Using novel causal inference approaches to improve decision-making in infectious diseases epidemiology

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Health care professionals face challenges in infectious diseases(ID) treatment and control from rapid spread of drug-resistant pathogens. Most evidence has come from randomised clinical trials (RCT); however, these are expensive to run, and their generalisability has been questioned. Causal inference methods are available to address this issue, but the uptake of these methods in ID has been limited. This study aims to utilise these epidemiological modelling to enhance the quality of future RCTs.