Table 1 presents a descriptive summary of the characteristics of the survey respondents. Respondents were more likely to be female (68.81%, 1544/2244), aged 26-35 years (46.48%, 1043/2244), local residents (86.68%, 1945/2244), married (85.16%, 1911/2244), have a bachelor’s degree or higher (42.02%, 943/2244), working in a government agency (34.49%, 774/2244), have an annual income of 50,000-100,000 Chinese Yuan (31.24%, 701/2244), and report being in good health (90.24%, 2025/2244). In addition, the majority of respondents portrayed low perceived susceptibility (93.49%, 2098/2244) and mild perceived severity of COVID-19 (81.11%, 1820/2244) although they had high awareness of the COVID-19 (92.78%, 2082/2244). Respondents were almost equally distributed between the two selected cities.
Table 1
Characteristics of study respondents by the willingness and uptake of COVID-19 test
Characteristics | Total (%) | Uptake of COVID-19 test | Willingness of COVID-19 test |
Tested/scheduled (%) | Not tested/scheduled (%) | Willing (%) | Unwilling (%) |
Total | 2244 (100) | 1177 (52.45) | 1067 (47.55) | 2146 (95.63) | 98 (4.37) |
City | | P<0.001 | | P<0.001 | |
Nanjing | 1091 (48.62) | 626 (57.38) | 465 (42.62) | 1024 (93.86) | 67 (6.14) |
Chizhou | 1153 (51.38) | 551 (47.79) | 602 (52.21) | 1122 (97.31) | 31 (2.69) |
Gender | | P=0.638 | | P=0.152 | |
Male | 700 (31.19) | 362 (51.71) | 338 (48.29) | 663 (94.71) | 37 (5.29) |
Female | 1544 (68.81) | 815 (52.78) | 729 (47.22) | 1483 (96.05) | 61 (3.95) |
Age (years) | | P=0.099 | | P=0.199 | |
18-25 | 218 (9.71) | 119 (54.59) | 99 (45.41) | 208 (95.41) | 10 (4.59) |
26-35 | 1043 (46.48) | 519 (49.76) | 524 (50.24) | 998 (95.69) | 45 (4.31) |
36-45 | 567 (25.27) | 317 (55.91) | 250 (44.09) | 549 (96.83) | 18 (3.17) |
>=46 | 416 (18.54) | 222 (53.37) | 194 (46.63) | 391 (93.99) | 25 (6.01) |
Residency | | P=0.309 | | P=0.003 | |
Local residents | 1945 (86.68) | 1012 (52.03) | 933 (47.97) | 1870 (96.14) | 75 (3.86) |
Migrants | 299 (13.32) | 165 (55.18) | 134 (44.82) | 276 (92.31) | 23 (7.69) |
Marital status | | P=0.044 | | P=0.352 | |
Single | 283 (12.61) | 168 (59.36) | 115 (40.64) | 266 (93.99) | 17 (6.01) |
Married | 1911 (85.16) | 984 (51.49) | 927 (48.51) | 1832 (95.87) | 79 (4.13) |
Divorced/widow | 50 (2.23) | 25 (50) | 25 (50) | 48 (96) | 2 (4) |
Educational attainment | | P<0.001 | | P=0.343 | |
Middle school or lower | 341 (15.20) | 131 (38.42) | 210 (61.58) | 329 (96.48) | 12 (3.52) |
High school or technical secondary school | 402 (17.91) | 163 (40.55) | 239 (59.45) | 378 (94.03) | 24 (5.97) |
Junior college | 558 (24.87) | 289 (51.79) | 269 (48.21) | 536 (96.06) | 22 (3.94) |
Bachelor's degree or higher | 943 (42.02) | 594 (62.99) | 349 (37.01) | 903 (95.76) | 40 (4.24) |
Occupation | | P<0.001 | | P=0.001 | |
Government agency | 774 (34.49) | 582 (75.19) | 192 (24.81) | 758 (97.93) | 16 (2.07) |
Service industry | 580 (25.85) | 273 (47.07) | 307 (52.93) | 547 (94.31) | 33 (5.69) |
Manufacturing industry or agriculture | 302 (13.46) | 102 (33.77) | 200 (66.23) | 290 (96.03) | 12 (3.97) |
Others | 588 (26.20) | 220 (37.41) | 368 (62.59) | 551 (93.71) | 37 (6.29) |
Annual individual income | | P=0.001 | | P=0.821 | |
<20k | 244 (10.87) | 107 (43.85) | 137 (56.15) | 230 (94.26) | 14 (5.74) |
