Modelling the impact of antimicrobial use and external introductions on commensal E. coli colistin resistance in small-scale chicken farms of the Mekong delta of Vietnam

Colistin is a critically important antimicrobial for human medicine, and colistin-resistant Escherichia coli are commonly found in poultry and poultry products in Southeast Asia. Here, we aim at disentangling the within-farm and outside-farm drivers of colistin resistance in small-scale chicken farms of the Mekong delta of Vietnam. Nineteen Vietnamese chicken farms were followed up along a whole production cycle, during which weekly antimicrobial use data were recorded. At the beginning, middle and end of each production cycle, commensal E. coli samples from birds were collected, pooled and tested for colistin resistance. Twelve models were fitted to the data using an expectation-maximization algorithm and compared. We further tested the spatial clustering of the occurrence of resistance importations from external sources using the local Moran's I statistic. In the best model, colistin resistance in E. coli from chickens was found to be mostly affected by importations of resistance, and, to a lesser extent, by the use of antimicrobials in the last 1.73 weeks [0.00; 2.90], but not by the use of antimicrobials in day-olds, nor their colistin resistance carriage from hatchery. The occurrence of external source importations proved to be sometimes spatially clustered, suggesting a role of local environmental sources of colistin resistance.

Optimizing management of invasions in an uncertain world using dynamic spatial models

Dispersal drives invasion dynamics of nonnative species and pathogens. Applying knowledge of dispersal to optimize the management of invasions can mean the difference between a failed and a successful control program and dramatically improve the return on investment of control efforts. A common approach to identifying optimal management solutions for invasions is to optimize dynamic spatial models that incorporate dispersal. Optimizing these spatial models can be very challenging because the interaction of time, space, and uncertainty rapidly amplifies the number of dimensions being considered. Addressing such problems requires advances in and the integration of techniques from multiple fields, including ecology, decision analysis, bioeconomics, natural resource management, and optimization. By synthesizing recent advances from these diverse fields, we provide a workflow for applying ecological theory to advance optimal management science and highlight priorities for optimizing the control of invasions. One of the striking gaps we identify is the extremely limited consideration of dispersal uncertainty in optimal management frameworks, even though dispersal estimates are highly uncertain and greatly influence invasion outcomes. In addition, optimization frameworks rarely consider multiple types of uncertainty (we describe five major types) and their interrelationships. Thus, feedbacks from management or other sources that could magnify uncertainty in dispersal are rarely considered. Incorporating uncertainty is crucial for improving transparency in decision risks and identifying optimal management strategies. We discuss gaps and solutions to the challenges of optimization using dynamic spatial models to increase the practical application of these important tools and improve the consistency and robustness of management recommendations for invasions.

Measuring Obesogenicity and Assessing Its Impact on Child Obesity: A Cross-Sectional Ecological Study for England Neighbourhoods

Both major influences on changing obesity levels (diet and physical activity) may be mediated by the environment, with environments that promote higher weight being denoted obesogenic. However, while many conceptual descriptions and definitions of obesogenic environments are available, relatively few attempts have been made to quantify obesogenic environments (obesogenicity). The current study is an ecological study (using area units as observations) which has as its main objective to propose a methodology for obtaining a numeric index of obesogenic neighbourhoods, and assess this methodology in an application to a major national dataset. One challenge in such a task is that obesogenicity is a latent aspect, proxied by observed environment features, such as poor access to healthy food and recreation, as well as socio-demographic neighbourhood characteristics. Another is that obesogenicity is potentially spatially clustered, and this feature should be included in the methodology. Two alternative forms of measurement model (i.e., models representing a latent quantity using observed indicators) are considered in developing the obesogenic environment index, and under both approaches we find that both food and activity indicators are pertinent to measuring obesogenic environments (though with varying relevance), and that obesogenic environments are spatially clustered. We then consider the role of the obesogenic environment index in explaining obesity and overweight rates for children at ages 10-11 in English neighbourhoods, along with area deprivation, population ethnicity, crime levels, and a measure of urban-rural status. We find the index of obesogenic environments to have a significant effect in elevating rates of child obesity and overweight. As a major conclusion, we establish that obesogenic environments can be measured using appropriate methods, and that they play a part in explaining variations in child weight indicators; in short, area context is relevant.

