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AuthorMonia, Makhoul
AuthorAbu-Hijleh, Farah
AuthorAyoub, Houssein H.
AuthorSeedat, Shaheen
AuthorChemaitelly, Hiam
AuthorAbu-Raddad, Laith J.
Available date2022-04-24T07:38:37Z
Publication Date2022-06-30
Publication NameEpidemics
Identifierhttp://dx.doi.org/10.1016/j.epidem.2022.100567
CitationMakhoul, M., Abu-Hijleh, F., Ayoub, H. H., Seedat, S., Chemaitelly, H., & Abu-Raddad, L. J. (2022). Modeling the population-level impact of treatment on COVID-19 disease and SARS-CoV-2 transmission. Epidemics, 100567.
ISSN17554365
URIhttps://www.sciencedirect.com/science/article/pii/S1755436522000214
URIhttp://hdl.handle.net/10576/30243
AbstractDifferent 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.
SponsorThe authors are grateful for support provided by the Biomedical Research Program and the Biostatistics, Epidemiology, and Biomathematics Research Core, both at Weill Cornell Medicine-Qatar. This publication was made possible by extension of models developed through the National Priorities Research Program (NPRP), Qatar, grant number 9–040-3–008 (Principal investigator: LJA) and NPRP grant number 12S-0216–190094 (Principal investigator: LJA) from the Qatar National Research Fund (a member of Qatar Foundation; https://www.qnrf.org). The statements made herein are solely the responsibility of the authors. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Languageen
PublisherElsevier
SubjectSARS-CoV-2
COVID-19
Treatment
Transmission
Mathematical model
Population-level
TitleModeling the population-level impact of treatment on COVID-19 disease and SARS-CoV-2 transmission
TypeArticle
Volume Number39
Open Access user License http://creativecommons.org/licenses/by/4.0/
dc.accessType Open Access


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