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Given the public health responses to previous respiratory disease pandemics, and in the absence of treatments and vaccines, the mitigation of the COVID-19 pandemic relies on population engagement in nonpharmaceutical interventions. This engagement is largely driven by risk perception, anxiety levels, and knowledge, as well as by historical exposure to disease outbreaks, government responses, and cultural factors.
The aim of this study is to compare psychobehavioral responses in Hong Kong and the United Kingdom during the early phase of the COVID-19 pandemic.
Comparable cross-sectional surveys were administered to adults in Hong Kong and the United Kingdom during the early phase of the epidemic in each setting. Explanatory variables included demographics, risk perception, knowledge of COVID-19, anxiety level, and preventive behaviors. Responses were weighted according to census data. Logistic regression models, including effect modification to quantify setting differences, were used to assess the association between the explanatory variables and the adoption of social distancing measures.
Data from 3431 complete responses (Hong Kong, 1663; United Kingdom, 1768) were analyzed. Perceived severity of symptoms differed by setting, with weighted percentages of 96.8% for Hong Kong (1621/1663) and 19.9% for the United Kingdom (366/1768). A large proportion of respondents were abnormally or borderline anxious (Hong Kong: 1077/1603, 60.0%; United Kingdom: 812/1768, 46.5%) and regarded direct contact with infected individuals as the transmission route of COVID-19 (Hong Kong: 94.0%-98.5%; United Kingdom: 69.2%-93.5%; all percentages weighted), with Hong Kong identifying additional routes. Hong Kong reported high levels of adoption of various social distancing measures (Hong Kong: 32.6%-93.7%; United Kingdom: 17.6%-59.0%) and mask-wearing (Hong Kong: 98.8% (1647/1663); United Kingdom: 3.1% (53/1768)). The impact of perceived severity of symptoms and perceived ease of transmission of COVID-19 on the adoption of social distancing measures varied by setting. In Hong Kong, these factors had no impact, whereas in the United Kingdom, those who perceived their symptom severity as “high” were more likely to adopt social distancing (adjusted odds ratios [aORs] 1.58-3.01), and those who perceived transmission as “easy” were prone to adopt both general social distancing (aOR 2.00, 95% CI 1.57-2.55) and contact avoidance (aOR 1.80, 95% CI 1.41-2.30). The impact of anxiety on adopting social distancing did not vary by setting.
Our results suggest that health officials should ascertain baseline levels of risk perception and knowledge in populations, as well as prior sensitization to infectious disease outbreaks, during the development of mitigation strategies. Risk should be communicated through suitable media channels—and trust should be maintained—while early intervention remains the cornerstone of effective outbreak response.
In December 2019, a novel coronavirus, SARS-CoV-2, emerged in Wuhan, Hubei Province, China, and spread rapidly worldwide, forming the second pandemic of the 21st century [
Prior to the availability of effective treatments and vaccines, strategies to mitigate the impact of the pandemic have been primarily nonpharmaceutical [
Previous studies of the severe acute respiratory syndrome and influenza pandemics showed that governments should account for risk perception and anxiety when promoting preventative measures. There is evidence that higher perceived risk of infection is associated with increased adoption of precautionary measures [
During the current COVID-19 pandemic, researchers have examined public risk perceptions and knowledge in various countries, including Finland [
This initial evidence that there is variation across context in affective responses, risk perceptions, and the impact of sociodemographic factors on the uptake of preventative behaviors has significant implications when tailoring policies. To elucidate these relationships, a more thorough comparative analysis is required. However, studies in different countries often use different metrics to measure the same behavior, which can lead to difficulty when interpreting the significance of heterogeneous contexts.
In this study, we examined and compared public perception and adoption of preventive behaviors in response to the early phase of the COVID-19 pandemic in two different settings: Hong Kong and the United Kingdom. We further investigated the factors associated with greater adoption of different types of social distancing measures. Our results have immediate implications on how health officials plan and communicate strategies to mitigate the ongoing COVID-19 pandemic to communities.
