'Out-of-the-box' thinking to help stop the spread of antibiotic resistance

Alternatively, a ‘traffic-light’ system (based on for example: the actual use of antibiotics during food production; or the use of antibiotics of ‘last resort’, e.g.,colistin; or on the level of use of antibiotics within a particular agricultural region), could bring the problem of antibiotic resist...

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Bibliographic Details
Published inFuture microbiology Vol. 11; no. 8; pp. 995 - 998
Main Author Hays, John P
Format Journal Article
LanguageEnglish
Published England Future Medicine Ltd 01.08.2016
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Summary:Alternatively, a ‘traffic-light’ system (based on for example: the actual use of antibiotics during food production; or the use of antibiotics of ‘last resort’, e.g.,colistin; or on the level of use of antibiotics within a particular agricultural region), could bring the problem of antibiotic resistance into the full view of the general public every time that they do their ‘weekly shopping’. Data collection could involve linking local healthcare data, for example, local antibiotic prescribing practices, local antibiotic resistance profiles, rates of patient relapse, etc., to ‘wearable technologies’(5) measuring, for example, fever, increased pulse rate, change in blood pressure and rate of sweat production, among others. Governments and healthcare authorities could be encouraging companies such as IBM, Apple, Google, etc., to think about anonymized data collection and the development of supercomputer algorithms for global antibiotic resistance. Similarities between cigarette smoking and taking antibiotics include: the general public may ignore the advice of health professionals relating to both subjects; patients may consider that any negative effects will only occur to someone else, or will occur sometime in the future, or may believe that taking one small dose now will have little effect on the development of serious side effects to other individuals (think of passive smoking and the transfer of antibiotic resistant organisms between individuals).
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ISSN:1746-0913
1746-0921
DOI:10.2217/fmb-2016-0121