Showing papers by "Santa Fe Institute published in 2020"

Ranking the effectiveness of worldwide COVID-19 government interventions.

Abstract: Assessing the effectiveness of non-pharmaceutical interventions (NPIs) to mitigate the spread of SARS-CoV-2 is critical to inform future preparedness response plans. Here we quantify the impact of 6,068 hierarchically coded NPIs implemented in 79 territories on the effective reproduction number, Rt, of COVID-19. We propose a modelling approach that combines four computational techniques merging statistical, inference and artificial intelligence tools. We validate our findings with two external datasets recording 42,151 additional NPIs from 226 countries. Our results indicate that a suitable combination of NPIs is necessary to curb the spread of the virus. Less disruptive and costly NPIs can be as effective as more intrusive, drastic, ones (for example, a national lockdown). Using country-specific ‘what-if’ scenarios, we assess how the effectiveness of NPIs depends on the local context such as timing of their adoption, opening the way for forecasting the effectiveness of future interventions. Analysing over 50,000 government interventions in more than 200 countries, Haug et al. find that combinations of softer measures, such as risk communication or those increasing healthcare capacity, can be almost as effective as disruptive lockdowns.

Serial Interval of COVID-19 among Publicly Reported Confirmed Cases.

Abstract: We estimate the distribution of serial intervals for 468 confirmed cases of coronavirus disease reported in China as of February 8, 2020. The mean interval was 3.96 days (95% CI 3.53-4.39 days), SD 4.75 days (95% CI 4.46-5.07 days); 12.6% of case reports indicated presymptomatic transmission.

Global ecosystem thresholds driven by aridity

Abstract: Aridity, which is increasing worldwide because of climate change, affects the structure and functioning of dryland ecosystems. Whether aridification leads to gradual (versus abrupt) and systemic (versus specific) ecosystem changes is largely unknown. We investigated how 20 structural and functional ecosystem attributes respond to aridity in global drylands. Aridification led to systemic and abrupt changes in multiple ecosystem attributes. These changes occurred sequentially in three phases characterized by abrupt decays in plant productivity, soil fertility, and plant cover and richness at aridity values of 0.54, 0.7, and 0.8, respectively. More than 20% of the terrestrial surface will cross one or several of these thresholds by 2100, which calls for immediate actions to minimize the negative impacts of aridification on essential ecosystem services for the more than 2 billion people living in drylands.

Supply and demand shocks in the COVID-19 pandemic: an industry and occupation perspective

Abstract: We provide quantitative predictions of first-order supply and demand shocks for the US economy associated with the [Coronavirus Disease 2019] COVID-19 pandemic at the level of individual occupations and industries. To analyze the supply shock, we classify industries as essential or non-essential and construct a Remote Labor Index, which measures the ability of different occupations to work from home. Demand shocks are based on a study of the likely effect of a severe influenza epidemic developed by the US Congressional Budget Office. Compared to the pre-COVID period, these shocks would threaten around 22 per cent of the US economy's [gross domestic product] GDP, jeopardise 24 per cent of jobs and reduce total wage income by 17 per cent. At the industry level, sectors such as transport are likely to have output constrained by demand shocks, while sectors relating to manufacturing, mining and services are more likely to be constrained by supply shocks. Entertainment, restaurants and tourism face large supply and demand shocks. At the occupation level, we show that high-wage occupations are relatively immune from adverse supply and demand side shocks, while low-wage occupations are much more vulnerable. We should emphasize that our results are only first-order shocks - we expect them to be substantially amplified by feedback effects in the production network.

Risk for Transportation of Coronavirus Disease from Wuhan to Other Cities in China.

Abstract: On January 23, 2020, China quarantined Wuhan to contain coronavirus disease (COVID-19). We estimated the probability of transportation of COVID-19 from Wuhan to 369 other cities in China before the quarantine. Expected COVID-19 risk is >50% in 130 (95% CI 89-190) cities and >99% in the 4 largest metropolitan areas.

