Simple decision rules to predict local surges in COVID-19 hospitalizations during the winter and spring of 2022

Low rates of vaccination, emergence of novel variants of SARS-CoV-2, and increasing transmission relating to seasonal changes leave many U.S. communities at risk for surges of COVID-19 during the winter and spring of 2022 that might strain hospital capacity, as in previous waves. The trajectories of COVID-19 hospitalizations during this period are expected to differ across communities depending on their age distributions, vaccination coverage, cumulative incidence, and adoption of risk mitigating behaviors. Yet, existing predictive models of COVID-19 hospitalizations are almost exclusively focused on national- and state-level predictions. This leaves local policymakers in urgent need of tools that can provide early warnings about the possibility that COVID-19 hospitalizations may rise to levels that exceed local capacity. In this work, we develop simple decision rules to predict whether COVID-19 hospitalization will exceed the local hospitalization capacity within a 4- or 8-week period if no additional mitigating strategies are implemented during this time. These decision rules use real-time data related to hospital occupancy and new hospitalizations associated with COVID-19, and when available, genomic surveillance of SARS-CoV-2. We showed that these decision rules present reasonable accuracy, sensitivity, and specificity (all ≥80%) in predicting local surges in hospitalizations under numerous simulated scenarios, which capture substantial uncertainties over the future trajectories of COVID-19 during the winter and spring of 2022. Our proposed decision rules are simple, visual, and straightforward to use in practice by local decision makers without the need to perform numerical computations.

Automatic energy demand and system simulation at district level

The importance of climate protection and sustainability is steadily increasing all over the world. However, there is a large potential for reducing emissions in the heating demand reduction and renewable heat supply of buildings that needs to be addressed. Therefore, a method was developed within the scope of this work that allows local decision-makers such as energy supply companies, project developers and the public sector to calculate, evaluate and compare different scenarios to make buildings and city districts more sustainable based on few and widely available input data. It includes both the determination of the heat demand and measures for its reduction as well as the selection and simulation of centralised and decentralised supply systems. A combination of different methods from the fields of geoinformatics, heuristic decision-making and object-oriented modelling is used. The latter forms a focal point in the work with the development of a data model for energy system components to enable automatic simulation. The applicability as well as the transferability of the method is shown in several case studies. Based on the simulations results, which can be related to CO2 emissions as well as costs, recommendations for the implementation of measures can be given and implemented.The paper is a summary of the dissertation with the title “Automatische Simulation von Wärmebedarf und -versorgung auf Quartiersebene” by the first author at Karlsruhe Institute for Technology.

Public-Private Negotiation of the Increase in Land or Property Value by Urban Variant: An Analytical Approach Tested on a Case of Real Estate Development

The insufficiency of public resources in Europe, which increased due to the debt crisis of 2010, has raised the need for combined financing forms to activate urban settlement transformation processes. Among these is the partial recapture of surplus value generated by interventions that derogate from urban planning tools as a regulation form of the differential rent phenomenon. This form of financing recalls the concept of land value recapture; it consists of an extraordinary charge of urbanisation (ECU) paid to policymakers. In Italy, the national law (2014) assigns responsibility for ECU determination to local decision-makers. Their plurality of operational guidelines are generally inspired by the transformation value criterion, and are sometimes methodologically incoherent and dispersive in their modus operandi. To support policymakers in the programming of public works within the limits of their available financial resources, the aim of the present work is to test a coherent, rational and applicable procedure in the field of estimation in order to analytically determine the “surplus value” generated by the intervention ante and post urban variant. The proposed procedural model is based on the structural characterisation of multiple methodologies used in practice and in the literature. The procedure was tested on a case study in the Italian context of Rome City. The results deduced from its implementation clarify that the ECU evaluation must also appropriately weigh the mutual benefits according to the “timing” and “riskiness” of the investment.

Projecting Future Vegetation Change for Northeast China Using CMIP6 Model

Northeast China lies in the transition zone from the humid monsoonal to the arid continental climate, with diverse ecosystems and agricultural land highly susceptible to climate change. This region has experienced significant greening in the past three decades, but future trends remain uncertain. In this study, we provide a quantitative assessment of how vegetation, indicated by the leaf area index (LAI), will change in this region in response to future climate change. Based on the output of eleven CMIP6 global climates, Northeast China is likely to get warmer and wetter in the future, corresponding to an increase in regional LAI. Under the medium emissions scenario (SSP245), the average LAI is expected to increase by 0.27 for the mid-century (2041–2070) and 0.39 for the late century (2071–2100). Under the high emissions scenario (SSP585), the increase is 0.40 for the mid-century and 0.70 for the late century, respectively. Despite the increase in the regional mean, the LAI trend shows significant spatial heterogeneity, with likely decreases for the arid northwest and some sandy fields in this region. Therefore, climate change could pose additional challenges for long-term ecological and economic sustainability. Our findings could provide useful information to local decision makers for developing effective sustainable land management strategies in Northeast China.

A Within-Study Approach to Evaluating the Role of Moderators of Impact in Limiting Generalizations from “Large to Small”

There is a burgeoning body of evidence on the average impacts of educational programs. Yet, for many local decision makers, because impacts can vary across sites, the question of whether a certain program will work in their particular district or school remains. This article addresses the question of the generalizability of large-scale average causal effects to specific locales, that is, from “large to small.” Our method evaluates whether impacts measured on the large-scale generalize to individual sites and whether adjusting for variation among sites in their characteristics accounts for impact heterogeneity that limits generalization. Our application to a multisite experimental evaluation in education shows that the average impact does not readily generalize to sites, with discrepancies between 0.17 and 0.38 standard deviations, and that characteristics of sites account only minimally for this variation. This emphasizes need for caution by local decision makers in accepting average impact findings as generalizable to their specific locales.

