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1.
Risk Management and Healthcare Policy ; 15:1727-1740, 2022.
Article in English | ProQuest Central | ID: covidwho-2039551

ABSTRACT

Purpose: To evaluate the resulting level of fiscal medical and health expenditure in China, and to provide the scientific basis for further improving fiscal medical and health service capacity in China. Patients and Methods: The data envelopment method and Gini coefficient method were used to analyze the efficiency and regional fairness of fiscal medical and health expenditure results by using the relevant provincial and municipal data of China from 2007 to 2019. Results: 1.Overall, from 2007 to 2019, the total expenditure continued to increase, the expenditure efficiency increased first and then decreased, and the expenditure fairness continued to improve. 2. From the perspective of subregions, there are apparent differences between regions in terms of total expenditure, expenditure efficiency, and expenditure fairness, showing a better situation in the central, western, northeast and a lower situation in the east. Conclusion: The overall level of fiscal medical and health expenditure in China shows an upward trend, but there is still much room for improvement. At the same time, there are pronounced regional differences, and the problems of efficiency and fairness coexist among regions. Therefore, in the future, we should increase medical and health investment and enhance the government’s close attention;Improve the expenditure performance appraisal system;Formulate policies according to local conditions and avoid “one size fits all.”.

2.
Journal of Medical Virology ; 19:19, 2022.
Article in English | MEDLINE | ID: covidwho-2034902

ABSTRACT

mRNA vaccines are promising alternatives to conventional vaccines in many aspects. We previously developed a lipopolyplex (LPP)-based mRNA vaccine (SW0123) that demonstrated robust immunogenicity and strong protective capacity against SARS-CoV-2 infection in mice and rhesus macaques. However, the immune profiles and mechanisms of pulmonary protection induced by SW0123 remain unclear. Through high-resolution single-cell analysis, we found that SW0123 vaccination effectively suppressed SARS-CoV-2-induced inflammatory responses by inhibiting the recruitment of pro-inflammatory macrophages and increasing the frequency of polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs). In addition, the apoptotic process in both lung epithelial and endothelial cells was significantly inhibited, which was proposed to be one major mechanism contributing to vaccine-induced lung protection. Cell-cell interaction in the lung compartment was also altered by vaccination. These data collectively unravel the mechanisms by which the SW0123 protects against lung damage caused by SARS-CoV-2 infection. This article is protected by copyright. All rights reserved.

3.
Journal of Infectious Diseases ; 22:22, 2022.
Article in English | MEDLINE | ID: covidwho-2034602

ABSTRACT

BACKGROUND: As of early 2022, the Omicron variants are the predominant circulating lineages globally. Understanding neutralizing antibody responses against Omicron BA.1 and BA.2 following vaccine breakthrough infections will provide insights into BA.2 infectivity and susceptibility to subsequent re-infection. METHODS: Live virus neutralization assays were used to study immunity against Delta and Omicron BA.1 and BA.2 variants in samples from 86 individuals, 24 unvaccinated (27.9%) and 63 vaccinated (72.1%), who were infected with Delta (n = 42, 48.8%) or BA.1 (n = 44, 51.2%). Among the 63 vaccinated individuals, 39 were unboosted (45.3%), while 23 were boosted (26.7%). RESULTS: In unvaccinated infections, neutralizing antibodies (nAbs) against the three variants were weak or undetectable, except against Delta for Delta-infected individuals. Both Delta and BA.1 breakthrough infections resulted in strong nAb responses against ancestral wild-type and Delta lineages, but moderate nAb responses against BA.1 and BA.2, with similar titers between unboosted and boosted individuals. Antibody titers against BA.2 were generally higher than those against BA.1 in breakthrough infections. CONCLUSIONS: These results underscore the decreased immunogenicity of BA.1 as compared to BA.2, insufficient neutralizing immunity against BA.2 in unvaccinated individuals, and moderate to strong neutralizing immunity induced against BA.2 in Delta and BA.1 breakthrough infections.

