Integrating wastewater surveillance and meteorological data to monitor seasonal variability of enteric and respiratory pathogens for infectious disease control in Dhaka city

IF 4.5 2区医学 Q1 INFECTIOUS DISEASES

International journal of hygiene and environmental health Pub Date : 2025-05-21 DOI:10.1016/j.ijheh.2025.114591

Farjana Jahan , Mizanul Islam Nasim , Yuke Wang , Sk Md Kamrul Bashar , Rezaul Hasan , Afroza Jannat Suchana , Nuhu Amin , Rehnuma Haque , Md Abul Hares , Akash Saha , Mohammad Enayet Hossain , Mohammed Ziaur Rahman , Megan Diamond , Suraja Raj , Stephen Patrick Hilton , Pengbo Liu , Christine Moe , Mahbubur Rahman

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引用次数: 0

Abstract

Background

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.

Methods

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.

Results

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.

Conclusion

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.

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整合废水监测和气象数据，监测达喀市肠道和呼吸道病原体的季节性变化，以控制传染病

季节气象变化影响传染病的传播。废水监测有助于了解病原体传播动态，特别是在孟加拉国等气候脆弱国家的城市地区。方法分析了孟加拉国达卡54周的废水监测、临床监测和气象数据。对11个地点的样本进行了霍乱弧菌（V. cholae）、SARS-CoV-2、肠沙门氏菌亚种肠血清型伤寒（S. Typhi）和A组轮状病毒检测。腹泻病监测数据来自icddr，b和孟加拉国气象部门的气象数据。采用校正了地点和时间变化的回归模型进行统计分析。结果雨季后腹泻病监测新兵中霍乱确诊病例比例最高(系数：2.53；95% CI: 0.41 ~ 4.67；p = 0.029)。废水中霍乱弧菌log10浓度与季风前呈正相关(系数：0.93；95% CI: 0.26 ~ 1.58；p = 0.010)，而SARS-CoV-2在季风期间达到峰值(系数：1.85；95% CI: 0.96 ~ 2.73；p & lt;0.001)。伤寒沙门氏菌和轮状病毒log10浓度与季风前呈负相关(系数：- 0.96；95% CI:−1.68 ~−0.27；P = 0.011和- 0.84；95% CI: - 1.17 ~ - 0.50；p & lt;分别为0.001)。温度正影响霍乱弧菌的log10浓度(相对值：0.09；95% CI: 0.02 ~ 0.15；p = 0.014)和SARS-CoV-2 (adj. coef: 0.19；95% CI: 0.10 ~ 0.27；p & lt;0.001)，但与轮状病毒呈负相关(形容词系数：- 0.06；95% CI:−0.10 ~−0.03；p & lt;0.001)。在病原体阳性样本和温度之间也发现了类似的关联。结论季节和气象因素（尤其是温度）会影响废水中病原体的分布模式和丰度，有助于了解不同天气模式下的疾病传播。

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来源期刊

International journal of hygiene and environmental health 医学-传染病学

CiteScore

11.50

自引率

5.00%

发文量

151

审稿时长

22 days

期刊介绍： The International Journal of Hygiene and Environmental Health serves as a multidisciplinary forum for original reports on exposure assessment and the reactions to and consequences of human exposure to the biological, chemical, and physical environment. Research reports, short communications, reviews, scientific comments, technical notes, and editorials will be peer-reviewed before acceptance for publication. Priority will be given to articles on epidemiological aspects of environmental toxicology, health risk assessments, susceptible (sub) populations, sanitation and clean water, human biomonitoring, environmental medicine, and public health aspects of exposure-related outcomes.