In Hong Kong and the United Kingdom, cross-sectional surveys were conducted during the early phase of the COVID-19 pandemic, when limited government-level interventions were in place [
In Hong Kong, all 452 district councilors were invited to distribute an open web-based survey by sharing a survey link and promotion messages on their webpages, social media platforms, or any channels which they usually used to convey information to their targeted residents. Individuals aged ≥18 years who understood Chinese and lived in Hong Kong were eligible to participate [
The study instruments are freely available on the web (Hong Kong: [
Sociodemographic variables included age, sex, educational attainment, and employment status. Anxiety level was measured using the Hospital Anxiety and Depression scale–Anxiety (HASD-A) (0-7=normal; 8-10=borderline abnormal; 11-21=abnormal) [
Descriptive statistics for all variables present the number of respondents and the raw or weighted percentages. In this manuscript, weighted percentages were used for description except for demographics. The responding samples were weighted to be representative of the United Kingdom (2011 census [
Common and comparable sociodemographic factors considered in separate analytical studies [
The study was approved by the Imperial College London Research Ethics Committee (reference number: 20IC5861) and the Survey and Behavioral Research Ethics Committee of The Chinese University of Hong Kong (reference number: SBRE-19-625).
In Hong Kong, there were initially 2478 clicks on the survey link. After removing 763 cases with missing demographics and 52 cases with ambiguous responses on the perceived ease of transmission, 1663 complete cases were included in the analysis. In the United Kingdom, 2500 individuals were approached, and the response rate was 84.3% (2108/2500). After excluding cases with missing demographics or perceived severity and cases with ambiguous responses on the perceived ease of transmission, 1768 cases were included in the analysis.
There were significant differences in the sociodemographic characteristics of the study respondents between the two settings. Hong Kong respondents were younger, with 26.0% (433/1663) aged 18-24 years, compared with 9.4% (166/1768) for the United Kingdom (
Characteristics of the study respondents in the United Kingdom and Hong Kong (all
Characteristics |
United Kingdom (n=1768) | Hong Kong (n=1663) | ||||||
n | % (unweighted) | % (weighted) | n | % (unweighted) | % (weighted) | |||
|
||||||||
|
18-24 | 166 | 9.4 | 9.9 | 433 | 26.0 | 17.0 | |
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25-34 | 243 | 13.7 | 14.3 | 535 | 32.2 | 23.5 | |
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35-44 | 335 | 18.9 | 19.5 | 370 | 22.2 | 23.9 | |
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45-54 | 300 | 17.0 | 17.7 | 193 | 11.6 | 22.2 | |
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≥55 | 724 | 41.0 | 38.6 | 132 | 7.9 | 13.4 | |
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Female | 936 | 52.9 | 51.8 | 1141 | 68.6 | 57.1 | |
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Male | 832 | 47.1 | 48.2 | 522 | 31.4 | 42.9 | |
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No formal qualification/lower secondary or below | 100 | 5.7 | 5.5 | 53 | 3.2 | 9.9 | |
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Secondary level qualification/higher secondary | 738 | 41.7 | 43.2 | 292 | 17.6 | 32.5 | |
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Postsecondary but below degree | 334 | 18.9 | 18.3 | 267 | 16.1 | 16.2 | |
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Degree or above | 596 | 33.7 | 32.9 | 1051 | 63.2 | 41.5 | |
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Employer/employee | 1025 | 58.0 | 59.6 | 1135 | 68.3 | 66.0 | |
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Full-time student | 90 | 5.1 | 5.3 | 278 | 16.7 | 12.5 | |
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Unemployed/not working | 172 | 9.7 | 10.4 | 206 | 12.4 | 17.2 | |
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Retired | 481 | 27.2 | 24.7 | 44 | 2.6 | 4.3 | |
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Level 1 | 96 | 5.4 | 5.2 | 1071 | 64.4 | 65.0 | |
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Level 2 | 270 | 15.3 | 14.7 | 550 | 33.1 | 31.8 | |
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Level 3 | 1058 | 59.8 | 60.2 | 32 | 1.9 | 2.2 | |
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Level 4 | 320 | 18.1 | 18.5 | 7 | 0.4 | 0.7 | |
