  Turkey hosts almost 3.5M refugees and has to face a humanitarian emergency of
unprecedented levels. We use mobile phone data to map the mobility patterns of
both Turkish and Syrian refugees, and use these patterns to build data-driven
computational models for quantifying the risk of epidemics spreading for
measles -- a disease having a satisfactory immunization coverage in Turkey but
not in Syria, due to the recent civil war -- while accounting for hypothetical
policies to integrate the refugees with the Turkish population. Our results
provide quantitative evidence that policies to enhance social integration
between refugees and the hosting population would reduce the transmission
potential of measles by almost 50%, preventing the onset of widespread large
epidemics in the country. Our results suggest that social segregation does not
hamper but rather boosts potential outbreaks of measles to a greater extent in
Syrian refugees but also in Turkish citizens, although to a lesser extent. This
is due to the fact that the high immunization coverage of Turkish citizens can
shield Syrian refugees from getting exposed to the infection and this in turn
reduces potential sources of infection and spillover of cases among Turkish
citizens as well, in a virtuous cycle reminiscent of herd immunity.

Populations and Evolution;Social and Information Networks;Physics and Society