6533b7d6fe1ef96bd1266869
RESEARCH PRODUCT
Diffusion modeling of COVID-19 under lockdown
Nicola SerraConsolato SergiTeresa ReaPaola Di Carlosubject
Settore MED/17 - Malattie InfettiveCoronavirus disease 2019 (COVID-19)Fitness landscapeSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)virusesComputational Mechanicsmedicine.disease_cause01 natural sciencesSettore MED/01 - Statistica Medica010305 fluids & plasmassymbols.namesakeARTICLES0103 physical sciencesmedicineStatistical physicsDiffusion (business)010306 general physicsCoronavirusFluid Flow and Transfer ProcessesPhysicsDiffusion modelingBiofluid MechanicsMechanical EngineeringMarkov chain Monte CarloCondensed Matter PhysicsDiffusion modeling COVI 19Mechanics of MaterialssymbolsIsing modeldescription
Viral immune evasion by sequence variation is a significant barrier to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine design and coronavirus disease-2019 diffusion under lockdown are unpredictable with subsequent waves. Our group has developed a computational model rooted in physics to address this challenge, aiming to predict the fitness landscape of SARS-CoV-2 diffusion using a variant of the bidimensional Ising model (2DIMV) connected seasonally. The 2DIMV works in a closed system composed of limited interaction subjects and conditioned by only temperature changes. Markov chain Monte Carlo method shows that an increase in temperature implicates reduced virus diffusion and increased mobility, leading to increased virus diffusion.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2021-04-01 | Physics of Fluids |