Extended SIR Prediction of the Epidemics Trend of COVID-19 in Italy and Compared With Hunan, China
Background: Coronavirus Disease 2019 (COVID-19) is currently a global public health threat. Outside of China, Italy is one of the countries suffering the most with the COVID-19 epidemic. It is important to predict the epidemic trend of the COVID-19 epidemic in Italy to help develop public health str...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2020-05-01
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| Series: | Frontiers in Medicine |
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| Online Access: | https://www.frontiersin.org/article/10.3389/fmed.2020.00169/full |
| _version_ | 1830299568247406592 |
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| author | Jia Wangping Jia Wangping Han Ke Song Yang Cao Wenzhe Wang Shengshu Yang Shanshan Wang Jianwei Kou Fuyin Tai Penggang Li Jing Liu Miao He Yao |
| author_facet | Jia Wangping Jia Wangping Han Ke Song Yang Cao Wenzhe Wang Shengshu Yang Shanshan Wang Jianwei Kou Fuyin Tai Penggang Li Jing Liu Miao He Yao |
| author_sort | Jia Wangping |
| collection | DOAJ |
| description | Background: Coronavirus Disease 2019 (COVID-19) is currently a global public health threat. Outside of China, Italy is one of the countries suffering the most with the COVID-19 epidemic. It is important to predict the epidemic trend of the COVID-19 epidemic in Italy to help develop public health strategies.Methods: We used time-series data of COVID-19 from Jan 22 2020 to Apr 02 2020. An infectious disease dynamic extended susceptible-infected-removed (eSIR) model, which covers the effects of different intervention measures in dissimilar periods, was applied to estimate the epidemic trend in Italy. The basic reproductive number was estimated using Markov Chain Monte Carlo methods and presented using the resulting posterior mean and 95% credible interval (CI). Hunan, with a similar total population number to Italy, was used as a comparative item.Results: In the eSIR model, we estimated that the mean of basic reproductive number for COVID-19 was 4.34 (95% CI, 3.04–6.00) in Italy and 3.16 (95% CI, 1.73–5.25) in Hunan. There would be a total of 182 051 infected cases (95%CI:116 114–274 378) under the current country blockade and the endpoint would be Aug 05 in Italy.Conclusion: Italy's current strict measures can efficaciously prevent the further spread of COVID-19 and should be maintained. Necessary strict public health measures should be implemented as soon as possible in other European countries with a high number of COVID-19 cases. The most effective strategy needs to be confirmed in further studies. |
| first_indexed | 2024-12-19T08:11:38Z |
| format | Article |
| id | doaj.art-16c56bf9c7f448be9b0a1fb34b5e9481 |
| institution | Directory Open Access Journal |
| issn | 2296-858X |
| language | English |
| last_indexed | 2024-12-19T08:11:38Z |
| publishDate | 2020-05-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Medicine |
| spelling | doaj.art-16c56bf9c7f448be9b0a1fb34b5e94812022-12-21T20:29:37ZengFrontiers Media S.A.Frontiers in Medicine2296-858X2020-05-01710.3389/fmed.2020.00169544001Extended SIR Prediction of the Epidemics Trend of COVID-19 in Italy and Compared With Hunan, ChinaJia Wangping0Jia Wangping1Han Ke2Song Yang3Cao Wenzhe4Wang Shengshu5Yang Shanshan6Wang Jianwei7Kou Fuyin8Tai Penggang9Li Jing10Liu Miao11He Yao12Beijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatrics Diseases, Second Medical Center of Chinese PLA General Hospital, Institute of Geriatrics, Beijing, ChinaDepartment of Military Medical Technology Support, School of Non-commissioned Officer, Army Medical University, Shijiazhuang, ChinaBeijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatrics Diseases, Second Medical Center of Chinese PLA General Hospital, Institute of Geriatrics, Beijing, ChinaBeijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatrics Diseases, Second Medical Center of Chinese PLA General Hospital, Institute of Geriatrics, Beijing, ChinaBeijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatrics Diseases, Second Medical Center of Chinese PLA General Hospital, Institute of