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AbstractIntroductionKey populations bear a disproportionate HIV burden and have substantial unmet treatment needs. Routine viral load monitoring represents the gold standard for assessing treatment response at the individual and programme levels; at the population‐level, community viral load is a metric of HIV programme effectiveness and can identify "hotspots" of HIV transmission. Nevertheless, there are specific implementation and ethical challenges to effectively operationalize and meaningfully interpret viral load data at the community level among these often marginalized populations.DiscussionViral load monitoring enhances HIV treatment, and programme evaluation, and offers a better understanding of HIV surveillance and epidemic trends. Programmatically, viral load monitoring can provide data related to HIV service delivery coverage and quality, as well as inequities in treatment access and uptake. From a population perspective, community viral load data provides information on HIV transmission risk. Furthermore, viral load data can be used as an advocacy tool to demonstrate differences in service delivery and to promote allocation of resources to disproportionately affected key populations and communities with suboptimal health outcomes. However, in order to perform viral load monitoring for individual and programme benefit, health surveillance and advocacy purposes, careful consideration must be given to how such key population programmes are designed and implemented. For example, HIV risk factors, such as particular sex practices, sex work and drug use, are stigmatized or even criminalized in many contexts. Consequently, efforts must be taken so that routine viral load monitoring among marginalized populations does not cause inadvertent harm. Furthermore, given the challenges of reaching representative samples of key populations, significant attention to meaningful recruitment, decentralization of care and interpretation of results is needed. Finally, improving the interoperability of health systems through judicious use of biometrics or identifiers when confidentiality can be maintained is important to generate more valuable data to inform monitoring programmes.ConclusionsOpportunities for expanded viral load monitoring could and should benefit all those affected by HIV, including key populations. The promise of the increasing routinization of viral load monitoring as a tool to advance HIV treatment equity is great and should be prioritized and appropriately implemented within key population programmatic and research agendas.

BACKGROUND: In-depth analysis of the HIV pandemic at its epicenter in the Congo basin has been hampered by 40 years of political unrest and lack of functional public health infrastructure. In recent surveillance studies (2017-18), we found that the prevalence of HIV in Kinshasa, Democratic Republic of Congo (11%) far exceeded previous estimates. METHODS: 10,457 participants were screened in Kinshasa with rapid tests from 2017-2019. Individuals confirmed as reactive by the Abbott ARCHITECT HIV Ag/Ab Combo assay (n=1968) were measured by the Abbott RealTime HIV-1 viral load assay. Follow up characterization of samples was performed with alternate manufacturer viral load assays, qPCR for additional blood borne viruses, unbiased next generation sequencing, and HIV Western blotting. FINDINGS: Our data suggested the existence of a significant cohort (n=429) of HIV antibody positive/viral load negative individuals. We systematically eliminated collection site bias, sample integrity, and viral genetic diversity as alternative explanations for undetectable viral loads. Mass spectroscopy unexpectedly detected the presence of 3TC antiviral medication in approximately 60% of those tested (209/354), and negative Western blot results indicated false positive serology in 12% (49/404). From the remaining Western blot positives (n=53) and indeterminates (n=31) with reactive Combo and rapid test results, we estimate 2.7-4.3% of infections in DRC to be potential elite controllers. We also analyzed samples from the DRC collected in 1987 and 2001-03, when antiretroviral drugs were not available, and found similarly elevated trends. INTERPRETATION: Viral suppression to undetectable viral loads without therapy occurs infrequently in HIV-1 infected patients around the world. Mining of global data suggests a unique ability to control HIV infection arose early in central Africa and occurs in <1% of founder populations. Identification of this group of elite controllers presents a unique opportunity to study potentially novel genetic ...

