High Resolution Spatio-Temporal Model for Room-Level Airborne Pandemic Spread
Airborne pandemics have caused millions of deaths worldwide, large-scale economic losses, and catastrophic sociological shifts in human history. Researchers have developed multiple mathematical models and computational frameworks to investigate and predict pandemic spread on various levels and scale...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-01-01
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| Series: | Mathematics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-7390/11/2/426 |
| _version_ | 1797438990583857152 |
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| author | Teddy Lazebnik Ariel Alexi |
| author_facet | Teddy Lazebnik Ariel Alexi |
| author_sort | Teddy Lazebnik |
| collection | DOAJ |
| description | Airborne pandemics have caused millions of deaths worldwide, large-scale economic losses, and catastrophic sociological shifts in human history. Researchers have developed multiple mathematical models and computational frameworks to investigate and predict pandemic spread on various levels and scales such as countries, cities, large social events, and even buildings. However, attempts of modeling airborne pandemic dynamics on the smallest scale, a single room, have been mostly neglected. As time indoors increases due to global urbanization processes, more infections occur in shared rooms. In this study, a high-resolution spatio-temporal epidemiological model with airflow dynamics to evaluate airborne pandemic spread is proposed. The model is implemented, using Python, with high-resolution 3D data obtained from a light detection and ranging (LiDAR) device and computing model based on the Computational Fluid Dynamics (CFD) model for the airflow and the Susceptible–Exposed–Infected (SEI) model for the epidemiological dynamics. The pandemic spread is evaluated in four types of rooms, showing significant differences even for a short exposure duration. We show that the room’s topology and individual distribution in the room define the ability of air ventilation to reduce pandemic spread throughout breathing zone infection. |
| first_indexed | 2024-03-09T11:46:23Z |
| format | Article |
| id | doaj.art-42bd9a0cc4fa43e5b18d4879cf1d3fd0 |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-09T11:46:23Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-42bd9a0cc4fa43e5b18d4879cf1d3fd02023-11-30T23:22:03ZengMDPI AGMathematics2227-73902023-01-0111242610.3390/math11020426High Resolution Spatio-Temporal Model for Room-Level Airborne Pandemic SpreadTeddy Lazebnik0Ariel Alexi1Department of Cancer Biology, Cancer Institute, University College London, London WC1E 6BT, UKDepartment of Information Science, Bar-Ilan University, Ramat-Gan 5290002, IsraelAirborne pandemics have caused millions of deaths worldwide, large-scale economic losses, and catastrophic sociological shifts in human history. Researchers have developed multiple mathematical models and computational frameworks to investigate and predict pandemic spread on various levels and scales such as countries, cities, large social events, and even buildings. However, attempts of modeling airborne pandemic dynamics on the smallest scale, a single room, have been mostly neglected. As time indoors increases due to global urbanization processes, more infections occur in shared rooms. In this study, a high-resolution spatio-temporal epidemiological model with airflow dynamics to evaluate airborne pandemic spread is proposed. The model is implemented, using Python, with high-resolution 3D data obtained from a light detection and ranging (LiDAR) device and computing model based on the Computational Fluid Dynamics (CFD) model for the airflow and the Susceptible–Exposed–Infected (SEI) model for the epidemiological dynamics. The pandemic spread is evaluated in four types of rooms, showing significant differences even for a short exposure duration. We show that the room’s topology and individual distribution in the room define the ability of air ventilation to reduce pandemic spread throughout breathing zone infection.https://www.mdpi.com/2227-7390/11/2/426agent-based simulationindoor pandemicairborne pathogensSEI modelCFD |
| spellingShingle | Teddy Lazebnik Ariel Alexi High Resolution Spatio-Temporal Model for Room-Level Airborne Pandemic Spread Mathematics agent-based simulation indoor pandemic airborne pathogens SEI model CFD |
| title | High Resolution Spatio-Temporal Model for Room-Level Airborne Pandemic Spread |
| title_full | High Resolution Spatio-Temporal Model for Room-Level Airborne Pandemic Spread |
| title_fullStr | High Resolution Spatio-Temporal Model for Room-Level Airborne Pandemic Spread |
| title_full_unstemmed | High Resolution Spatio-Temporal Model for Room-Level Airborne Pandemic Spread |
| title_short | High Resolution Spatio-Temporal Model for Room-Level Airborne Pandemic Spread |
| title_sort | high resolution spatio temporal model for room level airborne pandemic spread |
| topic | agent-based simulation indoor pandemic airborne pathogens SEI model CFD |
| url | https://www.mdpi.com/2227-7390/11/2/426 |
| work_keys_str_mv | AT teddylazebnik highresolutionspatiotemporalmodelforroomlevelairbornepandemicspread AT arielalexi highresolutionspatiotemporalmodelforroomlevelairbornepandemicspread |