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The unbalanced allocation of healthcare resources is a major challenge that hinders access to healthcare. Taking Shenzhen as an example, this study aimed to enhance equity in obtaining healthcare services, through measuring and visualizing the spatial accessibility of community healthcare centers (CHC), and optimizing CHC geospatial allocation. We used the number of health technicians per 10,000 to represent the CHC's service capacity, combined with resident points and census data to calculate the population the CHC needs to carry, and then analyzed the accessibility based on the Gaussian two‐step floating catchment area method. In 2020, five regions in Shenzhen had better spatial accessibility scores: Nanshan (0.250), Luohu (0.246), Futian (0.244), Dapeng (0.226), and Yantian (0.196). The spatial accessibility of CHCs shows a gradual decrease from the city center to the edge, which is affected by economic and topographic factors. With the support of the maximal covering location problem model, we selected up to 567 candidate locations for the new CHC, which could improve Shenzhen's accessibility score from 0.189 to 0.361 and increase the coverage population by 63.46% within a 15‐min impedance. By introducing spatial techniques and maps, this study provides (a) new evidence for promoting equitable access to primary healthcare services in Shenzhen and (b) a foundation for improving the accessibility of public service facilities in other areas. Plain Language Summary This study aimed to enhance equity in obtaining primary healthcare services for residents. Taking Shenzhen, China as an example, measuring and visualizing the spatial accessibility of community healthcare centers, and optimizing its geospatial allocation to reduce the barriers for residents to healthcare institutions. Key Points The problem of unbalanced allocation of primary healthcare resources is gradually emerging Shenzhen residents have unequal access to primary healthcare within 15‐min Economic and topographic factors affect the inequity of access to primary healthcare in Shenzhen

The behavior of complex networks under failure or attack depends strongly on the specific scenario. Of special interest are scale-free networks, which are usually seen as robust under random failure but appear to be especially vulnerable to targeted attacks. In recent studies of public transport networks of fourteen major cities of the world it was shown that these systems when represented by appropriate graphs may exhibit scale-free behavior [Physica A 380, 585 (2007); Eur. Phys. J. B 68, 261 (2009)]. Our present analysis focuses on the effects that defunct or removed nodes have on the properties of public transport networks. Simulating different directed attack strategies, we derive vulnerability criteria that result in minimal strategies with high impact on these systems.

The Multi‐Threat Medical Countermeasure (MTMC) technique is crucial for developing common biochemical signaling pathways, molecular mediators, and cellular processes. This study revealed that the Nod‐like receptor 3 (NLRP3) inflammasome pathway may be a significant contributor to the cytotoxicity induced by various organophosphorus pesticides (OPPs). The study demonstrated that exposure to six different types of OPPs (paraoxon, dichlorvos, fenthion, dipterex, dibrom, and dimethoate) led to significant cytotoxicity in BV2 cells, which was accompanied by increased expression of NLRP3 inflammasome complexes (NLRP3, ASC, Caspase‐1) and downstream inflammatory cytokines (IL‐1β, IL‐18), in which the order of cytotoxicity was dichlorvos > dipterex > dibrom > paraoxon > fenthion > dimethoate, based on the IC50 values of 274, 410, 551, 585, 2,158, and 1,527,566 μM, respectively. The findings suggest that targeting the NLRP3 inflammasome pathway could be a potential approach for developing broad‐spectrum antitoxic drugs to combat multi‐OPPs‐induced toxicity. Moreover, inhibition of NLRP3 efficiently protected the cells against cytotoxicity induced by these six OPPs, and the expression of NLRP3, ASC, Caspase‐1, IL‐1β, and IL‐18 decreased accordingly. The order of NLRP3 affinity for OPPs was dimethoate > paraoxon > dichlorvos > dibrom > (fenthion and dipterex) based on KD values of 89.8, 325, 1,460, and 2,690 μM, respectively. Furthermore, the common molecular mechanism of NLRP3‐OPPs was clarified by the presence of toxicity effector groups (benzene ring, nitrogen/oxygen‐containing functional group); =O, ‐O‐, or =S (active) groups; and combination residues (Gly271, Asp272). This finding provided valuable insights into exploring the common mechanisms of multiple threats and developing effective therapeutic strategies to prevent OPPs poisoning. Plain Language Summary This study aimed to explore the role of Nod‐like receptor 3 (NLRP3) inflammasome activation in organophosphorus pesticide (OPPs)‐induced cytotoxicity. Six different OPPs, including dimethoate, paraoxon, dichlorvos, dibrom, fenthion, and dipterex, were introduced to BV2 cells and caused significant cytotoxicity along with increased expression of NLRP3 inflammasome complexes and downstream cytokines. Inversely, inhibition of NLRP3 protected against these OPPs. We believe that our study makes a significant contribution to the literature because it suggests that the NLRP3 inflammasome pathway may be a common mechanism of multi‐OPPs‐induced cytotoxicity. By introducing a therapeutic target for OPPs poisoning prevention, broad‐spectrum antitoxic drugs may be designed to effectively protect against OPPs‐induced cytotoxicity. Key Points The NLRP3 inflammasome potentially contributes to cytotoxicity induced by six types of OPPs Inhibition of the NLRP3 pathway effectively prevented cytotoxicity caused by six OPPs The study proposed targets for broad‐spectrum antitoxic drugs to prevent OPPs‐poisoning

