Ontology highlight
ABSTRACT: Background
Travel restrictions were implemented on an unprecedented scale in 2015 in Sierra Leone to contain and eliminate Ebola virus disease. However, the impact of epidemic travel restrictions on mobility itself remains difficult to measure with traditional methods. New 'big data' approaches using mobile phone data can provide, in near real-time, the type of information needed to guide and evaluate control measures.Methods
We analysed anonymous mobile phone call detail records (CDRs) from a leading operator in Sierra Leone between 20 March and 1 July in 2015. We used an anomaly detection algorithm to assess changes in travel during a national 'stay at home' lockdown from 27 to 29 March. To measure the magnitude of these changes and to assess effect modification by region and historical Ebola burden, we performed a time series analysis and a crossover analysis.Results
Routinely collected mobile phone data revealed a dramatic reduction in human mobility during a 3-day lockdown in Sierra Leone. The number of individuals relocating between chiefdoms decreased by 31% within 15 km, by 46% for 15-30 km and by 76% for distances greater than 30 km. This effect was highly heterogeneous in space, with higher impact in regions with higher Ebola incidence. Travel quickly returned to normal patterns after the restrictions were lifted.Conclusions
The effects of travel restrictions on mobility can be large, targeted and measurable in near real-time. With appropriate anonymization protocols, mobile phone data should play a central role in guiding and monitoring interventions for epidemic containment.
SUBMITTER: Peak CM
PROVIDER: S-EPMC6208277 | biostudies-literature | 2018 Oct
REPOSITORIES: biostudies-literature
International journal of epidemiology 20181001 5
<h4>Background</h4>Travel restrictions were implemented on an unprecedented scale in 2015 in Sierra Leone to contain and eliminate Ebola virus disease. However, the impact of epidemic travel restrictions on mobility itself remains difficult to measure with traditional methods. New 'big data' approaches using mobile phone data can provide, in near real-time, the type of information needed to guide and evaluate control measures.<h4>Methods</h4>We analysed anonymous mobile phone call detail records ...[more]