Genetics data have provided unprecedented insights into evolutionary aspects of colonization by non‐native populations. Yet, our understanding of how artificial (human‐mediated) and natural dispersal pathways of non‐native individuals influence genetic metrics, evolution of genetic structure, and admixture remains elusive. We capitalize on the widespread colonization of Chinook salmon Oncorhynchus tshawytscha in South America, mediated by both dispersal pathways, to address these issues using data from a panel of polymorphic SNPs. First, genetic diversity and the number of effective breeders (N b) were higher among artificial than natural populations. Contemporary gene flow was common between adjacent artificial and natural and adjacent natural populations, but uncommon between geographically distant populations. Second, genetic structure revealed four distinct clusters throughout the Chinook salmon distributional range with varying levels of genetic connectivity. Isolation by distance resulted from weak differentiation between adjacent artificial and natural and between natural populations, with strong differentiation between distant Pacific Ocean and Atlantic Ocean populations, which experienced strong genetic drift. Third, genetic mixture analyses revealed the presence of at least six donor geographic regions from North America, some of which likely hybridized as a result of multiple introductions. Relative propagule pressure or the proportion of Chinook salmon propagules introduced from various geographic regions according to government records significantly influenced genetic mixtures for two of three artificial populations. Our findings support a model of colonization in which high‐diversity artificial populations established first; some of these populations exhibited significant admixture resulting from propagule pressure. Low‐diversity natural populations were likely subsequently founded from a reduced number of individuals.

AbstractIntroductionAntiretroviral treatment (ART) sharing has been reported among fishermen and sex workers in Uganda and South Africa. However, no population‐based studies have documented ART diversion prevalence (including sharing [giving/receiving], buying and selling) or its relationship with viremia among men and women living with HIV in Africa.MethodsIn 2018–2020, we surveyed people living with HIV aged 15–49 years in 41 communities in the Rakai Community Cohort Study, a population‐based cohort in south‐central Uganda. We assessed the prevalence and correlates of self‐reported lifetime and past‐year ART diversion, stratifying by age and gender and documenting sources of diverted drugs. We used log‐binomial regression to quantify the relationship between diversion patterns and viremia (viral load >40 copies/ml), reported as unadjusted and adjusted prevalence ratios (aPR) with 95% confidence intervals (CI).ResultsOf 2852 people living with HIV and self‐reporting current ART use, 266 (9.3%) reported lifetime ART diversion. Giving/receiving drugs were most common; few participants reported buying, and none reported selling. Men (12.9%) were more likely to report lifetime diversion than women (7.4%), with men aged 25–34 reporting high levels of sharing (18.9%). Friends were the most common sources of shared drugs, followed by spouses/sexual partners. Patterns of lifetime and past‐year diversion were similar. Among participants with viral load results, 8.6% were viraemic. In adjusted analyses, people who reported only giving ART were nearly twice as likely to be viraemic than those who reported no diversion (aPR: 1.94, 95% CI: 1.10−3.44), and those reporting only receiving ART were less likely to exhibit viremia (aPR: 0.46, 95% CI: 0.12−1.79), although the latter was not statistically significant. Reporting both giving and receiving ART was not associated with viremia (aPR: 0.79, 95% CI: 0.43−1.46). Reporting buying ART, though rare, was also correlated with higher rates of viremia, but this relationship was not statistically significant (aPR: 1.98, 95% CI: 0.72−5.45).ConclusionsART sharing is common among persons reporting ART use in rural Uganda, particularly among men. Sharing ART was associated with viremia, and receiving ART may facilitate viral suppression. HIV programmes may benefit from considering ART sharing in counselling messages.

