Modeling the Inactivation of Viruses from the Coronaviridae Family in Response to Temperature and Relative Humidity in Suspensions or on Surfaces.
Laurent GuillierSandra Martin-LatilEstelle ChaixAnne ThébaultNicole PavioSophie Le PoderChristophe BatéjatFabrice V BiotLionel KochDonald W SchaffnerMoez Sanaanull nullPublished in: Applied and environmental microbiology (2020)
Temperature and relative humidity are major factors determining virus inactivation in the environment. This article reviews inactivation data regarding coronaviruses on surfaces and in liquids from published studies and develops secondary models to predict coronaviruses inactivation as a function of temperature and relative humidity. A total of 102 D values (i.e., the time to obtain a log10 reduction of virus infectivity), including values for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), were collected from 26 published studies. The values obtained from the different coronaviruses and studies were found to be generally consistent. Five different models were fitted to the global data set of D values. The most appropriate model considered temperature and relative humidity. A spreadsheet predicting the inactivation of coronaviruses and the associated uncertainty is presented and can be used to predict virus inactivation for untested temperatures, time points, or any coronavirus strains belonging to Alphacoronavirus and Betacoronavirus genera.IMPORTANCE The prediction of the persistence of SARS-CoV-2 on fomites is essential in investigating the importance of contact transmission. This study collects available information on inactivation kinetics of coronaviruses in both solid and liquid fomites and creates a mathematical model for the impact of temperature and relative humidity on virus persistence. The predictions of the model can support more robust decision-making and could be useful in various public health contexts. A calculator for the natural clearance of SARS-CoV-2 depending on temperature and relative humidity could be a valuable operational tool for public authorities.
Keyphrases
- sars cov
- respiratory syndrome coronavirus
- public health
- decision making
- healthcare
- case control
- electronic health record
- emergency department
- escherichia coli
- randomized controlled trial
- coronavirus disease
- staphylococcus aureus
- machine learning
- meta analyses
- cystic fibrosis
- disease virus
- deep learning
- artificial intelligence