The Disconnect Between Short- and Long-Term Population Projections for Plant Reintroductions

The reintroduction of rare species in natural preserves is a commonly used restoration strategy to prevent species extinction. An essential first step in planning successful reintroductions is identifying which life stages (e.g., seeds or large adults) should be used to establish these new populations. Following this initial establishment phase, it is necessary to determine the level of survival, growth, and recruitment needed to maintain population persistence over time and identify management actions that will achieve these goals. In this 5-year study, we projected the short- and long-term population growth rates of a critically endangered long-lived shrub, Delissea waianaeensis. Using this model system, we show that reintroductions established with mature individuals have the lowest probability of quasi-population extinction (10 individuals) and the highest increase in population abundance. However, our results also demonstrate that short-term increases in population abundances are overly optimistic of long-term outcomes. Using long-term stochastic model simulations, we identified the level of natural seedling regeneration needed to maintain a positive population growth rate over time. These findings are relevant for planning future reintroduction efforts for long-lived species and illustrate the need to forecast short- and long-term population responses when evaluating restoration success.

Investigating Temporal and Spatial Precipitation Patterns in the Southern Mid-Atlantic United States

The investigation of regional vulnerability to extreme hydroclimatic events (e.g., floods and hurricanes) is quite challenging due to its dependence on reliable precipitation estimates. Better understanding of past precipitation trends is crucial to examine changing precipitation extremes, optimize future water demands, stormwater infrastructure, extreme event measures, irrigation management, etc., especially if combined with future climate and population projections. The objective of the study is to investigate the spatial-temporal variability of average and extreme precipitation at a sub-regional scale, specifically in the Southern Mid-Atlantic United States, a region characterized by diverse topography and is among the fastest-growing areas in North America. Particularly, this work investigates past precipitation trends and patterns using the North American Land Data Assimilation System, Version 2 (NLDAS-2, 12 km/1 h resolution) reanalysis dataset during 1980–2018. Both parametric (linear regression) and non-parametric (e.g., Theil-Sen) robust statistical tools are employed in the study to analyze trend magnitudes, which are tested for statistical significance using the Mann-Kendall test. Standard precipitation indices from ETCCDI are also used to characterize trends in the relative contribution of extreme events to precipitation in the area. In the region an increasing trend (4.3 mm/year) is identified in annual average precipitation with ~34% of the domain showing a significant increase (at the 0.1 significance level) of +3 to +5 mm/year. Seasonal and sub-regional trends are also investigated, with the most pronounced increasing trends identified during summers along the Virginia and Maryland border. The study also finds a statistically significant positive trend (at a 0.05 significance level) in the annual maximum precipitation. Furthermore, the number of daily extremes (daily total precipitation higher than the 95th and 99th percentiles) also depicts statistically significant increases, indicating the increased frequency of extreme precipitation events. Investigations into the proportion of annual precipitation occurring on wet days and extremely wet days (95th and 99th percentile) also indicate a significant increase in their relative contribution. The findings of this study have the potential to improve local-scale decision-making in terms of river basin management, flood control, irrigation scheme scheduling, and stormwater infrastructure planning to address urban resilience to hydrometeorological hazards.

The importance of saturating density dependence for population-level predictions of SARS-CoV-2 resurgence compared with density-independent or linearly density-dependent models, England, 23 March to 31 July 2020

Background Population-level mathematical models of outbreaks typically assume that disease transmission is not impacted by population density (‘frequency-dependent’) or that it increases linearly with density (‘density-dependent’). Aim We sought evidence for the role of population density in SARS-CoV-2 transmission. Methods Using COVID-19-associated mortality data from England, we fitted multiple functional forms linking density with transmission. We projected forwards beyond lockdown to ascertain the consequences of different functional forms on infection resurgence. Results COVID-19-associated mortality data from England show evidence of increasing with population density until a saturating level, after adjusting for local age distribution, deprivation, proportion of ethnic minority population and proportion of key workers among the working population. Projections from a mathematical model that accounts for this observation deviate markedly from the current status quo for SARS-CoV-2 models which either assume linearity between density and transmission (30% of models) or no relationship at all (70%). Respectively, these classical model structures over- and underestimate the delay in infection resurgence following the release of lockdown. Conclusion Identifying saturation points for given populations and including transmission terms that account for this feature will improve model accuracy and utility for the current and future pandemics.

Providing Nursing Home Care in an Era of Increasing Scarcity: The Case of Pennsylvania

Medicaid financing of nursing home (NH) care provides the strongest safety net for low income older adults, persons who have high-intensity long-term care (LTC) needs, and consumers with exorbitant LTC costs. Yet, NHs currently face serious threats to their financial viability, particularly in the context of the COVID-19 pandemic, where the costs of caring for residents in a safe way have increased significantly, even as the ability to recoup these costs from the Medicaid program has been constrained. The purpose of this study is to assess key demand and supply factors affecting the performance of the NH industry in Pennsylvania over time. It draws from several large, national data sources, including NH Compare, LTCFocus.org, the U.S. Bureaus of the Census and Labor Statistics, and Certification and Survey Provider Enhanced Reports, as well as state-level population projections and Departments of Health and Human Services data. An aggregate database was constructed with historical data points at the facility, regional, and state level. Annual total and regional trends were examined from 2010 to 2020. Findings suggest a growing gap between what NHs require to meet the needs of residents and the level of reimbursement paid by the largest funder: Medicaid. Considering demographic trends, this gap will only grow over time in the absence of policy change. The pandemic has further highlighted the existing challenges resulting from an underfunded service infrastructure and the need for additional investment if NHs are to provide high quality care to a growing cohort of older adults requiring support.