Novel Spatio-Temporal Continuous Sign Language Recognition Using an Attentive Multi-Feature Network

Given video streams, we aim to correctly detect unsegmented signs related to continuous sign language recognition (CSLR). Despite the increase in proposed deep learning methods in this area, most of them mainly focus on using only an RGB feature, either the full-frame image or details of hands and face. The scarcity of information for the CSLR training process heavily constrains the capability to learn multiple features using the video input frames. Moreover, exploiting all frames in a video for the CSLR task could lead to suboptimal performance since each frame contains a different level of information, including main features in the inferencing of noise. Therefore, we propose novel spatio-temporal continuous sign language recognition using the attentive multi-feature network to enhance CSLR by providing extra keypoint features. In addition, we exploit the attention layer in the spatial and temporal modules to simultaneously emphasize multiple important features. Experimental results from both CSLR datasets demonstrate that the proposed method achieves superior performance in comparison with current state-of-the-art methods by 0.76 and 20.56 for the WER score on CSL and PHOENIX datasets, respectively.

Age- and Sex-Specific Association Between Vegetation Cover and Mental Health Disorders: Bayesian Spatial Study

BACKGROUND

Despite growing evidence that reduced vegetation cover could be a putative risk factor for mental health disorders, the age- and the sex-specific association between vegetation and mental health disorder cases in urban areas is poorly understood. However, with rapid urbanization across the globe, there is an urgent need to study this association and understand the potential impact of vegetation loss on the mental well-being of urban residents.

OBJECTIVE

This study aims to analyze the spatial association between vegetation cover and the age- and sex-stratified mental health disorder cases in the neighborhoods of Toronto, Canada.

METHODS

We used remote sensing to detect urban vegetation and Bayesian spatial hierarchical modeling to analyze the relationship between vegetation cover and mental health disorder cases. Specifically, an Enhanced Vegetation Index was used to detect urban vegetation, and Bayesian Poisson lognormal models were implemented to study the association between vegetation and mental health disorder cases of males and females in the 0-19, 20-44, 45-64, and ≥65 years age groups, after controlling for marginalization and unmeasured (latent) spatial and nonspatial covariates at the neighborhood level.

RESULTS

The results suggest that even after adjusting for marginalization, there were significant age- and sex-specific effects of vegetation on the prevalence of mental health disorders in Toronto. Mental health disorders were negatively associated with the vegetation cover for males aged 0-19 years (-7.009; 95% CI -13.130 to -0.980) and for both males (-4.544; 95% CI -8.224 to -0.895) and females (-3.513; 95% CI -6.289 to -0.681) aged 20-44 years. However, for older adults in the 45-64 and ≥65 years age groups, only the marginalization covariates were significantly associated with mental health disorder cases. In addition, a substantial influence of the unmeasured (latent) and spatially structured covariates was detected in each model (relative contributions>0.7), suggesting that the variations in area-specific relative risk were mainly spatial in nature.

CONCLUSIONS

As significant and negative associations between vegetation and mental health disorder cases were found for young males and females, investments in urban greenery can help reduce the future burden of mental health disorders in Canada. The findings highlight the urgent need to understand the age-sex dynamics of the interaction between surrounding vegetation and urban dwellers and its subsequent impact on mental well-being.

Local Disproportions of Quality of Life and Their Influence on the Process of Green Economy Development in Polish Voivodships in 2010-2020

Voivodships are centres of economic, social, and cultural life-they gather economic and social activities. This research aimed to evaluate the spatial differentiation of the quality of life in voivodships in Poland with the use of a synthetic measure. To achieve the research objective, the research methods used were literature analysis, statistical analysis, and synthetic measure. The Technique for Order Preference by Similarity to an Ideal Solution method was used to build synthetic measures. The choice of variables in 2010-2020 was largely conditioned by the availability of data collected in the regional system at the level of voivodships at the Local Data Bank of the Central Statistical Office. As a result of the analysis of voivodships in Poland, based on the quality of life measure, four groups were distinguished (according to the value of quartiles). In the group of the best voivodeships there were: Pomerania, Masovia, Lower Silesia, and West Pomeranian in 2010, and Masovia, Pomerania, Greater Poland, Lower Silesia, and Lesser Poland in 2020, and in the IV, the weakest group: Lodz Province, Podlasie Province, Lubusz Province, and Holy Cross in 2010, and Lodz Province, Podlasie Province, Holy Cross, and Lublin Province in 2020. The synthetic quality of life ranged from 0.37 to 0.56 in 2010 and from 0.39 to 0.64 in 2020. Regional authorities, taking care to improve economic potential, cause increasing the attractiveness of the area and attracting new entrepreneurs, create new jobs, and improve the quality of life of the inhabitants. Quality of life is shaped by economic activity and working conditions, health, education, free time and social relations, economic and physical security, and the quality of the natural environment. The results of the research conducted allow local governments to make comparisons. The conclusions drawn may allow them to identify potential directions for developing policy optimization.

