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. Author manuscript; available in PMC: 2016 Sep 1.
Published in final edited form as: J Glob Antimicrob Resist. 2015 Jun 3;3(3):174–183. doi: 10.1016/j.jgar.2015.04.006

Fig. 4.

Fig. 4

Correlation between actual resistance and predicted resistance for the test years using BARDmaps and linear regression predictions. Each dot designates a bacteria/antimicrobial pair (BAP) in a specific country. Solid line = identity line. R shown on the graph is the Pearson's coefficient. (A) Correlation between actual resistance and resistance predicted by BARDmaps for 1-year (left panel) and 2-year predictions (right panel). Prediction for 1 future year: slope = 0.93; significant correlation (P < 0.0001); Pearson's coefficient, R = 0.96; N = 644. Prediction for 2 future years: slope = 0.99; significant correlation (P < 0.0001); Pearson's coefficient, R = 0.97. (B) The correlation graphs for predictions based on linear regression for 1 year (Pearson's coefficient, R = 0.98; N = 644) and 2 years (Pearson's coefficient, R = 0.88; N = 644). (C) Expansion of the region between 0% and 50% resistance for the graphs of panel (A) showing that high correlation also exist between BARDmaps predictions and actual resistances for BAPs at the lower end of resistance levels (R = 0.90 for 1-year prediction and R = 0.91 for 2-year prediction). A detailed comparison between BARDmaps and linear regression predictions is shown in Table 1.