COVID-19 pandemic and Rohingya refugees in Bangladesh: What are the major concerns?

Banik, Rajon; Rahman, Mahmudur; Hossain, M. Ibrahim; Sikder, Md. Tajuddin; Gozal, David

doi:10.1080/17441692.2020.1812103

Cited by 30 publications

(28 citation statements)

References 4 publications

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“…Pre-COVID-19, Rohingya refugees were already suffering from insufficient essential services such as food, education, water and sanitation, and basic health care ( Banik et al., 2020 ; Islam and Nuzhath, 2018 ). For adolescents, the focus of this paper, previous mixed-methods research in Cox's Bazar found that Rohingya adolescent girls and boys are a particularly marginalised subpopulation that is failing to develop their full cognitive, emotional and social capabilities due to their precarious displacement status ( Gender and Adolescence: Global Evidence (GAGE) 2020 ; Guglielmi et al., 2020 a; 2020 b; 2020 c; 2020 d; Bakali and Wasty, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

Exploring the impacts of COVID-19 on Rohingya adolescents in Cox's Bazar: A mixed-methods study

Guglielmi

Seager

Mitu

et al. 2020

Journal of Migration and Health

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Highlights Displaced Rohingya adolescents face intersecting vulnerabilities during COVID-19. Food insecurity has been exacerbated for Rohingya adolescents during the pandemic. Resuming education is key for the long-term progress of Rohingya adolescents. Health crises in humanitarian contexts negatively impact adolescent trajectories.

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Section: Introductionmentioning

confidence: 99%

Exploring the impacts of COVID-19 on Rohingya adolescents in Cox's Bazar: A mixed-methods study

Guglielmi

Seager

Mitu

et al. 2020

Journal of Migration and Health

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“…In an attempt to define tourist knowledge, Tsaur et al (2010) showed that travel-related information and skills represent tourists' perception of associated knowledge about any travel. In this case, declarative knowledge refers to tourist's perception of the specific travel destination and procedural knowledge denotes the practical use the knowledge by tourists in the traveling period starting from planning to the end of the trip (Banik et al, 2020;Begum et al, 2020;Hanefeld et al, 2015;Hasan et al, 2017). Peattie et al (2005), defined tourist health risk as the probability of suffering from diseases or other health complexities due to the exposure to any traveling experiences.…”

Section: Tourist Knowledgementioning

confidence: 99%

“…Therefore, Floyd and Pennington-Gray ( 2004) also emphasize the importance of the study of the tourist risk perception as there is evidence of association of higher risk with decreased visitation (Deb et al, 2020;Drimili et al, 2020). In the context of the tourism industry, a more comprehensive perspective of understanding tourist perception of risk includes evaluating tourists' health concern both in terms of perception of susceptibility and severity (Banik et al, 2020;Cahyanto et al, 2016). Additionally, Chien et al (2017) expressed that perception of tourists of health risk is one of the critical inputs in tourist's decision-making method Suhartanto et al, 2020).…”

Section: The Mediation Role Of Tourist Perceptionmentioning

confidence: 99%

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How does tourist perception lead to tourist hesitation? Empirical evidence from Bangladesh

Polas

Saha

Tabash

2021

Environ Dev Sustain

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The paper aims to identify the factors that cause prospective tourists’ hesitation to travel. The study also examines whether this relationship is mediated by the tourist perception in Bangladesh. The study is of quantitative design, and the relationships between tourist knowledge, tourist health risk, and destination personality with tourist hesitation were explored using a sample of 322 Bangladeshi prospective tourists. The three relationships were also examined through tourist perception. By using cross-sectional data, the researchers hypothesized that tourist knowledge, tourist health risk, and destination personality have a positive and significant effect on tourist hesitation. Besides, the researchers also hypothesized that tourist perception mediates the relationships between tourist knowledge, tourist health risk, and destination personality with tourist hesitation. In this respect, the Smart PLS 3.0 was employed to analyze the data. The results of the study confirm findings of previous related studies by not only highlighting the importance of tourist perception in shaping tourist hesitation but also indicating the way each dimension of tourism either enhances or inhibits the tourist hesitation. The results of the study also reveal a positive and significant relationship between tourist knowledge and tourist health risk with tourist hesitation. The analysis of data showed no conventional relationship between destination personality and tourist hesitation. Accordingly, this study identified the extent to which tourist perception mediates the relationship between tourist knowledge and destination personality with tourist hesitation. Meanwhile, the results of the study indicate the absence of any mediation role of tourist perception between tourist health risk and tourist hesitation. The study outcomes would encourage the government, policymakers, and tourism managements in creating a tailor-made responsiveness program by building a scenario that could offer more prominent sustainable tourism establishments. Besides, the results may assist stakeholders of tourist destinations in understanding tourist perception and the causes of tourist’s hesitation.

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“…In areas with high population density, the distance between individuals is shorter and the spread range of individuals is wider. Because of higher contact frequency and more neighbors around them, infectivity and the probability of being infected also increase with the increase of population density [8][9][10]. Thus population density is likely to have an effect on the number of daily cases, and cities or regions or countries with higher population density is likely to hit harder by COVID-19 epidemic.…”

Section: Introductionmentioning

confidence: 99%

Time to and extent of widespread testing for COVID-19 outbreak: Experience from the first wave in Australia and Italy

Abedin

Khan²,

Khan

2020

Preprint

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Background: At the beginning of COVID-19 outbreak, very little was known about its control options and most of the intervention options relied mainly on other virus outbreak and influenza epidemic. Different countries started responding to this epidemic somewhat in different ways to achieve a common goal of transmission reduction. Population-wide intervention measures such as social distancing, testing and isolation were implemented in different countries. However, commonly adopted intervention measures impacted different countries in different ways. Differential effects of those interventions become apparent in Australia and Italy, where Australia's success to control the epidemic has been in limelight. Differences in time to and extent of widespread testing are likely to have differential effects on the daily number of confirmed cases in both countries.Methods: We apply panel generalized linear models for daily number of cases to explore differential effects of timing to and extent of widespread testing on daily number of cases. We have analyzed daily number of confirmed cases data from the first reported cases in Australia and Italy to 31 May 2020. Our data sets can be downloaded from an open source database at https://ourworldindata.org.Results: More tests during the early stage of outbreak prior to reach the peak may reduce the daily number of cases by almost 40%. Only 1% increase in test positivity on the (t-5)th day may incur 1.84% increase in daily number of cases on the t-th day. For 1% increase in test positivity rate on the (t-5)th day, a country with one unit higher logarithm of population density may result in 2.82 times higher number of cases on the t-th day.Conclusion: Conducting widespread testing during the early stage prior to reaching the peak has favored Australia to control the outbreak much faster than Italy. Early adoption of widespread testing with lower degree of test positivity rates flattens the curve faster. Population density has a moderating effect. Even if the test positivity rate is the same, a region with higher population density is likely to experience a peak with higher number of daily confirmed cases.

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COVID-19 pandemic and Rohingya refugees in Bangladesh: What are the major concerns?

Cited by 30 publications

References 4 publications

Exploring the impacts of COVID-19 on Rohingya adolescents in Cox's Bazar: A mixed-methods study

Exploring the impacts of COVID-19 on Rohingya adolescents in Cox's Bazar: A mixed-methods study

How does tourist perception lead to tourist hesitation? Empirical evidence from Bangladesh

Time to and extent of widespread testing for COVID-19 outbreak: Experience from the first wave in Australia and Italy

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