Back

Informing antiviral effectiveness for influenza A andSARS-CoV-2 by quantifying within-host interaction betweentransmission and immunity

Gokhale, D.; Criado, M. F.; Rowe, D. K.; Tomkins, S. M.; Rohani, P.

2025-03-12 ecology
10.1101/2025.03.11.642706 bioRxiv
Show abstract

Antiviral therapies are among the most effective pharmaceutical interventions in treatment of a variety of viral pathogens. To optimize the antiviral effectiveness it is crucial to characterize the relationship between multiple cellular modes of antiviral action and the complex response of the hosts innate immune system relative to the within host dynamics of a proliferating virus. Since their introduction in 1968 and 2019, Influenza A virus (IAV) H3N2 and Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), respectively, have caused unprecedented damage on the public health infrastructure globally. In addition to the substantial burden of morbidity and mortality around the world, both viruses have the potential of undergoing evolution leading to antigenic escape from the prevailing interventions. These biological characteristics advocate for urgent development of effective antivirals for the treatment of IAV and SARS-CoV-2. In this multi-stage study, we develop a suite of within-host models encompassing a number of hypotheses regarding virus-specific innate host functional responses and their impacts on the proliferation of IAV H3N2 and SARS-CoV-2 viruses. We use likelihood-based statistical inference to confront these hypotheses with infection data on IAV H3N2 and SARS-CoV-2 from infection experiments in ferrets. Upon identifying the best-fitting model of within-host dynamics, we can quantify the potential impact of antiviral drug therapy as a function of effectiveness and timing of initiation. We find significant mechanistic differences between the infection dynamics of H3N2 IAV and SARS-CoV-2 and associated model parameters. The treatment consequences of these differences are that SARS-CoV-2 is harder to control with antivirals, requiring earlier initiation and a more effective drug. Author summaryAntiviral drugs are prophylactic chemical agents that are used to contain several viral infections. Influenza A H3N2 virus (H3N2) and Severe Acute Respiratory Syndrome Corona Virus-2 (SARS-CoV-2) are very important viral pathogens that have caused unprecedented, global public health damage in the recent times. This makes development of antiviral drugs crucial along with other pharmaceutical prophylactics like vaccination. To optimize the pathogen specific effectiveness, however, it is necessary to simultaneously explore the relationship among the intra-host viral kinetics, immune dynamics and modes of antiviral action. In this article we theoretically analyze antiviral action of a drug in union with effect of the hosts innate immune system in containing infections of SARS-CoV-2 and H3N2 in infection experiments with ferrets. We find fundamental differences in the requisite antiviral effectiveness which, we posit, is due to substantially different inter-cellular proliferation potential between the two viruses.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

1
Journal of Theoretical Biology
144 papers in training set
Top 0.1%
33.5%
2
PLOS Computational Biology
1633 papers in training set
Top 2%
15.0%
3
iScience
1063 papers in training set
Top 2%
4.9%
50% of probability mass above
4
PLOS ONE
4510 papers in training set
Top 31%
4.9%
5
Scientific Reports
3102 papers in training set
Top 22%
4.9%
6
Bulletin of Mathematical Biology
84 papers in training set
Top 0.8%
2.1%
7
Journal of The Royal Society Interface
189 papers in training set
Top 2%
2.1%
8
Proceedings of the Royal Society B: Biological Sciences
341 papers in training set
Top 3%
2.1%
9
eLife
5422 papers in training set
Top 35%
2.1%
10
Vaccines
196 papers in training set
Top 0.9%
2.1%
11
Archives of Clinical and Biomedical Research
28 papers in training set
Top 0.6%
1.8%
12
Viruses
318 papers in training set
Top 3%
1.7%
13
Journal of Biosciences
12 papers in training set
Top 0.1%
1.7%
14
Frontiers in Ecology and Evolution
60 papers in training set
Top 3%
1.1%
15
PeerJ
261 papers in training set
Top 15%
0.8%
16
mSystems
361 papers in training set
Top 7%
0.7%
17
Ecology
70 papers in training set
Top 0.8%
0.7%
18
Proceedings of the National Academy of Sciences
2130 papers in training set
Top 45%
0.7%
19
Computers in Biology and Medicine
120 papers in training set
Top 5%
0.7%
20
Computational and Structural Biotechnology Journal
216 papers in training set
Top 11%
0.7%
21
Theoretical Ecology
21 papers in training set
Top 0.2%
0.5%
22
Frontiers in Immunology
586 papers in training set
Top 10%
0.5%
23
Journal of Chemical Information and Modeling
207 papers in training set
Top 4%
0.5%
24
Virus Evolution
140 papers in training set
Top 2%
0.5%
25
Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences
15 papers in training set
Top 1%
0.5%
26
Frontiers in Virology
15 papers in training set
Top 0.2%
0.5%