Copula Geo-Additive Modeling of Anaemia and Malnutrition among Children under Five Years in Angola, Senegal, and Malawi

Notwithstanding the interventions implemented to address child mortality, anaemia and malnutrition remain a concern for the future of developing countries. Anaemia and malnutrition contribute a high proportion of the causes of childhood morbidity in Africa. The objective of this study is to jointly model anaemia and malnutrition using a copula geo-additive model. This study is a secondary data analysis where a Demographic and Health Survey of 2016 data from Angola, Malawi, and Senegal was used. The descriptive analysis was conducted in SPSS and the copula geo-additive model analysis was performed in R 3.63. The results showed that female children are notably associated with anaemia and a malnourished status (female estimate = 0.144, p-value = 0.027 for anaemia; female estimate = −0.105, p-value = 000 for malnutrition). The probability of each result decreased with an improvement in the mother’s level of schooling. This indicates an urgent requirement for interventions to be implemented by policymakers in order to manage children’s mortality rates. These interventions can include the introduction of educational programs for older adults, children’s dietary programs, and income generation initiatives (starting a small business, etc.). It is hoped that this paper can foster the utilization of copula methodology in this field of science with the use of cross-sectional data.

Impact of Match Type and Match Halves on Referees' Physical Performance and Decision-Making Distance in Chinese Football Super League

The purpose of this study was to explore how Chinese Football Super League (CSL) referees' physical performance and decision-making distance varied according to match type and match halves. Data from 107 matches played by top-4 ranked and bottom-4 ranked teams during 2018-2019 CSL seasons were collected. Level of matches was classified into three groups: (a) upper-ranked (top-4) teams against top-4 teams, (b) top-4 teams against lower-ranked teams (bottom-4), and (c) bottom-4 teams against bottom-4 teams. Two-way ANOVA and Scheirer-Ray-Hare test were used to examine the statistical differences of referees' physical and spatial related distance variables among different match levels and halves. The Euclidean distance to the ball at the following three variables were statistically different among three match types: clearance (p = 0.03,E R 2 = 0.03), running with the ball (p = 0.01,E R 2 = 0.04), and shot off target (p = 0.04,E R 2 = 0.03). In addition, referees' distance to the ball at three events were statistically different between both match halves: pass (p < 0.001, r = 0.69), reception (p < 0.001, r = 0.76), and running with the ball (p < 0.001, r = 0.77). The total running distance was statistically different between both match halves (p = 0.001, d = 0.05). The findings indicated that although CSL referees showed little difference in physical performance when officiating matches of three competitive levels and two halves, distinct rhythms of competitions determined that they needed to adjust running strategies to maintain proper distance to the ball. This study implied that the CSL referees' match performance was affected by the teams' style of play and match status.

Large herbivores trigger spatiotemporal changes in forest plant diversity

Large herbivores can exert top-down control on terrestrial plant communities, but the magnitude, direction, and scale-dependency of their impacts remain equivocal, especially in temperate and boreal forests, where multiple disturbances often interact. Using a unique, long-term and replicated landscape experiment, we assessed the influence of a high density of white-tailed deer (Odocoileus virginianus) on the spatiotemporal dynamics of diversity, composition, and successional trajectories of understorey plant assemblages in recently logged boreal forests. This experiment provided a rare opportunity to test whether deer herbivory represents a direct filter on plant communities or if it mainly acts to suppress dominant plants which, in turn, release other plant species from strong negative plant-plant interactions. These two hypotheses make different predictions about changes in community composition, alpha and beta diversity in different vegetation layers and at different spatial scales. Our results showed that deer had strong effects on plant community composition and successional trajectories, but the resulting impacts on plant alpha and beta diversity patterns were markedly scale-dependent in both time and space. Responses of tree and non-tree vegetation layers were strongly asymmetric. Deer acted both as a direct filter and as a suppressor of dominant plant species during early forest succession, but the magnitude of both processes was specific to tree and non-tree vegetation layers. Although our data supported the ungulate-driven homogenization hypothesis, compositional shifts and changes of alpha diversity were poor predictors of beta diversity loss. Our findings underscore the importance of long-term studies in revealing non-linear temporal community trends, and they challenge managers to prioritize particular community properties and scales of interest, given contrasting trends of composition, alpha, and beta diversity across spatial scales.

