A document by Yifan Zhou. Click on the document to view its contents.

This article provides a commentary about the state of Integrated, equitable outcomes. GeoHealth research both characterizes and predicts problems at the nexus of earth and human systems like climate change, pollution, and natural hazards. While GeoHealth excels in the area of integrated science, there is a need to improve coordinated and networked efforts to produce open science that is for and with frontline populations that are disproportionately marginalized by environmental injustice or unequal protection from environmental harms and lack of access and meaningful engagement in decision-making for a healthy environment (EPA). GeoHealth practice has the opportunity to advance environmental justice or the “fair treatment and meaningful involvement of all people regardless of race, color, national origin, or income” with respect to how research and collaboration of GeoHealth professionals supports the “development, implementation, and enforcement of environmental laws, regulations, and policies” that produce equal protection from environmental and health hazards and access to the decision-making for a health environment (EPA). Here we highlight barriers and opportunities to apply an equity-centered ICON framework to the field of GeoHealth to advance environmental justice and health equity.

Purpose:Flooding following heavy rains precipitated by hurricanes/tropical storms has previously been shown to increase fecal-oral diseases, vector-borne disease transmission and pregnancy complications during or following inundation. Remote sensing can be used to spatio-temporally resolve inundation extents for subsequent analysis of risks associated with flooding at a finer scale. Here we combined earth observations of the flooding caused by Hurricane Harvey in 2017 with Emergency Department (ED) visit data to evaluate health outcomes associated with flooding.Methods:Our study area included 1073 flooded and 1809 non-flooded census tracts in Texas which were categorized using the inundation maps from Dartmouth Flood Observatory. These maps were created using Sentinel and MODIS satellite imagery captured between 28th Aug - 4th Sep 2017 following the landfall of the hurricane. ED visits in the study area were obtained from Texas Department of State Health Services. A controlled interrupted time series design was employed using ED visits from non-flooded tracts as the control series and ED visits before a week of the landfall and through 2018 as control period. Poisson regression using generalized estimating equation with census tracts as the group variable was used to estimate the relative risk of the health outcomes associated with flooding during and following the flooded days, adjusting for the age, ethnicity, race, sex of the patient, day of week, month and year trends. Results:Flooding was associated with a 35% (95% CI: 22%-48%) increase in risk for insect stings and 24% (17%-31%) increase in risk of pregnancy complications during the flood period. Similarly, relative risks were also elevated (>1) for drowning, hypothermia, and intestinal infectious diseases in the flooded tracts. Also, in the months following the flood period, the relative risk was still elevated (>1) for pregnancy complications and insect stings while asthma and acute respiratory infections showed decreased risks. Conclusion: Earth observations have helped in understanding the health risks that are related to flooding. These earth observations can in turn be used to identify specific communities with increased health risks during and following flooding events.

The Middle East is one of the world’s most vulnerable areas to climate change, which has exacerbated environmental, agricultural, water conflict, and public health issues in the region. Here we analyze the latest climate model projections of precipitation and temperature for the very high emissions scenario, SSP5-8.5, to detect potential future changes in this region. A baseline period (1981-2010) is compared with the middle (2040-2069) and end (2070-2099) of the 21st century. The results, representing the worst-case scenario, identify the Tigris-Euphrates headwaters as the hotspot of future compounding effects of climate change in the Middle East. Those effects result from the coincidence of elevated temperature, reduced precipitation, and enhanced interannual variability of precipitation. The hotspot overlays the location of the Southeastern Anatolia Project (in Turkish, GAP) irrigation initiative. In this climate context, risks to GAP viability and downstream water security, and associated potential for water-related conflicts and migration are considerable and demand a reconsideration of the risk-benefit assessment of GAP. This need has become more urgent after the recent widespread and deadly climate-related conflicts and wildfires in summer 2021 across the Middle East that further underlined vulnerability of the region to climate extremes.

Access to accurate estimates of water withdrawal is requisite for urban planners as well as operators of critical infrastructure systems to make optimal operational decisions and investment plans to ensure reliable and affordable provisioning of water. Furthermore, identifying the key predictors of water withdrawal is important to regulators for promoting sustainable development policies to reduce water use. In this paper, we developed a rigorously evaluated predictive model, using statistical learning theory, to estimate state-level, per-capita water withdrawal as a function of various geographic, climatic and socio-economic variables. We then harnessed the data-driven predictive model to identify the key factors associated with high water-usage intensity among different sectors in the U.S. We analyzed the predictive accuracy of a range of parametric models (e.g., generalized linear models) and non-parametric, flexible learning algorithms (e.g., generalized additive models, multivariate adaptive regression splines and random forest). Our results identified irrigated farming, thermo-electric energy generation and urbanization as the most water-intensive anthropogenic activities, on a per-capita basis. Among the climate factors, precipitation was also found to be a key predictor of per-capita water withdrawal, with drier conditions associated with higher water withdrawals. Results of the first-order sensitivity analysis indicated changes between +/-10% in the future water withdrawal across the U.S., in response to precipitation changes, by the end of the 21st Century under the business-as-usual scenario. Overall, our study highlights the utility of leveraging statistical learning theory in developing data-driven models that can yield valuable insights related to the water withdrawal patterns across expansive geographical areas.

