Evidence map›Paper›PMID 32719764›Full record

ArticleFrontiers in public health2020

Survival-Convolution Models for Predicting COVID-19 Cases and Assessing Effects of Mitigation Strategies.

Qinxia Wang, Shanghong Xie, Yuanjia Wang, Donglin Zeng

Abstract read
In one paragraph

Article in Frontiers in public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Accuracy of US CDC COVID-19 forecasting models.Frontiers in public health · 2024
    Article
  2. Article
  3. Article
  4. PAN-cODE: COVID-19 forecasting using conditional latent ODEs.Journal of the American Medical Informatics Association : JAMIA · 2022
    Article
  5. Article
  6. Article
  7. Optimized Post-Vaccination Strategies and Preventative Measures for SARS-CoV-2.medRxiv : the preprint server for health sciences · 2021
    Article
  8. Article
  9. Article
  10. COVID-19: Current knowledge in clinical features, immunological responses, and vaccine development.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2021
    Review
  11. Article
  12. Article
  13. Article
  14. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Qinxia WangDepartment of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, United States.
Shanghong XieDepartment of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, United States.
Yuanjia WangDepartment of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, United States.
Donglin ZengDepartment of Biostatistics, Gillings School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.

Funding

Statistical Methods for Integrating Mixed-type Biomarkers and Phenotypes in Neurodegenerative Disease ModelingR01NS073671 · NINDS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI WANG, YUANJIA · 2011 to 2025
$3.9M
Statistical and Machine Learning Methods to Improve Dynamic Treatment Regimens Estimation Using Real World Data.R01GM124104 · NIGMS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Yuanjia Wang, Donglin Zeng · 2018 to 2026
$3.1M
Integrative Learning to Combine Evidence for Personalized Treatment Strategies.R21MH117458 · NIMH · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI WANG, YUANJIA · 2018 to 2019
$446k
NIGMS NIH HHS R01 GM124104NIMH NIH HHS R21 MH117458NINDS NIH HHS R01 NS073671
6 · The paper itself

Abstract

Countries around the globe have implemented unprecedented measures to mitigate the coronavirus disease 2019 (COVID-19) pandemic. We aim to predict the COVID-19 disease course and compare the effectiveness of mitigation measures across countries to inform policy decision making using a robust and parsimonious survival-convolution model. We account for transmission during a pre-symptomatic incubation period and use a time-varying effective reproduction number (

Indexed as

Communicable Disease ControlBasic Reproduction NumberChinaCOVID-19HumansItalyRepublic of KoreaUnited StatesCOVID-19mitigation measurespredictionsurvival-convolution modeltime-varying effective reproduction number

Identifiers

PMID32719764
PMCPMC7347904

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.