Polish Local Government’s Perspective on Revitalisation: A Framework for Future Socially Sustainable Solutions

The principal goal of this paper is to investigate the views of local government officials on revitalisation priorities in Polish municipalities. To accomplish this, the perception of revitalisation objectives by local government representatives (who, according to Polish regulations, are responsible for revitalisation planning and carrying it out) was examined. A catalogue of revitalisation objectives, which were assessed by the respondents, was drawn up on the basis of a review of research on the conceptualisation and measurement of sustainable revitalisation and social sustainability at the local level. Exploratory factor analysis was the method used in the study. In total, the list of the examined revitalisation objectives includes 26 objectives related to the following revitalisation dimensions: infrastructure, community, economy, environment, space, co-governance, and inclusion. A survey of the executive bodies of 573 municipalities in Poland revealed a discrepancy between the sustainable approach to revitalisation advocated by the researchers and the perception of revitalisation objectives by the local decision makers. The study demonstrated that decision makers ranked objectives related to the physical dimension of revitalisation and selected objectives related to the social dimension of revitalisation and oriented at counteracting social exclusion by far the highest. The proactive objectives, related to the engagement, mobilisation and integration of the inhabitants, improvement of human capital, stimulation of the local economy and residential satisfaction, were viewed as definitely less important. The challenges facing revitalisation in Poland still fail to be perceived holistically by decision makers, which may hinder the building of strong and sustainable communities.

Reducing inequality in avoidable emergency admissions: Case studies of local health care systems in England using a realist approach

Objective People in disadvantaged areas are more likely to have an avoidable emergency hospital admission. Socio-economic inequality in avoidable emergency hospital admissions is monitored in England. Our aim was to inform local health care purchasing and planning by identifying recent health care system changes (or other factors), as reported by local health system leaders, that might explain narrowing or widening trends. Methods Case studies were undertaken in one pilot and at five geographically distinct local health care systems (Clinical Commissioning Groups, CCGs), identified as having consistently increasing or decreasing inequality. Local settings were explored through discussions with CCG officials and stakeholders to identify potential local determinants. Data were analysed using a realist evaluation approach to generate context-mechanism-outcome (CMO) configurations. Results Of the five geographically distinct CCGs, two had narrowing inequality, two widening, and one narrowing inequality, which widened during the project. None of the CCGs had designed a large-scale package of service changes with the explicit aim of reducing socio-economic inequality in avoidable emergency admissions, and local decision makers were unfamiliar with their own trends. Potential primary and community care determinants included: workforce, case finding and exclusion, proactive care co-ordination for patients with complex needs, and access and quality. Potential commissioning determinants included: data use and incentives, and targeting of services. Other potential determinants included changes in care home services, national A&E targets, and wider issues - such as public services financial constraints, residential gentrification, and health care expectations. Conclusions We did not find any bespoke initiatives that explained the inequality trends. The trends were more likely due to an interplay of multiple health care and wider system factors. Local decision makers need greater awareness, understanding and support to interpret, use and act upon inequality indicators. They are unlikely to find simple, cheap interventions to reduce inequalities in avoidable emergency admissions. Rather, long-term multifaceted interventions are required that embed inequality considerations into mainstream decision making.

Using landscape metrics to characterize towns along an urban-rural gradient

Context Urban-rural gradients are useful tools when examining the influence of human disturbances on ecological, social and coupled systems, yet the most commonly used gradient definitions are based on single broad measures such as housing density or percent forest cover that fail to capture landscape patterns important for conservation. Objectives We present an approach to defining urban–rural gradients that integrates multiple landscape pattern metrics related to ecosystem processes important for natural resources and wildlife sustainability. Methods We develop a set of land cover composition and configuration metrics and then use them as inputs to a cluster analysis process that, in addition to grouping towns with similar attributes, identifies exemplar towns for each group. We compare the outcome of the cluster-based urban-rural gradient typology to outcomes for four commonly-used rule-based typologies and discuss implications for resource management and conservation. Results The resulting cluster-based typology defines five town types (urban, suburban, exurban, rural, and agricultural) and notably identifies a bifurcation along the gradient distinguishing among rural forested and agricultural towns. Landscape patterns (e.g., core and islet forests) influence where individual towns fall along the gradient. Designations of town type differ substantially among the five different typologies, particularly along the middle of the gradient. Conclusions Understanding where a town occurs along the urban-rural gradient could aid local decision-makers in prioritizing and balancing between development and conservation scenarios. Variations in outcomes among the different urban-rural gradient typologies raise concerns that broad-measure classifications do not adequately account for important landscape patterns. We suggest future urban-rural gradient studies utilize more robust classification approaches.

Ecological Forecasts for a Rapidly Changing Coastal Ocean

The U.S. Integrated Ocean Observing System (IOOS) has a vision to provide ecological forecasts that inform response to multiple stressors in the face of rapid changes in our ocean and Great Lakes. IOOS supports 11 nationally distributed Regional Associations, each with established ties to local decision makers and regional coastal scientists. IOOS also supports thematic networks of platforms and observations to characterize and monitor marine ecosystems and living resources throughout the nation. IOOS serves as the U.S. contribution to the Global Ocean Observing System. This infrastructure, stakeholder engagement, and local-to-global reach uniquely positions IOOS to advance development of an ecological forecast system, across sectors and disciplines, that is responsive and effective.