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Strategic Study of Chinese Academy of Engineering >> 2021, Volume 23, Issue 5 doi: 10.15302/J-SSCAE-2021.05.004

Precise Control and Integrated Management of Public Health Emergencies

Institute for Public Safety Research, Tsinghua University, Beijing 100084, China

Received:2021-07-28 Revised:2021-08-30 Available online:2021-10-20

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Abstract

As public health emergencies become increasingly complex and frequent worldwide, modernization of the public health emergency system is urgently required for improving the overall security level of a country; it is also crucial for the modernization of the national governance system. In this study, we summarize China’s response to public health emergencies from three aspects: epidemic surveillance and reporting system, sentinel surveillance and multipoint trigger mechanism, and mobile terminal application for individuals. Moreover, we explore the development paths for precise control and integrated management of public health emergencies and propose corresponding suggestions. Specifically, precision control can be realized by combining the following aspects: temporal and spatial modeling and calculation for the epidemic, epidemic data collection and information statistics, grassroots community prevention and control, and emergency resource supply. Integrated management should focus on: collection and perception of social governance information, data analysis and calculation platforms, rapid response and command at the grassroots level, epidemic monitoring/early warning/prediction, and continuous risk assessment. Furthermore, we suggest that China should strengthen information technology to enable epidemic prevention and control, improve its epidemic monitoring and reporting system, and build an integrated prevention and control system for public health governance.

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References

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[2]  Ruktanonchai N W, Floyd J R, Lai S, et al. Assessing the impact of coordinated COVID-19 exit strategies across Europe [J]. Science, 2020, 369(6510): 1465–1470. link1

[3]  Flaxman S, Mishra S, Gandy A, et al. Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe [J]. Nature, 2020, 584(7820): 257–261. link1

[4]  Davis E L, Lucas T C D, Borlase A, et al. Contact tracing is an imperfect tool for controlling COVID-19 transmission and relies on population adherence [J]. Nature Communications, 2021, 12(9): 1–8. link1

[5]  Moon S A, Scoglio C M. Contact tracing evaluation for COVID-19 transmission in the different movement levels of a rural college town in the USA [J]. Scientific Reports, 2021, 11(3): 1–12. link1

[6]  Huang Q S, Wood T, Jelley L, et al. Impact of the COVID-19 nonpharmaceutical interventions on influenza and other respiratory viral infections in New Zealand [J]. Nature Communications, 2021,12(2): 1–7. link1

[7]  Suryanarayanan P, Tsou C H, Poddar A, et al. AI-assisted tracking of worldwide non-pharmaceutical interventions for COVID- 19 [J]. Scientific Data, 2021, 8(3): 1–14. link1

[8]  The State Council Information Office of the People’s Republic of China. Evaluation report on the implementation of the national human rights action plan (2012―2015) [EB/OL]. (2016-06-14)[2021-07-20]. http://www.gov.cn/xinwen/2016- 06/14/content_5082026.htm. Chinese. link1

[9]  Zhao Z X, Zhao J, Ma J Q. Conception of an integrated information system for notifiable disease communicable surveillance in China [J]. Disease Surveillance, 2018, 33(5): 423– 427. Chinese. link1

[10]  Wang Y, Xiang N J, Ni D X, et al. Performance of surveillance system of pneumonia with unknown etiology in two hospitals at municipal (prefecture) level in Anhui Province [J]. Disease Surveillance, 2017, 32(5): 428–432. Chinese. link1

[11]  Wang X Y. Global conspiracy for influenza prevention and control [N]. Health News, 2018-05-24(01). Chinese.

[12]  Shanghai Municipal Health Commission, Shanghai Municipal Development & Reform Commission, Shanghai Municipal Commission of Economy and Informatization, et al. Three years action plan for strengthening the construction of public health system in Shanghai (2020―2022) [EB/OL]. (2020-06-01)[2021-07-20]. https://www.shanghai.gov.cn/nw12344/20200813/0001-12344_65151.html. Chinese. link1

[13]  China Internet Network Information Center. The 47th China statistical report on Internet development [EB/OL]. (2021-02- 03) [2021-07-20]. http://www.cnnic.net.cn/hlwfzyj/hlwxzbg/hlwtjbg/202102/t20210203_71361.htm. Chinese. link1

[14]  Kermack W O, Mckendrick A G. A contribution to the mathematical theory of epidemics [J]. Proceedings of the Royal Society of London Series A, Containing Papers of A Mathematical and Physical Character, 1927, 115(772): 700–721. link1

[15]  Han H, Ma A N, Zhao X, et al. SIRS model with the long distance spread and emulation [J]. Journal of Wuhan University of Technology, 2010, 32(2): 141–145. Chinese. link1

[16]  Du Y F, Xiao P, Cao H. Dynamic behavior of a periodic seir epidemic model with stage-structure [J]. Journal of Sichuan Normal University (Natural Science), 2017, 40(1): 73–77. Chinese. link1

[17]  Hethcote H W. The mathematics of infectious diseases [J]. SIAM Review, 2000, 42(4): 599–653. link1

[18]  Castillo-Chavez C, Castillo-Garsow C W, Yakubu A A. Mathematical models of isolation and quarantine [J]. The Journal of American Medical Association, 2003, 290(21): 2876–2877. link1

[19]  Lucia1 U, Deisboeck T S, Grisolia1 G. Entropy-based pandemics forecasting [J]. Frontiers in Physics, 2020, 8: 1–7. link1

[20]  Roques L, Klein E K, Papax J, et al. Impact of lockdown on the epidemic dynamics of COVID-19 in France [J]. Frontiers in Medicine, 2020, 7: 1–7. link1

[21]  Della M M, Orlando D, Sannino F. Renormalisation group approach to pandemics: The COVID-19 case [J]. Frontiers in Physics, 2020, 8: 1–7. link1

[22]  Fisman D N, Hauck T S, Tuite A R, et al. An IDEA for short term outbreak projection: nearcasting using the basic reproduction number [J]. PLOS ONE, 2013, 8(12): 1–7. link1

[23]  Tuite A R, Fisman D N. The IDEA model: A single equation approach to the Ebola forecasting challenge [J]. Epidemics, 2018, 22: 71–77. link1

[24]  Hsieh Y. Richards model: A simple procedure for real-time prediction of outbreak severity [M]// Ma Z, Zhou Y, Wu J. Modeling and dynamics of infectious diseases, Singapore: World Scientific, 2009: 216–236. link1

[25]  Wang B G, Qu B, Guo H Q, et al. Study on mathematical model of infectious disease prediction [J]. Chinese Journal of Health Statistics, 2007, 24(5): 536–540. Chinese. link1

[26]  Moirano G, Richiardi L, Novara C, et al. approaches to daily monitoring of the SARS-CoV-2 outbreak in Northern Italy [J]. Frontiers in Public Health, 2020, 8: 1–7. link1

[27]  Brooks L C, Farrow D C, Hyun S, et al. Flexible modeling of epidemics with an empirical Bayes framework [J]. PLOS Computational Biology, 2015, 11: 1–51. link1

[28]  Yang Z, Zeng Z, Wang K, et al. Modified SEIR and AI prediction of the epidemics trend of COVID-19 in China under public health interventions [J]. Journal of Thoracic Disease, 2020, 12(3): 165–174.

[29]  Hu Z X, Ge Q Y, Li S D, et al. Forecasting and evaluating multiple interventions for COVID-19 worldwide [J]. Frontiers in Physics, 2020, 3: 1–10. link1

[30]  Utsunomiya Y T, Utsunomiya A, Torrecilha R, et al. Growth rate and acceleration analysis of the COVID-19 pandemic reveals the effect of public health measures in real time [J]. Frontiers in Medicine, 2020, 7: 1–10. link1

[31]  Tsallis C, Tirnakli U. Predicting COVID-19 peaks around the world [J]. Frontiers in Physics, 2020, 8: 1–6. link1

[32]  Buckee C, Noor A, Sattenspiel L. Thinking clearly about social aspects of infectious disease transmission [J]. Nature, 2021. 595(7866): 205–213. link1

[33]  Wang F Y, Zeng D J, Mao W J. Social computing: Its significance, development and research status [J]. e-Science Technology & Application, 2010, 1(2): 3–14. Chinese. link1

[34]  Minar N, Burkhart R, Langton C G, et al. The swarm simulation system: A toolkit for building multi-agent simulations [EB/OL]. (1996-06-21)[2021-07-21]. https://santafe.edu/research/results/working-papers/the-swarm-simulation-system-atoolkit-for-building. link1

[35]  Collier N. RePast: An extensible framework for agent simulation [J]. Natural Resources and Environmental Issues (NREI), 2001 (8): 17–21. link1

[36]  Tisue S, Wilensky U. NetLogo: A simple environment for modeling complexity [C]. Boston: The Fifth International Conference on Complex Systems, 2004: 1–9. link1

[37]  Yuan H Y, Liang M C, Huang Q Y, et al. Application of empirical data assimilation method in trend analysis of COVID-19 [J]. Science & Technology Review, 2020, 38(6): 83–89. Chinese. link1

[1]  Lai S, Ruktanonchai N W, Zhou L, et al. Effect of nonpharmaceutical interventions to contain COVID-19 in China [J]. Nature, 2020, 585(7825): 410–413. link1

[2]  Ruktanonchai N W, Floyd J R, Lai S, et al. Assessing the impact of coordinated COVID-19 exit strategies across Europe [J]. Science, 2020, 369(6510): 1465–1470. link1

[3]  Flaxman S, Mishra S, Gandy A, et al. Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe [J]. Nature, 2020, 584(7820): 257–261. link1

[4]  Davis E L, Lucas T C D, Borlase A, et al. Contact tracing is an imperfect tool for controlling COVID-19 transmission and relies on population adherence [J]. Nature Communications, 2021, 12(9): 1–8. link1

[5]  Moon S A, Scoglio C M. Contact tracing evaluation for COVID-19 transmission in the different movement levels of a rural college town in the USA [J]. Scientific Reports, 2021, 11(3): 1–12. link1

[6]  Huang Q S, Wood T, Jelley L, et al. Impact of the COVID-19 nonpharmaceutical interventions on influenza and other respiratory viral infections in New Zealand [J]. Nature Communications, 2021,12(2): 1–7. link1

[7]  Suryanarayanan P, Tsou C H, Poddar A, et al. AI-assisted tracking of worldwide non-pharmaceutical interventions for COVID- 19 [J]. Scientific Data, 2021, 8(3): 1–14. link1

[8]  The State Council Information Office of the People’s Republic of China. Evaluation report on the implementation of the national human rights action plan (2012―2015) [EB/OL]. (2016-06-14)[2021-07-20]. http://www.gov.cn/xinwen/2016- 06/14/content_5082026.htm. Chinese. link1

[9]  Zhao Z X, Zhao J, Ma J Q. Conception of an integrated information system for notifiable disease communicable surveillance in China [J]. Disease Surveillance, 2018, 33(5): 423– 427. Chinese. link1

[10]  Wang Y, Xiang N J, Ni D X, et al. Performance of surveillance system of pneumonia with unknown etiology in two hospitals at municipal (prefecture) level in Anhui Province [J]. Disease Surveillance, 2017, 32(5): 428–432. Chinese. link1

[11]  Wang X Y. Global conspiracy for influenza prevention and control [N]. Health News, 2018-05-24(01). Chinese.

[12]  Shanghai Municipal Health Commission, Shanghai Municipal Development & Reform Commission, Shanghai Municipal Commission of Economy and Informatization, et al. Three years action plan for strengthening the construction of public health system in Shanghai (2020―2022) [EB/OL]. (2020-06-01)[2021-07-20]. https://www.shanghai.gov.cn/nw12344/20200813/0001-12344_65151.html. Chinese. link1

[13]  China Internet Network Information Center. The 47th China statistical report on Internet development [EB/OL]. (2021-02- 03) [2021-07-20]. http://www.cnnic.net.cn/hlwfzyj/hlwxzbg/hlwtjbg/202102/t20210203_71361.htm. Chinese. link1

[14]  Kermack W O, Mckendrick A G. A contribution to the mathematical theory of epidemics [J]. Proceedings of the Royal Society of London Series A, Containing Papers of A Mathematical and Physical Character, 1927, 115(772): 700–721. link1

[15]  Han H, Ma A N, Zhao X, et al. SIRS model with the long distance spread and emulation [J]. Journal of Wuhan University of Technology, 2010, 32(2): 141–145. Chinese. link1

[16]  Du Y F, Xiao P, Cao H. Dynamic behavior of a periodic seir epidemic model with stage-structure [J]. Journal of Sichuan Normal University (Natural Science), 2017, 40(1): 73–77. Chinese. link1

[17]  Hethcote H W. The mathematics of infectious diseases [J]. SIAM Review, 2000, 42(4): 599–653. link1

[18]  Castillo-Chavez C, Castillo-Garsow C W, Yakubu A A. Mathematical models of isolation and quarantine [J]. The Journal of American Medical Association, 2003, 290(21): 2876–2877. link1

[19]  Lucia1 U, Deisboeck T S, Grisolia1 G. Entropy-based pandemics forecasting [J]. Frontiers in Physics, 2020, 8: 1–7. link1

[20]  Roques L, Klein E K, Papax J, et al. Impact of lockdown on the epidemic dynamics of COVID-19 in France [J]. Frontiers in Medicine, 2020, 7: 1–7. link1

[21]  Della M M, Orlando D, Sannino F. Renormalisation group approach to pandemics: The COVID-19 case [J]. Frontiers in Physics, 2020, 8: 1–7. link1

[22]  Fisman D N, Hauck T S, Tuite A R, et al. An IDEA for short term outbreak projection: nearcasting using the basic reproduction number [J]. PLOS ONE, 2013, 8(12): 1–7. link1

[23]  Tuite A R, Fisman D N. The IDEA model: A single equation approach to the Ebola forecasting challenge [J]. Epidemics, 2018, 22: 71–77. link1

[24]  Hsieh Y. Richards model: A simple procedure for real-time prediction of outbreak severity [M]// Ma Z, Zhou Y, Wu J. Modeling and dynamics of infectious diseases, Singapore: World Scientific, 2009: 216–236. link1

[25]  Wang B G, Qu B, Guo H Q, et al. Study on mathematical model of infectious disease prediction [J]. Chinese Journal of Health Statistics, 2007, 24(5): 536–540. Chinese. link1

[26]  Moirano G, Richiardi L, Novara C, et al. approaches to daily monitoring of the SARS-CoV-2 outbreak in Northern Italy [J]. Frontiers in Public Health, 2020, 8: 1–7. link1

[27]  Brooks L C, Farrow D C, Hyun S, et al. Flexible modeling of epidemics with an empirical Bayes framework [J]. PLOS Computational Biology, 2015, 11: 1–51. link1

[28]  Yang Z, Zeng Z, Wang K, et al. Modified SEIR and AI prediction of the epidemics trend of COVID-19 in China under public health interventions [J]. Journal of Thoracic Disease, 2020, 12(3): 165–174.