From the heated debates over the airborne transmission of the novel coronavirus to the abrupt Earth system changes caused by the sudden lockdowns, the dire circumstances resulting from the coronavirus disease 2019 (COVID-19) pandemic has brought the field of GeoHealth to the forefront of visibility in science and policy. The pandemic has inadvertently provided an opportunity to study how human response has impacted the Earth system, how the Earth system may impact the pandemic, and the capacity of GeoHealth to inform real-time policy. The lessons learned throughout our responses to the COVID-19 pandemic are shaping the future of GeoHealth.

The highlands of Ethiopia are a densely populated, agriculturally active region characterized by strong topographic contrasts. These contrasts have significant implications for agricultural productivity and for vulnerability to climate variability and change. These differing vulnerabilities are evident in analyses of economic and health outcomes over time, and they were on stark display during the major El Niño drought of 2015. To provide meaningful analysis of climate vulnerability in this region and, ultimately, to support climate resilience strategies, it is necessary to account for this topographic diversity. Recognizing this, the Government of Ethiopia has applied an “adaptation zone” approach to climate change planning, in which adaptation zones are defined in large part by agroecology. Here, we present results of studies we have performed in the Ethiopian Highlands over the past decade in which agroecosystems were applied as a lens for analyzing hydrology, land management and change, agricultural production, and nutrition under climate variability. This approach has informed a number of active development initiatives in the region, including protection of high elevation zones, farmer-led initiatives on soil and water management, and introduction of new cropping strategies. Looking forward, climate projections at the scale of the agroecosystem point to emerging risks and opportunities for resilient agricultural development in the region.

GeoHealth represents the critical intersection between the Earth and environmental sciences, and agricultural and health sciences. Following a specific request from the National Science Foundation (NSF) this report provides a series of recommendations aimed at empowering research, building fundamental workforce capacity, and improving communication around GeoHealth to the public and policy makers. This development is critical as a robust GeoHealth research enterprise is essential to global health, human and ecosystem well-being, and sustainability. The AGU community along with those from several allied societies provided the recommendations in this report; these were developed for a detailed survey and two workshops. The survey and other input revealed several broad challenges and needs, including highly siloed funding and support for researchers across institutions and societies, the inability to access or combine key datasets, and in particular the lack of clear career trajectories and support. The recommendations consist of: (i) six programmatic areas where significant attention to building a GeoHealth research enterprise is needed; (ii) approaches and concepts for four specific challenges in GeoHealth for which significant results could be enabled rapidly, within 2-3 years; (iii) ideas for developing an education/career path and for outreach; (iv) larger “moonshot” ideas that might yield very significant impacts over ca. 10 years. All of these have several common elements and themes: they leverage many directorates within NSF, including all within the GEO division; can build off of existing initiatives; are best developed through partnerships with other agencies and communities; and rely on open and FAIR data sets. Although the focus of these recommendations is toward and for the NSF, the suggestions are more general and hopefully will be considered by other funding agencies and other parts of the research enterprise in the U.S. and internationally.

Brazil has been severely affected by the COVID-19 pandemic. Temperature and humidity have been purported as drivers of SARS-CoV-2 transmission, but no consensus has been reached in the literature regarding the relative roles of meteorology, governmental policy, and mobility on transmission in Brazil. We compiled data on meteorology, governmental policy, and mobility in Brazil’s 26 states and one federal district from June 2020 to August 2021. Associations between these variables and the time-varying reproductive number (Rt) of SARS-CoV-2 were examined using generalized additive models fit to data from the entire fifteen-month period and several shorter, three-month periods. Accumulated local effects and variable importance metrics were calculated to analyze the relationship between input variables and Rt. We found that transmission is strongly influenced by unmeasured sources of between-state heterogeneity and the near-recent trajectory of the pandemic. Increased temperature generally was associated with decreased transmission and specific humidity with increased transmission. However, the impact of meteorology, policy, and mobility on Rt varied in direction, magnitude, and significance across our study period. This time variance could explain inconsistencies in the published literature to date. While meteorology weakly modulates SARS-CoV-2 transmission, daily or seasonal weather variations alone will not stave off future surges in COVID-19 cases in Brazil. Investigating how the roles of environmental factors and disease control interventions may vary with time should be a deliberate consideration of future research on the drivers of SARS-CoV-2 transmission.