key: cord-0690163-xn7f6s2h authors: Hsieh, Hsu-Sheng; Hsia, Hao-Ching title: Can continued anti-epidemic measures help post-COVID-19 public transport recovery? Evidence from Taiwan date: 2022-05-20 journal: J Transp Health DOI: 10.1016/j.jth.2022.101392 sha: 106cacf35ec2b1d6633e74dc6f2fe71164acf902 doc_id: 690163 cord_uid: xn7f6s2h INTRODUCTION AND OBJECTIVE: COVID-19 has transformed economic activities and travel behavior, especially for public transport use. When a pandemic ebbs, clarifying travel behavior changes and whether to continue public transport anti-epidemic measures is essential for a post-COVID-19 public transport renaissance. Therefore, this study investigated citizens’ metro use behavior across the pre-, in-, and post-COVID-19 phases and post-COVID-19 mode choice in transit service and anti-epidemic policies. METHODS: Through face-to-face interviews, 235 citizens were systematically sampled in proportion to district populations in Kaohsiung, Taiwan, as respondents to conduct analysis of variance for metro use changes and mixed logit modeling for mode choice. RESULTS: Analysis of variance indicated an overall decrease in metro use from the pre-to in-COVID-19 phase and, for loyal-metro-user citizens, a recovery after entering the post-COVID-19 phase. Moreover, a mixed logit model illustrated that post-COVID-19 metro use was facilitated by mandatory mask-wearing in the metro system, rather than transit service levels, and affected by age, number of household children, and pre-COVID-19 travel habits. CONCLUSIONS: Continuing mandatory mask wearing within public transport in an early post-pandemic time and fostering transit use habits in non-pandemic times can help recover post-COVID-19 transit ridership. Moreover, a transit use promotion scheme may not need to target royal users with original use before and no complete suspension after COVID-19. pandemic since early 2020 worldwide. In Taiwan, located in East-South Asia, profound 36 changes in travel patterns occurred in the first half of 2020. According to the cellular 37 data obtained from Taiwanese residents, from middle January (when the Taiwanese 38 government announced the COVID-19 alert) to middle August in 2020, trips with 39 purposes for shopping necessities and open spaces increased respectively by 9% and 40 24%; however, those for public transit stations and workplaces decreased respectively 41 by 7% and 12% (Google, 2020) . Regarding travel mode use changes, during this period, 42 private car trips increased by 15%, walking trips increased by 8%, but public transit 43 trips decreased by 11% (Apple, 2020) . These changes have suggested that trips are more 44 likely to be made for necessary life needs and low infection risk places but not for 45 crowded places, such as entertainment and commercial venues, which are the major 46 venues visited by confirmed COVID-19 cases ( Even if the pandemic turns to ebb in the future, travelers probably may not fully recover 58 the level of public transit use before the COVID-19 outbreak, and the increasing 59 tendency of private transport may threaten environmental sustainability. For this reason, 60 Shaheen and Wong (2020) proposed short (within one year), intermediate (from 1-3 61 years), and long term (from 4-6 years) strategies for sustainable transport recovery from 62 COVID-19 impact, respectively, through restructuring funding and partnership based 63 on prioritizing frequent public transport users, shaping active travel environment, and 64 integrating electric vehicles into shared mobility for travelers captive to private modes. 65 Nevertheless, the short-term goal cannot be achieved without considering emerging 66 demand with COVID-19. For example, the Taiwanese government had eliminated the 67 first wave of COVID-19 community transmission since middle May 2020 and avoided 68 a domestic pandemic through early border control and stringent quarantine procedures 69 (See Table 1 ); however, public transit demand has not fully recovered despite, for the 70 case of Kaohsiung, the largest city in southern Taiwan, adopting the same headway and 71 enhanced transfer availability compared to the pre-COVID-19 phase (see Table 2 ). This 72 situation implies that COVID-19 has impacted intra-city public transport for work, 73 school, shopping, and tourism, served by Kaohsiung City Bus for the whole city and 74 Kaohsiung Metro for the urban area. Furthermore, understanding the unprecedented 75 travel demand is needed to improve transport equity since epidemic impacts on access 76 to healthcare and avoidance of high infection risk are uneven across sociodemographic 77 groups (Hsieh et This study defined three phases by important anti-epidemic events to observe the 81 impact of COVID-19 on public transport passenger volume in Taiwan public transport mask-wearing, but appealed to community works and living habits to 90 prevent the epidemic (see Fig. 1 ). Based on the definition, Table 2 shows that the impact 91 of COVID-19 on public transport, excluding the cause of seasonal influence by 92 displaying year-over-year volume, has markedly emerged both in inter-and intra-city 93 travel. As the primary inter-city mode of transport for work, business, and tourism, 94 Taiwan and cycling and public transport could provide mutual aid in a post-COVID-19 phase. 