowledge (myths) P-value
Mean SD
Age groups
18–30 years 7.07 3.22 0.13
31–40 years 7.12 3.21
41–60 years 7.09 3.35
61+ years 7.85 3.36
Gender
Male 7.30 3.27 0.23
Female 7.05 3.27
Educational level
High school 7.77 3.32 0.007*
Undergraduate degree 7.31 3.23
Postgraduate degree 6.84 3.26
Total mean score 7.17 3.27
P<0.05: Statistically significant

On the whole, 55.31% of the surveyed population had low levels of myths that were significant in comparison to number of people who had high levels of incorrect knowledge (P = 0.0001). On the basis of level of incorrect knowledge, none of the demographic variables revealed a significant difference [Table 5].

Table 5: Association between levels of incorrect knowledge (myths) with demographic profile.
Demographic profile Levels of incorrect knowledge n(%) Total p-value
Low level High level
Age groups
18–30 years 267 (56.81) 203 (43.19) 470 0.10
31–40 years 114 (54.29) 96 (45.71) 210
41–60 years 128 (58.45) 91 (41.55) 219
61+ years 53 (45.30) 64 (54.70) 117
Gender
Male 275 (54.24) 232 (45.76) 507 0.49
Female 287 (56.39) 222 (43.61) 509
Education
High school 67 (49.26) 69 (50.74) 136 0.14
Undergraduate degree 243 (54.24) 205 (45.76) 448
Postgraduate degree 252 (58.33) 180 (41.67) 432
Total 562 (55.31) 454 (44.69) 1016 0.0001*
P<0.05: Statistically significant

Multiple logistic regression analysis indicated that respondents with high school level of education had 1.56 higher odds of incorrect knowledge as compared to those with postgraduate degree. Younger age group (18–30 years) (P = 0.01) and middle age groups (41–60 years) (P = 0.04) were at higher odds of myths related to COVID-19 as compared to older age group (61+ years) [Table 6].

Table 6: Multiple logistic regression analysis of levels of incorrect knowledge.
Demographic profile OR 95% CI for OR P-value
Lower Upper
Age groups
18–30 years 0.59 0.39 0.90 0.01*
31–40 years 0.75 0.48 1.20 0.23
41–60 years 0.62 0.39 0.98 0.04*
61+ years Ref.
Gender
Male Ref.
Female 1.56 1.03 2.36 0.69
Education
High school 1.56 1.03 2.36 0.03*
Undergraduate degree 1.29 0.96 1.72 0.08
Postgraduate degree Ref.
P<0.05: Statistically significant

DISCUSSION

Preventive measures are the sole existing strategy to limit the spread of COVID-19 infection as there are no substantiated treatment protocols and vaccine till date.[8]

It has been established that assessing knowledge and awareness related to the varying preventive measures or myths among general population would be critical in reducing the transmission of infection which has been studied and reported within the literature.[9-11] Obtaining appropriate information at the right time about the perception of public may be the key to successful management through these perplexing times.

“Myth” is a generic term for popular beliefs, which have been proven over time to be invalid.[12] Myths are more powerful than logic to which it has always been opposed.[13] Thus, for correct understanding of an illness, it is vital to enlighten the general public concerning the frequently prevailing myths.

Our study highlights the importance of identifying the prevalence of myths concerning COVID-19 among general population that might facilitate the health regulative authorities to conduct relevant information campaigns, communication of health-care staff with the patients.

Furthermore, with a myriad of data available, it is vital to know which information to trust.

In the present study, the overall mean scores were 7.17 ± 3.27 that signify the participants who had adequate knowledge with less of myths. On the whole, 44.69% of population had high levels of incorrect knowledge and myths concerning the disease. This identifies and places them as vulnerable group, requiring adequate dissemination of knowledge and awareness relating to the facts on COVID-19 by the health authorities. To this end, Government of India has made information available in vernacular languages, with pictorial representation of messages and also adopted audio communication modes to reach out to all sectors of the society.

About 55.31% of the participants demonstrated significant low levels of myths (P = 0.0001). This could be attributed to a convenient population of sample enrolled in the study. The educational status and good knowledge regarding the high infectivity of the COVID-19 virus and its strategies of transmission might have influenced the scores obtained. This group can further be encouraged to gain better knowledge through various authentic sources of information, being helpful to educate the others within the society.

A convenient sampling technique was employed to suit the WhatsApp-based method of circulation of the questionnaire which was prepared based on the myths listed by the WHO in their website.[5]

Since the emergence of the pandemic, several myths that might have been circulated in the numerous social media platforms or through word of mouth may have influenced the general population. The most frequently believed myth is the usage of multivitamins and immunoboosters to forestall the disease. Consistent with literature our physiology needs adequate amounts of micronutrients such as Vitamins A,C, D, and E and zinc to function normally. Micronutrients are integral to immune system to ensure proper functioning of physical barriers and immune cells.[14,15]

However, higher doses of micronutrients have not been proved to boost the system function better[16] and till date there are not any evidenced treatment strategies in regard to the COVID-19 disease.