[29]  Hu Z X, Ge Q Y, Li S D, et al. Forecasting and evaluating multiple interventions for COVID-19 worldwide [J]. Frontiers in Physics, 2020, 3: 1–10. link1

[30]  Utsunomiya Y T, Utsunomiya A, Torrecilha R, et al. Growth rate and acceleration analysis of the COVID-19 pandemic reveals the effect of public health measures in real time [J]. Frontiers in Medicine, 2020, 7: 1–10. link1

[31]  Tsallis C, Tirnakli U. Predicting COVID-19 peaks around the world [J]. Frontiers in Physics, 2020, 8: 1–6. link1

[32]  Buckee C, Noor A, Sattenspiel L. Thinking clearly about social aspects of infectious disease transmission [J]. Nature, 2021. 595(7866): 205–213. link1

[33]  Wang F Y, Zeng D J, Mao W J. Social computing: Its significance, development and research status [J]. e-Science Technology & Application, 2010, 1(2): 3–14. Chinese. link1

[34]  Minar N, Burkhart R, Langton C G, et al. The swarm simulation system: A toolkit for building multi-agent simulations [EB/OL]. (1996-06-21)[2021-07-21]. https://santafe.edu/research/results/working-papers/the-swarm-simulation-system-atoolkit-for-building. link1

[35]  Collier N. RePast: An extensible framework for agent simulation [J]. Natural Resources and Environmental Issues (NREI), 2001 (8): 17–21. link1

[36]  Tisue S, Wilensky U. NetLogo: A simple environment for modeling complexity [C]. Boston: The Fifth International Conference on Complex Systems, 2004: 1–9. link1

[37]  Yuan H Y, Liang M C, Huang Q Y, et al. Application of empirical data assimilation method in trend analysis of COVID-19 [J]. Science & Technology Review, 2020, 38(6): 83–89. Chinese. link1

[1]  Lai S, Ruktanonchai N W, Zhou L, et al. Effect of nonpharmaceutical interventions to contain COVID-19 in China [J]. Nature, 2020, 585(7825): 410–413. link1

[2]  Ruktanonchai N W, Floyd J R, Lai S, et al. Assessing the impact of coordinated COVID-19 exit strategies across Europe [J]. Science, 2020, 369(6510): 1465–1470. link1

[3]  Flaxman S, Mishra S, Gandy A, et al. Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe [J]. Nature, 2020, 584(7820): 257–261. link1

[4]  Davis E L, Lucas T C D, Borlase A, et al. Contact tracing is an imperfect tool for controlling COVID-19 transmission and relies on population adherence [J]. Nature Communications, 2021, 12(9): 1–8. link1

[5]  Moon S A, Scoglio C M. Contact tracing evaluation for COVID-19 transmission in the different movement levels of a rural college town in the USA [J]. Scientific Reports, 2021, 11(3): 1–12. link1

[6]  Huang Q S, Wood T, Jelley L, et al. Impact of the COVID-19 nonpharmaceutical interventions on influenza and other respiratory viral infections in New Zealand [J]. Nature Communications, 2021,12(2): 1–7. link1

[7]  Suryanarayanan P, Tsou C H, Poddar A, et al. AI-assisted tracking of worldwide non-pharmaceutical interventions for COVID- 19 [J]. Scientific Data, 2021, 8(3): 1–14. link1

[8]  The State Council Information Office of the People’s Republic of China. Evaluation report on the implementation of the national human rights action plan (2012―2015) [EB/OL]. (2016-06-14)[2021-07-20]. http://www.gov.cn/xinwen/2016- 06/14/content_5082026.htm. Chinese. link1

[9]  Zhao Z X, Zhao J, Ma J Q. Conception of an integrated information system for notifiable disease communicable surveillance in China [J]. Disease Surveillance, 2018, 33(5): 423– 427. Chinese. link1

[10]  Wang Y, Xiang N J, Ni D X, et al. Performance of surveillance system of pneumonia with unknown etiology in two hospitals at municipal (prefecture) level in Anhui Province [J]. Disease Surveillance, 2017, 32(5): 428–432. Chinese. link1

[11]  Wang X Y. Global conspiracy for influenza prevention and control [N]. Health News, 2018-05-24(01). Chinese.

[12]  Shanghai Municipal Health Commission, Shanghai Municipal Development & Reform Commission, Shanghai Municipal Commission of Economy and Informatization, et al. Three years action plan for strengthening the construction of public health system in Shanghai (2020―2022) [EB/OL]. (2020-06-01)[2021-07-20]. https://www.shanghai.gov.cn/nw12344/20200813/0001-12344_65151.html. Chinese. link1

[13]  China Internet Network Information Center. The 47th China statistical report on Internet development [EB/OL]. (2021-02- 03) [2021-07-20]. http://www.cnnic.net.cn/hlwfzyj/hlwxzbg/hlwtjbg/202102/t20210203_71361.htm. Chinese. link1

[14]  Kermack W O, Mckendrick A G. A contribution to the mathematical theory of epidemics [J]. Proceedings of the Royal Society of London Series A, Containing Papers of A Mathematical and Physical Character, 1927, 115(772): 700–721. link1

[15]  Han H, Ma A N, Zhao X, et al. SIRS model with the long distance spread and emulation [J]. Journal of Wuhan University of Technology, 2010, 32(2): 141–145. Chinese. link1

[16]  Du Y F, Xiao P, Cao H. Dynamic behavior of a periodic seir epidemic model with stage-structure [J]. Journal of Sichuan Normal University (Natural Science), 2017, 40(1): 73–77. Chinese. link1

[17]  Hethcote H W. The mathematics of infectious diseases [J]. SIAM Review, 2000, 42(4): 599–653. link1

[18]  Castillo-Chavez C, Castillo-Garsow C W, Yakubu A A. Mathematical models of isolation and quarantine [J]. The Journal of American Medical Association, 2003, 290(21): 2876–2877. link1

[19]  Lucia1 U, Deisboeck T S, Grisolia1 G. Entropy-based pandemics forecasting [J]. Frontiers in Physics, 2020, 8: 1–7. link1

[20]  Roques L, Klein E K, Papax J, et al. Impact of lockdown on the epidemic dynamics of COVID-19 in France [J]. Frontiers in Medicine, 2020, 7: 1–7. link1

[21]  Della M M, Orlando D, Sannino F. Renormalisation group approach to pandemics: The COVID-19 case [J]. Frontiers in Physics, 2020, 8: 1–7. link1

[22]  Fisman D N, Hauck T S, Tuite A R, et al. An IDEA for short term outbreak projection: nearcasting using the basic reproduction number [J]. PLOS ONE, 2013, 8(12): 1–7. link1

[23]  Tuite A R, Fisman D N. The IDEA model: A single equation approach to the Ebola forecasting challenge [J]. Epidemics, 2018, 22: 71–77. link1

[24]  Hsieh Y. Richards model: A simple procedure for real-time prediction of outbreak severity [M]// Ma Z, Zhou Y, Wu J. Modeling and dynamics of infectious diseases, Singapore: World Scientific, 2009: 216–236. link1

[25]  Wang B G, Qu B, Guo H Q, et al. Study on mathematical model of infectious disease prediction [J]. Chinese Journal of Health Statistics, 2007, 24(5): 536–540. Chinese. link1

[26]  Moirano G, Richiardi L, Novara C, et al. approaches to daily monitoring of the SARS-CoV-2 outbreak in Northern Italy [J]. Frontiers in Public Health, 2020, 8: 1–7. link1

[27]  Brooks L C, Farrow D C, Hyun S, et al. Flexible modeling of epidemics with an empirical Bayes framework [J]. PLOS Computational Biology, 2015, 11: 1–51. link1

[28]  Yang Z, Zeng Z, Wang K, et al. Modified SEIR and AI prediction of the epidemics trend of COVID-19 in China under public health interventions [J]. Journal of Thoracic Disease, 2020, 12(3): 165–174.

[29]  Hu Z X, Ge Q Y, Li S D, et al. Forecasting and evaluating multiple interventions for COVID-19 worldwide [J]. Frontiers in Physics, 2020, 3: 1–10. link1

[30]  Utsunomiya Y T, Utsunomiya A, Torrecilha R, et al. Growth rate and acceleration analysis of the COVID-19 pandemic reveals the effect of public health measures in real time [J]. Frontiers in Medicine, 2020, 7: 1–10. link1

[31]  Tsallis C, Tirnakli U. Predicting COVID-19 peaks around the world [J]. Frontiers in Physics, 2020, 8: 1–6. link1

[32]  Buckee C, Noor A, Sattenspiel L. Thinking clearly about social aspects of infectious disease transmission [J]. Nature, 2021. 595(7866): 205–213. link1

[33]  Wang F Y, Zeng D J, Mao W J. Social computing: Its significance, development and research status [J]. e-Science Technology & Application, 2010, 1(2): 3–14. Chinese. link1

[34]  Minar N, Burkhart R, Langton C G, et al. The swarm simulation system: A toolkit for building multi-agent simulations [EB/OL]. (1996-06-21)[2021-07-21]. https://santafe.edu/research/results/working-papers/the-swarm-simulation-system-atoolkit-for-building. link1

[35]  Collier N. RePast: An extensible framework for agent simulation [J]. Natural Resources and Environmental Issues (NREI), 2001 (8): 17–21. link1

[36]  Tisue S, Wilensky U. NetLogo: A simple environment for modeling complexity [C]. Boston: The Fifth International Conference on Complex Systems, 2004: 1–9. link1

[37]  Yuan H Y, Liang M C, Huang Q Y, et al. Application of empirical data assimilation method in trend analysis of COVID-19 [J]. Science & Technology Review, 2020, 38(6): 83–89. Chinese. link1

[1]  Lai S, Ruktanonchai N W, Zhou L, et al. Effect of nonpharmaceutical interventions to contain COVID-19 in China [J]. Nature, 2020, 585(7825): 410–413. link1

[2]  Ruktanonchai N W, Floyd J R, Lai S, et al. Assessing the impact of coordinated COVID-19 exit strategies across Europe [J]. Science, 2020, 369(6510): 1465–1470. link1

[3]  Flaxman S, Mishra S, Gandy A, et al. Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe [J]. Nature, 2020, 584(7820): 257–261. link1

[4]  Davis E L, Lucas T C D, Borlase A, et al. Contact tracing is an imperfect tool for controlling COVID-19 transmission and relies on population adherence [J]. Nature Communications, 2021, 12(9): 1–8. link1

[5]  Moon S A, Scoglio C M. Contact tracing evaluation for COVID-19 transmission in the different movement levels of a rural college town in the USA [J]. Scientific Reports, 2021, 11(3): 1–12. link1

[6]  Huang Q S, Wood T, Jelley L, et al. Impact of the COVID-19 nonpharmaceutical interventions on influenza and other respiratory viral infections in New Zealand [J]. Nature Communications, 2021,12(2): 1–7. link1

[7]  Suryanarayanan P, Tsou C H, Poddar A, et al. AI-assisted tracking of worldwide non-pharmaceutical interventions for COVID- 19 [J]. Scientific Data, 2021, 8(3): 1–14. link1

[8]  The State Council Information Office of the People’s Republic of China. Evaluation report on the implementation of the national human rights action plan (2012―2015) [EB/OL]. (2016-06-14)[2021-07-20]. http://www.gov.cn/xinwen/2016- 06/14/content_5082026.htm. Chinese. link1

[9]  Zhao Z X, Zhao J, Ma J Q. Conception of an integrated information system for notifiable disease communicable surveillance in China [J]. Disease Surveillance, 2018, 33(5): 423– 427. Chinese. link1

[10]  Wang Y, Xiang N J, Ni D X, et al. Performance of surveillance system of pneumonia with unknown etiology in two hospitals at municipal (prefecture) level in Anhui Province [J]. Disease Surveillance, 2017, 32(5): 428–432. Chinese. link1

[11]  Wang X Y. Global conspiracy for influenza prevention and control [N]. Health News, 2018-05-24(01). Chinese.