West Nile virus (WNV) is a zoonotic virus with a mosquito‐avian transmission cycle having occasional spillover to mammals. A network analysis of annual log‐transformed WNV case numbers (2003–2022) generated four spatially and temporally coherent clusters among 48 U.S. states and six Canadian provinces. Cluster 1 and Cluster 3 were the largest groups corresponding to the Central Flyway and the closely associated Eastern Flyway (with an east‐coast subset). Cluster 2 and Cluster 4 corresponded with less‐well defined segments of a distinctly different Western Flyway. Thus, clustering can be explained by migratory pathways of terrestrial birds. We investigated avian involvement in the spread of WNV from potential sources in the southern U.S. Analyses revealed consistent patterns in log‐transformed case numbers of human WNV. This study highlights the significant role of migratory birds in shaping the spatiotemporal patterns of WNV incidence across North America. However, the observed variability in incidence also likely reflects the interplay of other factors including local environmental conditions, mosquito populations, and regional variations in both migratory and non‐migratory bird populations. Plain Language Summary West Nile virus (WNV) is a disease that spreads between mosquitoes and birds, sometimes affecting humans. Previous studies focused on human WNV case numbers from Texas to the Dakotas and suggested that migratory birds might help spread the virus. Our analysis; however, points to the role of terrestrial birds. By examining the patterns of human WNV cases over time, we found evidence that the virus may spread from southern states like Texas, Louisiana, and Mississippi to northern areas. Large populations of blackbirds, which migrate in these regions, may contribute to the spread of WNV. Additionally, the presence of these birds in areas with high numbers of mosquitoes in wetlands creates conditions that favor the spread of the virus. As a result, Nebraska, the Dakotas, and Southern Saskatchewan often experience higher numbers of human WNV cases per population than other regions. Key Points Large annual incidences of human cases of West Nile virus (WNV) are associated with the Northern Great Plains of North America Statistical analyses implicate the spreading of WNV by terrestrial birds, such as blackbirds that migrate to southern states in fall The large WNV incidences represent a “perfect storm” in terms of large numbers of terrestrial birds and the most competent mosquito vector

Cardiovascular diseases (CVDs) remain a leading cause of mortality globally, with environmental risk factors playing a significant role in their prevalence. This review aims to critically evaluate the current methodologies employed in spatiotemporal analyses of CVDs and provides recommendations to enhance the accuracy and practical application of these models. A systematic search of the literature was conducted using Scopus, PubMed, and Embase databases. Studies were selected based on their use of spatiotemporal models to assess the relationship between environmental factors and CVDs. We evaluated the methodological quality of included studies using the Spatial Methodology Appraisal of Research Tool (SMART). Significant challenges were noted, including the need for higher spatial resolution data sets and improved methods for addressing the modifiable areal and temporal unit problems and ecological bias. Additionally, the visualization of spatiotemporal data remains underutilized and underdeveloped, limiting the practical utility of the findings. We also discuss combining parameters to form an indicator that better represents environmental conditions, as well as cases where ground, satellite, or modeled data products are suitable. These recommendations could extend to other acquired chronic diseases and their relationship with environmental risk factors to improve the utility of spatiotemporal models. While spatiotemporal modeling holds considerable promise in understanding and mitigating CVD risks associated with environmental factors, appropriate data selection, addressing methodological pitfalls and reporting spatial and temporal model outcomes are necessary to enhance their reliability and impact. Plain Language Summary Cardiovascular diseases (CVDs), like heart attacks and strokes, are major causes of death worldwide, with environmental factors such as air pollution and temperature linked to their occurrence. The occurrence of CVDs and environmental factors are closely linked to the geographical location, as well as changes over time. This review looks at how researchers are using models that track changes over space and time to study these links. Our review highlights key challenges in these models, such as the need for more precise data on where people live and better methods to account for the way different time periods and regions are grouped. We also found that tools for visualizing this data are often underdeveloped, making it harder for researchers and policymakers to apply the findings in real‐world settings. We provide recommendations on choosing the best data sources to reflect environmental conditions accurately and combining several factors into one indicator to better represent environmental risks. These recommendations could improve the way we model and understand how CVDs and environmental factors are connected, benefiting research into other chronic diseases as well. By enhancing the data and methods used in these models, we can better understand and ultimately reduce CVD risks related to environmental factors. Key Points Spatiotemporal models provide a robust understanding of the relationship between health effects and environmental risk factors Current applications require improvements in spatial and temporal resolution of data sets to reduce generalization of exposure levels Advanced visualization tools are needed to interpret spatiotemporal data for improving their utility in a public health setting

