Modeling the population-level impact of treatment on COVID-19 disease and SARS-CoV-2 transmission
Monia Makhoul,
Farah Abu-Hijleh,
Houssein H. Ayoub,
Shaheen Seedat,
Hiam Chemaitelly,
Laith J. Abu-Raddad
Affiliations
Monia Makhoul
Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha 24144, Qatar; World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University, Qatar-Foundation-Education City, Doha 24144, Qatar; Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York City, NY 10021, USA
Farah Abu-Hijleh
Department of Public Health, College of Health Sciences, Academic Quality Affairs Office, QU Health, Qatar University, Doha 2713, Qatar
Houssein H. Ayoub
Mathematics Program, Department of Mathematics, Statistics and Physics, College of Arts and Sciences, Qatar University, Doha 2713, Qatar
Shaheen Seedat
Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha 24144, Qatar; World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University, Qatar-Foundation-Education City, Doha 24144, Qatar; Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York City, NY 10021, USA
Hiam Chemaitelly
Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha 24144, Qatar; World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University, Qatar-Foundation-Education City, Doha 24144, Qatar; Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York City, NY 10021, USA
Laith J. Abu-Raddad
Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha 24144, Qatar; World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University, Qatar-Foundation-Education City, Doha 24144, Qatar; Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York City, NY 10021, USA; Correspondence to: Infectious Disease Epidemiology Group, Weill Cornell Medicine - Qatar, Qatar Foundation - Education City, P.O. Box 24144, Doha, Qatar.
Different COVID-19 treatment candidates are under development, and some are becoming available including two promising drugs from Merck and Pfizer. This study provides conceptual frameworks for the effects of three types of treatments, both therapeutic and prophylactic, and to investigate their population-level impact, to inform drug development, licensure, decision-making, and implementation. Different drug efficacies were assessed using an age-structured mathematical model describing SARS-CoV-2 transmission and disease progression, with application to the United States as an illustrative example. Severe and critical infection treatment reduces progression to COVID-19 severe and critical disease and death with small number of treatments needed to avert one disease or death. Post-exposure prophylaxis treatment had a large impact on flattening the epidemic curve, with large reductions in infection, disease, and death, but the impact was strongly age dependent. Pre-exposure prophylaxis treatment had the best impact and effectiveness, with immense reductions in infection, disease, and death, driven by the robust control of infection transmission. Effectiveness of both pre-exposure and post-exposure prophylaxis treatments was disproportionally larger when a larger segment of the population was targeted than a specific age group. Additional downstream potential effects of treatment, beyond the primary outcome, enhance the population-level impact of both treatments. COVID-19 treatments are an important modality in controlling SARS-CoV-2 disease burden. Different types of treatment act synergistically for a larger impact, for these treatments and vaccination.
