Abstract

BackgroundDengue is the most widespread arboviral disease globally. Serotyping of dengue viruses and their genotyping is important in tracing the epidemiology of the disease, monitoring trends and anticipating the possibility of outbreaks in a community.MethodsThis study is a retrospective analysis, based on data from a tertiary care center from Delhi, India and their correlation with reported literature on circulation and outbreaks of dengue in this region of north India since 1996, when the first virus isolation confirmed outbreak of dengue was reported by our virology laboratory (an Apex Laboratory of the National Vector Borne Disease Control Program, Government of India).Circulating serotypes of DENV were detected and identified from serum samples of suspected dengue patients with fever of 5 days duration or less, by virus isolation in cell culture and/or by real-time or conventional reverse transcription polymerase chain reaction (PCR). Representative serum samples of patients with suspected dengue with duration of fever <5 days were inoculated onto the C6/36 clone of Aedes albopictus cells, and the isolates were identified by indirect immunofluorescence using serotype-specific monoclonal antibodies. Sequencing was done for representative strains as required.ResultsThe predominant serotypes identified were DENV 2 (1996), followed temporally by DENV 1 (1997–2002), DENV 3 (2003–2007), DENV 1 (2008–2012), DENV 2 (2013–2015), and DENV 3 (2016–2018). In 2003, Delhi became hyper-endemic for dengue, with all dengue serotypes co-circulating. Predominant serotypes continued to circulate for 3–6 years. Outbreaks occurred either in the year a serotype was re-introduced after a gap of a few years to become the predominant serotype, or in the following year; except in 2015, when there was a genotypic lineage change in a DENV 2 serotype which had been predominant since 2 years prior to the outbreak year.ConclusionRe-introduction of a dengue serotype which was out of circulation for a few years can precipitate an outbreak. Analysis of temporal patterns and close monitoring of circulating virus strains, particularly at either end of the transmission season, may help in early prediction of the trend for a given year, providing an opportunity to put in place control measures well in time.Disclosures All authors: No reported disclosures.

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