tetano
Editor, Senior Moderator
BMC Med
. 2021 Mar 1;19(1):54.
doi: 10.1186/s12916-021-01926-5.
Optimizing antiviral treatment for seasonal influenza in the USA: a mathematical modeling analysis
Matan Yechezkel[SUP] #[/SUP][SUP] 1 [/SUP], Martial L Ndeffo Mbah[SUP] #[/SUP][SUP] 2 3 [/SUP], Dan Yamin[SUP] #[/SUP][SUP] 4 5 6 [/SUP]
Affiliations
Abstract
Background: Seasonal influenza remains a major cause of morbidity and mortality in the USA. Despite the US Centers for Disease Control and Prevention recommendation promoting the early antiviral treatment of high-risk patients, treatment coverage remains low.
Methods: To evaluate the population-level impact of increasing antiviral treatment timeliness and coverage among high-risk patients in the USA, we developed an influenza transmission model that incorporates data on infectious viral load, social contact, and healthcare-seeking behavior. We modeled the reduction in transmissibility in treated individuals based on their reduced daily viral load. The reduction in hospitalizations following treatment was based on estimates from clinical trials. We calibrated the model to weekly influenza data from Texas, California, Connecticut, and Virginia between 2014 and 2019. We considered in the baseline scenario that 2.7-4.8% are treated within 48 h of symptom onset while an additional 7.3-12.8% are treated after 48 h of symptom onset. We evaluated the impact of improving the timeliness and uptake of antiviral treatment on influenza cases and hospitalizations.
Results: Model projections suggest that treating high-risk individuals as early as 48 h after symptom onset while maintaining the current treatment coverage level would avert 2.9-4.5% of all symptomatic cases and 5.5-7.1% of all hospitalizations. Geographic variability in the effectiveness of earlier treatment arises primarily from variabilities in vaccination coverage and population demographics. Regardless of these variabilities, we found that when 20% of the high-risk individuals were treated within 48 h, the reduction in hospitalizations doubled. We found that treatment of the elderly population (> 65 years old) had the highest impact on reducing hospitalizations, whereas treating high-risk individuals aged 5-19 years old had the highest impact on reducing transmission. Furthermore, the population-level benefit per treated individual is enhanced under conditions of high vaccination coverage and a low attack rate during an influenza season.
Conclusions: Increased timeliness and coverage of antiviral treatment among high-risk patients have the potential to substantially reduce the burden of seasonal influenza in the USA, regardless of influenza vaccination coverage and the severity of the influenza season.
Keywords: Antiviral treatment; Mathematical modeling; Seasonal influenza; Vaccination.
. 2021 Mar 1;19(1):54.
doi: 10.1186/s12916-021-01926-5.
Optimizing antiviral treatment for seasonal influenza in the USA: a mathematical modeling analysis
Matan Yechezkel[SUP] #[/SUP][SUP] 1 [/SUP], Martial L Ndeffo Mbah[SUP] #[/SUP][SUP] 2 3 [/SUP], Dan Yamin[SUP] #[/SUP][SUP] 4 5 6 [/SUP]
Affiliations
- PMID: 33641677
- DOI: 10.1186/s12916-021-01926-5
Abstract
Background: Seasonal influenza remains a major cause of morbidity and mortality in the USA. Despite the US Centers for Disease Control and Prevention recommendation promoting the early antiviral treatment of high-risk patients, treatment coverage remains low.
Methods: To evaluate the population-level impact of increasing antiviral treatment timeliness and coverage among high-risk patients in the USA, we developed an influenza transmission model that incorporates data on infectious viral load, social contact, and healthcare-seeking behavior. We modeled the reduction in transmissibility in treated individuals based on their reduced daily viral load. The reduction in hospitalizations following treatment was based on estimates from clinical trials. We calibrated the model to weekly influenza data from Texas, California, Connecticut, and Virginia between 2014 and 2019. We considered in the baseline scenario that 2.7-4.8% are treated within 48 h of symptom onset while an additional 7.3-12.8% are treated after 48 h of symptom onset. We evaluated the impact of improving the timeliness and uptake of antiviral treatment on influenza cases and hospitalizations.
Results: Model projections suggest that treating high-risk individuals as early as 48 h after symptom onset while maintaining the current treatment coverage level would avert 2.9-4.5% of all symptomatic cases and 5.5-7.1% of all hospitalizations. Geographic variability in the effectiveness of earlier treatment arises primarily from variabilities in vaccination coverage and population demographics. Regardless of these variabilities, we found that when 20% of the high-risk individuals were treated within 48 h, the reduction in hospitalizations doubled. We found that treatment of the elderly population (> 65 years old) had the highest impact on reducing hospitalizations, whereas treating high-risk individuals aged 5-19 years old had the highest impact on reducing transmission. Furthermore, the population-level benefit per treated individual is enhanced under conditions of high vaccination coverage and a low attack rate during an influenza season.
Conclusions: Increased timeliness and coverage of antiviral treatment among high-risk patients have the potential to substantially reduce the burden of seasonal influenza in the USA, regardless of influenza vaccination coverage and the severity of the influenza season.
Keywords: Antiviral treatment; Mathematical modeling; Seasonal influenza; Vaccination.