Modelling the impact of control measures against the COVID-19 pandemic in Viet Nam
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Abstract
Objectives
Health care system of many countries are facing a surging burden of COVID-19. Although Vietnam has successfully controlled the COVID-19 pandemic to date, there is a sign of initial community transmission. An estimate of possible scenarios to prepare health resources in the future is needed. We used modelling methods to estimate impacts of mitigation measures on the COVID-19 pandemic in Vietnam.
Methods
SEIR model built in the COVIDSIM1.1 tool was adopted using available data for estimation. The herd immunization scenario was with no intervention implemented. Other scenarios consisted of isolation and social distancing at different levels (25%, 50%, 75% and 10%, 20%, 30%, respectively). Outcomes include epidemic apex, daily new and cumulative cases, deaths, hospitalized patients and ICU beds needed.
Results
By April 8, 2020, there would be 465 infected cases with COVID-19 in Viet Nam, of those 50% were detected. Cumulatively, there would be 1,400 cases and 30 deaths by end of 2020, if 75% of cases was detected and isolated, and 30% of social distancing could be maintained.
The most effective intervention scenario is the detection and isolation of 75% infected cases and reduction of 10% social contacts. This will require an expansion of testing capacity at health facilities and in the community, posing a challenge to identify high-risk groups to prioritized testing.
Conclusions
In a localized epidemic setting, the expansion of testing should be the key measure to control the epidemic. Social distancing plays a significant role to prevent further transmission to the community.
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SciScore for 10.1101/2020.04.24.20078030: (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:Our study has a number of limitations. So far, we still have limited knowledge of epidemiology and pathology of the SARS-CoV-2. Data of our models were based on multiple assumptions from data of countries where outbreaks have occurred. These models did not adjust for levels of virus transmission that could be affected by weather factors. …
SciScore for 10.1101/2020.04.24.20078030: (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:Our study has a number of limitations. So far, we still have limited knowledge of epidemiology and pathology of the SARS-CoV-2. Data of our models were based on multiple assumptions from data of countries where outbreaks have occurred. These models did not adjust for levels of virus transmission that could be affected by weather factors. In fact, we do not have evidences of changing levels of transmission by outdoor temperature. These models did not consider of unusual epicenters that their frequency and context of social contacts could be different from common contacts, such as the recent outbreak among men who have sex with men in Ho Chi Minh City. These models calculated mathematically the level of isolation and social distancing. In fact, defining what activities will reduce 10% or 20% social contacts, what actions will do to isolate infected cases is a matter. This requires consultation of researchers on social science. The mortality rate in our models only covers deaths of COVID-19, but other deaths due to overload of health system. Finally, these models did not consider impacts of the effective medication and vaccine.
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
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.
- Thank you for including a protocol registration statement.
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