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Case report: Zika surveillance complemented with wastewater and mosquito testingResearch in context
- Source :
- EBioMedicine, Vol 101, Iss , Pp 105020- (2024)
- Publication Year :
- 2024
- Publisher :
- Elsevier, 2024.
-
Abstract
- Summary: Background: In June 2023, a local cluster of 15 Zika cases was reported in a neighbourhood in Northeastern Singapore. The last significant local transmission of Zika virus (ZIKV) with more than 450 cases was in 2016–2017. To monitor the situation and mitigate further transmission, case, entomological and wastewater-based surveillance were carried out. Methods: Primary healthcare practitioners and the community were alerted to encourage timely case identification. Surveillance was enhanced through testing of Aedes mosquitoes collected from the National Gravitrap surveillance system, and wastewater samples were collected from a network of autosamplers deployed at manholes across the country. Findings: ZIKV RNA was detected in mosquito pools (3/43; 7%) and individual mosquitoes (3/82; 3.7%) captured, and in wastewater samples (13/503) collected from the vicinity of the cluster of cases. Respective samples collected from other sites across the country were negative. The peak detection of ZIKV RNA in mosquitoes and wastewater coincided temporally with the peak in the number of cases in the area (15–25 May 2023). Interpretation: The restriction of ZIKV signals from wastewater and mosquitoes within the neighbourhood suggested limited ZIKV transmission. The subsequent waning of signals suggested effectiveness of control measures. We demonstrate the utility of wastewater-based surveillance of ZIKV, which complements existing case- and entomological-based surveillance. The non-intrusive approach is particularly useful to monitor diseases such as Zika, which generally causes silent or mild infections, but may cause severe outcomes such as congenital Zika syndrome. Funding: This study was funded by Singapore’s Ministry of Finance and the National Environment Agency, Singapore.
Details
- Language :
- English
- ISSN :
- 23523964
- Volume :
- 101
- Issue :
- 105020-
- Database :
- Directory of Open Access Journals
- Journal :
- EBioMedicine
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.f5556cbe33f744ccb1e75cd7a43dda04
- Document Type :
- article
- Full Text :
- https://doi.org/10.1016/j.ebiom.2024.105020