Grant et al., 2020,[17] have stated that since Vitamins D and C reduce the risk of microbial and viral infection, it was proposed to be effective in preventing and treating COVID-19.[18] However, this needs human clinical trials addressing the dosage and combinations in different population to substantiate the benefits.[15]

Ayurveda is an ancient system of medicine of Indian subcontinent. Garlic, ginger, turmeric, and oils are widely used in Ayurvedic preparations and also conjointly as home remedies in India. It is believed that they possess antimicrobial and anti-inflammatory properties. This could have been the reason for the widely prevailing myth that eating garlic, turmeric, ginger, or applying oil can help prevent COVID-19 reported in the present study. However, there is no evidence from the current outbreak that eating garlic, turmeric, and ginger have protected people from COVID-19.[5,16]

Racial/ethnic variations in chronic disease morbidity and mortality are well documented.[19,20] The fact that COVID-19 originated from China could be the reason for general public to believe that eating food from Chinese restaurants would increase the risk of getting infected with the virus. This signifies lack of information relating to the disease transmission. Since there is no evidence that the COVID-19 virus is confined to a specific group this can be considered a myth.

The previous studies have shown the importance of weather variables within the transmission of infectious diseases, such as influenza and severe acute respiratory syndrome (SARS). A sharp change of ambient temperature was associated with increased risk of SARS[21,22] and influenza transmission is usually increased in the presence of cold and/or dry air.[23] However, it has been proven that COVID-19 virus can sustain high temperature and UV radiation.[24]

Similarly, cold weather and snow cannot kill or spread the virus and exposing to sun or higher temperatures also does not prevent nor cure COVID-19. The fact that normal human body temperature remains around 36.5°C and 37°C regardless of the external temperature or weather confirms the fact that spread of disease is independent of weather conditions.[5]

Finally, the study population believed that washing vegetables and groceries with disinfectants would forestall the COVID-19 disease which lacks any documented evidence. According to the WHO, the vegetables ought to be washed meticulously in any circumstances practicing hand hygiene before and after handling vegetables.[5]

In the present study, multiple logistic regression analysis indicated that respondents with high school level of education had 1.56 higher odds of incorrect knowledge as compared to those with postgraduate degree. This attributed to the intense scenario of the pandemic compelling them to actively acquire knowledge of this infectious disease from various channels of information such as televisions, official website of the WHO, and Centre for disease Control. The significant positive association between levels of education and lower incorrect knowledge scores supports this speculation.[25]

Younger age group (18–30 years) (P = 0.01) and middle age groups (41–60 years) (P = 0.04) were at higher odds of myths related to COVID-19 as compared to older age group (61+ years). As stated in the literature, this could be attributed to better understanding and sensible knowledge of the circumstances.[25-27]

The limitations of the present study embody the convenient sampling technique, as opposed to random sampling, may not avoid subjective selection bias and thus diminish the internal validity. The cross-sectional nature of the study design fails to establish cause-effect association highlighting the necessity for a longitudinal study. Smartphone-based application and English language are some of the short comings of the study because of which vulnerable populations of the Indian society under the COVID-19 pandemic such as older adults and rural people at grassroot could not be included within the study. A standardized questionnaire was not employed in the study.

CONCLUSION

The findings of this study suggest that the health authorities need to focus on the vulnerable population who have shown high levels of incorrect knowledge this might most likely ensue to restricted access to internet and online health information resources. Hence, the authorities and health-care employees need to target such population and provide them with the correct information which might facilitate in prevention and transmission of the disease.

Declaration of patient consent

The authors certify that they have obtained all appropriate patient consent.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