Geographic accessibility to health facilities predicts uptake of community-based tuberculosis screening in an urban setting

Objectives:

Annually, more than 30% of individuals with tuberculosis (TB) remain undiagnosed. We aimed to assess whether geographic accessibility measures can identify neighborhoods that would benefit from TB screening services targeted toward closing the diagnosis gap.

Methods:

We used data from a community-based mobile TB screening program in Carabayllo district, Lima, Peru. We constructed four accessibility measures from the geographic center of neighborhoods to health facilities. We used logistic regression to assess the association between these measures and screening uptake in one’s residential neighborhood versus elsewhere, with quasi-information criterion values to assess the association.

Results:

We analyzed the screening locations for 25,000 Carabayllo residents from 49 neighborhoods. Pedestrian walk time was preferable to Euclidean distance or vehicular time in our models. For each additional 12 minutes walking time between the neighborhood and the health facility, the odds of residents using TB screening units located in their neighborhoods increased by 50% (95% CI: 26%–78%). Females had 9% (95% CI: 3%–16%) increased odds versus males of using a screening unit in their own neighborhood.

Conclusion:

Placing mobile TB screening units in neighborhoods with longer pedestrian time to access health facilities could benefit individuals who face more acute access barriers to health care.

Persistent neuronal firing in the medial temporal lobe supports performance and workload of visual working memory in humans

The involvement of the medial temporal lobe (MTL) in working memory is controversially discussed. Recent findings suggest that persistent neural firing in the hippocampus during maintenance in verbal working memory is associated with workload. Here, we recorded single neuron firing in 13 epilepsy patients (7 male) while they performed a visual working memory task. The number of coloured squares in the stimulus set determined the workload of the trial. Performance was almost perfect for low workload (1 and 2 squares) and dropped at high workload (4 and 6 squares), suggesting that high workload exceeded working memory capacity. We identified maintenance neurons in MTL neurons that showed persistent firing during the maintenance period. More maintenance neurons were found in the hippocampus for trials with correct compared to incorrect performance. Maintenance neurons increased and decreased firing in the hippocampus and increased firing in the entorhinal cortex for high compared to low workload. Population firing predicted workload particularly during the maintenance period. Prediction accuracy of workload based on single-trial activity during maintenance was strongest for neurons in the entorhinal cortex and hippocampus. The data suggest that persistent neural firing in the MTL reflects a domain-general process of maintenance supporting performance and workload of multiple items in working memory below and beyond working memory capacity. Persistent neural firing during maintenance in the entorhinal cortex may be associated with its preference to process visual-spatial arrays.

A Bayesian Hierarchical Spatial Model to Correct for Misreporting in Count Data: Application to State-Level COVID-19 Data in the United States

The COVID-19 pandemic that began at the end of 2019 has caused hundreds of millions of infections and millions of deaths worldwide. COVID-19 posed a threat to human health and profoundly impacted the global economy and people's lifestyles. The United States is one of the countries severely affected by the disease. Evidence shows that the spread of COVID-19 was significantly underestimated in the early stages, which prevented governments from adopting effective interventions promptly to curb the spread of the disease. This paper adopts a Bayesian hierarchical model to study the under-reporting of COVID-19 at the state level in the United States as of the end of April 2020. The model examines the effects of different covariates on the under-reporting and accurate incidence rates and considers spatial dependency. In addition to under-reporting (false negatives), we also explore the impact of over-reporting (false positives). Adjusting for misclassification requires adding additional parameters that are not directly identified by the observed data. Informative priors are required. We discuss prior elicitation and include R functions that convert expert information into the appropriate prior distribution.

Age and Auditory Spatial Perception in Humans: Review of Behavioral Findings and Suggestions for Future Research

It has been well documented, and fairly well known, that concomitant with an increase in chronological age is a corresponding increase in sensory impairment. As most people realize, our hearing suffers as we get older; hence, the increased need for hearing aids. The first portion of the present paper is how the change in age apparently affects auditory judgments of sound source position. A summary of the literature evaluating the changes in the perception of sound source location and the perception of sound source motion as a function of chronological age is presented. The review is limited to empirical studies with behavioral findings involving humans. It is the view of the author that we have an immensely limited understanding of how chronological age affects perception of space when based on sound. In the latter part of the paper, discussion is given to how auditory spatial perception is traditionally conducted in the laboratory. Theoretically, beneficial reasons exist for conducting research in the manner it has been. Nonetheless, from an ecological perspective, the vast majority of previous research can be considered unnatural and greatly lacking in ecological validity. Suggestions for an alternative and more ecologically valid approach to the investigation of auditory spatial perception are proposed. It is believed an ecological approach to auditory spatial perception will enhance our understanding of the extent to which individuals perceive sound source location and how those perceptual judgments change with an increase in chronological age.