170 Organizing empirical evidence, Gkiotsalitis and Cats (2020) recommended that the 172 models capable of aiding public transport service planning were urgently necessary 173 given that the models considering contagious respiratory diseases were absent in the 174 pre-COVID-19 time. In their review, although mask use and temperature checks for 175 public transport were suggested to hinder the virus from spreading in the post-shutdown 176 phase, the association of these intervention measures with travel behavior was not 177 explored. In contrast to most research on the short-term impact of COVID-19 on travel 178 behavior, Delbosc and Mccarthy (2021) studied the long-term COVID-19 impact on 179 Australian young adults' life plans and future mobility. Interviews disclosed that daily 180 travel was profoundly affected by the pandemic, but long-term mobility decisions (e.g., 181 residential and job locations, working from home, and car driving) were additionally 182 mediated by life milestones (e.g., education completion, career choice, and childbirth). 183 The study also found that COVID-19 has accelerated car dependence owing to changed 184 life plans and that the long-term impact on mobility was indirect and unevenly spread. 185 Therefore, though private transport promotion and investment seem a solution to 186 epidemic risk, the solution has aggravated social inequality and environmental 187 problems. Public transport still needs a boost after an epidemic peak. 188 public transport, and in commuting and non-commuting purpose trips; afterward, they 213 advanced a model identifying WFH and its impacts on commuting car and public 214 transport trips, enabling forecasting the number of weekly commuting trips by private 215 and public modes. The WFH strategy as an effective response to the pandemic may 216 entail that the strategy could facilitate both organizations' improvements in productivity 217 and employees' benefits. Thus, the success in introducing WFH into Australia may 218 result from a high percentage of citizens (70%) believing their productivity under WFH 219 to be the same or higher than at the office. This belief is because the spent time for 220 original long commuting could be spent with family and on leisure. Finally, in addition 221 to focusing on WFH, the study recommended that travel patterns without epidemic 222 prevention restrictions should be further modeled. 223 For an example of developing countries, Abdullah, Ali, Hussain, Aslam, and Javid 225 (2021) explored Pakistan's travel pattern changes before and during the pandemic. 226 Pakistan conducted a nationwide lockdown in April 2020 for around a month and 227 continuously extended it in some areas in megacities with severe clusters, called smart 228 lockdown. The extension is partly because public transport in developing countries 229 often carries millions of people beyond design capacity. The overcapacity in public 230 J o u r n a l P r e -p r o o f transport has caused hygiene and social distancing maintenance problems. Therefore, 231 the study on the case also considered travelers' perceived health safety in public 232 transport. The results revealed a significant mode shift from public transport to private 233 cars for long distances (over 5 km). The study also elicited epidemic prevention factors 234 of public transport that were considered by travelers during COVID-19 but did not 235 examine their effects on mode choice. 236 intention by using data collected in June 2020 after the epidemic's highest timepoint in 242 China, which could be treated as a post-COVID-19 phase. They concluded that public 243 transport was the primary choice for long trips, that ride-hailing service use sharply 244 declined, and that carless people intended to buy electric scooters more than 245 automobiles. That is, even though the pandemic ebbed, people tended to travel alone 246 for short daily trips. Thus, the study provided sufficient information on citizens' travel 247 mode preferences in the low infection-risk time but, unfortunately, did not clarify the 248 influence of anti-epidemic measures in public transport on the preferences. This study took Kaohsiung Metro (in Kaohsiung City, Taiwan), which was extensively 279 impacted by COVID-19 (see Table 2 Initially, to investigate metro use behavior changes by ANOVA, this study took weekly 294 metro use frequency as the dependent variable, the COVID-19 phase containing three 295 periods as the factor, and the binary loyal metro use as the segmentation variable used 296 to examine the difference in COVID-19 impact. The group of loyal metro users was 297 defined as the respondents with any metro use (≧1 trip) in all three COVID-19 phases. 