Wastewater-Informed Digital Advertising as a COVID-19 Geotargeted Neighborhood Intervention: Jefferson County, Kentucky, 2021-2022.

We sought to deliver a geotargeted digital health advertising intervention. We assessed risk of community infection through an integrated public health and wastewater rubric and delivered advertisements between November 2021 and April 2022 in Louisville, Kentucky. The average daily click-through rates for the campaigns were 0.19%, 0.15%, and 0.13%. Results show potential for digital public health interventions that are geographically anchored to subcity sewersheds and community interest and willingness to engage with targeted wastewater-themed public health messaging. (Am J Public Health. 2024;114(1):34-37. https://doi.org/10.2105/AJPH.2023.307439).

Generative AI as a Tool for Environmental Health Research Translation.

One valuable application for generative artificial intelligence (AI) is summarizing research studies for non-academic readers. We submitted five articles to Chat Generative Pre-trained Transformer (ChatGPT) for summarization, and asked the article's author to rate the summaries. Higher ratings were assigned to more insight-oriented activities, such as the production of eighth-grade reading level summaries, and summaries highlighting the most important findings and real-world applications. The general summary request was rated lower. For the field of environmental health science, no-cost AI technology such as ChatGPT holds the promise to improve research translation, but it must continue to be improved (or improve itself) from its current capability.

Generative AI as a Tool for Environmental Health Research Translation.

Generative artificial intelligence, popularized by services like ChatGPT, has been the source of much recent popular attention for publishing health research. Another valuable application is in translating published research studies to readers in non-academic settings. These might include environmental justice communities, mainstream media outlets, and community science groups. Five recently published (2021-2022) open-access, peer-reviewed papers, authored by University of Louisville environmental health investigators and collaborators, were submitted to ChatGPT. The average rating of all summaries of all types across the five different studies ranged between 3 and 5, indicating good overall content quality. ChatGPT’s general summary request was consistently rated lower than all other summary types. Whereas higher ratings of 4 and 5 were assigned to the more synthetic, insight-oriented activities, such as the production of a plain language summaries suitable for an 8 th grade reading level and identifying the most important finding and real-world research applications. This is a case where artificial intelligence might help level the playing field, for example by creating accessible insights and enabling the large-scale production of high-quality plain language summaries which would truly bring open access to this scientific information. This possibility, combined with the increasing public policy trends encouraging and demanding free access for research supported with public funds, may alter the role journal publications play in communicating science in society. For the field of environmental health science, no-cost AI technology such as ChatGPT holds the promise to improve research translation, but it must continue to be improved (or improve itself) from its current capability.

Nationwide public perceptions regarding the acceptance of using wastewater for community health monitoring in the United States.

To assess the levels of infection across communities during the coronavirus disease 2019 pandemic, researchers have measured severe acute respiratory syndrome coronavirus 2 RNA in feces dissolved in sewer water. This activity is colloquially known as sewer monitoring and is referred to as wastewater-based epidemiology in academic settings. Although global ethical principles have been described, sewer monitoring is unregulated for health privacy protection when used for public health surveillance in the United States. This study used Qualtrics XM, a national research panel provider, to recruit participants to answer an online survey. Respondents (N = 3,083) answered questions about their knowledge, perceptions of what is to be monitored, where monitoring should occur, and privacy concerns related to sewer monitoring as a public health surveillance tool. Furthermore, a privacy attitude questionnaire was used to assess the general privacy boundaries of respondents. Participants were more likely to support monitoring for diseases (92%), environmental toxins (92%), and terrorist threats (88%; e.g., anthrax). Two-third of the respondents endorsed no prohibition on location sampling scale (e.g., monitoring single residence to entire community was acceptable); the most common location category respondents wanted to prohibit sampling was at personal residences. Sewer monitoring is an emerging technology, and our study sheds light on perceptions that could benefit from educational programs in areas where public acceptance is comparatively lower. Respondents clearly communicated guard rails for sewer monitoring, and public opinion should inform future policy, application, and regulation measures.

Public Awareness of and Support for the Use of Wastewater for SARS-CoV-2 Monitoring: A Community Survey in Louisville, Kentucky.

The majority of sewer systems in the United States and other countries are operated by public utilities. In the absence of any regulation, the public perception of wastewater monitoring for population health biomarkers is an important consideration for a public utility commission when allocating resources for this purpose. We conducted a survey in August 2021 as part of an ongoing COVID-19 community prevalence study in Louisville/Jefferson County, KY, US. The survey comprised seven questions about wastewater awareness and privacy concerns and was sent to approximately 35 000 households randomly distributed within the county. A total of 1220 adults were involved in the probability sample, and data from 981 respondents were used in the analysis. A total of 2444 adults additionally responded to the convenience sample, and data from 1751 respondents were used in the analysis. The samples were weighted to obtain estimates representative of all adults in the county. Public awareness of tracking the virus that causes COVID-19 in sewers was low. Opinions strongly support the public disclosure of monitoring results. Responses showed that people more strongly supported measurements in the largest areas (>50 000 households), typically representing population levels found in a large community wastewater treatment plant. Those with a history of COVID-19 infection were more likely to support highly localized monitoring. Understanding wastewater surveillance strategies and privacy concern thresholds requires an in-depth and comprehensive analysis of public opinion for continued success and effective public health monitoring.