Unveiling hidden migration and mobility patterns in climate stressed regions: A longitudinal study of six million anonymous mobile phone users in Bangladesh

Lu, Xin; Wrathall, David; Sundsøy, Pål; Nadiruzzaman, Md.; Wetter, Erik; Iqbal, Asif; Qureshi, Taimur; Tatem, Andrew J.; Canright, Geoffrey; Engø‐Monsen, Kenth; Bengtsson, Linus

doi:10.1016/j.gloenvcha.2016.02.002

Cited by 164 publications

(113 citation statements)

References 40 publications

Supporting

Mentioning

112

Contrasting

Order By: Relevance

“…Iqbal and Roy (2015) used district-level data on climate, agricultural production and net migration to show that climate-linked increases in production had a weak positive effect on net migration, but was limited by the use of indirect methods to estimate net migration (Iqbal & Roy, 2015). Most recently, Lu and colleagues (2016) used a large dataset of call records from mobile phones to examine population mobility associated with Cyclone Mahasen. Their analysis successfully documented short-term mobility in the hours before the storm, but was not able to document longer-term changes (Lu et al, 2016).…”

Section: Analyzing Environmentally-induced Temporary Migrationmentioning

confidence: 99%

Disruption, not displacement: Environmental variability and temporary migration in Bangladesh

Call

Gray²,

Yunus

et al. 2017

Global Environmental Change

128

View full text Add to dashboard Cite

Mass migration is one of the most concerning potential outcomes of global climate change. Recent research into environmentally induced migration suggests that relationship is much more complicated than originally posited by the ‘environmental refugee’ hypothesis. Climate change is likely to increase migration in some cases and reduce it in others, and these movements will more often be temporary and short term than permanent and long term. However, few large-sample studies have examined the evolution of temporary migration under changing environmental conditions. To address this gap, we measure the extent to which temperature, precipitation, and flooding can predict temporary migration in Matlab, Bangladesh. Our analysis incorporates high-frequency demographic surveillance data, a discrete time event history approach, and a range of sociodemographic and contextual controls. This approach reveals that migration declines immediately after flooding but quickly returns to normal. In contrast, optimal precipitation and high temperatures have sustained positive effects on temporary migration that persist over one to two year periods. Building on previous studies of long-term migration, these results challenge the common assumption that flooding, precipitation extremes and high temperatures will consistently increase temporary migration. Instead, our results are consistent with a livelihoods interpretation of environmental migration in which households draw on a range of strategies to cope with environmental variability.

show abstract

Section: Analyzing Environmentally-induced Temporary Migrationmentioning

confidence: 99%

Disruption, not displacement: Environmental variability and temporary migration in Bangladesh

Call

Gray²,

Yunus

et al. 2017

Global Environmental Change

128

View full text Add to dashboard Cite

show abstract

“…Phone based positioning does not depend on a specific application platform, such as Twitter or Foursquare/Swarm. However, obtaining a cohesive set of spatio-temporal locations from phone records across multiple countries appears to be challenging, given that most studies that analyze mobility from phone records are geographically limited to the city level [60,61] or country level [62], with only a few exceptions that extend beyond national or continental boundaries [63].…”

Section: Summary and Discussionmentioning

confidence: 99%

Analyzing Refugee Migration Patterns Using Geo-tagged Tweets

Hübl

Cvetojevic

Hochmair

et al. 2017

IJGI

View full text Add to dashboard Cite

Abstract:Over the past few years, analysts have begun to materialize the "Citizen as Sensors" principle by analyzing human movements, trends and opinions, as well as the occurrence of events from tweets. This study aims to use geo-tagged tweets to identify and visualize refugee migration patterns from the Middle East and Northern Africa to Europe during the initial surge of refugees aiming for Europe in 2015, which was caused by war and political and economic instability in those regions. The focus of this study is on exploratory data analysis, which includes refugee trajectory extraction and aggregation as well as the detection of topical clusters along migration routes using the V-Analytics toolkit. Results suggest that only few refugees use Twitter, limiting the number of extracted travel trajectories to Europe. Iterative exploration of filter parameters, dynamic result mapping, and content analysis were essential for the refinement of trajectory extraction and cluster detection. Whereas trajectory extraction suffers from data scarcity, hashtag-based topical clustering draws a clearer picture about general refugee routes and is able to find geographic areas of high tweet activities on refugee related topics. Identified spatio-temporal clusters can complement migration flow data published by international authorities, which typically come at the aggregated (e.g., national) level. The paper concludes with suggestions to address the scarcity of geo-tagged tweets in order to obtain more detailed results on refugee migration patterns.

show abstract

“…Despite these issues, our methodology could be easily modified to incorporate other model formulations, although the lack of access of mobility data such as mobile phone records hinders the applicability of models with free parameters. On the other hand, the use of mobile phone data has been shown to be relevant at the urban scale [53, 54], thus the increasing availability of mobile phone records in cholera-stricken countries could soon overcome the need for human mobility models altogether [21, 22, 55]. In an intermediate phase, and to inform efforts in locations where phone data are not readily available, comparisons of the fluxes based on methods such as the present one against phone data, where available, would be of interest.…”

Section: Discussionmentioning

confidence: 99%

Climate-driven endemic cholera is modulated by human mobility in a megacity

Perez-Saez

King

Rinaldo

et al. 2017

Advances in Water Resources

View full text Add to dashboard Cite

Although a differential sensitivity of cholera dynamics to climate variability has been reported in the spatially heterogeneous megacity of Dhaka, Bangladesh, the specific patterns of spread of the resulting risk within the city remain unclear. We build on an established probabilistic spatial model to investigate the importance and role of human mobility in modulating spatial cholera transmission. Mobility fluxes were inferred using a straightforward and generalizable methodology that relies on mapping population density based on a high resolution urban footprint product, and a parameter-free human mobility model. In accordance with previous findings, we highlight the higher sensitivity to the El Niño Southern Oscillation (ENSO) in the highly populated urban center than in the more rural periphery. More significantly, our results show that cholera risk is largely transmitted from the climate-sensitive core to the periphery of the city, with implications for the planning of control efforts. In addition, including human mobility improves the outbreak prediction performance of the model with an 11 month lead. The interplay between climatic and human mobility factors in cholera transmission is discussed from the perspective of the rapid growth of megacities across the developing world.

show abstract

Unveiling hidden migration and mobility patterns in climate stressed regions: A longitudinal study of six million anonymous mobile phone users in Bangladesh

Cited by 164 publications

References 40 publications

Disruption, not displacement: Environmental variability and temporary migration in Bangladesh

Disruption, not displacement: Environmental variability and temporary migration in Bangladesh

Analyzing Refugee Migration Patterns Using Geo-tagged Tweets

Climate-driven endemic cholera is modulated by human mobility in a megacity

Contact Info

Product

Resources

About