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Dynamic model of COVID-19 transmission and assessment of control interventions based on causal analysis
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Science & Technology Review | 2020, 38(6) : 90 - 96
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Science & Technology Review | 2020, 38(6): 90-96
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Dynamic model of COVID-19 transmission and assessment of control interventions based on causal analysis
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YOU Guangrong1, YOU Hanlin1, ZHAO Dezhi2, LIAN Zhenyu1
Affiliations
    1. Center for Assessment and Demonstration Research, Academy of Military Science, Beijing 100091, China;
    2. School of Graduate, Academy of Military Science, Beijing 100091, China
Published: 2020-03-28 doi: 10.3981/j.issn.1000-7857.2020.06.013
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A modified SEIR model of single-population infectious disease (SEIRD) is proposed to investigate the transmission trend of coronavirus disease 2019 (COVID-19) in Chinese Mainland, whose outbreak originated in Wuhan, Hubei Province. The SEIRD model preforms well in fitting training data and can be used to predict the future transmission trend. The counterfactual inference is applied to assess the control interventions based on SEIRD model. Using the quantitative analysis results, the effect on COVID-19 transmission can be assessed systematically under the adjustable control interventions, such as delaying the Wuhan Lockdown. Finally, the conclusions are summarized:the assessment approach combining modeling & simulation and causal inference is applicable in the bidirectional deduction study of decision-making and implementation in major public health emergencies (MPHE), which contributes to improve the social governance capabilities handling with MPHE of the governments in each level.
COVID-19  /  SEIR models  /  causal analysis  /  counterfactual inference
YOU Guangrong, YOU Hanlin, ZHAO Dezhi, LIAN Zhenyu. Dynamic model of COVID-19 transmission and assessment of control interventions based on causal analysis[J]. Science & Technology Review, 2020 , 38 (6) : 90 -96 . DOI: 10.3981/j.issn.1000-7857.2020.06.013
Year 2020 volume 38 Issue 6
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doi: 10.3981/j.issn.1000-7857.2020.06.013
  • Receive Date:2020-03-18
  • Online Date:2020-05-11
  • Published:2020-03-28
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  • Received:2020-03-18
  • Revised:2020-03-26
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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