A COVID-19 model incorporating variants, vaccination, waning immunity, and population behavior
Abstract Vaccines for COVID-19 have allowed countries to combat the spread of the disease. However, new variants have resulted in significant spikes in cases and raised severe health and economic concerns. We present a COVID-19 model to predict coupled effects of vaccine multiple-dose roll-out strat...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2022-11-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-022-24967-z |
| _version_ | 1811187085708623872 |
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| author | Zachary LaJoie Thomas Usherwood Shailen Sampath Vikas Srivastava |
| author_facet | Zachary LaJoie Thomas Usherwood Shailen Sampath Vikas Srivastava |
| author_sort | Zachary LaJoie |
| collection | DOAJ |
| description | Abstract Vaccines for COVID-19 have allowed countries to combat the spread of the disease. However, new variants have resulted in significant spikes in cases and raised severe health and economic concerns. We present a COVID-19 model to predict coupled effects of vaccine multiple-dose roll-out strategies, vaccine efficacy, waning immunity, population level of caution, sense of safety, under-reporting of cases, and highly prevalent variants such as the Delta (B.1.617.2) and Omicron (B.1.1.529). The modeling framework can incorporate new variants as they emerge to give critical insights into the new cases and guide public policy decision-making concerning vaccine roll-outs and reopening strategies. The model is shown to recreate the history of COVID-19 for five countries (Germany, India, Japan, South Africa, and the United States). Parameters for crucial aspects of the pandemic, such as population behavior, new variants, vaccination, and waning immunity, can be adjusted to predict pandemic scenarios. The model was used to conduct trend analysis to simulate pandemic dynamics taking into account the societal level of caution, societal sense of safety, and the proportions of individuals vaccinated with first, second, and booster doses. We used the results of serological testing studies to estimate the actual number of cases across countries. The model allows quantification of otherwise hard to quantify aspects such as the infectious power of variants and the effectiveness of government mandates and population behavior. Some example cases are presented by investigating the competitive nature of COVID variants and the effect of different vaccine distribution strategies between immunity groups. |
| first_indexed | 2024-04-11T13:56:04Z |
| format | Article |
| id | doaj.art-8f2c5e4ad5ab4e96a74d704cf7a0c5f9 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-11T13:56:04Z |
| publishDate | 2022-11-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-8f2c5e4ad5ab4e96a74d704cf7a0c5f92022-12-22T04:20:20ZengNature PortfolioScientific Reports2045-23222022-11-0112111110.1038/s41598-022-24967-zA COVID-19 model incorporating variants, vaccination, waning immunity, and population behaviorZachary LaJoie0Thomas Usherwood1Shailen Sampath2Vikas Srivastava3School of Engineering, Brown UniversitySchool of Engineering, Brown UniversitySchool of Engineering, Brown UniversitySchool of Engineering, Brown UniversityAbstract Vaccines for COVID-19 have allowed countries to combat the spread of the disease. However, new variants have resulted in significant spikes in cases and raised severe health and economic concerns. We present a COVID-19 model to predict coupled effects of vaccine multiple-dose roll-out strategies, vaccine efficacy, waning immunity, population level of caution, sense of safety, under-reporting of cases, and highly prevalent variants such as the Delta (B.1.617.2) and Omicron (B.1.1.529). The modeling framework can incorporate new variants as they emerge to give critical insights into the new cases and guide public policy decision-making concerning vaccine roll-outs and reopening strategies. The model is shown to recreate the history of COVID-19 for five countries (Germany, India, Japan, South Africa, and the United States). Parameters for crucial aspects of the pandemic, such as population behavior, new variants, vaccination, and waning immunity, can be adjusted to predict pandemic scenarios. The model was used to conduct trend analysis to simulate pandemic dynamics taking into account the societal level of caution, societal sense of safety, and the proportions of individuals vaccinated with first, second, and booster doses. We used the results of serological testing studies to estimate the actual number of cases across countries. The model allows quantification of otherwise hard to quantify aspects such as the infectious power of variants and the effectiveness of government mandates and population behavior. Some example cases are presented by investigating the competitive nature of COVID variants and the effect of different vaccine distribution strategies between immunity groups.https://doi.org/10.1038/s41598-022-24967-z |
| spellingShingle | Zachary LaJoie Thomas Usherwood Shailen Sampath Vikas Srivastava A COVID-19 model incorporating variants, vaccination, waning immunity, and population behavior Scientific Reports |
| title | A COVID-19 model incorporating variants, vaccination, waning immunity, and population behavior |
| title_full | A COVID-19 model incorporating variants, vaccination, waning immunity, and population behavior |
| title_fullStr | A COVID-19 model incorporating variants, vaccination, waning immunity, and population behavior |
| title_full_unstemmed | A COVID-19 model incorporating variants, vaccination, waning immunity, and population behavior |
| title_short | A COVID-19 model incorporating variants, vaccination, waning immunity, and population behavior |
| title_sort | covid 19 model incorporating variants vaccination waning immunity and population behavior |
| url | https://doi.org/10.1038/s41598-022-24967-z |
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