Evidence map›Paper›PMID 34016952›Full record

ArticleTranslational psychiatry2021

Is the worst of the COVID-19 global pandemic yet to come? Application of financial mathematics as candidate predictive tools.

Prashant Dogra, Eugene J Koay, Zhihui Wang, Farhaan S Vahidy, Mauro Ferrari, Renata Pasqualini, Wadih Arap, Marc L Boom, H Dirk Sostman, Vittorio Cristini

Open access · goldAbstract read
In one paragraph

Article in Translational psychiatry, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.7field-weighted citation impact, top 32% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Article
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  4. Review
  5. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 4 institutions in 1 country.

Prashant DograMathematics in Medicine Program, Houston Methodist Research Institute, Houston, TX, USA.
Eugene J KoayDepartment of Gastrointestinal Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Zhihui WangMathematics in Medicine Program, Houston Methodist Research Institute, Houston, TX, USA.
Farhaan S VahidyCenter for Outcomes Research, Houston Methodist Research Institute, Houston, TX, USA.
Mauro FerrariDepartment of Pharmaceutics, University of Washington, Seattle, WA, USA.
Renata PasqualiniRutgers Cancer Institute of New Jersey, Newark, NJ, USA.
Wadih ArapRutgers Cancer Institute of New Jersey, Newark, NJ, USA.
Marc L BoomDepartment of Medicine, Houston Methodist, Houston, TX, USA.
H Dirk SostmanWeill Cornell Medicine, New York, NY, USA.
Vittorio CristiniMathematics in Medicine Program, Houston Methodist Research Institute, Houston, TX, USA. vcristini@houstonmethodist.org.ORCID 0000-0002-7909-4278
Houston Methodist · USRutgers, The State University of New Jersey · USThe University of Texas MD Anderson Cancer Center · USUniversity of Washington · US

Funding

Transport Oncophysics CoreU54CA210181 · NCI · METHODIST HOSPITAL RESEARCH INSTITUTE · PI SHEN, HAIFA · 2016 to 2020
$9.3M
Imaging and Molecular Correlates of Progression in Cystic Neoplasms of the PancreasU01CA196403 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI MAITRA, ANIRBAN · 2015 to 2020
$5.8M
A Targeted Nanomedicine Prototype Against Enzalutamide-resistant Prostate CancerR01CA226537 · NCI · RBHS -CANCER INSTITUTE OF NEW JERSEY · PI ARAP, WADIH, BRINKER, C JEFFREY · 2018 to 2022
$3.2M
miR-155 targeted therapeutics for precision medicine in lung cancerR01CA222007 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI CALIN, GEORGE A., CRISTINI, VITTORIO · 2018 to 2022
$2.6M
Targeted therapeutics for ovarian cancer and its microenvironment - treatment and theoretical modelingU01CA213759 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI LOPEZ-BERESTEIN, GABRIEL · 2017 to 2021
$2.5M
NCI NIH HHS R01 CA222007NCI NIH HHS R01 CA226537NCI NIH HHS U01 CA196403NCI NIH HHS U01 CA213759NCI NIH HHS U54 CA210181
6 · The paper itself

Abstract

The Elliott Wave principle is a time-honored, oft-used method for predicting variations in the financial markets. It is based on the notion that human emotions drive financial decisions. In the fight against the COVID-19 global pandemic, human emotions are similarly decisive, for instance in that they determine one's willingness to be vaccinated, and/or to follow preventive measures including the personal wearing of masks, the application of social distancing protocols, and frequent handwashing. On this basis, we postulated that the Elliott Wave Principle may similarly be used to predict the future evolution of the COVID-19 pandemic. We demonstrated that this method reproduces the data pattern for various countries and the world (daily new cases). Potential scenarios were then extrapolated, from the best-case corresponding to a rapid, full vaccination of the population, to the utterly disastrous case of slow vaccination, and poor adherence to preventive protocols.

Indexed as

COVID-19PandemicsHumansMasksMathematicsSARS-CoV-2

Identifiers

PMID34016952
PMCPMC8134815
OpenAlexW3163603767

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.