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Level 5 | 24 | 1.4 | 1.4 | 3 | 0.2 | 0.3 | |
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Very worried | 536 | 30.3 | 30.1 | 852 | 51.2 | 49.4 | |
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Fairly worried | 858 | 48.5 | 48.4 | 723 | 43.5 | 43.2 | |
|
Neutral/don’t know | 5 | 0.3 | 0.3 | 40 | 2.4 | 3.2 | |
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Not very worried | 295 | 16.7 | 16.9 | 1 | 0.1 | 0.1 | |
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Not at all worried | 74 | 4.2 | 4.3 | 47 | 2.8 | 4.1 | |
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Normal | 956 | 54.1 | 53.5 | 586 | 35.2 | 40.0 | |
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Borderline abnormal | 336 | 19.0 | 19.4 | 512 | 30.8 | 27.3 | |
|
Abnormal | 476 | 26.9 | 27.1 | 565 | 34.0 | 32.7 |
aLevel 1=very serious (Hong Kong)/life-threatening (United Kingdom); Level 2=serious (Hong Kong)/severe (eg, may need care and treatment in hospital) (United Kingdom); Level 3=neutral (Hong Kong)/moderate (eg, may need self-care and rest in bed) (United Kingdom); Level 4=not serious (Hong Kong)/mild (eg, can go about daily tasks normally) (United Kingdom); Level 5=not serious at all (Hong Kong)/no symptoms (United Kingdom).
The Hong Kong sample contained a greater proportion of women (Hong Kong: 1141/1663, 68.6%, vs United Kingdom: 936/1768, 52.9%;
Higher perceived severity of COVID-19 was observed among Hong Kong respondents, with 96.8% (1621/1663) rating the symptoms of COVID-19 infection as serious or very serious compared with only 19.9% (366/1768) of the UK respondents. In terms of levels of concern, 92.6% (1575/1663) of the Hong Kong sample responded that they felt very or fairly worried, compared with 78.5% (1394/1768) of the UK sample. The HADS-A scores reflected similar trends, with 60.0% (1077/1663) of the Hong Kong sample recording an abnormal or borderline abnormal result, compared with 46.5% (812/1768) of the UK sample (
The majority of respondents regarded direct contact with infected individuals (Hong Kong: 94.0%-98.5%; United Kingdom: 69.2%-93.5%) or virus-contaminated environments (Hong Kong: 1594/1663, 96.3%; United Kingdom: 1411/1768, 79.5%) as the primary means of virus transmission (
Knowledge of COVID-19 transmission.
“Are the following transmission routes of COVID-19?” |
Respondents answering “yes” | ||||||
United Kingdom (n=1768) | Hong Kong (n=1663) | ||||||
n | % (unweighted) | % (weighted) | n | % (unweighted) | % (weighted) | ||
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Face-to-face conversation (no physical contact) with someone who has SARS-CoV-2 but no symptoms | 1234 | 69.8 | 69.2 | 1564 | 94.0 | 94.0 |
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Face-to-face conversation (no physical contact) with someone who has SARS-CoV-2 with symptoms | 1398 | 79.1 | 78.7 | 1616 | 97.2 | 96.8 |
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Physical contact with someone who has SARS-CoV-2 but no symptoms | 1580 | 89.4 | 89.0 | 1635 | 98.3 | 98.1 |
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Physical contact with someone with SARS-CoV-2 who has symptoms | 1657 | 93.7 | 93.5 | 1644 | 98.9 | 98.5 |
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Droplets | N/Aa | N/A | N/A | 1649 | 99.2 | 99.2 |
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Aerosol when infected people cough or sneeze | N/A | N/A | N/A | 1478 | 88.9 | 91.2 |
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Being in close contact (ie, within 2 meters) with someone who has SARS-CoV-2 when they cough or sneeze | 1604 | 90.7 | 90.4 | N/A | N/A | N/A |
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Being further away (ie, further than 2 meters) from someone who has SARS-CoV-2 when they cough or sneeze | 615 | 34.8 | 34.8 | N/A | N/A | N/A |
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Contact with virus-contaminated environment | 1411 | 79.8 | 79.5 | 1594 | 95.9 | 96.3 |
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Consumption of wild animal meat | 199 | 11.3 | 11.3 | 1546 | 93.0 | 93.4 |
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Visiting a wet market | 374 | 21.2 | 21.5 | 1342 | 80.7 | 81.1 |
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Consumption of seafood imported from specific regionsb | 258 | 14.6 | 14.8 | 1199 | 72.1 | 70.9 |
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Consumption/use of products imported from specific regionsb | 209 | 11.8 | 12.1 | 1101 | 66.2 | 66.6 |
aN/A: not applicable.
