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Quantifying the value of surveillance data for improving model predictions of lymphatic filariasis elimination

Fig 2

Comparison of the distributions of predicted timelines to LF elimination from the three models for Kirare, Tanzania.

This visual comparison shows that the predictions coming from the model-only simulations (scenario 0) have the widest spread in their distributions for all three models compared to model predictions obtained via constraining using subsequent data scenarios. Pairwise Kolmogorov-Smirnov tests for equal distributions were performed on the results from each model to evaluate whether updating the models with sequential data changed the distribution of predictions. Significance was determined using the Benjamini-Hochberg procedure for controlling the false discovery rate (q = 0.05). Apart from scenarios 2 and 3 for EPIFIL and scenarios 3 and 4 for LYMFASIM, all distributions were significantly different from one another (see S2 Supplementary Information for results from the villages of Alagramam and Peneng).

Fig 2