The immunopathology of COVID-19 placentitis: A multi-omic spatial approach

Problem: COVID-19 placentitis is a rare complication of maternal SARS-CoV-2 respiratory infection associated with serious adverse obstetric outcomes, including intra-uterine death. The precise role of SARS-CoV-2 in COVID-19 placentitis is uncertain, as trophoblast infection is only observed in around one-half of the affected placenta. Method of Study: Through multi-omic spatial profiling, including Nanostring GeoMX digital spatial profiling and Lunaphore COMET multiplex IHC, we provide a deep characterization of the immunopathology of placentitis from obstetrically complicated maternal COVID-19 infection. Result(s):We show that SARS-CoV-2 infection of placental trophoblasts is associated with a distinct innate and adaptive immune cell infiltrate, florid cytokine expression and upregulation of viral restriction factors. Quantitative spatial analyses reveal a unique microenvironment surrounding virus-infected trophoblasts characterizedd by multiple immune evasion mechanisms, including immune checkpoint expression, cytotoxic T-cell exclusion, and interferon blunting. Placental viral loads inversely correlated with the duration of maternal infection consistent with progressive virus clearance, potentially explaining the absence of virus in some cases. Conclusion(s): Our results demonstrate a central role for placental SARS-CoV-2 infection in driving the unique immunopathology of COVID-19 placentitis.

Spatial determinants affected maternal mortality of East Java province during the covid-19 pandemic era, in 2020-2021

Background. Every life aspect and group of the community have changed during the COVID-19 pandemic, including the group of pregnant, childbirth, and postpartum woman. COVID-19 Pandemic occurred in 2020-2021. Maternal mortality in East Java Province was the highest in Indonesia during the pandemic. Objective. This study analyzed the effect of spatial determinants that consist of antenatal, childbirth, and post-partum care on maternal mortality in East Java Province during the Pandemic. Methods. This study used a crossectional method with the unit of analysis in this study was all pregnant, childbirth and postpartum women in 38 districts of East Java Province from 2020 until 2021. Data were analyzed with spatial regression by using Geographically Weighted Regression Software. Results. Maternal mortality in East Java had a spreading pat-tern and negative value of the diff criterion, so we concluded that there was a spatial influence. The variables of antenatal care, accessibility of healthcare service, third postpartum visit, and complication service had significant effects on maternal mortality in all regions (P<0,05). There were four groups of districts that showed a similarity of significant factors. This result showed that each region's diversity of the accessibility of health services affects maternal mortality during the COVID-19 era. Antenatal services, access to health facilities and complication services affected maternal mortality in regions with high maternal mortality rate. Conclusion. Every region has its spatial determinants of maternal mortality. The top government should give authority to local government to have programs to reduce maternal mortality according to the condition in their region. r.Copyright © the Author(s), 2023.

GIS-Based Analysis of the Spatial Distribution and Influencing Factors of Traditional Villages in Hebei Province, China

Traditional villages are a valuable cultural asset that occupy an important position in Chinese traditional culture. This study focuses on 206 traditional villages in Hebei Province and aims to explore their spatial distribution characteristics and influencing factors using ArcGIS spatial analysis. The analysis shows that traditional villages in Hebei Province were distributed in clusters during different historical periods, and eventually formed three core clusters in Shijiazhuang, Zhangjiakou and Xingtai-Handan after different historical periods. Moreover, the overall distribution of traditional villages in Hebei Province is very uneven, with clear regional differences, and most of them are concentrated in the eastern foothills of the Taihang Mountains. To identify the factors influencing traditional villages, natural environmental factors, socio-economic factors, and historical and cultural factors are considered. The study finds that socio-economic and natural environmental factors alternate in the spatial distribution of traditional villages in Hebei Province. The influence of the interaction of these factors increases significantly, and socio-economic factors have a stronger influence on the spatial distribution. Specifically, the spatial distribution of traditional villages in Hebei Province is influenced by natural environmental factors, while socio-economic factors act as drivers of spatial distribution. Historical and cultural factors act as catalysts of spatial distribution, and policy directions are external forces of spatial distribution. Overall, this study provides valuable insights into the spatial distribution characteristics and influencing factors of traditional villages in Hebei Province, which can be used to develop effective strategies for rural revitalisation in China.

