» Articles » PMID: 33874998

Effectiveness of Potential Antiviral Treatments in COVID-19 Transmission Control: a Modelling Study

Abstract

Background: Novel coronavirus disease 2019 (COVID-19) causes an immense disease burden. Although public health countermeasures effectively controlled the epidemic in China, non-pharmaceutical interventions can neither be maintained indefinitely nor conveniently implemented globally. Vaccination is mainly used to prevent COVID-19, and most current antiviral treatment evaluations focus on clinical efficacy. Therefore, we conducted population-based simulations to assess antiviral treatment effectiveness among different age groups based on its clinical efficacy.

Methods: We collected COVID-19 data of Wuhan City from published literature and established a database (from 2 December 2019 to 16 March 2020). We developed an age-specific model to evaluate the effectiveness of antiviral treatment in patients with COVID-19. Efficacy was divided into three types: (1) viral activity reduction, reflected as transmission rate decrease [reduction was set as v (0-0.8) to simulate hypothetical antiviral treatments]; (2) reduction in the duration time from symptom onset to patient recovery/removal, reflected as a 1/γ decrease (reduction was set as 1-3 days to simulate hypothetical or real-life antiviral treatments, and the time of asymptomatic was reduced by the same proportion); (3) fatality rate reduction in severely ill patients (f) [reduction (z) was set as 0.3 to simulate real-life antiviral treatments]. The population was divided into four age groups (groups 1, 2, 3 and 4), which included those aged ≤ 14; 15-44; 45-64; and ≥ 65 years, respectively. Evaluation indices were based on outbreak duration, cumulative number of cases, total attack rate (TAR), peak date, number of peak cases, and case fatality rate (f).

Results: Comparing the simulation results of combination and single medication therapy s, all four age groups showed better results with combination medication. When 1/γ = 2 and v = 0.4, age group 2 had the highest TAR reduction rate (98.48%, 56.01-0.85%). When 1/γ = 2, z = 0.3, and v = 0.1, age group 1 had the highest reduction rate of f (83.08%, 0.71-0.12%).

Conclusions: Antiviral treatments are more effective in COVID-19 transmission control than in mortality reduction. Overall, antiviral treatments were more effective in younger age groups, while older age groups showed higher COVID-19 prevalence and mortality. Therefore, physicians should pay more attention to prevention of viral spread and patients deaths when providing antiviral treatments to patients of older age groups.

Citing Articles

Insights from a community-based survey on factors influencing acceptance and uptake of Paxlovid (nirmatrelvir and ritonavir) as a COVID-19 antiviral medication in Singapore.

Soh S, Ong W, Thein T, Griva K, Chen I BMC Public Health. 2024; 24(1):2332.

PMID: 39198783 PMC: 11351289. DOI: 10.1186/s12889-024-19687-0.


Model-based analysis of the incidence trends and transmission dynamics of COVID-19 associated with the Omicron variant in representative cities in China.

Ma Y, Xu S, Luo Y, Li J, Lei L, He L BMC Public Health. 2023; 23(1):2400.

PMID: 38042794 PMC: 10693062. DOI: 10.1186/s12889-023-17327-7.


Impact of vaccination and non-pharmacological interventions on COVID-19: a review of simulation modeling studies in Asia.

Thakkar K, Spinardi J, Yang J, Kyaw M, Ozbilgili E, Mendoza C Front Public Health. 2023; 11:1252719.

PMID: 37818298 PMC: 10560858. DOI: 10.3389/fpubh.2023.1252719.


Epidemiological characteristics and transmission dynamics of the COVID-19 outbreak in Hohhot, China: a time-varying SQEIAHR model analysis.

Ma Y, Xu S, Luo Y, Qin Y, Li J, Lei L Front Public Health. 2023; 11:1175869.

PMID: 37415698 PMC: 10321150. DOI: 10.3389/fpubh.2023.1175869.


Optimal control strategies of SARS-CoV-2 Omicron supported by invasive and dynamic models.

Rui J, Zheng J, Chen J, Wei H, Yu S, Zhao Z Infect Dis Poverty. 2022; 11(1):115.

PMID: 36435792 PMC: 9701379. DOI: 10.1186/s40249-022-01039-y.


References
1.
Wu Z, McGoogan J . Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72 314 Cases From the Chinese Center for Disease Control and Prevention. JAMA. 2020; 323(13):1239-1242. DOI: 10.1001/jama.2020.2648. View

2.
Cao Y, Su B, Guo X, Sun W, Deng Y, Bao L . Potent Neutralizing Antibodies against SARS-CoV-2 Identified by High-Throughput Single-Cell Sequencing of Convalescent Patients' B Cells. Cell. 2020; 182(1):73-84.e16. PMC: 7231725. DOI: 10.1016/j.cell.2020.05.025. View

3.
Broockman D, Kalla J, Guerrero A, Budolfson M, Eyal N, Jewell N . Broad cross-national public support for accelerated COVID-19 vaccine trial designs. Vaccine. 2020; 39(2):309-316. PMC: 7831807. DOI: 10.1016/j.vaccine.2020.11.072. View

4.
Guan W, Ni Z, Hu Y, Liang W, Ou C, He J . Clinical Characteristics of Coronavirus Disease 2019 in China. N Engl J Med. 2020; 382(18):1708-1720. PMC: 7092819. DOI: 10.1056/NEJMoa2002032. View

5.
Sterne J, Murthy S, Diaz J, Slutsky A, Villar J, Angus D . Association Between Administration of Systemic Corticosteroids and Mortality Among Critically Ill Patients With COVID-19: A Meta-analysis. JAMA. 2020; 324(13):1330-1341. PMC: 7489434. DOI: 10.1001/jama.2020.17023. View