4.
European Respiratory Journal ; 14:14, 2022.
Article in English | MEDLINE | ID: covidwho-2029683

ABSTRACT

BACKGROUND: Patients who present to an emergency department with respiratory symptoms are often conservatively triaged in favour of hospitalization. We sought to determine if an inflammatory biomarker panel that identifies the host response better predicts hospitalization in order to improve the precision of clinical decision-making in the emergency department. PATIENTS AND METHODS: From April 2020 to March 2021, plasma samples of 641 patients with symptoms of respiratory illness were collected from emergency departments in an international multicentre study: Canada (n=310), Italy (n=131), and Brazil (n=200). Patients were followed prospectively for 28 days. Subgroup analysis was conducted on confirmed COVID-19 patients (n=245). An inflammatory profile was determined using a rapid, 50-minute, biomarker panel: Rapid Acute Lung Injury Diagnostic (RALI-Dx), which measures IL-6, IL-8, IL-10, sTNFR1, and sTREM1. RESULTS: RALI-Dx biomarkers were significantly elevated in patients who required hospitalization across all three sites. A machine learning algorithm that was applied to predict hospitalization using RALI-Dx biomarkers had an area under the receiver operating characteristic curve of 76+/-6% (Canada), 84+/-4% (Italy), and 86+/-3% (Brazil). Model performance in COVID-19 patients was 82+/-3% and 87+/-7% for patients with a confirmed pneumonia diagnosis. CONCLUSIONS: The rapid diagnostic biomarker panel accurately identified the need for inpatient care in patients presenting with respiratory symptoms, including COVID-19. The RALI-Dx test is broadly and easily applicable across many jurisdictions and represents an important diagnostic adjunct to advance emergency department decision-making protocols.

5.
Fractals-Complex Geometry Patterns and Scaling in Nature and Society ; 30(05), 2022.
Article in English | Web of Science | ID: covidwho-2020335

ABSTRACT

Mathematical modeling can be utilized to find out how the coronavirus spreads within a population. Hence, considering models that can precisely describe natural phenomena is of crucial necessity. Besides, although one of the most significant benefits of mathematical modeling is designing optimal policies for battling the disease, there are a few studies that employ this beneficial aspect. To this end, this study aims to design optimal management policies for the novel coronavirus disease 2019 (COVID-19). This is a pioneering research that designs optimal policies based on multi-objective evolutionary algorithms for control of the fractional-order model of the COVID-19 outbreak. First, a fractional-order model of the disease dynamic is presented. The impacts of the fractional derivative's value on the modeling and forecasting of the disease spread are considered. After that, a multi-objective optimization problem is proposed by considering the rate of communication, the transition of symptomatic infected class to the quarantined one, and the release of quarantined uninfected individuals. Numerical results clearly corroborate that by solving the proposed multi-objective problem, governments can control the massive disease outbreak while economic factors have reasonable values that prevent economic collapse.

6.
Bioinformatics ; 2022.
Article in English | PubMed | ID: covidwho-2017735

ABSTRACT

MOTIVATION: A common experimental output in biomedical science is a list of genes implicated in a given biological process or disease. The gene lists resulting from a group of studies answering the same, or similar, questions can be combined by ranking aggregation methods to find a consensus or a more reliable answer. Evaluating a ranking aggregation method on a specific type of data before using it is required to support the reliability since the property of a dataset can influence the performance of an algorithm. Such evaluation on gene lists is usually based on a simulated database because of the lack of a known truth for real data. However, simulated datasets tend to be too small compared to experimental data and neglect key features, including heterogeneity of quality, relevance and the inclusion of unranked lists. RESULTS: In this study, a group of existing methods and their variations which are suitable for meta-analysis of gene lists are compared using simulated and real data. Simulated data was used to explore the performance of the aggregation methods as a function of emulating the common scenarios of real genomic data, with various heterogeneity of quality, noise level, and a mix of unranked and ranked data using 20000 possible entities. In addition to the evaluation with simulated data, a comparison using real genomic data on the SARS-CoV-2 virus, cancer (NSCLC), and bacteria (macrophage apoptosis) was performed. We summarise the results of our evaluation in a simple flowchart to select a ranking aggregation method, and in an automated implementation using the meta-analysis by information content (MAIC) algorithm to infer heterogeneity of data quality across input data sets. AVAILABILITY: The code for simulated data generation and running edited version of algorithms: https://github.com/baillielab/comparison_of_RA_methods.Code to perform an optimal selection of methods based on the results of this review, using the MAIC algorithm to infer the characteristics of an input dataset, can be downloaded here: https://github.com/baillielab/maic. An online service for running MAIC: https://baillielab.net/maic. SUPPLEMENTARY INFORMATION: Supplementary file 1 is available at Bioinformatics online. Supporting data 1-7 (supporting results and collected real genomic data) are available on GitHub at: https://github.com/baillielab/comparison_of_RA_methods.

