Irrigation plays a critical role in global food production and climate adaptation and exercises profound influence over humanity's water use. Yet despite its critical importance, there is a persistent lack of understanding of fine-scale irrigation patterns across the planet, knowledge which is essential for informing global food security and sustainability targets. Utilizing either statistical downscaling or remote sensing approaches, existing global irrigation datasets are constrained by coarse spatial resolutions, a lack of timeliness, or varying robustness and reliability. To address this gap, here we integrate multi-source Earth observation and environmental datasets and use machine learning to develop a medium-resolution (30 m) global irrigated area dataset for the 2023/24 growing season. Within existing cropland extent, we leverage a newly compiled set of georeferenced irrigated (N=230,683) and non-irrigated (N=153,194) ground-truth points and integrate seasonal vegetation metrics derived from Landsat 8/9 imagery with agroecological-zone information and hydroclimatic and topographic variables. We subsequently develop and evaluate two machine-learning frameworks, a continental Agro-Ecological Zone (AEZ) tile-based framework and a continental-scale framework, and apply the best-performing approach for each continent. Evaluation using held-out test samples yielded a global accuracy of 80.5 ± 2.1%. The resulting maps were also validated against independent global and national irrigation datasets and statistics, demonstrating broad agreement in the spatial distribution of irrigated areas. This approach is robust and reliable because it is built on a harmonized global ground-truth database, incorporates multiple predictors, and is rigorously validated using independent datasets. All code, ground-truth, and data products are freely and publicly available and can serve as a robust, scale-neutral, and fully reproducible framework for fine-resolution irrigation mapping. These advances provide the critical and long-needed foundation for near-real-time monitoring and early warning systems, and fine-scale land and water resource management.

ABSTRACTQuantifying ecosystem services provided by mobile species like insectivorous bats remains a challenge, particularly in understanding where and how these services vary over space and time. Bats are known to offer valuable ecosystem services, such as mitigating insect pest damage to crops, reducing pesticide use, and reducing nuisance pest populations. However, determining where bats forage is difficult to monitor. In this study, we use a weather‐radar‐based bat‐monitoring algorithm to estimate bat foraging distributions during the peak season of 2019 in California's Northern Central Valley. This region is characterized by valuable agricultural crops and significant populations of both crop and nuisance pests, including midges, moths, mosquitos, and flies. Our results show that bat activity is high but unevenly distributed, with rice fields experiencing significantly elevated activity compared to other land cover types. Specifically, bat activity over rice fields is 1.5 times higher than over any other land cover class and nearly double that of any other agricultural land cover. While irrigated rice fields may provide abundant prey, wetland and water areas showed less than half the bat activity per hectare compared to rice fields. Controlling for land cover type, we found bat activity significantly associated with higher flying insect abundance, indicating that bats forage in areas where crop and nuisance pests are likely to be found. This study demonstrates the effectiveness of radar‐based bat monitoring in identifying where and when bats provide ecosystem services.

The increasing availability of high-resolution climate data has greatly expanded the study of how the climate impacts humans and society. However, the processing of these multi-dimensional datasets poses significant challenges for researchers in this growing field, most of whom are social scientists. This paper introduces stagg, or “space-time aggregator”, a new R package that streamlines three critical components of climate data processing for impacts analysis: nonlinear transformation, spatial and temporal aggregation, and spatial weighting by social or economic variables. The package consolidates the data processing pipeline into a few lines of code, lowering barriers to entry for researchers and facilitating a larger and more diverse research community. The paper provides an overview of stagg's functions, followed by an applied example demonstrating the package's utility in climate impacts research. stagg has the potential to be a valuable tool in generating evidence-based estimates of the likely impacts of future climate change.

Mosquito-borne diseases contribute substantially to the global burden of disease, and are strongly influenced by environmental conditions. Ongoing and rapid environmental change necessitates improved understanding of the response of mosquito-borne diseases to environmental factors like temperature, and novel approaches to mapping and monitoring risk. Recent development of trait-based mechanistic models has improved understanding of the temperature dependence of transmission, but model predictions remain challenging to validate in the field. Using West Nile virus (WNV) as a case study, we illustrate the use of a novel remote sensing-based approach to mapping temperature-dependent mosquito and viral traits at high spatial resolution and across the diurnal cycle. We validate the approach using mosquito and WNV surveillance data controlling for other key factors in the ecology of WNV, finding strong agreement between temperature-dependent traits and field-based metrics of risk. Moreover, we find that WNV infection rate in mosquitos exhibits a unimodal relationship with temperature, peaking at ~24.6-25.2°C, in the middle of the 95% credible interval of optimal temperature for transmission of WNV predicted by trait-based mechanistic models. This study represents one of the highest resolution validations of trait-based model predictions, and illustrates the utility of a novel remote sensing approach to predicting mosquito-borne disease risk.