Future of the human climate niche.

Abstract: All species have an environmental niche, and despite technological advances, humans are unlikely to be an exception. Here, we demonstrate that for millennia, human populations have resided in the same narrow part of the climatic envelope available on the globe, characterized by a major mode around ∼11 °C to 15 °C mean annual temperature (MAT). Supporting the fundamental nature of this temperature niche, current production of crops and livestock is largely limited to the same conditions, and the same optimum has been found for agricultural and nonagricultural economic output of countries through analyses of year-to-year variation. We show that in a business-as-usual climate change scenario, the geographical position of this temperature niche is projected to shift more over the coming 50 y than it has moved since 6000 BP. Populations will not simply track the shifting climate, as adaptation in situ may address some of the challenges, and many other factors affect decisions to migrate. Nevertheless, in the absence of migration, one third of the global population is projected to experience a MAT >29 °C currently found in only 0.8% of the Earth’s land surface, mostly concentrated in the Sahara. As the potentially most affected regions are among the poorest in the world, where adaptive capacity is low, enhancing human development in those areas should be a priority alongside climate mitigation.

A high-resolution summary of Cambrian to Early Triassic marine invertebrate biodiversity

Abstract: One great challenge in understanding the history of life is resolving the influence of environmental change on biodiversity. Simulated annealing and genetic algorithms were used to synthesize data from 11,000 marine fossil species, collected from more than 3000 stratigraphic sections, to generate a new Cambrian to Triassic biodiversity curve with an imputed temporal resolution of 26 ± 14.9 thousand years. This increased resolution clarifies the timing of known diversification and extinction events. Comparative analysis suggests that partial pressure of carbon dioxide (Pco2) is the only environmental factor that seems to display a secular pattern similar to that of biodiversity, but this similarity was not confirmed when autocorrelation within that time series was analyzed by detrending. These results demonstrate that fossil data can provide the temporal and taxonomic resolutions necessary to test (paleo)biological hypotheses at a level of detail approaching those of long-term ecological analyses.

Development of structure–function coupling in human brain networks during youth

Abstract: The protracted development of structural and functional brain connectivity within distributed association networks coincides with improvements in higher-order cognitive processes such as executive function. However, it remains unclear how white-matter architecture develops during youth to directly support coordinated neural activity. Here, we characterize the development of structure–function coupling using diffusion-weighted imaging and n-back functional MRI data in a sample of 727 individuals (ages 8 to 23 y). We found that spatial variability in structure–function coupling aligned with cortical hierarchies of functional specialization and evolutionary expansion. Furthermore, hierarchy-dependent age effects on structure–function coupling localized to transmodal cortex in both cross-sectional data and a subset of participants with longitudinal data (n = 294). Moreover, structure–function coupling in rostrolateral prefrontal cortex was associated with executive performance and partially mediated age-related improvements in executive function. Together, these findings delineate a critical dimension of adolescent brain development, whereby the coupling between structural and functional connectivity remodels to support functional specialization and cognition.

Crowding and the shape of COVID-19 epidemics.

Abstract: The coronavirus disease 2019 (COVID-19) pandemic is straining public health systems worldwide, and major non-pharmaceutical interventions have been implemented to slow its spread1-4. During the initial phase of the outbreak, dissemination of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was primarily determined by human mobility from Wuhan, China5,6. Yet empirical evidence on the effect of key geographic factors on local epidemic transmission is lacking7. In this study, we analyzed highly resolved spatial variables in cities, together with case count data, to investigate the role of climate, urbanization and variation in interventions. We show that the degree to which cases of COVID-19 are compressed into a short period of time (peakedness of the epidemic) is strongly shaped by population aggregation and heterogeneity, such that epidemics in crowded cities are more spread over time, and crowded cities have larger total attack rates than less populated cities. Observed differences in the peakedness of epidemics are consistent with a meta-population model of COVID-19 that explicitly accounts for spatial hierarchies. We paired our estimates with globally comprehensive data on human mobility and predict that crowded cities worldwide could experience more prolonged epidemics.

