Evidence map›Paper›PMID 32607515›Full record

ArticlemedRxiv : the preprint server for health sciences2020

Predicting the Trajectory of Any COVID19 Epidemic From the Best Straight Line.

Michael Levitt, Andrea Scaiewicz, Francesco Zonta

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Michael LevittDepartment of Structural Biology, Stanford School of Medicine, Stanford, CA 94305, USA.
Andrea ScaiewiczDepartment of Structural Biology, Stanford School of Medicine, Stanford, CA 94305, USA.
Francesco ZontaShanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University, Shanghai, China.

Funding

Emergent Properties of Complex Systems: From Atoms to Macromolecules; from Humans to SocietiesR35GM122543 · NIGMS · STANFORD UNIVERSITY · PI MICHAEL LEVITT · 2017 to 2026
$5.1M
NIGMS NIH HHS R35 GM122543
6 · The paper itself

Abstract

A pipeline involving data acquisition, curation, carefully chosen graphs and mathematical models, allows analysis of COVID-19 outbreaks at 3,546 locations world-wide (all countries plus smaller administrative divisions with data available). Comparison of locations with over 50 deaths shows all outbreaks have a common feature:

Identifiers

PMID32607515
PMCPMC7325180

What OpenQuestion holds

Textmetadata
LicenceCC BY-ND
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.