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Predictability of population displacement after the 2010 Haiti earthquake

Proceedings of the National Academy of Sciences - PNAS, 2012-07, Vol.109 (29), p.11576-11581

2012

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Improved response to disasters and outbreaks by tracking population movements with mobile phone network data: a post-earthquake geospatial study in Haiti

PLoS medicine, 2011-08, Vol.8 (8), p.e1001083-e1001083

2011

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Using mobile phone data to predict the spatial spread of cholera

Scientific reports, 2015-03, Vol.5 (1), p.8923-8923, Article 8923

2015

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Mapping poverty using mobile phone and satellite data

Journal of the Royal Society interface, 2017-02, Vol.14 (127)

2017

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Digital epidemiology

PLoS computational biology, 2012-07, Vol.8 (7), p.e1002616-e1002616

2012

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The promise and perils of big gender data

Nature medicine, 2020-01, Vol.26 (1), p.17-18

2020

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Implementation of web-based respondent-driven sampling among men who have sex with men in Vietnam

PloS one, 2012-11, Vol.7 (11), p.e49417-e49417

2012

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Implementation of Web-Based Respondent Driven Sampling among Men Who Have Sex with Men in Sweden

PloS one, 2015-10, Vol.10 (10), p.e0138599-e0138599

2015

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Mathematical models for predicting human mobility in the context of infectious disease spread: introducing the impedance model

International journal of health geographics, 2017-11, Vol.16 (1), p.42-42, Article 42

2017

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Using gridded population and quadtree sampling units to support survey sample design in low-income settings

International journal of health geographics, 2020-03, Vol.19 (1), p.10-16, Article 10

2020

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Semi-automatic mapping of pre-census enumeration areas and population sampling frames

Humanities & social sciences communications, 2021-12, Vol.8 (1), p.1-14, Article 3

2021

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The sensitivity of respondent-driven sampling

Journal of the Royal Statistical Society. Series A, Statistics in society, 2012-01, Vol.175 (1), p.191-216

2012

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Comparison of contact patterns relevant for transmission of respiratory pathogens in Thailand and The Netherlands using respondent-driven sampling

PloS one, 2014-11, Vol.9 (11), p.e113711-e113711

2014

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Improving official statistics in emerging markets using machine learning and mobile phone data

EPJ data science, 2017-12, Vol.6 (1), p.3-21, Article 3

2017

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Online respondent-driven sampling for studying contact patterns relevant for the spread of close-contact pathogens: a pilot study in Thailand

PloS one, 2014-01, Vol.9 (1), p.e85256-e85256

2014

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Guiding principles to maintain public trust in the use of mobile operator data for policy purposes – CORRIGENDUM

Data & Policy, 2022, Vol.4, Article e18

2022

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Guiding principles to maintain public trust in the use of mobile operator data for policy purposes

Data & Policy, 2021-01, Vol.3, Article e24

2021

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Erratum to: Improving official statistics in emerging markets using machine learning and mobile phone data

EPJ data science, 2017-12, Vol.6 (1), p.8-1, Article 8

2017

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Approaching the limit of predictability in human mobility

Scientific reports, 2013-10, Vol.3 (1), p.2923-2923, Article 2923

2013

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Population mobility reductions associated with travel restrictions during the Ebola epidemic in Sierra Leone: use of mobile phone data

International journal of epidemiology, 2018-10, Vol.47 (5), p.1562-1570

2018

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

Global environmental change, 2016-05, Vol.38, p.1-7

2016

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Commentary: containing the ebola outbreak - the potential and challenge of mobile network data

PLoS currents, 2014, Vol.6

2014

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Predictability of population displacement after the 2010 Haiti earthquake

Improved response to disasters and outbreaks by tracking population movements with mobile phone network data: a post-earthquake geospatial study in Haiti

Using mobile phone data to predict the spatial spread of cholera

Mapping poverty using mobile phone and satellite data

Digital epidemiology

Rapid and Near Real-Time Assessments of Population Displacement Using Mobile Phone Data Following Disasters: The 2015 Nepal Earthquake

The promise and perils of big gender data

Implementation of web-based respondent-driven sampling among men who have sex with men in Vietnam

Implementation of Web-Based Respondent Driven Sampling among Men Who Have Sex with Men in Sweden

Mathematical models for predicting human mobility in the context of infectious disease spread: introducing the impedance model

Using gridded population and quadtree sampling units to support survey sample design in low-income settings

Semi-automatic mapping of pre-census enumeration areas and population sampling frames

The sensitivity of respondent-driven sampling

Comparison of contact patterns relevant for transmission of respiratory pathogens in Thailand and The Netherlands using respondent-driven sampling

Improving official statistics in emerging markets using machine learning and mobile phone data

Online respondent-driven sampling for studying contact patterns relevant for the spread of close-contact pathogens: a pilot study in Thailand

Guiding principles to maintain public trust in the use of mobile operator data for policy purposes – CORRIGENDUM

Guiding principles to maintain public trust in the use of mobile operator data for policy purposes

Erratum to: Improving official statistics in emerging markets using machine learning and mobile phone data

Approaching the limit of predictability in human mobility

Population mobility reductions associated with travel restrictions during the Ebola epidemic in Sierra Leone: use of mobile phone data

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

Past and future spread of the arbovirus vectors Aedes aegypti and Aedes albopictus

Commentary: containing the ebola outbreak - the potential and challenge of mobile network data

Comment: On the privacy-conscientious use of mobile phone data

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