The Influence of Density and Mixed Land Use on The Spread of Covid-19 in Surakarta City

Covid-19 has a significant risk of spreading in urban areas because of the aglomeration of built-up areas and people. It frequently contains a mix of land uses and is accessible to urban amenities. Due to the area's extensive usage of mixed land uses, it is better able to provide internal urban services on its own. Greater use of area lockdown and social separation strategies could result from this situation. The most populous city in the province of Central Java, Surakarta, has a significant risk of contracting COVID-19. The purpose of this study is to evaluate the impact of density and levels of mixed land use on the Covid-19 distribution in Surakarta City.Population density is used to calculate density. The entropy index approach was used to measure the amount of mixed land use. It is a method for calculating the balance between each form of land use. The availability of current land use data being processed by the spatial analysis with the Arc GIS application provided help for the analysis. Additionally, it makes use of information on Covid-19 cases in relation to the general populace that is supplied by the Surakarta Municipality. The relationship between mixed land use and Covid-19 risk was analyzed using a linear regression approach. The study's findings indicated a minor influence between density and the spread of COVID-19. Meanwhile, the level of mixed land use does not influence the spread of the Covid-19 virus in Surakarta City.

Spatio-Temporal Evolution and Driving Factors of "Non-Grain Production” in Hubei Province Based on a Non-Grain Index

Non-grain production (NGP) on cultivated land has become a common phenomenon due to the prosperity of the rural economy and the optimisation of the agricultural structure. However, the excessive use of cultivating land for NGP has threatened food production and the sustainable use of cultivated land. To halt this trend and to ensure food security, the authors of this paper applied a novel non-grain index to measure NGP, which could reflect multiple NGP activities;designated Hubei Province as its object of research;and revealed NGP's spatio-temporal patterns of the past 30 years. We then assessed the characteristics of NGP based on spatial autocorrelation analysis, the Theil index, and geographically weighted regression. The results showed that the value of the non-grain index grew from 0.497 to 1.113 as NGP increased significantly in Hubei Province. The number of high-NGP counties increased, spatial agglomeration became obvious, and the eastern and western sides of Hubei Province witnessed an observable growth in NGP. As a result, the NGP in the eastern and western regions overtook production in the central region. Despite a series of historical subsidy policies and agricultural modernisation initiatives that promoted the planting of grain crops, the policy of "grain on valuable cultivated land” could be better implemented. We conclude by making some suggestions for reducing NGP and protecting cultivated land.

Spatial Analysis of Haikou Third-level First-class Hospitals Based on Geographic Information System

Nowadays, spatial geographic data analysis and GIS related software are more and more applied to the planning of urban public facilities. Under the COVID-19, people pay more attention to the protection of medical facilities for people's health, and a reasonable distribution of hospital facilities is conducive to people's health. Taking Haikou City as an example, this research will optimize the location of hospital space layout according to the existing third-level first-class general hospitals in Haikou City by using GIS software, road analysis, spatial analysis, and other methods. The results show that the existing hospitals in Haikou are too concentrated in the central urban area, the overall distribution of medical facilities is lack of balance, and there is a serious lack of medical facilities in new urban development areas and suburbs. According to the comparison between population density analysis and traffic analysis and the service scope of existing hospitals, the author finds out the scope of hospitals that need to be supplemented, and then calculates the scope of service area after taking several random points within the scope, and finally finds the one with the largest service scope is the optimal location. The results obtained by optimizing the site selection can provide a scientific reference for the rational layout of medical facilities in Haikou City in the future. © 2023 SPIE.