A structured open dataset of government interventions in response to COVID-19.

Abstract: In response to the COVID-19 pandemic, governments have implemented a wide range of non-pharmaceutical interventions (NPIs). Monitoring and documenting government strategies during the COVID-19 crisis is crucial to understand the progression of the epidemic. Following a content analysis strategy of existing public information sources, we developed a specific hierarchical coding scheme for NPIs. We generated a comprehensive structured dataset of government interventions and their respective timelines of implementation. To improve transparency and motivate collaborative validation process, information sources are shared via an open library. We also provide codes that enable users to visualise the dataset. Standardization and structure of the dataset facilitate inter-country comparison and the assessment of the impacts of different NPI categories on the epidemic parameters, population health indicators, the economy, and human rights, among others. This dataset provides an in-depth insight of the government strategies and can be a valuable tool for developing relevant preparedness plans for pandemic. We intend to further develop and update this dataset until the end of December 2020.

The serial interval of COVID-19 from publicly reported confirmed cases

Abstract: We estimate the distribution of serial intervals for 468 confirmed cases of COVID-19 reported in 93 Chinese cities by February 8, 2020. The mean and standard deviation are 3.96 (95% CI 3.53-4.39) and 4.75 (95% CI 4.46-5.07) days, respectively, with 12.6% of reports indicating pre-symptomatic transmission.

Open Science principles for accelerating trait-based science across the Tree of Life

Abstract: Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological and evolutionary science, and new data and methods have proliferated rapidly. Yet accessing and integrating disparate data sources remains a considerable challenge, slowing progress toward a global synthesis to integrate trait data across organisms. Trait science needs a vision for achieving global integration across all organisms. Here, we outline how the adoption of key Open Science principles-open data, open source and open methods-is transforming trait science, increasing transparency, democratizing access and accelerating global synthesis. To enhance widespread adoption of these principles, we introduce the Open Traits Network (OTN), a global, decentralized community welcoming all researchers and institutions pursuing the collaborative goal of standardizing and integrating trait data across organisms. We demonstrate how adherence to Open Science principles is key to the OTN community and outline five activities that can accelerate the synthesis of trait data across the Tree of Life, thereby facilitating rapid advances to address scientific inquiries and environmental issues. Lessons learned along the path to a global synthesis of trait data will provide a framework for addressing similarly complex data science and informatics challenges.

The megabiota are disproportionately important for biosphere functioning.

Abstract: A prominent signal of the Anthropocene is the extinction and population reduction of the megabiota-the largest animals and plants on the planet. However, we lack a predictive framework for the sensitivity of megabiota during times of rapid global change and how they impact the functioning of ecosystems and the biosphere. Here, we extend metabolic scaling theory and use global simulation models to demonstrate that (i) megabiota are more prone to extinction due to human land use, hunting, and climate change; (ii) loss of megabiota has a negative impact on ecosystem metabolism and functioning; and (iii) their reduction has and will continue to significantly decrease biosphere functioning. Global simulations show that continued loss of large animals alone could lead to a 44%, 18% and 92% reduction in terrestrial heterotrophic biomass, metabolism, and fertility respectively. Our findings suggest that policies that emphasize the promotion of large trees and animals will have disproportionate impact on biodiversity, ecosystem processes, and climate mitigation.

