ArticleScientific reports2022
A simple model of COVID-19 explains disease severity and the effect of treatments.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed, 26 citations in OpenAlex.
- Utilizing Virtual Clinical Trials to Inform Target Coverage That Drives RSV Antiviral Efficacy.CPT: pharmacometrics & systems pharmacology · 2026Article
- INHERITANCE OF INTRACELLULAR VIRAL RNA IN A MULTISCALE MODEL OF HEPATITIS C INFECTION.SIAM journal on applied mathematics · 2026Article
- Viral Dynamic Models During COVID-19: Are We Ready for the Next Pandemic?CPT: pharmacometrics & systems pharmacology · 2025Review
- Post-recovery viral shedding shapes wastewater-based epidemiological inferences.Communications medicine · 2025Article
- The Performance of a Rapid Coronavirus Disease 2019 Antigen Test in Rural Gabon.The American journal of tropical medicine and hygiene · 2025Article
- A biomathematical model of SARS-CoV-2 in Syrian hamsters.Scientific reports · 2024Article
- A unifying model to explain frequent SARS-CoV-2 rebound after nirmatrelvir treatment and limited prophylactic efficacy.Nature communications · 2024Article
- A unifying model to explain high nirmatrelvir therapeutic efficacy against SARS-CoV-2, despite low post-exposure prophylaxis efficacy and frequent viral rebound.medRxiv : the preprint server for health sciences · 2024Article
- Control of complement-induced inflammatory responses to SARS-CoV-2 infection by anti-SARS-CoV-2 antibodies.The EMBO journal · 2024Article
- COVID-19 epidemiology and rural healthcare: a survey in a Spanish village.Epidemiology and infection · 2023Article
- Multi-Omic Candidate Screening for Markers of Severe Clinical Courses of COVID-19.Journal of clinical medicine · 2023Article
- Making waves: Integrating wastewater surveillance with dynamic modeling to track and predict viral outbreaks.Water research · 2023Article
- Dynamical modelling of viral infection and cooperative immune protection in COVID-19 patients.PLoS computational biology · 2023Article
- A Continuation Technique for Maximum Likelihood Estimators in Biological Models.Bulletin of mathematical biology · 2023Article
- Relationship between the inclusion/exclusion criteria and sample size in randomized controlled trials for SARS-CoV-2 entry inhibitors.Journal of theoretical biology · 2023Article
- Article
- Could a simple model of COVID-19 infections be the key to designing better virus-based therapies?Synthetic biology (Oxford, England) · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
Considerable effort has been made to better understand why some people suffer from severe COVID-19 while others remain asymptomatic. This has led to important clinical findings; people with severe COVID-19 generally experience persistently high levels of inflammation, slower viral load decay, display a dysregulated type-I interferon response, have less active natural killer cells and increased levels of neutrophil extracellular traps. How these findings are connected to the pathogenesis of COVID-19 remains unclear. We propose a mathematical model that sheds light on this issue by focusing on cells that trigger inflammation through molecular patterns: infected cells carrying pathogen-associated molecular patterns (PAMPs) and damaged cells producing damage-associated molecular patterns (DAMPs). The former signals the presence of pathogens while the latter signals danger such as hypoxia or lack of nutrients. Analyses show that SARS-CoV-2 infections can lead to a self-perpetuating feedback loop between DAMP expressing cells and inflammation, identifying the inability to quickly clear PAMPs and DAMPs as the main contributor to hyperinflammation. The model explains clinical findings and reveal conditions that can increase the likelihood of desired clinical outcome from treatment administration. In particular, the analysis suggest that antivirals need to be administered early during infection to have an impact on disease severity. The simplicity of the model and its high level of consistency with clinical findings motivate its use for the formulation of new treatment strategies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.