7.
Journal of Xi'an Jiaotong University (Medical Sciences) ; 43(5):653-657, 2022.
Article in Chinese | EMBASE | ID: covidwho-2010480

ABSTRACT

Objective: To establish a three-in-one smart hospital characterized with smart service, smart medical care and smart management to improve the hospital's ability to prevent and control and respond to coronavirus disease 2019 (COVID-19). Methods: Combined with the core needs of normalized prevention and control of the epidemic, the overall structure of the smart hospital was established. Emerging technologies were used as the means to strengthen system integration and security as the basis, and the interconnection and electronic medical record project were the starting point to carry out 31 projects of information system construction and integration. Results: Through the construction of smart service, a service mechanism that integrates online and offline services and covers the whole process of diagnosis and treatment has been realized. Through the construction of integrated physician workstations, smart nursing, medical quality control and other platforms with electronic medical records as the core, the clinical diagnosis and treatment capabilities have been improved. Through the improvement and optimization of the information system, the capacity of the hospital's emergency management of the epidemic has been effectively improved. Conclusion: The construction of smart hospitals can provide a solid guarantee for the prevention and control of COVID-19, but it also faces many problems. The construction of smart service needs the strong support of the competent government departments, the integration of smart medical care needs to be further strengthened, and smart management needs to be further strengthened.

8.
Biomed Eng Online ; 21, 2022.
Article in English | PMC | ID: covidwho-2009406

ABSTRACT

Background: With the spread of COVID-19, telemedicine has played an important role, but tele-auscultation is still unavailable in most countries. This study introduces and tests a tele-auscultation system (Stemoscope) and compares the concordance of the Stemoscope with the traditional stethoscope in the evaluation of heart murmurs. Methods: A total of 57 patients with murmurs were recruited, and echocardiographs were performed. Three cardiologists were asked to correctly categorize heart sounds (both systolic murmur and diastolic murmur) as normal vs. abnormal with both the Stemoscope and a traditional acoustic stethoscope under different conditions. Firstly, we compared the in-person auscultation agreement between Stemoscope and the conventional acoustic stethoscope. Secondly, we compared tele-auscultation (recorded heart sounds) agreement between Stemoscope and acoustic results. Thirdly, we compared both the Stemoscope tele-auscultation results and traditional acoustic stethoscope in-person auscultation results with echocardiography. Finally, ten other cardiologists were asked to complete a qualitative questionnaire to assess their experience using the Stemoscope. Results: For murmurs detection, the in-person auscultation agreement between Stemoscope and the acoustic stethoscope was 91% (p = 0.67). The agreement between Stemoscope tele-auscultation and the acoustic stethoscope in-person auscultation was 90% (p = 0.32). When using the echocardiographic findings as the reference, the agreement between Stemoscope (tele-auscultation) and the acoustic stethoscope (in-person auscultation) was 89% vs. 86% (p = 1.00). The system evaluated by ten cardiologists is considered easy to use, and most of them would consider using it in a telemedical setting. Conclusion: In-person auscultation and tele-auscultation by the Stemoscope are in good agreement with manual acoustic auscultation. The Stemoscope is a helpful heart murmur screening tool at a distance and can be used in telemedicine.

9.
Clinical & Translational Immunology ; 11(8), 2022.
Article in English | Web of Science | ID: covidwho-2003593

ABSTRACT

Objective. Despite the high vaccine efficacy of mRNA COVID-19 vaccines, there are individuals who developed excessive reactogenic and/or allergic responses after the first mRNA dose and were considered ineligible for further mRNA doses. CoronaVac, an inactivated SARS-CoV-2 vaccine, is recommended in Singapore as an alternative. Methods. Individuals, ineligible for further mRNA vaccines (BNT162b2 or mRNA-1273) because of excessive reactive responses to prime mRNA vaccination, were recruited and offered two doses of CoronaVac as booster vaccination 38-224 days post their mRNA vaccine dose. Individuals who did not develop any excessive reactive responses after the prime mRNA vaccination were also recruited and given another mRNA vaccine as booster vaccination. Blood samples were collected at days 0, 21 and 90 post first CoronaVac dose and mRNA dose, respectively, for analysis. Results. We showed that two CoronaVac booster doses induced specific immunity in these mRNA vaccine-primed individuals. Although the spike-specific antibody response was lower, their memory B cell response against the receptor-binding domain (RBD) of the spike protein was similar, compared with individuals who received two BNT162b2 injections. The spike-specific memory T cell response also increased following CoronaVac booster doses. However, specific immunity against the Omicron variant was low, similar to individuals with two BNT162b2 doses. Conclusion. Our findings showed that while mRNA vaccine-primed individuals can opt for two subsequent doses of CoronaVac, an additional dose may be necessary to achieve protection, especially against newly emerging immune escape variants such as Omicron.

