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Etemad K, Mohseni P, Shojaei S, Mousavi SA, Taherkhani S, Fallah Atatalab F, Ghajari H, Hashemi Nazari SS, Karami M, Izadi N, Hajipour M. Non-Pharmacologic Interventions in COVID-19 Pandemic Management; a Systematic Review. ARCHIVES OF ACADEMIC EMERGENCY MEDICINE 2023; 11:e52. [PMID: 37671267 PMCID: PMC10475751 DOI: 10.22037/aaem.v11i1.1828] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 09/07/2023]
Abstract
Introduction Different countries throughout the world have adopted non-pharmacologic interventions to reduce and control SARS - CoV-2. In this systematic approach, the impact of non-pharmacologic interventions in management of COVID-19 pandemic was assessed. Methods Following Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines, systematic search was carried out on the basis of a search strategy on PubMed, Web of Science, Scopus, and WHO databases on COVID-19. The impact of travel ban, personal protective equipment, distancing, contact tracing, school closure, and social distancing and the combined effect of interventions on COVID-19 were assessed. Results Of the 14,857 articles found, 44 were relevant. Studies in different countries have shown that various non-pharmacological interventions have been used during the COVID-19 pandemic. The travel ban, either locally or internationally in most of the countries, movement restriction, social distancing, lockdown, Personal Protective Equipment (PPE), quarantine, school closure, work place closure, and contact tracing had a significant impact on the reduction of mortality or morbidity of COVID-19. Conclusion Evidence shows that the implementation of non-pharmacologic interventions (NPIs), for this study suggests that the effectiveness of any NPI alone is probably limited, thus, a combination of various actions, for example, social distancing, isolation, and quarantine, distancing in the workplace and use of personal protective equipment, is more effective in reducing COVID-19.
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Affiliation(s)
- Koorosh Etemad
- Department of Epidemiology, School of Public Health and safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Parisa Mohseni
- Fertility and Infertility Research Center, Hormozgan University of Medical Sciences, Bandar Abbas, Iran
| | - Saeideh Shojaei
- Department of Epidemiology, School of Public Health and safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Seyed Ali Mousavi
- Department of Public Health, Shoushtar Faculty of Medical Science, Shoushtar, Iran
| | - Shakiba Taherkhani
- Department of Epidemiology, School of Public Health and safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Fatemeh Fallah Atatalab
- Department of Epidemiology, School of Public Health and safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Hadis Ghajari
- Department of Epidemiology, School of Public Health and safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Seyed Saeed Hashemi Nazari
- Department of Epidemiology, School of Public Health and safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Manoochehr Karami
- Department of Epidemiology, School of Public Health and safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Neda Izadi
- Department of Epidemiology, School of Public Health and safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Mahmoud Hajipour
- Pediatric Gastroenterology, Hepatology and Nutrition Research Center, Research Institute for Children’s Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran
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Boselli PM, Soriano JM. COVID-19 in Italy: Is the Mortality Analysis a Way to Estimate How the Epidemic Lasts? BIOLOGY 2023; 12:biology12040584. [PMID: 37106784 PMCID: PMC10135801 DOI: 10.3390/biology12040584] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 03/25/2023] [Accepted: 04/06/2023] [Indexed: 04/29/2023]
Abstract
When an epidemic breaks out, many health, economic, social, and political problems arise that require a prompt and effective solution. It would be useful to obtain all information about the virus, including epidemiological ones, as soon as possible. In a previous study of our group, the analysis of the positive-alive was proposed to estimate the epidemic duration. It was stated that every epidemic ends when the number of positive-alive (=infected-healed-dead) glides toward zero. In fact, if with the contagion everyone can enter the epidemic phenomenon, only by healing or dying can they get out of it. In this work, a different biomathematical model is proposed. A necessary condition for the epidemic to be resolved is that the mortality reaches the asymptotic value, from there, remains stable. At that time, the number of positive-alive must also be close to zero. This model seems to allow us to interpret the entire development of the epidemic and highlight its phases. It is also more appropriate than the previous one, especially when the spread of the infection is so rapid that the increase in live positives is staggering.
