Changes in public bike usage after the COVID-19 outbreak: A survey of Seoul public bike sharing users.

When the COVID-19 pandemic swept across the world, people tended to seek more individualized and viable transportation modes, such as a bicycle. In this study, we examined the factors influencing changes in public bike sharing (PBS) in Seoul, to assess this trend post-pandemic. We conducted an online survey of 1,590 Seoul PBS users between July 30 and August 7, 2020. Using a difference-in-differences analysis, we found that participants who were affected by the pandemic used PBS 44.6 h more than unaffected individuals throughout the year. In addition, we used a multinomial logistic regression analysis to identify the factors affecting changes in PBS usage. In this analysis, the discrete dependent variables of increased, unchanged, and decreased were considered, representing the changes in PBS usage after the COVID-19 outbreak. Results revealed that PBS usage increased among female participants during weekday trips such as commuting to work and when there were perceived health benefits of using PBS. Conversely, PBS usage tended to decrease when the weekday trip purpose was for leisure or working out. Our findings offer insight into PBS user behaviors within the context of the COVID-19 pandemic and present policy implications to revitalize PBS usage.

Attentive Multi-Task Prediction of Atmospheric Particulate Matter: Effect of the COVID-19 Pandemic

Air pollution, especially the continual increase in atmospheric particulate matter (PM), is a global environmental challenge. To reduce the PM concentration, a remarkable amount of machine learning-based research has been proposed. However, increasing the accuracy of the predictions and providing clear interpretations of the predictions are challenging. In particular, no studies have addressed models that predict and interpret PM before and during the COVID-19 pandemic. In this paper, we present a two-step predictive and explainable model to obtain insights into reducing PM. We first use attentive multi-task learning to predict the air quality of cities. To accurately predict the concentration of particles with sizes of similar to 10 mu m or similar to 2.5 mu m (PM10 and PM2.5, respectively), we demonstrate a performance difference between single-task and multi-task learning, as well as among the state-of-the art methods. The proposed attentive model with multi-task learning outperformed the others in terms of accuracy performance. We then used Shapley additive explanations, a representative explainable artificial intelligence framework, to interpret and determine the significance of features for predicting PM10 and PM2.5. We demonstrated the superiority of the proposed approach in predicting and explaining both PM10 and PM2.5 concentrations, and observed a statistically significant difference in air pollution before and during the COVID-19 pandemic.

Insight of Zoonotic Viruses at Human-Animal Interfaces in Cambodia

*Presenting author Emerging infectious diseases have been causing outbreaks in humans for centuries and most infectious diseases originate in animals. Re-emerging zoonotic pathogens are rapidly increasing in prevalence or geographic range and causing a significant and growing threat to global health. The present work provides an insight of zoonotic viruses risk at human-bat/rodent interfaces in Cambodia. We conducted studies to investigate the circulation of zoonotic viruses and the risk of exposure in human living at the interfaces with bats and rodents. Rodent's samples were collected in rural and urban areas of Cambodia. Organs were tested for Hantavirus, Orthohepevirus species C and Arenavirus. Bat's samples were collected in Steung Treng for Sarbecovirus and in Battambang and Kandal for Nipah virus detection. People working/living at the human-animal interfaces were screened for IgG antibodies. In rodents (750), hantavirus was detected in 3.3% rodents from urban areas only. Seoul orthohantavirus was the most predominant virus followed by Thottapalayam virus. HEV-C was detected only in rodents from urban settings (1.8%). Arenavirus was detected in both rural (6.8%) and urban (2.5%) areas. In humans (788), the seroprevalence of IgG antibodies against hantavirus, HEV-A and Arenavirus was 10.0%, 24% and 23.4% respectively. NiV was detected in flying fox's urines collected between 2013-2016 in Kandal (0.63%) and in Battambang (1.03%). Blood samples collected in both provinces were negative for NiV antibodies. SARS-CoV-2 related virus was detected in Rhinolphus shameli in Steung Treng in 2010, 2020 and 2021. Blood samples from people living at the vicinity of positive bats were positive for antibodies against CoV (7.7%), but no specific neutralizing SARS-CoV2 antibodies were detected. Our studies provided insight of the risk of zoonoses in Cambodia and highlighted the importance of zoonotic surveillance and further One Health effort to prevent, detect, and respond to future cross-species transmission.Copyright © 2023

Investigation on changes in the usage patterns of Seoul Bike usage patterns owing to COVID-19 according to pass type.

