Moiz Usmani

GeoHealth is a rapidly growing, transdisciplinary field that integrates Earth and health sciences to understand the complex interactions between these domains. In 2017, the GeoHealth section of the American Geophysical Union and affiliated journal were established and both have grown rapidly since. Despite this growth, the field faces current and foreseeable challenges in translating scientific insights into action, including fragmented data infrastructure, funding gaps, and an evolving policy landscape. This commentary piece advocates for a GeoHealth Decadal Survey, a consensus‐driven report to identify priority research questions, guide workforce development, build community consensus, and inform strategic investments over the next decade.

Key Points: The editors thank the 2025 peer reviewers

Climate change amplifies many threats to human health. Despite advances in understanding climate change dynamics and impacts, there remains a critical gap in translating scientific knowledge into equitable, and community‐driven health interventions. The inaugural One Earth , One Health workshop sought to explore this gap through human‐centered design exercises involving interdisciplinary researchers from climate and Earth sciences, engineering, epidemiology, microbiology, and environmental health. Although participants did not co‐develop solutions with affected communities, they used stakeholder role‐playing to guide ideation and lay groundwork for actionable plans. Through these methods, participants identified community needs and proposed prototype solutions to alleviate health threats exacerbated by global environmental change. Prototypes were organized around infectious diseases, extreme weather, and air quality, as illustrative themes rather than an exhaustive set of risks. Key solutions included strategies for anticipatory systems and early warning (e.g., integrating environmental signals with health data), inclusive communication and infrastructure needs for responding to extreme weather events, and integrated platforms visualizing air quality trends to support tailored, context‐aware guidance beyond one‐size‐fits‐all alerts. The workshop highlighted opportunities such as leveraging machine learning, Earth observation, and real‐time surveillance to protect communities, but also noted barriers including data quality, technological redundancy, privacy, and governance challenges. Additionally, participants emphasized the need for interdisciplinary teams capable of collaborating across sectors, breaking down silos and addressing gaps in training and education. Overall, the workshop illustrates how process‐driven, human‐centered approaches can help surface user needs and generate testable prototype concepts, while underscoring the importance of direct community partnership for implementation.

Climate-sensitive infectious pathogens native to the aquatic environment require determination of hydrological and ecological conditions that support their growth and proliferation. Recent advancements in satellite technology have substantially improved the quality and utility of remotely sensed data, enabling identification of environmental proxies critical for forecasting outbreaks of climate sensitive infectious diseases. The new tools allow estimation of outbreak likelihood across spatial and temporal scales. Here, we examined technological progress enhancing the ability to quantify environmental, hydrological, and ecological indicators that can serve as predictors of pathogen presence. We synthesized findings from 1,137 peer-reviewed studies published between 1996 and 2025, employing keywords “remote sensing” or “satellite”, in conjunction with waterborne, airborne, and vector-borne infectious diseases. Our analysis highlights the growing precision of satellite-based detection of pathogen-favorable environments driven by the evolution of satellite missions—from Landsat 1 to Landsat 8, Sentinel 1 through Sentinel 6B, and SPOT 1 to SPOT 5, which brought substantial improvement in spatial, spectral, and temporal resolution. These technological advancements provide a potentially transformative public health tool, shifting from reactive response to proactive disease management. Enhanced remote sensing can empower health authorities to anticipate outbreaks, implement early intervention, and strengthen preparedness.

Climate change amplifies many threats to human health. Despite advances in understanding climate change dynamics and impacts, there remains a critical gap in translating scientific knowledge into equitable, and community-driven health interventions. The inaugural One Earth, One Health workshop sought to explore this gap through human centered design exercises involving interdisciplinary researchers from climate and earth sciences, engineering, epidemiology, microbiology, and environmental health. Although participants did not co-develop solutions with affected communities, they used stakeholder role-playing to guide ideation and lay groundwork for actionable plans. Through these methods, participants identified community needs and proposed prototype solutions to alleviate health threats exacerbated by global environmental change without getting into contentious debate about climate change. Participants focused on three examples---infectious disease, extreme weather, and air quality---while recognizing these do not encompass all health threats. Key solutions included advanced strategies for predicting infectious disease outbreaks, inclusive communication and infrastructure needs for responding to extreme weather events, and integrated platforms visualizing air quality trends to make tailored public health recommendations. The workshop highlighted opportunities such as leveraging artificial intelligence and real-time epidemiological surveillance to protect communities, but also noted barriers including data quality, technological redundancy, and limitations. Additionally, participants emphasized the need for interdisciplinary teams capable of collaborating across sectors, breaking down silos and addressing gaps in training and education. The suite of proposed strategies highlights the importance of cross-sector collaboration, interdisciplinary training, and direct community involvement in co-creating content-specific, inclusive responses for mitigating health threats amplified by global environmental change.

