The field of environmental health is facing increasingly complex challenges that require innovative approaches to research and decision-making. One promising strategy is to expand the participation of the community, which has the potential to enhance the effectiveness and relevance of health sciences. Although this approach is relatively new in the field of environmental health, it has a long history of success in other scientific disciplines such as ornithology, where citizen science initiatives like bird counts have been taking place for over a century, and geography where land use surveys were carried out by school children in Britain in the 1930s and 1940s.
Crowdsourcing could achieve in months what would take years through conventional research approaches. Passive Citizen science and digital citizen panels speed up research by increasing the numbers of participants and data points, making data collection more cost-effective and efficient, and by improving the engagement and participation of community members. “Extreme” citizen science and quantified-self approaches would go even further to involve the public in co-creation, co-design, data analysis, interpretation, and, ultimately, public health actions. Awareness to stay fit and healthy and the use of fitness trackers continues to rise, especially among a growing aging population with disposable income to burn, but this hasn't yet resulted in the rise of Collaboratory Health Research.
Crowdsourced online information has been used for tracking the spread of biological contaminants and infectious diseases for several years now. While games like Flu-City, and Big Tech- or government-supported programs like HealthMap, FluTracking, EPA maps, many other apps ceased to exist. Sickweather, launched in 2011 reached an audience of 10 million daily active users during the heights of the COVID-19 pandemic, filed for bankruptcy in 2022. Apparently their "NoPeek” privacy solution wasn't sufficient for gaining citizens’ trust and engagement.
Despite the early promise of passive crowdsourcing, it often struggles with accuracy issues. For example, Google Flu Trends (launched in 2008 and used aggregated search query data, initially claiming 97% accuracy when compared to CDC data) was criticized for not being able to predict the 2009 H1N1 pandemic and overestimating influenza-like activity in the United States during the 2012–2013 flu season. Web-based crowdsourcing was used to digitize geospatial information on thousands of public drinking water service areas in California.
Controlled community-team-based studies (active crowdsourcing) also report larger numbers for disease incidence and side effects of drugs (adverse event preventing from daily activities). This, however, is not an overestimate - and it is in line with recent findings of circulating unbound spike protein after COVID-19 vaccination.
Communities are better able to provide key ground-truthed information. People's perception of environmental health hazards may not be consistently associated with their health outcomes since their health vulnerabilities vary, depending on the age, gender and other variables. Citizen scientists can, however, operate sensors to collect more objective and accurate data - continuously and in real-time. In our community-based studies, these were gut microbiome, urine, blood, environmental and exhaled air samples. The development of portable air monitors, sensing platforms for detection of various inorganic, organic, and biological analytes and home urine labs has made it possible to track changes in environmental health on a global scale. While there are limitations to sensor technology in terms of sensitivity and selectivity, they continue to evolve along with participatory health approaches and have the potential to greatly enhance our understanding of the impact of the environment on human health.
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