Modeling pastoralist movement in response to environmental variables and conflict in Somaliland: Combining agent-based modeling and geospatial data.

Pastoralism is widely practiced in arid lands and is the primary means of livelihood for approximately 268 million people across Africa. Environmental, interpersonal, and transactional variables such as vegetation and water availability, conflict, ethnic tensions, and private/public land delineation influence the movements of these populations. The challenges of climate change and conflict are widely felt by nomadic pastoralists in Somalia, where resources are scarce, natural disasters are increasingly common, and protracted conflict has plagued communities for decades. Bereft of real-time data, researchers and programmatic personnel often turn to post hoc analysis to understand the interaction between climate, conflict, and migration, and design programs to address the needs of nomadic pastoralists. By designing an Agent-Based Model to simulate the movement of nomadic pastoralists based on typologically-diverse, historical data of environmental, interpersonal, and transactional variables in Somaliland and Puntland between 2008 and 2018, this study explores how pastoralists respond to changing environments. Through subsequent application of spatial analysis such as choropleth maps, kernel density mapping, and standard deviational ellipses, we characterize the resultant pastoralist population distribution in response to these variables. Outcomes demonstrate a large scale spatio-temporal trend of pastoralists migrating to the southeast of the study area with high density areas in the south of Nugaal, the northwest of Sool, and along the Ethiopian border. While minimal inter-seasonal variability is seen, multiple analyses support the consolidation of pastoralists to specifically favorable regions. Exploration of the large-scale population, climate, and conflict trends allows for cogent narratives and associative hypotheses regarding the pastoralist migration during the study period. While this model produces compelling associations between pastoralist movements and terrestrial and conflict variables, it relies heavily on assumptions and incomplete data that are not necessarily representative of realities on the ground. Given the paucity of data regarding pastoralist decision-making and migration, validation remains challenging.

Gender-based vulnerability: combining Pareto ranking and spatial statistics to model gender-based vulnerability in Rohingya refugee settlements in Bangladesh.

BACKGROUND: The Rohingya refugee crisis in Bangladesh continues to outstrip humanitarian resources and undermine the health and security of over 900,000 people. Spatial, sector-specific information is required to better understand the needs of vulnerable populations, such as women and girls, and to target interventions with improved efficiency and effectiveness. This study aimed to create a gender-based vulnerability index and explore the geospatial and thematic variations in gender-based vulnerability of Rohingya refugees residing in Bangladesh by utilizing pre-existing, open source data. METHODS: Data sources included remotely-sensed REACH data on humanitarian infrastructure, United Nations Population Fund resource availability data, and the Needs and Population Monitoring Survey conducted by the International Organization for Migration in October 2017. Data gaps were addressed through probabilistic interpolation. A vulnerability index was designed through a process of literature review, variable selection and thematic grouping, normalization, and scorecard creation, and Pareto ranking was employed to rank sites based on vulnerability scoring. Spatial autocorrelation of vulnerability was analyzed with the Global and Anselin Local Moran's I applied to both combined vulnerability index rank and disaggregated thematic ranking. RESULTS: Of the settlements, 24.1% were ranked as 'most vulnerable,' with 30 highly vulnerable clusters identified predominantly in the northwest region of metropolitan Cox's Bazar. Five settlements in Dhokkin, Somitapara, and Pahartoli were categorized as less vulnerable outliers amongst highly vulnerable neighboring sites. Security- and health-related variables appear to be the most significant drivers of gender-specific vulnerability in Cox's Bazar. Clusters of low security and education vulnerability measures are shown near Kutupalong. CONCLUSION: The humanitarian sector produces tremendous amounts of data that can be analyzed with spatial statistics to improve research targeting and programmatic intervention. The critical utilization of these data and the validation of vulnerability indexes are required to improve the international response to the global refugee crisis. This study presents a novel methodology that can be utilized to not only spatially characterize gender-based vulnerability in refugee populations, but can also be calibrated to identify and serve other vulnerable populations during crises.

Flying into the hurricane: A case study of UAV use in damage assessment during the 2017 hurricanes in Texas and Florida.

Unmanned aerial vehicles (UAVs) or drones have been used by disaster relief organizations in the United States since 2005. However, their place in the disaster response ecosystem-the standardization, utility, ethical, and legal challenges of drone use-remains largely unstudied. This case series describes how UAVs were used by two teams of responders for damage assessment purposes during the 2017 southeastern US Hurricanes Harvey and Irma. Data streams ranged from social media, direct observation, participant-observation and semi-directed interviews. Qualitative analysis was performed for thematic content derived from field observation and from post-hoc interviews. Outcomes of the qualitative analysis emphasize the barriers to deploying drones in the disaster context, their tactical implementation, programmatic integration, and ethical and legal challenges. These observations lay the groundwork for both future research on the utilization of drones and the prudent and ethical implementation of programs that employ drones in post-disaster settings.

Beyond mapping: a case for geospatial analytics in humanitarian health.

The humanitarian sector is increasingly adopting geospatial data to support operations. However, the utilization of these data in the humanitarian health arena is predominantly in thematic map format, thereby limiting the full insight and utility of geospatial information. Geospatial analytics, in contrast, including pattern analysis, interpolation, and predictive modeling, have tremendous potential within the field of humanitarian health. This paper explores a variety of historical and contemporary geospatial applications in the public health and humanitarian fields and argues for greater integration of geospatial analysis into humanitarian health research and programming. From remote sensing to create sampling frames, to spatial interpolation for environmental exposure analysis, and multi-objective optimization algorithms for humanitarian logistics, spatial analysis has transformed epistemological paradigms, research methods and programming landscapes across diverse disciplines. The field of humanitarian health, which is inextricably bounded by geography and resource limitations, should leverage the unique capacities of spatial methods and strategically integrate geospatial analytics into research and programming not only to fortify the academic legitimacy and professionalization of the field but also to improve operational efficiency and mitigation strategies.

Point-of-Care Ultrasound Diagnosis of a Catheter-Associated Atrial Thrombus.

BACKGROUND: Emergency physicians can utilize point-of-care thoracic ultrasound to aid in the diagnosis of a variety of cardiovascular and respiratory complaints. CASE REPORT: An emergency physician utilized point-of-care cardiac ultrasound to identify catheter-associated atrial thrombi in a hemodialysis patient presenting with dyspnea. WHY SHOULD AN EMERGENCY PHYSICIAN BE AWARE OF THIS?: Based on this case, point-of-care ultrasound can be utilized in patients with central venous catheters, to identify intracardiac thrombi as the cause of dyspnea, thereby facilitating appropriate consultation and treatment.