ArticleJournal of investigative medicine : the official publication of the American Federation for Clinical Research2021
COVID-19 epidemic outside China: 34 founders and exponential growth.
Article in Journal of investigative medicine : the official publication of the American Federation for Clinical Research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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.
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.
Who cites it
11 citing papers in PubMed.
- COVID-19 Detection Mechanism in Vehicles Using a Deep Extreme Machine Learning Approach.Diagnostics (Basel, Switzerland) · 2023Article
- CPPE-5: Medical Personal Protective Equipment Dataset.SN computer science · 2023Article
- A sustainable advanced artificial intelligence-based framework for analysis of COVID-19 spread.Environment, development and sustainability · 2022Article
- Enabling Artificial Intelligence for Genome Sequence Analysis of COVID-19 and Alike Viruses.Interdisciplinary sciences, computational life sciences · 2022Article
- Data Empowerment of Decision-Makers in an Era of a Pandemic: Intersection of "Classic" and Artificial Intelligence in the Service of Medicine.Journal of medical Internet research · 2021Article
- Impact of COVID-19 on older adults and role of long-term care facilities during early stages of epidemic in Italy.Scientific reports · 2021Article
- Mathematical modeling of coronavirus disease COVID-19 dynamics using CF and ABC non-singular fractional derivatives.Chaos, solitons, and fractals · 2021Article
- The Number of Confirmed Cases of Covid-19 by using Machine Learning: Methods and Challenges.Archives of computational methods in engineering : state of the art reviews · 2021Article
- Patterns of the COVID-19 pandemic spread around the world: exponential versus power laws.Journal of the Royal Society, Interface · 2020Article
- Predicting the growth and trend of COVID-19 pandemic using machine learning and cloud computing.Internet of things (Amsterdam, Netherlands) · 2020Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
COVID-19 raised tension both within China and internationally. Here, we used mathematical modeling to predict the trend of patient diagnosis outside China in future, with the aim of easing anxiety regarding the emergent situation. According to all diagnosis number from WHO website and combining with the transmission mode of infectious diseases, the mathematical model was fitted to predict future trend of outbreak. Daily diagnosis numbers from countries outside China were downloaded from WHO situation reports. The data used for this analysis were collected from January 21, 2020 and currently end at February 28, 2020. A simple regression model was developed based on these numbers, as follows: [Formula: see text], where [Formula: see text] is the total diagnosed patient till the i-th day and t=1 at February 1, 2020. Based on this model, we estimate that there were approximately 34 undetected founder patients at the beginning of the spread of COVID-19 outside China. The global trend was approximately exponential, with an increase rate of 10-fold every 19 days. Through establishment of this model, we call for worldwide strong public health actions, with reference to the experiences learned from China and Singapore.
Indexed as
Identifiers
What OpenQuestion holds
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.