[12]  Shanghai Municipal Health Commission, Shanghai Municipal Development & Reform Commission, Shanghai Municipal Commission of Economy and Informatization, et al. Three years action plan for strengthening the construction of public health system in Shanghai (2020―2022) [EB/OL]. (2020-06-01)[2021-07-20]. https://www.shanghai.gov.cn/nw12344/20200813/0001-12344_65151.html. Chinese. link1

[13]  China Internet Network Information Center. The 47th China statistical report on Internet development [EB/OL]. (2021-02- 03) [2021-07-20]. http://www.cnnic.net.cn/hlwfzyj/hlwxzbg/hlwtjbg/202102/t20210203_71361.htm. Chinese. link1

[14]  Kermack W O, Mckendrick A G. A contribution to the mathematical theory of epidemics [J]. Proceedings of the Royal Society of London Series A, Containing Papers of A Mathematical and Physical Character, 1927, 115(772): 700–721. link1

[15]  Han H, Ma A N, Zhao X, et al. SIRS model with the long distance spread and emulation [J]. Journal of Wuhan University of Technology, 2010, 32(2): 141–145. Chinese. link1

[16]  Du Y F, Xiao P, Cao H. Dynamic behavior of a periodic seir epidemic model with stage-structure [J]. Journal of Sichuan Normal University (Natural Science), 2017, 40(1): 73–77. Chinese. link1

[17]  Hethcote H W. The mathematics of infectious diseases [J]. SIAM Review, 2000, 42(4): 599–653. link1

[18]  Castillo-Chavez C, Castillo-Garsow C W, Yakubu A A. Mathematical models of isolation and quarantine [J]. The Journal of American Medical Association, 2003, 290(21): 2876–2877. link1

[19]  Lucia1 U, Deisboeck T S, Grisolia1 G. Entropy-based pandemics forecasting [J]. Frontiers in Physics, 2020, 8: 1–7. link1

[20]  Roques L, Klein E K, Papax J, et al. Impact of lockdown on the epidemic dynamics of COVID-19 in France [J]. Frontiers in Medicine, 2020, 7: 1–7. link1

[21]  Della M M, Orlando D, Sannino F. Renormalisation group approach to pandemics: The COVID-19 case [J]. Frontiers in Physics, 2020, 8: 1–7. link1

[22]  Fisman D N, Hauck T S, Tuite A R, et al. An IDEA for short term outbreak projection: nearcasting using the basic reproduction number [J]. PLOS ONE, 2013, 8(12): 1–7. link1

[23]  Tuite A R, Fisman D N. The IDEA model: A single equation approach to the Ebola forecasting challenge [J]. Epidemics, 2018, 22: 71–77. link1

[24]  Hsieh Y. Richards model: A simple procedure for real-time prediction of outbreak severity [M]// Ma Z, Zhou Y, Wu J. Modeling and dynamics of infectious diseases, Singapore: World Scientific, 2009: 216–236. link1

[25]  Wang B G, Qu B, Guo H Q, et al. Study on mathematical model of infectious disease prediction [J]. Chinese Journal of Health Statistics, 2007, 24(5): 536–540. Chinese. link1

[26]  Moirano G, Richiardi L, Novara C, et al. approaches to daily monitoring of the SARS-CoV-2 outbreak in Northern Italy [J]. Frontiers in Public Health, 2020, 8: 1–7. link1

[27]  Brooks L C, Farrow D C, Hyun S, et al. Flexible modeling of epidemics with an empirical Bayes framework [J]. PLOS Computational Biology, 2015, 11: 1–51. link1

[28]  Yang Z, Zeng Z, Wang K, et al. Modified SEIR and AI prediction of the epidemics trend of COVID-19 in China under public health interventions [J]. Journal of Thoracic Disease, 2020, 12(3): 165–174.

[29]  Hu Z X, Ge Q Y, Li S D, et al. Forecasting and evaluating multiple interventions for COVID-19 worldwide [J]. Frontiers in Physics, 2020, 3: 1–10. link1

[30]  Utsunomiya Y T, Utsunomiya A, Torrecilha R, et al. Growth rate and acceleration analysis of the COVID-19 pandemic reveals the effect of public health measures in real time [J]. Frontiers in Medicine, 2020, 7: 1–10. link1

[31]  Tsallis C, Tirnakli U. Predicting COVID-19 peaks around the world [J]. Frontiers in Physics, 2020, 8: 1–6. link1

[32]  Buckee C, Noor A, Sattenspiel L. Thinking clearly about social aspects of infectious disease transmission [J]. Nature, 2021. 595(7866): 205–213. link1

[33]  Wang F Y, Zeng D J, Mao W J. Social computing: Its significance, development and research status [J]. e-Science Technology & Application, 2010, 1(2): 3–14. Chinese. link1

[34]  Minar N, Burkhart R, Langton C G, et al. The swarm simulation system: A toolkit for building multi-agent simulations [EB/OL]. (1996-06-21)[2021-07-21]. https://santafe.edu/research/results/working-papers/the-swarm-simulation-system-atoolkit-for-building. link1

[35]  Collier N. RePast: An extensible framework for agent simulation [J]. Natural Resources and Environmental Issues (NREI), 2001 (8): 17–21. link1

[36]  Tisue S, Wilensky U. NetLogo: A simple environment for modeling complexity [C]. Boston: The Fifth International Conference on Complex Systems, 2004: 1–9. link1

[37]  Yuan H Y, Liang M C, Huang Q Y, et al. Application of empirical data assimilation method in trend analysis of COVID-19 [J]. Science & Technology Review, 2020, 38(6): 83–89. Chinese. link1

[1]  Lai S, Ruktanonchai N W, Zhou L, et al. Effect of nonpharmaceutical interventions to contain COVID-19 in China [J]. Nature, 2020, 585(7825): 410–413. link1

[2]  Ruktanonchai N W, Floyd J R, Lai S, et al. Assessing the impact of coordinated COVID-19 exit strategies across Europe [J]. Science, 2020, 369(6510): 1465–1470. link1

[3]  Flaxman S, Mishra S, Gandy A, et al. Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe [J]. Nature, 2020, 584(7820): 257–261. link1

[4]  Davis E L, Lucas T C D, Borlase A, et al. Contact tracing is an imperfect tool for controlling COVID-19 transmission and relies on population adherence [J]. Nature Communications, 2021, 12(9): 1–8. link1

[5]  Moon S A, Scoglio C M. Contact tracing evaluation for COVID-19 transmission in the different movement levels of a rural college town in the USA [J]. Scientific Reports, 2021, 11(3): 1–12. link1

[6]  Huang Q S, Wood T, Jelley L, et al. Impact of the COVID-19 nonpharmaceutical interventions on influenza and other respiratory viral infections in New Zealand [J]. Nature Communications, 2021,12(2): 1–7. link1

[7]  Suryanarayanan P, Tsou C H, Poddar A, et al. AI-assisted tracking of worldwide non-pharmaceutical interventions for COVID- 19 [J]. Scientific Data, 2021, 8(3): 1–14. link1

[8]  The State Council Information Office of the People’s Republic of China. Evaluation report on the implementation of the national human rights action plan (2012―2015) [EB/OL]. (2016-06-14)[2021-07-20]. http://www.gov.cn/xinwen/2016- 06/14/content_5082026.htm. Chinese. link1

[9]  Zhao Z X, Zhao J, Ma J Q. Conception of an integrated information system for notifiable disease communicable surveillance in China [J]. Disease Surveillance, 2018, 33(5): 423– 427. Chinese. link1

[10]  Wang Y, Xiang N J, Ni D X, et al. Performance of surveillance system of pneumonia with unknown etiology in two hospitals at municipal (prefecture) level in Anhui Province [J]. Disease Surveillance, 2017, 32(5): 428–432. Chinese. link1

[11]  Wang X Y. Global conspiracy for influenza prevention and control [N]. Health News, 2018-05-24(01). Chinese.

[12]  Shanghai Municipal Health Commission, Shanghai Municipal Development & Reform Commission, Shanghai Municipal Commission of Economy and Informatization, et al. Three years action plan for strengthening the construction of public health system in Shanghai (2020―2022) [EB/OL]. (2020-06-01)[2021-07-20]. https://www.shanghai.gov.cn/nw12344/20200813/0001-12344_65151.html. Chinese. link1

[13]  China Internet Network Information Center. The 47th China statistical report on Internet development [EB/OL]. (2021-02- 03) [2021-07-20]. http://www.cnnic.net.cn/hlwfzyj/hlwxzbg/hlwtjbg/202102/t20210203_71361.htm. Chinese. link1

[14]  Kermack W O, Mckendrick A G. A contribution to the mathematical theory of epidemics [J]. Proceedings of the Royal Society of London Series A, Containing Papers of A Mathematical and Physical Character, 1927, 115(772): 700–721. link1

[15]  Han H, Ma A N, Zhao X, et al. SIRS model with the long distance spread and emulation [J]. Journal of Wuhan University of Technology, 2010, 32(2): 141–145. Chinese. link1

[16]  Du Y F, Xiao P, Cao H. Dynamic behavior of a periodic seir epidemic model with stage-structure [J]. Journal of Sichuan Normal University (Natural Science), 2017, 40(1): 73–77. Chinese. link1

[17]  Hethcote H W. The mathematics of infectious diseases [J]. SIAM Review, 2000, 42(4): 599–653. link1

[18]  Castillo-Chavez C, Castillo-Garsow C W, Yakubu A A. Mathematical models of isolation and quarantine [J]. The Journal of American Medical Association, 2003, 290(21): 2876–2877. link1

[19]  Lucia1 U, Deisboeck T S, Grisolia1 G. Entropy-based pandemics forecasting [J]. Frontiers in Physics, 2020, 8: 1–7. link1

[20]  Roques L, Klein E K, Papax J, et al. Impact of lockdown on the epidemic dynamics of COVID-19 in France [J]. Frontiers in Medicine, 2020, 7: 1–7. link1

[21]  Della M M, Orlando D, Sannino F. Renormalisation group approach to pandemics: The COVID-19 case [J]. Frontiers in Physics, 2020, 8: 1–7. link1

[22]  Fisman D N, Hauck T S, Tuite A R, et al. An IDEA for short term outbreak projection: nearcasting using the basic reproduction number [J]. PLOS ONE, 2013, 8(12): 1–7. link1

[23]  Tuite A R, Fisman D N. The IDEA model: A single equation approach to the Ebola forecasting challenge [J]. Epidemics, 2018, 22: 71–77. link1

[24]  Hsieh Y. Richards model: A simple procedure for real-time prediction of outbreak severity [M]// Ma Z, Zhou Y, Wu J. Modeling and dynamics of infectious diseases, Singapore: World Scientific, 2009: 216–236. link1

[25]  Wang B G, Qu B, Guo H Q, et al. Study on mathematical model of infectious disease prediction [J]. Chinese Journal of Health Statistics, 2007, 24(5): 536–540. Chinese. link1

[26]  Moirano G, Richiardi L, Novara C, et al. approaches to daily monitoring of the SARS-CoV-2 outbreak in Northern Italy [J]. Frontiers in Public Health, 2020, 8: 1–7. link1

[27]  Brooks L C, Farrow D C, Hyun S, et al. Flexible modeling of epidemics with an empirical Bayes framework [J]. PLOS Computational Biology, 2015, 11: 1–51. link1

[28]  Yang Z, Zeng Z, Wang K, et al. Modified SEIR and AI prediction of the epidemics trend of COVID-19 in China under public health interventions [J]. Journal of Thoracic Disease, 2020, 12(3): 165–174.

[29]  Hu Z X, Ge Q Y, Li S D, et al. Forecasting and evaluating multiple interventions for COVID-19 worldwide [J]. Frontiers in Physics, 2020, 3: 1–10. link1

[30]  Utsunomiya Y T, Utsunomiya A, Torrecilha R, et al. Growth rate and acceleration analysis of the COVID-19 pandemic reveals the effect of public health measures in real time [J]. Frontiers in Medicine, 2020, 7: 1–10. link1

[31]  Tsallis C, Tirnakli U. Predicting COVID-19 peaks around the world [J]. Frontiers in Physics, 2020, 8: 1–6. link1

[32]  Buckee C, Noor A, Sattenspiel L. Thinking clearly about social aspects of infectious disease transmission [J]. Nature, 2021. 595(7866): 205–213. link1

[33]  Wang F Y, Zeng D J, Mao W J. Social computing: Its significance, development and research status [J]. e-Science Technology & Application, 2010, 1(2): 3–14. Chinese. link1

[34]  Minar N, Burkhart R, Langton C G, et al. The swarm simulation system: A toolkit for building multi-agent simulations [EB/OL]. (1996-06-21)[2021-07-21]. https://santafe.edu/research/results/working-papers/the-swarm-simulation-system-atoolkit-for-building. link1

[35]  Collier N. RePast: An extensible framework for agent simulation [J]. Natural Resources and Environmental Issues (NREI), 2001 (8): 17–21. link1

[36]  Tisue S, Wilensky U. NetLogo: A simple environment for modeling complexity [C]. Boston: The Fifth International Conference on Complex Systems, 2004: 1–9. link1

[37]  Yuan H Y, Liang M C, Huang Q Y, et al. Application of empirical data assimilation method in trend analysis of COVID-19 [J]. Science & Technology Review, 2020, 38(6): 83–89. Chinese. link1

[1]  Lai S, Ruktanonchai N W, Zhou L, et al. Effect of nonpharmaceutical interventions to contain COVID-19 in China [J]. Nature, 2020, 585(7825): 410–413. link1

[2]  Ruktanonchai N W, Floyd J R, Lai S, et al. Assessing the impact of coordinated COVID-19 exit strategies across Europe [J]. Science, 2020, 369(6510): 1465–1470. link1

[3]  Flaxman S, Mishra S, Gandy A, et al. Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe [J]. Nature, 2020, 584(7820): 257–261. link1

[4]  Davis E L, Lucas T C D, Borlase A, et al. Contact tracing is an imperfect tool for controlling COVID-19 transmission and relies on population adherence [J]. Nature Communications, 2021, 12(9): 1–8. link1

[5]  Moon S A, Scoglio C M. Contact tracing evaluation for COVID-19 transmission in the different movement levels of a rural college town in the USA [J]. Scientific Reports, 2021, 11(3): 1–12. link1

[6]  Huang Q S, Wood T, Jelley L, et al. Impact of the COVID-19 nonpharmaceutical interventions on influenza and other respiratory viral infections in New Zealand [J]. Nature Communications, 2021,12(2): 1–7. link1

[7]  Suryanarayanan P, Tsou C H, Poddar A, et al. AI-assisted tracking of worldwide non-pharmaceutical interventions for COVID- 19 [J]. Scientific Data, 2021, 8(3): 1–14. link1

[8]  The State Council Information Office of the People’s Republic of China. Evaluation report on the implementation of the national human rights action plan (2012―2015) [EB/OL]. (2016-06-14)[2021-07-20]. http://www.gov.cn/xinwen/2016- 06/14/content_5082026.htm. Chinese. link1

[9]  Zhao Z X, Zhao J, Ma J Q. Conception of an integrated information system for notifiable disease communicable surveillance in China [J]. Disease Surveillance, 2018, 33(5): 423– 427. Chinese. link1

[10]  Wang Y, Xiang N J, Ni D X, et al. Performance of surveillance system of pneumonia with unknown etiology in two hospitals at municipal (prefecture) level in Anhui Province [J]. Disease Surveillance, 2017, 32(5): 428–432. Chinese. link1

[11]  Wang X Y. Global conspiracy for influenza prevention and control [N]. Health News, 2018-05-24(01). Chinese.