Human mobility has been significantly impacted by varying degrees of social distancing and stay-at-home directives that have been implemented in many countries to prevent the spread of COVID-19; this effect was observed regardless of the mode of transportation. Several studies have indicated that bike-sharing is a relatively safe option in terms of COVID-19 infection, and more resilient than public transportation. However, previous studies on the effects of COVID-19 on bike-sharing, rarely considered the type of pass in their investigation of the pandemic-induced changes in usage patterns of shared bikes. To overcome this limitation, this study used trip records obtained from Seoul Bike to investigate the changes in usage patterns of shared bikes during the COVID-19 pandemic. The spatiotemporal usage patterns were characterized in this study based on the type of pass. Additionally, using t-tests and k-means clustering, we discovered significant factors that influenced changes in one-day pass usage rates and temporal usage patterns at the station level. Finally, we constructed spatial regression models to estimate changes in bike rentals caused by COVID-19 based on pass type. The findings provided a comprehensive understanding of how bike-sharing usage varies depending on pass type, which is closely related to shared bikes trip purposes.

Air pollution assessment in Seoul, South Korea, using an updated daily air quality index

The variability of daily air quality index DAQx* was analyzed for types of air quality monitoring stations (AQMSs) in Seoul, South Korea, from 2018 to 2021. Daily maximum 1-h means of O3 and NO2 and daily 24-h means of PM10 and PM2.5 from 42 AQMSs were used to calculate the DAQx*. The frequencies of DAQx* values in DAQx* classes 3 (satisfactory) and 4 (sufficient) dominated for all station types, followed by DAQx* class 5 (poor). The variability of DAQx* values within station types mostly corresponded approximately to one DAQx* class, with mean frequencies of 82% for roadside, 81% for urban, and 72% for background stations. Lower air pollution levels on weekends than weekdays were shown for roadside stations by frequencies of DAQx* values in classes 3 (11% higher) and 4 (12% lower) during summer. NO2 was the air pollutant that annually most frequently formed DAQx* at roadside (48%) and urban (32%) stations, while O3 was the dominant pollutant (38%) at background stations. In winter, PM10 was the most common contributor to the DAQx* (at least 47%) at all station types. The dominant air pollutants in summer were NO2 at roadside stations (72%) and O3 at urban (63%) and background (68%) stations. Air quality improvement during a stronger social distancing period in 2020 due to the COVID-19 pandemic was evidenced by higher frequencies in DAQx* class 3 (up to 26%) but lower frequencies in DAQx* class 4 (up to 24%) than that during the reference period, especially for the roadside stations. © 2023 Turkish National Committee for Air Pollution Research and Control

Distribution Impact of Rent Control on Seoul Market Rents during the COVID-19

After the outbreak of the COVID-19 in the early 2020, Korea has attempted to reinforce the existing rent controls to help the lowincome households. From July 2000, the tenants' right of lease renewal came into effect, as a policy tool to enforce the upper bound percentage of rent increases within Korea. Purpose: This study aims to examine the impact of rent control on the uncontrolled rents in Seoul Metropolitan Area (SMA). Research design, data and methodology: The study regresses the monthly panel data from 58 municipalities in SMA from January 2020 to March 2022, during the COVID-19 pandemic. Results: The data indicates that the policy had the effect of lowering rents for a period of two months, and subsequently monetary policy including quantitative easing and low interest rates, coupled with asset market bubbles lead to rent increases. During the sample data period, the quantity of money supply increased by 12.6% and CPI rose by 3.0%, these phenomena collectively increased the rents by up to 14.7%. Conclusions: The results of the present study support the findings of earlier studies in part: namely, that rent control without the government's steps to stabilize the property price may have an undesirable effect on rental tenants. © Copyright: Korean Distribution Science Association (KODISA

Time-variant reproductive number of COVID-19 in Seoul, Korea.

OBJECTIVES: To estimate time-variant reproductive number (Rt) of coronavirus disease 19 based on either number of daily confirmed cases or their onset date to monitor effectiveness of quarantine policies. METHODS: Using number of daily confirmed cases from January 23, 2020 to March 22, 2020 and their symptom onset date from the official website of the Seoul Metropolitan Government and the district office, we calculated Rt using program R's package "EpiEstim". For asymptomatic cases, their symptom onset date was considered as -2, -1, 0, +1, and +2 days of confirmed date. RESULTS: Based on the information of 313 confirmed cases, the epidemic curve was shaped like 'propagated epidemic curve'. The daily Rt based on Rt_c peaked to 2.6 on February 20, 2020, then showed decreased trend and became <1.0 from March 3, 2020. Comparing both Rt from Rt_c and from the number of daily onset cases, we found that the pattern of changes was similar, although the variation of Rt was greater when using Rt_c. When we changed assumed onset date for asymptotic cases (-2 days to +2 days of the confirmed date), the results were comparable. CONCLUSIONS: Rt can be estimated based on Rt_c which is available from daily report of the Korea Centers for Disease Control and Prevention. Estimation of Rt would be useful to continuously monitor the effectiveness of the quarantine policy at the city and province levels.

