Bayesian Framework for Multi-Wave COVID-19 Epidemic Analysis Using Empirical Vaccination Data
The COVID-19 pandemic has highlighted the necessity of advanced modeling inference using the limited data of daily cases. Tracking a long-term epidemic trajectory requires explanatory modeling with more complexities than the one with short-time forecasts, especially for the highly vaccinated scenari...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-12-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/10/1/21 |
| _version_ | 1827668195724492800 |
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| author | Jiawei Xu Yincai Tang |
| author_facet | Jiawei Xu Yincai Tang |
| author_sort | Jiawei Xu |
| collection | DOAJ |
| description | The COVID-19 pandemic has highlighted the necessity of advanced modeling inference using the limited data of daily cases. Tracking a long-term epidemic trajectory requires explanatory modeling with more complexities than the one with short-time forecasts, especially for the highly vaccinated scenario in the latest phase. With this work, we propose a novel modeling framework that combines an epidemiological model with Bayesian inference to perform an explanatory analysis on the spreading of COVID-19 in Israel. The Bayesian inference is implemented on a modified SEIR compartmental model supplemented by real-time vaccination data and piecewise transmission and infectious rates determined by change points. We illustrate the fitted multi-wave trajectory in Israel with the checkpoints of major changes in publicly announced interventions or critical social events. The result of our modeling framework partly reflects the impact of different stages of mitigation strategies as well as the vaccination effectiveness, and provides forecasts of near future scenarios. |
| first_indexed | 2024-03-10T03:32:42Z |
| format | Article |
| id | doaj.art-49cb8f0152bf49658475702d6883f805 |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-10T03:32:42Z |
| publishDate | 2021-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-49cb8f0152bf49658475702d6883f8052023-11-23T11:52:56ZengMDPI AGMathematics2227-73902021-12-011012110.3390/math10010021Bayesian Framework for Multi-Wave COVID-19 Epidemic Analysis Using Empirical Vaccination DataJiawei Xu0Yincai Tang1Department of Statistics, East China Normal University, Shanghai 200062, ChinaDepartment of Statistics, East China Normal University, Shanghai 200062, ChinaThe COVID-19 pandemic has highlighted the necessity of advanced modeling inference using the limited data of daily cases. Tracking a long-term epidemic trajectory requires explanatory modeling with more complexities than the one with short-time forecasts, especially for the highly vaccinated scenario in the latest phase. With this work, we propose a novel modeling framework that combines an epidemiological model with Bayesian inference to perform an explanatory analysis on the spreading of COVID-19 in Israel. The Bayesian inference is implemented on a modified SEIR compartmental model supplemented by real-time vaccination data and piecewise transmission and infectious rates determined by change points. We illustrate the fitted multi-wave trajectory in Israel with the checkpoints of major changes in publicly announced interventions or critical social events. The result of our modeling framework partly reflects the impact of different stages of mitigation strategies as well as the vaccination effectiveness, and provides forecasts of near future scenarios.https://www.mdpi.com/2227-7390/10/1/21COVID-19Bayesian inferencechange pointmulti-wave trajectoryvaccinationNUTS |
| spellingShingle | Jiawei Xu Yincai Tang Bayesian Framework for Multi-Wave COVID-19 Epidemic Analysis Using Empirical Vaccination Data Mathematics COVID-19 Bayesian inference change point multi-wave trajectory vaccination NUTS |
| title | Bayesian Framework for Multi-Wave COVID-19 Epidemic Analysis Using Empirical Vaccination Data |
| title_full | Bayesian Framework for Multi-Wave COVID-19 Epidemic Analysis Using Empirical Vaccination Data |
| title_fullStr | Bayesian Framework for Multi-Wave COVID-19 Epidemic Analysis Using Empirical Vaccination Data |
| title_full_unstemmed | Bayesian Framework for Multi-Wave COVID-19 Epidemic Analysis Using Empirical Vaccination Data |
| title_short | Bayesian Framework for Multi-Wave COVID-19 Epidemic Analysis Using Empirical Vaccination Data |
| title_sort | bayesian framework for multi wave covid 19 epidemic analysis using empirical vaccination data |
| topic | COVID-19 Bayesian inference change point multi-wave trajectory vaccination NUTS |
| url | https://www.mdpi.com/2227-7390/10/1/21 |
| work_keys_str_mv | AT jiaweixu bayesianframeworkformultiwavecovid19epidemicanalysisusingempiricalvaccinationdata AT yincaitang bayesianframeworkformultiwavecovid19epidemicanalysisusingempiricalvaccinationdata |