Machine learning has revolutionized environmental sciences by estimating scarce environmental data, such as air quality, land cover type, wildlife population counts, and disease risk. However, current methods for validating these models often ignore the spatial or temporal structure commonly found in environmental data, leading to inaccurate evaluations of model quality. This paper outlines the problems that can arise from such validation methods and describes how to avoid erroneous assumptions about training data structure. In an example on air quality estimation, we show that a poor model with an r ^2 of 0.09 can falsely appear to achieve an r ^2 value of 0.73 by failing to account for Simpson’s paradox. This same model’s r ^2 can further inflate to 0.82 when improperly splitting data. To ensure high-quality synthetic data for research in environmental science, justice, and health, researchers must use validation procedures that reflect the structure of their training data.

Efficiently managing agricultural irrigation is vital for food security today and into the future under climate change. Yet, evaluating agriculture’s hydrological impacts and strategies to reduce them remains challenging due to a lack of field-scale data on crop water consumption. Here, we develop a method to fill this gap using remote sensing and machine learning, and leverage it to assess water saving strategies in California’s Central Valley. We find that switching to lower water intensity crops can reduce consumption by up to 93%, but this requires adopting uncommon crop types. Northern counties have substantially lower irrigation efficiencies than southern counties, suggesting another potential source of water savings. Other practices that do not alter land cover can save up to 11% of water consumption. These results reveal diverse approaches for achieving sustainable water use, emphasizing the potential of sub-field scale crop water consumption maps to guide water management in California and beyond.

School closures may reduce the size of social networks among children, potentially limiting infectious disease transmission. To estimate the impact of K–12 closures and reopening policies on children's social interactions and COVID-19 incidence in California's Bay Area, we collected data on children's social contacts and assessed implications for transmission using an individual-based model. Elementary and Hispanic children had more contacts during closures than high school and non-Hispanic children, respectively. We estimated that spring 2020 closures of elementary schools averted 2167 cases in the Bay Area (95% CI: −985, 5572), fewer than middle (5884; 95% CI: 1478, 11.550), high school (8650; 95% CI: 3054, 15 940) and workplace (15 813; 95% CI: 9963, 22 617) closures. Under assumptions of moderate community transmission, we estimated that reopening for a four-month semester without any precautions will increase symptomatic illness among high school teachers (an additional 40.7% expected to experience symptomatic infection, 95% CI: 1.9, 61.1), middle school teachers (37.2%, 95% CI: 4.6, 58.1) and elementary school teachers (4.1%, 95% CI: −1.7, 12.0). However, we found that reopening policies for elementary schools that combine universal masking with classroom cohorts could result in few within-school transmissions, while high schools may require masking plus a staggered hybrid schedule. Stronger community interventions (e.g. remote work, social distancing) decreased the risk of within-school transmission across all measures studied, with the influence of community transmission minimized as the effectiveness of the within-school measures increased.

Mosquito-borne diseases (MBD) threaten over 80% of the world’s population, and are increasing in intensity and shifting in geographical range with land use and climate change. Mitigation hinges on understanding disease-specific risk profiles, but current risk maps are severely limited in spatial resolution. One important determinant of MBD risk is temperature, and though the relationships between temperature and risk have been extensively studied, maps are often created using sparse data that fail to capture microclimatic conditions. Here, we leverage high resolution land surface temperature (LST) measurements, in conjunction with established relationships between air temperature and MBD risk factors like mosquito biting rate and transmission probability, to produce fine resolution (70 m) maps of MBD risk components. We focus our case study on West Nile virus (WNV) in the San Joaquin Valley of California, where temperatures vary widely across the day and the diverse agricultural/urban landscape. We first use field measurements to establish a relationship between LST and air temperature, and apply it to Ecosystem Spaceborne Thermal Radiometer Experiment data (2018–2020) in peak WNV transmission months (June–September). We then use the previously derived equations to estimate spatially explicit mosquito biting and WNV transmission rates. We use these maps to uncover significant differences in risk across land cover types, and identify the times of day which contribute to high risk for different land covers. Additionally, we evaluate the value of high resolution spatial and temporal data in avoiding biased risk estimates due to Jensen’s inequality, and find that using aggregate data leads to significant biases of up to 40.5% in the possible range of risk values. Through this analysis, we show that the synergy between novel remote sensing technology and fundamental principles of disease ecology can unlock new insights into the spatio-temporal dynamics of MBDs.

