How do migration decisions and drivers differ against extreme environmental events?

Migration is often understood to be a livelihood strategy to cope with the effects of environmental threats and climate change. Yet, the extent to which migration decisions differ due to the type, severity, and frequency of environmental events has been little explored. This paper employs household surveys in southwestern Bangladesh to explore this research gap. A multinominal regression model is used to simulate reported future migration decisions (200 sample households) in the context of both rapid-onset (i.e. cyclone and flood) and slow-onset (salinity, siltation, and riverbank erosion) environmental phenomena. Results show: i) previous disaster experience and increasing conflict in the community motivate migration in the near future in the context of slow-onset phenomena (salinity); (ii) economic strength and self-efficacy increase non-migration intention in both contexts of sudden and slow-onset events; and (iii) the extent and pattern of these influences on migration differ across demographics, including education, religion, and age. Importantly, this analysis shows that the relationship between migration decisions and the type, severity, and frequency of environmental events is influenced by socioeconomic conditions. Therefore, this research supports future adaptation planning specifically tailored to the type and exposure of extreme environmental events.

A bibliometric review on the drivers of environmental migration.

A large body of literature exists arguing that numerous, complex factors result in environmental migration. Thus, in order to understand environmental migration, we must investigate how its drivers are defined, explained and interrelated. This study aims to produce a comprehensive analysis of the literature on the drivers of environmental migration and assess future opportunities for studying 'environmental migration'. We conduct a systematic literature search using the keywords 'environmental migration' and 'drivers' in Scopus and Web of Knowledge, analysing 146 publications. The findings are organised as a bibliometric analysis, including network analysis and evaluation of publication metrics. Results show that the literature on environmental migration drivers constitutes a relatively new, growing field largely developed in the USA. It is rooted in the wider environmental migration literature and strongly associated with the discourse of climate change impacts as driving factors. Typologies of 'migrants' are more prevalent than 'refugees' when referring to actors.

In harm's way: Non-migration decisions of people at risk of slow-onset coastal hazards in Bangladesh.

Non-migration is an adaptive strategy that has received little attention in environmental migration studies. We explore the leveraging factors of non-migration decisions of communities at risk in coastal Bangladesh, where exposure to both rapid- and slow-onset natural disasters is high. We apply the Protection Motivation Theory (PMT) to empirical data and assess how threat perception and coping appraisal influences migration decisions in farming communities suffering from salinization of cropland. This study consists of data collected through quantitative household surveys (n = 200) and semi-structured interviews from four villages in southwest coastal Bangladesh. Results indicate that most respondents are unwilling to migrate, despite better economic conditions and reduced environmental risk in other locations. Land ownership, social connectedness, and household economic strength are the strongest predictors of non-migration decisions. This study is the first to use the PMT to understand migration-related behaviour and the findings are relevant for policy planning in vulnerable regions where exposure to climate-related risks is high but populations are choosing to remain in place.

Analysis of residential satisfaction: An empirical evidence from neighbouring communities of Rohingya camps in Cox's Bazar, Bangladesh.

This study aims to understand the level of residential satisfaction of the host communities' aftermath of the influx of Rohingya in Bangladesh. A total of 151 household heads were randomly interviewed from Ukhiya and Ramu Upazila of Cox's Bazar district, Bangladesh. A residential satisfaction index is developed with a total of twenty-two variables comprised of four components- social environment (SE), neighbourhood environment (NE), public services and facilities (PS&F), and dwelling units (DU). The coefficients of the components indicate that the PS&F, SE, and NE impact much on the overall residential satisfaction compare to the DU. The analysis demonstrates that the people who have tertiary level education, who is Muslim and whose work opportunities remain the same as before, are more satisfied, but older people are less satisfied than younger. Besides, the degradation of social harmony, livestock and agricultural land losses, and decreased wages were the significant causes of dissatisfaction. These findings may contribute to taking appropriate policies and programs for the host communities taken by the government and non-government organizations.

