Alarid-Escudero, Fernando2018-02-092018-02-092017-10-23https://hdl.handle.net/11299/193363Conference poster presented at the 39th Annual Meeting of the Society for Medical Decision Making Pittsburgh, Pennsylvania, October 22-25, 2017Purpose: Helicobacter pylori (H. pylori) is the strongest known risk factor for gastric cancer and peptic ulcer disease. Programs under consideration in high risk countries to prevent H. pylori- related diseases via broad population treatment could be complicated by increasing levels of antibiotic resistance (ABR). We evaluate the impact of different mass-treatment policies on H. pylori infection and ABR in Mexico using a mathematical model. Methods: We developed an age-structured, susceptible-infected-susceptible (SIS) transmission model of H. pylori infection in Mexico that included both treatment-sensitive and treatment- resistant strains. Antibiotic treatment was assumed to either clear sensitive strains or induce acquired resistance. In addition, the model included the effects of both background antibiotic use and antibiotic treatment specifically intended to treat H. pylori infection. Model parameters were derived from the published literature and estimated from primary data. Using the model, we projected H. pylori infection and resistance levels over 20 years without treatment and for three hypothetical population-wide treatment policies assumed to be implemented in 2018: (1) treat children only (2-6 year-olds); (2) treat older adults only (>40 years old); (3) treat everyone regardless of age. Clarithromycin -introduced in Mexico in 1991- was the antibiotic considered for the treatment policies. In sensitivity analyses, we considered different mixing patterns and trends of background antibiotic use. We validated the model against historical values of prevalence of infection and ABR of H. pylori. Results: In the absence of a mass-treatment policy, our model predicts infection begins to rise in 2021, mostly caused by treatment-induced resistant strains as a product of background use of antibiotics. The impact of the policies is immediate on decreasing infection but also increasing ABR (see Figure). For example, policy 3 decreases infection by 11% but increases ABR by 23% after the first year of implementation. The relative size of the decrease in infection is 50% the increase in ABR for policies 2 and 3, and 20% for policy 1. These results agree across all scenarios considered in sensitivity analysis. Conclusions: Conclusions: Mass-treatment policies have a higher effect on increasing ABR letting resistant strains take over infection. Given the high proportion of ABR at the time of the policy implementation, mass treatment strategies are not recommended for Mexico.enH. pyloriInfectious disease modelingAntibiotic resistanceCompartmental modelMexicoOther10.1177/0272989X17751695