10.
Frontiers in Environmental Science ; 10, 2022.
Article in English | Scopus | ID: covidwho-1993784

ABSTRACT

Shared mobility is becoming increasingly popular worldwide, and travelers show more complex choice preferences during the post-pandemic era. This study explored the role of shared mobility in the context of coronavirus disease (COVID-19) by comparing the travel mode choice behavior with and without shared mobility. Considering the shared mobility services of ride-hailing, ride-sharing, car-sharing, and bike-sharing, the stated preference survey was designed, and the mixed logit model with panel data was applied. The results show that if shared mobility is absent, approximately 50% of motorized mobility users and 84.62% of bike-sharing adopters will switch to using private car and public transport, respectively. The perceived pandemic severity positively affects the usage of car-sharing and bike-sharing, while it negatively affects the ride-sharing usage. Under different pandemic severity levels, the average probabilities of private car choice with and without shared mobility are 38.70 and 57.77%, respectively;thus, shared mobility would alleviate the dependence on private car in post-pandemic future. It also helps to decrease the on-road carbon emissions when the pandemic severity is lower than 53. These findings suggest policymakers to maintain the shared mobility ridership and simultaneously contain the pandemic. Additionally, pricing discount and safety enhancement are more effective than reducing detour time to protect ride-sharing against COVID-19. Copyright © 2022 Zhang, Shao, Wang, Huang, Mi and Zhuang.

12.
Economic Change and Restructuring ; 2022.
Article in English | Scopus | ID: covidwho-1982218

ABSTRACT

Carbon pricing is one of the key policy tools in the green recovery of the post-COVID-19 era. As linkages among ETSs worldwide are future trend, the carbon price spillover effects among markets are needed to be explored. This study examines the spillover effects and dynamic linkages of carbon prices using the example of China’s pilot carbon markets during 2015–2019, which are seemingly independent carbon markets. A structural vector error correction model and an improved directed acyclic graph approach are applied. The main results are as follows. First, the linkages among the five pilots demonstrate features of “two small-world networks.” Specifically, these are the Guangdong and Hubei network and the Beijing, Shenzhen and Shanghai network. Second, Shenzhen, Beijing and Hubei ranked as the top three pilots in terms of external spillover effect, accounting for 36.25%, 29.76%, and 25.59%, respectively. Second, Guangdong pilot has increasing influence on the Hubei, Shenzhen and Beijing pilots. Third, trading activities are positive contributors to the spillover, while the allowance illiquidity ratio and volatility are negative factors. The findings imply that to retain an expectable abatement costs in achieving the climate goals in green recovery, carbon prices in other potentially related markets should be considered by the policy maker in addition to its own policy design. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

13.
Journal of Transport & Health ; 25:1, 2022.
Article in English | Web of Science | ID: covidwho-1976043
14.
China Oncology ; 32(6):499-511, 2022.
Article in Chinese | Scopus | ID: covidwho-1964893

ABSTRACT

[] The corona virus disease 2019 (COVID-19) pandemic continues to severely impact healthcare systems around the world, and patients with cancer are even worse affected owing to compromised immune status and greater exposure risk. In the present review, we retrieved the relevant literature including guidelines and consensuses directly related to the purpose of this study from the PubMed database, and then summarized the research data on cancer and COVID-19, aiming to discuss the personal protection, systemic anti-cancer therapy, outcome of co-infection, and the clinical management strategy in this population. We found that patients with malignant tumors had a higher chance of suffering COVID-19, co-infection of whom had an even worse clinical prognosis, especially for those with lung cancer or hematologic cancers. Systemic chemotherapy may delay the clearance of severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) virus of human body, and thus have a negative impact on the clinical outcomes of COVID-19, while certain endocrine therapy and targeted drugs having limited or no impact. There has been no sufficient evidence for the impact of immune checkpoint therapy on the outcomes of COVID-19 till now. It is of great value to strengthen the personal protection of patients, adjust the anti-tumor treatments rationally and optimize the clinical management processes. © 2022, Editorial Office of China Oncology. All rights reserved.