Spatial Distribution and Predictive Significance of Dendritic Cells and Macrophages in Esophageal Cancer Treated With Combined Chemoradiotherapy and PD-1 Blockade

Background

The first clinical study (NCT03671265) of first-line chemoradiotherapy combined with PD-1 blockade showed promising treatment outcomes in locally advanced esophageal squamous cell carcinoma (ESCC). However, partial patients did not respond to the combination treatment. The roles of dendritic cells (DCs) and macrophages in this combination treatment remain poorly understood.

Methods

We performed multiplexed immunofluorescence method to identify CD11c⁺ DCs, CD68⁺ macrophages, and their PD-L1^- or PD-L1⁺ subpopulations in paired tumor biopsies (n = 36) collected at baseline and during the combination treatment (after radiation, 40 Gy) from the phase Ib trial (NCT03671265). We applied whole exome sequencing in the baseline tumor biopsies (n = 14) to estimate tumor mutation burden (TMB). We dynamically investigated the spatial distribution of DCs and macrophages under chemoradiotherapy combined with PD-1 blockade, and evaluated the association between their spatial distribution and combination outcome, and TMB.

Results

The results showed that high percentages of PD-L1^- DCs and macrophages in the baseline tumor compartment, but not in the stromal compartment, predicted improved OS and PFS. Chemoradiotherapy combined with PD-1 blockade promoted DCs and macrophages to migrate closer to tumor cells. During combination treatment, PD-L1^- tumor cells were nearest to PD-L1^- DCs and macrophages, while PD-L1⁺ tumor cells were next to PD-L1⁺ DCs and macrophages. High TMB was closely associated with a shorter distance from tumor cells to DCs and macrophages. Shorter distance between PD-L1⁺ tumor cells and PD-L1⁺ DCs or PD-L1^- macrophages during the combination was correlated with better OS. Shorter distance between PD-L1^- tumor cells and PD-L1^- macrophages during combination was associated with both longer OS and PFS.

Conclusions

PD-L1^- or PD-L1⁺ DCs and macrophages exhibit distinct spatial distribution in ESCC. The close distance between tumor cells and these antigen-presenting cells (APCs) is critical to the clinical outcome in chemoradiotherapy combined with PD-1 blockade in ESCC patients. Our results highlight the predictive potential of spatial patterns of APCs in chemoradiotherapy combined with immunotherapy and reveal the underlying mechanism of APCs participating in chemoradiotherapy-induced antitumor immune response in ESCC.

Spatial mapping and socio-demographic determinants of COVID-19 mortality in India

Background

COVID-19 is caused by SARS-CoV-2. The first case of COVID-19 was detected in Wuhan city of China in December 2019. Geographic information system (GIS) mapping is important for the surveillance of infectious diseases.

Objectives

The objectives of the study are to map spatially total cases and case fatality rate of COVID-19 and to build a linear regression model for mortality based on socio-demographic variables.

Methology

We plotted the epidemiological data of COVID-19 of Indian states as on 11^th May 2021 using the Q-GIS software. We used socio-demographic variables as the predictors of COVID-19 mortality and developed a linear regression model.

Results

Adjusted R-squared in linear regression model based on socio-demographic variables for COVID-19 deaths is 0.82.

Conclusions

There are spatial variations in COVID-19 cases and deaths.

Spatially Resolved Transcriptomic Analysis of Acute Kidney Injury in a Female Murine Model

BACKGROUND

Single-cell sequencing technologies have advanced our understanding of kidney biology and disease, but the loss of spatial information in these datasets hinders our interpretation of intercellular communication networks and regional gene expression patterns. New spatial transcriptomic sequencing platforms make it possible to measure the topography of gene expression at genome depth.

METHODS

We optimized and validated a female bilateral ischemia-reperfusion injury model. Using the 10× Genomics Visium Spatial Gene Expression solution, we generated spatial maps of gene expression across the injury and repair time course, and applied two open-source computational tools, Giotto and SPOTlight, to increase resolution and measure cell-cell interaction dynamics.

