Estimating the population-level effects of nonpharmaceutical interventions when transmission rates of COVID-19 vary by orders of magnitude from one contact to another.

Publication date: Dec 01, 2024

Statistical physicists have long studied systems where the variable of interest spans many orders of magnitude, the classic example is the relaxation times of glassy materials, which are often found to follow power laws. A power-law dependence has been found for the probability of transmission of COVID-19, as a function of length of time a susceptible person is in contact with an infected person. This is in data from the United Kingdom’s COVID-19 app. The amount of virus in infected people spans many orders of magnitude. Inspired by this, I assume that the power-law behavior found in COVID-19 transmission is due to the effective transmission rate varying over orders of magnitude from one contact to another. I then use a model from statistical physics to estimate that if a population all wear FFP2/N95 masks, this reduces the effective reproduction number for COVID-19 transmission by a factor of approximately nine.

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Concepts Keywords
Covid COVID-19
N95 Humans
Physicists Masks
Relaxation SARS-CoV-2
Virus

Semantics

Type Source Name
disease MESH COVID-19
pathway REACTOME Reproduction
drug DRUGBANK Medical air
disease IDO process
disease MESH tuberculosis
pathway KEGG Tuberculosis
disease MESH infection
disease IDO intervention
disease IDO susceptibility
disease MESH viral load
disease MESH viral infection
drug DRUGBANK Prothrombin
drug DRUGBANK Water
drug DRUGBANK Ranitidine
disease MESH bile
disease IDO assay
disease MESH respiratory diseases
drug DRUGBANK Pentaerythritol tetranitrate
disease MESH infectious diseases
disease MESH severe acute respiratory syndrome
drug DRUGBANK Tromethamine
disease MESH respiratory infections
drug DRUGBANK Adenosine 5′-phosphosulfate
disease IDO infectivity
disease MESH Inflammation
drug DRUGBANK Vorinostat
disease IDO pathogen
disease IDO host

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