Scientific Reports (Jun 2022)

Combining host and vector data informs emergence and potential impact of an Usutu virus outbreak in UK wild birds

  • Becki Lawson,
  • Robert A. Robinson,
  • Andrew G. Briscoe,
  • Andrew A. Cunningham,
  • Anthony R. Fooks,
  • Joseph P. Heaver,
  • Luis M. Hernández-Triana,
  • Shinto K. John,
  • Nicholas Johnson,
  • Colin Johnston,
  • Fabian Z. X. Lean,
  • Shaheed K. Macgregor,
  • Nicholas J. Masters,
  • Fiona McCracken,
  • Lorraine M. McElhinney,
  • Jolyon M. Medlock,
  • Paul Pearce-Kelly,
  • Katharina Seilern-Moy,
  • Simon Spiro,
  • Alexander G. C. Vaux,
  • Arran J. Folly

DOI
https://doi.org/10.1038/s41598-022-13258-2
Journal volume & issue
Vol. 12, no. 1
pp. 1 – 10

Abstract

Read online

Abstract Following the first detection in the United Kingdom of Usutu virus (USUV) in wild birds in 2020, we undertook a multidisciplinary investigation that combined screening host and vector populations with interrogation of national citizen science monitoring datasets to assess the potential for population impacts on avian hosts. Pathological findings from six USUV-positive wild passerines were non-specific, highlighting the need for molecular and immunohistochemical examinations to confirm infection. Mosquito surveillance at the index site identified USUV RNA in Culex pipiens s.l. following the outbreak. Although the Eurasian blackbird (Turdus merula) is most frequently impacted by USUV in Europe, national syndromic surveillance failed to detect any increase in occurrence of clinical signs consistent with USUV infection in this species. Furthermore, there was no increase in recoveries of dead blackbirds marked by the national ringing scheme. However, there was regional clustering of blackbird disease incident reports centred near the index site in 2020 and a contemporaneous marked reduction in the frequency with which blackbirds were recorded in gardens in this area, consistent with a hypothesis of disease-mediated population decline. Combining results from multidisciplinary schemes, as we have done, in real-time offers a model for the detection and impact assessment of future disease emergence events.