RESULTS

An ischemia time of 34 minutes in a female murine model resulted in comparable injury to 22 minutes for males. We report a total of 16,856 unique genes mapped across our injury and repair time course. Giotto, a computational toolbox for spatial data analysis, enabled increased resolution mapping of genes and cell types. Using a seeded nonnegative matrix regression (SPOTlight) to deconvolute the dynamic landscape of cell-cell interactions, we found that injured proximal tubule cells were characterized by increasing macrophage and lymphocyte interactions even 6 weeks after injury, potentially reflecting the AKI to CKD transition.

CONCLUSIONS

In this transcriptomic atlas, we defined region-specific and injury-induced loss of differentiation markers and their re-expression during repair, as well as region-specific injury and repair transcriptional responses. Lastly, we created an interactive data visualization application for the scientific community to explore these results (http://humphreyslab.com/SingleCell/).

Spatio-Temporal Distribution and Demographic Characteristics of Congenital Heart Defects in Guangdong, China, 2016-2020

BACKGROUND

Congenital heart defects are the most common type of birth defects and bring a heavy disease burden in China. Examining the temporal and spatial trends of congenital heart defects epidemics can give some elementary knowledge for succeeding studies.

OBJECTIVE

To characterize the spatial-temporal patterns of the prevalence of congenital heart defects based on a substantial cohort of the perinatal fetus in south China in 2016-2020.

METHODS

This study was a retrospective population-based cohort study conducted in Guangdong, China from 2016 to 2020. Pregnant women and their infants received birth defect surveillance during pregnancy and seven days after delivery in more than 1,900 midwifery hospitals in 21 cities. Perinatal infants with congenital heart defects were identified and enrolled. The prevalence of congenital heart defects was calculated according to cities, years, urban and rural areas, regions of Guangdong, categories of maternal age at delivery, seasons of delivery, and infant's gender.

RESULTS

A total of 8,653,206 perinatal infants and 53,912 total congenital heart defects were monitored in Guangdong, including 46,716 (86.65%) without other defects and 7,736 (13.35%) with other defects. The average prevalence of total congenital heart defects was 62.30/10,000 (95% CI, 61.78/10,000-62.83/10,000), congenital heart defects without other defects was 53.36/10,000 (95% CI, 52.88/10,000-53.85/10,000), and congenital heart defects with other defects was 8.94/10,000 (95%CI, 8.74/10,000-9.14/10,000). From 2016 to 2020, the prevalence of total congenital heart defects was 54.92/10,000, 54.23/10,000, 63.79/10,000, 73.11/10,000, 68.20/10,000, respectively. We observed geographical variations within the prevalence of congenital heart defects. The prevalence of congenital heart defects was much higher in the Pearl River Delta region than in the non-Pearl River Delta region, as well as higher in urban areas than in rural areas.

CONCLUSION

The findings of this study are helpful to the understanding of the etiology and epidemiology characteristics of congenital heart defects in south China. Our data likely reflect a better estimate of the spatiotemporal trends in congenital heart defects prevalence than reported previously.

Efficient design of geographically-defined clusters with spatial autocorrelation

Clusters form the basis of a number of research study designs including survey and experimental studies. Cluster-based designs can be less costly but also less efficient than individual-based designs due to correlation between individuals within the same cluster. Their design typically relies on ad hoc choices of correlation parameters, and is insensitive to variations in cluster design. This article examines how to efficiently design clusters where they are geographically defined by demarcating areas incorporating individuals and households or other units. Using geostatistical models for spatial autocorrelation, we generate approximations to within cluster average covariance in order to estimate the effective sample size given particular cluster design parameters. We show how the number of enumerated locations, cluster area, proportion sampled, and sampling method affect the efficiency of the design and consider the optimization problem of choosing the most efficient design subject to budgetary constraints. We also consider how the parameters from these approximations can be interpreted simply in terms of 'real-world' quantities and used in design analysis.