20-50k | 373 (16.62) | 181 (48.53) | 192 (51.47) | 359 (96.25) | 14 (3.75) |
50-100k | 701 (31.24) | 359 (51.21) | 342 (48.79) | 672 (95.86) | 29 (4.14) |
100-200k | 606 (27.01) | 339 (55.94) | 267 (44.06) | 579 (95.54) | 27 (4.46) |
>200k | 320 (14.26) | 191 (59.69) | 129 (40.31) | 306 (95.63) | 14 (4.38) |
Self-reported health status | | P=0.382 | | P=0.232 | |
Good | 2025 (90.24) | 1056 (52.15) | 969 (47.85) | 1940 (95.80) | 85 (4.20) |
Poor | 219 (9.76) | 121 (55.25) | 98 (44.75) | 206 (94.06) | 13 (5.94) |
Awareness of COVID-19 | | P=0.014 | | P<0.001 | |
High | 2082 (92.78) | 1107 (53.17) | 975 (46.83) | 2007 (96.40) | 75 (3.60) |
Low | 162 (7.22) | 70 (43.21) | 92 (56.79) | 139 (85.80) | 23 (14.20) |
Perceived susceptibility of COVID-19 | | P<0.001 | | P=0.157 | |
High | 146 (6.51) | 116 (79.45) | 30 (20.55) | 143 (97.95) | 3 (2.05) |
Low | 2098 (93.49) | 1061 (50.57) | 1037 (49.43) | 2003 (95.47) | 95 (4.53) |
Perceived severity of COVID-19 | | P=0.034 | | P=0.696 | |
Severe or moderate | 424 (18.89) | 242 (57.08) | 182 (42.92) | 404 (95.28) | 20 (4.72) |
Mild | 1820 (81.11) | 935 (51.37) | 885 (48.63) | 1742 (95.71) | 78 (4.29) |
Figure 1 presents the survey respondent’s willingness to receive and uptake COVID-19 testing and vaccination. At the time of the survey, 52.45% (1177/2244) and 23.62% (530/2244) of respondents had received or scheduled at least one COVID-19 test and COVID-19 vaccine, respectively (Figure 1A). Among the respondents who had ever received or scheduled a COVID-19 test, 57.50% (675/1174) did so because of community-wide mass testing led by governments, followed by mandatory testing policies for travel (31.35%, 368/1174), and personal health needs (11.16%, 131/1174) (Figure 2). Concerning willingness to receive COVID-19 tests or vaccines, 95.63% (2146/2244) reported being willing to receive a COVID-19 test, and 63.28% (1418/2241) either received, scheduled, or reported being willing to receive a COVID-19 vaccination (Figure 1B).
Table 1 also contains a descriptive summary of the respondents’ characteristics stratified by their willingness to receive and uptake COVID-19 testing. More respondents in Nanjing city had received or scheduled a COVID-19 test at least once (57.38%, 626/1091), compared to respondents in Chizhou city (47.79%, 551/1153). About three-fourths (75.19%, 582/774) of respondents who worked in a government agency had ever received or scheduled a COVID-19 test, than respondents working in service, manufacturing, agriculture, and other industries. Respondents who had completed junior college or received a bachelor’s degree or higher had a greater uptake rate of COVID-19 testing—51.79% (289/558) and 62.99% (594/943), respectively. However, fewer respondents (39.57% [294/743]) with lower educational attainment (high school and lower) had ever received/scheduled a COVID-19 test. More than half of the respondents with an annual individual income over 50,000 Chinese Yuan had received or scheduled a test at least once. A similar proportion (53.17% [1107/2082] of respondents who reported a high level of COVID-19 awareness had ever received or scheduled a COVID-19 test. Across each group, more than 85.80% of respondents were willing to receive a test.