Quantitative Evaluation on the Drivers of PM2.5 Concentration Change in South Korea during the 1(st) -3(rd) Seasonal PM2.5 Management Periods

Since 2019, Korean Ministry of Environment has implemented the 1st -3rd PM2.5 Seasonal Management Plans(SMP) to reduce PM2.5 concentration during high PM2.5 concentration period. In this study, we quantitatively evaluated the major drivers(meteorology, foreign emissions, and domestic emissions) of which changes led to change of PM2.5 concen-trations in South Korea during the PM2.5 SMP periods(S1, Dec. 2019-Mar. 2020;S2, Dec. 2020-Mar. 2021;S3, Dec. 2021-Mar. 2022) based on observational data and Community Multiscale Air Quality(CMAQ) simulation results. The nation-wide period mean PM2.5 concentration in S1, S2, and S3 decreased by 8.7, 9.1, and 10.1 mu g/m3 compared to that during Dec. 2018-Mar. 2019. Results show that anthropogenic emission reductions in Northeast Asia decreased the PM2.5 concentration by 5.9, 5.5, and 8.8 mu g/m3 respectively during S1-S3. Note that the effect of the regional emission reduction includes not only domestic emission reduction but also reductions in foreign emission impact. The combined impact of meteorology and foreign emission changes explained 65%, 61% of the total PM2.5 decreases over South Korea and the Seoul Metropolitan Area(SMA) respectively during the S1-S3. Consequently, domestic emission reductions including governmental air quality management plans(i.e., the PM2.5 SMP) and socioeconomic changes(i.e., COVID-19 outbreak) led to PM2.5 concentration decrease in South Korea by 35% during the periods. Among seventeen provinces in South Korea, the impacts of domestic emission reduction on the PM2.5 concentration decreases were as high as 39% and 56% in the SMA and Chungnam where the major emission sources such as transportation, power generation facilities, and industrial complex locate and where the PM2.5 SMP measures were probably penetrated. It implies that the effects of domestic emission controls were meaningful to lower PM2.5concentrations during the periods.

Analysis of the Rate of Confirmed COVID-19 Cases in Seoul and Factors Affecting It Using Big Data Analysis.

Coronavirus disease (COVID-19) is caused by infection with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and presents with mild to severe symptoms. Vaccines have been developed, but COVID-19 persists. Therefore, it is necessary to analyze big data at an early stage to establish an effective infection prevention strategy. To reduce SARS-CoV-2 infection, this study aimed to analyze the infection factors by region within Seoul, Korea and identify the major factors affecting the infection rate. For ease of data aggregation, the study was conducted after a data refinement operation that organized data in the same group into categories, and classified them in detail by specific keywords. Based on the results of this study, if preventive measures are established after identifying the representative infectious factors, periods, and routes of COVID-19 infection, the infection rate could be effectively reduced in the future.

Semiotic fieldwork on chaordic tourism destination image management in Seoul during COVID-19

Tourism destination image management has been impacted by COVID-19 in Seoul, and a chaordic response to social distancing policies are visually evident in its built and inhabited landscape. The purpose of this study is to explore chaordic changes in the urban tourism destination as an effect of social distance, using a structural-social semiotics methodology. Online sampling was combined with naturalistic fieldwork to identify signs where these effects are visually evident. Online research was performed in early 2020 and onsite research was conducted in early 2021. Findings show how signs of the disease changed over time, from idealized representations of prevention, to hastily implemented acts of mitigation. The implications suggest that semiotic methodologies can enable decision makers to visualize the chaordic effects of policy during crisis and to make better structural planning decisions for their unique urban tourism destination to mitigate the conspicuous disappearance of the tourist during times of crisis.