30% land conservation and climate action reduces tropical extinction risk by more than 50%

Abstract: Limiting climate change to less than 2°C is the focus of international policy under the climate convention (UNFCCC), and is essential to preventing extinctions, a focus of the Convention on Biological Diversity (CBD). The post‐2020 biodiversity framework drafted by the CBD proposes conserving 30% of both land and oceans by 2030. However, the combined impact on extinction risk of species from limiting climate change and increasing the extent of protected and conserved areas has not been assessed. Here we create conservation spatial plans to minimize extinction risk in the tropics using data on 289 219 species and modeling two future greenhouse gas concentration pathways (RCP2.6 and 8.5) while varying the extent of terrestrial protected land and conserved areas from <17% to 50%. We find that limiting climate change to 2°C and conserving 30% of terrestrial area could more than halve aggregate extinction risk compared with uncontrolled climate change and no increase in conserved area.

Projections for first-wave COVID-19 deaths across the US using social-distancing measures derived from mobile phones

Abstract: We propose a Bayesian model for projecting first-wave COVID-19 deaths in all 50 U.S. states. Our model’s projections are based on data derived from mobile-phone GPS traces, which allows us to estimate how social-distancing behavior is “flattening the curve” in each state. In a two-week look-ahead test of out-of-sample forecasting accuracy, our model significantly outperforms the widely used model from the Institute for Health Metrics and Evaluation (IHME), achieving 42% lower prediction error: 13.2 deaths per day average error across all U.S. states, versus 22.8 deaths per day average error for the IHME model. Our model also provides an accurate, if slightly conservative, assessment of forecasting accuracy: in the same look-ahead test, 98% of data points fell within the model’s 95% credible intervals. Our model’s projections are updated daily at https://covid-19.tacc.utexas.edu/projections/.

Antibiotic combination therapy against resistant bacterial infections: synergy, rejuvenation and resistance reduction

Abstract: Introduction: Anti-Microbial Resistance (AMR) is a pandemic which threatens modern medicine. There is a lack of effective drug treatment due to the slow pace, high cost and low achievable sales prices of new antibiotic monotherapies. New hope comes in the shape of antibiotic combination therapy, which although used by mother nature, is under-explored and could provide the solution to AMR.Areas covered: We performed a search of Pubmed and Medline using the keywords 'combination therapy', 'antimicrobial resistance' for articles between 1930 and 2019, as supplemented with other relevant references to our knowledge. We have reviewed the theoretical considerations for combination development and examine the existing and future clinical indications of combination therapies. We have discussed the potential of antibiotic combinations to provide therapeutic synergy, rejuvenating the effectiveness of old antibiotics to which the bacteria had developed resistance previously. We have examined the current thinking and evidence on resistance reduction using combination therapies, with a review on toxicity and drug-drug antagonism.Expert opinion: Antibiotic combination therapy, exploiting synergies, old-drug rejuvenation and resistance reduction could provide the solution to AMR. The number of pharmaceutical companies in this area is likely to expand, bringing promising combinations to the bedside, to save millions of lives worldwide.

Mars Extant Life: What's Next? Conference Report.

Abstract: On November 5–8, 2019, the “Mars Extant Life: What's Next?” conference was convened in Carlsbad, New Mexico. The conference gathered a community of actively publishing experts in disciplines relate...

On the co-evolution of surface oxygen levels and animals.

Abstract: Few topics in geobiology have been as extensively debated as the role of Earth's oxygenation in controlling when and why animals emerged and diversified. All currently described animals require oxygen for at least a portion of their life cycle. Therefore, the transition to an oxygenated planet was a prerequisite for the emergence of animals. Yet, our understanding of Earth's oxygenation and the environmental requirements of animal habitability and ecological success is currently limited; estimates for the timing of the appearance of environments sufficiently oxygenated to support ecologically stable populations of animals span a wide range, from billions of years to only a few million years before animals appear in the fossil record. In this light, the extent to which oxygen played an important role in controlling when animals appeared remains a topic of debate. When animals originated and when they diversified are separate questions, meaning either one or both of these phenomena could have been decoupled from oxygenation. Here, we present views from across this interpretive spectrum-in a point-counterpoint format-regarding crucial aspects of the potential links between animals and surface oxygen levels. We highlight areas where the standard discourse on this topic requires a change of course and note that several traditional arguments in this "life versus environment" debate are poorly founded. We also identify a clear need for basic research across a range of fields to disentangle the relationships between oxygen availability and emergence and diversification of animal life.

