Trends and prediction in daily incidence of novel coronavirus infection in China, Hubei Province and Wuhan City: an application of Farr's law.

Jie Xu, Yajiao Cheng, Xiaoling Yuan, Wei Vivian Li, Lanjing Zhang

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Article in American journal of translational research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

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8citing papers in PubMed

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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

A Data-driven, Dynamic and Flexible Approach to Safely Lifting Mask Mandate: A Proposal.Exploratory research and hypothesis in medicine · 2022
Article
Analysis of the Effects of COVID-19 Mask Mandates on Hospital Resource Consumption and Mortality at the County Level.Southern medical journal · 2021
Article
The role of T2E mediated CBF-1/RBP-Jκ signaling in metastatic thyroid cancer.American journal of translational research · 2021
Article
Associations of Stay-at-Home Order and Face-Masking Recommendation with Trends in Daily New Cases and Deaths of Laboratory-Confirmed COVID-19 in the United States.Exploratory research and hypothesis in medicine · 2020
Article
Trends and prediction in daily incidence and deaths of COVID-19 in the United States: a search-interest based model.medRxiv : the preprint server for health sciences · 2020
Article
Trends and Prediction in Daily New Cases and Deaths of COVID-19 in the United States: An Internet Search-Interest Based Model.Exploratory research and hypothesis in medicine · 2020
Article
State heterogeneity in the associations of human mobility with COVID-19 epidemics in the European Union.American journal of translational research · 2020
Article
Clinical interventions for severe and critical COVID-19: what are the options.American journal of translational research · 2020
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5 · Who and what money

Authors and funding

5 authors.

Jie XuDepartment of Infectious Disease, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine Shanghai, China.

Yajiao ChengDepartment of Infectious Disease, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine Shanghai, China.

Xiaoling YuanDepartment of Infectious Disease, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine Shanghai, China.

Wei Vivian LiDepartment of Biostatistics and Epidemiology, Rutgers School of Public Health Piscataway, NJ, USA.

Lanjing ZhangDepartment of Pathology, Princeton Medical Center Plainsboro, NJ, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe recent outbreak of novel coronavirus (2019-nCoV) has infected tens of thousands of patients in China. Studies have forecasted future trends of the incidence of 2019-nCoV infection, but appeared unsuccessful. Farr's law is a classic epidemiology theory/practice for predicting epidemics. Therefore, we used and validated a model based on Farr's law to predict the daily-incidence of 2019-nCoV infection in China and 2 regions of high-incidence.

methodsWe extracted the 2019-nCoV incidence data of China, Hubei Province and Wuhan City from websites of the Chinese and Hubei health commissions. A model based on Farr's law was developed using the data available on Feb. 8, 2020, and used to predict daily-incidence of 2019-nCoV infection in China, Hubei Province and Wuhan City afterward.

resultsWe observed 50,995 (37,001 on or before Feb. 8) incident cases in China from January 16 to February 15, 2020. The daily-incidence has peaked in China, Hubei Providence and Wuhan City, but with different downward slopes. If no major changes occur, our model shows that the daily-incidence of 2019-nCoV will drop to single-digit by February 25 for China and Hubei Province, but by March 8 for Wuhan city. However, predicted 75% confidence intervals of daily-incidence in all 3 regions of interest had an upward trend. The predicted trends overall match the prospectively-collected data, confirming usefulness of these models.

conclusionsThis study shows the daily-incidence of 2019-nCoV in China, Hubei Province and Wuhan City has reached the peak and was decreasing. However, there is a possibility of upward trend.

Indexed as

Chinaincidencenovel coronaviruspandemicTrend

Identifiers

PMID32355547

PMCPMC7191162

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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.