Citation
Mohd Jaffar, Mai Zurwatul Ahlam and Zailan, Aimi Najwa
(2021)
Antimicrobial Resistance (AMR)-Forecast for 30 countries in Europe.
Science Heritage Journal, 5 (2).
44 - 48.
ISSN 2521-0858; ESSN: 2521-0866
Abstract
Antimicrobial resistance (AMR) has emerged among the most serious public health issues, prompting the creation of worldwide implementation strategies. In this study, the application of seasonal or time-series approaches was suggested for forecasting the unknown percentages of resistance towards other microbial groups for seven microorganisms. Annual data between 2012 and 2019 were acquired from European Centre for Disease Prevention, and Control (ECDC) reports. Microsoft Excel’s function, ‘FORECAST.ETS’, was used for prediction purposes. Then, a brief analysis was done on the forecasted results. Forecasting AMR’s percentage makes it possible to develop a strategy for dealing with any situation that may emerge.
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Additional Metadata
| Item Type: | Article |
|---|---|
| Divisions: | Faculty of Science |
| DOI Number: | https://doi.org/10.26480/gws.02.2021.44.48 |
| Publisher: | Zibeline International |
| Keywords: | Antimicrobial resistance; Antimicrobials; Forecasting |
| Depositing User: | Ms. Nuraida Ibrahim |
| Date Deposited: | 21 Mar 2023 04:16 |
| Last Modified: | 21 Mar 2023 04:16 |
| Altmetrics: | http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.26480/gws.02.2021.44.48 |
| URI: | http://psasir.upm.edu.my/id/eprint/95920 |
| Statistic Details: | View Download Statistic |
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