Geographic information system-aided evaluation of epidemiological trends of dengue serotypes in West Bengal, India.

BACKGROUND OBJECTIVES: West Bengal is a dengue-endemic State in India, with all four dengue serotypes in co-circulation. The present study was conceived to determine the changing trends of circulating dengue virus (DENV) serotypes in five consecutive years (2015-2019) using a geographic information system (GIS) during the dengue season in West Bengal, India. METHODS: Molecular serotyping of dengue NS1 sero-reactive serum samples from individuals with ≤5 days of fever was performed using conventional nested reverse transcriptase-PCR. GIS techniques such as Getis-Ord Gi* hotspot analysis and heatmap were used to elucidate dengue transmission based on the received NS1-positive cases and vector data analysis was used to point out risk-prone areas. RESULTS: A total of 3915 dengue NS1 sero-positive samples were processed from most parts of West Bengal and among these, 3249 showed RNA positivity. The major circulating serotypes were DENV 3 (63.54%) in 2015, DENV 1 (52.79%) in 2016 and DENV 2 (73.47, 76.04 and 47.15%) in 2017, 2018 and 2019, respectively. Based on the NS1 positivity, dengue infections were higher in males than females and young adults of 21-30 yr were mostly infected. Getis-Ord Gi* hotspot cluster analysis and heatmap indicate that Kolkata has become a hotspot for dengue outbreaks and serotype plotting on maps confirms a changing trend of predominant serotypes during 2015-2019 in West Bengal. INTERPRETATION CONCLUSIONS: Co-circulation of all the four dengue serotypes was observed in this study, but only one serotype became prevalent during an outbreak. Representation of NS1-positive cases and serotype distribution in GIS mapping clearly showed serotypic shift in co-circulation. The findings of this study suggest the need for stringent surveillance in dengue-endemic areas to limit the impact of dengue and implement better vector-control strategies.

Changing pattern of circulating dengue serotypes in the endemic region: An alarming risk to the healthcare system during the pandemic.

BACKGROUND: The pandemic of COVID-19 has created an unprecedented burden on the healthcare system and medical communities resulting in new public health challenges. On the other hand, in tropical countries, another concern arises due to the similar spectrum of clinical manifestations between COVID-19 and dengue fever. Thus, the neglected tropical disease 'Dengue' writhed with more inattention. This study aims to find the effect of the COVID-19 pandemic on dengue infections in endemic areas of West Bengal, India, and their combined impact on public health. The alterations in circulating dengue serotype and their genomic diversity in different COVID-19 waves were also monitored. METHODS: A total of 1782 patients were included in this study. Dengue NS1 ELISA, molecular serotyping, genotyping and their phylogenetic analysis were performed. GISaided analysis of various dengue serotypes and hotspot identification for risk maps of severe dengue in endemic zones were done. The burden of dengue fever and the sustainability of their viral strains with changing meteorological parameters in parallel to COVID-19 waves were analyzed. RESULTS: Co-circulation of all the four dengue serotypes with rapid change in the pattern of prevalent serotype DENV4 (Genotype-I) in the year 2020 and DENV3 (Genotype-III) in 2021 were observed, in parallel to different circulating strains of COVID-19. Spatiotemporal distribution of DENV using Geographic Information System (GIS) applications observed a serotypic shift and hotspot mapping for risk analysis detected Kolkata as a dengue hotspot, which has also reported the maximum number of COVID-19 cases. CONCLUSION: This study indicates the increased fitness of circulating dengue virus strains with optimal virulence as per changing environmental conditions and the inhabitant's immunity. The high infectivity rate of both the RNA viruses and considering.the consequences of severe dengue and COVID-19 in the population of the same geographical settings is an alarming risk.