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Development of a Model for the Spread of Nosocomial Infection Outbreaks Using COVID-19 Data
| Title: | Development of a Model for the Spread of Nosocomial Infection Outbreaks Using COVID-19 Data |
| Authors: | Ueda, Ryuichiro Browse this author | | Goto, Ayato Browse this author | | Kita, Ryuki Browse this author | | Ogasawara, Katsuhiko Browse this author →KAKEN DB |
| Keywords: | COVID-19 | | nosocomial infection | | simulation |
| Issue Date: | 3-Mar-2022 |
| Publisher: | MDPI |
| Journal Title: | Healthcare |
| Volume: | 10 |
| Issue: | 3 |
| Start Page: | 471 |
| Publisher DOI: | 10.3390/healthcare10030471 |
| PMID: | 35326949 |
| Abstract: | We constructed and validated a mathematical model of infectious diseases to simulate the impact of COVID-19 nosocomial infection outbreaks outside hospitals. The model was constructed with two populations, one inside the hospital and one outside the hospital, and a population diffusion rate k (0 <= k <= 1) was set as a parameter to simulate the flow of people inside the hospital to outside the hospital. To validate the model, we divided the values of the population diffusion rate k into k = 0-0.25, 0.25-0.50, 0.50-0.75, and 0.75-1.0, and the initial value at the beginning of the simulation was set as day 1. The number of infected people was calculated for a 60-day period. The change in the number of people infected outside the hospital due to the out-break of nosocomial infection was calculated. As a result of the simulation, the number of people infected outside the hospital increased as the population diffusion rate k increased from 0.50 to 0.75, but the number of people infected from 0.75 to 1.0 was almost the same as that from 0 to 0.25, with the peak day being earlier. In future, it will be necessary to examine epidemiological information that has a large impact on the results. |
| Type: | article |
| URI: | http://hdl.handle.net/2115/85529 |
| Appears in Collections: | 保健科学院・保健科学研究院 (Graduate School of Health Sciences / Faculty of Health Sciences) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)
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