15.
IEEE Transactions on Artificial Intelligence ; 3(3):323-343, 2022.
Article in English | Scopus | ID: covidwho-1922771

ABSTRACT

Coronavirus disease 2019 (COVID-19) continues to pose a great challenge to the world since its outbreak. To fight against the disease, a series of artificial intelligence (AI) techniques are developed and applied to real-world scenarios such as safety monitoring, disease diagnosis, infection risk assessment, and lesion segmentation of COVID-19 CT scans. The coronavirus epidemics have forced people wear masks to counteract the transmission of virus, which also brings difficulties to monitor large groups of people wearing masks. In this article, we primarily focus on the AI techniques of masked facial detection and related datasets. We survey the recent advances, beginning with the descriptions of masked facial detection datasets. A total of 13 available datasets are described and discussed in detail. Then, the methods are roughly categorized into two classes: conventional methods and neural network-based methods. The conventional methods are usually trained by boosting algorithms with hand-crafted features, which accounts for a small proportion. Neural network-based methods are further classified as three parts according to the number of processing stages. Representative algorithms are described in detail, coupled with some typical techniques that are described briefly. Finally, we summarize the recent benchmarking results, give the discussions on the limitations of datasets and methods, and expand future research directions. To our knowledge, this is the first survey about masked facial detection methods and datasets. Hopefully our survey could provide some help to fight against epidemics. © 2020 IEEE.

16.
Iet Biometrics ; : 12, 2022.
Article in English | English Web of Science | ID: covidwho-1882778

ABSTRACT

Biometrics are the among most popular authentication methods due to their advantages over traditional methods, such as higher security, better accuracy and more convenience. The recent COVID-19 pandemic has led to the wide use of face masks, which greatly affects the traditional face recognition technology. The pandemic has also increased the focus on hygienic and contactless identity verification methods. The forearm is a new biometric that contains discriminative information. In this paper, we proposed a multimodal recognition method that combines the veins and geometry of a forearm. Five features are extracted from a forearm Near-Infrared (Near-Infrared) image: SURF, local line structures, global graph representations, forearm width feature and forearm boundary feature. These features are matched individually and then fused at the score level based on the Improved Analytic Hierarchy Process-entropy weight combination. Comprehensive experiments were carried out to evaluate the proposed recognition method and the fusion rule. The matching results showed that the proposed method can achieve a satisfactory performance.

17.
Law, Technology and Humans ; 3(1):35-50, 2021.
Article in English | Scopus | ID: covidwho-1876037

ABSTRACT

Governments worldwide view contact tracing as a key tool to mitigate COVID-19 community transmission. Contact tracing investigations are time consuming and labour intensive. Mobile phone location tracking has been a new data-driven option to potentially obviate investigative inefficiencies. However, using mobile phone apps for contact tracing purposes gives rise to complex privacy issues. Governmental presentation and implementation of contact tracing apps, therefore, requires careful and sensitive delivery of a coherent policy position to establish citizen trust, which is an essential component of uptake and use. This article critically examines the Australian Government’s initial implementation of the COVIDSafe app. We outline a series of implementation misalignments that juxtapose an underpinning regulatory rationality predicated on the implementation of information privacy law protections with rhetorical campaigns to reinforce different justifications for the app’s use. We then examine these implementation misalignments from Mayer and colleagues’ lens of trustworthiness (1995) and its three core domains: ability, integrity and benevolence. The three domains are used to examine how the Australian Government’s implementation strategy provided a confused understanding of processes that enhance trustworthiness in the adoption of new technologies. In conclusion, we provide a better understanding about securing trustworthiness in new technologies through the establishment of a value consensus that requires alignment of regulatory rationales and rhetorical campaigning. © The Author/s 2021