Dominant Modes of Agricultural Production Helped Structure Initial COVID-19 Spread in the US Midwest

The spread of COVID-19 is geographically uneven in agricultural regions. Explanations proposed include differences in occupational risks, access to healthcare, racial inequalities, and approaches to public health. Here, we additionally explore the impacts of coexisting modes of agricultural production across counties from twelve midwestern U.S. states. In modeling COVID-19 spread before vaccine authorization, we employed and extended spatial statistical methods that make different assumptions about the natures and scales of underlying sociospatial processes. In the process, we also develop a novel approach to visualizing the results of geographically weighted regressions that allows us to identify distinctive regional regimes of epidemiological processes. Our approaches allowed for models using spatial weights (e.g., inverse-squared distances) to be meaningfully improved by also integrating process-specific relations (e.g., the geographical relations of the food system or of commuting). We thus contribute in several ways to methods in health geography and epidemiology for identifying contextually sensitive public engagements in socio-eco-epidemiological issues. Our results further show that agricultural modes of production are associated with the spread of COVID-19, with counties more engaged in modes of regenerative agricultural production having lower COVID-19 rates than those dominated by modes of conventional agricultural production, even when accounting for other factors.

Geographic Information Systems for Facilitating Audits of the Urban Built Environment

Data collection and large-scale urban audits are challenging and can be time consuming processes. Geographic information systems can extract and combine relevant data that can be used as input to calculation tools that provide results and quantify indicators with sufficient spatial analysis to facilitate the local decision-making process for building renovations and sustainability assessment. This work presents an open-access tool that offers an automated process that can be used to audit an urban area in order to extract relevant information about the characteristics of the built environment, analyze the building characteristics to evaluate energy performance, assess the potential for the installation of photovoltaics on available building rooftops, and quantify ground permeability. A case study is also presented to demonstrate data collection and processing for an urban city block, and the relevant results are elaborated upon. The method is easily replicable and is based on open data and non-commercial tools.

Esoteric Beliefs and Opposition to Corona Restrictions in Germany.

Governmental measures against the spread of the Corona virus have been met with varying levels of opposition in many countries worldwide. Existing research has claimed that some of this opposition is linked to esoteric and anthroposophical beliefs. This research note tests this in an observational study using election results from the 2021 parliamentary election in Germany and new data on the distribution of natural healers, homeopathic doctors and Steiner schools. Results show that counter to common expectations, there is no evidence that esoteric beliefs systematically lead to increased support for the established right-wing AFD. Rather, some indicators for esoteric beliefs - in particular, the presence of homeopathic doctors and Waldorf schools - are related to higher support for the new fringe party dieBasis, a single-issue party campaigning against governmental Corona measures.

Distinct Red Blotch Disease Epidemiological Dynamics in Two Nearby Vineyards.

Grapevine red blotch virus (GRBV) causes red blotch disease and is transmitted by the three-cornered alfalfa hopper, Spissistilus festinus. GRBV isolates belong to a minor phylogenetic clade 1 and a predominant clade 2. Spatiotemporal disease dynamics were monitored in a 1-hectare 'Merlot' vineyard planted in California in 2015. Annual surveys first revealed disease onset in 2018 and a 1.6% disease incidence in 2022. Ordinary runs and phylogenetic analyses documented significant aggregation of vines infected with GRBV clade 1 isolates in one corner of the vineyard (Z = -4.99), despite being surrounded by clade 2 isolates. This aggregation of vines harboring isolates from a non-prevalent clade is likely due to infected rootstock material at planting. GRBV clade 1 isolates were predominant in 2018-2019 but displaced by clade 2 isolates in 2021-2022, suggesting an influx of the latter isolates from outside sources. This study is the first report of red blotch disease progress immediately after vineyard establishment. A nearby 1.5-hectare 'Cabernet Sauvignon' vineyard planted in 2008 with clone 4 (CS4) and 169 (CS169) vines was also surveyed. Most CS4 vines that exhibited disease symptoms one-year post-planting, likely due to infected scion material, were aggregated (Z = -1.73). GRBV isolates of both clades were found in the CS4 vines. Disease incidence was only 1.4% in non-infected CS169 vines in 2022 with sporadic infections of isolates from both clades occurring via secondary spread. Through disentangling GRBV infections due to the planting material and S. festinus-mediated transmission, this study illustrated how the primary virus source influences epidemiological dynamics of red blotch disease.

A global spatial analysis of factors associated with case and mortality rates for coronavirus disease 2019 during the first year of the pandemic.

