Years of life lost due to the psychosocial consequences of COVID19 mitigation strategies based on Swiss data
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Abstract
The pandemic caused by COVID-19 has forced governments to implement strict social mitigation strategies to reduce the morbidity and mortality from acute infections. These strategies however carry a significant risk for mental health which can lead to increased short-term and long-term mortality and is currently not included in modelling the impact of the pandemic.
Methods
We used years of life lost (YLL) as the main outcome measure as applied to Switzerland as an exemplar. We focused on suicide, depression, alcohol use disorder, childhood trauma due to domestic violence, changes in marital status and social isolation as these are known to increase YLL in the context of imposed restriction in social contact and freedom of movement. We stipulated a minimum duration of mitigation of 3 months based on current public health plans.
Results
The study projects that the average person would suffer 0.205 YLL due to psychosocial consequence of COVID-19 mitigation measures. However, this loss would be entirely borne by 2.1% of the population, who will suffer an average 9.79 YLL.
Conclusions
The results presented here are likely to underestimate the true impact of the mitigation strategies on YLL. However, they highlight the need for public health models to expand their scope in order to provide better estimates of the risks and benefits of mitigation.
Article activity feed
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SciScore for 10.1101/2020.04.17.20069716: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. 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:Limitations: As we demonstrate here, the evidence base for building such comprehensive models is limited and accordingly we had to make several assumptions. In this sense, our model projection is obviously constrained by the …
SciScore for 10.1101/2020.04.17.20069716: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. 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:Limitations: As we demonstrate here, the evidence base for building such comprehensive models is limited and accordingly we had to make several assumptions. In this sense, our model projection is obviously constrained by the limitations of the available literature which, itself, involves a number of unknowns. Given the time constraints, the uncertainty in those assumptions is increased; the authors however judge the urgency of such projections to be very high at the moment. Moreover, in this respect our model is not dissimilar to current projections of the spread and consequences of COVID19 which are being continually revised as more. Additionally, the present projection is not all-encompassing concerning potential effects of confinement: such as (prolonged) grief, elder abuse, increase of sedentary lifestyle or change of diet. The pandemic is also likely to have multiple additional consequences including distress due to job losses and financial hardship. The projection also does not model potentially positive changes in behaviour, for example reductions in car accidents and air pollution. Due to frequent co-occurrence of certain phenomena it is possible that a single individual may be affected by more than one of the factors presented. When possible, data were adjusted for age, sex and socioeconomics. However, for several factors, possibilities to do so were impeded by virtue of limitations of the current literature.
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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SciScore for 10.1101/2020.04.17.20069716: (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
Results from OddPub: We did not find a statement about open data. We also did not find a statement about open code. Researchers are encouraged to share open data when possible (see Nature blog).
About SciScore
SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore is not a substitute for expert review. SciScore checks for the presence and correctness of RRIDs (research resource identifiers) in the manuscript, and detects sentences that appear to be missing RRIDs. …
SciScore for 10.1101/2020.04.17.20069716: (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
Results from OddPub: We did not find a statement about open data. We also did not find a statement about open code. Researchers are encouraged to share open data when possible (see Nature blog).
About SciScore
SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore is not a substitute for expert review. SciScore checks for the presence and correctness of RRIDs (research resource identifiers) in the manuscript, and detects sentences that appear to be missing RRIDs. SciScore also checks to make sure that rigor criteria are addressed by authors. It does this by detecting sentences that discuss criteria such as blinding or power analysis. SciScore does not guarantee that the rigor criteria that it detects are appropriate for the particular study. Instead it assists authors, editors, and reviewers by drawing attention to sections of the manuscript that contain or should contain various rigor criteria and key resources. For details on the results shown here, including references cited, please follow this link.
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