To investigate the effect of parameter changes on the results presented by simulations in the main text using baseline values, we performed sensitivity analyses by considering a sampling approach that allows for the simultaneous variations of several key parameters, including the basic reproduction number R 0 , the rate of de novo resistant mutations α, the rate of conversion between resistant strains γ, the relative transmissibility of the resistant strain δ r , and the probability of developing clinical disease p. Using the Latin Hypercube Sampling technique [2] , we generated samples of size n = 1000 in which each parameter is treated as a random variable and assigned a probability function. In this technique, the parameters are uniformly distributed and sampled within their respective ranges. The reproduction number was uniformly sampled from the range [1.5, 2.5] (values found in references [3, 4] ), and the rate of de novo resistant emergence was sampled from the range [0.018, 0.072] (values taken from references [5, 6] ). The corresponding range for the conversion rate of resistant strains was computed using the constraint that the fraction of treated individuals hosting resistance, which undergoes compensatory mutations and subsequently generates resistant strains with high fitness, lies between 1/5000 and 1/500 [7, 8] .