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000858958 020__ $$a9780190492427 $$q(electronic book)
000858958 035__ $$a(StDuBDS)EDZ0001639848
000858958 040__ $$aStDuBDS$$beng$$cStDuBDS$$erda$$epn
000858958 050_0 $$aRA418
000858958 08204 $$a362.1$$223
000858958 24500 $$aSystems science and population health /$$cAbdulrahman M. El-Sayed and Sandro Galea.
000858958 264_1 $$aNew York, NY :$$bOxford University Press,$$c2017.
000858958 300__ $$a1 online resource
000858958 336__ $$atext$$2rdacontent
000858958 337__ $$acomputer$$2rdamedia
000858958 338__ $$aonline resource$$2rdacarrier
000858958 504__ $$aIncludes bibliographical references and index.
000858958 506__ $$aAccess limited to authorized users.
000858958 5208_ $$aThis work employs principles from across a range of sciences to refine the way we understand population health. By augmenting traditional analytic approaches with new tools like machine learning, microsimulation, and social network analysis, population health can be studied as a dynamic and complex system. This allows us to understand population health as a complex whole, offering new insights and perspectives that stand to improve the health of the public. The text offers the first educational and practical guide to this forward-thinking approach.
000858958 588__ $$aDescription based on online resource; title from home page (viewed on February 20, 2017).
000858958 650_0 $$aPublic health.
000858958 650_0 $$aPublic health$$xData processing.
000858958 650_0 $$aSystem theory.
000858958 7001_ $$aEl-Sayed, Abdulrahman M.,$$eeditor.
000858958 7001_ $$aGalea, Sandro,$$eeditor.
000858958 77608 $$iPrint version: $$z9780190492397
000858958 85280 $$bebk$$hOxford Scholarship Online
000858958 85640 $$3Oxford scholarship online$$uhttps://univsouthin.idm.oclc.org/login?url=https://dx.doi.org/10.1093/acprof:oso/9780190492397.001.0001$$zOnline Access
000858958 909CO $$ooai:library.usi.edu:858958$$pGLOBAL_SET
000858958 980__ $$aBIB
000858958 983__ $$aOnline