ArticleSafety science2020
Prediction of CoVid-19 infection, transmission and recovery rates: A new analysis and global societal comparisons.
Article in Safety science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 20 citations in OpenAlex.
- COVID-19 Pandemic Risk Assessment: Systematic Review.Risk management and healthcare policy · 2024Review
- An optimization model for planning testing and control strategies to limit the spread of a pandemic - The case of COVID-19.European journal of operational research · 2023Article
- Behavioral biases and heuristics in perceptions of COVID-19 risks and prevention decisions.Risk analysis : an official publication of the Society for Risk Analysis · 2022Article
- Data-driven test strategy for COVID-19 using machine learning: A study in Lahore, Pakistan.Socio-economic planning sciences · 2022Article
- A systems-theoretic approach for two-stage emergency risk analysis.Journal of loss prevention in the process industries · 2021Article
- Globalization and global risk: How risk analysis needs to be enhanced to be effective in confronting current threats.Reliability engineering & system safety · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We analyze the process of infection rate growth and decline for the recent global pandemic, applying a new method to the available global data. We describe and utilize an original approach based on statistical physics to predict the societal transmission timescale and the universal recovery trajectory resulting from the countermeasures implemented in entire societies. We compare the whole-society infection growth rates for many countries and local regions, to illustrate the common physical and mathematical basis for the viral spread and infection rate reduction, and validate the theory and resulting correlations. We show that methods traditionally considered for the numerical analysis and the control of individual virus transmission (e.g. ℜ
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.