| Id |
Subject |
Object |
Predicate |
Lexical cue |
| T72 |
0-7 |
Sentence |
denotes |
Results |
| T73 |
9-45 |
Sentence |
denotes |
Comparison of traffic (2019 vs 2020) |
| T74 |
46-185 |
Sentence |
denotes |
Our study analyzed traffic volumes alongside trends in the spread of COVID-19 after the first COVID-19 patient in South Korea was detected. |
| T75 |
186-263 |
Sentence |
denotes |
Traffic was analyzed in terms of the number of vehicles operating nationwide. |
| T76 |
264-419 |
Sentence |
denotes |
The difference in nationwide traffic between 2019 and 2020 is displayed as ‘Traffic gap (2019 vs 2020)’ in Figure 4, corresponding to the gray shaded area. |
| T77 |
420-513 |
Sentence |
denotes |
Figure 4 Traffic trends based on VDS in 2019 and 2020, and COVID-19 trends in 2020 by region. |
| T78 |
514-609 |
Sentence |
denotes |
Data are presented from January 1 to March 31, 2020, on (a) national and (b–f) regional scales. |
| T79 |
610-727 |
Sentence |
denotes |
The left y-axis corresponds to traffic and the right y-axis corresponds to the number of confirmed COVID-19 patients. |
| T80 |
728-860 |
Sentence |
denotes |
The bold red line corresponds to the traffic trend curve for 2020, and January 19 indicates the first confirmed case in South Korea. |
| T81 |
861-1072 |
Sentence |
denotes |
The gray dotted line is the difference in traffic between 2019 and 2020, the blue data points are the newly confirmed COVID-19 cases, and the green data points are the cumulative numbers released from isolation. |
| T82 |
1073-1208 |
Sentence |
denotes |
During the first 3 weeks of 2020, the traffic was around 7% lower than in 2019 (first week −6.7%, second week −0.4%, third week −2.6%). |
| T83 |
1209-1398 |
Sentence |
denotes |
However, following the first confirmed COVID-19 case in South Korea on January 19, 2020, the fourth week of January in 2020 showed a 17.3% increase in nationwide traffic compared with 2019. |
| T84 |
1399-1478 |
Sentence |
denotes |
In the first week of February, nationwide traffic was 23.3% lower than in 2019. |
| T85 |
1479-1597 |
Sentence |
denotes |
Thereafter, nationwide traffic continued to decrease – in the fourth week of February it was 26.1% lower than in 2019. |
| T86 |
1598-1768 |
Sentence |
denotes |
In March 2020, nationwide traffic shifted back to an increasing trend from March 7 onwards, as shown by the 2020 traffic trend curve, displayed as a red line in Figure 4. |
| T87 |
1769-1950 |
Sentence |
denotes |
Compared with the same period in 2019, however, traffic was lower throughout March (first week −25.1%, second week −14.6%, third week −13.7%, fourth week −14.0%, fifth week −22.0%). |
| T88 |
1951-2126 |
Sentence |
denotes |
The mean daily nationwide traffic between January 1 and March 31 was 143 655 563 vehicles, which was 9.7% lower than the same period in 2019 (159 044 566 vehicles) (Table 1 ). |
| T89 |
2127-2212 |
Sentence |
denotes |
Table 1 Average traffic per day in 2019 and 2020, and COVID-19 trend per day in 2020. |
| T90 |
2213-2305 |
Sentence |
denotes |
Date Traffic average per day Gapa (%)b Daily new confirmed cases (N) Released from isolation |
| T91 |
2306-2315 |
Sentence |
denotes |
2019 2020 |
| T92 |
2316-2377 |
Sentence |
denotes |
Jan – 1st week 145 797 502 135 994 670 −9 802 832 (−6.7%) 0 0 |
| T93 |
2378-2437 |
Sentence |
denotes |
Jan – 2nd week 149 049 737 148 389 105 −660 632 (−0.4%) 0 0 |
| T94 |
2438-2499 |
Sentence |
denotes |
Jan – 3rd week 150 897 726 146 908 915 −3 988 811 (−2.6%) 1 0 |
| T95 |
2500-2564 |
Sentence |
denotes |
Jan – 4th week 149 778 529 185 314 734 +25 844 728 (+17.3%) 10 0 |
| T96 |
2565-2626 |
Sentence |
denotes |
Jan – 5th week 147 251 673 150 482 955 +3 231 282 (+2.2%) 7 0 |
| T97 |
2627-2690 |
Sentence |
denotes |
Feb – 1st week 182 825 475 140 144 295 −42 681 180 (−23.3%) 6 2 |
| T98 |
2691-2752 |
Sentence |
denotes |
Feb – 2nd week 162 747 801 165 831 722 +3 083 921 (+1.9%) 4 7 |
| T99 |
2753-2817 |
Sentence |
denotes |
Feb – 3rd week 151 192 280 142 631 273 −8 561 006 (−5.7%) 176 18 |
| T100 |
2818-2885 |
Sentence |
denotes |
Feb – 4th week 170 090 529 125 730 973 −44 359 556 (−26.1%) 2133 27 |
| T101 |
2886-2954 |
Sentence |
denotes |
