Literature DB >> 33574387

Evaluation of the number of undiagnosed infected in an outbreak using source of infection measurements.

Akiva Bruno Melka1, Yoram Louzoun2,3.   

Abstract

In times of outbreaks, an essential requirement for better monitoring is the evaluation of the number of undiagnosed infected individuals. An accurate estimate of this fraction is crucial for the assessment of the situation and the establishment of protective measures. In most current studies using epidemics models, the total number of infected is either approximated by the number of diagnosed individuals or is dependent on the model parameters and assumptions, which are often debated. We here study the relationship between the fraction of diagnosed infected out of all infected, and the fraction of infected with known contaminator out of all diagnosed infected. We show that those two are approximately the same in exponential models and across most models currently used in the study of epidemics, independently of the model parameters. As an application, we compute an estimate of the effective number of infected by the SARS-CoV-2 virus in various countries.

Entities:  

Year:  2021        PMID: 33574387      PMCID: PMC7878881          DOI: 10.1038/s41598-021-82691-6

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  27 in total

1.  Predicting case numbers during infectious disease outbreaks when some cases are undiagnosed.

Authors:  K Glass; N Becker; M Clements
Journal:  Stat Med       Date:  2007-01-15       Impact factor: 2.373

2.  Invasion Rate Versus Diversity in Population Dynamics with Catastrophes.

Authors:  A Melka; N Dori; Y Louzoun
Journal:  Phys Rev Lett       Date:  2020-04-17       Impact factor: 9.161

3.  Presumed Asymptomatic Carrier Transmission of COVID-19.

Authors:  Yan Bai; Lingsheng Yao; Tao Wei; Fei Tian; Dong-Yan Jin; Lijuan Chen; Meiyun Wang
Journal:  JAMA       Date:  2020-04-14       Impact factor: 56.272

4.  A SIR model assumption for the spread of COVID-19 in different communities.

Authors:  Ian Cooper; Argha Mondal; Chris G Antonopoulos
Journal:  Chaos Solitons Fractals       Date:  2020-06-28       Impact factor: 9.922

5.  Responding to global infectious disease outbreaks: lessons from SARS on the role of risk perception, communication and management.

Authors:  Richard D Smith
Journal:  Soc Sci Med       Date:  2006-09-15       Impact factor: 4.634

6.  Impact of quarantine on the 2003 SARS outbreak: a retrospective modeling study.

Authors:  Ying-Hen Hsieh; Chwan-Chuan King; Cathy W S Chen; Mei-Shang Ho; Sze-Bi Hsu; Yi-Chun Wu
Journal:  J Theor Biol       Date:  2006-09-16       Impact factor: 2.691

7.  A generalized-growth model to characterize the early ascending phase of infectious disease outbreaks.

Authors:  Cécile Viboud; Lone Simonsen; Gerardo Chowell
Journal:  Epidemics       Date:  2016-02-01       Impact factor: 4.396

8.  The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: a modelling study.

Authors:  Kiesha Prem; Yang Liu; Timothy W Russell; Adam J Kucharski; Rosalind M Eggo; Nicholas Davies; Mark Jit; Petra Klepac
Journal:  Lancet Public Health       Date:  2020-03-25

9.  An investigation of transmission control measures during the first 50 days of the COVID-19 epidemic in China.

Authors:  Huaiyu Tian; Yonghong Liu; Yidan Li; Chieh-Hsi Wu; Bin Chen; Moritz U G Kraemer; Bingying Li; Jun Cai; Bo Xu; Qiqi Yang; Ben Wang; Peng Yang; Yujun Cui; Yimeng Song; Pai Zheng; Quanyi Wang; Ottar N Bjornstad; Ruifu Yang; Bryan T Grenfell; Oliver G Pybus; Christopher Dye
Journal:  Science       Date:  2020-03-31       Impact factor: 47.728

10.  SARS-CoV-2 Infections in the World: An Estimation of the Infected Population and a Measure of How Higher Detection Rates Save Lives.

Authors:  Carlos Villalobos
Journal:  Front Public Health       Date:  2020-09-25
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