[12]  Shanghai Municipal Health Commission, Shanghai Municipal Development & Reform Commission, Shanghai Municipal Commission of Economy and Informatization, et al. Three years action plan for strengthening the construction of public health system in Shanghai (2020―2022) [EB/OL]. (2020-06-01)[2021-07-20]. https://www.shanghai.gov.cn/nw12344/20200813/0001-12344_65151.html. Chinese. link1

[13]  China Internet Network Information Center. The 47th China statistical report on Internet development [EB/OL]. (2021-02- 03) [2021-07-20]. http://www.cnnic.net.cn/hlwfzyj/hlwxzbg/hlwtjbg/202102/t20210203_71361.htm. Chinese. link1

[14]  Kermack W O, Mckendrick A G. A contribution to the mathematical theory of epidemics [J]. Proceedings of the Royal Society of London Series A, Containing Papers of A Mathematical and Physical Character, 1927, 115(772): 700–721. link1

[15]  Han H, Ma A N, Zhao X, et al. SIRS model with the long distance spread and emulation [J]. Journal of Wuhan University of Technology, 2010, 32(2): 141–145. Chinese. link1

[16]  Du Y F, Xiao P, Cao H. Dynamic behavior of a periodic seir epidemic model with stage-structure [J]. Journal of Sichuan Normal University (Natural Science), 2017, 40(1): 73–77. Chinese. link1

[17]  Hethcote H W. The mathematics of infectious diseases [J]. SIAM Review, 2000, 42(4): 599–653. link1

[18]  Castillo-Chavez C, Castillo-Garsow C W, Yakubu A A. Mathematical models of isolation and quarantine [J]. The Journal of American Medical Association, 2003, 290(21): 2876–2877. link1

[19]  Lucia1 U, Deisboeck T S, Grisolia1 G. Entropy-based pandemics forecasting [J]. Frontiers in Physics, 2020, 8: 1–7. link1

[20]  Roques L, Klein E K, Papax J, et al. Impact of lockdown on the epidemic dynamics of COVID-19 in France [J]. Frontiers in Medicine, 2020, 7: 1–7. link1

[21]  Della M M, Orlando D, Sannino F. Renormalisation group approach to pandemics: The COVID-19 case [J]. Frontiers in Physics, 2020, 8: 1–7. link1

[22]  Fisman D N, Hauck T S, Tuite A R, et al. An IDEA for short term outbreak projection: nearcasting using the basic reproduction number [J]. PLOS ONE, 2013, 8(12): 1–7. link1

[23]  Tuite A R, Fisman D N. The IDEA model: A single equation approach to the Ebola forecasting challenge [J]. Epidemics, 2018, 22: 71–77. link1

[24]  Hsieh Y. Richards model: A simple procedure for real-time prediction of outbreak severity [M]// Ma Z, Zhou Y, Wu J. Modeling and dynamics of infectious diseases, Singapore: World Scientific, 2009: 216–236. link1

[25]  Wang B G, Qu B, Guo H Q, et al. Study on mathematical model of infectious disease prediction [J]. Chinese Journal of Health Statistics, 2007, 24(5): 536–540. Chinese. link1

[26]  Moirano G, Richiardi L, Novara C, et al. approaches to daily monitoring of the SARS-CoV-2 outbreak in Northern Italy [J]. Frontiers in Public Health, 2020, 8: 1–7. link1

[27]  Brooks L C, Farrow D C, Hyun S, et al. Flexible modeling of epidemics with an empirical Bayes framework [J]. PLOS Computational Biology, 2015, 11: 1–51. link1

[28]  Yang Z, Zeng Z, Wang K, et al. Modified SEIR and AI prediction of the epidemics trend of COVID-19 in China under public health interventions [J]. Journal of Thoracic Disease, 2020, 12(3): 165–174.

[29]  Hu Z X, Ge Q Y, Li S D, et al. Forecasting and evaluating multiple interventions for COVID-19 worldwide [J]. Frontiers in Physics, 2020, 3: 1–10. link1

[30]  Utsunomiya Y T, Utsunomiya A, Torrecilha R, et al. Growth rate and acceleration analysis of the COVID-19 pandemic reveals the effect of public health measures in real time [J]. Frontiers in Medicine, 2020, 7: 1–10. link1

[31]  Tsallis C, Tirnakli U. Predicting COVID-19 peaks around the world [J]. Frontiers in Physics, 2020, 8: 1–6. link1

[32]  Buckee C, Noor A, Sattenspiel L. Thinking clearly about social aspects of infectious disease transmission [J]. Nature, 2021. 595(7866): 205–213. link1

[33]  Wang F Y, Zeng D J, Mao W J. Social computing: Its significance, development and research status [J]. e-Science Technology & Application, 2010, 1(2): 3–14. Chinese. link1

[34]  Minar N, Burkhart R, Langton C G, et al. The swarm simulation system: A toolkit for building multi-agent simulations [EB/OL]. (1996-06-21)[2021-07-21]. https://santafe.edu/research/results/working-papers/the-swarm-simulation-system-atoolkit-for-building. link1

[35]  Collier N. RePast: An extensible framework for agent simulation [J]. Natural Resources and Environmental Issues (NREI), 2001 (8): 17–21. link1

[36]  Tisue S, Wilensky U. NetLogo: A simple environment for modeling complexity [C]. Boston: The Fifth International Conference on Complex Systems, 2004: 1–9. link1

[37]  Yuan H Y, Liang M C, Huang Q Y, et al. Application of empirical data assimilation method in trend analysis of COVID-19 [J]. Science & Technology Review, 2020, 38(6): 83–89. Chinese. link1

[1]  Lai S, Ruktanonchai N W, Zhou L, et al. Effect of nonpharmaceutical interventions to contain COVID-19 in China [J]. Nature, 2020, 585(7825): 410–413. link1

[2]  Ruktanonchai N W, Floyd J R, Lai S, et al. Assessing the impact of coordinated COVID-19 exit strategies across Europe [J]. Science, 2020, 369(6510): 1465–1470. link1

[3]  Flaxman S, Mishra S, Gandy A, et al. Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe [J]. Nature, 2020, 584(7820): 257–261. link1

[4]  Davis E L, Lucas T C D, Borlase A, et al. Contact tracing is an imperfect tool for controlling COVID-19 transmission and relies on population adherence [J]. Nature Communications, 2021, 12(9): 1–8. link1

[5]  Moon S A, Scoglio C M. Contact tracing evaluation for COVID-19 transmission in the different movement levels of a rural college town in the USA [J]. Scientific Reports, 2021, 11(3): 1–12. link1

[6]  Huang Q S, Wood T, Jelley L, et al. Impact of the COVID-19 nonpharmaceutical interventions on influenza and other respiratory viral infections in New Zealand [J]. Nature Communications, 2021,12(2): 1–7. link1

[7]  Suryanarayanan P, Tsou C H, Poddar A, et al. AI-assisted tracking of worldwide non-pharmaceutical interventions for COVID- 19 [J]. Scientific Data, 2021, 8(3): 1–14. link1

[8]  The State Council Information Office of the People’s Republic of China. Evaluation report on the implementation of the national human rights action plan (2012―2015) [EB/OL]. (2016-06-14)[2021-07-20]. http://www.gov.cn/xinwen/2016- 06/14/content_5082026.htm. Chinese. link1

[9]  Zhao Z X, Zhao J, Ma J Q. Conception of an integrated information system for notifiable disease communicable surveillance in China [J]. Disease Surveillance, 2018, 33(5): 423– 427. Chinese. link1

[10]  Wang Y, Xiang N J, Ni D X, et al. Performance of surveillance system of pneumonia with unknown etiology in two hospitals at municipal (prefecture) level in Anhui Province [J]. Disease Surveillance, 2017, 32(5): 428–432. Chinese. link1

[11]  Wang X Y. Global conspiracy for influenza prevention and control [N]. Health News, 2018-05-24(01). Chinese.

[12]  Shanghai Municipal Health Commission, Shanghai Municipal Development & Reform Commission, Shanghai Municipal Commission of Economy and Informatization, et al. Three years action plan for strengthening the construction of public health system in Shanghai (2020―2022) [EB/OL]. (2020-06-01)[2021-07-20]. https://www.shanghai.gov.cn/nw12344/20200813/0001-12344_65151.html. Chinese. link1

[13]  China Internet Network Information Center. The 47th China statistical report on Internet development [EB/OL]. (2021-02- 03) [2021-07-20]. http://www.cnnic.net.cn/hlwfzyj/hlwxzbg/hlwtjbg/202102/t20210203_71361.htm. Chinese. link1

[14]  Kermack W O, Mckendrick A G. A contribution to the mathematical theory of epidemics [J]. Proceedings of the Royal Society of London Series A, Containing Papers of A Mathematical and Physical Character, 1927, 115(772): 700–721. link1

[15]  Han H, Ma A N, Zhao X, et al. SIRS model with the long distance spread and emulation [J]. Journal of Wuhan University of Technology, 2010, 32(2): 141–145. Chinese. link1

[16]  Du Y F, Xiao P, Cao H. Dynamic behavior of a periodic seir epidemic model with stage-structure [J]. Journal of Sichuan Normal University (Natural Science), 2017, 40(1): 73–77. Chinese. link1

[17]  Hethcote H W. The mathematics of infectious diseases [J]. SIAM Review, 2000, 42(4): 599–653. link1

[18]  Castillo-Chavez C, Castillo-Garsow C W, Yakubu A A. Mathematical models of isolation and quarantine [J]. The Journal of American Medical Association, 2003, 290(21): 2876–2877. link1

[19]  Lucia1 U, Deisboeck T S, Grisolia1 G. Entropy-based pandemics forecasting [J]. Frontiers in Physics, 2020, 8: 1–7. link1

[20]  Roques L, Klein E K, Papax J, et al. Impact of lockdown on the epidemic dynamics of COVID-19 in France [J]. Frontiers in Medicine, 2020, 7: 1–7. link1

[21]  Della M M, Orlando D, Sannino F. Renormalisation group approach to pandemics: The COVID-19 case [J]. Frontiers in Physics, 2020, 8: 1–7. link1

[22]  Fisman D N, Hauck T S, Tuite A R, et al. An IDEA for short term outbreak projection: nearcasting using the basic reproduction number [J]. PLOS ONE, 2013, 8(12): 1–7. link1

[23]  Tuite A R, Fisman D N. The IDEA model: A single equation approach to the Ebola forecasting challenge [J]. Epidemics, 2018, 22: 71–77. link1

[24]  Hsieh Y. Richards model: A simple procedure for real-time prediction of outbreak severity [M]// Ma Z, Zhou Y, Wu J. Modeling and dynamics of infectious diseases, Singapore: World Scientific, 2009: 216–236. link1

[25]  Wang B G, Qu B, Guo H Q, et al. Study on mathematical model of infectious disease prediction [J]. Chinese Journal of Health Statistics, 2007, 24(5): 536–540. Chinese. link1

[26]  Moirano G, Richiardi L, Novara C, et al. approaches to daily monitoring of the SARS-CoV-2 outbreak in Northern Italy [J]. Frontiers in Public Health, 2020, 8: 1–7. link1

[27]  Brooks L C, Farrow D C, Hyun S, et al. Flexible modeling of epidemics with an empirical Bayes framework [J]. PLOS Computational Biology, 2015, 11: 1–51. link1

[28]  Yang Z, Zeng Z, Wang K, et al. Modified SEIR and AI prediction of the epidemics trend of COVID-19 in China under public health interventions [J]. Journal of Thoracic Disease, 2020, 12(3): 165–174.

[29]  Hu Z X, Ge Q Y, Li S D, et al. Forecasting and evaluating multiple interventions for COVID-19 worldwide [J]. Frontiers in Physics, 2020, 3: 1–10. link1

[30]  Utsunomiya Y T, Utsunomiya A, Torrecilha R, et al. Growth rate and acceleration analysis of the COVID-19 pandemic reveals the effect of public health measures in real time [J]. Frontiers in Medicine, 2020, 7: 1–10. link1

[31]  Tsallis C, Tirnakli U. Predicting COVID-19 peaks around the world [J]. Frontiers in Physics, 2020, 8: 1–6. link1

[32]  Buckee C, Noor A, Sattenspiel L. Thinking clearly about social aspects of infectious disease transmission [J]. Nature, 2021. 595(7866): 205–213. link1

[33]  Wang F Y, Zeng D J, Mao W J. Social computing: Its significance, development and research status [J]. e-Science Technology & Application, 2010, 1(2): 3–14. Chinese. link1

[34]  Minar N, Burkhart R, Langton C G, et al. The swarm simulation system: A toolkit for building multi-agent simulations [EB/OL]. (1996-06-21)[2021-07-21]. https://santafe.edu/research/results/working-papers/the-swarm-simulation-system-atoolkit-for-building. link1

[35]  Collier N. RePast: An extensible framework for agent simulation [J]. Natural Resources and Environmental Issues (NREI), 2001 (8): 17–21. link1

[36]  Tisue S, Wilensky U. NetLogo: A simple environment for modeling complexity [C]. Boston: The Fifth International Conference on Complex Systems, 2004: 1–9. link1

[37]  Yuan H Y, Liang M C, Huang Q Y, et al. Application of empirical data assimilation method in trend analysis of COVID-19 [J]. Science & Technology Review, 2020, 38(6): 83–89. Chinese. link1

[1]  Lai S, Ruktanonchai N W, Zhou L, et al. Effect of nonpharmaceutical interventions to contain COVID-19 in China [J]. Nature, 2020, 585(7825): 410–413. link1

[2]  Ruktanonchai N W, Floyd J R, Lai S, et al. Assessing the impact of coordinated COVID-19 exit strategies across Europe [J]. Science, 2020, 369(6510): 1465–1470. link1

[3]  Flaxman S, Mishra S, Gandy A, et al. Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe [J]. Nature, 2020, 584(7820): 257–261. link1

[4]  Davis E L, Lucas T C D, Borlase A, et al. Contact tracing is an imperfect tool for controlling COVID-19 transmission and relies on population adherence [J]. Nature Communications, 2021, 12(9): 1–8. link1

[5]  Moon S A, Scoglio C M. Contact tracing evaluation for COVID-19 transmission in the different movement levels of a rural college town in the USA [J]. Scientific Reports, 2021, 11(3): 1–12. link1

[6]  Huang Q S, Wood T, Jelley L, et al. Impact of the COVID-19 nonpharmaceutical interventions on influenza and other respiratory viral infections in New Zealand [J]. Nature Communications, 2021,12(2): 1–7. link1

[7]  Suryanarayanan P, Tsou C H, Poddar A, et al. AI-assisted tracking of worldwide non-pharmaceutical interventions for COVID- 19 [J]. Scientific Data, 2021, 8(3): 1–14. link1

[8]  The State Council Information Office of the People’s Republic of China. Evaluation report on the implementation of the national human rights action plan (2012―2015) [EB/OL]. (2016-06-14)[2021-07-20]. http://www.gov.cn/xinwen/2016- 06/14/content_5082026.htm. Chinese. link1

[9]  Zhao Z X, Zhao J, Ma J Q. Conception of an integrated information system for notifiable disease communicable surveillance in China [J]. Disease Surveillance, 2018, 33(5): 423– 427. Chinese. link1

[10]  Wang Y, Xiang N J, Ni D X, et al. Performance of surveillance system of pneumonia with unknown etiology in two hospitals at municipal (prefecture) level in Anhui Province [J]. Disease Surveillance, 2017, 32(5): 428–432. Chinese. link1

[11]  Wang X Y. Global conspiracy for influenza prevention and control [N]. Health News, 2018-05-24(01). Chinese.