Stacking models for nearly optimal link prediction in complex networks.

Abstract: Most real-world networks are incompletely observed. Algorithms that can accurately predict which links are missing can dramatically speed up network data collection and improve network model validation. Many algorithms now exist for predicting missing links, given a partially observed network, but it has remained unknown whether a single best predictor exists, how link predictability varies across methods and networks from different domains, and how close to optimality current methods are. We answer these questions by systematically evaluating 203 individual link predictor algorithms, representing three popular families of methods, applied to a large corpus of 550 structurally diverse networks from six scientific domains. We first show that individual algorithms exhibit a broad diversity of prediction errors, such that no one predictor or family is best, or worst, across all realistic inputs. We then exploit this diversity using network-based metalearning to construct a series of "stacked" models that combine predictors into a single algorithm. Applied to a broad range of synthetic networks, for which we may analytically calculate optimal performance, these stacked models achieve optimal or nearly optimal levels of accuracy. Applied to real-world networks, stacked models are superior, but their accuracy varies strongly by domain, suggesting that link prediction may be fundamentally easier in social networks than in biological or technological networks. These results indicate that the state of the art for link prediction comes from combining individual algorithms, which can achieve nearly optimal predictions. We close with a brief discussion of limitations and opportunities for further improvements.

The origin of animal body plans: a view from fossil evidence and the regulatory genome

Abstract: The origins and the early evolution of multicellular animals required the exploitation of holozoan genomic regulatory elements and the acquisition of new regulatory tools. Comparative studies of metazoans and their relatives now allow reconstruction of the evolution of the metazoan regulatory genome, but the deep conservation of many genes has led to varied hypotheses about the morphology of early animals and the extent of developmental co-option. In this Review, I assess the emerging view that the early diversification of animals involved small organisms with diverse cell types, but largely lacking complex developmental patterning, which evolved independently in different bilaterian clades during the Cambrian Explosion.

The interpretation of urban scaling analysis in time

Abstract: Scaling is a general analytical framework used by many disciplines-from physics to biology and the social sciences-to characterize how population-averaged properties of a collective vary with its size. The observation of scale invariance over some range identifies general system types, be they ideal gases, ecosystems or cities. The use of scaling in the analysis of cities quantifies many of their arguably fundamental general characteristics, especially their capacity to create interrelated economies of scale in infrastructure and increasing returns to scale in socio-economic activities. However, the measurement of these effects, and the relationship of observable parameters to theory, hinge on how scaling analysis is used empirically. Here, we show how two equivalent approaches to urban scaling-cross-sectional and temporal-lead to the measurement of different mixtures of the same fundamental parameters describing pure scale and pure temporal phenomena. Specifically, temporal exponents are sensitive to the intensive growth of urban quantities and to circumstances when population growth vanishes, leading to instabilities and infinite divergences. These spurious effects are avoided in cross-sectional scaling, which is more common and closer to theory in terms of quantitative testable expectations for its parameters.

Selection enhances protein evolvability by increasing mutational robustness and foldability.

Abstract: Natural selection can promote or hinder a population's evolvability-the ability to evolve new and adaptive phenotypes-but the underlying mechanisms are poorly understood. To examine how the strength of selection affects evolvability, we subjected populations of yellow fluorescent protein to directed evolution under different selection regimes and then evolved them toward the new phenotype of green fluorescence. Populations under strong selection for the yellow phenotype evolved the green phenotype most rapidly. They did so by accumulating mutations that increase both robustness to mutations and foldability. Under weak selection, neofunctionalizing mutations rose to higher frequency at first, but more frequent deleterious mutations undermined their eventual success. Our experiments show how selection can enhance evolvability by enhancing robustness and create the conditions necessary for evolutionary success.