BACKGROUND: A increasing number of studies have revealed associations between country-level determinants and coronavirus disease 2019 (COVID-19) outcomes. This ecological study was conducted to analyze country-level parameters related to COVID-19 infections and deaths during the first year of the pandemic. METHODS: The examined predictors comprised demographics, economic factors, disease prevalence and healthcare system status, and the relevant data were obtained from public databases. The index dates were set to 15 July 2020 (Time 1) and 15 December 2020 (Time 2). The adjusted spatial autoregression models used a first-order queen contiguity spatial weight for the main analysis and a second-order queen contiguity spatial weight for a sensitivity analysis to examine the predictors associated with COVID-19 case and mortality rates. RESULTS: Obesity was significantly and positively associated with COVID-19 case and mortality rates in both the main and sensitivity analyses. The sensitivity analysis revealed that a country's gross domestic product, population density, life expectancy and proportion of the population older than 65 y are positively associated with COVID-19 case and mortality rates. CONCLUSIONS: With the increasing global prevalence of obesity, the relationship between obesity and COVID-19 disease at the country level must be clarified and continually monitored.

Using the social vulnerability index to assess COVID-19 vaccine uptake in Louisiana.

Using data from the Louisiana Department of Public Health, we explored the spatial relationships between the Social Vulnerability Index (SVI) and COVID-19-related vaccination and mortality rates. Publicly available COVID-19 vaccination and mortality data accrued from December 2020 to October 2021 was downloaded from the Louisiana Department of Health website and merged with the SVI data; geospatial analysis was then performed to identify the spatial association between the SVI and vaccine uptake and mortality rate. Bivariate Moran's I analysis revealed significant clustering of high SVI ranking with low COVID-19 vaccination rates (1.00, p < 0.001) and high smoothed mortality rates (0.61, p < 0.001). Regression revealed that for each 10% increase in SVI ranking, COVID-19 vaccination rates decreased by 3.02-fold (95% CI = 3.73-2.30), and mortality rates increased by a factor of 1.19 (95% CI = 0.99-1.43). SVI values are spatially linked and significantly associated with Louisiana's COVID-19-related vaccination and mortality rates. We also found that vaccination uptake was higher in whites than in blacks. These findings can help identify regions with low vaccination rates and high mortality, enabling the necessary steps to increase vaccination rates in disadvantaged neighborhoods.

Unambiguous Linkage Between the Vaccination Coverage and the Spread of COVID-19: Geostatistical Evidence from the Slovak LAU 1 Regions

This case study refutes some controversial findings about a minor connection between the vaccination coverage and the spread of COVID-19. We try to eliminate some methodological shortcomings and risks, which are included in such previously published studies. Firstly, our selection comprises all regional units in one country. Secondly, the quality of data is basically identical in all examined regions within the country. Thirdly, all Slovak regions had an equal starting position. They were at the same stages of the COVID-19 wave, and the measures taken were analogous in all regions. Slovakia with a significantly different vaccination rates among regions is a very suitable study case. We used the empirical data at the level of its LAU 1 regions for the two latest COVID-19 waves at that time (Delta, Omicron). The methods of regression analysis and geostatistical methods were applied in the study. Indubitably, there is an obvious link between the vaccination coverage and the spread of COVID-19. We have shown that the incidence-trajectories among regions vary based on the vaccination rates. The positivity and incidence in the most vaccinated regional populations were significantly lower than in the least vaccinated regions in a whole analyzed period. Their values in the best vaccinated regions were lower by roughly 20-25 % during the delta and omicron wave-peaks. Using the spatial autocorrelation, we also managed to clearly identify a close relationship between vaccination on the one hand and standardized incidence and positivity on the other hand, although some regions deviated from this general finding.