AbstractIntroductionPopulation‐level data on durable HIV viral load suppression (VLS) following the implementation of Universal Test and Treat (UTT) in Africa are limited. We assessed trends in durable VLS and viraemia among persons living with HIV in 40 Ugandan communities during the UTT scale‐up.MethodsIn 2015–2020, we measured VLS (<200 RNA copies/ml) among participants in the Rakai Community Cohort Study, a longitudinal population‐based HIV surveillance cohort in southern Uganda. Persons with unsuppressed viral loads were characterized as having low‐level (200–999 copies/ml) or high‐level (≥1000 copies/ml) viraemia. Individual virologic outcomes were assessed over two consecutive RCCS survey visits (i.e. visit‐pairs; ∼18‐month visit intervals) and classified as durable VLS (<200 copies/ml at both visits), new/renewed VLS (<200 copies/ml at follow‐up only), viral rebound (<200 copies/ml at initial visit only) or persistent viraemia (≥200 copies/ml at both visits). Population prevalence of each outcome was assessed over calendar time. Community‐level prevalence and individual‐level predictors of persistent high‐level viraemia were also assessed using multivariable Poisson regression with generalized estimating equations.ResultsOverall, 3080 participants contributed 4604 visit‐pairs over three survey rounds. Most visit‐pairs (72.4%) exhibited durable VLS, with few (2.5%) experiencing viral rebound. Among those with any viraemia at the initial visit (23.5%, n = 1083), 46.9% remained viraemic through follow‐up, 91.3% of which was high‐level viraemia. One‐fifth (20.8%) of visit‐pairs exhibiting persistent high‐level viraemia self‐reported antiretroviral therapy (ART) use for ≥12 months. Prevalence of persistent high‐level viraemia varied substantially across communities and was significantly elevated among young persons aged 15–29 years (vs. 40‐ to 49‐year‐olds; adjusted risk ratio [adjRR] = 2.96; 95% confidence interval [95% CI]: 2.21–3.96), males (vs. females; adjRR = 2.40, 95% CI: 1.87–3.07), persons reporting inconsistent condom use with non‐marital/casual partners (vs. persons with marital/permanent partners only; adjRR = 1.38, 95% CI: 1.10–1.74) and persons reporting hazardous alcohol use (adjRR = 1.09, 95% CI: 1.03–1.16). The prevalence of persistent high‐level viraemia was highest among males <30 years (32.0%).ConclusionsFollowing universal ART provision, most persons living with HIV in south‐central Uganda are durably suppressed. Among persons exhibiting any viraemia, nearly half exhibited high‐level viraemia for ≥12 months and reported higher‐risk behaviours associated with onward HIV transmission. Intensified efforts linking individuals to HIV treatment services could accelerate momentum towards HIV epidemic control.

Aerodynamic canopy height (h(a)) is the effective height of vegetation canopy for its influence on atmospheric fluxes and is a key parameter of surface-atmosphere coupling. However, methods to estimate h(a) from data are limited. This synthesis evaluates the applicability and robustness of the calculation of h(a) from eddy covariance momentum-flux data. At 69 forest sites, annual h(a) robustly predicted site-to-site and year-to-year differences in canopy heights (R-2=0.88, 111site-years). At 23 cropland/grassland sites, weekly h(a) successfully captured the dynamics of vegetation canopies over growing seasons (R-2>0.70 in 74site-years). Our results demonstrate the potential of flux-derived h(a) determination for tracking the seasonal, interannual, and/or decadal dynamics of vegetation canopies including growth, harvest, land use change, and disturbance. The large-scale and time-varying h(a) derived from flux networks worldwide provides a new benchmark for regional and global Earth system models and satellite remote sensing of canopy structure. Plain Language Summary Vegetation canopy height is a key descriptor of the Earth surface and is in use by many modeling and conservation applications. However, large-scale and time-varying data of canopy heights are often unavailable. This synthesis evaluates the applicability and robustness of the calculation of canopy heights from the momentum flux data measured at eddy covariance flux tower sites (i.e., meteorological observation towers with high frequency measurements of wind speed and surface fluxes). We show that the aerodynamic estimation of annual canopy heights robustly predicts the site-to-site and year-to-year differences in canopy heights across a wide variety of forests. The weekly aerodynamic