bSpecific regions refer to China (United Kingdom)/Wuhan (Hong Kong).
There were variations in the weighted proportions of Hong Kong and the UK respondents who adopted precautionary measures against COVID-19 (
Adoption of precautionary measures against COVID-19. “Affected areas” refers to China (Hong Kong)/affected areas in the world (United Kingdom); “Specific regions in a limited period” refers to Wuhan in the past one month (Hong Kong)/affected areas in the past 14 days (United Kingdom). The “Going to work” category only included respondents who were employees or employers (n=2160), and the “Going to school/letting your children go to school” category only included respondents who were full-time students or had at least one child (n=1239).
Sociodemographic factors were associated with the three social distancing measures (Table S3 in
Factors associated with the adoption of different social distancing measures.
Factor | Types of social distancing measures | ||||||||||||||
Generala (n=3431) (Model 1) | Contactb (n=3431) (Model 2) | Workc (n=2160) (Model 3) | |||||||||||||
aORd (95% CI) | aOR (95% CI) | aOR (95% CI) | |||||||||||||
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|||||||||||||||
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18-24 | Reference | N/Ae | Reference | N/A | Reference | N/A | ||||||||
|
25-34 | 1.54 (1.16-2.05) | .003 | 0.96 (0.68-1.35) | .81 | 1.00 (0.72-1.39) | .99 | ||||||||
|
35-44 | 1.25 (0.93-1.68) | .13 | 0.74 (0.53-1.05) | .09 | 0.95 (0.68-1.33) | .77 | ||||||||
|
45-54 | 1.30 (0.95-1.79) | .10 | 0.67 (0.47-0.97) | .03 | 0.72 (0.49-1.05) | .09 | ||||||||
|
55+ | 0.99 (0.70-1.41) | .97 | 0.81 (0.55-1.19) | .28 | 0.60 (0.39-0.93) | .02 | ||||||||
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Female | Reference | N/A | Reference | N/A | Reference | N/A | ||||||||
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Male | 0.82 (0.71-0.95) | .01 | 0.74 (0.63-0.88) | <.001 | 0.95 (0.78-1.16) | .62 | ||||||||
|
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No formal qualification/lower secondary or below | Reference | N/A | Reference | N/A | Reference | N/A | ||||||||
|
Secondary level qualification/higher secondary | 0.99 (0.68-1.44) | .96 | 0.96 (0.64-1.44) | .85 | 1.04 (0.46-2.34) | .92 | ||||||||
|
Postsecondary but below degree | 1.06 (0.72-1.55) | .78 | 1.12 (0.74-1.71) | .58 | 1.09 (0.48-2.47) | .83 | ||||||||
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Degree or above | 1.27 (0.87-1.83) | .21 | 0.98 (0.66-1.47) | .94 | 1.94 (0.88-4.28) | .10 | ||||||||
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Employed | Reference | N/A | Reference | N/A | N/A | N/A | ||||||||
|
Full-time student | 1.35 (0.98-1.85) | .07 | 1.08 (0.73-1.59) | .70 | N/A | N/A | ||||||||
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Unemployed | 1.65 (1.30-2.09) | <.001 | 1.20 (0.91-1.58) | .20 | N/A | N/A | ||||||||
|
Retired | 1.92 (1.43-2.59) | <.001 | 1.40 (1.03-1.91) | .03 | N/A | N/A | ||||||||
|
|||||||||||||||
|
Hong Kong | Reference | N/A | Reference | N/A | Reference | N/A | ||||||||
|
United Kingdom | 0.35 (0.30-0.41) | <.001 | 0.08 (0.07-0.10) | <.001 | 0.70 (0.57-0.87) | <.001 |
aGeneral: avoiding going to crowded areas; going to social events; and going out.
bContact: avoiding contacting individuals who had a fever or respiratory symptoms and had been to Wuhan in the past month (Hong Kong)/affected areas in the past 14 days (United Kingdom).
cWork: avoiding going to work.
daOR: adjusted odds ratio.
eN/A: not applicable.