Table 2 presents the factors associated with willingness to receive and uptake of COVID-19 testing using multivariate logistic regressions. Location, occupation, awareness of and perceived susceptibility to COVID-19 were significantly associated with receiving testing. Compared to respondents living in Nanjing city, fewer respondents in Chizhou city had ever received or scheduled a COVID-19 test (aOR=0.765, 95% CI=0.619-0.946). However, more respondents in Chizhou city were willing to receive the test than in Nanjing city (aOR=2.097, 95% CI=1.248-3.524). Compared to respondents who reported working in a government agency, respondents with less secure occupations (service, manufacturing, agricultural or other industries) had a significantly lower uptake and willingness to receive of COVID-19 tests. Associations between the other socio-demographic factors (i.e., marital status, educational attainment, annual individual income) and the willingness to receive and uptake of COVID-19 testing failed to reach statistical significance in the multivariate analysis. The uptake rate among respondents with a high perceived susceptibility to COVID-19 was nearly three times (aOR: 2.719, 95% CI=1.739-4.251) higher than those with lower perceived susceptibility. The willingness to receive testing among respondents with high COVID-19 awareness was 4.318 times (95% CI=2.550-7.314) higher than those with low awareness.
Table 2
Factors associated with the willingness and uptake of COVID-19 test
| Uptake of COVID-19 test (aOR) | 95%CI | Willingness of COVID-19 test (aOR) | 95%CI |
City (ref: Nanjing) |
Chizhou | 0.765* | (0.619 - 0.946) | 2.097** | (1.248 - 3.524) |
Gender (ref: male) |
Female | 1.116 | (0.912 - 1.367) | 1.436 | (0.913 - 2.259) |
Age (ref: 18-25 years) |
26-35 | 0.703 | (0.487 - 1.013) | 0.707 | (0.305 - 1.641) |
36-45 | 0.725 | (0.478 - 1.098) | 0.750 | (0.272 - 2.066) |
>=46 | 0.832 | (0.537 - 1.290) | 0.429 | (0.155 - 1.189) |
Residency (ref: local residents) |
Migrants | 1.179 | (0.893 - 1.555) | 0.606 | (0.348 - 1.055) |
Marital status (ref: single) |
Married | 0.912 | (0.652 - 1.275) | 1.229 | (0.609 - 2.479) |
Divorced/widow | 0.783 | (0.396 - 1.547) | 1.511 | (0.305 - 7.494) |
Educational attainment (ref: middle school or lower) |
High school or technical secondary school | 0.862 | (0.630 - 1.179) | 0.552 | (0.263 - 1.161) |
Junior college | 1.022 | (0.747 - 1.398) | 0.717 | (0.326 - 1.576) |
Bachelor's degree or higher | 1.252 | (0.893 - 1.756) | 0.686 | (0.302 - 1.558) |
Occupation (ref: government agency) |
Service industry | 0.307** | (0.239 - 0.395) | 0.403** | (0.212 - 0.767) |
Manufacturing industry or agriculture | 0.190** | (0.138 - 0.261) | 0.570 | (0.253 - 1.284) |
Others | 0.216** | (0.164 - 0.283) | 0.316** | (0.162 - 0.617) |
Annual individual income (ref: <20k) |
20-50k | 1.207 | (0.854 - 1.706) | 1.295 | (0.591 - 2.837) |
50-100k | 1.021 | (0.739 - 1.410) | 1.294 | (0.640 - 2.617) |
100-200k | 0.895 | (0.632 - 1.267) | 1.230 | (0.580 - 2.609) |
>200k | 0.804 | (0.539 - 1.199) | 1.196 | (0.500 - 2.860) |
Self-reported health status (ref: good) |
Poor | 1.087 | (0.795 - 1.486) | 0.833 | (0.436 - 1.594) |
Awareness of COVID-19 (ref: low) |
High | 1.286 | (0.910 - 1.817) | 4.318** | (2.550 - 7.314) |
Perceived susceptibility of COVID-19 (ref: low) |
High | 2.719** | (1.739 - 4.251) | 2.261 | (0.673 - 7.597) |
Perceived severity of COVID-19 (ref: mild) |
Severe or moderate | 1.006 | (0.792 - 1.278) | 0.829 | (0.486 - 1.417) |
*p<0.05. **p<0.01. |
