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Role of Asymptomatic COVID-19 Cases in Viral Transmission: Findings From a Hierarchical Community Contact Network Model.
Luo, Tianyi; Cao, Zhidong; Wang, Yuejiao; Zeng, Daniel; Zhang, Qingpeng.
  • Luo T; State Key Laboratory of Management and Control for Complex SystemsInstitute of Automation, Chinese Academy of Sciences Beijing 100190 China.
  • Cao Z; School of Artificial IntelligenceUniversity of Chinese Academy of Sciences Beijing 100049 China.
  • Wang Y; State Key Laboratory of Management and Control for Complex SystemsInstitute of Automation, Chinese Academy of Sciences Beijing 100190 China.
  • Zeng D; State Key Laboratory of Management and Control for Complex SystemsInstitute of Automation, Chinese Academy of Sciences Beijing 100190 China.
  • Zhang Q; School of Artificial IntelligenceUniversity of Chinese Academy of Sciences Beijing 100049 China.
IEEE Trans Autom Sci Eng ; 19(2): 576-585, 2022 Apr.
Article in English | MEDLINE | ID: covidwho-1416229
ABSTRACT
As part of ongoing efforts to contain the coronavirus disease (COVID-19) pandemic, understanding the role of asymptomatic patients in the transmission system is essential for infection control. However, the optimal approach to risk assessment and management of asymptomatic cases remains unclear. This study proposed a Susceptible, Exposed, Infectious, No symptoms, Hospitalized and reported, Recovered, Death (SEINRHD) epidemic propagation model. The model was constructed based on epidemiological characteristics of COVID-19 in China and accounting for the heterogeneity of social contact networks. The early community outbreaks in Wuhan were reconstructed and fitted with the actual data. We used this model to assess epidemic control measures for asymptomatic cases in three dimensions. The impact of asymptomatic cases on epidemic propagation was examined based on the effective reproduction number, abnormally high transmission events, and type and structure of transmission. Management of asymptomatic cases can help flatten the infection curve. Tracing 75% of the asymptomatic cases corresponds to a 32.5% overall reduction in new cases (compared with tracing no asymptomatic cases). Regardless of population-wide measures, household transmission is higher than other types of transmission, accounting for an estimated 50% of all cases. The magnitude of tracing of asymptomatic cases is more important than the timing; when all symptomatic patients were traced, tested, and isolated in a timely manner, the overall epidemic was not sensitive to the time of implementing the measures to trace asymptomatic patients. Disease control and prevention within families should be emphasized during an epidemic. Note to Practitioners-This article addresses the urgent need to assess the risk of another COVID-19 outbreak caused by asymptomatic cases and to find the optimal, most practical approach to asymptomatic case management. Previous studies mostly focused on the clinical and statistical characteristics of asymptomatic cases; few have evaluated the impact of asymptomatic case measures using mathematical modeling at the community scale. This study proposed a Susceptible, Exposed, Infectious, No symptoms, Hospitalized and reported, Recovered, Death (SEINRHD) propagation model based on local community structures and social contact networks, according to the development characteristics and trend of COVID-19 in a Chinese community. The conclusion provides theoretical support for emergency work of relevant departments in different periods of an epidemic. In the early stages of the epidemic, timely detection and isolation of symptomatic patients should be a priority. Where there are surplus resources for epidemic prevention, the authorities should consider increasing the proportion of asymptomatic patients being traced. Epidemic prevention measures among family members should be a primary focus of attention. This combination of strategies can help reduce the rate of viral transmission and result in extinguishing the epidemic.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Diagnostic study / Experimental Studies / Observational study / Prognostic study Language: English Journal: IEEE Trans Autom Sci Eng Year: 2022 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Diagnostic study / Experimental Studies / Observational study / Prognostic study Language: English Journal: IEEE Trans Autom Sci Eng Year: 2022 Document Type: Article