Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2022;14(4):60-70.
doi: 10.17691/stm2022.14.4.07. Epub 2022 Jul 29.

Trends in Population-Based Studies: Molecular and Digital Epidemiology (Review)

N S Denisov  1 , E M Kamenskikh  2 , O S Fedorova  3
Affiliations
Review

Trends in Population-Based Studies: Molecular and Digital Epidemiology (Review)

N S Denisov et al. Sovrem Tekhnologii Med. 2022.

Abstract

The development of high-throughput technologies has sharply increased the opportunities to research the human body at the molecular, cellular, and organismal levels in the last decade. Rapid progress in biotechnology has caused a paradigm shift in population-based studies. Advances in modern biomedical sciences, including genomic, genome-wide, post-genomic research and bioinformatics, have contributed to the emergence of molecular epidemiology focused on the study of the personalized molecular mechanism of disease development and its extrapolation to the population level. The work of research teams at the intersection of information technology and medicine has become the basis for highlighting digital epidemiology, the important tools of which are machine learning, the ability to work with real world data, and accumulated big data. The developed approaches accelerate the process of collecting and processing biomedical data, testing new scientific hypotheses. However, new methods are still in their infancy, they require testing of application under various conditions, as well as standardization. This review highlights the role of omics and digital technologies in population-based studies.

Keywords: digital epidemiology; information technologies; molecular epidemiology; omics technologies; population-based studies in medicine.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflicts of interest in preparing the publication.

Figures

Figure 1.
Figure 1.. Pathogen sequencing during infectious disease outbreaks
Schematically presented relationship between obtaining genomic data and creating health-saving technologies
Figure 2.
Figure 2.. Transition from classical to digital epidemiology [94]
Formation of digital epidemiology as a field of knowledge
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

References

    1. Diaz-Beltran L., Cano C., Wall D.P., Esteban F.J. Systems biology as a comparative approach to understand complex gene expression in neurological diseases. Behav Sci (Basel) 2013;3(2):253–272. doi: 10.3390/bs3020253. - DOI - PMC - PubMed
    1. Wang Q., Lu Q., Zhao H. A review of study designs and statistical methods for genomic epidemiology studies using next generation sequencing. Front Genet. 2015;6:149. doi: 10.3389/fgene.2015.00149. - DOI - PMC - PubMed
    1. Pareek C.S., Smoczynski R., Tretyn A. Sequencing technologies and genome sequencing. J Appl Genet. 2011;52(4):413–435. doi: 10.1007/s13353-011-0057-x. - DOI - PMC - PubMed
    1. Hill V., Ruis C., Bajaj S., Pybus O.G., Kraemer M.U.G. Progress and challenges in virus genomic epidemiology. Trends Parasitol. 2021;37(12):1038–1049. doi: 10.1016/j.pt.2021.08.007. - DOI - PubMed
    1. Armstrong G.L., MacCannell D.R., Taylor J., Carleton H.A., Neuhaus E.B., Bradbury R.S., Posey J.E., Gwinn M. Pathogen genomics in public health. N Engl J Med. 2019;381(26):2569–2580. doi: 10.1056/nejmsr1813907. - DOI - PMC - PubMed

LinkOut - more resources