BMJ Open (Nov 2024)

Diagnostics for optimised dengue surveillance: a qualitative focus group study to investigate user experience and requirements in Thailand

  • Raheelah Ahmad,
  • Alison Holmes,
  • Pantelis Georgiou,
  • Paul Arkell,
  • Sanhapon Ketklao,
  • Adisak Songjaeng,
  • Dumrong Mairiang,
  • Jesus Rodriguez-Manzano,
  • Prida Malasit,
  • Panisadee Avirutnan,
  • Saranath Lawpoolsri

DOI
https://doi.org/10.1136/bmjopen-2024-085946
Journal volume & issue
Vol. 14, no. 11

Abstract

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Objectives Effective, real-time surveillance of dengue may provide early warning of outbreaks and support targeted disease-control intervention but requires widespread accurate diagnosis and timely case reporting. Research directing innovation in diagnostics for dengue surveillance is lacking. This study aimed to describe experience and requirements of relevant prospective users.Design A qualitative, focus group study was conducted.Participants Data were collected from 19 users of diagnostic technology who work across the Thai dengue surveillance system.Data collection and analysis Contextual knowledge, experience and needs were explored in focus groups. Discussions were translated, transcribed, analysed thematically and mapped to Consolidated Framework for Implementation Research domains.Results Participants expressed a need for rapid, accurate, serotype-specific tests which can be operated easily by non-expert users without laboratory equipment. They supported integration of diagnostics with surveillance systems and felt this would increase the quantity and speed of case reporting as well as provide healthcare professionals with up-to-date information about the number of cases locally, thereby aiding interpretation of test results. Concerns included those relating to data security and the cost of tests.Conclusions Engagement to understand prospective user experience and requirements can improve relevance and uptake of new technology, leading to system efficiencies. The present study highlights specific needs for accurate, serotype-specific, remote-connected diagnostics which are integrated with surveillance systems and support dengue case reporting at the point-of-care.