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Affiliation(s)
- Pietro M Boselli
- Group of Nutritional Modelling Biology, Departament de Biosciencies, University of Milan, 20122 Milan, Italy
| | - Jose M Soriano
- Food & Health Lab, Institute of Materials Science, University of Valencia, 46980 Paterna, Spain
- Joint Research Unit on Endocrinology, Nutrition and Clinical Dietetics, Health Research Institute La Fe-University of Valencia, 46026 Valencia, Spain
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Model Development and Prediction of Covid-19 Pandemic in Bangladesh with Nonlinear Incident. IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY. TRANSACTION A, SCIENCE 2023:1-10. [PMID: 36643978 PMCID: PMC9826761 DOI: 10.1007/s40995-022-01410-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/28/2022] [Accepted: 12/23/2022] [Indexed: 01/17/2023]
Abstract
We introduce a SEIRD compartmental model to analyze the dynamics of the pandemic in Bangladesh. The multi-wave patterns of the new infective in Bangladesh from the day of the official confirmation to August 15, 2021, are simulated in the proposed SEIRD model. To solve the model equations numerically, we use the RK-45 method. Primarily, we establish some theorems including local and global stability for the proposed model. The analysis shows that the death curve simulated by the model provides a very good agreement with the officially confirmed death data for the Covid-19 pandemic in Bangladesh. Furthermore, the proposed model estimates the duration and peaks of Covid-19 in Bangladesh which are compared with the real data.
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Modeling Dynamic Responses to COVID-19 Epidemics: A Case Study in Thailand. Trop Med Infect Dis 2022; 7:tropicalmed7100303. [PMID: 36288044 PMCID: PMC9612314 DOI: 10.3390/tropicalmed7100303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 09/26/2022] [Accepted: 10/12/2022] [Indexed: 11/05/2022] Open
Abstract
Quantifying the effects of control measures during the emergence and recurrence of SARS-CoV-2 poses a challenge to understanding the dynamic responses in terms of effectiveness and the population’s reaction. This study aims to estimate and compare the non-pharmaceutical interventions applied in the first and second outbreaks of COVID-19 in Thailand. We formulated a dynamic model of transmission and control. For each outbreak, the time interval was divided into subintervals characterized by epidemic events. We used daily case report data to estimate the transmission rates, the quarantine rate, and its efficiency by the maximum likelihood method. The duration-specific control reproduction numbers were calculated. The model predicts that the reproduction number dropped by about 91% after the nationwide lockdown in the first wave. In the second wave, after a high number of cases had been reported, the reproduction number decreased to about 80% in the next phase, but the spread continued. The estimated value was below the threshold in the last phase. For both waves, successful control was mainly induced by decreased transmission rate, while the explicit quarantine measure showed less effectiveness. The relatively weak control measure estimated by the model may have implications for economic impact and the adaptation of people.
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Behavioral Economics in the Epidemiology of the COVID-19 Pandemic: Theory and Simulations. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19159557. [PMID: 35954908 PMCID: PMC9368471 DOI: 10.3390/ijerph19159557] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Revised: 07/29/2022] [Accepted: 07/31/2022] [Indexed: 02/01/2023]
Abstract
We provide a game-theoretical epidemiological model for the COVID-19 pandemic that takes into account that: (1) asymptomatic individuals can be contagious, (2) contagion is behavior-dependent, (3) behavior is determined by a game that depends on beliefs and social interactions, (4) there can be systematic biases in the perceptions and beliefs about the pandemic. We incorporate lockdown decisions by the government into the model. The citizens’ and government’s beliefs can exhibit several biases that we discuss from the point of view of behavioral economics. We provide simulations to understand the effect of lockdown decisions and the possibility of “nudging” citizens in the right direction by improving the accuracy of their beliefs.