Background: To understand the effect of air quality on cognition, air quality measurements should reflect real-world exposure. Currently, air quality exposure is derived from outdoor air quality monitors despite older adults spending most of their time indoors. Objective: To examine if there are discrepancies between indoor particulate matter 2.5 (PM _2.5 ) at older adults’ personal residences, PM _2.5 levels measured with nearest outdoor public air monitors, and remotely accessed gridded ensemble air quality data. Methods: PM _2.5 levels collected in older adults’ residences, collected from the nearest outdoor public air quality monitors and ensemble data from Hazardous Air Quality Ensemble System (HAQES) were compared using Spearman correlation coefficients and Wilcoxon signed-rank tests. Daily PM _2.5 profiles in these homes were also examined. Results: Ambient air quality was assessed in 23 residences of older adults from October 2021 to August 2024. Indoor PM _2.5 measurement was lower than outdoor public air monitors for all but 3 homes. Estimates of PM _2.5 level from HAQES were also significantly higher than those indoors. High inter- and intra-home variability over time was observed. Spikes in daily indoor PM _2.5 levels were common, and they could exceed the United States Environmental Protection Agency (US EPA)'s recommendation for 24 -hour average. Use of home appliances and indoor activities may contribute to changes in indoor PM _2.5 level throughout the day. Conclusions: To optimally estimate air quality exposure risk, monitoring both indoor and outdoor environments is likely needed.

The incidence of vibriosis is rising globally with evidence of climate variability influencing environmental processes that support growth of pathogenic Vibrio spp. The waterborne pathogen, Vibrio vulnificus can invade wounds and has one of the highest case fatality rates in humans. The bacterium cannot be eradicated from the aquatic environment, hence climate driven environmental conditions enhancing growth and dissemination of V. vulnificus need to be understood to provide preemptive assessment of its presence and distribution in aquatic systems. To achieve this objective, satellite remote sensing was employed to quantify the association of sea surface temperature (SST) and chlorophyll‐a (chl‐a) in locations with reported V. vulnificus infections. Monthly analysis was done in two populated regions of the Gulf of Mexico—Tampa Bay, Florida, and Galveston Bay, Texas. Results indicate warm water, characterized by a 2‐month lag in SST, high concentration of phytoplankton, proxied for zooplankton using 1 month lagged chl‐a values, was statistically linked to higher odds of V. vulnificus infection in the human population. Identification of climate and ecological processes thresholds is concluded to be useful for development of an heuristic prediction system designed to determine risk of infection for coastal populations.

: Current modeling practices for environmental and sociological modulated infectious diseases remain inadequate to forecast the risk of outbreak(s) in human populations, partly due to a lack of integration of disciplinary knowledge, limited availability of disease surveillance datasets, and overreliance on compartmental epidemiological modeling methods. Harvesting data knowledge from virus transmission (aerosols) and detection (wastewater) of SARS-CoV-2, a heuristic score-based environmental predictive intelligence system was developed that calculates the risk of COVID-19 in the human population. Seasonal validation of the algorithm was uniquely associated with wastewater surveillance of the virus, providing a lead time of 7–14 days before a county-level outbreak. Using county-scale disease prevalence data from the United States, the algorithm could predict COVID-19 risk with an overall accuracy ranging between 81% and 98%. Similarly, using wastewater surveillance data from Illinois and Maryland, the SARS-CoV-2 detection rate was greater than 80% for 75% of the locations during the same time the risk was predicted to be high. Results suggest the importance of a holistic approach across disciplinary boundaries that can potentially allow anticipatory decision-making policies of saving lives and maximizing the use of available capacity and resources.

Indoor air quality (IAQ) in schools has received attention over the past decades but still lacks specific standards and regulations. This study aimed to review the impact of bioaerosol activity in indoor environments on acute respiratory diseases and explore whether carbon dioxide can be used as an indicator of bioaerosol and respiratory diseases in indoor environments in K-12 school systems. Findings suggest a lack of a consensual approach to evaluate bioaerosols impacting IAQ in indoor infrastructures, particularly in school environments; an elevated CO₂ concentration inside the school classrooms was not uncommon, and the evidence of unsatisfactory and degraded IAQ (surpassing ASHRAE standards) at public schools in rural and urban settings in one of the North Central County, Florida. It was found that CO₂ levels can be associated with bioaerosol activity, and sufficient ventilation within the space substantially reduces the airborne time of respiratory droplets and CO₂ levels. CO₂ monitoring can act as an effective, low-cost alternative to surveying or detecting the prevalence of respiratory diseases, which may hold strength through establishing critical CO₂ thresholds and, thereafter associating it with the infectious doses of pathogen activity.

Climate change raises an old disease to a new level of public health threat. The causative agent, Vibrio cholerae , native to aquatic ecosystems, is influenced by climate and weather processes. The risk of cholera is elevated in vulnerable populations lacking access to safe water and sanitation infrastructure. Predictive intelligence, employing mathematical algorithms that integrate earth observations and heuristics derived from microbiological, sociological, and weather data, can provide anticipatory decision-making capabilities to reduce the burden of cholera and save human lives. An example offered here is the recent outbreak of cholera in Malawi, predicted in advance by such algorithms.