Measles cases are surging in the United States, with over 2,500 confirmed cases reported since the start of January 2025, and three deaths, according to the Centers for Disease Control and Prevention. This increase comes a year after Texas reported a measles case that initiated a multi-state outbreak. As vaccination rates decline, scientists are exploring innovative methods to detect and prevent the spread of the disease, including wastewater surveillance.

Wastewater analysis, which involves examining sewage for biological markers, gained prominence during the COVID-19 pandemic. "Wastewater contains saliva, urine, feces, shed skin, and more. You could consider it a rich biological sample," explained Dr. Emily Carter, a researcher at the forefront of this effort. The technique allows scientists to identify the presence of the measles virus in a community, even before individuals show symptoms or seek medical attention. This early detection can provide crucial time for public health officials to implement targeted interventions, such as vaccination campaigns and isolation measures.

The application of wastewater surveillance for measles is still in its early stages, but initial results are promising. Researchers are using advanced techniques, including AI-powered data analysis, to identify and quantify the virus in wastewater samples. AI algorithms can detect subtle patterns and anomalies in the data, providing insights that might be missed by traditional methods. This technology allows for a more comprehensive and timely understanding of measles transmission dynamics.

Globally, significant progress has been made in combating measles through vaccination efforts. The World Health Organization (WHO) estimates that measles vaccinations saved nearly 59 million lives since 2000, leading to an 88% drop in measles deaths between 2000 and 2024. Despite these gains, an estimated 95,000 people died from measles. The resurgence of measles in the U.S. underscores the importance of maintaining high vaccination rates and exploring new surveillance methods.

The use of AI in wastewater surveillance raises important ethical considerations. The collection and analysis of wastewater data must be conducted in a way that protects individual privacy and prevents discrimination. Public health officials must ensure transparency and engage with communities to address concerns about data security and potential misuse.

Looking ahead, researchers plan to refine wastewater surveillance techniques and integrate them with other public health data sources, such as electronic health records and social media data. This integrated approach could provide a more complete picture of measles transmission and inform more effective prevention strategies. The ongoing efforts to combat measles highlight the importance of innovation and collaboration in protecting public health.