000			01993nam a22003017c 4500
001			00004808
003			ES-MaONT
005			20220207171830.0
008			181126s2018 ||||frt|||i001 0 eng d
020			_a978-92-64-30759-9
024			_2doi _a10.1787/9789264307599-en
040			_aES-MaONT
110			_aOrganización de Cooperación y Desarrollo Económico _92843
245	0	4	_aStemming the Superbug Tide _cOECD _bJust A Few Dollars More
260			_aParís _bOECD Publishing _c2018
300			_a220 p. _c; 1 documento PDF
336			_atexto (visual) _2isbdcontent
337			_aelectrónico _2isbdmedia
338			_arecurso en línea _2rdacarrier
490	1		_aOECD Health Policy Studies
520			_aAntimicrobial resistance (AMR) is a large and growing problem with the potential for enormous health and economic consequences, globally. As such, AMR has become a central issue at the top of the public health agenda of OECD countries and beyond. In this report, OECD used advanced techniques, including machine learning, ensemble modelling and a microsimulation model, to provide support for policy action in the human health sector. AMR rates are high and are projected to grow further, particularly for second- and third-line antibiotics, and if no effective action is taken this is forecasted to produce a significant health and economic burden in OECD and EU28 countries. This burden can be addressed by implementing effective public health initiatives. This report reviews policies currently in place in high-income countries and identifies a set of ‘best buys’ to tackle AMR that, if scaled up at the national level, would provide an affordable and cost-effective instrument in the fight against AMR
650		7	_aSanidad digital _92065
653			_aantimicrobial resistence
653			_amachine learning
830	0		_aOECD Health Policy Studies _92589
856	4	2	_uhttps://doi.org/10.1787/9789264307599-en _x0 _yAcceso al documento _qpdf
942			_2z _cINF
999			_c4808 _d4808