A five-compartment model of age-specific transmissibility of SARS-CoV-2
Abstract Background The novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, also called 2019-nCoV) causes different morbidity risks to individuals in different age groups. This study attempts to quantify the age-specific transmissibility using a mathematical model. Method...
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| Format: | Article |
| Language: | English |
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BMC
2020-08-01
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| Series: | Infectious Diseases of Poverty |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s40249-020-00735-x |
| _version_ | 1828880399377367040 |
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| author | Ze-Yu Zhao Yuan-Zhao Zhu Jing-Wen Xu Shi-Xiong Hu Qing-Qing Hu Zhao Lei Jia Rui Xing-Chun Liu Yao Wang Meng Yang Li Luo Shan-Shan Yu Jia Li Ruo-Yun Liu Fang Xie Ying-Ying Su Yi-Chen Chiang Ben-Hua Zhao Jing-An Cui Ling Yin Yan-Hua Su Qing-Long Zhao Li-Dong Gao Tian-Mu Chen |
| author_facet | Ze-Yu Zhao Yuan-Zhao Zhu Jing-Wen Xu Shi-Xiong Hu Qing-Qing Hu Zhao Lei Jia Rui Xing-Chun Liu Yao Wang Meng Yang Li Luo Shan-Shan Yu Jia Li Ruo-Yun Liu Fang Xie Ying-Ying Su Yi-Chen Chiang Ben-Hua Zhao Jing-An Cui Ling Yin Yan-Hua Su Qing-Long Zhao Li-Dong Gao Tian-Mu Chen |
| author_sort | Ze-Yu Zhao |
| collection | DOAJ |
| description | Abstract Background The novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, also called 2019-nCoV) causes different morbidity risks to individuals in different age groups. This study attempts to quantify the age-specific transmissibility using a mathematical model. Methods An epidemiological model with five compartments (susceptible–exposed–symptomatic–asymptomatic–recovered/removed [SEIAR]) was developed based on observed transmission features. Coronavirus disease 2019 (COVID-19) cases were divided into four age groups: group 1, those ≤ 14 years old; group 2, those 15 to 44 years old; group 3, those 45 to 64 years old; and group 4, those ≥ 65 years old. The model was initially based on cases (including imported cases and secondary cases) collected in Hunan Province from January 5 to February 19, 2020. Another dataset, from Jilin Province, was used to test the model. Results The age-specific SEIAR model fitted the data well in each age group (P < 0.001). In Hunan Province, the highest transmissibility was from age group 4 to 3 (median: β 43 = 7.71 × 10− 9; SAR 43 = 3.86 × 10− 8), followed by group 3 to 4 (median: β 34 = 3.07 × 10− 9; SAR 34 = 1.53 × 10− 8), group 2 to 2 (median: β 22 = 1.24 × 10− 9; SAR 22 = 6.21 × 10− 9), and group 3 to 1 (median: β 31 = 4.10 × 10− 10; SAR 31 = 2.08 × 10− 9). The lowest transmissibility was from age group 3 to 3 (median: β 33 = 1.64 × 10− 19; SAR 33 = 8.19 × 10− 19), followed by group 4 to 4 (median: β 44 = 3.66 × 10− 17; SAR 44 = 1.83 × 10− 16), group 3 to 2 (median: β 32 = 1.21 × 10− 16; SAR 32 = 6.06 × 10− 16), and group 1 to 4 (median: β 14 = 7.20 × 10− 14; SAR 14 = 3.60 × 10− 13). In Jilin Province, the highest transmissibility occurred from age group 4 to 4 (median: β 43 = 4.27 × 10− 8; SAR 43 = 2.13 × 10− 7), followed by group 3 to 4 (median: β 34 = 1.81 × 10− 8; SAR 34 = 9.03 × 10− 8). Conclusions SARS-CoV-2 exhibits high transmissibility between middle-aged (45 to 64 years old) and elderly (≥ 65 years old) people. Children (≤ 14 years old) have very low susceptibility to COVID-19. This study will improve our understanding of the transmission feature of SARS-CoV-2 in different age groups and suggest the most prevention measures should be applied to middle-aged and elderly people. |
| first_indexed | 2024-12-13T09:48:05Z |
| format | Article |
| id | doaj.art-01116dfc530643a6ba6750629679e66d |
| institution | Directory Open Access Journal |
| issn | 2049-9957 |
| language | English |
| last_indexed | 2024-12-13T09:48:05Z |
| publishDate | 2020-08-01 |
| publisher | BMC |
| record_format | Article |
| series | Infectious Diseases of Poverty |
| spelling | doaj.art-01116dfc530643a6ba6750629679e66d2022-12-21T23:52:00ZengBMCInfectious Diseases of Poverty2049-99572020-08-019111510.1186/s40249-020-00735-xA five-compartment model of age-specific transmissibility of SARS-CoV-2Ze-Yu Zhao0Yuan-Zhao Zhu1Jing-Wen Xu2Shi-Xiong Hu3Qing-Qing Hu4Zhao Lei5Jia Rui6Xing-Chun Liu7Yao Wang8Meng Yang9Li Luo10Shan-Shan Yu11Jia Li12Ruo-Yun Liu13Fang Xie14Ying-Ying Su15Yi-Chen Chiang16Ben-Hua Zhao17Jing-An Cui18Ling Yin19Yan-Hua Su20Qing-Long Zhao21Li-Dong Gao22Tian-Mu Chen23State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen UniversityState Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen UniversityState Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen UniversityHunan Provincial Center for Disease Control and PreventionDivision of Public Health, School of Medicine, University of UtahState Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen