1384. Conceptual Economic Model Methodology for Infant Pneumococcal Conjugate Vaccine Program and its Impact on Antimicrobial Resistance

Background Antimicrobial resistance (AMR) is a global threat to effective prevention and treatment of an ever-increasing range of infections. Pneumococcal conjugate vaccines (PCV) used in infant national immunization programs have been shown to decrease AMR pneumococci. Cost-effectiveness models evaluating the value for money of PCV programs have not considered the economic impact of reducing antimicrobial prescribing or prolonged infections due to treatment failures. Standardized frameworks are needed for models to address outcomes and impact on health resource utilization related to AMR. Methods We developed a conceptual modeling methodology suitable for a health economic evaluation of an infant PCV program. We considered impact of PCVs on pneumococcal disease (PD) specifically related to clinical management of AMR-PD, including AMR epidemiology, antibiotic prescribing patterns, and healthcare resource utilization. Model inputs were evaluated regarding optimal and available data sources considering the complex nature of AMR at the national, regional, and global level. Results The proposed framework considers impact of PCVs on antimicrobial prescribing due to invasive pneumococcal disease (IPD), community acquired pneumonia (CAP), and acute otitis media (AOM) across 3 pathways (Figure 1). The population and pathogen-level pathway describe epidemiology and vaccine impact. The care level pathway describes clinical disease management. The health outcomes pathway characterizes resistant or successfully treated PD costs and quality of life. Conceptual Economic Model Methodology Conclusion We present a generalizable methodology to quantify impact of PCVs on cases and outcomes of PD related to AMR. Modelling vaccine-preventable burden of AMR-PD requires data extrapolations and assumptions due to the myriad of interconnected pathways (i.e. microbiology, epidemiology, environment, health systems). Further work is needed to validate assumptions and linkages across incomplete data sources. Disclosures Raymond Farkouh, PhD, Pfizer (Employee) Arianna Nevo, MPH, Pfizer, Inc. (Other Financial or Material Support, I am an employee of IQVIA. IQVIA received funding from Pfizer to carry out the project.) Jennifer Uyei, PhD, MPH, Pfizer, Inc. (Other Financial or Material Support, I am an employee of IQVIA. IQVIA received funding from Pfizer to carry out the project.) Cassandra Hall-Murray, PharmD, Pfizer, Inc. (Employee) Joseph Lewnard, PhD, Pfizer, Inc. (Consultant, Grant/Research Support, Advisor or Review Panel member) Matthew Wasserman, MSc., Pfizer Inc. (Employee)