Detecting climate adaptation with mobile network data in Bangladesh: anomalies in communication, mobility and consumption patterns during cyclone Mahasen

Large-scale data from digital infrastructure, like mobile phone networks, provides rich information on the behavior of millions of people in areas affected by climate stress. Using anonymized data on mobility and calling behavior from 5.1 million Grameenphone users in Barisal Division and Chittagong District, Bangladesh, we investigate the effect of Cyclone Mahasen, which struck Barisal and Chittagong in May 2013. We characterize spatiotemporal patterns and anomalies in calling frequency, mobile recharges, and population movements before, during and after the cyclone. While it was originally anticipated that the analysis might detect mass evacuations and displacement from coastal areas in the weeks following the storm, no evidence was found to suggest any permanent changes in population distributions. We detect anomalous patterns of mobility both around the time of early warning messages and the storm’s landfall, showing where and when mobility occurred as well as its characteristics. We find that anomalous patterns of mobility and calling frequency correlate with rainfall intensity (r = .75, p < 0.05) and use calling frequency to construct a spatiotemporal distribution of cyclone impact as the storm moves across the affected region. Likewise, from mobile recharge purchases we show the spatiotemporal patterns in people’s preparation for the storm in vulnerable areas. In addition to demonstrating how anomaly detection can be useful for modeling human adaptation to climate extremes, we also identify several promising avenues for future improvement of disaster planning and response activities

Physiological responses during ascent to high altitude and the incidence of acute mountain sickness.

Acute mountain sickness (AMS) occurs when there is failure of acclimatisation to high altitude. The aim of this study was to describe the relationship between physiological variables and the incidence of AMS during ascent to 5300 m. A total of 332 lowland-dwelling volunteers followed an identical ascent profile on staggered treks. Self-reported symptoms of AMS were recorded daily using the Lake Louise score (mild 3-4; moderate-severe ≥5), alongside measurements of physiological variables (heart rate, respiratory rate (RR), peripheral oxygen saturation (SpO2 ) and blood pressure) before and after a standardised Xtreme Everest Step-Test (XEST). The overall occurrence of AMS among participants was 73.5% (23.2% mild, 50.3% moderate-severe). There was no difference in gender, age, previous AMS, weight or body mass index between participants who developed AMS and those who did not. Participants who had not previously ascended >5000 m were more likely to get moderate-to-severe AMS. Participants who suffered moderate-to-severe AMS had a lower resting SpO2 at 3500 m (88.5 vs. 89.6%, p = 0.02), while participants who suffered mild or moderate-to-severe AMS had a lower end-exercise SpO2 at 3500 m (82.2 vs. 83.8%, p = 0.027; 81.5 vs. 83.8%, p 5000 m (OR 2.740, p-value 0.003) predicted the development of moderate-to-severe AMS. The Xtreme Everest Step-Test offers a simple, reproducible field test to help predict AMS, albeit with relatively limited predictive precision

The Characterisation of Pulmonary Function in Patients with Mucopolysaccharidoses IVA: A Longitudinal Analysis.

Mucopolysaccharidoses type IVA (Morquio disease) is a rare, autosomal recessive lysosomal storage disease that causes both obstructive and restrictive airway pathology, with respiratory failure being the primary cause of death. In this retrospective, longitudinal, repeated-measures cohort study, descriptive statistics and non-parametric correlation were performed for demographic, respiratory function and oximetry (sleep studies) variables over a study period from January 2009 to December 2018. Composite clinical endpoints used in this study for evaluating pulmonary function included spirometry and oximetry variables.We provides original data on the longitudinal characterization of pulmonary function changes in children with Mucopolysaccharidoses (MPS) IVA by presenting the data and nuanced trends of changes from sequential spirometry and oximetry. The sample size included 16 subjects, 13 had undergone enzyme replacement therapy (ERT), three had not undergone ERT treatment. A total of 180 induvial plots are presented for spirometry variables (FEV1, FEV1 [%Pred] FVC, FVC [%Pred] and FEV1/FVC), 6MWT and oximetry variables (median %Spo2, ODI 3%, mean nadir 3%, ODI 4%, mean nadir 4% and min dip SpO2 [%]); over a nine-year period at a single quaternary pediatric metabolic center. This data has been made public and has utility to clinicians and researchers by providing the first comprehensive report of detailed changes in pulmonary function in children with MPS IVA, with and without ERT; as well as changes in pulmonary function following the institution of non-invasive ventilation (NIV) and adenotonsillectomy. The data is supplemental to our study “The Characterization of Pulmonary Function in Patients with Mucopolysaccharidoses IVA: A Longitudinal Analysis” by Kenth et al

The Characterisation of Pulmonary Function in Patients with Mucopolysaccharidoses IVA: A Longitudinal Analysis.

Mucopolysaccharidoses type IVA (Morquio disease) is a rare, autosomal recessive lysosomal storage disease that causes both obstructive and restrictive airway pathology, with respiratory failure being the primary cause of death. In this retrospective, longitudinal, repeated-measures cohort study, descriptive statistics and non-parametric correlation were performed for demographic, respiratory function and oximetry (sleep studies) variables over a study period from January 2009 to December 2018. Composite clinical endpoints used in this study for evaluating pulmonary function included spirometry variables (FEV1, FEV1 [%Pred] FVC, FVC [%Pred] and FEV1/FVC), 6MWT and oximetry variables (median %Spo2, ODI 3%, mean nadir 3%, ODI 4%, mean nadir 4% and min dip SpO2 [%]). We provides original data on the longitudinal characterization of pulmonary function changes in children with Mucopolysaccharidoses (MPS) IVA by presenting the data and nuanced trends of changes from sequential spirometry and oximetry. The sample size included 16 subjects, 13 had undergone enzyme replacement therapy (ERT), three had not undergone ERT treatment. A total of 180 induvial plots are presented for spirometry variables (FEV1, FEV1 [%Pred] FVC, FVC [%Pred] and FEV1/FVC), 6MWT and oximetry variables (median %Spo2, ODI 3%, mean nadir 3%, ODI 4%, mean nadir 4% and min dip SpO2 [%]); over a nine-year period at a single quaternary pediatric metabolic center. This data has been made public and has utility to clinicians and researchers by providing the first comprehensive report of detailed changes in pulmonary function in children with MPS IVA, with and without ERT; as well as changes in pulmonary function following the institution of non-invasive ventilation (NIV) and adenotonsillectomy. The data is supplemental to our study “The Characterization of Pulmonary Function in Patients with Mucopolysaccharidoses IVA: A Longitudinal Analysis” by Kenth et al

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

Climate change is likely to drive migration from environmentally stressed areas. However quantifying short and long-term movements across large areas is challenging due to difficulties in the collection of highly spatially and temporally resolved human mobility data. In this study we use two datasets of individual mobility trajectories from six million de-identified mobile phone users in Bangladesh over three months and two years respectively. Using data collected during Cyclone Mahasen, which struck Bangladesh in May 2013, we show first how analyses based on mobile network data can describe important short-term features (hours–weeks) of human mobility during and after extreme weather events, which are extremely hard to quantify using standard survey based research. We then demonstrate how mobile data for the first time allow us to study the relationship between fundamental parameters of migration patterns on a national scale. We concurrently quantify incidence, direction, duration and seasonality of migration episodes in Bangladesh. While we show that changes in the incidence of migration episodes are highly correlated with changes in the duration of migration episodes, the correlation between in- and out-migration between areas is unexpectedly weak. The methodological framework described here provides an important addition to current methods in studies of human migration and climate change

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