Mar – 1st week 164 855 643 123 492 052 −41 363 591 (−25.1%) 4430 117 |
| T102 |
2955-3023 |
Sentence |
denotes |
Mar – 2nd week 154 628 156 132 054 132 −22 574 024 (−14.6%) 1319 713 |
| T103 |
3024-3092 |
Sentence |
denotes |
Mar – 3rd week 158 348 967 136 602 840 −21 746 126 (−13.7%) 713 2611 |
| T104 |
3093-3161 |
Sentence |
denotes |
Mar – 4th week 162 656 743 139 886 152 −22 770 591 (−14.0%) 679 4811 |
| T105 |
3162-3231 |
Sentence |
denotes |
Mar – 5th weekc 176 503 164 137 714 570 −38 788 594 (−22.0%) 308 5567 |
| T106 |
3232-3284 |
Sentence |
denotes |
Average 159 044 566 143 655 563 −201 776 965 (−9.7%) |
| T107 |
3285-3290 |
Sentence |
denotes |
Data: |
| T108 |
3291-3375 |
Sentence |
denotes |
Public data portal, Korea Expressway Corporation point traffic data (date of access: |
| T109 |
3376-3574 |
Sentence |
denotes |
April 1, 2020) (http://data.ex.co.kr/portal/fdwn/view?type=VDS&num=37&requestfrom=dataset#); Korea Centers for Disease Control and Prevention (KCDC), South Korea COVID-19 press release (KCDC, 2020). |
| T110 |
3575-3647 |
Sentence |
denotes |
a Gap = average traffic per day (2020) − average traffic per day (2019). |
| T111 |
3648-3725 |
Sentence |
denotes |
b %: (average traffic per day (2020) ÷ average traffic per day (2019)) × 100. |
| T112 |
3726-3770 |
Sentence |
denotes |
c March 29, 2020 to March 31, 2020 (3 days). |
| T113 |
3771-3941 |
Sentence |
denotes |
As shown by the regional traffic trend curves in Figure 4, all regions showed a decreasing trend for traffic in February, which shifted to an increasing trend from March. |
| T114 |
3942-4133 |
Sentence |
denotes |
In particular, there was almost no change in traffic in Seoul, while Incheon showed a continuous decrease in traffic from January that shifted to an increasing trend from the end of February. |
| T115 |
4134-4293 |
Sentence |
denotes |
In Gyeonggi, traffic increased in January, showed a slight decrease after the first COVID-19 case, and then switched to an increasing trend again from March 7. |
| T116 |
4294-4345 |
Sentence |
denotes |
In Sejong, the traffic suddenly increased in March. |
| T117 |
4346-4517 |
Sentence |
denotes |
In Daegu, the traffic decreased significantly compared with other regions in February, and shifted to an increasing trend in March; however, overall traffic was still low. |
| T118 |
4519-4557 |
Sentence |
denotes |
Changes in traffic and COVID-19 trends |
| T119 |
4558-4666 |
Sentence |
denotes |
In Figure 4, the first COVID-19 patient in South Korea is indicated by a vertical dotted line on January 19. |
| T120 |
4667-4847 |
Sentence |
denotes |
The daily new confirmed cases are displayed as a blue line, and the cumulative number released from isolation is displayed as green squares, corresponding to the right-hand y-axis. |
| T121 |
4848-5096 |
Sentence |
denotes |
Following the first COVID-19 patient in South Korea, the traffic trend curve (displayed as a red line) decreased continuously until the first week of March, while the frequency of daily new confirmed COVID-19 cases increased during the same period. |
| T122 |
5097-5347 |
Sentence |
denotes |
Thereafter, the national traffic trend curve shifted to an increasing trend from March 7, while the daily new confirmed COVID-19 cases shifted to a decreasing trend, and the cumulative number released from isolation began to show an increasing trend. |
| T123 |
5348-5493 |
Sentence |
denotes |
Thus, as the COVID-19 situation in South Korea began to improve after March 7, the rate of increase in the traffic trend curve continued to grow. |
| T124 |
5494-5704 |
Sentence |
denotes |
When the regional traffic trend curves and COVID-19 trends were analyzed in Seoul, Incheon, and Gyeonggi, the number of new confirmed cases and the traffic trends in March both increased compared with February. |
| T125 |
5705-5844 |
Sentence |
denotes |
Other regions showed a decrease in the number of new confirmed cases compared with February, while the traffic trends increased (Figure 4). |
| T126 |
5845-6028 |
Sentence |
denotes |
Scatter plots were created to show regional daily traffic in 2020 against the daily new confirmed COVID-19 cases (Figure 5 ), and single regression analyses were performed (Table 2 ). |