Estimation of the SARS-CoV-2 Virus Inactivation Time Using Spectral Ultraviolet Radiation

Corona Virus Disease 19 pandemic (COVID-19) causes many deaths worldwide, and has enormous impacts on society and economy. The COVID-19 was caused by a new type of coronavirus (Severe Acute Respiratory Syndrome Cornonavirus 2;SARS-CoV-2), which has been found that these viruses can be effectively inactivated by ultraviolet (UV) radiation of 290315 nm. In this study, 90% inactivation time of the SARS-CoV-2 virus was analyzed using ground observation data from Brewer spectrophotometer at Yonsei University, Seoul and simulation data from UVSPEC for the period of 2015-2017 and 2020. Based on 12:00-13:00 noon time, the shortest virus inactivation time were estimated as 13.5 minutes in June and 4.8 minutes in July/August, respectively, under all sky and clear sky conditions. In the diurnal and seasonal variations, SARS-CoV-2 could be inactivated by 90% when exposed to UV radiation within 60 minutes from 10:00 to 14:00, for the period of spring to autumn. However, in winter season, the natural prevention effect was meaningless because the intensity of UV radiation weakened, and the time required for virus inactivation increased. The spread of infectious diseases such as COVID-19 is related to various and complex interactions of several variables, but the natural inactivation of viruses by UV radiation presented in this study, especially seasonal differences, need to be considered as major variables.

Examining the COVID-19 effects on travel behavior using smart IoT sensors: A case study of smart city planning in Gangnam, Seoul

The application of IoT in cities is a critical component in constructing a smart city. Seoul Metropolitan Government began installing IoT sensors known collectively as S-DoT in 2019. S-DoT collects real-time climate and floating population data. This study aims to introduce a smart city planning application in Seoul, to validate the S-DoT application, and to suggest a research framework for using S-DoT data. We analyzed S-DoT collected floating population data to examine travel behavior, volume, and patterns during the COVID-19 pandemic. The result showed that micro-level spatiotemporal analysis was possible using S-DoT data, and we identified different floating population patterns. The panel regression result that explained the effects of urban factors on the floating population revealed that the degree of COVID-19 seems to impact people’s travel behavior significantly. As more S-DoT technologies are planning to be deployed in Seoul, the city will begin to collect more sophisticated real-time data. However, planners and policymakers should be attentive to the issues and limitations of newly installed S-DoT systems and find better strategies to use S-DoT data. © International Journal of Sustainable Building Technology and Urban Development.

Impacts of COVID-19 on Air Quality through Traffic Reduction.

In 2020, the first case of COVID-19 was confirmed in Korea, and social distancing was implemented to prevent its spread. This reduced the movement of people, and changes in air quality were expected owing to reduced emissions. In the present paper, the impact of traffic volume change caused by COVID-19 on air quality in Seoul, Korea, is examined. Two regression analyses were performed using the generalized additive model (GAM), assuming a Gaussian distribution; the relationships between (1) the number of confirmed COVID-19 cases in 2020-2021 and the rate of change in the traffic volume in Seoul, and (2) the traffic volume and the rate of change in the air quality in Seoul from 2016 to 2019 were analyzed. The regression results show that traffic decreased by 0.00431% per COVID-19 case; when traffic fell by 1%, the PM10, PM2.5, CO, NO2, O3, and SO2 concentrations fell by 0.48%, 0.94%, 0.39%, 0.74%, 0.16%, and -0.01%, respectively. This mechanism accounts for air quality improvements in PM10, PM2.5, CO, NO2, and O3 in Seoul during 2020-2021. From these results, the majority of the reduction in pollutant concentrations in 2020-2021 appears to be the result of a long-term declining trend rather than COVID-19.

Correlation Between Social Distancing Levels and Nighttime Light (NTL) during COVID-19 Pandemic in Seoul, South Korea Based on The Day-Night Band (DNB) Onboard The Suomi National Polar-Orbiting Partnership (S-NPP) Satellite

In order to reduce the spread of infection due to COVID-19, South Korea has established a four-step social distancing standard and implemented it by changing the steps based on the rate of confirmed cases. The implementation of social distancing brought about a change in the amount of activity of citizens by limiting social contact such as movement and gathering of people. One of the data that can intuitively confirm this is Night Time Light (NTL). NTL is a variable that can measure the size of the national economy measured using lights captured by satellites, and can be used to understand people's social activities during the night. The NTL visible data is obtained via the Visible Infrared Imaging Radiometer Suite (VIIRS) Day-Night Band (DNB) onboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite. 1023 of Suomi data from 1 January 2019 until 26 October 2021 were collected to generate time series of NTL radiance change over Seoul to analyze the correlation with social distancing policy. The results show that implementing the level of social distancing generally decreased the NTL radiance both in spatial disparities and temporal patterns. The higher level of policy, limiting human activities combined with the low number of people who have been vaccinated and the closure of various facilities. Because of social distancing, the differences in human activities affected the nighttime light during the COVID-19 pandemic, especially in Seoul, South Korea. Therefore, this study can be used as a reference for the government in evaluating and improving policies related to efforts reducing the transmission of COVID-19.