[12]  Shanghai Municipal Health Commission, Shanghai Municipal Development & Reform Commission, Shanghai Municipal Commission of Economy and Informatization, et al. Three years action plan for strengthening the construction of public health system in Shanghai (2020―2022) [EB/OL]. (2020-06-01)[2021-07-20]. https://www.shanghai.gov.cn/nw12344/20200813/0001-12344_65151.html. Chinese. link1

[13]  China Internet Network Information Center. The 47th China statistical report on Internet development [EB/OL]. (2021-02- 03) [2021-07-20]. http://www.cnnic.net.cn/hlwfzyj/hlwxzbg/hlwtjbg/202102/t20210203_71361.htm. Chinese. link1

[14]  Kermack W O, Mckendrick A G. A contribution to the mathematical theory of epidemics [J]. Proceedings of the Royal Society of London Series A, Containing Papers of A Mathematical and Physical Character, 1927, 115(772): 700–721. link1

[15]  Han H, Ma A N, Zhao X, et al. SIRS model with the long distance spread and emulation [J]. Journal of Wuhan University of Technology, 2010, 32(2): 141–145. Chinese. link1

[16]  Du Y F, Xiao P, Cao H. Dynamic behavior of a periodic seir epidemic model with stage-structure [J]. Journal of Sichuan Normal University (Natural Science), 2017, 40(1): 73–77. Chinese. link1

[17]  Hethcote H W. The mathematics of infectious diseases [J]. SIAM Review, 2000, 42(4): 599–653. link1

[18]  Castillo-Chavez C, Castillo-Garsow C W, Yakubu A A. Mathematical models of isolation and quarantine [J]. The Journal of American Medical Association, 2003, 290(21): 2876–2877. link1

[19]  Lucia1 U, Deisboeck T S, Grisolia1 G. Entropy-based pandemics forecasting [J]. Frontiers in Physics, 2020, 8: 1–7. link1

[20]  Roques L, Klein E K, Papax J, et al. Impact of lockdown on the epidemic dynamics of COVID-19 in France [J]. Frontiers in Medicine, 2020, 7: 1–7. link1

[21]  Della M M, Orlando D, Sannino F. Renormalisation group approach to pandemics: The COVID-19 case [J]. Frontiers in Physics, 2020, 8: 1–7. link1

[22]  Fisman D N, Hauck T S, Tuite A R, et al. An IDEA for short term outbreak projection: nearcasting using the basic reproduction number [J]. PLOS ONE, 2013, 8(12): 1–7. link1

[23]  Tuite A R, Fisman D N. The IDEA model: A single equation approach to the Ebola forecasting challenge [J]. Epidemics, 2018, 22: 71–77. link1

[24]  Hsieh Y. Richards model: A simple procedure for real-time prediction of outbreak severity [M]// Ma Z, Zhou Y, Wu J. Modeling and dynamics of infectious diseases, Singapore: World Scientific, 2009: 216–236. link1

[25]  Wang B G, Qu B, Guo H Q, et al. Study on mathematical model of infectious disease prediction [J]. Chinese Journal of Health Statistics, 2007, 24(5): 536–540. Chinese. link1

[26]  Moirano G, Richiardi L, Novara C, et al. approaches to daily monitoring of the SARS-CoV-2 outbreak in Northern Italy [J]. Frontiers in Public Health, 2020, 8: 1–7. link1

[27]  Brooks L C, Farrow D C, Hyun S, et al. Flexible modeling of epidemics with an empirical Bayes framework [J]. PLOS Computational Biology, 2015, 11: 1–51. link1

[28]  Yang Z, Zeng Z, Wang K, et al. Modified SEIR and AI prediction of the epidemics trend of COVID-19 in China under public health interventions [J]. Journal of Thoracic Disease, 2020, 12(3): 165–174.

[29]  Hu Z X, Ge Q Y, Li S D, et al. Forecasting and evaluating multiple interventions for COVID-19 worldwide [J]. Frontiers in Physics, 2020, 3: 1–10. link1

[30]  Utsunomiya Y T, Utsunomiya A, Torrecilha R, et al. Growth rate and acceleration analysis of the COVID-19 pandemic reveals the effect of public health measures in real time [J]. Frontiers in Medicine, 2020, 7: 1–10. link1

[31]  Tsallis C, Tirnakli U. Predicting COVID-19 peaks around the world [J]. Frontiers in Physics, 2020, 8: 1–6. link1

[32]  Buckee C, Noor A, Sattenspiel L. Thinking clearly about social aspects of infectious disease transmission [J]. Nature, 2021. 595(7866): 205–213. link1

[33]  Wang F Y, Zeng D J, Mao W J. Social computing: Its significance, development and research status [J]. e-Science Technology & Application, 2010, 1(2): 3–14. Chinese. link1

[34]  Minar N, Burkhart R, Langton C G, et al. The swarm simulation system: A toolkit for building multi-agent simulations [EB/OL]. (1996-06-21)[2021-07-21]. https://santafe.edu/research/results/working-papers/the-swarm-simulation-system-atoolkit-for-building. link1

[35]  Collier N. RePast: An extensible framework for agent simulation [J]. Natural Resources and Environmental Issues (NREI), 2001 (8): 17–21. link1

[36]  Tisue S, Wilensky U. NetLogo: A simple environment for modeling complexity [C]. Boston: The Fifth International Conference on Complex Systems, 2004: 1–9. link1

[37]  Yuan H Y, Liang M C, Huang Q Y, et al. Application of empirical data assimilation method in trend analysis of COVID-19 [J]. Science & Technology Review, 2020, 38(6): 83–89. Chinese. link1

[1]  Lai S, Ruktanonchai N W, Zhou L, et al. Effect of nonpharmaceutical interventions to contain COVID-19 in China [J]. Nature, 2020, 585(7825): 410–413. link1

[2]  Ruktanonchai N W, Floyd J R, Lai S, et al. Assessing the impact of coordinated COVID-19 exit strategies across Europe [J]. Science, 2020, 369(6510): 1465–1470. link1

[3]  Flaxman S, Mishra S, Gandy A, et al. Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe [J]. Nature, 2020, 584(7820): 257–261. link1

[4]  Davis E L, Lucas T C D, Borlase A, et al. Contact tracing is an imperfect tool for controlling COVID-19 transmission and relies on population adherence [J]. Nature Communications, 2021, 12(9): 1–8. link1

[5]  Moon S A, Scoglio C M. Contact tracing evaluation for COVID-19 transmission in the different movement levels of a rural college town in the USA [J]. Scientific Reports, 2021, 11(3): 1–12. link1

[6]  Huang Q S, Wood T, Jelley L, et al. Impact of the COVID-19 nonpharmaceutical interventions on influenza and other respiratory viral infections in New Zealand [J]. Nature Communications, 2021,12(2): 1–7. link1

[7]  Suryanarayanan P, Tsou C H, Poddar A, et al. AI-assisted tracking of worldwide non-pharmaceutical interventions for COVID- 19 [J]. Scientific Data, 2021, 8(3): 1–14. link1

[8]  The State Council Information Office of the People’s Republic of China. Evaluation report on the implementation of the national human rights action plan (2012―2015) [EB/OL]. (2016-06-14)[2021-07-20]. http://www.gov.cn/xinwen/2016- 06/14/content_5082026.htm. Chinese. link1

[9]  Zhao Z X, Zhao J, Ma J Q. Conception of an integrated information system for notifiable disease communicable surveillance in China [J]. Disease Surveillance, 2018, 33(5): 423– 427. Chinese. link1

[10]  Wang Y, Xiang N J, Ni D X, et al. Performance of surveillance system of pneumonia with unknown etiology in two hospitals at municipal (prefecture) level in Anhui Province [J]. Disease Surveillance, 2017, 32(5): 428–432. Chinese. link1

[11]  Wang X Y. Global conspiracy for influenza prevention and control [N]. Health News, 2018-05-24(01). Chinese.

[12]  Shanghai Municipal Health Commission, Shanghai Municipal Development & Reform Commission, Shanghai Municipal Commission of Economy and Informatization, et al. Three years action plan for strengthening the construction of public health system in Shanghai (2020―2022) [EB/OL]. (2020-06-01)[2021-07-20]. https://www.shanghai.gov.cn/nw12344/20200813/0001-12344_65151.html. Chinese. link1

[13]  China Internet Network Information Center. The 47th China statistical report on Internet development [EB/OL]. (2021-02- 03) [2021-07-20]. http://www.cnnic.net.cn/hlwfzyj/hlwxzbg/hlwtjbg/202102/t20210203_71361.htm. Chinese. link1

[14]  Kermack W O, Mckendrick A G. A contribution to the mathematical theory of epidemics [J]. Proceedings of the Royal Society of London Series A, Containing Papers of A Mathematical and Physical Character, 1927, 115(772): 700–721. link1

[15]  Han H, Ma A N, Zhao X, et al. SIRS model with the long distance spread and emulation [J]. Journal of Wuhan University of Technology, 2010, 32(2): 141–145. Chinese. link1

[16]  Du Y F, Xiao P, Cao H. Dynamic behavior of a periodic seir epidemic model with stage-structure [J]. Journal of Sichuan Normal University (Natural Science), 2017, 40(1): 73–77. Chinese. link1

[17]  Hethcote H W. The mathematics of infectious diseases [J]. SIAM Review, 2000, 42(4): 599–653. link1

[18]  Castillo-Chavez C, Castillo-Garsow C W, Yakubu A A. Mathematical models of isolation and quarantine [J]. The Journal of American Medical Association, 2003, 290(21): 2876–2877. link1

[19]  Lucia1 U, Deisboeck T S, Grisolia1 G. Entropy-based pandemics forecasting [J]. Frontiers in Physics, 2020, 8: 1–7. link1

[20]  Roques L, Klein E K, Papax J, et al. Impact of lockdown on the epidemic dynamics of COVID-19 in France [J]. Frontiers in Medicine, 2020, 7: 1–7. link1

[21]  Della M M, Orlando D, Sannino F. Renormalisation group approach to pandemics: The COVID-19 case [J]. Frontiers in Physics, 2020, 8: 1–7. link1

[22]  Fisman D N, Hauck T S, Tuite A R, et al. An IDEA for short term outbreak projection: nearcasting using the basic reproduction number [J]. PLOS ONE, 2013, 8(12): 1–7. link1

[23]  Tuite A R, Fisman D N. The IDEA model: A single equation approach to the Ebola forecasting challenge [J]. Epidemics, 2018, 22: 71–77. link1

[24]  Hsieh Y. Richards model: A simple procedure for real-time prediction of outbreak severity [M]// Ma Z, Zhou Y, Wu J. Modeling and dynamics of infectious diseases, Singapore: World Scientific, 2009: 216–236. link1

[25]  Wang B G, Qu B, Guo H Q, et al. Study on mathematical model of infectious disease prediction [J]. Chinese Journal of Health Statistics, 2007, 24(5): 536–540. Chinese. link1

[26]  Moirano G, Richiardi L, Novara C, et al. approaches to daily monitoring of the SARS-CoV-2 outbreak in Northern Italy [J]. Frontiers in Public Health, 2020, 8: 1–7. link1

[27]  Brooks L C, Farrow D C, Hyun S, et al. Flexible modeling of epidemics with an empirical Bayes framework [J]. PLOS Computational Biology, 2015, 11: 1–51. link1

[28]  Yang Z, Zeng Z, Wang K, et al. Modified SEIR and AI prediction of the epidemics trend of COVID-19 in China under public health interventions [J]. Journal of Thoracic Disease, 2020, 12(3): 165–174.