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Waewwab P, Pan-ngum W, Siri S, Bhopdhornangkul B, Mahikul W. Knowledge, Attitudes, and Practices Regarding “New Normal” Guidelines and Quality of Life Among Thai People During the COVID-19 Outbreak: An Online Cross-Sectional Survey. Front Public Health 2022; 10:914417. [PMID: 35874992 PMCID: PMC9301185 DOI: 10.3389/fpubh.2022.914417] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 06/06/2022] [Indexed: 12/23/2022] Open
Abstract
In Thailand, strict prevention and control strategies have been implemented to mitigate the rapid spread of coronavirus disease 2019 (COVID-19). “New normal” guidelines and a series of mobile health applications have been introduced by the healthcare sector and implemented to aid the disease control monitoring and prevention of widespread outbreaks. This study aimed to assess the knowledge, attitudes, and practices (KAP) regarding “new normal” guidelines and quality of life (QOL) among Thai people during the COVID-19 outbreak, and to determine the association between KA, QOL, and practices. An online cross-sectional survey was conducted from 7 June to 12 September 2021 among Thai people in Public Health Region 6 aged ≥ 18 years old. Of the 506 survey participants, 80.3% were female, and 65.0% were 25–59 years old. The survey revealed that 52.2% of participants were classified as having more accurate knowledge, 58.9% were classified as having more positive attitudes, and 80.8% were classified as having more frequent practices regarding “new normal” guidelines, and 54.7% had high QOL. Of the participants, 93.7% agreed that “people who have been fully vaccinated should wear a mask while outside,” and 95.5% wore a face mask outdoors in crowded places. However, 60.9% of participants misunderstood some details regarding online applications for contact tracing and vaccination services, 44.2% felt that these applications were difficult to use, and 33.4% rarely or never downloaded or used these applications. In logistic regression analyses, accurate knowledge of COVID-19 was associated with higher education, being a government employee, monthly family income > 30,000 Thai Baht, and regular use of social media. More positive attitudes regarding “new normal” guidelines and high QOL were associated with positive practices. High QOL was associated with older age, and higher education. Enhancement of attitudes and QOL is also important for improving practices in the general population during the COVID-19 pandemic. Significant factors identified in KAP will be crucial for developing effective prevention and control programs to mitigate the spread of COVID-19. To implement mobile health applications effectively, more work is required to improve the ease of use and promotion strategies.
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Affiliation(s)
- Pathavee Waewwab
- Division of Communicable Disease Control, Rayong Provincial Public Health Office, Rayong, Thailand
| | - Wirichada Pan-ngum
- Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
- Department of Tropical Hygiene, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
| | - Sukhontha Siri
- Department of Epidemiology, Faculty of Public Health, Mahidol University, Bangkok, Thailand
| | - Bhophkrit Bhopdhornangkul
- Infectious of Disease Control and Entomology Section, Division of Health Promotion and Preventive Medicine, Royal Thai Army Medical Crops, Bangkok, Thailand
| | - Wiriya Mahikul
- Princess Srisavangavadhana College of Medicine, Chulabhorn Royal Academy, Bangkok, Thailand
- *Correspondence: Wiriya Mahikul
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7
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Wilasang C, Jitsuk NC, Sararat C, Modchang C. Reconstruction of the transmission dynamics of the first COVID-19 epidemic wave in Thailand. Sci Rep 2022; 12:2002. [PMID: 35132106 PMCID: PMC8821624 DOI: 10.1038/s41598-022-06008-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Accepted: 01/19/2022] [Indexed: 12/14/2022] Open
Abstract
Thailand was the first country reporting the first Coronavirus disease 2019 (COVID-19) infected individual outside mainland China. Here we delineated the course of the COVID-19 outbreak together with the timeline of the control measures and public health policies employed by the Thai government during the first wave of the COVID-19 outbreak in Thailand. Based on the comprehensive epidemiological data, we reconstructed the dynamics of COVID-19 transmission in Thailand using a stochastic modeling approach. Our stochastic model incorporated the effects of individual heterogeneity in infectiousness on disease transmission, which allows us to capture relevant features of superspreading events. We found that our model could accurately capture the transmission dynamics of the first COVID-19 epidemic wave in Thailand. The model predicted that at the end of the first wave, the number of cumulative confirmed cases was 3091 (95%CI: 2782-3400). We also estimated the time-varying reproduction number (Rt) during the first epidemic wave. We found that after implementing the nationwide interventions, the Rt in Thailand decreased from the peak value of 5.67 to a value below one in less than one month, indicating that the control measures employed by the Thai government during the first COVID-19 epidemic wave were effective. Finally, the effects of transmission heterogeneity and control measures on the likelihood of outbreak extinction were also investigated.
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Affiliation(s)
- Chaiwat Wilasang
- Biophysics Group, Department of Physics, Faculty of Science, Mahidol University, Bangkok, 10400, Thailand
| | - Natcha C Jitsuk
- Biophysics Group, Department of Physics, Faculty of Science, Mahidol University, Bangkok, 10400, Thailand
| | - Chayanin Sararat
- Biophysics Group, Department of Physics, Faculty of Science, Mahidol University, Bangkok, 10400, Thailand
| | - Charin Modchang
- Biophysics Group, Department of Physics, Faculty of Science, Mahidol University, Bangkok, 10400, Thailand. .,Centre of Excellence in Mathematics, CHE, Bangkok, 10400, Thailand. .,Thailand Center of Excellence in Physics, CHE, 328 Si Ayutthaya Road, Bangkok, 10400, Thailand.
