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10.1016/j.jdeveco.2020.102559 http://scihub22266oqcxt.onion/10.1016/j.jdeveco.2020.102559 33144750!7561616!33144750     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       J+Dev+Econ 2020 ; 147 (ä): 102559 Nephropedia Template TP {{tp|p=33144750|t=2020. Managing the spread of disease with mobile phone data |pdf=|usr=}}{{33144750}} gab.com Text Managing the spread of disease with mobile phone data JO: J Dev Econ http://www.kidney.de/pget.php?&tw=1&pmid=33144750 #FOAvip While human mobility has important benefits for economic growth, it can generate negative externalities. This paper studies the effect of mobility on the spread of disease in a low-incidence setting when people do not internalize their risks to others. Using malaria as a case study and 15 billion mobile phone records across nine million SIM cards, this paper quantifies the relationship between travel and the spread of disease. The estimates indicate that an infected traveler contributes to 1.66 additional cases reported in the health facility at the traveler's destination. This paper develops a simulation-based policy tool that uses mobile phone data to inform strategic targeting of travelers based on their origins and destinations. The simulations suggest that targeting informed by mobile phone data could reduce the caseload by 50 percent more than current strategies that rely only on previous incidence. Twit Text FOAVip Managing the spread of disease with mobile phone data ????J Dev Econ http://www.kidney.de/pget.php?&tw=1&pmid=33144750 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33144750 #FOAvip English Wikipedia <ref>{{Cite pmid|33144750}}</ref> Managing the spread of disease with mobile phone data #MMPMID33144750 Milusheva S J Dev Econ 2020[Nov]; 147 (ä): 102559 PMID33144750show ga While human mobility has important benefits for economic growth, it can generate negative externalities. This paper studies the effect of mobility on the spread of disease in a low-incidence setting when people do not internalize their risks to others. Using malaria as a case study and 15 billion mobile phone records across nine million SIM cards, this paper quantifies the relationship between travel and the spread of disease. The estimates indicate that an infected traveler contributes to 1.66 additional cases reported in the health facility at the traveler's destination. This paper develops a simulation-based policy tool that uses mobile phone data to inform strategic targeting of travelers based on their origins and destinations. The simulations suggest that targeting informed by mobile phone data could reduce the caseload by 50 percent more than current strategies that rely only on previous incidence. äManaging the spread of disease with mobile phone data (epmc).pdf DeepDyve Pubget Overpricing