UniversityState Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen UniversityState Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen UniversityState Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen UniversityState Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen UniversityState Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen UniversityState Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen UniversityState Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen UniversityState Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen UniversityState Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen UniversityState Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen UniversityState Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen UniversityState Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen UniversityDepartment of Mathematics, School of Science, Beijing University of Civil Engineering and ArchitectureShenzhen Institutes of Advanced Technology, Chinese Academy of SciencesState Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen UniversityJilin Provincial Center for Disease Control and PreventionHunan Provincial Center for Disease Control and PreventionState Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen UniversityAbstract Background The novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, also called 2019-nCoV) causes different morbidity risks to individuals in different age groups. This study attempts to quantify the age-specific transmissibility using a mathematical model. Methods An epidemiological model with five compartments (susceptible–exposed–symptomatic–asymptomatic–recovered/removed [SEIAR]) was developed based on observed transmission features. Coronavirus disease 2019 (COVID-19) cases were divided into four age groups: group 1, those ≤ 14 years old; group 2, those 15 to 44 years old; group 3, those 45 to 64 years old; and group 4, those ≥ 65 years old. The model was initially based on cases (including imported cases and secondary cases) collected in Hunan Province from January 5 to February 19, 2020. Another dataset, from Jilin Province, was used to test the model. Results The age-specific SEIAR model fitted the data well in each age group (P < 0.001). In Hunan Province, the highest transmissibility was from age group 4 to 3 (median: β 43 = 7.71 × 10− 9; SAR 43 = 3.86 × 10− 8), followed by group 3 to 4 (median: β 34 = 3.07 × 10− 9; SAR 34 = 1.53 × 10− 8), group 2 to 2 (median: β 22 = 1.24 × 10− 9; SAR 22 = 6.21 × 10− 9), and group 3 to 1 (median: β 31 = 4.10 × 10− 10; SAR 31 = 2.08 × 10− 9). The lowest transmissibility was from age group 3 to 3 (median: β 33 = 1.64 × 10− 19; SAR 33 = 8.19 × 10− 19), followed by group 4 to 4 (median: β 44 = 3.66 × 10− 17; SAR 44 = 1.83 × 10− 16), group 3 to 2 (median: β 32 = 1.21 × 10− 16; SAR 32 = 6.06 × 10− 16), and group 1 to 4 (median: β 14 = 7.20 × 10− 14; SAR 14 = 3.60 × 10− 13). In Jilin Province, the highest transmissibility occurred from age group 4 to 4 (median: β 43 = 4.27 × 10− 8; SAR 43 = 2.13 × 10− 7), followed by group 3 to 4 (median: β 34 = 1.81 × 10− 8; SAR 34 = 9.03 × 10− 8). Conclusions SARS-CoV-2 exhibits high transmissibility between middle-aged (45 to 64 years old) and elderly (≥ 65 years old) people. Children (≤ 14 years old) have very low susceptibility to COVID-19. This study will improve our understanding of the transmission feature of SARS-CoV-2 in different age groups and suggest the most prevention measures should be applied to middle-aged and elderly people.http://link.springer.com/article/10.1186/s40249-020-00735-xTransmissibilitySARS-CoV-2COVID-19Compartmental modelAge-specific dynamics |
| spellingShingle | Ze-Yu Zhao Yuan-Zhao Zhu Jing-Wen Xu Shi-Xiong Hu Qing-Qing Hu Zhao Lei Jia Rui Xing-Chun Liu Yao Wang Meng Yang Li Luo Shan-Shan Yu Jia Li Ruo-Yun Liu Fang Xie Ying-Ying Su Yi-Chen Chiang Ben-Hua Zhao Jing-An Cui Ling Yin Yan-Hua Su Qing-Long Zhao Li-Dong Gao Tian-Mu Chen A five-compartment model of age-specific transmissibility of SARS-CoV-2 Infectious Diseases of Poverty Transmissibility SARS-CoV-2 COVID-19 Compartmental model Age-specific dynamics |
| title | A five-compartment model of age-specific transmissibility of SARS-CoV-2 |
| title_full | A five-compartment model of age-specific transmissibility of SARS-CoV-2 |
| title_fullStr | A five-compartment model of age-specific transmissibility of SARS-CoV-2 |
| title_full_unstemmed | A five-compartment model of age-specific transmissibility of SARS-CoV-2 |
| title_short | A five-compartment model of age-specific transmissibility of SARS-CoV-2 |
| title_sort | five compartment model of age specific transmissibility of sars cov 2 |
| topic | Transmissibility SARS-CoV-2 COVID-19 Compartmental model Age-specific dynamics |
| url | http://link.springer.com/article/10.1186/s40249-020-00735-x |
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