Estimating asymptomatic COVID-19 infections and policy effects

In summary, a meta-analysis of 94 case studies on asymptomatic and presymptomatic SARS-CoV-2 infections found that approximately 20% of people remain asymptomatic throughout infection. However, there is evidence of bias in the selection of participants. The study also found that the secondary attack rate is lower in contacts of people with asymptomatic infection compared to those with symptomatic infection. Therefore, it suggests that a combination of prevention measures such as hand hygiene, masks, testing, tracing, isolation, and social distancing will still be necessary to control the spread of the virus. The study was published in PLOS Medicine on September 22, 2020 and is open access for anyone to read and observe the peer review process.
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jim mcnamara
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TL;DR Summary
The estimated asymptomatic population for the full duration of infection is 20%. This has infection control policy implications
If you want to critique this meta-analysis of case studies, please read the article. First. PLOS is open access. Anyone can see it.
Note the ability to see the peer review process, which is interesting.

"Occurrence and transmission potential of asymptomatic and presymptomatic SARS-CoV-2 infections: A living systematic review and meta-analysis"
Diana Buitrago-Garcia, et al.
PLOS MEDICINE Published: September 22, 2020
https://doi.org/10.1371/journal.pmed.1003346

This study implies that we need to consider the continued infection control measures that are in place. This kind of study is not an RCT. It is based on 94 case study papers, sort of a lesser form of scientific rigor. But this is about as good as it gets for this kind of investigation.

Results:
We included a total of 94 studies. The overall estimate of the proportion of people who become infected with SARS-CoV-2 and remain asymptomatic throughout infection was 20% (95% confidence interval [CI] 17–25) with a prediction interval of 3%–67% in 79 studies that addressed this review question. There was some evidence that biases in the selection of participants influence the estimate. In seven studies of defined populations screened for SARS-CoV-2 and then followed, 31% (95% CI 26%–37%, prediction interval 24%–38%) remained asymptomatic. The proportion of people that is presymptomatic could not be summarised, owing to heterogeneity. The secondary attack rate was lower in contacts of people with asymptomatic infection than those with symptomatic infection (relative risk 0.35, 95% CI 0.10–1.27).

Conclusion:
The contribution of presymptomatic and asymptomatic infections to overall SARS-CoV-2 transmission means that combination prevention measures, with enhanced hand hygiene, masks, testing tracing, and isolation strategies and social distancing, will continue to be needed.
 
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Having a second thought on this!
 

1. What is the definition of asymptomatic COVID-19 infections?

Asymptomatic COVID-19 infections refer to cases where individuals have been infected with the virus, but do not exhibit any symptoms. These individuals may still be able to transmit the virus to others, even though they do not feel sick themselves.

2. How are asymptomatic COVID-19 infections estimated?

Asymptomatic COVID-19 infections can be estimated through various methods, such as seroprevalence studies, contact tracing, and surveillance testing. These methods involve testing individuals who may have been exposed to the virus, even if they do not show symptoms.

3. Why is estimating asymptomatic COVID-19 infections important?

Estimating asymptomatic COVID-19 infections is important because it allows us to better understand the spread of the virus and its impact on the population. It can also help inform public health policies and interventions to control the spread of the virus.

4. How do policy effects play a role in estimating asymptomatic COVID-19 infections?

Policies such as mask mandates, social distancing guidelines, and lockdowns can affect the number of asymptomatic COVID-19 infections by reducing the spread of the virus. By comparing infection rates before and after implementing these policies, we can estimate their effectiveness in controlling the spread of the virus.

5. What are the limitations of estimating asymptomatic COVID-19 infections?

There are several limitations to estimating asymptomatic COVID-19 infections, including the accuracy of testing methods and the potential for false negative results. Additionally, not all asymptomatic individuals may be tested, leading to underestimation of the true number of cases. It is important to consider these limitations when interpreting estimates of asymptomatic infections.

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