canopy heights successfully capture the dynamics of vegetation canopies over growing seasons at cropland and grassland sites. Our results demonstrate the potential of aerodynamic canopy heights for tracking the seasonal, interannual, and/or decadal dynamics of vegetation canopies including growth, harvest, land use change, and disturbance. Given the amount of data collected and the diversity of vegetation covered by the global networks of eddy covariance flux tower sites, the flux-derived canopy height has great potential for providing a new benchmark for regional and global Earth system models and satellite remote sensing of canopy structure. ; U.S. Department of Energy's Office of ScienceUnited States Department of Energy (DOE) [DE-SC0012456, DE-AC02-05CH11231] ; This study is supported by FLUXNET and AmeriFlux projects, sponsored by U.S. Department of Energy's Office of Science (DE-SC0012456 and DE-AC02-05CH11231). We thank the supports from AmeriFlux Data Team: Gilberto Pastorello, Deb Agarwal, Danielle Christianson, You-Wei Cheah, Norman Beekwilder, Tom Boden, Bai Yang, and Dario Papale, and Berkeley Biomet Lab: Siyan Ma, Joseph Verfaillie, Elke Eichelmann, and Sara Knox. This work uses eddy covariance and BADM data acquired and shared by the investigators involved in the AmeriFlux and Fluxnet-Canada Research Network. The site list and corresponding references are provided in the supporting information. We thank Claudia Wagner-Riddle, Andy Suyker, David Cook, Asko Noormets, Paul Stoy, and Brian Amiro for providing additional data. All actual canopy height data can be downloaded from AmeriFlux BADM. The R codes and aerodynamic canopy height data can be accessed at http://github.com/chuhousen/aerodynamic_canopy_height. ; Public domain authored by a U.S. government employee

Direct quantification of terrestrial biosphere responses to global change is crucial for projections of future climate change in Earth system models. Here, we synthesized ecosystem carbon-cycling data from 1,119 experiments performed over the past four decades concerning changes in temperature, precipitation, CO2 and nitrogen across major terrestrial vegetation types of the world. Most experiments manipulated single rather than multiple global change drivers in temperate ecosystems of the USA, Europe and China. The magnitudes of warming and elevated CO2 treatments were consistent with the ranges of future projections, whereas those of precipitation changes and nitrogen inputs often exceeded the projected ranges. Increases in global change drivers consistently accelerated, but decreased precipitation slowed down carbon-cycle processes. Nonlinear (including synergistic and antagonistic) effects among global change drivers were rare. Belowground carbon allocation responded negatively to increased precipitation and nitrogen addition and positively to decreased precipitation and elevated CO2. The sensitivities of carbon variables to multiple global change drivers depended on the background climate and ecosystem condition, suggesting that Earth system models should be evaluated using site-specific conditions for best uses of this large dataset. Together, this synthesis underscores an urgent need to explore the interactions among multiple global change drivers in under-represented regions such as semi-arid ecosystems, forests in the tropics and subtropics, and Arctic tundra when forecasting future terrestrial carbon-climate feedback. ; National Natural Science Foundation of ChinaNational Natural Science Foundation of China [31430015, 31830012]; US NSFNational Science Foundation (NSF) [DEB-0955771]; ClimMani COST actionEuropean Cooperation in Science and Technology (COST) [ES1308] ; We thank J. Wang (Hebei University), S. Yang (Institute of Botany, Chinese Academy of Sciences), L. Zhou (East China Normal University), C. Qiao (Xinyang Normal University) and H. Li (Henan University) for their help in meta-analyses and interaction analyses, and H. Li, Y. Liu (Institute of Tibetan Plateau Research, Chinese Academy of Sciences) and Y. He (Peking University) for their help in plotting figures. This work was financially supported by the National Natural Science Foundation of China (grant nos. 31430015 and 31830012). This study emerged from the INTERFACE Workshop in Beijing, China (https://www.bio.purdue.edu/INTERFACE/) supported by the US NSF DEB-0955771. We also acknowledge support from the ClimMani COST action (ES1308). ; Public domain authored by a U.S. government employee