The impact of perceived severity of infection (
Setting-specific effects and effect modification (by setting) of perceived severity on the adoption of social distancing measures. The models have been adjusted for all covariates.
Settings and variables |
Types of social distancing | |||||||||||||||||
Model 4.1 | Model 5.1 | Model 6.1 | ||||||||||||||||
Generala (n=3431) | Contactb (n=3431) | Workc (n=2160) | ||||||||||||||||
|
|
|
aORd (95% CI) | aOR (95% CI) | aOR (95% CI) | |||||||||||||
|
||||||||||||||||||
|
Not seriouse | Reference | N/Af |
Reference | N/A |
Reference | N/A |
|||||||||||
|
Seriousg | 0.93 (0.50-1.74) | .82 | 1.71 (0.85-3.47) | .13 | 0.63 (0.30-1.30) | .21 | |||||||||||
|
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Not serious | Reference | N/A |
Reference | N/A |
Reference | N/A |
|||||||||||
|
Serious | 3.01 (2.35-3.86) | <.001 | 1.90 (1.48-2.43) | <.001 | 1.58 (1.06-2.37) | .03 | |||||||||||
Effect modificationh | 3.24 (1.65-6.35) | <.001 |
1.11 (0.52-2.34) | .79 |
2.52 (1.09-5.80) | .03 |
aGeneral: avoiding going to crowded areas and social events and going out.
bContact: avoiding contacting individuals who had a fever or respiratory symptoms and had been to Wuhan in the past one month (Hong Kong) or affected areas in the past 14 days (United Kingdom).
cWork: avoiding going to work.
daOR: adjusted odds ratio.
eFor perceived severity, “not serious” refers to levels 3-5 (neutral to not serious at all, Hong Kong; moderate to no symptoms, United Kingdom).
fN/A: not applicable.
gFor perceived severity, “serious” refers to levels 1-2 (very serious to serious, Hong Kong; life-threatening to severe, United Kingdom).
hMeasures the difference of the effect being considered due to difference in setting; its value is the ratio of the two setting-specific effects.
Setting-specific effects and effect modification (by setting) of perceived ease of transmission on the adoption of social distancing measures. The models have been adjusted for all covariates.
Settings and variables |
Types of social distancing | |||||||||||||||||
Model 4.2 | Model 5.2 | Model 6.2 | ||||||||||||||||
Generala (n=3431) | Contactb (n=3431) | Workc (n=2160) | ||||||||||||||||
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|
|
aORd (95% CI) | aOR (95% CI) | aOR (95% CI) | |||||||||||||
|
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|
Difficulte |
Reference | N/Af |
Reference | N/A |
Reference | N/A |
|||||||||||
|
Easyg | 1.15 (0.77-1.74) | .50 | 1.00 (0.58-1.71) | .99 | 0.61 (0.37-1.03) | .07 | |||||||||||
|
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Difficult |
Reference | N/A |
Reference | N/A |
Reference | N/A |
|||||||||||
|
Easy | 2.00 (1.57-2.55) | <.001 | 1.80 (1.41-2.30) | <.001 | 1.34 (0.96-1.87) | .09 | |||||||||||
Effect modificationh |
1.73 (1.07-2.79) | .02 |
1.81 (1.00-3.28) | .05 |
2.18 (1.18- 4.04) | .01 |
aGeneral: avoiding going to crowded areas and social events and going out.
bContact: avoiding contacting individuals who had a fever or respiratory symptoms and had been to Wuhan in the past one month (Hong Kong) or affected areas in the past 14 days (United Kingdom).
cWork: avoiding going to work.
daOR: adjusted odds ratio.
eFor perceived ease of transmission, “difficult” means that the virus cannot be transmitted by face-to face conversation with someone who has SARS-CoV-2 but no symptoms.
fN/A: not applicable.
gFor perceived ease of transmission, “easy” means that the virus can be transmitted by face-to face conversation with someone who has SARS-CoV-2 but no symptoms.
hMeasures the difference of the effect being considered due to difference in setting; its value is the ratio of the two setting-specific effects.
