MEASLES DIAGNOSTICS: PROBLEMS AND MODERN APPROACHES

Cover Page

Cite item

Abstract

Key methods of measles diagnostics are presented in the paper. Immunoenzyme, chemiluminiscent assays and polymerase chain reaction are the most effective modern measles diagnostic methods. Development of more perfect diagnostic techniques is essential component of WHO Global measles and rubella strategic plan.

About the authors

M. B. Rayev

FSBSI Institute of Ecology and Genetics of Microorganisms UB RAS

Author for correspondence.
Russian Federation

P. V. Khramtsov

FSBSI Institute of Ecology and Genetics of Microorganisms UB RAS; FSBEIHPE Perm State National Research University

Russian Federation

M. S. Bochkova

FSBSI Institute of Ecology and Genetics of Microorganisms UB RAS

Russian Federation

V. P. Timganova

FSBSI Institute of Ecology and Genetics of Microorganisms UB RAS

Russian Federation

S. A. Zamorina

FSBSI Institute of Ecology and Genetics of Microorganisms UB RAS; FSBEIHPE Perm State National Research University

Russian Federation

References

  1. Bester J. C. Measles and Measles Vaccination: A Review. jAMA Pediatrics. 2016, 170 (vol.), 1209-1215.
  2. Vero/hSLAM Cells for Isolation of Measles Virus. https://www.cdc.gov/measles/lab-tools/vero-slam. html
  3. De Ory F., Minguito T., Balfagon P., Sanz J. C. Comparison of chemiluminescent immunoassay andEL-ISA for measles IgG and IgM. APMIS. 2015, 123 (vol.), 648-651.
  4. Yasui Y., Mori Y., Adachi H., Kobayashi S., Yamashi-ta T., Minagawa H. Detection and genotyping of rubella virus from exanthematous patients suspected of having measles using reverse transcription-PCR. Jpn. J. Infect. Dis. 2014, 67 (vol.), 389-391.
  5. Holzmann H., Hengel H., Tenbusch M., Doerr H. W. Eradication of measles: remaining challenges. Med. Microbiol. Immunol. 2016, 205 (vol.), 201-208.

Supplementary files

Supplementary Files
Action
1. JATS XML

Copyright (c) 2017 Rayev M.B., Khramtsov P.V., Bochkova M.S., Timganova V.P., Zamorina S.A.

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Согласие на обработку персональных данных

 

Используя сайт https://journals.rcsi.science, я (далее – «Пользователь» или «Субъект персональных данных») даю согласие на обработку персональных данных на этом сайте (текст Согласия) и на обработку персональных данных с помощью сервиса «Яндекс.Метрика» (текст Согласия).