RESUMO
BACKGROUND AND OBJECTIVES: Nirmatrelvir/ritonavir was administered orally to manage mild to moderate symptoms of COVID-19 in adult patients. The objectives of this study were to (i) evaluate the cost-effectiveness of prescribing nirmatrelvir/ritonavir within 5 days of a COVID-19 illness in order to avert hospitalization within a 30-day period in the Malaysia setting; (ii) determine how variations in pricing and hospitalization rates will affect the cost-effectiveness of nirmatrelvir/ritonavir. METHODS: The 30-day hospitalization related to COVID-19 was determined using 1 to 1 propensity score-matched real-world data in Malaysia from 14 July 2022 to 14 November 2022. To determine the total per-person costs related to COVID-19, we added the cost of drug (nirmatrelvir/ritonavir or control), clinic visits and inpatient care. Incremental cost-effectiveness ratio (ICER) per hospitalization averted was calculated. RESULTS: Our cohort included 31,487 patients. The rate of hospitalization within 30 days was found to be 0.35% for the group treated with nirmatrelvir/ritonavir, and 0.52% for the control group. The nirmatrelvir/ritonavir group cost an additional MYR 1,625.72 (USD 358.88) per patient. This treatment also resulted in a reduction of 0.17% risk for hospitalization, which corresponded to an ICER of MYR 946,801.26 (USD 209,006.90) per hospitalization averted. CONCLUSION: In Malaysia, where vaccination rates were high, nirmatrelvir/ritonavir has been shown to be beneficial in the outpatient treatment of adults with COVID-19 who have risk factors; however, it was only marginally cost effective against hospitalization for healthy adults during the Omicron period.
RESUMO
The conventional susceptible-infectious-recovered (SIR) model tends to magnify the transmission dynamics of infectious diseases, and thus the estimated total infections and immunized population may be higher than the threshold required for infection control and eradication. The study developed a new SIR framework that allows the transmission rate of infectious diseases to decline along with the reduced risk of contact infection to overcome the limitations of the conventional SIR model. Two new SIR models were formulated to mimic the declining transmission rate of infectious diseases at different stages of transmission. Model A utilized the declining transmission rate along with the reduced risk of contact infection following infection, while Model B incorporated the declining transmission rate following recovery. Both new models and the conventional SIR model were then used to simulate an infectious disease with a basic reproduction number (r0) of 3.0 and a herd immunity threshold (HIT) of 0.667 with and without vaccination. Outcomes of simulations were assessed at the time when the total immunized population reached the level predicted by the HIT, and at the end of simulations. Further, all three models were used to simulate the transmission dynamics of seasonal influenza in the United States and disease burdens were projected and compared with estimates from the Centers for Disease Control and Prevention. For the simulated infectious disease, in the initial phase of the outbreak, all three models performed expectedly when the sizes of infectious and recovered populations were relatively small. As the infectious population increased, the conventional SIR model appeared to overestimate the infections even when the HIT was achieved in all scenarios with and without vaccination. For the same scenario, Model A appeared to attain the level predicted by the HIT and in comparison, Model B projected the infectious disease to be controlled at the level predicted by the HIT only at high vaccination rates. For infectious diseases with high r0, and at low vaccination rates, the level at which the infectious disease was controlled cannot be accurately predicted by the current theorem. Transmission dynamics of infectious diseases with herd immunity can be accurately modelled by allowing the transmission rate of infectious diseases to decline along with the reduction of contact infection risk after recovery or vaccination. Model B provides a credible framework for modelling infectious diseases with herd immunity in a randomly mixed population.