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Model Predictive Control of COVID-19 Pandemic with Social Isolation and Vaccination Policies in Thailand. AXIOMS 2021. [DOI: 10.3390/axioms10040274] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
This study concerns the COVID-19 pandemic in Thailand related to social isolation and vaccination policies. The behavior of disease spread is described by an epidemic model via a system of ordinary differential equations. The invariant region and equilibrium point of the model, as well as the basic reproduction number, are also examined. Moreover, the model is fitted to real data for the second wave and the third wave of the pandemic in Thailand by a sum square error method in order to forecast the future spread of infectious diseases at each time. Furthermore, the model predictive control technique with quadratic programming is used to investigate the schedule of preventive measures over a time horizon. As a result, firstly, the plan results are proposed to solve the limitation of ICU capacity and increase the survival rate of patients. Secondly, the plan to control the outbreak without vaccination shows a strict policy that is difficult to do practically. Finally, the vaccination plan significantly prevents disease transmission, since the populations who get the vaccination have immunity against the virus. Moreover, the outbreak is controlled in 28 weeks. The results of a measurement strategy for preventing the disease are examined and compared with a control and without a control. Thus, the schedule over a time horizon can be suitably used for controlling.
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9
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Sun Q, McMahon DE, Ugwu-Dike PO, Sun Q, Tang K, Zhang H, Suchonwanit P, Oh CC, Chong AH, Willems A, Galván C, Dodiuk-Gad RP, Fantini F, Recalcati S, Avancini J, Miyamoto D, Sanches JA, Raboobee N, Bravo F, Freeman EE. How Coronavirus Disease 2019 Changed Dermatology Practice in 1 Year Around the World: Perspectives from 11 Countries. Dermatol Clin 2021; 39:639-651. [PMID: 34556253 PMCID: PMC8452267 DOI: 10.1016/j.det.2021.05.014] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Affiliation(s)
- Qisi Sun
- Department of Dermatology, Yale University School of Medicine, 333 Cedar Street, New Haven, CT 06510, USA
| | - Devon E McMahon
- Department of Dermatology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA 02114, USA
| | - Pearl O Ugwu-Dike
- Department of Dermatology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA 02114, USA
| | - Qiuning Sun
- Department of Dermatology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, 9 Dongdan 3rd Alley, Dong Dan, Dongcheng Qu, Beijing Shi, China
| | - Keyun Tang
- Department of Dermatology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, 9 Dongdan 3rd Alley, Dong Dan, Dongcheng Qu, Beijing Shi, China
| | - Hanlin Zhang
- Department of Dermatology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, 9 Dongdan 3rd Alley, Dong Dan, Dongcheng Qu, Beijing Shi, China
| | - Poonkiat Suchonwanit
- Division of Dermatology, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, 270 Thanon Rama VI, Khwaeng Thung Phaya Thai, Khet Ratchathewi, Krung Thep Maha Nakhon 10400, Thailand
| | - Choon Chiat Oh
- Department of Dermatology, Singapore General Hospital, Singapore, Outram Rd, Singapore 169608, Singapore
| | - Alvin H Chong
- Skin Health Institute, level 1/80 Drummond St, Carlton, VIC 3053, Australia; Department of Medicine (Dermatology), St Vincent's Hospital Melbourne, University of Melbourne, Parkville, VIC 3010, Australia
| | - Anneliese Willems
- Skin Health Institute, level 1/80 Drummond St, Carlton, VIC 3053, Australia
| | - Cristina Galván
- Department of Dermatology, Hospital Universitario de Móstoles, Calle Río Júcar, S/N, 28935 Móstoles, Madrid, Spain
| | - Roni P Dodiuk-Gad
- Bruce Rappaport Faculty of Medicine, Technion - Institute of Technology, Haifa, 3200003, Israel; Department of Dermatology, Emek Medical Center, Yitshak Rabin Boulevard 21, Afula, 1834111, Israel; Division of Dermatology, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, 2075 Bayview Ave, Toronto, ON M4N 3M5, Canada
| | - Fabrizio Fantini
- Department of Dermatology, Dermatology Unit, ASST Lecco, Alessandro Manzoni Hospital, Via dell'Eremo, 9/11, 23900 Lecco LC, Italy
| | - Sebastiano Recalcati
- Department of Dermatology, Dermatology Unit, ASST Lecco, Alessandro Manzoni Hospital, Via dell'Eremo, 9/11, 23900 Lecco LC, Italy
