ArticleSafety science2021
Diagnostic model for the society safety under COVID-19 pandemic conditions.
Article in Safety science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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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.
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Who cites it
9 citing papers in PubMed.
- Coronavirus-Related Searches on the Internet Predict COVID-19 Vaccination Rates in the Real World: A Behavioral Immune System Perspective.Social psychological and personality science · 2023Article
- Socio-economic analysis of short-term trends of COVID-19: modeling and data analytics.BMC public health · 2022Article
- Article
- Perception of COVID-19 Testing in the Entire Population.Frontiers in public health · 2022Article
- Analysis of COVID-19 epidemic model with sumudu transform.AIMS public health · 2022Article
- Using logistic regression to develop a diagnostic model for COVID-19: A single-center study.Journal of education and health promotion · 2022Article
- COVID-19 pandemic decision support system for a population defense strategy and vaccination effectiveness.Safety science · 2021Article
- Associations between mobility patterns and COVID-19 deaths during the pandemic: A network structure and rank propagation modelling approach.Array (New York, N.Y.) · 2021Article
- The Signature of the Coronavirus Lockdown in Air Pollution in Greece.Water, air, and soil pollution · 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
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The aim of this paper is to develop an information-modeling method for assessing and predicting the consequences of the COVID-19 pandemic. To this end, a detailed analysis of official statistical information provided by global and national organizations is carried out. The developed method is based on the algorithm of multi-channel big data processing considering the demographic and socio-economic information. COVID-19 data are analyzed using an instability indicator and a system of differential equations that describe the dynamics of four groups of people: susceptible, infected, recovered and dead. Indicators of the global sustainable development in various sectors are considered to analyze COVID-19 data. Stochastic processes induced by COVID-19 are assessed with the instability indicator showing the level of stability of official data and the reduction of the level of uncertainty. It turns out that the number of deaths is rising with the Human Development Index. It is revealed that COVID-19 divides the global population into three groups according to the relationship between Gross Domestic Product and the number of infected people. The prognosis for the number of infected people in December 2020 and January-February 2021 shows negative events which will decrease slowly.
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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.