Urban Boundary Demarcation—An iCN Model Approach

During the last two decades, determining the urban boundaries of cities has become one of the major concerns in the urban and regional planning subject domains. Many scholars have tried to model the change of urban boundaries as it helps with sustainable development, population projections and social policy making, but such efforts have been futile, owing to the complex nature of urbanization and the theoretical and technical limitations of the proposed applications. Hence, many countries continue to rely on the administrative boundary demarcation, which rarely represent the actual urbanizing pattern. In such context, this study utilized the “Intersection-Based Clustered Network Model—(iCN Model)” to determine the urban boundaries of cities and selected Sri Lanka as the study area and considered few cities to test the model empirically, with satellite imagery classified urban boundaries. The findings of the study depict that the iCN Model is capable of capturing the complex and dynamic socioeconomic interdependencies of cities via the transportation network configurations. Therefore, the proposed approach is an excellent proxy to derive the urban boundaries of cities, which correspond with the same, derived by the satellite imageries. The proposed model is entirely based on open-source GIS applications and is free to implement and modify using the methods described in this paper.

Projected number of osteoarthritis patients in Austria for the next decades – quantifying the necessity of treatment and prevention strategies in Europe

Background The present study aimed to predict the expected number of patients with osteoarthritis (OA) in Austria up to the year 2080. Methods Demographic data and population projections between 2019 and 2080 were obtained from European authorities. Information about recent age- and sex-stratified prevalence of patients with self-reported physician-diagnosed OA was obtained from the Austrian Health Interview Survey (n=15,771). Projections were stratified by age and sex; sensitivity analyses were performed based on aging (lower), main (most likely), and growth (upper) scenarios of the population. Results Based on the projection, the overall increase in the total number of patients with OA from 2019 to 2080 will be 38% for men and women. In 2019, the highest number of OA-patients nested in the groups of persons aged 70-79 (n=238,749) and 60-69 (n=237,729) years. In 2080, the 80+ age group is predicted to have the highest number of OA with 421,548 individuals (i.e. factor 3.45 and factor 2.48 increase in the male and female group, respectively, compared to 2019), followed by the group aged 70-79 with 314,617 individuals (factor 1.45 and factor 1.28 increase in the male and female group, respectively, compared to 2019). Similar trends were found in the ageing and growing scenarios. Conclusions The projected increase in the occurrence of OA will likely lead to a substantial socioeconomic burden for the Austrian healthcare system in the near and far future. The current findings plead for the development of sustainable concepts for the treatment and prevention of OA by European authorities.

Balance of sugarcane plantation land needs in Lamongan Regency in 2031 based on land-use changes using SPOT imagery

The volume of Indonesia's sugar imports in 2019 reached 4,09 million tons. The high volume of imports was influenced by the decreasing area of sugarcane plantations. Lamongan Regency is one of the sugarcane and sugar-producing regencies in East Java. Sugarcane and sugar production in Lamongan Regency has experienced quite diverse dynamics and has been influenced by changes in land-use conditions. This study aims to analyze the balance of land needs for sugarcane plantations in Lamongan Regency in 2031 based on an analysis of land-use changes using SPOT imagery of 2007, 2013, and 2019. The study was conducted by analyzing land-use changes, population projections, and land demand balance analysis for sugarcane plantations. The results of the analysis showed that the population of Lamongan Regency in 2031 is projected to reach 1.419.843 people with a land requirement for sugarcane plantations of 2.362,29 ha. There will be a land surplus of 1.276,92 ha but it is still concentrated in 7 of the 27 sub-districts. Sugarcane plantations in Lamongan Regency have the potential to be developed considering that the land allocation for plantations in the Lamongan Regency Spatial Plan of 2011-2031 reaches 10.022,42 ha.

Quantifying the potential market for new contraceptive technologies: global projections of 2040 contraceptive needs and preferences

Background: Despite a wide range of contraceptive methods, unmet need persists. New contraceptive technologies (CTs) have the potential to improve uptake and continuation. CT development has a long-time horizon; products will be introduced into markets that look very different than today. Identifying viable investments requires an understanding of these future markets. For this work the 2040 potential contraceptive market is described utilizing seven market segments based on marital status, fertility preferences, and patterns of sexual activity outside of marriage. Methods: Market size estimates are developed by country for all countries in the world for a current market (2020) and a future market (2040). United Nation’s (UN) population projections of the number of women of reproductive age (WRA) form the basis of this work. WRA are then segmented into market segments based on marital status, fertility intentions, and patterns of sexual activity outside of marriage. Each segment is further subdivided by contraceptive use versus non-use. Segmentation draws from UN projections, household surveys, census data, and modeling techniques developed for this work. Results: The largest market increases will be seen in Africa; most notably among the segment of married women wanting no more children. By contrast, Asia will see declines across all three married segments, coupled with increases among sexually active unmarried segments. Levels of contraceptive use are projected to vary widely by segment, with differential patters across regions. Conclusions: This analysis projects the impact of demographic changes, evolving fertility preferences, shifts in sexual activity outside of marriage and increased utilization of contraceptives in shaping the contraceptive market of 2040. Results show that there is not one global market, but distinct markets that vary in size and shape across the world. This diversity suggests that a range of different new CTs could have potential for uptake.