Background Large-scale school closures have been implemented worldwide to curb the spread of COVID-19. However, the impact of school closures and re-opening on epidemic dynamics remains unclear. Methods We simulated COVID-19 transmission dynamics using an individual-based stochastic model, incorporating social-contact data of school-aged children during shelter-in-place orders derived from Bay Area (California) household surveys. We simulated transmission under observed conditions and counterfactual intervention scenarios between March 17-June 1, and evaluated various fall 2020 K-12 reopening strategies. Findings Between March 17-June 1, assuming children <10 were half as susceptible to infection as older children and adults, we estimated school closures averted a similar number of infections (13,842 cases; 95% CI: 6,290, 23,040) as workplace closures (15,813; 95% CI: 9,963, 22,617) and social distancing measures (7,030; 95% CI: 3,118, 11,676). School closure effects were driven by high school and middle school closures. Under assumptions of moderate community transmission, we estimate that fall 2020 school reopenings will increase symptomatic illness among high school teachers (an additional 40.7% expected to experience symptomatic infection, 95% CI: 1.9, 61.1), middle school teachers (37.2%, 95% CI: 4.6, 58.1), and elementary school teachers (4.1%, 95% CI: -1.7, 12.0). Results are highly dependent on uncertain parameters, notably the relative susceptibility and infectiousness of children, and extent of community transmission amid re-opening. The school-based interventions needed to reduce the risk to fewer than an additional 1% of teachers infected varies by grade level. A hybrid-learning approach with halved class sizes of 10 students may be needed in high schools, while maintaining small cohorts of 20 students may be needed for elementary schools. Interpretation Multiple in-school intervention strategies and community transmission reductions, beyond the extent achieved to date, will be necessary to avoid undue excess risk associated with school reopening. Policymakers must urgently enact policies that curb community transmission and implement within-school control measures to simultaneously address the tandem health crises posed by COVID-19 and adverse child health and development consequences of long-term school closures.