The Impact of Demographic, Socio-Economic and Geographic Factors on Mortality Risk among People Living with Dementia in England (2002-2016)

Increasing numbers of people living with dementia (PLWD), and a pressured health and social care system, will exacerbate inequalities in mortality for PLWD. There is a dearth of research examining multiple factors in mortality risk among PLWD, including application of large administrative datasets to investigate these issues. This study explored variation mortality risk variation among people diagnosed with dementia between 2002-2016, based on: age, sex, ethnicity, deprivation, geography and general practice (GP) contacts. Data were derived from electronic health records from a cohort of Clinical Practice Research Datalink GP patients in England (n = 142,340). Cox proportional hazards regression modelled mortality risk separately for people with early- and later- onset dementia. Few social inequalities were observed in early-onset dementia; men had greater risk of mortality. For early- and later-onset, higher rates of GP observations-and for later-onset only dementia medications-are associated with increased mortality risk. Social inequalities were evident in later-onset dementia. Accounting for other explanatory factors, Black and Mixed/Other ethnicity groups had lower mortality risk, more deprived areas had greater mortality risk, and higher mortality was observed in North East, South Central and South West GP regions. This study provides novel evidence of the extent of mortality risk inequalities among PLWD. Variance in mortality risk was observed by social, demographic and geographic factors, and frequency of GP contact. Findings illustrate need for greater person-centred care discussions, prioritising tackling inequalities among PLWD. Future research should explore more outcomes for PLWD, and more explanatory factors of health outcomes.

Spatial and Temporal Variations in PM10 Concentrations between 2010-2017 in South Africa

Particulate matter less than or equal to 10 μm in aerodynamic diameter (PM₁₀ µg/m³) is a priority air pollutant and one of the most widely monitored ambient air pollutants in South Africa. This study analyzed PM₁₀ from monitoring 44 sites across four provinces of South Africa (Gauteng, Mpumalanga, Western Cape and KwaZulu-Natal) and aimed to present spatial and temporal variation in the PM₁₀ concentration across the provinces. In addition, potential influencing factors of PM₁₀ variations around the three site categories (Residential, Industrial and Traffic) were explored. The spatial trend in daily PM₁₀ concentration variation shows PM₁₀ concentration can be 5.7 times higher than the revised 2021 World Health Organization annual PM₁₀ air quality guideline of 15 µg/m³ in Gauteng province during the winter season. Temporally, the highest weekly PM₁₀ concentrations of 51.4 µg/m³, 46.8 µg/m³, 29.1 µg/m³ and 25.1 µg/m³ at Gauteng, Mpumalanga, KwaZulu-Natal and Western Cape Province were recorded during the weekdays. The study results suggest a decrease in the change of annual PM₁₀ levels at sites in Gauteng and Mpumalanga Provinces. An increased change in annual PM₁₀ levels was reported at most sites in Western Cape and KwaZulu-Natal.

Chronic, Mild Vestibulopathy Leads to Deficits in Spatial Tasks that Rely on Vestibular Input While Leaving Other Cognitive Functions and Brain Volumes Intact

Objectives: In this study, based on the known vestibulo-hippocampal connections, we asked whether mild chronic vestibulopathy leads only to vestibular-related deficits or whether there are effects on hippocampal function, structure, and cognition in general. In more detail, we assessed whether chronic vestibulopathy leads to (a) deficits in vestibular tasks without cognitive demand (balancing), (b) deficits in spatial cognitive tasks that require vestibular input (path integration, rotational memory), (c) deficits in spatial cognitive tasks that do not rely on vestibular input, (d) deficits in general cognitive function, and (e) atrophy in the brain. Methods: A total of 15 patients with chronic uni- or bilateral vestibulopathy (56.8 ± 10.1 years; 4 females) were included in this study and were age- and gender-matched by the control participants (57.6 ± 10.5) in a pairwise manner. Given their clinical symptoms and their deficits of the vestibulo-ocular reflex (VOR) the patients could be classified as being mildly affected. All participants of the underwent the following tests: clinical balance (CBT), triangle completion (TCT) for path integration, rotational memory (RM), the visuo-spatial subset of the Berlin intelligence structure test (BIS-4) and d2-R for attention and concentration, and a structural MRI for gray matter analysis using voxel-based morphometry (VBM). Results: Compared to the healthy controls, the vestibulopathy patients performed significantly worse in terms of CBT, TCT, and RM but showed no differences in terms of the BIS-4 and d2-R. There were also no significant volumetric gray matter differences between the two groups. Conclusions: This study provides evidence that both non-cognitive and cognitive functions that rely on vestibular input (balancing, path integration, rotational memory) are impaired, even in mild chronic vestibulopathy, while other cognitive functions, which rely on visual input (visuo-spatial memory, attention), are unimpaired in this condition, together with an overall intact brain structure. These findings may reflect a segregation between vestibular- and visual-dependent processes in the medial temporal lobe on the one hand and a structure–function dissociation on the other.