Livelihood challenges of 'double strike' disasters: Evidence from rural communities of southwest coastal Bangladesh during the Covid-19 pandemic and cyclone Amphan.

The Covid-19 pandemic has adversely affected livelihoods in the Global South and exacerbated the effects of natural disaster. This study examines the 'double strike' of the Covid-19 lockdown and 'super-cyclone' Amphan on the 12 villages of Dakshin Bedkashi Union, southwest Bangladesh. It employs questionnaire surveys to assess the impact of the compound disaster on rural livelihoods over a period of five months, comparing pre-lockdown, post-lockdown, and post-Amphan phases. The results demonstrate the severe impact of the pandemic on income, occupation, and workdays, and consequently on livelihood resilience leading up to Amphan. Although effects vary moderately by livelihood category, village, and socio-spatial characteristics, overall rates of income reduction (58%) and occupation loss (77%) between the advent of the lockdown and the aftermath of Amphan are high. Thus, livelihood resilience to the double strike is generally poor. The study analyses the predictors of lost working days to illuminate the influences on livelihood resilience throughout the double strike. We conclude that the pandemic has presented novel challenges to this region, complicating vulnerability to more common cyclonic natural hazards. Finding that the degree of livelihood diversification is low in the sample, we recommend implementing diversification policies and strengthening local networks and community trust to better anticipate and combat the complex, varied impacts of double strike scenarios in future.

Key opportunities and challenges for the use of big data in migration research and policy.

Migration is one of the defining issues of the 21st century. Better data is required to improve understanding about how and why people are moving, target interventions and support evidence-based migration policy. Big data, defined as large, complex data from diverse sources, is regularly proposed as a solution to help address current gaps in knowledge. The authors participated in a workshop held in London, UK, in July 2019, that brought together experts from the United Nations (UN), humanitarian non-governmental organisations (NGOs), policy and academia to develop a better understanding of how big data could be used for migration research and policy. We identified six key areas regarding the application of big data in migration research and policy: accessing and utilising data; integrating data sources and knowledge; understanding environmental drivers of migration; improving healthcare access for migrant populations; ethical and security concerns around the use of big data; and addressing political narratives. We advocate the need for careful consideration of the challenges faced by the use of big data, as well as increased cross-disciplinary collaborations to advance the use of big data in migration research whilst safeguarding vulnerable migrant communities.

Challenges of Testing COVID-19 Cases in Bangladesh.

Keeping the dynamic nature of Coronaviruses (COVID-19) pandemic in mind, we have opted to explore the importance of the decentralization of COVID-19 testing centers across the country of Bangladesh in order to combat the pandemic. In doing so, we considered quantitative, qualitative, and geographic information systems (GIS) datasets to identify the location of existing COVID-19 testing centers. Moreover, we attempted to collect data from the existing centers in order to demonstrate testing times at the divisional level of the country. Results show that the number of testing centers is not enough to cater to the vast population of the country. Additionally, we found that the number of days it takes to receive the results from the COVID-19 testing centers is not optimal at divisional cities, let alone the remote rural areas. Finally, we propose a set of recommendations in order to enhance the existing system to assist more people under a testing range of COVID-19 viruses at the local level.

Cyclone shelters and their locational suitability: an empirical analysis from coastal Bangladesh.

Bangladesh is one of the poorest and the most disaster-prone countries in Asia; it is important, therefore, to know how its disaster reduction strategies are organised and planned. Cyclone shelters comprise a widely acceptable form of infrastructural support for disaster management in Bangladesh. This paper attempts to analyse empirically their use during cyclones in a sample study area along the southwest coastal belt of the country. It shows how the location of a cyclone shelter can determine the social power structure in coastal Bangladesh. The results reveal that the establishment of cyclone shelters in the studied communities is determined by neither a right-based nor a demand-based planning approach; rather, their creation is dependent on the socio-political affluence of local-level decision-makers. The paper goes on to demonstrate that socially vulnerable households (defined, for example, by income or housing conditions) are afforded disproportionately less access to cyclone shelters as compared to less socially vulnerable households.