References

  1. . Rolling Updates on Corona Virus COVID-10. Available from: https://www.who.int/emergencies/diseases/novel-coronavirus-2019/events-as-theyhappen [Last accessed on 2020 Apr 25]
    [Google Scholar]
  2. . 2019-nCoV Outbreak is an Emergency of International Concern. . Available from: http://www.euro.who.int/en/healthtopics/emergencies/pages/news/news/2020/01/2019-ncov-outbreak-is-an-emergency-of-international-concern [Last accessed on 2020 Feb 16]
    [Google Scholar]
  3. . Over the Past Week, the Refrain in Government Circles Has Changed from Flattening the Curve to Learning to Live with the Virus. New Delhi: IST R Sukumar Hindustan Times; . Available from: https://www.hindustantimes.com/india-news/covid-19-what-you-need-to-know-today/story [Last accessed on 2020 May 14]
    [Google Scholar]
  4. , . The health belief model: A decade later. Health Educ Q. 1984;11:1-47.
    [CrossRef] [PubMed] [Google Scholar]
  5. . Coronavirus Disease (COVID-19) Advice for the Public: Myth Busters. Available from: https://www.who.int/emergencies/diseases/novel-coronavirus-2019/advice-for-public/myth-busters [Last accessed on 2020 Mar 30]
    [Google Scholar]
  6. . Use of rapid online surveys to assess people's perceptions during infectious disease outbreaks: A cross-sectional survey on COVID-19. J Med Internet Res. 2020;22:e18790.
    [CrossRef] [PubMed] [Google Scholar]
  7. , , . An interactive web-based dashboard to track COVID-19 in real time. Lancet Infect Dis. 2020;20:533-4.
    [CrossRef] [Google Scholar]
  8. , , . Features, Evaluation and Treatment Coronavirus (COVID-19)) Treasure Island, FL: StatPearls Publishing; . p. :1-12.
    [Google Scholar]
  9. , , . Assessment of Iranian nurses' knowledge and anxiety toward COVID-19 during the current outbreak in Iran. Arch Clin Infect Dis. 2020;15:e102848.
    [CrossRef] [Google Scholar]
  10. , , , , , , et al. COVID-19 awareness among healthcare students and professionals in Mumbai metropolitan region: A questionnaire based survey. Cureus. 2020;12:e7514.
    [CrossRef] [Google Scholar]
  11. , , , , , . Study of knowledge, attitude, anxiety and perceived mental healthcare need in Indian population during COVID-19 pandemic. Asian J Psychiatr. 2020;51:102083.
    [CrossRef] [PubMed] [Google Scholar]
  12. . Medical Dictionary United States: Farlex Inc; .
    [Google Scholar]
  13. , . Myths and medicine. West J Med. 2000;172:208.
    [CrossRef] [PubMed] [Google Scholar]
  14. , , , , , , et al. Self-care for common colds: The pivotal role of Vitamin D, Vitamin C, zinc, and Echinacea in three main immune interactive clusters (physical barriers, innate and adaptive immunity) involved during an episode of common colds-practical advice on dosages and on the time to take these nutrients/botanicals in order to prevent or treat common colds. Evid Based Complement Alternat Med. 2018;2018:5813095.
    [CrossRef] [PubMed] [Google Scholar]
  15. , , . A review of micronutrients and the immune system-working in harmony to reduce the risk of infection. Nutrients. 2020;12:236.
    [CrossRef] [PubMed] [Google Scholar]
  16. . Available from: http://www.fip.org/coronavirus [Last accessed on 2020 Mar 26]
  17. , , , , , , et al. Evidence that Vitamin D supplementation could reduce risk of influenza and COVID-19 infections and deaths. Nutrients. 2020;12:E988.
    [CrossRef] [PubMed] [Google Scholar]
  18. . Global epidemic of coronavirus-COVID-19: What we can do to minimzerisksl. Eur J Biomed Pharm Sci. 2020;7:432-8.
    [Google Scholar]
  19. , . Socioeconomic status and racial and ethnic differences in functional status associated with chronic diseases. Am J Public Health. 1997;87:805-10.
    [CrossRef] [PubMed] [Google Scholar]
  20. , , , . Contribution of major diseases to disparities in mortality. N Engl J Med. 2002;347:1585.
    [CrossRef] [PubMed] [Google Scholar]
  21. , , , , , . An initial investigation of the association between the SARS outbreak and weather: With the view of the environmental temperature and its variation. J Epidemiol Community Health. 2005;59:186-92.
    [CrossRef] [PubMed] [Google Scholar]
  22. . Coronavirus Disease (COVID-2019) Situation Reports. Available from: https://www.who.int/docs/default-source/coronavirusesituation-reports/20200227-sitrep-38-covid19.pdf?sfvrsn=9f98940c_2 [Last accessed on 2020 Feb 27]
    [Google Scholar]
  23. , , , , , . Air pollution, temperature and pediatric influenza in Brisbane, Australia. Environ Int. 2013;59:384-8.
    [CrossRef] [PubMed] [Google Scholar]
  24. , , , , , , et al. No association of COVID-19 transmission with temperature or UV radiation in Chinese cities. Eur Respir J. 2020;55:2000517.
    [CrossRef] [PubMed] [Google Scholar]
  25. , , , , , , et al. Knowledge, attitudes, and practices towards COVID-19 among Chinese residents during the rapid rise period of the COVID-19 outbreak: A quick online cross-sectional survey. Int J Biol Sci. 2020;16:1745-52.
    [CrossRef] [PubMed] [Google Scholar]
  26. , , , , , , et al. Knowledge, Attitude and Practice Associated with COVID-19 Among University Students: A Cross-sectional Survey in China. BMC Public Health Preprint;. ;2020
    [CrossRef] [Google Scholar]
  27. , , . Prevention and treatment knowledge towards SARS of urban population in Jinan. Prev Med Trib. 2004;10:659-60.
    [Google Scholar]
Show Sections