Urban restaurants and online food delivery during the COVID-19 pandemic: a spatial and socio-demographic analysis

In this research, we analyzed the delivery service areas of restaurants, customer satisfaction, and restaurant sales of urban restaurants during the COVID-19 pandemic. We obtained the datasets on food ordering options and restaurant rankings based on Google Maps, Open Street Map, and widely known online food order applications in Iran. Based on this analysis we further modeled suitable areas for future extension of restaurants. We analyzed the online food order data of restaurants' sales and food delivery reports for 1050 restaurants in the city of Tabriz. We collected and analyzed data on the restaurant locations, the number of food orders for each restaurant, and the number of customers and their locations. Our results revealed that the spatial dimension of the newly emerging food delivery areas is of utmost importance for the success of restaurants. This indicates that an optimal location is not longer only dependent on factors like population density and competitors in the direct vicinity but on the services density even from more distant competitors. The results indicate that an optimized spatial distribution of the restaurants together with efficient quality in services can contribute to optimistic urban development. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

The Way from the Leading Position to the Last: Geo-demographic Analysis of the COVID-19 Pandemic in Czechia

This chapter is devoted to the spread of the SARS-CoV-2 virus in time and space in Czechia and in a brief context of its neighboring countries. It is (except for the theoretical background and data description) thematically divided into three parts and uses different approaches in the analysis. The first part descriptively outlines the trajectories of the virus in the Czech population. The second part, based on the demographic approach, examines the potential impact of COVID-19 on mortality. The third part presents a time-space analysis of the spread of COVID-19 at the regional level. Among the fundamental risk factors for Czechia, there is the inexperience of the Czech health and hygiene systems in dealing with more serious infectious epidemics in the past, the absence of a scientific and independent public health institution, and non-conceptual political decisions in the management of pandemics. In the analysis, the interdisciplinary scientific approach is used (medical geography, demography, and spatial analysis) to analyze such a complex phenomenon. It was shown that during the first year of pandemics (March 2020-March 2021) there were four pandemic waves in Czechia. Except for the preventive and anti-pandemic measures, the effect on the mortality level and socioeconomic status in particular regions could be expected. The estimated effect of COVID-19 on the life expectancy at birth was estimated around a 1 year decrease, the same as in other Central European countries. This impact is expected to be much lower in the case of Germany. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

Global modeling of the socioeconomic, political, and environmental relations of farmer seed systems (FSS): Spatial analysis and insights for sustainable development

Accessible, high-quality seed is vital to the agricultural, food, and nutrition sovereignty needed for justice-based sustainable development. Multiregion, interdisciplinary research on farmers' seed systems (FSS) can complement case-based and thematic approaches.This study's goals are to (1) provide a synthetic overview of current major FSS concepts;(2) design and evaluate a novel social- and political-ecological model of FSS using globally representative data from mountain agricultural areas of Africa, Asia, and Latin America;(3) model and evaluate FSS relations to socioeconomic, political, and environmental factors including main food crops (rice, wheat, maize, potato, and common bean);(4) generate new spatial, geographic, and demographic estimates;and (5) strengthen FSS for justice-based sustainable development of agriculture, land use, and food systems. The conceptual framework of FSS-related factors guided the global modeling of data from 11 countries in Africa, Asia, and Latin America. A multiple regression model explained FSS utilization (R2 1/4 0.53, P < 0.0001), specifying the significant inverse relations to mean farm area (strong), per-capita Gross Domestic Product at the district level (strong), and urban distance (moderate). FSS showed strong positive relations to aridity and topographic ruggedness. FSS were positively related to elevation in a 5-country Andean subsample. Results estimated FSS utilization by 136 million farmers within the 11 countries. Novel insights to strengthen FSS policies and programs are the importance of FSS to extremely small farm-area subgroups and other distinct FSS stakeholders, global-region geopolitical distinctness of FSS-farm area relations, multidistrict FSS concentrations that enable extralocal FSS spatial connectivity, FSS capacities in climate-change hot spots, and high FSS encompassing periurban areas. Policy-relevant results on global geographic and demographic extensiveness of FSS and key spatial, socioeconomic, political, and environment relations demonstrate that globally FSS are key to supporting agrobiodiversity, agroecology, nutrition, and the sustainability of food systems. These advise strengthening FSS through pro-poor and linked urban-rural policies at regional scales in addition to expanding local initiatives.

