Cost-Effectiveness of Public Health Measures to Control COVID-19 in China: A Microsimulation Modeling Study
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Abstract
This study aimed to assess the cost-effectiveness of various public health measures in dealing with coronavirus disease 2019 (COVID-19) in China. A stochastic agent-based model was used to simulate the progress of the COVID-19 outbreak in scenario I (imported one case) and scenario II (imported four cases) with a series of public health measures. The main outcomes included the avoided infections and incremental cost-effectiveness ratios (ICERs). Sensitivity analyses were performed to assess uncertainty. The results indicated that isolation-and-quarantine averted the COVID-19 outbreak at the lowest ICERs. The joint strategy of personal protection and isolation-and-quarantine averted one more case than only isolation-and-quarantine with additional costs. The effectiveness of isolation-and-quarantine decreased with lowering quarantine probability and increasing delay time. The strategy that included community containment would be cost-effective when the number of imported cases was >65, or the delay time of the quarantine was more than 5 days, or the quarantine probability was below 25%, based on current assumptions. In conclusion, isolation-and-quarantine was the most cost-effective intervention. However, personal protection combined with isolation-and-quarantine was the optimal strategy for averting more cases. The community containment could be more cost-effective as the efficiency of isolation-and-quarantine drops and the imported cases increases.
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SciScore for 10.1101/2020.03.20.20039644: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:There were some limitations in the study. First, COVID-19 was recently emerged disease first reported in Wuhan, China, therefore the availability of epidemiological data is insufficient. We set the study parameters referring to the existing published epidemiological studies and adopted the Gamma distribution to some of the parameters, …
SciScore for 10.1101/2020.03.20.20039644: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:There were some limitations in the study. First, COVID-19 was recently emerged disease first reported in Wuhan, China, therefore the availability of epidemiological data is insufficient. We set the study parameters referring to the existing published epidemiological studies and adopted the Gamma distribution to some of the parameters, which could improve the precision of estimate. Second, the cost of societal interventions was difficult to estimate. In our study, human capital approach was borrowed which might more conservatively estimate the cost. The cost of the disease would also increase, if according to the actual situation in Wuhan, China. Third, our model simulated a local area with 2000 humans, which may result in limited extrapolation ability. Finally, the simplification of the model will have some biases compared with the real situation, because the flow of people will be affected by many factors.
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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