[29]  Hu Z X, Ge Q Y, Li S D, et al. Forecasting and evaluating multiple interventions for COVID-19 worldwide [J]. Frontiers in Physics, 2020, 3: 1–10. link1

[30]  Utsunomiya Y T, Utsunomiya A, Torrecilha R, et al. Growth rate and acceleration analysis of the COVID-19 pandemic reveals the effect of public health measures in real time [J]. Frontiers in Medicine, 2020, 7: 1–10. link1

[31]  Tsallis C, Tirnakli U. Predicting COVID-19 peaks around the world [J]. Frontiers in Physics, 2020, 8: 1–6. link1

[32]  Buckee C, Noor A, Sattenspiel L. Thinking clearly about social aspects of infectious disease transmission [J]. Nature, 2021. 595(7866): 205–213. link1

[33]  Wang F Y, Zeng D J, Mao W J. Social computing: Its significance, development and research status [J]. e-Science Technology & Application, 2010, 1(2): 3–14. Chinese. link1

[34]  Minar N, Burkhart R, Langton C G, et al. The swarm simulation system: A toolkit for building multi-agent simulations [EB/OL]. (1996-06-21)[2021-07-21]. https://santafe.edu/research/results/working-papers/the-swarm-simulation-system-atoolkit-for-building. link1

[35]  Collier N. RePast: An extensible framework for agent simulation [J]. Natural Resources and Environmental Issues (NREI), 2001 (8): 17–21. link1

[36]  Tisue S, Wilensky U. NetLogo: A simple environment for modeling complexity [C]. Boston: The Fifth International Conference on Complex Systems, 2004: 1–9. link1

[37]  Yuan H Y, Liang M C, Huang Q Y, et al. Application of empirical data assimilation method in trend analysis of COVID-19 [J]. Science & Technology Review, 2020, 38(6): 83–89. Chinese. link1

[1]  Lai S, Ruktanonchai N W, Zhou L, et al. Effect of nonpharmaceutical interventions to contain COVID-19 in China [J]. Nature, 2020, 585(7825): 410–413. link1

[2]  Ruktanonchai N W, Floyd J R, Lai S, et al. Assessing the impact of coordinated COVID-19 exit strategies across Europe [J]. Science, 2020, 369(6510): 1465–1470. link1

[3]  Flaxman S, Mishra S, Gandy A, et al. Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe [J]. Nature, 2020, 584(7820): 257–261. link1

[4]  Davis E L, Lucas T C D, Borlase A, et al. Contact tracing is an imperfect tool for controlling COVID-19 transmission and relies on population adherence [J]. Nature Communications, 2021, 12(9): 1–8. link1

[5]  Moon S A, Scoglio C M. Contact tracing evaluation for COVID-19 transmission in the different movement levels of a rural college town in the USA [J]. Scientific Reports, 2021, 11(3): 1–12. link1

[6]  Huang Q S, Wood T, Jelley L, et al. Impact of the COVID-19 nonpharmaceutical interventions on influenza and other respiratory viral infections in New Zealand [J]. Nature Communications, 2021,12(2): 1–7. link1

[7]  Suryanarayanan P, Tsou C H, Poddar A, et al. AI-assisted tracking of worldwide non-pharmaceutical interventions for COVID- 19 [J]. Scientific Data, 2021, 8(3): 1–14. link1

[8]  The State Council Information Office of the People’s Republic of China. Evaluation report on the implementation of the national human rights action plan (2012―2015) [EB/OL]. (2016-06-14)[2021-07-20]. http://www.gov.cn/xinwen/2016- 06/14/content_5082026.htm. Chinese. link1

[9]  Zhao Z X, Zhao J, Ma J Q. Conception of an integrated information system for notifiable disease communicable surveillance in China [J]. Disease Surveillance, 2018, 33(5): 423– 427. Chinese. link1

[10]  Wang Y, Xiang N J, Ni D X, et al. Performance of surveillance system of pneumonia with unknown etiology in two hospitals at municipal (prefecture) level in Anhui Province [J]. Disease Surveillance, 2017, 32(5): 428–432. Chinese. link1

[11]  Wang X Y. Global conspiracy for influenza prevention and control [N]. Health News, 2018-05-24(01). Chinese.

[12]  Shanghai Municipal Health Commission, Shanghai Municipal Development & Reform Commission, Shanghai Municipal Commission of Economy and Informatization, et al. Three years action plan for strengthening the construction of public health system in Shanghai (2020―2022) [EB/OL]. (2020-06-01)[2021-07-20]. https://www.shanghai.gov.cn/nw12344/20200813/0001-12344_65151.html. Chinese. link1

[13]  China Internet Network Information Center. The 47th China statistical report on Internet development [EB/OL]. (2021-02- 03) [2021-07-20]. http://www.cnnic.net.cn/hlwfzyj/hlwxzbg/hlwtjbg/202102/t20210203_71361.htm. Chinese. link1

[14]  Kermack W O, Mckendrick A G. A contribution to the mathematical theory of epidemics [J]. Proceedings of the Royal Society of London Series A, Containing Papers of A Mathematical and Physical Character, 1927, 115(772): 700–721. link1

[15]  Han H, Ma A N, Zhao X, et al. SIRS model with the long distance spread and emulation [J]. Journal of Wuhan University of Technology, 2010, 32(2): 141–145. Chinese. link1

[16]  Du Y F, Xiao P, Cao H. Dynamic behavior of a periodic seir epidemic model with stage-structure [J]. Journal of Sichuan Normal University (Natural Science), 2017, 40(1): 73–77. Chinese. link1

[17]  Hethcote H W. The mathematics of infectious diseases [J]. SIAM Review, 2000, 42(4): 599–653. link1

[18]  Castillo-Chavez C, Castillo-Garsow C W, Yakubu A A. Mathematical models of isolation and quarantine [J]. The Journal of American Medical Association, 2003, 290(21): 2876–2877. link1

[19]  Lucia1 U, Deisboeck T S, Grisolia1 G. Entropy-based pandemics forecasting [J]. Frontiers in Physics, 2020, 8: 1–7. link1

[20]  Roques L, Klein E K, Papax J, et al. Impact of lockdown on the epidemic dynamics of COVID-19 in France [J]. Frontiers in Medicine, 2020, 7: 1–7. link1

[21]  Della M M, Orlando D, Sannino F. Renormalisation group approach to pandemics: The COVID-19 case [J]. Frontiers in Physics, 2020, 8: 1–7. link1

[22]  Fisman D N, Hauck T S, Tuite A R, et al. An IDEA for short term outbreak projection: nearcasting using the basic reproduction number [J]. PLOS ONE, 2013, 8(12): 1–7. link1

[23]  Tuite A R, Fisman D N. The IDEA model: A single equation approach to the Ebola forecasting challenge [J]. Epidemics, 2018, 22: 71–77. link1

[24]  Hsieh Y. Richards model: A simple procedure for real-time prediction of outbreak severity [M]// Ma Z, Zhou Y, Wu J. Modeling and dynamics of infectious diseases, Singapore: World Scientific, 2009: 216–236. link1

[25]  Wang B G, Qu B, Guo H Q, et al. Study on mathematical model of infectious disease prediction [J]. Chinese Journal of Health Statistics, 2007, 24(5): 536–540. Chinese. link1

[26]  Moirano G, Richiardi L, Novara C, et al. approaches to daily monitoring of the SARS-CoV-2 outbreak in Northern Italy [J]. Frontiers in Public Health, 2020, 8: 1–7. link1

[27]  Brooks L C, Farrow D C, Hyun S, et al. Flexible modeling of epidemics with an empirical Bayes framework [J]. PLOS Computational Biology, 2015, 11: 1–51. link1

[28]  Yang Z, Zeng Z, Wang K, et al. Modified SEIR and AI prediction of the epidemics trend of COVID-19 in China under public health interventions [J]. Journal of Thoracic Disease, 2020, 12(3): 165–174.

[29]  Hu Z X, Ge Q Y, Li S D, et al. Forecasting and evaluating multiple interventions for COVID-19 worldwide [J]. Frontiers in Physics, 2020, 3: 1–10. link1

[30]  Utsunomiya Y T, Utsunomiya A, Torrecilha R, et al. Growth rate and acceleration analysis of the COVID-19 pandemic reveals the effect of public health measures in real time [J]. Frontiers in Medicine, 2020, 7: 1–10. link1

[31]  Tsallis C, Tirnakli U. Predicting COVID-19 peaks around the world [J]. Frontiers in Physics, 2020, 8: 1–6. link1

[32]  Buckee C, Noor A, Sattenspiel L. Thinking clearly about social aspects of infectious disease transmission [J]. Nature, 2021. 595(7866): 205–213. link1

[33]  Wang F Y, Zeng D J, Mao W J. Social computing: Its significance, development and research status [J]. e-Science Technology & Application, 2010, 1(2): 3–14. Chinese. link1

[34]  Minar N, Burkhart R, Langton C G, et al. The swarm simulation system: A toolkit for building multi-agent simulations [EB/OL]. (1996-06-21)[2021-07-21]. https://santafe.edu/research/results/working-papers/the-swarm-simulation-system-atoolkit-for-building. link1

[35]  Collier N. RePast: An extensible framework for agent simulation [J]. Natural Resources and Environmental Issues (NREI), 2001 (8): 17–21. link1

[36]  Tisue S, Wilensky U. NetLogo: A simple environment for modeling complexity [C]. Boston: The Fifth International Conference on Complex Systems, 2004: 1–9. link1

[37]  Yuan H Y, Liang M C, Huang Q Y, et al. Application of empirical data assimilation method in trend analysis of COVID-19 [J]. Science & Technology Review, 2020, 38(6): 83–89. Chinese. link1

[1]  Lai S, Ruktanonchai N W, Zhou L, et al. Effect of nonpharmaceutical interventions to contain COVID-19 in China [J]. Nature, 2020, 585(7825): 410–413. link1

[2]  Ruktanonchai N W, Floyd J R, Lai S, et al. Assessing the impact of coordinated COVID-19 exit strategies across Europe [J]. Science, 2020, 369(6510): 1465–1470. link1

[3]  Flaxman S, Mishra S, Gandy A, et al. Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe [J]. Nature, 2020, 584(7820): 257–261. link1

[4]  Davis E L, Lucas T C D, Borlase A, et al. Contact tracing is an imperfect tool for controlling COVID-19 transmission and relies on population adherence [J]. Nature Communications, 2021, 12(9): 1–8. link1

[5]  Moon S A, Scoglio C M. Contact tracing evaluation for COVID-19 transmission in the different movement levels of a rural college town in the USA [J]. Scientific Reports, 2021, 11(3): 1–12. link1

[6]  Huang Q S, Wood T, Jelley L, et al. Impact of the COVID-19 nonpharmaceutical interventions on influenza and other respiratory viral infections in New Zealand [J]. Nature Communications, 2021,12(2): 1–7. link1

[7]  Suryanarayanan P, Tsou C H, Poddar A, et al. AI-assisted tracking of worldwide non-pharmaceutical interventions for COVID- 19 [J]. Scientific Data, 2021, 8(3): 1–14. link1

[8]  The State Council Information Office of the People’s Republic of China. Evaluation report on the implementation of the national human rights action plan (2012―2015) [EB/OL]. (2016-06-14)[2021-07-20]. http://www.gov.cn/xinwen/2016- 06/14/content_5082026.htm. Chinese. link1

[9]  Zhao Z X, Zhao J, Ma J Q. Conception of an integrated information system for notifiable disease communicable surveillance in China [J]. Disease Surveillance, 2018, 33(5): 423– 427. Chinese. link1

[10]  Wang Y, Xiang N J, Ni D X, et al. Performance of surveillance system of pneumonia with unknown etiology in two hospitals at municipal (prefecture) level in Anhui Province [J]. Disease Surveillance, 2017, 32(5): 428–432. Chinese. link1

[11]  Wang X Y. Global conspiracy for influenza prevention and control [N]. Health News, 2018-05-24(01). Chinese.

[12]  Shanghai Municipal Health Commission, Shanghai Municipal Development & Reform Commission, Shanghai Municipal Commission of Economy and Informatization, et al. Three years action plan for strengthening the construction of public health system in Shanghai (2020―2022) [EB/OL]. (2020-06-01)[2021-07-20]. https://www.shanghai.gov.cn/nw12344/20200813/0001-12344_65151.html. Chinese. link1

[13]  China Internet Network Information Center. The 47th China statistical report on Internet development [EB/OL]. (2021-02- 03) [2021-07-20]. http://www.cnnic.net.cn/hlwfzyj/hlwxzbg/hlwtjbg/202102/t20210203_71361.htm. Chinese. link1

[14]  Kermack W O, Mckendrick A G. A contribution to the mathematical theory of epidemics [J]. Proceedings of the Royal Society of London Series A, Containing Papers of A Mathematical and Physical Character, 1927, 115(772): 700–721. link1

[15]  Han H, Ma A N, Zhao X, et al. SIRS model with the long distance spread and emulation [J]. Journal of Wuhan University of Technology, 2010, 32(2): 141–145. Chinese. link1

[16]  Du Y F, Xiao P, Cao H. Dynamic behavior of a periodic seir epidemic model with stage-structure [J]. Journal of Sichuan Normal University (Natural Science), 2017, 40(1): 73–77. Chinese. link1

[17]  Hethcote H W. The mathematics of infectious diseases [J]. SIAM Review, 2000, 42(4): 599–653. link1

[18]  Castillo-Chavez C, Castillo-Garsow C W, Yakubu A A. Mathematical models of isolation and quarantine [J]. The Journal of American Medical Association, 2003, 290(21): 2876–2877. link1

[19]  Lucia1 U, Deisboeck T S, Grisolia1 G. Entropy-based pandemics forecasting [J]. Frontiers in Physics, 2020, 8: 1–7. link1

[20]  Roques L, Klein E K, Papax J, et al. Impact of lockdown on the epidemic dynamics of COVID-19 in France [J]. Frontiers in Medicine, 2020, 7: 1–7. link1

[21]  Della M M, Orlando D, Sannino F. Renormalisation group approach to pandemics: The COVID-19 case [J]. Frontiers in Physics, 2020, 8: 1–7. link1

[22]  Fisman D N, Hauck T S, Tuite A R, et al. An IDEA for short term outbreak projection: nearcasting using the basic reproduction number [J]. PLOS ONE, 2013, 8(12): 1–7. link1

[23]  Tuite A R, Fisman D N. The IDEA model: A single equation approach to the Ebola forecasting challenge [J]. Epidemics, 2018, 22: 71–77. link1

[24]  Hsieh Y. Richards model: A simple procedure for real-time prediction of outbreak severity [M]// Ma Z, Zhou Y, Wu J. Modeling and dynamics of infectious diseases, Singapore: World Scientific, 2009: 216–236. link1

[25]  Wang B G, Qu B, Guo H Q, et al. Study on mathematical model of infectious disease prediction [J]. Chinese Journal of Health Statistics, 2007, 24(5): 536–540. Chinese. link1

[26]  Moirano G, Richiardi L, Novara C, et al. approaches to daily monitoring of the SARS-CoV-2 outbreak in Northern Italy [J]. Frontiers in Public Health, 2020, 8: 1–7. link1

[27]  Brooks L C, Farrow D C, Hyun S, et al. Flexible modeling of epidemics with an empirical Bayes framework [J]. PLOS Computational Biology, 2015, 11: 1–51. link1

[28]  Yang Z, Zeng Z, Wang K, et al. Modified SEIR and AI prediction of the epidemics trend of COVID-19 in China under public health interventions [J]. Journal of Thoracic Disease, 2020, 12(3): 165–174.