Childhood lead poisoning is an issue that continues to plague major U.S. cities. Despite efforts by the Philadelphia Department of Public Health to curtail systemic childhood lead poisoning, children continue to be identified with elevated blood lead levels. The persistence of elevated blood lead levels in children is concerning because lead poisoning has been linked to decreases in academic achievement and IQ, with associated repercussions for entire communities. This paper reports the results of an analysis of the spatial distribution of houses with lead paint (i.e., pre‐1978), demolitions, and occurrence of historic smelters, in West and North Philadelphia, relative to elevated blood lead level data, to determine which lead sources act as primary lead‐risk factors. The presence of lead paint in homes and the number of demolitions of older properties were found to have the highest correlations to elevated blood lead levels for children in Philadelphia. Using lead‐risk factors including lead paint, housing code violations, demolitions, and owner‐occupied housing units, a lead‐risk assessment was performed at the census tract level to identify future soil sampling sites and high‐risk neighborhoods in Philadelphia. These sites of high risk for lead exposure, and in particular the census tracts 175 and 172, should be prioritized for lead poisoning prevention initiatives. Plain Language Summary Childhood lead poisoning is an issue that continues to plague major U.S. cities. Despite efforts by the Philadelphia Department of Public Health to reduce the number of lead‐poisoned children, new cases are identified every month. Childhood lead poisoning is concerning because it has been linked to decreases in academic achievement and IQ, with impacts at the larger scale for entire communities. This research investigates where lead paint, demolitions, and lead smelters exist in West and North Philadelphia, in order to identify which sources of lead are the primary culprits for childhood lead poisoning. The presence of lead paint in homes and the number of building demolitions were found to be most consistently linked to lead‐poisoned children in these parts of Philadelphia. Using lead sources, and factors that are linked to lead‐hazard production, such as lead paint, housing code violations, demolitions, and owner‐occupied units, a lead‐risk assessment was performed at the census tract level to identify both future soil‐sampling sites and neighborhoods at high risk for childhood lead poisoning. These sites of high risk for lead pollution should be prioritized for lead poisoning prevention initiatives. Key Points In areas with high homeownership, owner‐occupied units can serve as lead‐risk indicators for childhood lead poisoning Demolitions and lead paint of older housing are critical lead‐source emissions for childhood lead poisoning in Philadelphia North Philadelphia soils, and especially open‐land around historic smelters, are highly undersampled

