Correlation study on influenza epidemic in representative 5 cities in the middle and lower reaches of the Yangtze River based on detection of oseltamivir metabolite in wastewater
10.11665/j.issn.1000-5048.2024062401
- VernacularTitle:基于污水中奥司他韦代谢物检测对长江中下游代表性5城市流感流行情况的相关性研究
- Author:
Chen SHI
1
,
2
;
Manlei ZHANG
;
Xinxin ZHOU
;
Mengyi CHEN
;
Chenzhi HOU
;
Bin DI
Author Information
1. 中国药科大学药物分析系, 南京 210009
2. 国家禁毒委员会办公室-中国药科大学禁毒关键技术联合实验室, 南京 210009
- Publication Type:Journal Article
- Keywords:
waste water-based epidemiology;
oseltamivir carboxylate;
influenza;
seasonal epidemics
- From:
Journal of China Pharmaceutical University
2025;56(2):155-159
- CountryChina
- Language:Chinese
-
Abstract:
By selecting stable and detectable drug prototypes or metabolites in sewage samples, near real-time detection of disease conditions can be achieved. This study selected oseltamivir carboxylate, the primary metabolite of first-line antiviral oseltamivir, as a biomarker. Based on the concentration of oseltamivir carboxylate in wastewater, the consumption and usage rate of oseltamivir were calculated by reverse engineering. Quarterly sampling was conducted at 46 urban sewage treatment plants in representative 5 cities in the middle and lower reaches of the Yangtze River, from November 2022 to December 2023. The concentration range of oseltamivir acid in sewage samples is 1.270−1 279 ng/L, the daily mass load of oseltamivir per 1 000 inhabitants in the surveyed cities ranged from 9.560 to 544.7 mg/d, and the average utilization rate is 0.06‰−3.63‰. The research results indicate that in March 2023, Wuxi City experienced a spring influenza peak, while Bengbu, Tongling, Suzhou, and Changzhou City experienced a small summer influenza peak in May. In November and December 2023, Wuxi, Changzhou, and Bengbu City experienced a winter influenza peak, the results are consistent with the official statistics of the National Center for Disease Control and Prevention and the National Influenza Center, which reflect the influenza epidemic situation in southern cities. The integration of this methodology with clinical diagnostic rates could provide near real-time data support for future influenza prevention and control strategies.