Abbreviation: aOR=adjusted odds ratio. |
The uptake of COVID-19 vaccination differed across socio-demographic characteristics, awareness of and perceived susceptibility to COVID-19 (Table 3). Among the 2244 respondents, there were significant differences in the uptake of COVID-19 vaccines by location, age, educational attainment, occupation, annual income, and COVID-19 awareness. When participant’s occupations were considered, the percentages of respondents who had not been or scheduled a vaccination ranged from 53.10% (411/774) for those working in government agencies to 92.72% (280/302) for those working in the manufacturing industry or agriculture. Respondents with low perceived susceptibility to COVID-19 were more likely to have not received or scheduled a COVID-19 vaccine (78.60%, 1649/2098), while those with high perceived susceptibility had a higher uptake rate of COVID-19 vaccinations (55.84%, 81/146). Regarding willingness to receive COVID-19 vaccinations among the 1711 respondents who had not been vaccinated or did not have vaccinations scheduled, 49.12% (419/853) from Nanjing city and 54.66% (469/858) from Chizhou city reported being willing to receive the vaccination. A large proportion of respondents in both the high and low perceived susceptibility to COVID-19 categories were willing to receive a vaccination, 65.63 % (42/64) and 51.37% (846/1647), respectively. Respondents with high COVID-19 awareness were more willing to receive COVID-19 vaccination (54.20%, 851/1570), while those with low awareness had a lower willingness to receive COVID-19 vaccination (26.24%, 37/141).
Table 3
Characteristics of study respondents by the willingness and uptake of COVID-19 vaccination
Characteristics | Uptake of COVID-19 vaccination | Willingness of COVID-19 vaccination among those not vaccinated |
Vaccinated /scheduled (%) | Not vaccinated/scheduled (%) | Willing (%) | Unwilling (%) |
Total | 530 (23.62) | 1714 (76.38) | 888 (51.90) | 823 (48.10) |
City | P=0.040 | | P=0.022 | |
Nanjing | 237 (21.72) | 854 (78.28) | 419 (49.12) | 434 (50.88) |
Chizhou | 293 (25.41) | 860 (74.59) | 469 (54.66) | 389 (45.34) |
Gender | P=0.252 | | P=0.082 | |
Male | 176 (25.14) | 524 (74.86) | 288 (55.07) | 235 (44.93) |
Female | 354 (22.93) | 1190 (77.07) | 600 (50.51) | 588 (49.49) |
Age (years) | P<0.001 | | P=0.799 | |
18-25 | 46 (21.10) | 172 (78.90) | 90 (52.33) | 82 (47.67) |
26-35 | 183 (17.55) | 860 (82.45) | 454 (52.98) | 403 (47.02) |
36-45 | 186 (32.80) | 381 (67.20) | 193 (50.66) | 188 (49.34) |
>=46 | 115 (27.64) | 301 (72.36) | 151 (50.17) | 150 (49.83) |
Residency | P=0.499 | | P=0.822 | |
Local residents | 464 (23.86) | 1481 (76.14) | 766 (51.79) | 713 (48.21) |
Migrants | 66 (22.07) | 233 (77.93) | 122 (52.59) | 110 (47.41) |
Marital status | P=0.667 | | P=0.277 | |
Single | 70 (24.73) | 213 (75.27) | 113 (53.05) | 100 (46.95) |
Married | 446 (23.34) | 1465 (76.66) | 761 (52.05) | 701 (47.95) |
Divorced/widow | 14 (28) | 36 (72) | 14 (38.89) | 22 (61.11) |
Educational attainment | P<0.001 | | P=0.784 | |
Middle school or lower | 33 (9.68) | 308 (90.32) | 155 (50.49) | 152 (49.51) |
High school or technical secondary school | 53 (13.18) | 349 (86.82) | 188 (54.18) | 159 (45.82) |
Junior college | 149 (26.70) | 409 (73.30) | 209 (51.10) | 200 (48.90) |
Bachelor's degree or higher | 295 (31.28) | 648 (68.72) | 336 (51.85) | 312 (48.15) |
Occupation | P<0.001 | | P=0.321 | |
Government agency | 363 (46.90) | 411 (53.10) | 221 (53.77) | 190 (46.23) |
Service industry | 101 (17.41) | 479 (82.59) | 251 (52.51) | 227 (47.49) |
