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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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Jaffar et al. (2021) studied this question.
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