COVID-19 prevention measures reduce dengue spread in Yunnan Province, China, but do not reduce established outbreak

• Published in: Emerging microbes & infections Vol. 11; no. 1; pp. 240 - 249
• Main Authors: Sheng, Z.Y., Li, M., Yang, R., Liu, Y.H., Yin, X.X., Mao, J. R., Brown, Heidi E., An, J., Zhou, H.N., Wang, P.G.
• Format: Journal Article
• Language: English
• Published: United States Taylor & Francis 01.12.2022; Taylor & Francis Ltd; Taylor & Francis Group
• Subjects: Animals; China - epidemiology; Chlorocebus aethiops; Communicable Disease Control - methods; Coronaviruses; COVID-19; COVID-19 - epidemiology; COVID-19 - prevention & control; Dengue - epidemiology; Dengue - prevention & control; Dengue - transmission; Dengue fever; Dengue Virus; Disease Outbreaks - prevention & control; Disease prevention; Disease transmission; Epidemics; Genotype; Humans; Pandemics; Pandemics - prevention & control; Phylogeny; RNA, Viral; SARS-CoV-2; Serogroup; Spatial Analysis; Vero Cells; China
• ISSN: 2222-1751; 2222-1751
• DOI: 10.1080/22221751.2021.2022438

The COVID-19 pandemic and measures against it provided a unique opportunity to understand the transmission of other infectious diseases and to evaluate the efficacy of COVID-19 prevention measures on them. Here we show a dengue epidemic in Yunnan, China, during the pandemic of COVID-19 was dramatically reduced compared to non-pandemic years and, importantly, spread was confined to only one city, Ruili. Three key features characterized this dengue outbreak: (i) the urban-to-suburban spread was efficiently blocked; (ii) the scale of epidemic in urban region was less affected; (iii) co-circulation of multiple strains was attenuated. These results suggested that countermeasures taken during COVID-19 pandemic are efficient to prevent dengue transmission between cities and from urban to suburban, as well to reduce the co-circulation of multiple serotypes or genotypes. Nevertheless, as revealed by the spatial analysis, once the dengue outbreak was established, its distribution was very stable and resistant to measures against COVID-19, implying the possibility to develop a precise prediction method.