The Community Land Model (CLM) is the land component of the Community Earth System Model (CESM) and is used in several global and regional modeling systems. In this paper, we introduce model developments included in CLM version 5 (CLM5), which is the default land component for CESM2. We assess an ensemble of simulations, including prescribed and prognostic vegetation state, multiple forcing data sets, and CLM4, CLM4.5, and CLM5, against a range of metrics including from the International Land Model Benchmarking (ILAMBv2) package. CLM5 includes new and updated processes and parameterizations: (1) dynamic land units, (2) updated parameterizations and structure for hydrology and snow (spatially explicit soil depth, dry surface layer, revised groundwater scheme, revised canopy interception and canopy snow processes, updated fresh snow density, simple firn model, and Model for Scale Adaptive River Transport), (3) plant hydraulics and hydraulic redistribution, (4) revised nitrogen cycling (flexible leaf stoichiometry, leaf N optimization for photosynthesis, and carbon costs for plant nitrogen uptake), (5) global crop model with six crop types and time-evolving irrigated areas and fertilization rates, (6) updated urban building energy, (7) carbon isotopes, and (8) updated stomatal physiology. New optional features include demographically structured dynamic vegetation model (Functionally Assembled Terrestrial Ecosystem Simulator), ozone damage to plants, and fire trace gas emissions coupling to the atmosphere. Conclusive establishment of improvement or degradation of individual variables or metrics is challenged by forcing uncertainty, parametric uncertainty, and model structural complexity, but the multivariate metrics presented here suggest a general broad improvement from CLM4 to CLM5. ; National Science Foundation (NSF)National Science Foundation (NSF); National Center for Atmospheric Research - NSF [1852977]; RUBISCO Scientific Focus Area (SFA) - Regional and Global Climate Modeling (RGCM) Program in the Climate and Environmental Sciences Division (CESD) of the Office of Biological and Environmental Research in the U.S. Department of Energy Office of Science; Columbia University Presidential Fellowship; U.S. Department of Agriculture NIFA Award [2015-67003-23485]; NASA Interdisciplinary Science Program Award [NNX17AK19G]; U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research, Terrestrial Ecosystem Science programUnited States Department of Energy (DOE) [DE-SC0008317, DESC0016188]; National Science FoundationNational Science Foundation (NSF) [DEB-1153401]; NASA's CARBON program; NASA's TE program; National Aeronautics and Space AdministrationNational Aeronautics & Space Administration (NASA) ; We would like to thank the reviewers for their insightful comments and helpful suggestions that improved the clarity and presentation of the manuscript. The CESM project is supported primarily by the National Science Foundation (NSF). This material is based upon work supported by the National Center for Atmospheric Research, which is a major facility sponsored by the NSF under Cooperative Agreement 1852977. Computing and data storage resources, including the Cheyenne supercomputer (doi:10.5065/D6RX99HX), were provided by the Computational and Information Systems Laboratory (CISL) at NCAR. D. M. L. was supported in part by the RUBISCO Scientific Focus Area (SFA), which is sponsored by the Regional and Global Climate Modeling (RGCM) Program in the Climate and Environmental Sciences Division (CESD) of the Office of Biological and Environmental Research in the U.S. Department of Energy Office of Science. D. K. and P. G. were supported by Columbia University Presidential Fellowship. G. B., D. L. L., W. R. W., and R. Q. T. were supported by the U.S. Department of Agriculture NIFA Award 2015-67003-23485. W. R. W. and G. K. A. were supported by the NASA Interdisciplinary Science Program Award NNX17AK19G. J. B. F. and M. S. carried out the research in part at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. California Institute of Technology. Government sponsorship acknowledged. All rights reserved. J. B. F. and M. S. were supported in part by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research, Terrestrial Ecosystem Science program under Awards DE-SC0008317 and DESC0016188; the National Science Foundation Ecosystem Science program (DEB-1153401); and NASA's CARBON and TE programs. All model data are archived and publicly available at the UCAR/NCAR Climate Data Gateway (https://doi.org/10.5065/d6154fwh).