Setting-specific effects and effect modification (by setting) of anxiety level on the adoption of social distancing measures. The models have been adjusted for all covariates.
Settings and variables |
Types of social distancing | |||||||||||||||||
Model 4.3 | Model 5.3 | Model 6.3 | ||||||||||||||||
Generala (n=3431) | Contactb (n=3431) | Workc (n=2160) | ||||||||||||||||
|
|
|
aORd (95% CI) | aOR (95% CI) | aOR (95% CI) | |||||||||||||
|
||||||||||||||||||
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Normal | Reference | N/Ae |
Reference | N/A |
Reference | N/A |
|||||||||||
|
Borderline abnormal | 1.62 (1.27-2.06) | <.001 | 1.26 (0.93-1.70) | .14 | 1.51 (1.10-2.06) | .01 | |||||||||||
|
Abnormal | 2.09 (1.64-2.66) | <.001 | 1.85 (1.34-2.56) | <.001 | 1.82 (1.34-2.48) | <.001 | |||||||||||
|
||||||||||||||||||
|
Normal | Reference | N/A |
Reference | N/A |
Reference | N/A |
|||||||||||
|
Borderline abnormal | 1.48 (1.11-1.96) | .01 | 1.36 (1.02-1.80) | .03 | 1.37 (0.92-2.02) | .12 | |||||||||||
|
Abnormal | 2.40 (1.87-3.09) | <.001 | 1.76 (1.37-2.27) | <.001 | 1.40 (0.99-1.98) | .06 | |||||||||||
Effect modificationf (borderline abnormal) | 0.91 (0.63-1.33) | .64 | 1.08 (0.71, 1.63) | .71 | 0.91 (0.55-1.49) | .70 | ||||||||||||
Effect modification (abnormal) | 1.15 (0.82-1.62) | .42 | 0.95 (0.63-1.42) | .80 | 0.77 (0.48-1.21) | .26 |
aGeneral: avoiding going to crowded areas and social events and going out.
bContact: avoiding contacting individuals who had a fever or respiratory symptoms and had been to Wuhan in the past one month (Hong Kong) or affected areas in the past 14 days (United Kingdom).
cWork: avoiding going to work.
daOR: adjusted odds ratio.
eN/A: not applicable.
fMeasures the difference of the effect being considered due to difference in setting; its value is the ratio of the two setting-specific effects.
This study compared the initial public perceptions and preventative behaviors during the COVID-19 pandemic across Hong Kong and the United Kingdom. The adoption of social-distancing measures was higher in Hong Kong than in the United Kingdom. Risk perception and knowledge of COVID-19 were consistently and significantly higher in Hong Kong; however, for the United Kingdom, respondents’ adoption of preventive behaviors was associated with two metrics: if transmission was considered to be “easy” and the perceived severity was “severe,” UK respondents were more likely to adopt preventive behaviors. Anxiety was a driver of behavior change in both settings: those who were more anxious were more likely to adopt preventative measures. This behavior is consistent with the wider literature surrounding the adoption of precautionary measures [
This study has three implications. First, health officials should account for context-specific baseline levels of risk perception and knowledge when designing and promoting mitigation strategies. The evidence presented in this study demonstrates that geographical and sociocultural context is important in terms of both how people understand risk and how risk drives behavior. Although the social, historical, and cultural heterogeneity between Hong Kong and the United Kingdom likely contributes to the results of this study, the importance of intrinsic factors such as population sensitization via past infectious disease outbreaks and state-led health promotion campaigns should not be underestimated. In other studies, public perceptions of these factors have been found to be significant drivers of adopting preventative behaviors during previous epidemics [
Second, risk communication should build upon baseline KAP outcomes, and trust should be developed across suitable media channels. Significant contextual heterogeneity in the public reliance on information sources provides insight here. Hong Kong reported greater reliance on social media and far less trust in official websites, suggesting that official messaging in Hong Kong did not likely drive individual behavior change; by contrast, the UK results suggested that although the UK government possessed an effective platform to influence public health behavior, government health messaging was insufficient to attain similar baseline knowledge levels to those in Hong Kong, particularly in the absence of prior population sensitization to infectious disease outbreaks. Therefore, there is a pressing need to tailor communication approaches, likely on a graduated scale, but at a minimum in a binary fashion to accommodate both “naive” and “experienced” populations.