Geriatrics, Beijing, ChinaBeijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatrics Diseases, Second Medical Center of Chinese PLA General Hospital, Institute of Geriatrics, Beijing, ChinaBeijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatrics Diseases, Second Medical Center of Chinese PLA General Hospital, Institute of Geriatrics, Beijing, ChinaBeijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatrics Diseases, Second Medical Center of Chinese PLA General Hospital, Institute of Geriatrics, Beijing, ChinaBeijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatrics Diseases, Second Medical Center of Chinese PLA General Hospital, Institute of Geriatrics, Beijing, ChinaBeijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatrics Diseases, Second Medical Center of Chinese PLA General Hospital, Institute of Geriatrics, Beijing, ChinaBeijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatrics Diseases, Second Medical Center of Chinese PLA General Hospital, Institute of Geriatrics, Beijing, ChinaBeijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatrics Diseases, Second Medical Center of Chinese PLA General Hospital, Institute of Geriatrics, Beijing, ChinaBeijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatrics Diseases, Second Medical Center of Chinese PLA General Hospital, Institute of Geriatrics, Beijing, ChinaBackground: Coronavirus Disease 2019 (COVID-19) is currently a global public health threat. Outside of China, Italy is one of the countries suffering the most with the COVID-19 epidemic. It is important to predict the epidemic trend of the COVID-19 epidemic in Italy to help develop public health strategies.Methods: We used time-series data of COVID-19 from Jan 22 2020 to Apr 02 2020. An infectious disease dynamic extended susceptible-infected-removed (eSIR) model, which covers the effects of different intervention measures in dissimilar periods, was applied to estimate the epidemic trend in Italy. The basic reproductive number was estimated using Markov Chain Monte Carlo methods and presented using the resulting posterior mean and 95% credible interval (CI). Hunan, with a similar total population number to Italy, was used as a comparative item.Results: In the eSIR model, we estimated that the mean of basic reproductive number for COVID-19 was 4.34 (95% CI, 3.04–6.00) in Italy and 3.16 (95% CI, 1.73–5.25) in Hunan. There would be a total of 182 051 infected cases (95%CI:116 114–274 378) under the current country blockade and the endpoint would be Aug 05 in Italy.Conclusion: Italy's current strict measures can efficaciously prevent the further spread of COVID-19 and should be maintained. Necessary strict public health measures should be implemented as soon as possible in other European countries with a high number of COVID-19 cases. The most effective strategy needs to be confirmed in further studies.https://www.frontiersin.org/article/10.3389/fmed.2020.00169/fullCOVID-19coronavirusItalypredictionepidemics trend |
| spellingShingle | Jia Wangping Jia Wangping Han Ke Song Yang Cao Wenzhe Wang Shengshu Yang Shanshan Wang Jianwei Kou Fuyin Tai Penggang Li Jing Liu Miao He Yao Extended SIR Prediction of the Epidemics Trend of COVID-19 in Italy and Compared With Hunan, China Frontiers in Medicine COVID-19 coronavirus Italy prediction epidemics trend |
| title | Extended SIR Prediction of the Epidemics Trend of COVID-19 in Italy and Compared With Hunan, China |
| title_full | Extended SIR Prediction of the Epidemics Trend of COVID-19 in Italy and Compared With Hunan, China |
| title_fullStr | Extended SIR Prediction of the Epidemics Trend of COVID-19 in Italy and Compared With Hunan, China |
| title_full_unstemmed | Extended SIR Prediction of the Epidemics Trend of COVID-19 in Italy and Compared With Hunan, China |
| title_short | Extended SIR Prediction of the Epidemics Trend of COVID-19 in Italy and Compared With Hunan, China |
| title_sort | extended sir prediction of the epidemics trend of covid 19 in italy and compared with hunan china |
| topic | COVID-19 coronavirus Italy prediction epidemics trend |
| url | https://www.frontiersin.org/article/10.3389/fmed.2020.00169/full |
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