298 The purpose of this definition was to feature original metro use before COVID-19 and 299 no complete suspension of the use after COVID-19. The detailed definitions and 300 adoption references of the variables are shown in Table 3 . Policy variables were specified as SP attributes to produce variances in policy levels 311 for policy evaluation since those levels did not appear in the current circumstance 312 except the current levels. The detailed definitions and adoption references of the 313 variables are exhibited in Table 4 . 314 In the SP scenarios of mode choice, the service level of the Kaohsiung metro was 316 characterized by waiting time and transfer availability. The average headway in the 317 survey period during the post-COVID-19 phase followed the in-COVID-19 level, such 318 that the current average waiting time (4 minutes) was longer than before responding to 319 COVID-19 (3.5 minutes). Thus, the pre-COVID-19 level of 3.5 minutes and the other 320 two possible levels of 3 and 2.5 minutes as the improved scenarios were specified to 321 design SP scenarios. Moreover, the current transferring public and shared modes of the 322 metro contained bus service and a recently developed shared bicycle system built with 323 each metro station. Therefore, the level without the shared bicycle system was 324 incorporated to examine the effect of developing active transport to respond to COVID-325 19 on metro use. In addition, the level with shared electric scooters as an available type 326 of transferring mode surrounding metro stations was added to the transfer availability 327 levels to evaluate the effect of shared electric scooters on metro use facilitation. 328 329 Moreover, in the post-COVID-19 phase, the Taiwanese government lifted the policy of 330 mandatory mask-wearing for entering metro ticket gates. Therefore, no mandatory 331 requirement, the in-COVID-19 mask-wearing policy, and a possible intermediate level 332 of mandatory mask-wearing for entering metro cars were specified as three mask-333 wearing policy levels. By contrast, the government maintained the in-COVID-19 policy 334 of temperature screening for entering metro ticket gates in the post-COVID-19 phase. 335 Hence, the other level of no temperature screening was included in SP scenarios. 336 337 The main travel mode before the COVID-19 announcement (15 January 2020)  Metro (as reference)  Car = 1; otherwise = 0  Scooter = 1; otherwise = 0  Walk = 1; otherwise = 0  Bicycle = 1; otherwise = 0  Bus = 1; otherwise = 0 Bamberg (2013) Pre-COVID-19 weekly metro use frequency (past habitual travel level) The average number of trips by metro per week before the COVID-19 announcement (15 January 2020) Bamberg was reduced to the one with 16 scenarios composed of policy attribute levels (see Table 345 5). Each respondent was asked to choose whether to use metro in two randomly selected 346 scenarios. 347 348 This study treated the citizens of the Kaohsiung urban area, the largest city in southern 399 Taiwan, as the population and the metro system of Kaohsiung Mass Rapid Transit as 400 the public transport case (see Fig. 2 ). This urban area features a population density of 401 9,829 inhabitants per km 2 in 11 administrative districts covering an area of 153.59 km 2 402 and two cross-shaped metro lines distributed across ten districts (one as an offshore 403 island). 404 There are three cities with a metro system in Taiwan Given the investigation into three-phase travel behavior, the questionnaire survey was 427 conducted through face-to-face interviews with explaining the phase periods to 428 respondents for data quality. The data collection procedure was established to increase 429 the sample representativeness as follows. (1) Set the sampling rate above 1.5‱ after 430 removing invalid samples as the objective. (2) Decide the expected number of 431 respondents in each district in proportion to the district population. (3) Randomly 432 sample 32 streets as the interview locations, whose respective number in a district was 433 proportional to the expected number of respondents in the district. (4) Systematically 434 invite each fifth person passing the interviewer. Finally, 235 valid respondents were 435 interviewed, and the SP mode choices of 470 choosers taken by these respondents (each 436 of whom was provided with two choice scenarios) were collected. To understand the 437 sample representativeness, Table 6 compares the distributions of respondent 438 characteristics with those in the census. Gender and vehicle license ownership reflected 439 the closeness between the sample and the population, while the comparison in age 440 implied a limitation upon the inference from the sample on seniors. 441 442 This study employed ANOVA with repeated measures to examine weekly metro use 455 frequency changes across the three COVID-19 phases. Initially, based on one-way 456 (phase) ANOVA results, as shown in Table 7 and Fig. 3 , total respondents (representing 457 ordinary citizens in the Kaohsiung city area) showed a significant decrease in weekly 458 metro use frequency from the pre-(1.66 times/week) to in-COVID-19 phase (1.38) (p 459 < 0.01) and a significant recovery from the in-to post-COVID-19 phase (1.57) (p < 460 0.01). Although the post-COVID-19 metro use level was lower than the pre-COVID-461 19 one, the difference between both phases was not statistically significant (p > 0.1). 