[29]  Hu Z X, Ge Q Y, Li S D, et al. Forecasting and evaluating multiple interventions for COVID-19 worldwide [J]. Frontiers in Physics, 2020, 3: 1–10. link1

[30]  Utsunomiya Y T, Utsunomiya A, Torrecilha R, et al. Growth rate and acceleration analysis of the COVID-19 pandemic reveals the effect of public health measures in real time [J]. Frontiers in Medicine, 2020, 7: 1–10. link1

[31]  Tsallis C, Tirnakli U. Predicting COVID-19 peaks around the world [J]. Frontiers in Physics, 2020, 8: 1–6. link1

[32]  Buckee C, Noor A, Sattenspiel L. Thinking clearly about social aspects of infectious disease transmission [J]. Nature, 2021. 595(7866): 205–213. link1

[33]  Wang F Y, Zeng D J, Mao W J. Social computing: Its significance, development and research status [J]. e-Science Technology & Application, 2010, 1(2): 3–14. Chinese. link1

[34]  Minar N, Burkhart R, Langton C G, et al. The swarm simulation system: A toolkit for building multi-agent simulations [EB/OL]. (1996-06-21)[2021-07-21]. https://santafe.edu/research/results/working-papers/the-swarm-simulation-system-atoolkit-for-building. link1

[35]  Collier N. RePast: An extensible framework for agent simulation [J]. Natural Resources and Environmental Issues (NREI), 2001 (8): 17–21. link1

[36]  Tisue S, Wilensky U. NetLogo: A simple environment for modeling complexity [C]. Boston: The Fifth International Conference on Complex Systems, 2004: 1–9. link1

[37]  Yuan H Y, Liang M C, Huang Q Y, et al. Application of empirical data assimilation method in trend analysis of COVID-19 [J]. Science & Technology Review, 2020, 38(6): 83–89. Chinese. link1

[1]  Lai S, Ruktanonchai N W, Zhou L, et al. Effect of nonpharmaceutical interventions to contain COVID-19 in China [J]. Nature, 2020, 585(7825): 410–413. link1

[2]  Ruktanonchai N W, Floyd J R, Lai S, et al. Assessing the impact of coordinated COVID-19 exit strategies across Europe [J]. Science, 2020, 369(6510): 1465–1470. link1

[3]  Flaxman S, Mishra S, Gandy A, et al. Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe [J]. Nature, 2020, 584(7820): 257–261. link1

[4]  Davis E L, Lucas T C D, Borlase A, et al. Contact tracing is an imperfect tool for controlling COVID-19 transmission and relies on population adherence [J]. Nature Communications, 2021, 12(9): 1–8. link1

[5]  Moon S A, Scoglio C M. Contact tracing evaluation for COVID-19 transmission in the different movement levels of a rural college town in the USA [J]. Scientific Reports, 2021, 11(3): 1–12. link1

[6]  Huang Q S, Wood T, Jelley L, et al. Impact of the COVID-19 nonpharmaceutical interventions on influenza and other respiratory viral infections in New Zealand [J]. Nature Communications, 2021,12(2): 1–7. link1

[7]  Suryanarayanan P, Tsou C H, Poddar A, et al. AI-assisted tracking of worldwide non-pharmaceutical interventions for COVID- 19 [J]. Scientific Data, 2021, 8(3): 1–14. link1

[8]  The State Council Information Office of the People’s Republic of China. Evaluation report on the implementation of the national human rights action plan (2012―2015) [EB/OL]. (2016-06-14)[2021-07-20]. http://www.gov.cn/xinwen/2016- 06/14/content_5082026.htm. Chinese. link1

[9]  Zhao Z X, Zhao J, Ma J Q. Conception of an integrated information system for notifiable disease communicable surveillance in China [J]. Disease Surveillance, 2018, 33(5): 423– 427. Chinese. link1

[10]  Wang Y, Xiang N J, Ni D X, et al. Performance of surveillance system of pneumonia with unknown etiology in two hospitals at municipal (prefecture) level in Anhui Province [J]. Disease Surveillance, 2017, 32(5): 428–432. Chinese. link1

[11]  Wang X Y. Global conspiracy for influenza prevention and control [N]. Health News, 2018-05-24(01). Chinese.

[12]  Shanghai Municipal Health Commission, Shanghai Municipal Development & Reform Commission, Shanghai Municipal Commission of Economy and Informatization, et al. Three years action plan for strengthening the construction of public health system in Shanghai (2020―2022) [EB/OL]. (2020-06-01)[2021-07-20]. https://www.shanghai.gov.cn/nw12344/20200813/0001-12344_65151.html. Chinese. link1

[13]  China Internet Network Information Center. The 47th China statistical report on Internet development [EB/OL]. (2021-02- 03) [2021-07-20]. http://www.cnnic.net.cn/hlwfzyj/hlwxzbg/hlwtjbg/202102/t20210203_71361.htm. Chinese. link1

[14]  Kermack W O, Mckendrick A G. A contribution to the mathematical theory of epidemics [J]. Proceedings of the Royal Society of London Series A, Containing Papers of A Mathematical and Physical Character, 1927, 115(772): 700–721. link1

[15]  Han H, Ma A N, Zhao X, et al. SIRS model with the long distance spread and emulation [J]. Journal of Wuhan University of Technology, 2010, 32(2): 141–145. Chinese. link1

[16]  Du Y F, Xiao P, Cao H. Dynamic behavior of a periodic seir epidemic model with stage-structure [J]. Journal of Sichuan Normal University (Natural Science), 2017, 40(1): 73–77. Chinese. link1

[17]  Hethcote H W. The mathematics of infectious diseases [J]. SIAM Review, 2000, 42(4): 599–653. link1

[18]  Castillo-Chavez C, Castillo-Garsow C W, Yakubu A A. Mathematical models of isolation and quarantine [J]. The Journal of American Medical Association, 2003, 290(21): 2876–2877. link1

[19]  Lucia1 U, Deisboeck T S, Grisolia1 G. Entropy-based pandemics forecasting [J]. Frontiers in Physics, 2020, 8: 1–7. link1

[20]  Roques L, Klein E K, Papax J, et al. Impact of lockdown on the epidemic dynamics of COVID-19 in France [J]. Frontiers in Medicine, 2020, 7: 1–7. link1

[21]  Della M M, Orlando D, Sannino F. Renormalisation group approach to pandemics: The COVID-19 case [J]. Frontiers in Physics, 2020, 8: 1–7. link1

[22]  Fisman D N, Hauck T S, Tuite A R, et al. An IDEA for short term outbreak projection: nearcasting using the basic reproduction number [J]. PLOS ONE, 2013, 8(12): 1–7. link1

[23]  Tuite A R, Fisman D N. The IDEA model: A single equation approach to the Ebola forecasting challenge [J]. Epidemics, 2018, 22: 71–77. link1

[24]  Hsieh Y. Richards model: A simple procedure for real-time prediction of outbreak severity [M]// Ma Z, Zhou Y, Wu J. Modeling and dynamics of infectious diseases, Singapore: World Scientific, 2009: 216–236. link1

[25]  Wang B G, Qu B, Guo H Q, et al. Study on mathematical model of infectious disease prediction [J]. Chinese Journal of Health Statistics, 2007, 24(5): 536–540. Chinese. link1

[26]  Moirano G, Richiardi L, Novara C, et al. approaches to daily monitoring of the SARS-CoV-2 outbreak in Northern Italy [J]. Frontiers in Public Health, 2020, 8: 1–7. link1

[27]  Brooks L C, Farrow D C, Hyun S, et al. Flexible modeling of epidemics with an empirical Bayes framework [J]. PLOS Computational Biology, 2015, 11: 1–51. link1

[28]  Yang Z, Zeng Z, Wang K, et al. Modified SEIR and AI prediction of the epidemics trend of COVID-19 in China under public health interventions [J]. Journal of Thoracic Disease, 2020, 12(3): 165–174.

[29]  Hu Z X, Ge Q Y, Li S D, et al. Forecasting and evaluating multiple interventions for COVID-19 worldwide [J]. Frontiers in Physics, 2020, 3: 1–10. link1

[30]  Utsunomiya Y T, Utsunomiya A, Torrecilha R, et al. Growth rate and acceleration analysis of the COVID-19 pandemic reveals the effect of public health measures in real time [J]. Frontiers in Medicine, 2020, 7: 1–10. link1

[31]  Tsallis C, Tirnakli U. Predicting COVID-19 peaks around the world [J]. Frontiers in Physics, 2020, 8: 1–6. link1

[32]  Buckee C, Noor A, Sattenspiel L. Thinking clearly about social aspects of infectious disease transmission [J]. Nature, 2021. 595(7866): 205–213. link1

[33]  Wang F Y, Zeng D J, Mao W J. Social computing: Its significance, development and research status [J]. e-Science Technology & Application, 2010, 1(2): 3–14. Chinese. link1

[34]  Minar N, Burkhart R, Langton C G, et al. The swarm simulation system: A toolkit for building multi-agent simulations [EB/OL]. (1996-06-21)[2021-07-21]. https://santafe.edu/research/results/working-papers/the-swarm-simulation-system-atoolkit-for-building. link1

[35]  Collier N. RePast: An extensible framework for agent simulation [J]. Natural Resources and Environmental Issues (NREI), 2001 (8): 17–21. link1

[36]  Tisue S, Wilensky U. NetLogo: A simple environment for modeling complexity [C]. Boston: The Fifth International Conference on Complex Systems, 2004: 1–9. link1

[37]  Yuan H Y, Liang M C, Huang Q Y, et al. Application of empirical data assimilation method in trend analysis of COVID-19 [J]. Science & Technology Review, 2020, 38(6): 83–89. Chinese. link1

[1]  Lai S, Ruktanonchai N W, Zhou L, et al. Effect of nonpharmaceutical interventions to contain COVID-19 in China [J]. Nature, 2020, 585(7825): 410–413. link1

[2]  Ruktanonchai N W, Floyd J R, Lai S, et al. Assessing the impact of coordinated COVID-19 exit strategies across Europe [J]. Science, 2020, 369(6510): 1465–1470. link1

[3]  Flaxman S, Mishra S, Gandy A, et al. Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe [J]. Nature, 2020, 584(7820): 257–261. link1

[4]  Davis E L, Lucas T C D, Borlase A, et al. Contact tracing is an imperfect tool for controlling COVID-19 transmission and relies on population adherence [J]. Nature Communications, 2021, 12(9): 1–8. link1

[5]  Moon S A, Scoglio C M. Contact tracing evaluation for COVID-19 transmission in the different movement levels of a rural college town in the USA [J]. Scientific Reports, 2021, 11(3): 1–12. link1

[6]  Huang Q S, Wood T, Jelley L, et al. Impact of the COVID-19 nonpharmaceutical interventions on influenza and other respiratory viral infections in New Zealand [J]. Nature Communications, 2021,12(2): 1–7. link1

[7]  Suryanarayanan P, Tsou C H, Poddar A, et al. AI-assisted tracking of worldwide non-pharmaceutical interventions for COVID- 19 [J]. Scientific Data, 2021, 8(3): 1–14. link1

[8]  The State Council Information Office of the People’s Republic of China. Evaluation report on the implementation of the national human rights action plan (2012―2015) [EB/OL]. (2016-06-14)[2021-07-20]. http://www.gov.cn/xinwen/2016- 06/14/content_5082026.htm. Chinese. link1

[9]  Zhao Z X, Zhao J, Ma J Q. Conception of an integrated information system for notifiable disease communicable surveillance in China [J]. Disease Surveillance, 2018, 33(5): 423– 427. Chinese. link1

[10]  Wang Y, Xiang N J, Ni D X, et al. Performance of surveillance system of pneumonia with unknown etiology in two hospitals at municipal (prefecture) level in Anhui Province [J]. Disease Surveillance, 2017, 32(5): 428–432. Chinese. link1

[11]  Wang X Y. Global conspiracy for influenza prevention and control [N]. Health News, 2018-05-24(01). Chinese.

[12]  Shanghai Municipal Health Commission, Shanghai Municipal Development & Reform Commission, Shanghai Municipal Commission of Economy and Informatization, et al. Three years action plan for strengthening the construction of public health system in Shanghai (2020―2022) [EB/OL]. (2020-06-01)[2021-07-20]. https://www.shanghai.gov.cn/nw12344/20200813/0001-12344_65151.html. Chinese. link1

[13]  China Internet Network Information Center. The 47th China statistical report on Internet development [EB/OL]. (2021-02- 03) [2021-07-20]. http://www.cnnic.net.cn/hlwfzyj/hlwxzbg/hlwtjbg/202102/t20210203_71361.htm. Chinese. link1

[14]  Kermack W O, Mckendrick A G. A contribution to the mathematical theory of epidemics [J]. Proceedings of the Royal Society of London Series A, Containing Papers of A Mathematical and Physical Character, 1927, 115(772): 700–721. link1

[15]  Han H, Ma A N, Zhao X, et al. SIRS model with the long distance spread and emulation [J]. Journal of Wuhan University of Technology, 2010, 32(2): 141–145. Chinese. link1

[16]  Du Y F, Xiao P, Cao H. Dynamic behavior of a periodic seir epidemic model with stage-structure [J]. Journal of Sichuan Normal University (Natural Science), 2017, 40(1): 73–77. Chinese. link1

[17]  Hethcote H W. The mathematics of infectious diseases [J]. SIAM Review, 2000, 42(4): 599–653. link1

[18]  Castillo-Chavez C, Castillo-Garsow C W, Yakubu A A. Mathematical models of isolation and quarantine [J]. The Journal of American Medical Association, 2003, 290(21): 2876–2877. link1

[19]  Lucia1 U, Deisboeck T S, Grisolia1 G. Entropy-based pandemics forecasting [J]. Frontiers in Physics, 2020, 8: 1–7. link1

[20]  Roques L, Klein E K, Papax J, et al. Impact of lockdown on the epidemic dynamics of COVID-19 in France [J]. Frontiers in Medicine, 2020, 7: 1–7. link1

[21]  Della M M, Orlando D, Sannino F. Renormalisation group approach to pandemics: The COVID-19 case [J]. Frontiers in Physics, 2020, 8: 1–7. link1

[22]  Fisman D N, Hauck T S, Tuite A R, et al. An IDEA for short term outbreak projection: nearcasting using the basic reproduction number [J]. PLOS ONE, 2013, 8(12): 1–7. link1

[23]  Tuite A R, Fisman D N. The IDEA model: A single equation approach to the Ebola forecasting challenge [J]. Epidemics, 2018, 22: 71–77. link1

[24]  Hsieh Y. Richards model: A simple procedure for real-time prediction of outbreak severity [M]// Ma Z, Zhou Y, Wu J. Modeling and dynamics of infectious diseases, Singapore: World Scientific, 2009: 216–236. link1

[25]  Wang B G, Qu B, Guo H Q, et al. Study on mathematical model of infectious disease prediction [J]. Chinese Journal of Health Statistics, 2007, 24(5): 536–540. Chinese. link1

[26]  Moirano G, Richiardi L, Novara C, et al. approaches to daily monitoring of the SARS-CoV-2 outbreak in Northern Italy [J]. Frontiers in Public Health, 2020, 8: 1–7. link1

[27]  Brooks L C, Farrow D C, Hyun S, et al. Flexible modeling of epidemics with an empirical Bayes framework [J]. PLOS Computational Biology, 2015, 11: 1–51. link1

[28]  Yang Z, Zeng Z, Wang K, et al. Modified SEIR and AI prediction of the epidemics trend of COVID-19 in China under public health interventions [J]. Journal of Thoracic Disease, 2020, 12(3): 165–174.

