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Strengthening the Reporting of Molecular Epidemiology for Infectious Diseases (STROME-ID): an extension of the STROBE statement

Journal

LANCET INFECTIOUS DISEASES
Volume 14, Issue 4, Pages 341-352

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/S1473-3099(13)70324-4

Keywords

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Funding

  1. National Institute for Health Research Academic Clinical Lectureship
  2. National Institute for Health Research Senior Research Fellowship
  3. National Institute for Health Research [CL-2010-18-010] Funding Source: researchfish

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Molecular data are now widely used in epidemiological studies to investigate the transmission, distribution, biology, and diversity of pathogens. Our objective was to establish recommendations to support good scientific reporting of molecular epidemiological studies to encourage authors to consider specific threats to valid inference. The statement Strengthening the Reporting of Molecular Epidemiology for Infectious Diseases (STROME-ID) builds upon the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) initiative. The STROME-ID statement was developed by a working group of epidemiologists, statisticians, bioinformaticians, virologists, and microbiologists with expertise in control of infection and communicable diseases. The statement focuses on issues relating to the reporting of epidemiological studies of infectious diseases using molecular data that were not addressed by STROBE. STROME-ID addresses terminology, measures of genetic diversity within pathogen populations, laboratory methods, sample collection, use of molecular markers, molecular clocks, timeframe, multiple-strain infections, non-independence of infectious-disease data, missing data, ascertainment bias, consistency between molecular and epidemiological data, and ethical considerations with respect to infectiousdisease research. In total, 20 items were added to the 22 item STROBE checklist. When used, the STROME-ID recommendations should advance the quality and transparency of scientific reporting, with clear benefits for evidence reviews and health-policy decision making.

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