Mapping Life Expectancy Loss in Barcelona in 2020

We use a Bayesian spatio-temporal model, first to smooth small-area initial life expectancy estimates in Barcelona for 2020, and second to predict what small-area life expectancy would have been in 2020 in absence of covid-19 using mortality data from 2007 to 2019. This allows us to estimate and map the small-area life expectancy loss, which can be used to assess how the impact of covid-19 varies spatially, and to explore whether that loss relates to underlying factors, such as population density, educational level, or proportion of older individuals living alone. We find that the small-area life expectancy loss for men and for women have similar distributions, and are spatially uncorrelated but positively correlated with population density and among themselves. On average, we estimate that the life expectancy loss in Barcelona in 2020 was of 2.01 years for men, falling back to 2011 levels, and of 2.11 years for women, falling back to 2006 levels.

An Investigation of the Impact and Resilience of British High Streets Following the COVID-19 Lockdown Restrictions.

British high streets have faced significant economic and cultural challenges as a consequence of the COVID-19 pandemic. This is predominantly due to government enforced restrictions which required all 'non-essential' retail to close, resulting in a significant change in the way consumers interacted with high streets. While all premises related to the retail or hospitality sector were forced to close, leading to rising vacancy rates, some high streets were more resilient to the economic shock than others. In this paper we detect some of the unforeseen consequences of the pandemic on British high streets and create a measure of resilience. The impact of the lockdown restrictions have resulted in some high streets, notably Spring Street in Paddington, London, experiencing disproportionate decline. Others including Northolt Road in Harrow, London were able maintain their occupancy. This study provides a typology of high street resilience incorporating the impact of the COVID-19 lockdown restrictions and links the impact of government policy to the economic performance of high streets. The outcomes from this research address both local and national policy contexts as the resilience typology has the potential to assist in funding allocation for recovery and regeneration projects.

Public transport access to drug treatment before and during COVID-19: Implications for the opioid epidemic.

Public transport disruptions caused by the COVID-19 pandemic had wide-ranging impacts on the ability of individuals to access health care. Individuals with opioid use disorder represent an especially vulnerable population due to the necessity of frequent, supervised doses of opioid agonists. Focused on Toronto, a major Canadian city suffering from the opioid epidemic, this analysis uses novel realistic routing methodologies to quantify how travel times to individuals\220 nearest clinics changed due to public transport disruptions from 2019 to 2020. Individuals seeking opioid agonist treatment face very constrained windows of access due to the need to manage work and other essential activities. We find that thousands of households in the most materially and socially deprived neighbourhoods crossed 30 and 20-minute travel time thresholds to their nearest clinic. As even small changes to travel times can lead to missed appointments and heighten the chances of overdose and death, understanding the distribution of those most impacted can help inform future policy measures to ensure adequate access to care.

Quantitative Identification Study of Epidemic Risk in the Spatial Environment of Harbin City

Global pandemics pose a threat to the sustainable development of urban health. As urban spaces are important places for people to interact, overcrowding in these spaces can increase the risk of disease transmission, which is detrimental to the sustainable development of urban health. Therefore, it is crucial to identify potential epidemic risk areas and assess their risk levels for future epidemic prevention and the sustainable development of urban health. This article takes the main urban area of Harbin as the research object and conducts a cluster spatial analysis from multiple perspectives, including building density, functional density, functional mix, proximity, intermediacy, and thermal intensity, proposing a comprehensive identification method. The study found that (1) functional density is the most significant influencing factor in the formation of epidemic risks. Among various urban functions, commercial and public service functions have the strongest impact on the generation and spread of epidemic risks, and their distribution also has the widest impact range. (2) The spaces with higher levels of epidemic risk in Harbin are mainly distributed in the core urban areas, while the peripheral areas have relatively lower levels of risk, showing a decreasing trend from the center to the periphery. At the same time, the hierarchical distribution of urban space also has an impact on the spatial distribution of the epidemic. (3) The method proposed in this study played an important role in identifying the spatial aggregation of epidemic risks in Harbin and successfully identified the risk levels of epidemic distribution in the city. In spatial terms, it is consistent with high-risk locations of epidemic outbreaks, which proves the effectiveness and feasibility of the proposed method. These research findings are beneficial for measures to promote sustainable urban development, improve the city's epidemic prevention capabilities and public health levels, and make greater contributions to the sustainable development of global public health, promoting global health endeavors.