<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Wu Y</submitter><funding>Key R&amp;D project in Shaanxi Province</funding><funding>National Science Foundation of China</funding><funding>Open fund of National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases</funding><pagination>2526</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC12654024</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>13(11)</volume><pubmed_abstract>Rural tropical regions face escalating threats from zoonotic AIV and dengue virus but lack sewered infrastructure for conventional wastewater surveillance. We implemented surface water-based surveillance (SWBS) in peri-urban Dhaka (Bangladesh) and Ruili (China) from July to November 2023 and coupled it with machine learning-enhanced digital epidemiology. Reverse transcription quantitative PCR (RT-qPCR) was employed to detect the M gene of AIV and to subtype H1, H5, H7, H9, and H10 in surface water. Wild bird feces (&lt;i>n&lt;/i> = 40) were collected within 3 km of positive sites to source-track AIV. For the dengue virus, a serogroup-specific RT-qPCR assay targeting the CprM gene was used. Genomic sequencing of AIV and dengue virus was performed to elucidate phylogenetic relationships with local</pubmed_abstract><journal>Microorganisms</journal><pubmed_title>Harnessing a Surface Water-Based Multifaceted Approach to Combat Zoonotic Viruses: A Rural Perspective from Bangladesh and China.</pubmed_title><pmcid>PMC12654024</pmcid><funding_grant_id>2025NC-YBXM-104</funding_grant_id><funding_grant_id>2024NITFID310</funding_grant_id><funding_grant_id>82505614</funding_grant_id><pubmed_authors>Yang X</pubmed_authors><pubmed_authors>Zahan N</pubmed_authors><pubmed_authors>Fu S</pubmed_authors><pubmed_authors>Du C</pubmed_authors><pubmed_authors>Long Y</pubmed_authors><pubmed_authors>Deng Z</pubmed_authors><pubmed_authors>Du X</pubmed_authors><pubmed_authors>Wu Y</pubmed_authors></additional><is_claimable>false</is_claimable><name>Harnessing a Surface Water-Based Multifaceted Approach to Combat Zoonotic Viruses: A Rural Perspective from Bangladesh and China.</name><description>Rural tropical regions face escalating threats from zoonotic AIV and dengue virus but lack sewered infrastructure for conventional wastewater surveillance. We implemented surface water-based surveillance (SWBS) in peri-urban Dhaka (Bangladesh) and Ruili (China) from July to November 2023 and coupled it with machine learning-enhanced digital epidemiology. Reverse transcription quantitative PCR (RT-qPCR) was employed to detect the M gene of AIV and to subtype H1, H5, H7, H9, and H10 in surface water. Wild bird feces (&lt;i>n&lt;/i> = 40) were collected within 3 km of positive sites to source-track AIV. For the dengue virus, a serogroup-specific RT-qPCR assay targeting the CprM gene was used. Genomic sequencing of AIV and dengue virus was performed to elucidate phylogenetic relationships with local</description><dates><release>2025-01-01T00:00:00Z</release><publication>2025 Nov</publication><modification>2026-05-19T03:26:56.994Z</modification><creation>2026-05-19T03:12:20.319Z</creation></dates><accession>S-EPMC12654024</accession><cross_references><pubmed>41304212</pubmed><doi>10.3390/microorganisms13112526</doi></cross_references></HashMap>