Introduction French Guiana is a French territory located in South America, surrounded by Brazil, Suriname, and the Atlantic Ocean. Despite the progress of France regarding HIV and AIDS services, French Guiana remains active with 907 new cases each year for every 10 000 inhabitants [1]. Furthermore, although progress has been made in urban areas, the rate of contamination continues to increase in rural and border regions [2]. Indeed, border areas represent a particular challenge, containing a high-risk population [3] with 37% of people living with HIV (PLHIV) diagnosed at an advanced stage (< 200 CD4+ cells/μl) [2], 46.6% of seropositive patients lost to follow-up (unpublished data from French Guiana primary health center – CDPS – and AIDS coordination – COREVIH, 2015). Similarly, Brazil is also a country demonstrably committed to HIV/AIDS prevention and care, making history in 1996 when its national HIV/AIDS program introduced universal access to HIV antiretrovirals. However, its borders remain vulnerable to HIV, particularly the North, which is more rural and whose HIV services and infrastructure are less developed [4]. Thus, two countries with different health systems committed to fight HIV have struggled to control HIV at their shared border. Personnel scarcity, rapid turnover, language and HIV-recommendation differences have hampered communication but both sides have recognized common goals. In the past decade, this has generated a growing level of interactions between health professionals and nongovernmental organizations (NGOs) from both countries, ultimately leading to a shared solution. The complexity of this region and the current failure to deliver optimal care called for an innovative and global approach, with an emphasis on cooperation between French Guiana and Brazil [4]. Currently, the French Guianese NGO !Dsanté, the Brazilian NGO DPAC Fronteira, and the main French Guianese hospital, Centre Hospitalier Andrée Rosemon, are working together to implement an ongoing project: Oyapock Cooperation Health (OCS in French and Portuguese). These field notes discuss the OCS project and its personalized approach in controlling the HIV epidemic in this area. The artificial limit dividing care at the Oyapock border The French and Brazilian border is defined by the Oyapock river, with small towns and villages clustered along its shores on either side. On the French side, the largest of these towns is St Georges, official population 4065 [5]. Not far along river, lies the Brazilian city of Oiapoque, with around 25 000 inhabitants [6] (Fig. 1). This region presents as continuous in climate, culture and people, mostly of Brazilian or indigenous (wayampi, teko, karipuna and palikur) descent. It is a site of interconnected movement and exchange, with nothing more than a short boat ride, drive or even swim to attain the other shore (Fig. 2). The Brazilian border represents a site of fallback for clandestine gold miners, originating from Brazil and working in French Guiana, and canoemen, resulting in over half of the population being transient [4]. The undocumented and illegal gold miners from unsanitary mining sites flock to Oiapoque for supplies, medical care or leisure [7]. Furthermore, the canoemen whose work demands movement along the Oyapock river present high rates of HIV infection and sexually risky behavior [2,8]. The population is largely illiterate and predominantly men [4]. Prostitution for miners and sexual tourists is particularly developed, resulting in many female sex workers with high percentages of HIV seropositivity and many who never get tested for HIV [3]. In addition, the population is vulnerable because of addictions or financial insecurity [9]. The Oyapock region, therefore, presents unstable populations and elevated risks for HIV promulgation [2].Fig. 1: Improvements of HIV treatment, care and prevention projected from 2017 to 2020 by Oiapoque Cooperation Health in St Georges, French Guiana and Oiapoque, Brazil.Fig. 2: Oyapock river and the city of Oiapoque, Brazil.In the Oyapock border area, resources to fight HIV are limited. On the French side, a ‘Centre Délocalisé de Prévention et de Soins’ (CDPS), or Primary Care Center, is located in St Georges. There, 40 PLHIV are treated, 28 of whom live in the city of Oiapoque (CDPS unpublished data, June 2017). The nearest hospital in French Guiana is in Cayenne, is 3 h away. On the Brazilian side, a hospital is present, but lacks an infectious disease physician and the capacities to screen, follow-up and treat HIV. Residents of Oiapoque must either go to the hospital in Macapa, which, if the road is passable, may take up to 12 h in the rainy season, or cross the river to the CDPS to obtain treatment (Fig. 1). Being treated in Macapa demands that patients take an employment leave, pay for housing and food and stay several days to complete tests. Some PLHIV from the Brazilian side, therefore, choose to be treated in French Guiana, or are simply lost to follow-up. Some are treated on both sides, without communication or continuum of care between both systems. Clearly, care needs to be drastically improved in this area, but most importantly it needs to happen in a coordinated fashion [4,10]. Breaking limits and innovating in response to the particularities of the area OCS is an ongoing 3-year project that proposes several improvements to the existing measures taken against HIV/AIDS. Its main goal consists of stopping the HIV epidemic along the border by developing a cross-border prevention and care network (Fig. 1). An infectious disease physician has been stationed in this border area to coordinate the combination of different approaches to stop HIV transmission. First and foremost, OCS aims to spearhead a rigorous screening campaign to uncover a largely invisible epidemic (Fig. 1). By 2018, every person seeking care of any sort at the CDPS will be systematically offered an HIV test. Targeted screening is being carried out on both sides of the border at sites frequented by particularly high-risk populations. OCS adopts UNAIDS's 90-90-90 goals in uncovering at least 