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Description
Thousands of human lives are lost every day due to chronic diseases, some more preventable than others. For years, the gold standard for diagnosing and monitoring these diseases has been through traditional methods such as individualized doctor-patient clinical evaluations, usually

Thousands of human lives are lost every day due to chronic diseases, some more preventable than others. For years, the gold standard for diagnosing and monitoring these diseases has been through traditional methods such as individualized doctor-patient clinical evaluations, usually involving laboratory tests. These methods, though effective, can be costly, time-consuming, and fail to encompass an overarching perspective of the health profile of the larger population. Wastewater-based epidemiology (WBE) has successfully been employed for decades as a population-level data source informing on the consumption of licit and illicit substance use. It also is showing promise for its use as a community-wide diagnostic tool for broader public health measurements. This literature review constitutes a theoretical evaluation of the potential use of WBE for monitoring the top two deadly diseases in the United States; cardiovascular disease (CVD) and cancer. Literature-reported metabolites indicative of these diseases were evaluated to determine if they were capable of being identified and monitored in wastewater. Potential analytes include cardiac-specific troponin, α-fenotroin, and inositol. Results obtained within suggest WBE could be used as a viable and economical tool to track and monitor the top deadly diseases in human populations. This methodology could be implemented in tandem with current practices in order to provide a more holistic understanding of prevalence and risk for CVD and cancer.


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Details

Title
  • Evaluating of the Potential for Assessing Cardiovascular Disease (CVD) and Cancer at the Population Level Using Analysis of Sewage-borne Biomarker Compounds
Contributors
Date Created
2020-05
Resource Type
  • Text
  • Machine-readable links