Evidence map›Paper›PMID 35342683›Full record

ArticleNetwork modeling and analysis in health informatics and bioinformatics2022

Deathdaily: A Python Package Index for predicting the number of daily COVID-19 deaths.

Yoshiyasu Takefuji

Abstract read
In one paragraph

Article in Network modeling and analysis in health informatics and bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

1 author.

Yoshiyasu TakefujiFaculty of Data Science, Musashino University, 3-3-3 Ariake Koto-ku, Tokyo, 135-8181 Japan.ORCID 0000-0002-1826-742X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper presents a new open-source program called deathdaily for predicting the number of daily COVID-19 deaths in the next 7 days. The predictions can be used by policymakers to determine whether current policies should be strengthened/mitigated or new policies should be challenged to mitigate the COVID-19 pandemic. Although vaccines have been mitigating the pandemic initially, the recent resurgence with new variants has been observed in many vaccinated countries. This paper shows how to use deathdaily to detect symptoms of resurgence. The proposed deathdaily is available in public and can be installed by a Python package manager PyPI. The deathdaily has been downloaded by 15,964 users worldwide, according to https://pepy.tech/project/deathdaily. The fact shows that the applicability, practicality, and usefulness of the proposed program have been duly evaluated.

Indexed as

COVID-19Scraping a datasetThe number of daily deathsVaccinesVariants

Identifiers

PMID35342683
PMCPMC8934376

What OpenQuestion holds

Textmetadata
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.