4.5 Review

A systematic review on global RSV genetic data: Identification of knowledge gaps

Journal

REVIEWS IN MEDICAL VIROLOGY
Volume 32, Issue 3, Pages -

Publisher

WILEY
DOI: 10.1002/rmv.2284

Keywords

molecular epidemiology; monoclonal antibodies; respiratory syncytial virus; RSV; systematic review

Categories

Funding

  1. AstraZeneca

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Respiratory syncytial virus (RSV) is a significant health issue, and understanding its circulation dynamics can help track resistance to current therapeutics. The field of RSV molecular epidemiology has rapidly evolved, but there are still knowledge gaps, including the need for whole-genome data, data from low- and middle-income countries, and data from global surveillance programs.
Respiratory syncytial virus (RSV) is a major health problem. A better understanding of the geographical and temporal dynamics of RSV circulation will assist in tracking resistance against therapeutics currently under development. Since 2015, the field of RSV molecular epidemiology has evolved rapidly with around 20-30 published articles per year. The objective of this systematic review is to identify knowledge gaps in recent RSV genetic literature to guide global molecular epidemiology research. We included 78 studies published between 2015 and 2020 describing 12,998 RSV sequences of which 8,233 (63%) have been uploaded to GenBank. Seventeen (22%) studies were performed in low- and middle-income countries (LMICs), and seven (9%) studies sequenced whole-genomes. Although most reported polymorphisms for monoclonal antibodies in clinical development (nirsevimab, MK-1654) have not been tested for resistance in neutralisation essays, known resistance was detected at low levels for the nirsevimab and palivizumab binding site. High resistance was found for the suptavumab binding site. We present the first literature review of an enormous amount of RSV genetic data. The need for global monitoring of RSV molecular epidemiology becomes increasingly important in evaluating the effectiveness of monoclonal antibody candidates as they reach their final stages of clinical development. We have identified the following three knowledge gaps: whole-genome data to study global RSV evolution, data from LMICs and data from global surveillance programs.

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