Modeling COVID-19 epidemics in an Excel spreadsheet to enable first-hand accurate predictions of the pandemic evolution in urban areas
Abstract COVID-19, the first pandemic of this decade and the second in less than 15 years, has harshly taught us that viral diseases do not recognize boundaries; however, they truly do discriminate between aggressive and mediocre containment responses. We present a simple epidemiological model that...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2021-02-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-021-83697-w |
| _version_ | 1818999386389086208 |
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| author | Mario Moisés Alvarez Everardo González-González Grissel Trujillo-de Santiago |
| author_facet | Mario Moisés Alvarez Everardo González-González Grissel Trujillo-de Santiago |
| author_sort | Mario Moisés Alvarez |
| collection | DOAJ |
| description | Abstract COVID-19, the first pandemic of this decade and the second in less than 15 years, has harshly taught us that viral diseases do not recognize boundaries; however, they truly do discriminate between aggressive and mediocre containment responses. We present a simple epidemiological model that is amenable to implementation in Excel spreadsheets and sufficiently accurate to reproduce observed data on the evolution of the COVID-19 pandemics in different regions [i.e., New York City (NYC), South Korea, Mexico City]. We show that the model can be adapted to closely follow the evolution of COVID-19 in any large city by simply adjusting parameters related to demographic conditions and aggressiveness of the response from a society/government to epidemics. Moreover, we show that this simple epidemiological simulator can be used to assess the efficacy of the response of a government/society to an outbreak. The simplicity and accuracy of this model will greatly contribute to democratizing the availability of knowledge in societies regarding the extent of an epidemic event and the efficacy of a governmental response. |
| first_indexed | 2024-12-20T22:16:36Z |
| format | Article |
| id | doaj.art-58d62bb463d64f87b25cb89aeedd46c6 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-12-20T22:16:36Z |
| publishDate | 2021-02-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-58d62bb463d64f87b25cb89aeedd46c62022-12-21T19:25:02ZengNature PortfolioScientific Reports2045-23222021-02-0111111210.1038/s41598-021-83697-wModeling COVID-19 epidemics in an Excel spreadsheet to enable first-hand accurate predictions of the pandemic evolution in urban areasMario Moisés Alvarez0Everardo González-González1Grissel Trujillo-de Santiago2Centro de Biotecnología-FEMSA, Tecnologico de MonterreyCentro de Biotecnología-FEMSA, Tecnologico de MonterreyCentro de Biotecnología-FEMSA, Tecnologico de MonterreyAbstract COVID-19, the first pandemic of this decade and the second in less than 15 years, has harshly taught us that viral diseases do not recognize boundaries; however, they truly do discriminate between aggressive and mediocre containment responses. We present a simple epidemiological model that is amenable to implementation in Excel spreadsheets and sufficiently accurate to reproduce observed data on the evolution of the COVID-19 pandemics in different regions [i.e., New York City (NYC), South Korea, Mexico City]. We show that the model can be adapted to closely follow the evolution of COVID-19 in any large city by simply adjusting parameters related to demographic conditions and aggressiveness of the response from a society/government to epidemics. Moreover, we show that this simple epidemiological simulator can be used to assess the efficacy of the response of a government/society to an outbreak. The simplicity and accuracy of this model will greatly contribute to democratizing the availability of knowledge in societies regarding the extent of an epidemic event and the efficacy of a governmental response.https://doi.org/10.1038/s41598-021-83697-w |
| spellingShingle | Mario Moisés Alvarez Everardo González-González Grissel Trujillo-de Santiago Modeling COVID-19 epidemics in an Excel spreadsheet to enable first-hand accurate predictions of the pandemic evolution in urban areas Scientific Reports |
| title | Modeling COVID-19 epidemics in an Excel spreadsheet to enable first-hand accurate predictions of the pandemic evolution in urban areas |
| title_full | Modeling COVID-19 epidemics in an Excel spreadsheet to enable first-hand accurate predictions of the pandemic evolution in urban areas |
| title_fullStr | Modeling COVID-19 epidemics in an Excel spreadsheet to enable first-hand accurate predictions of the pandemic evolution in urban areas |
| title_full_unstemmed | Modeling COVID-19 epidemics in an Excel spreadsheet to enable first-hand accurate predictions of the pandemic evolution in urban areas |
| title_short | Modeling COVID-19 epidemics in an Excel spreadsheet to enable first-hand accurate predictions of the pandemic evolution in urban areas |
| title_sort | modeling covid 19 epidemics in an excel spreadsheet to enable first hand accurate predictions of the pandemic evolution in urban areas |
| url | https://doi.org/10.1038/s41598-021-83697-w |
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