| T127 |
6029-6207 |
Sentence |
denotes |
In Incheon, there was a positive but insignificant linear relationship (β = 43 146; p = 0.056) with an increasing number of new confirmed cases associated with increased traffic. |
| T128 |
6208-6362 |
Sentence |
denotes |
Meanwhile, all the other regions showed negative linear relationships, with traffic decreasing as the numbers of new confirmed cases increased (Figure 5). |
| T129 |
6363-6719 |
Sentence |
denotes |
The regions showing significant linear relationships were the national region (β = −52 176, p < 0.001), Busan (β = −17 895, p < 0.001), Daegu (β = −1778.5, p < 0.001), Gwangju (β = −39 368, p = 0.005), Ulsan (β = −77 689, p = 0.003), Chungbuk (β = −637 223, p = 0.002), Gyeongbuk (β = −49 467, p < 0.001), and Gyeongnam (β = −230 313, p = 0.006) (Table 2). |
| T130 |
6720-6781 |
Sentence |
denotes |
Figure 5 Scatter plots and single regression lines by region. |
| T131 |
6782-6888 |
Sentence |
denotes |
Table 2 The result of single linear regression between traffic in 2020 and newly confirmed COVID-19 cases. |
| T132 |
6889-6902 |
Sentence |
denotes |
β β t-value p |
| T133 |
6903-6941 |
Sentence |
denotes |
(a) National −52 176.0 −4.17 <0.001*** |
| T134 |
6942-6972 |
Sentence |
denotes |
(b) Seoul −3 025.6 −0.72 0.474 |
| T135 |
6973-7004 |
Sentence |
denotes |
(c) Incheon 43 146.0 1.94 0.056 |
| T136 |
7005-7039 |
Sentence |
denotes |
(d) Gyeonggi −19 180.0 −0.30 0.766 |
| T137 |
7040-7075 |
Sentence |
denotes |
(e) Busan −17 895.0 −3.68 <0.001*** |
| T138 |
7076-7110 |
Sentence |
denotes |
(f) Daegu −1 778.5 −5.58 <0.001*** |
| T139 |
7111-7145 |
Sentence |
denotes |
(g) Gwangju −39 368.0 −2.9 0.005** |
| T140 |
7146-7179 |
Sentence |
denotes |
(h) Daejeon −71 490.0 −1.66 0.100 |
| T141 |
7180-7213 |
Sentence |
denotes |
(i) Ulsan −77 689.0 −3.03 0.003** |
| T142 |
7214-7243 |
Sentence |
denotes |
(j) Sejong −806.5 −1.84 0.069 |
| T143 |
7244-7281 |
Sentence |
denotes |
(k) Chungbuk −637 223.0 −3.23 0.002** |
| T144 |
7282-7316 |
Sentence |
denotes |
(l) Chungnam −62 733.0 −1.96 0.053 |
| T145 |
7317-7351 |
Sentence |
denotes |
(m) Jeonbuk −322 490.0 −1.03 0.308 |
| T146 |
7352-7386 |
Sentence |
denotes |
(n) Jeonnam −217 346.0 −1.15 0.255 |
| T147 |
7387-7426 |
Sentence |
denotes |
(o) Gyeongbuk −49 467.0 −5.05 <0.001*** |
| T148 |
7427-7465 |
Sentence |
denotes |
(p) Gyeongnam −230 313.0 −2.81 0.006** |
| T149 |
7466-7502 |
Sentence |
denotes |
*p < 0.05, **p < 0.01, ***p < 0.001. |
| T150 |
7504-7563 |
Sentence |
denotes |
Types of relationship between regional traffic and COVID-19 |
| T151 |
7564-7754 |
Sentence |
denotes |
In Table 3 the analyses in Table 2, Figure 4, and Figure 5 have been classified into types for each region, based on whether the trends in traffic and COVID-19 were increasing or decreasing. |
| T152 |
7755-7886 |
Sentence |
denotes |
Incheon was categorized as a region requiring strong control (Type 1), with increasing trends for both COVID-19 spread and traffic. |
| T153 |
7887-8091 |
Sentence |
denotes |
Gyeonggi and Seoul were categorized as regions in the early stages of focused control or requiring control (Type 2), with increasing traffic but a relatively stable trend for new confirmed COVID-19 cases. |
| T154 |
8092-8213 |
Sentence |
denotes |
The other regions were categorized as stable (Type 3), with increasing traffic but decreasing trends for COVID-19 spread. |
| T155 |
8214-8293 |
Sentence |
denotes |
Table 3 The level of relationship between traffic and COVID-19 in cities, 2020. |
| T156 |
8294-8321 |
Sentence |
denotes |
Trend in 2020 Specific City |
| T157 |
8322-8344 |
Sentence |
denotes |
Level Traffic COVID-19 |
| T158 |
8345-8391 |
Sentence |
denotes |
1 + + (Danger) Strong control required Incheon |
| T159 |
8392-8480 |
Sentence |
denotes |
2 0 (Caution) Control required, or in the early stage of focused control Gyeonggi, Seoul |
| T160 |
8481-8620 |
Sentence |
denotes |
3 − (Stable) Under stable control Daegu, Busan, Gwangju, Daejeon, Ulsan, Sejong, Chungbuk, Chungnam, Jeonbuk, Jeonnam, Gyeongbuk, Gyeongnam |
| T161 |
8621-8662 |
Sentence |
denotes |
+ = increasing; 0 = same; − = decreasing. |