18.
Fractals ; : 1, 2022.
Article in English | Academic Search Complete | ID: covidwho-1874693

ABSTRACT

Mathematical modeling can be utilized to find out how the coronavirus spreads within a population. Hence, considering models that can precisely describe natural phenomena is of crucial necessity. Besides, although one of the most significant benefits of mathematical modeling is designing optimal policies for battling the disease, there are a few studies that employ this beneficial aspect. To this end, this study aims to design optimal management policies for the novel coronavirus disease 2019 (COVID-19). This is a pioneering research that designs optimal policies based on multi-objective evolutionary algorithms for control of the fractional-order model of the COVID-19 outbreak. First, a fractional-order model of the disease dynamic is presented. The impacts of the fractional derivative’s value on the modeling and forecasting of the disease spread are considered. After that, a multi-objective optimization problem is proposed by considering the rate of communication, the transition of symptomatic infected class to the quarantined one, and the release of quarantined uninfected individuals. Numerical results clearly corroborate that by solving the proposed multi-objective problem, governments can control the massive disease outbreak while economic factors have reasonable values that prevent economic collapse. [ FROM AUTHOR] Copyright of Fractals is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

19.
Modern Pathology ; 35(SUPPL 2):815-816, 2022.
Article in English | EMBASE | ID: covidwho-1857624

ABSTRACT

Background: Although there are many studies examining the clinical outcomes of women and their infants diagnosed with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, during pregnancy, the reasons causing the possible adverse outcomes remain unclear1. This study examines placental pathology from women who contracted COVID-19 during pregnancy at this university hospital institution. Design: This study was centered around all 19 placenta specimens from patients infected with COVID-19 at this university hospital. The American College of Obstetricians and Gynecologists (ACOG) allow for the judgement of the Obstetrics physician to be the predominant factor in the decision of sending the placenta specimen for pathology evaluation. Therefore ACOG and CRICO (a risk retention group for medical practitioners) work in conjunction to recommend that placentas be sent for pathology evaluation when clinically indicated. All 19 placenta specimens that were submitted in this study met at least one of these recommendations and therefore 19 age matched controls without COVID-19 infection were reviewed in order to outline any significant clinical trends. The age matched controls were selected within the same time frame as the COVID-19 specimens, which was June 2020 to August 2021. Results: The interval of initial COVID-19 diagnosis and time of placenta evaluation was documented in each case, with the median time interval being 2 days (minimum 1day to maximum 91 days). The gestational age for each patient was calculated, and the average gestational age was a full term pregnancy of 37.2 weeks. 90% of the patients were identified to be of Hispanic ethnicity and heritage, while the other two patients were of Caucasian descent. 63% of the placental weights from the COVID specimens were 25th percentile or lower, whereas only 21% of the age matched controls were 25th percentile or lower. 63% of the cases were recognized to contain histopathological abnormalities, 10.5% in aged matched controls. 4 cases were found to have intra-placental infarction (figure 1), 2 cases were identified to have chorangiosis, 1 case of villous ischemic change, 1 case of decidual laminar necrosis, 1 case of meconium, and 2 cases of acute chorioamnionitis. Conclusions: In this study on average the placenta weight was identified to be lower than age matched controls and placental abnormalities were identified more often in patients infected with COVID 19 (63% vs. 10.5%). (Table Presented).

20.
Jiaotong Yunshu Xitong Gongcheng Yu Xinxi/Journal of Transportation Systems Engineering and Information Technology ; 22(2):186-196 and 205, 2022.
Article in Chinese | Scopus | ID: covidwho-1847860

ABSTRACT

To analyze the impact of COVID-19 on the travel mode choice behavior with diverse shared mobility services, this study designed the stated preference (SP) questionnaire for the multi-modal transportation system which include conventional travel modes, ride hailing, ride sharing, car sharing, and bike sharing. The mixed Logit models with panel data were proposed to investigate the travel mode choices before and during COVID-19. The influence differences of explanatory variables are compared, and the joint effects of perceived pandemic severity and mode choice inertia are examined. Based on the elasticity analysis, the mode choice preferences are predicted corresponding to different management policies under COVID-19 pandemic. The results indicate that the perception to pandemic severity has significant impacts on the ridership of ride sharing and car sharing, and the mode choice inertia obviously affects the usage of ride hailing, car sharing, and bike sharing. When the perceived pandemic severity reduces to 30%~50%, the strategy of increasing parking charge to 1.6~3.0 times would reduce the usage of private car to pre-pandemic condition, and the car sharing with lower close contact risk could become a main substitute. When the perceived pandemic severity is higher than 60%, the strategy of increasing the travel safety of ride sharing to 1.4~3.6 times would improve the ridership. Copyright © 2022 by Science Press.

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