| | - Joao Avancini
- Department of Dermatology, Hospital das Clínicas of the University of Sao Paulo, Rua, Av. Dr. Enéas Carvalho de Aguiar, 255-Cerqueira César, São Paulo-SP, 05403-000, Brazil
| | - Denise Miyamoto
- Department of Dermatology, Hospital das Clínicas of the University of Sao Paulo, Rua, Av. Dr. Enéas Carvalho de Aguiar, 255-Cerqueira César, São Paulo-SP, 05403-000, Brazil
| | - Jose A Sanches
- Department of Dermatology, Hospital das Clínicas of the University of Sao Paulo, Rua, Av. Dr. Enéas Carvalho de Aguiar, 255-Cerqueira César, São Paulo-SP, 05403-000, Brazil
| | - Noufal Raboobee
- Department of Dermatology, Westville Hospital, 7 Harry Gwala Rd, Westville, Durban, 3630, South Africa
| | - Francisco Bravo
- Department of Dermatology, Universidad Peruana Cayetano Heredia, Hospital Cayetano Heredia, Av. Honorio Delgado 430, San Martín de Porres 15102, Peru; Department of Pathology, Universidad Peruana Cayetano Heredia, Hospital Cayetano Heredia, 1 CV Zac, Av. Honorio Delgado 262, San Martín de Porres 15102, Peru
| | - Esther E Freeman
- Department of Dermatology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA 02114, USA.
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Estimation of Human Mobility Patterns for Forecasting the Early Spread of Disease. Healthcare (Basel) 2021; 9:healthcare9091224. [PMID: 34574996 PMCID: PMC8468459 DOI: 10.3390/healthcare9091224] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 09/14/2021] [Accepted: 09/14/2021] [Indexed: 01/12/2023] Open
Abstract
Human mobility data are indispensable in modeling large-scale epidemics, especially in predicting the spatial spread of diseases and in evaluating spatial heterogeneity intervention strategies. However, statistical data that can accurately describe large-scale population migration are often difficult to obtain. We propose an algorithm model based on the network science approach, which estimates the travel flow data in mainland China by transforming location big data and airline operation data into network structure information. In addition, we established a simplified deterministic SEIR (Susceptible-Exposed-Infectious-Recovered)-metapopulation model to verify the effectiveness of the estimated travel flow data in the study of predicting epidemic spread. The results show that individual travel distance in mainland China is mainly within 100 km. There is far more travel between prefectures within the same province than across provinces. The epidemic spatial spread model incorporating estimated travel data accurately predicts the spread of COVID-19 in mainland China. The results suggest that there are far more travelers than usual during the Spring Festival in mainland China, and the number of travelers from Wuhan mainly determines the number of confirmed cases of COVID-19 in each prefecture.
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COVID-19 Countermeasures and Passengers’ Confidence of Urban Rail Travel in Bangkok. SUSTAINABILITY 2021. [DOI: 10.3390/su13169377] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Rail transit systems around the world have been suffering from heavily reduced ridership due to reduced capacity for social distancing and passengers’ concern over the risk of COVID-19 infection. Various countermeasures were implemented to reduce the COVID-19 risk so that passengers felt safe to travel on rail. The objectives of this study were to evaluate COVID-19 countermeasures of Bangkok’s urban rail from passengers’ viewpoints and examine its influence on passenger’s confidence. The background of the COVID-19 pandemic in Thailand and the rail countermeasures implemented in Bangkok were summarized. The data were obtained from an interview survey of 1105 railway passengers conducted at the stations during the second wave of the pandemic. Factor analyses and structural equation modeling were conducted. The results revealed that social distancing was not satisfied by the passengers but adversely caused inconvenience and increased infection risk when the station or rail were congested. On the other hand, the passenger temperature check, face mask enforcement, and hand sanitization countermeasures were found to highly and positively contribute to passengers’ confidence. Contact tracing application was also found to raise awareness and confidence. The findings provided insights for rail authorities and related agencies to effectively implement the countermeasures that would be practically and financially sustainable.
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