Spatial Variation in Australian Neonicotinoid Usage and Priorities for Resistance Monitoring

Australia is the third largest exporting country of cereals and a leader in other major commodity crops, yet little data exist on pesticide usage patterns in agriculture. This knowledge gap limits the management of off-target chemical impacts, such as the evolution of pesticide resistance. Here, for the first time, we quantify spatial patterns in neonicotinoid applications in Australia by coalescing land use data with sales and market research data contributed by agrichemical and agribusiness companies. An example application to resistance management is explored through the development of recommendations for the cosmopolitan crop pest, Myzus persicae (Sulzer) (Hemiptera: Aphididae), utilizing spatial statistical models. This novel dataset identified Australian neonicotinoid usage patterns, with most neonicotinoid products in Australia applied as cereal, canola, cotton and legume seed treatments and soil applications in sugarcane. Importantly, there were strong regional differences in pesticide applications, which will require regionally specific strategies to manage off-target impacts. Indeed, the estimated spatial grid of neonicotinoid usage demonstrated a statistically significant influence on the distribution of M. persicae neonicotinoid resistance, indicating off-target impacts are unevenly distributed in space. Future research on neonicotinoid usage will be supported by the spatial grids generated and made available through this study. Overall, neonicotinoid pesticides are widely relied upon throughout Australia's plant production systems but will face increasing pressure from resistance evolution, emerging research on off-target impacts, and stricter regulatory pressures.

Global Harmonization of Urbanization Measures: Proceed with Care

By 2050, two-thirds of the world's population is expected to be living in cities and towns, a marked increase from today's level of 55 percent. If the general trend is unmistakable, efforts to measure it precisely have been beset with difficulties: the criteria defining urban areas, cities and towns differ from one country to the next and can also change over time for any given country. The past decade has seen great progress toward the long-awaited goal of scientifically comparable urbanization measures, thanks to the combined efforts of multiple disciplines. These efforts have been organized around what is termed the "statistical urbanization" concept, whereby urban areas are defined by population density, contiguity and total population size. Data derived from remote-sensing methods can now supply a variety of spatial proxies for urban areas defined in this way. However, it remains to be understood how such proxies complement, or depart from, meaningful country-specific alternatives. In this paper, we investigate finely resolved population census and satellite-derived data for the United States, Mexico and India, three countries with widely varying conceptions of urban places and long histories of debate and refinement of their national criteria. At the extremes of the urban-rural continuum, we find evidence of generally good agreement between the national and remote sensing-derived measures (albeit with variation by country), but identify significant disagreements in the middle ranges where today's urban policies are often focused.

Riverscape approaches in practice: perspectives and applications

Landscape perspectives in riverine ecology have been undertaken increasingly in the last 30 years, leading aquatic ecologists to develop a diverse set of approaches for conceptualizing, mapping and understanding 'riverscapes'. Spatiotemporally explicit perspectives of rivers and their biota nested within the socio-ecological landscape now provide guiding principles and approaches in inland fisheries and watershed management. During the last two decades, scientific literature on riverscapes has increased rapidly, indicating that the term and associated approaches are serving an important purpose in freshwater science and management. We trace the origins and theoretical foundations of riverscape perspectives and approaches and examine trends in the published literature to assess the state of the science and demonstrate how they are being applied to address recent challenges in the management of riverine ecosystems. We focus on approaches for studying and visualizing rivers and streams with remote sensing, modelling and sampling designs that enable pattern detection as seen from above (e.g. river channel, floodplain, and riparian areas) but also into the water itself (e.g. aquatic organisms and the aqueous environment). Key concepts from landscape ecology that are central to riverscape approaches are heterogeneity, scale (resolution, extent and scope) and connectivity (structural and functional), which underpin spatial and temporal aspects of study design, data collection and analysis. Mapping of physical and biological characteristics of rivers and floodplains with high-resolution, spatially intensive techniques improves understanding of the causes and ecological consequences of spatial patterns at multiple scales. This information is crucial for managing river ecosystems, especially for the successful implementation of conservation, restoration and monitoring programs. Recent advances in remote sensing, field-sampling approaches and geospatial technology are making it increasingly feasible to collect high-resolution data over larger scales in space and time. We highlight challenges and opportunities and discuss future avenues of research with emerging tools that can potentially help to overcome obstacles to collecting, analysing and displaying these data. This synthesis is intended to help researchers and resource managers understand and apply these concepts and approaches to address real-world problems in freshwater management.