Population movements after the nepal Earthquake v5 up to 19th Aug 2015

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Source Estimated population movements in Nepal after the 25 April earthquake.
Date of Dataset August 24, 2015-August 24, 2015
Updated 17 July 2016
Expected Update Frequency Never

For CSV file with above normal inflows: Population flows between districts are large under normal conditions. Here we present, for each district, the estimated above-normal inflows from all other districts. Inflows to a district are composed of people leaving their home area to come into the district, people returning to their home district after temporary visits elsewhere, and Nepalese relief workers (relief workers coming in after the earthquake are excluded). These estimates currently do not distinguish between these three groups.

For CSV file with trends: This file contains the development of above normal inflows (as described above) into the various districts for the weeks between mid-May and the beginning of July.

For csv file containing the number of people still away we estimate the number of people displaced in the two weeks after the earthquake and count the percentage who remain away for subsequent five day chunks after the initial period.

See additional information in the uploaded pdf. General methodology available here: http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001083

Caveats / Comments

Mobile phone use is relatively lower in several groups including women, children, the elderly, and the poorest. If these groups have substantially different movement patterns than groups with high mobile phone use, results will be biased. In general the relative distributions of flows across the country are more reliable than absolute numbers given per area. Both types of estimates will improve over time with additional data. Our previous field projects in Haiti and Kenya show that overall estimates of mobility corresponded well to population-level data [1-2], but the estimates provided here should be interpreted with the above mentioned caveats in mind.

[1] Bengtsson et al. (2011) Improved response to disasters and outbreaks with mobile phone data: a post-earthquake geospatial study of Haiti [2] Wesolowski et al. (2013) The impact of biases in mobile phone ownership on estimates of human mobility

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