462 Then, to clarify the impact of COVID-19 on loyal metro-user citizens and its difference 464 from those who use other modes entirely without using metro during any phase, two 465 groups were separated to conduct one-way ANOVA. One group was named the "loyal-466 metro-user group," comprising the respondents who had used metro at least once in all 467 three phases. The other group was named the "non-loyal-metro-user group," 468 comprising the respondents who had not used metro during any phase. Table 7 and Fig. 469 4 report the results. The loyal-metro-user group significantly decreased weekly metro 470 use frequency from the pre-(2.11 times/week) to in-COVID-19 phase (1.79) (p < 0.01) 471 but significantly increased it after entering the post-COVID-19 phase (1.98) (p < 0.05), 472 which recovered to the pre-COVID-19 level (p > 0.1). However, although the non-473 loyal-metro-user group also significantly decreased weekly metro use frequency from 474 the pre-(1.15) to in-COVID-19 phase (0.92) (p < 0.01), a significant recovery did not 475 emerge in the post-COVID-19 phase (1.08) (p > 0.1). 476 Furthermore, to confirm the interaction effect of the phase of COVID-19 and the loyalty 478 to metro on metro use frequency, three (pre-, in-, and post-COVID-19 phases) by two 479 (loyal-and non-loyal-metro-user groups) ANOVA was executed. Table 7 shows that 480 both the phase and group factors significantly affected metro use frequency, but their 481 interaction effect on metro use frequency did not arise. Namely, as exhibited in Fig. 4 ., 482 both groups had a similar trend of changes in metro use frequency across the COVID-483 19 phases. variables with a sign corresponding to a priori notions be included (probably turning to 505 be significant if based on large sample size), but other-type variables be rejected if not 506 significant at the 80% confidence level. 507 508 The final estimation is reported in According to the estimation results, waiting time and transfer availability as 518 conventionally key transport policy predictors of public transport use did not 519 significantly influence the metro choice probability in the post-COVID-19 phase (ps > 520 0.1). However, concerning the variables of anti-epidemic policies that might decrease 521 riding convenience and comfort, first, the rule of mandatory mask-wearing for entering 522 ticket gates increased the metro choice probability significantly (p < 0.05); in contrast, 523 the effect of the mask-wearing requirement for entering metro cars was not significant 524 (p > 0.1). Then, the temperature screening rule did not significantly influence the metro 525 choice probability (p > 0.1), implying that respondents may perceive mutual mask 526 protection as a more effective epidemic prevention measure than preventing people 527 with fever from riding metro. 528 529 Regarding socio-economic characteristics, respondents aged above 18 had a 530 significantly lower probability of using metro than those aged below 17 (ps < 0.1). This 531 propensity appeared more undeniable for seniors aged above 65 (p < 0.05). This result 532 may result from the government's suggestions on not going out for unnecessary 533 activities and to crowded places, especially for seniors vulnerable to the epidemic. Also, 534 the number of household members aged 6-17 was significantly negatively associated 535 with metro use probability (p < 0.1), probably because of the household demand for 536 joint trip generation (Kobayashi, Kita, & Tatano, 1996) . Moreover, pre-COVID-19 537 travel patterns were also influential in post-COVID-19 metro use. That is, the 538 respondents whose pre-COVID-19 main travel mode was car (p < 0.05) or scooter (p < 539 0.1) had a lower tendency to choose metro than those whose pre-COVID-19 main travel 540 mode was metro. In contrast, there was no significant difference in the metro use 541 probability between the respondents whose pre-COVID-19 main travel mode was 542 walking, cycling, bus (p > 0.1), and metro (as the reference category). In addition, pre-543 COVID-19 weekly metro use frequency was significantly positively associated with 544 the post-COVID-19 metro use probability (p < 0.1), despite metro use frequency 545 reductions from the pre-to in-COVID-19 phase (see Table 7 ). 