Associations of COVID-19 Knowledge and Risk Perception with the Full Adoption of Preventive Behaviors in Seoul.

This study explores the levels of COVID-19 knowledge, risk perception, and preventive behavior practice in Seoul, to determine whether knowledge and risk perception are significantly associated with the full adoption of preventive behaviors, for the delivery of a customized public campaign to Seoul's citizens. A total of 3000 Seoul residents participated in this study through an online questionnaire survey. They had a mean score of 84.6 for COVID-19 knowledge (range: 0-100 points) and 4.2 (range: 1-7 points) for risk perception. Of the participants, 33.4% practiced full adoption of all three preventive behaviors: hand hygiene, wearing a face mask, and social distancing; wearing a face mask was practiced the most (81.0%). Women significantly adopted these three preventive behaviors more often compared with men. Both COVID-19 knowledge and risk perception were found to be significantly associated with the full adoption of preventive behaviors; however, this association differed by the type of preventive behavior. This indicates that city-level information on the levels of COVID-19 knowledge, risk perception, and preventive behaviors should be clearly and periodically communicated among public officers and healthcare professionals to continually raise the public's awareness of the full adoption of non-pharmaceutical preventive behaviors.

Reduction in urban atmospheric CO2 enhancement in Seoul, South Korea, resulting from social distancing policies during the COVID-19 pandemic.

With the spread of the COVID-19 virus globally, cities worldwide have implemented unprecedented social distancing policies to mitigate infection rates. Many studies have demonstrated that improved air quality and reduced carbon emissions have resulted from the COVID-19 pandemic. Yet, questions remain regarding changes in atmospheric CO2 concentrations because of the complex cycles involving the interaction of CO2 with the natural environment. In this study, we compared the changes in urban CO2 enhancement (△CO2) reflecting the contribution of local CO2 emissions to the atmospheric CO2 in urban areas, according to the intensity of social distancing policies implemented during the COVID-19 pandemic in Seoul, South Korea. We used data from three CO2 ground observation sites in the central area of Seoul and outside the urban area of Seoul. By comparing the urban CO2 concentration in Seoul with that of the background area using two different methods, considering both vertical and horizontal differences in CO2 concentration, we quantified the △CO2 of the pre-COVID-19 period and two COVID-19 periods, during which intensive social distancing policies with different intensities were implemented (Level 1, Level 2.5). During the pre-COVID-19 period, the average △CO2 calculated using the two methods was 24.82 ppm, and it decreased significantly to 16.42 and 14.36 ppm during the Level 1 and Level 2.5 periods, respectively. In addition, the urban contribution of Seoul to atmospheric CO2 concentration decreased from 5.27% during the pre-COVID-19 period to 3.54% and 3.19% during the Level 1 and Level 2.5 periods, respectively. The results indicate that the social distancing policies implemented in Seoul resulted in reduced local CO2 emissions, leading to a reduction in atmospheric CO2 concentration. Interestingly, it also shows that the extent of atmospheric CO2 concentration reduction can be greatly affected by the intensity of policies. Our study suggests that changes in human activity could reduce the urban direct contribution to the background CO2 concentration helping to further mitigate climate change.

Spatial variability in reproduction number and doubling time across two waves of the COVID-19 pandemic in South Korea, February to July, 2020.

OBJECTIVES: In South Korea, 13 745 cases of coronavirus disease (COVID-19) had been reported as of 19 July, 2020. To examine spatiotemporal changes in the transmission potential, we aimed to present regional estimates of the doubling time and reproduction number (Rt) for COVID-19 in the country. METHODS: Daily series of confirmed COVID-19 cases in the most affected regions were extracted from publicly available sources. We employed established mathematical and statistical methods to investigate the time-varying reproduction numbers and doubling time for COVID-19 in Korea. RESULTS: At the regional level, Seoul and Gyeonggi Province experienced the first peak of COVID-19 in early March, followed by a second wave in early June, withRt exceeding 3.0 and mean doubling time ranging from 3.6 to 10.1 days. As of 19 July, 2020, Gyeongbuk Province and Daegu had yet to experience a second wave of the disease. During the first wave, mean Rt for these areas reached 3.5-4.4, and doubling time ranged from 2.8 to 4.6 days. CONCLUSIONS: Our findings support the effectiveness of control measures against COVID-19 in Korea. However, the easing of restrictions that had been imposed by the government in May 2020 facilitated a second wave in the greater Seoul area.