Jahan Farjana, Nasim Mizanul Islam, Wang Yuke, Kamrul Bashar Sk Md, Hasan Rezaul, Suchana Afroza Jannat, Amin Nuhu, Haque Rehnuma, Hares Md Abul, Saha Akash, Hossain Mohammad Enayet, Rahman Mohammed Ziaur, Diamond Megan, Raj Suraja, Hilton Stephen Patrick, Liu Pengbo, Moe Christine, Rahman Mahbubur
Environmental Health and WASH, International Centre for Diarrhoeal Disease Research, Bangladesh.
Environmental Health and WASH, International Centre for Diarrhoeal Disease Research, Bangladesh.
Int J Hyg Environ Health. 2025 Jun;267:114591. doi: 10.1016/j.ijheh.2025.114591. Epub 2025 May 21.
Seasonal meteorological variations influence the spread of infectious diseases. Wastewater surveillance helps understanding pathogen transmission dynamics, particularly in urban areas of climate-vulnerable countries like Bangladesh.
We analysed 54 weeks of wastewater surveillance, clinical surveillance, and meteorological data from Dhaka, Bangladesh. Samples from 11 sites were tested for Vibrio cholerae (V. cholerae), SARS-CoV-2, Salmonella enterica subspecies enterica serovar Typhi (S. Typhi), and Group A rotavirus. Diarrhoeal Disease Surveillance data were sourced from icddr,b, and meteorological data from the Bangladesh Meteorological Department. Regression models adjusted for site and time variations were used for statistical analysis.
Proportion of confirmed cholera cases among the diarrhoeal disease surveillance recruits were highest during post-monsoon (coef: 2.53; 95 % CI: 0.41 to 4.67; p = 0.029). V. cholerae log10 concentrations in wastewater were positively associated with pre-monsoon (coef: 0.93; 95 % CI: 0.26 to 1.58; p = 0.010), while SARS-CoV-2 peaked during monsoon (coef: 1.85; 95 % CI: 0.96 to 2.73; p < 0.001). S. Typhi and rotavirus log10 concentrations showed negative associations with pre-monsoon (coef: -0.96; 95 % CI: -1.68 to -0.27; p = 0.011, and -0.84; 95 % CI: -1.17 to -0.50; p < 0.001, respectively). Temperature positively influenced log10 concentrations of V. cholerae (adj. coef: 0.09; 95 % CI: 0.02 to 0.15; p = 0.014) and SARS-CoV-2 (adj. coef: 0.19; 95 % CI: 0.10 to 0.27; p < 0.001), but negatively associated with rotavirus (adj. coef: -0.06; 95 % CI: -0.10 to -0.03; p < 0.001). Similar associations were found between pathogen-positive samples and temperature.
Our study shows that seasonal, and meteorological factors (particularly temperature) influence the patterns and abundance of pathogens in wastewater and help in understanding disease transmission across different weather patterns.
季节性气象变化会影响传染病的传播。废水监测有助于了解病原体传播动态，尤其是在孟加拉国等气候脆弱国家的城市地区。
我们分析了来自孟加拉国达卡的54周废水监测、临床监测和气象数据。对11个地点的样本进行了霍乱弧菌、新冠病毒、伤寒沙门氏菌和A组轮状病毒检测。腹泻病监测数据来自孟加拉国腹泻病研究国际中心，气象数据来自孟加拉国气象局。采用针对地点和时间变化进行调整的回归模型进行统计分析。
腹泻病监测新发病例中确诊霍乱病例的比例在季风后最高（系数：2.53；95%置信区间：0.41至4.67；p = 0.029）。废水中霍乱弧菌的log10浓度与季风前呈正相关（系数：0.93；95%置信区间：0.26至1.58；p = 0.010），而新冠病毒在季风期间达到峰值（系数：1.85；95%置信区间：0.96至2.73；p < 0.001）。伤寒沙门氏菌和轮状病毒的log10浓度与季风前呈负相关（系数分别为：-0.96；95%置信区间：-1.68至-0.27；p = 0.011，以及-0.84；95%置信区间：-1.17至-0.50；p < 0.001）。温度对霍乱弧菌（调整后系数：0.09；95%置信区间：0.
