Isolating the net effect of multiple government interventions with an extended Susceptible-Exposed-Infectious-Recovered (SEIR) framework: empirical evidence from the second wave of COVID-19 pandemic in China

Abstract

Objective: By using a data-driven statistical approach, we isolated the net effect of multiple government interventions that were simultaneously implemented during the second wave of COVID-19 pandemic in China.

Design, data sources and eligibility criteria: We gathered epidemiological data and government interventions data of nine cities with local outbreaks during the second wave of COVID-19 pandemic in China. We employed the Susceptible-Exposed-Infectious-Recovered (SEIR) framework model to analyse the different pathways of transmission between cities with government interventions implementation and those without. We introduced new components to the standard SEIR model and investigated five themes of government interventions against COVID-19 pandemic.

Data extraction and synthesis: We extracted information including study objective, design, methods, main findings and implications. These were tabulated and a narrative synthesis was undertaken given the diverse research designs, methods and implications.

Results: Supported by extensive empirical validation, our results indicated that the net effect of some specific government interventions (including masks, environmental cleaning and disinfection, tracing, tracking and 14-day centralised quarantining close contacts) had been significantly underestimated in the previous investigation. We also identified important moderators and mediators for the effect of certain government interventions, such as closure of shopping mall and restaurant in the medium-risk level areas, etc. Linking the COVID-19 epidemiological dynamics with the implementation timing of government interventions, we detected that the earlier implementation of some specific government interventions (including targeted partial lockdown, tracing, tracking and 14-day centralised quarantining close contacts) achieved the strongest and most timely effect on controlling COVID-19, especially at the early period of local outbreak.

Conclusions: These findings provide important scientific information for decisions regarding which and when government interventions should be implemented to fight against COVID-19 in China and beyond. The proposed analytical framework is useful for policy-making in future endemic and pandemic as well.

Keywords: COVID-19; epidemiology; health policy; public health.

Figure 1

The cumulative number of confirmed cases (per 10 million population) in top 10 countries and China from 11 October 2020 to 4 February 2021.

Figure 2

The distribution of medium-risk level areas in nine cities from 11 October 2020 to 4 February 2021.

Figure 3

The cumulative number of confirmed cases (per 10 million population) in nine cities from 11 October 2020 to 4 February 2021.

Figure 4

The cumulative number of asymptomatic cases (per 10 million population) in nine cities from 11 October 2020 to 4 February 2021.

Figure 5

The implementation timing of government interventions in nine cities from 11 October 2020 to 4 February 2021.

Figure 6

Schematic of the Susceptible-Exposed-Infectious-Recovered framework model for linking government interventions implementation, in which transmission pathways are distinguished between (pathway 1) without government interventions implementation and (pathway 2) within government interventions implementation.

Figure 7

The distribution of COVID-19-infected sources in nine cities from 11 October 2020 to 4 February 2021.

Figure 8

Estimated growth rates of cumulative number of reported cases (per 10 million population) in nine cities, assuming a 5% increased reported cases due to different location-specific transmission, separably.

Figure 9

The distribution of case identification in nine cities from 11 October 2020 to 4 February 2021.

Figure 10

The distribution of quarantine ratio in nine cities from 11 October 2020 to 4 February 2021.