Predicting COVID-19 Peaks Around the World

Abstract: The official data for the time evolution of active cases of COVID-19 pandemics around the world are available online. For all countries, a peak has been either observed (China and South Korea) or is expected in the near future. The approximate dates and heights of those peaks have important epidemiological implications. Inspired by similar complex behavior of volumes of transactions of stocks at the NYSE and NASDAQ, we propose a q-statistical functional form that appears to describe satisfactorily the available data for all countries. Consistently, predictions of the dates and heights of those peaks in severely affected countries become possible unless efficient treatments or vaccines, or sensible modifications of the adopted epidemiological strategies, emerge.

Optimization in First-Passage Resetting.

Abstract: We investigate classic diffusion with the added feature that a diffusing particle is reset to its starting point each time the particle reaches a specified threshold. In an infinite domain, this process is nonstationary and its probability distribution exhibits rich features. In a finite domain, we define a nontrivial optimization in which a cost is incurred whenever the particle is reset and a reward is obtained while the particle stays near the reset point. We derive the condition to optimize the net gain in this system, namely, the reward minus the cost.

Ranking the effectiveness of worldwide COVID-19 government interventions

Abstract: Assessing the effectiveness of Non-Pharmaceutical Interventions (NPIs) to mitigate the spread of SARS-CoV-2 is critical to inform future preparedness response plans. Here we quantify the impact of 6,068 hierarchically coded NPIs implemented in 79 territories on the effective reproduction number, Rt, of COVID-19. We propose a novel modelling approach that combines four computational techniques merging for the first time statistical, inference and artificial intelligence tools. We validate our findings with two external datasets with 48,000 additional NPIs from 226 countries. Our results indicate that a suitable combination of NPIs is necessary to curb the spread of the virus. Less intrusive and costly NPIs can be as effective as more intrusive, drastic, ones, e.g., a national lockdown. Using country-specific what-if scenarios we assess how the effectiveness of NPIs depends on the local context such as timing of their adoption, opening the way for forecasting the effectiveness of future interventions.

Conservation value of small reserves.

Abstract: The importance of large reserves has been long maintained in the scientific literature, often leading to dismissal of the conservation potential of small reserves. However, over half the global protected-area inventory is composed of protected areas that are <100 ha, and the median size of added protected area is decreasing. Studies of the conservation value of small reserves and fragments of natural area are relatively uncommon in the literature. We reviewed SCOPUS and WOK for studies on small reserve and fragment contributions to biodiversity conservation and ecosystem services, and fifty-eight taxon-specific studies were included in the review. Small reserves harbored substantial portions (upward of 50%) of regional species diversity for many taxa (birds, plants, amphibians, and small mammals) and even some endemic, specialist bird species. Unfortunately, small reserves and fragments almost always harbored more generalist and exotic species than large reserves. Community composition depended on habitat quality, surrounding land use (agricultural vs. urban), and reserve and fragment size, which presents opportunities for management and improvement. Small reserves also provided ecosystem services, such as pollination and biological pest control, and cultural services, such as recreation and improved human health. Limitations associated with small reserves, such as extinction debt and support of area-sensitive species, necessitate a complement of larger reserves. However, we argue that small reserves can make viable and significant contributions to conservation goals directly as habitat and indirectly by increasing landscape connectivity and quality to the benefit of large reserves. To effectively conserve biodiversity for future generations in landscapes fragmented by human development, small reserves and fragments must be included in conservation planning.

Effects of Proactive Social Distancing on COVID-19 Outbreaks in 58 Cities, China.

Abstract: Cities across China implemented stringent social distancing measures in early 2020 to curb coronavirus disease outbreaks. We estimated the speed with which these measures contained transmission in cities. A 1-day delay in implementing social distancing resulted in a containment delay of 2.41 (95% CI 0.97-3.86) days.