[29]  Hu Z X, Ge Q Y, Li S D, et al. Forecasting and evaluating multiple interventions for COVID-19 worldwide [J]. Frontiers in Physics, 2020, 3: 1–10. link1

[30]  Utsunomiya Y T, Utsunomiya A, Torrecilha R, et al. Growth rate and acceleration analysis of the COVID-19 pandemic reveals the effect of public health measures in real time [J]. Frontiers in Medicine, 2020, 7: 1–10. link1

[31]  Tsallis C, Tirnakli U. Predicting COVID-19 peaks around the world [J]. Frontiers in Physics, 2020, 8: 1–6. link1

[32]  Buckee C, Noor A, Sattenspiel L. Thinking clearly about social aspects of infectious disease transmission [J]. Nature, 2021. 595(7866): 205–213. link1

[33]  Wang F Y, Zeng D J, Mao W J. Social computing: Its significance, development and research status [J]. e-Science Technology & Application, 2010, 1(2): 3–14. Chinese. link1

[34]  Minar N, Burkhart R, Langton C G, et al. The swarm simulation system: A toolkit for building multi-agent simulations [EB/OL]. (1996-06-21)[2021-07-21]. https://santafe.edu/research/results/working-papers/the-swarm-simulation-system-atoolkit-for-building. link1

[35]  Collier N. RePast: An extensible framework for agent simulation [J]. Natural Resources and Environmental Issues (NREI), 2001 (8): 17–21. link1

[36]  Tisue S, Wilensky U. NetLogo: A simple environment for modeling complexity [C]. Boston: The Fifth International Conference on Complex Systems, 2004: 1–9. link1

[37]  Yuan H Y, Liang M C, Huang Q Y, et al. Application of empirical data assimilation method in trend analysis of COVID-19 [J]. Science & Technology Review, 2020, 38(6): 83–89. Chinese. link1

[1]  Lai S, Ruktanonchai N W, Zhou L, et al. Effect of nonpharmaceutical interventions to contain COVID-19 in China [J]. Nature, 2020, 585(7825): 410–413. link1

[2]  Ruktanonchai N W, Floyd J R, Lai S, et al. Assessing the impact of coordinated COVID-19 exit strategies across Europe [J]. Science, 2020, 369(6510): 1465–1470. link1

[3]  Flaxman S, Mishra S, Gandy A, et al. Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe [J]. Nature, 2020, 584(7820): 257–261. link1

[4]  Davis E L, Lucas T C D, Borlase A, et al. Contact tracing is an imperfect tool for controlling COVID-19 transmission and relies on population adherence [J]. Nature Communications, 2021, 12(9): 1–8. link1

[5]  Moon S A, Scoglio C M. Contact tracing evaluation for COVID-19 transmission in the different movement levels of a rural college town in the USA [J]. Scientific Reports, 2021, 11(3): 1–12. link1

[6]  Huang Q S, Wood T, Jelley L, et al. Impact of the COVID-19 nonpharmaceutical interventions on influenza and other respiratory viral infections in New Zealand [J]. Nature Communications, 2021,12(2): 1–7. link1

[7]  Suryanarayanan P, Tsou C H, Poddar A, et al. AI-assisted tracking of worldwide non-pharmaceutical interventions for COVID- 19 [J]. Scientific Data, 2021, 8(3): 1–14. link1

[8]  The State Council Information Office of the People’s Republic of China. Evaluation report on the implementation of the national human rights action plan (2012―2015) [EB/OL]. (2016-06-14)[2021-07-20]. http://www.gov.cn/xinwen/2016- 06/14/content_5082026.htm. Chinese. link1

[9]  Zhao Z X, Zhao J, Ma J Q. Conception of an integrated information system for notifiable disease communicable surveillance in China [J]. Disease Surveillance, 2018, 33(5): 423– 427. Chinese. link1

[10]  Wang Y, Xiang N J, Ni D X, et al. Performance of surveillance system of pneumonia with unknown etiology in two hospitals at municipal (prefecture) level in Anhui Province [J]. Disease Surveillance, 2017, 32(5): 428–432. Chinese. link1

[11]  Wang X Y. Global conspiracy for influenza prevention and control [N]. Health News, 2018-05-24(01). Chinese.

[12]  Shanghai Municipal Health Commission, Shanghai Municipal Development & Reform Commission, Shanghai Municipal Commission of Economy and Informatization, et al. Three years action plan for strengthening the construction of public health system in Shanghai (2020―2022) [EB/OL]. (2020-06-01)[2021-07-20]. https://www.shanghai.gov.cn/nw12344/20200813/0001-12344_65151.html. Chinese. link1

[13]  China Internet Network Information Center. The 47th China statistical report on Internet development [EB/OL]. (2021-02- 03) [2021-07-20]. http://www.cnnic.net.cn/hlwfzyj/hlwxzbg/hlwtjbg/202102/t20210203_71361.htm. Chinese. link1

[14]  Kermack W O, Mckendrick A G. A contribution to the mathematical theory of epidemics [J]. Proceedings of the Royal Society of London Series A, Containing Papers of A Mathematical and Physical Character, 1927, 115(772): 700–721. link1

[15]  Han H, Ma A N, Zhao X, et al. SIRS model with the long distance spread and emulation [J]. Journal of Wuhan University of Technology, 2010, 32(2): 141–145. Chinese. link1

[16]  Du Y F, Xiao P, Cao H. Dynamic behavior of a periodic seir epidemic model with stage-structure [J]. Journal of Sichuan Normal University (Natural Science), 2017, 40(1): 73–77. Chinese. link1

[17]  Hethcote H W. The mathematics of infectious diseases [J]. SIAM Review, 2000, 42(4): 599–653. link1

[18]  Castillo-Chavez C, Castillo-Garsow C W, Yakubu A A. Mathematical models of isolation and quarantine [J]. The Journal of American Medical Association, 2003, 290(21): 2876–2877. link1

[19]  Lucia1 U, Deisboeck T S, Grisolia1 G. Entropy-based pandemics forecasting [J]. Frontiers in Physics, 2020, 8: 1–7. link1

[20]  Roques L, Klein E K, Papax J, et al. Impact of lockdown on the epidemic dynamics of COVID-19 in France [J]. Frontiers in Medicine, 2020, 7: 1–7. link1

[21]  Della M M, Orlando D, Sannino F. Renormalisation group approach to pandemics: The COVID-19 case [J]. Frontiers in Physics, 2020, 8: 1–7. link1

[22]  Fisman D N, Hauck T S, Tuite A R, et al. An IDEA for short term outbreak projection: nearcasting using the basic reproduction number [J]. PLOS ONE, 2013, 8(12): 1–7. link1

[23]  Tuite A R, Fisman D N. The IDEA model: A single equation approach to the Ebola forecasting challenge [J]. Epidemics, 2018, 22: 71–77. link1

[24]  Hsieh Y. Richards model: A simple procedure for real-time prediction of outbreak severity [M]// Ma Z, Zhou Y, Wu J. Modeling and dynamics of infectious diseases, Singapore: World Scientific, 2009: 216–236. link1

[25]  Wang B G, Qu B, Guo H Q, et al. Study on mathematical model of infectious disease prediction [J]. Chinese Journal of Health Statistics, 2007, 24(5): 536–540. Chinese. link1

[26]  Moirano G, Richiardi L, Novara C, et al. approaches to daily monitoring of the SARS-CoV-2 outbreak in Northern Italy [J]. Frontiers in Public Health, 2020, 8: 1–7. link1

[27]  Brooks L C, Farrow D C, Hyun S, et al. Flexible modeling of epidemics with an empirical Bayes framework [J]. PLOS Computational Biology, 2015, 11: 1–51. link1

[28]  Yang Z, Zeng Z, Wang K, et al. Modified SEIR and AI prediction of the epidemics trend of COVID-19 in China under public health interventions [J]. Journal of Thoracic Disease, 2020, 12(3): 165–174.

[29]  Hu Z X, Ge Q Y, Li S D, et al. Forecasting and evaluating multiple interventions for COVID-19 worldwide [J]. Frontiers in Physics, 2020, 3: 1–10. link1

[30]  Utsunomiya Y T, Utsunomiya A, Torrecilha R, et al. Growth rate and acceleration analysis of the COVID-19 pandemic reveals the effect of public health measures in real time [J]. Frontiers in Medicine, 2020, 7: 1–10. link1

[31]  Tsallis C, Tirnakli U. Predicting COVID-19 peaks around the world [J]. Frontiers in Physics, 2020, 8: 1–6. link1

[32]  Buckee C, Noor A, Sattenspiel L. Thinking clearly about social aspects of infectious disease transmission [J]. Nature, 2021. 595(7866): 205–213. link1

[33]  Wang F Y, Zeng D J, Mao W J. Social computing: Its significance, development and research status [J]. e-Science Technology & Application, 2010, 1(2): 3–14. Chinese. link1

[34]  Minar N, Burkhart R, Langton C G, et al. The swarm simulation system: A toolkit for building multi-agent simulations [EB/OL]. (1996-06-21)[2021-07-21]. https://santafe.edu/research/results/working-papers/the-swarm-simulation-system-atoolkit-for-building. link1

[35]  Collier N. RePast: An extensible framework for agent simulation [J]. Natural Resources and Environmental Issues (NREI), 2001 (8): 17–21. link1

[36]  Tisue S, Wilensky U. NetLogo: A simple environment for modeling complexity [C]. Boston: The Fifth International Conference on Complex Systems, 2004: 1–9. link1

[37]  Yuan H Y, Liang M C, Huang Q Y, et al. Application of empirical data assimilation method in trend analysis of COVID-19 [J]. Science & Technology Review, 2020, 38(6): 83–89. Chinese. link1

[1]  Lai S, Ruktanonchai N W, Zhou L, et al. Effect of nonpharmaceutical interventions to contain COVID-19 in China [J]. Nature, 2020, 585(7825): 410–413. link1

[2]  Ruktanonchai N W, Floyd J R, Lai S, et al. Assessing the impact of coordinated COVID-19 exit strategies across Europe [J]. Science, 2020, 369(6510): 1465–1470. link1

[3]  Flaxman S, Mishra S, Gandy A, et al. Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe [J]. Nature, 2020, 584(7820): 257–261. link1

[4]  Davis E L, Lucas T C D, Borlase A, et al. Contact tracing is an imperfect tool for controlling COVID-19 transmission and relies on population adherence [J]. Nature Communications, 2021, 12(9): 1–8. link1

[5]  Moon S A, Scoglio C M. Contact tracing evaluation for COVID-19 transmission in the different movement levels of a rural college town in the USA [J]. Scientific Reports, 2021, 11(3): 1–12. link1

[6]  Huang Q S, Wood T, Jelley L, et al. Impact of the COVID-19 nonpharmaceutical interventions on influenza and other respiratory viral infections in New Zealand [J]. Nature Communications, 2021,12(2): 1–7. link1

[7]  Suryanarayanan P, Tsou C H, Poddar A, et al. AI-assisted tracking of worldwide non-pharmaceutical interventions for COVID- 19 [J]. Scientific Data, 2021, 8(3): 1–14. link1

[8]  The State Council Information Office of the People’s Republic of China. Evaluation report on the implementation of the national human rights action plan (2012―2015) [EB/OL]. (2016-06-14)[2021-07-20]. http://www.gov.cn/xinwen/2016- 06/14/content_5082026.htm. Chinese. link1

[9]  Zhao Z X, Zhao J, Ma J Q. Conception of an integrated information system for notifiable disease communicable surveillance in China [J]. Disease Surveillance, 2018, 33(5): 423– 427. Chinese. link1

[10]  Wang Y, Xiang N J, Ni D X, et al. Performance of surveillance system of pneumonia with unknown etiology in two hospitals at municipal (prefecture) level in Anhui Province [J]. Disease Surveillance, 2017, 32(5): 428–432. Chinese. link1

[11]  Wang X Y. Global conspiracy for influenza prevention and control [N]. Health News, 2018-05-24(01). Chinese.

[12]  Shanghai Municipal Health Commission, Shanghai Municipal Development & Reform Commission, Shanghai Municipal Commission of Economy and Informatization, et al. Three years action plan for strengthening the construction of public health system in Shanghai (2020―2022) [EB/OL]. (2020-06-01)[2021-07-20]. https://www.shanghai.gov.cn/nw12344/20200813/0001-12344_65151.html. Chinese. link1

[13]  China Internet Network Information Center. The 47th China statistical report on Internet development [EB/OL]. (2021-02- 03) [2021-07-20]. http://www.cnnic.net.cn/hlwfzyj/hlwxzbg/hlwtjbg/202102/t20210203_71361.htm. Chinese. link1

[14]  Kermack W O, Mckendrick A G. A contribution to the mathematical theory of epidemics [J]. Proceedings of the Royal Society of London Series A, Containing Papers of A Mathematical and Physical Character, 1927, 115(772): 700–721. link1

[15]  Han H, Ma A N, Zhao X, et al. SIRS model with the long distance spread and emulation [J]. Journal of Wuhan University of Technology, 2010, 32(2): 141–145. Chinese. link1

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