Manufacturing industry or agriculture | 22 (7.28) | 280 (92.72) | 152 (54.29) | 128 (45.71) |
Others | 44 (7.48) | 544 (92.52) | 264 (48.71) | 278 (51.29) |
Annual individual income | P=0.007 | | P=0.973 | |
<20k | 37 (15.16) | 207 (84.84) | 107 (52.20) | 98 (47.80) |
20-50k | 81 (21.72) | 292 (78.28) | 151 (51.71) | 141 (48.29) |
50-100k | 173 (24.68) | 528 (75.32) | 270 (51.14) | 258 (48.86) |
100-200k | 151 (24.92) | 455 (75.08) | 235 (51.76) | 219 (48.24) |
>200k | 88 (27.50) | 232 (72.50) | 125 (53.88) | 107 (46.12) |
Self-reported health status | P=0.072 | | P=0.050 | |
Good | 489 (24.15) | 1536 (75.85) | 808 (52.71) | 725 (47.29) |
Poor | 41 (18.72) | 178 (81.28) | 80 (44.94) | 98 (55.06) |
Awareness of COVID-19 | P<0.001 | | P<0.001 | |
High | 510 (24.50) | 1572 (75.50) | 851 (54.20) | 719 (45.80) |
Low | 20 (12.35) | 142 (87.65) | 37 (26.24) | 104 (73.76) |
Perceived susceptibility of COVID-19 | P<0.001 | | P=0.025 | |
High | 81 (55.48) | 65 (44.52) | 42 (65.63) | 22 (34.38) |
Low | 449 (21.40) | 1649 (78.60) | 846 (51.37) | 801 (48.63) |
Perceived severity of COVID-19 | P=0.103 | | P=0.163 | |
Severe or moderate | 113 (26.65) | 311 (73.35) | 172 (55.48) | 138 (44.52) |
Mild | 417 (22.91) | 1403 (77.09) | 716 (51.11) | 685 (48.89) |
Note: Only 1714 participants who haven't received or scheduled a COVID-19 vaccine were asked their willingness. Among them, three participants didn't report their willingness, so the sample size of the vaccination willingness question was limited to 1711. |
Table 4 presents the factors associated with willingness to receive and uptake of COVID-19 vaccinations in the study sites. Location, age, residence, educational attainment, occupation, self-reported health status, and perceived susceptibility to COVID-19 were significantly associated with uptake of COVID-19 vaccination among the survey respondents. Respondents living in Chizhou city, compared to Nanjing city, had a higher uptake rate of COVID-19 vaccination (aOR=1.928, 95% CI=1.488-2.498). Persons aged 46 years or older (aOR=2.012, 95% CI=1.133-3.574), compared to those aged 18-25 years, were more likely to receive or schedule a vaccination, while respondents who had poor perceived health were less likely to receive or schedule a vaccination (aOR=0.540, 95% CI=0.352-0.829). Vaccination uptake among migrants was 1.479 times (95% CI=1.040-2.104) higher than among local residents. Respondents who had educational attainment of junior college or higher and worked in government agencies had higher uptake of COVID-19 vaccinations than those with lower educational attainment or less secure occupations (i.e., industry). The vaccine uptake rate among respondents with high perceived susceptibility to COVID-19 was 3.457 times (95% CI=2.298-5.199) higher than those with low perceived susceptibility. In terms of willingness to receive COVID-19 vaccination, among 1711 respondents who had not been or scheduled a vaccination, more respondents in Chizhou city reported being willing to receive a COVID-19 vaccination than those living in Nanjing city (aOR=1.404, 95% CI=1.110-1.776). Willingness to be vaccinated among respondents with high awareness of and perceived susceptibility to COVID-19 was 3.391 (95% CI=2.285-5.032) and 1.950 (95% CI=1.119-3.398) times higher than those with low awareness and perceived susceptibility, respectively. Other socio-demographic characteristics were not associated with the willingness to receive a COVID-19 vaccination among those who had been vaccinated.
