OBJECTIVES: Some oral SARS-CoV-2 antivirals have been approved in Japan under COVID-19 pandemic. However, the actual prescription volume was far below the number of COVID-19 patients. To assess the reason for this, we built a state transitional agent-based model reflecting the clinical pathway of COVID-19 patients using validated parameters such as the number of the infections and the prescription volume of oral antivirals.

METHODS: We developed an Agent-based Model to reproduce the therapeutic situation in March 2023. In the model, Parameter 1 (P1) denotes the probability of experiencing symptoms given infected; P2, of visiting medical institutions given experiencing symptoms without self-tests; P3, of conducting self-tests given experiencing symptoms; P4, of conducting self-tests given not experiencing symptoms; P5, of visiting medical institutions given self-tests; P6, of being diagnosed with COVID-19 at the medical institutions authorized to prescribe the antivirals given visiting institutions; P7, of prescription of the antivirals given being diagnosed COVID-19 at the institutions. The parameters, P1, P2, P3, P4, and P7 were referred to previous studies. We validated the parameters using the government data on 1) the volume of the antiviral prescription and 2) the number of infections. The remaining parameters were estimated thorough the validation. In this study, we used the prescription volume of ensitrelvir, one of the oral antivirals.

RESULTS: The assigned parameters were P1=67%, P2=34%, P3=36%, P4=10% and P7=17%. The remaining parameters were estimated as P5=46% and P6=12%. P6 value was notable low and increasing of P6 value resulted in a notable increase in the prescription volume.

CONCLUSIONS: Our analysis implies that the primary reason for a low amount of prescription is that medical institutions are not prepared to prescribe the oral antivirals. Japan has relaxed COVID-19 infection control measures since May 2023. Therefore, we will update the model for the predictions to reflect the latest situation.