90% of the hidden epidemic, treating 90% of the known PLHIV, with 90% of those treated with an undetectable viral load [11]. To accomplish this, OCS also aims to develop availability and accessibility of care. OCS takes a multilateral approach in ensuring accessibility to care. In Oiapoque, OCS aims to help implement the necessary infrastructure to screen, follow-up and treat HIV. On both sides of the border, mediators facilitate communication between institutions of care and HIV-positive patients, as well as aid patients in accessing their rights. DPAC Fronteira, one of the contributors of OCS, is one of the organizations, which provides such mediators. It is currently putting workshops into place concerning sexual and reproductive health (SRH) and HIV prevention for the general population and key groups (Fig. 3). In the future, such mediators will equally be present at the site of DPAC Fronteira's ‘centro de apoio,’ which is in the planning process. This will be a ‘housing first’ initiative providing around 10 beds to individuals who need medical, therapeutic and social assistance at certain key instances in their lives. Considering the low level of stability in the region, particularly concerning housing, and the mobility of the population, this sub-project will address an important issue specific to the area. Another way OCS aims to empower the patient is through therapeutic education currently being introduced at the CDPS.Fig. 3: DPAC Fronteira hosts a sexual and reproductive health workshop for middle school children.Other preventive measures are to be reinforced or put into place by OCS. Postexposure prophylaxis (PEP) and preexposure prophylaxis (PrEP) will be offered as a preventive treatment measure at the CDPS at St Georges. PrEP promises to be particularly beneficial for at-risk populations such as sex workers and men who have sexual relations with men. Furthermore, OCS has already begun training key members of the community in SRH education. As much of the community is not comfortable with reading, OCS strategically recruits key individuals (ex. health professionals, teachers) already in place as verbal and visual educators. This includes equipping them with knowledge about SRH and the available care in the area, as well as granting them a set of tools to effectively communicate this knowledge. For example, they are trained in the Theater of the Oppressed, which is a style of theatre, which allows interaction with the audience (Fig. 4). Each trained individual is then supported in creating their own project contributing to the education and sexual well being of the community. For example, one middle school teacher from St Georges plans to train groups of students in the Theater of the Oppressed such that they can present SRH on both sides of the border (students in St Georges are bilingual). We hope that the interactive quality of this type of theater will allow students to witness different experiences and perspectives concerning SRH in the area.Fig. 4: Key individuals from both sides of the border are trained in the Theater of the Oppressed.Conclusion The Franco-Brazilian border, like many borders worldwide, is a unique region presenting challenges unique to its geography, populations and political climate. Its specificities have led to suboptimal care in the past for PLHIV in the area, and therefore, calls for a deviation from traditional approaches. OCS is a binational, multicultural and multidisciplinary project that aims to create an area of cohesion and health, and to do so it tailors its actions to the particularities of the area. As OCS remains both innovative and extremely ambitious considering the political and logistical challenges it has taken on, the project will have to be evaluated once carried out. With hope, this approach will prove successful, thus, promising adaptation by other areas. Acknowledgements We thank the project team: Paul Brousse, Carolina Nakano, José Gomes, Marie Auz, Dr Carlos Carrera, who made this project and work possible. E.M. and S.R. are the Principal investigators of the OCS project and were responsible for all phases of the project, including design, data collection, analysis, and interpretation of the public health findings and issues. B.B., S.M., N.G., A.M.M., F.L., F.H., L.A., M.N. provided technical expertise and contributed to interpretation of project prospects. A.S.B. and E.M. wrote the manuscript. All co-authors reviewed, contributed and approved the final manuscript. This project was funded by the European Regional Development Fund (FEDER, SYNERGIE CTE: 3895), the Territorial Collectivity of French Guiana, the Regional Health Agency of French Guiana, Fundo Posithivo, and the Panamerican Health Organization. These sources of support had no role in the writing of or the decision to publish the manuscript. Conflicts of interest There are no conflicts of interest.

Although AIDS care is generally improving in French Guiana, disparities among regions and certain key populations remain significant. The purpose of this study was to describe the spatial and clinical characteristics of people living with HIV (PLHIV) in remote areas in comparison to those followed in hospitals on the urban coast of French Guiana. The data presented were obtained from outpatient on primary care centers located in rural regions away from the urban coast. Data were compared with that from medical records of PLHIV treated in French Guiana's urban care. The evolution of the annual rate of discovery of HIV seropositivity indicates a lag in remote areas as compared to urban and coastal areas. In recent years, the epidemic appeared as particularly active in rural areas among Brazilian patients. The median age of PLHIV in remote areas was 43.8 years, the sex ratio (M/F) was 0.93. Nearly 37% of PLHIV were discovered with advanced disease (<200 CD4/mm3). The percentage of virological success after six months of HAART was 80% and 88% in remote areas and urban area, respectively. Efforts must be made to control and halt the spread of the HIV epidemic, as these remote sites represent strategic points.