In March 2020, the first known cases of COVID‐19 occurred in Europe. Subsequently, the pandemic developed a seasonal pattern. The incidence of COVID‐19 comprises spatial heterogeneity and seasonal variations, with lower and/or shorter peaks resulting in lower total incidence and higher and/or longer peaks resulting higher total incidence. The reason behind this phenomena is still unclear. Unraveling factors that explain why certain places have higher versus lower total COVID‐19 incidence can help health decision makers understand and plan for future waves of the pandemic. We test whether differences in the total incidence of COVID‐19 within five European countries (Norway, Sweden, Germany, Italy, and Spain), correlate with two environmental factors: the Köppen‐Geiger climate zones and the Continentality Index, while statistically controlling for crowding. Our results show that during the first 16 months of the pandemic (March 2020 to July 2021), climate zones with larger annual differences in temperature and annually distributed precipitation show a higher total incidence than climate zones with smaller differences in temperature and dry seasons. This coincides with lower continentality values. Total incidence increases with continentality, up to a Continentality Index value of 19, where a peak is reached in the semicontinental zone. Low continentality (high oceanic influence) appears to be a strong suppressing factor for COVID‐19 spread. The incidence in our study area is lowest at open low continentality west coast areas. Plain Language Summary In March 2020, the first known cases of COVID‐19 occurred in Europe. Over the next 16 months (March 2020 to July 2021) a pattern emerged where some areas had higher versus lower COVID‐19 spread. We studied whether this pattern could be explained by climatological factors in five European countries (Norway, Sweden, Germany, Italy, and Spain). Our results show that areas with larger annual temperature ranges and year‐round rain had higher COVID‐19 spread than areas with smaller annual temperature ranges and dry seasons. We also examined continentality, which measures the influence of the ocean on climate. In Europe, where predominant winds come from the west, we find the highest oceanic influence at open west coasts; in our study area these are represented by north‐west Spain, northernmost Germany, and south‐west Norway. In these areas, COVID‐19 spread was lowest. With decreasing oceanic influence, COVID‐19 spread was higher. For the five countries we studied, we found highest COVID‐19 spread in south‐east Norway, the entire south of Sweden, the south‐eastern part of Germany, northern Italy, and central Spain. Healthcare decision makers in areas that have wide ranges of temperature and rain throughout the year or that have little oceanic influence should expect a higher COVID‐19 spread. Key Points We study the reason for within country differences of the COVID‐19 pandemic for Norway, Sweden, Germany, Italy, and Spain COVID‐19 incidence is lower in climate zones with smaller annual temperature ranges and a clear division between wet and dry seasons Incidence patterns can be explained by continentality; oceanic impact limits COVID‐19 at open west coasts in the European west wind zone

Motivated by growing amounts of data and enhanced resolution from orbiters and rovers, systems for computer‐aided decision support are becoming invaluable in planetary exploration. This article illustrates the value of such systems for a case study on the exploration of the Martian geology, along with improvements in assessing the favorability for landing. Under the current technical status quo for landing and rover's mobility, results show that Eastern Margaritifer Terra and Meridiani Planum stand out due to their high density of scientific targets and flat surfaces. However, our approach allows us to scale the analysis using different scenarios for the entire planet, quantifying the substantial benefits should higher landing elevations and higher rover speeds be realized in the future. This analysis offers new insights into the interplay of technical and scientific constraints. Key Points We introduce a new system helping decision making for planetary exploration We present an in‐depth case study for Mars, providing new insights to aid future geological studies and landing site selections We quantify the impact of higher landing elevations and higher rover speeds on our ability to explore Mars

Don't simply show your data--tell a story with it!Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data.You'll discover the power of storytelling and the way to make data a pivotal point in your story.

IntroductionData visualization is a powerful communication tool to facilitate the understanding of a complex process or data. Data visualization has been used in health technology assessment (HTA) reports for a long period (e.g., PRISMA flow diagrams, critical assessments, or GRADE). This study aims to investigate the number and manners in which HTA reports have been using descriptive data visualization for the years 2021 to 2023.MethodsThe international HTA database was used to identify and download the HTA reports from the years 2021 to 2023. We applied the database limits: full HTA and completed reports. The records were imported into a Microsoft Excel spreadsheet and screened by eight independent researchers applying the inclusion criteria: full HTA (according to methodological definition), access to the full text, and use of data visualization with a descriptive purpose (we excluded PRISMA flow diagrams, forest plots, and others). The data were observed with the software Power BI. Our analysis included variables such as agency name, country, section, type of visualization, and software.ResultsFrom the international HTA database, 1,128 records were exported: 89 records were directly excluded from this set as they were tagged as ongoing or other types of reports in the database; 1,039 records were screened. Around 30 percent of records were included for the data visualization screening criteria after fulfilling our inclusion criteria (full HTA and available full text). Finally, 12 percent of the reports included data visualizations for a descriptive purpose of their results or conclusions. The countries with a higher number of records included in this analysis were Germany (28%), Canada (18%), the UK (16%), and Spain (11%).ConclusionsIn our sample, we observed that data visualization is not widely used so far to describe outcomes and/or conclusions from HTA reports. An additional finding was the number of records tagged as full HTA in the international HTA database that were excluded as non-full HTA from our study.