546 547 This study investigated citizens' metro use behavior across the pre-, in-, and post-558 COVID-19 phases and the post-COVID-19 stated preference mode choice in the 559 scenarios constituted by public transport service and anti-epidemic policies. Therefore, 560 this study clarified COVID-19 impact on metro use frequency changes across the three 561 phases, the predictors of post-COVID-19 metro use choice, and the controversial 562 question of whether the government should continue mandatory anti-epidemic 563 measures in public transport for ridership recovery when a higher level of epidemic 564 alert is reduced or removed. Consequently, the analysis results showed a significant 565 decrease in metro use from the pre-to in-COVID-19 phase and, for loyal metro-user 566 citizens, a significant recovery from the in-to post-COVID-19 phase. Notably, the 567 results also suggested that mandatory mask-wearing policy facilitated and pre-COVID-568 19 travel habits affected post-COVID-19 metro use. These findings could provide 569 answers to the three proposed research questions, as discussed below. 570 (1) Do loyal public transport users change use intensity across COVID-19 phases? 572 573 The statistically significant differences in metro use frequency emerged between the 574 pre-and in-COVID-19 phase (showing a decrease) and between the in-and post-575 COVID-19 phase (showing an increase). However, given group distinction, the post-576 COVID-19 metro use frequency recovery from the in-COVID-19 phase was found only 577 from loyal metro users who did not wholly escape from metro use in each phase. Hence, 578 although loyal users significantly decreased metro use frequency after the COVID-19 579 outbreak, they significantly recovered it to the pre-COVID-19 level when perceiving a 580 reduction in epidemic alert. In addition to considering the influence of pre-epidemic 581 travel patterns on post-COVID-19 metro use, these results implied that fostering public 582 transport use habits in a low infection-risk period could help ridership recovery from a 583 colossal epidemic impact. 584 (2) Do lifting mandatory anti-epidemic measures in public transport benefit or 586 harm post-COVID-19 ridership recovery? 587 588 The Taiwanese government lifted the mandatory wear-masking requirement in public 589 transport on 8 June 2020 after controlling the first wave of COVID-19 community 590 transmission with gradually built standard operation procedures for epidemic 591 prevention. However, the government, still taking control of the epidemic during the 592 not implemented mask-wearing period, decided to resume the policy on 5 August 2020. 593 Is lifting or resuming the mask policy better for public transport renaissance in a post-594 COVID-19 phase? Although lifting the mask policy may lower riding inconvenience 595 and discomfort, the perceived transmission risk may increase, and thus, the willingness 596 to take metro may decline. Physiological safety needs may arise as crucial focuses even 597 in post-COVID-19 times with the disease's vast and long-term health threat. Hence, a 598 continued and more stringent mandatory mask-wearing rule for entering ticket gates, 599 rather than the one for entering metro cars, may benefit ridership recovery from a 600 pandemic. 601 This finding regarding mandatory mask-wearing benefits corresponds to Nguyen and 603 Pojani (2021), indicating that mandates worked better than awareness-raising 604 campaigns and that mask use and, differently from our finding, hand sanitizer use were 605 sufficient to keep the minor threats of COVID-19 while still maintaining regular bus 606 operations most of the time. Similarly, Dzisi and Dei (2020) presented the necessity of 607 mandatory mask use within public transport. In that case, the use of fines and policing 608 to enforce the mask policy might be better ways for public transport travelers to adhere 609 to the mask policy. However, it is noteworthy that although the validity of wearing 610 masks to prevent the epidemic from spreading has been confirmed in many studies 611 (Eikenberry et Do public transport service levels affect post-COVID-19 mode choice? 624 The two factors belong to the components of reliability, treated as the 627 most basic/functional attribute (needing to be first satisfied) in the hierarchy of transit 628 needs than safety, customer services, and comfort (more hedonic) based on Maslow's 629 hierarchy of needs For the present case, mask-wearing protection for physiological safety may respond to 633 the focal need, whereas transit system changes in waiting time and transfer availability 634 regarding reliability did not influence mode choice in the post-COVID-19 phase the adverse effects of lowering perceived customer services and comfort 638 but did not undermine post-COVID-19 metro use. Thus, it could be speculated that 639 COVID-19 has restructured the hierarchy of transit needs such that safety may shift into 640 the most basic need, as illustrated in Fig. 5. In this structure, citizens may not first 641 pursue satisfaction with other attributes before satisfying safety needs. The 642 confirmation of this structure should entail future research integrating epidemic safety 643 into the physiological safety of public transit needs, including criminal security, road 644 safety, and noise and pollution exposure safety identified before COVID-19 (Allen et 645 al., 2019). 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