Third, the comparative snapshots of initial community responses captured by this study demonstrate the diversity in approaches and pandemic responses during the early phases of the COVID-19 pandemic. Across many contexts, national lockdowns became commonplace as the true magnitude of transmission became apparent; however, the associated indirect costs render blanket strategies untenable in the medium term. As national lockdowns are lifted, countries worldwide face the challenge of resurging cases and must consider nuanced approaches to prevent additional harm. Driven by anxiety, high perceived severity and knowledge, Hong Kong conducted widespread preventive measures early and en masse. Together with early government actions [
From a methodological perspective, the UK sampling approach enabled the sample size to be achieved quickly, thereby accurately capturing prevailing sentiment and behavior across a short time frame (2 days). However, this approach likely came at the expense of excluding participants without access to the internet, and it contrasted with the survey period in Hong Kong (3 weeks); this likely led to some sampling bias, especially during the initial phase of the pandemic (when there was much uncertainty about the disease). Additionally, both samples varied across the demographic spectrum; thus, although responses were weighted, caution should be taken when extrapolating study findings to wider populations. Moreover, given the incompatibility of region-specific weights and the controversy in estimating standard errors when survey weights are involved [
This study compared the initial community responses to COVID-19 in Hong Kong and the United Kingdom. In line with the high baseline level of risk perception and knowledge and with historical exposure to respiratory disease outbreaks, the adoption of preventive measures was higher in Hong Kong. However, the UK sample demonstrated that this adoption could be improved by heightened risk perception and knowledge, best driven by improved public health campaigns. Together, these results suggest that health officials should ascertain baseline levels of risk perception and knowledge, as well as prior sensitization to infectious disease outbreaks, when developing mitigation strategies. Risk communication should be performed through suitable media channels—and trust should be maintained—while early intervention remains the cornerstone of effective outbreak response.
Supplementary files.
adjusted odds ratio
Hospital Anxiety and Depression scale–Anxiety
knowledge, attitudes, and practices
The study was supported by Imperial NIHR Research Capability Funding and the internal funding of The Chinese University of Hong Kong. HW is a National Institute for Health Research (NIHR) Senior Investigator and receives funding from the Imperial NIHR Biomedical Research Centre, the NIHR Applied Research Collaborative North West London, the NIHR School for Public Health Research, and the Wellcome Trust. KOK would like to acknowledge the Research Fund for the Control of Infectious Diseases, Hong Kong (number:INF-CUHK-1); General Research Fund (number:14112818); Early Career Scheme (number: 24104920); Health and Medical Research Fund (numbers:17160302, 18170312); The Wellcome Trust (number: 200861/Z/16/Z); and a Direct Grant for Research of The Chinese University of Hong Kong (CUHK) (number: 2019.020).
LRB, KOK, HW, CA, and SYSW conceived the study; KOK, WIW, and CA collected the data; KOK, YYY, and WIW analyzed the data; LRB, KOK, RER, HW, WIW, CA, and SYSW interpreted the data; LRB wrote the first draft of the manuscript; and KOK, RER, YYY, HW, WIW, CA, and SYSW edited the manuscript. LRB and KOK contributed equally as the joint first author. CA and SYSW also contributed equally as the joint last author. KOK and CA also contributed equally as the joint corresponding author.
None declared.