<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The developed numerical model assesses the risk of a COVID-19 infection in a room based on the measurements of temperature, relative humidity, CO<sub>2</sub> and particle concentration, as well as the number of people and occurrences of speech, coughing, and sneezing obtained through a low-cost sensor system. As the model operates faster than real-time, it can dynamically inform the persons in the room or building management system about the predicted risk level. When the infection risk is high, the model can activate an air purifier equipped with filtration and UV-C disinfection. This solution improves energy efficiency by reducing the ventilation intensity required during colder seasons to maintain the same safety level and activating the purifier only when the predicted infection risk surpasses a specified threshold.</p>
</abstract>

The developed numerical model assesses the risk of a COVID-19 infection in a room based on the measurements of temperature, relative humidity, CO2 and particle concentration, as well as the number of people and occurrences of speech, coughing, and sneezing obtained through a low-cost sensor system. As the model operates faster than real-time, it can dynamically inform the persons in the room or building management system about the predicted risk level. When the infection risk is high, the model can activate an air purifier equipped with filtration and UV-C disinfection. This solution improves energy efficiency by reducing the ventilation intensity required during colder seasons to maintain the same safety level and activating the purifier only when the predicted infection risk surpasses a specified threshold.

Numerical Model and System for Prediction and Reduction of Indoor Infection Risk

Latvian Journal of Physics and Technical Sciences

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Numerical Model and System for Prediction and Reduction of Indoor Infection Risk"}

The developed numerical model assesses the risk of a COVID-19 infection in a room based on the measurements of temperature, relative humidity, CO2 and particle...

Numerical Model and System for Prediction and Reduction of Indoor Infection Risk

Online veröffentlicht: 09. Dez. 2023

Seitenbereich: 5 - 19

DOI: https://doi.org/10.2478/lpts-2023-0041

Schlüsselwörter
Air purification efficacy, indoor infection risk, virion concentration modelling

© 2023 J. Virbulis et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Numerical Model and System for Prediction and Reduction of Indoor Infection Risk

Online veröffentlicht: 09. Dez. 2023

Seitenbereich: 5 - 19

DOI: https://doi.org/10.2478/lpts-2023-0041

SchlüsselwörterAir purification efficacy, indoor infection risk, virion concentration modelling

© 2023 J. Virbulis et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
Air purification efficacy, indoor infection risk, virion concentration modelling