Table 4
Factors associated with the willingness and uptake of COVID-19 vaccination
| Uptake of COVID-19 vaccination (aOR) | 95%CI | Willingness of COVID-19 vaccination (aOR) | 95%CI |
City (ref:Nanjing) |
Chizhou | 1.928** | (1.488 - 2.498) | 1.404** | (1.110 - 1.776) |
Gender (ref: male) |
Female | 0.999 | (0.781 - 1.278) | 0.867 | (0.694 - 1.083) |
Age (ref: 18-25 years) |
26-35 | 0.713 | (0.436 - 1.166) | 1.024 | (0.693 - 1.512) |
36-45 | 1.680 | (0.979 - 2.882) | 0.953 | (0.607 - 1.495) |
>=46 | 2.012* | (1.133 - 3.574) | 0.946 | (0.588 - 1.521) |
Residency (ref: local residents) |
Migrants | 1.479* | (1.040 - 2.104) | 1.107 | (0.818 - 1.499) |
Marital status (ref: single) |
Married | 0.761 | (0.500 - 1.159) | 0.897 | (0.624 - 1.290) |
Divorced/widow | 1.092 | (0.479 - 2.490) | 0.567 | (0.262 - 1.224) |
Educational attainment (ref: middle school or lower) |
High school or technical secondary school | 1.085 | (0.652 - 1.807) | 1.206 | (0.873 - 1.667) |
Junior college | 1.996** | (1.236 - 3.225) | 1.023 | (0.734 - 1.425) |
Bachelor's degree or higher | 2.473** | (1.494 - 4.094) | 1.024 | (0.716 - 1.465) |
Occupation (ref: government agency) |
Service industry | 0.285** | (0.214 - 0.381) | 1.010 | (0.756 - 1.348) |
Manufacturing industry or agriculture | 0.104** | (0.0630 - 0.171) | 1.008 | (0.718 - 1.416) |
Others | 0.119** | (0.0809 - 0.175) | 0.846 | (0.626 - 1.145) |
Annual individual income (ref: <20k) |
20-50k | 1.487 | (0.909 - 2.432) | 0.939 | (0.650 - 1.358) |
50-100k | 1.061 | (0.672 - 1.677) | 0.905 | (0.644 - 1.273) |
100-200k | 0.719 | (0.445 - 1.163) | 0.955 | (0.661 - 1.379) |
>200k | 0.747 | (0.441 - 1.265) | 1.106 | (0.724 - 1.689) |
Self-reported health status (ref: good) |
Poor | 0.540** | (0.352 - 0.829) | 0.757 | (0.543 - 1.056) |
Awareness of COVID-19 (ref: low) |
High | 1.683 | (0.991 - 2.859) | 3.391** | (2.285 - 5.032) |
Perceived susceptibility of COVID-19 (ref: low) |
High | 3.457** | (2.298 - 5.199) | 1.950* | (1.119 - 3.398) |
Perceived severity of COVID-19 (ref: mild) |
Severe or moderate | 0.844 | (0.629 - 1.133) | 1.213 | (0.933 - 1.578) |
*p<0.05. **p<0.01. |
Abbreviation: aOR=adjusted odds ratio. |