Space-time Classification Index for Assessing COVID-19 Hotspots

Objectives: To develop new methods to address problems associated with use of traditional measures of disease surveillance, including prevalence and positivity rates. Methods: We use data from the public New York Times Github repository to develop a space-time classification index of COVID-19 hotspots. The Local Indicator of Spatial Association (LISA) statistic is applied to identify daily clusters of COVID-19 cases, from July 4th to July 19th. Results: The classification index is a spatial and temporal assessment tool that seeks to incorporate temporal trends of the clusters that are "high-high" and "high-low". Two classifications support the index: severity and temporal duration. We define severity as the number of times a county is statistically significant and temporal duration captures the number of consecutive days a county is a hotspot. Conclusions: The space-time classification index provides a statistically robust measure of the spatial patterns of COVID-19 hotspots. Spatial information is not captured through measures like the positivity rate, which merely divides the number of cases by tests conducted. The index proposed in this paper can guide intervention efforts by classifying counties with six-levels of importance.

Analisis Tipe Dan Bidang Gelincir Longsor Di Kabupaten Gorontalo Utara

The purpose of this study was to determine the type of landslides and analyze the landslide slip in North Gorontalo District, Gorontalo Province using the geoelectric method. This research begins by determining the type and kind of landslides found in the North Gorontalo District. The location of the measurement was carried out at 4 (four) locations, 1st Track in Tomilito District; 2nd track in Sumalata District; 3rd track in Monano District; and 4th track in East Sumalata District. The research method used was a field survey with a land unit approach. Data analysis to determine the type and kind of landslides is using the landslide classification index method. Analysis of geoelectric measurement results using the Schlumberger-Configuration. The results showed that the types of landslides that occurred in North Gorontalo Regency were the type of planar slide, rotational slide, slide flow, rock/topples. The average depth of the landslide slip that occurred was 5 – 15.9 meters. In general, landslides that occur in North Gorontalo Regency are caused by high rainfall and land conversion for agriculture.

Climate change in MATOPIBA region of Brazil using Thornthwaite (1948) classification

Identify the climatic characterization of a region and its spatial and temporal variation, as well as its changes in the face of climate change events, is essential for agrometeorological studies because they can assist in the planning of strategies that reduce the negative impacts generated in the cultures exposed to critical climatic conditions. Thus, this study aimed to characterize the climatic conditions of the MATOPIBA region and its changes in scenarios of climate change using the classification index of Thornthwaite (1948). Daily time series of rainfall and temperature data in the 1950–1990 period were used, arranged in a 0.25º × 0.25º grid, covering 467 points over the studied region. The data set was used to estimate climatological water balance and climate index Thornthwaite (1948), and obtain the trends climatological according to IPCC (2014) climate change projections, with changes in the average air temperature (+ 1.5°C and − 1.5°C) and precipitation (+ 30% and − 30%). The MATOPIBA region is characterized by its humid, dry subhumid, and Moist subhumid climate, with the rainy seasons, between October and April, and drought, from May to September, well defined. In MATOPIBA climate change scenarios, climatic extreme indices tend to alter the pattern, frequency, and distribution of climate class, which can increase climate risk and impact crop production. Therefore, the results obtained can be used to develop strategies to mitigate the vulnerability of crops to climate change conditions.

“Books, physical spaces, rules, people”: A holistic analysis of young Chinese children’s perceptions of public libraries

Young children’s perceptions of library services are often ignored when providing library services to this group. In order to reveal young children’s perceptions, grounded theory technique was used to analyze the interview data from 92 young Chinese children. The authors first proposed an integrated model of young children’s perceptions of Chinese public libraries, including the elements of books, physical spaces, rules, and people. Subsequently, the model is compared to the adult experts’ perspectives, revealing that young children could perceive all the experts’ proposed services and functions. Besides, they could perceive rules in libraries. Furthermore, young children were able to convert the abstract library classification index system to perceptible clues. The findings could be used to improve library services to accurately conform to young children’s perspectives.

Developing an Internally Validated Veterans Affairs Women Cardiovascular Disease Risk Score Using Veterans Affairs National Electronic Health Records

Background The current American College of Cardiology/American Heart Association women cardiovascular disease (CVD) risk score suboptimally estimates CVD risk for young and minority women in the military. The current study developed an internally validated CVD risk score for women military service members and veterans using the Veterans Affairs (VA) national electronic health records data. Methods and Results The study cohort included 69 574 White, Black, and Hispanic women service members and veterans aged 30 to 79 years in 2007 treated in the VA Health Care System between January 1, 2007 and December 31, 2017 (henceforth, VA women). Stratified by race and ethnicity, the new VA women CVD risk model estimated risk coefficients and 10‐year CVD risk using a time‐variant covariate Cox model. Harrell C‐statistics, calibration plots, and net classification index were used to assess accuracy and prognostic performance of the new VA women CVD risk model. The new internally validated VA women CVD risk score performed better in predicting VA women 10‐year atherosclerosis cardiovascular disease risk than the pooled cohort American College of Cardiology/American Heart Association risk score in both accuracy (White Harrell C‐statistics, 70% versus 61%; Black, 68% versus 63%) and prognostic performance (White net classification index, 0.31; 95% CI, 0.26–0.33; Black net classification index, 0.06; 95% CI, 0.03–0.09). Conclusions The proposed VA women CVD risk score improves accuracy of the existing American College of Cardiology/American Heart Association CVD risk assessment tool in predicting long‐term CVD risk for VA women, particularly in young and racial/ethnic minority women.

Classification of Sediment Quality according to Its Behavior in the Accelerated Particle Wear Test (APW)

One of the main problems faced in coastal management is the loss or destruction of beaches due to erosion. A considerable diversity of factors is involved in coastal erosion, which makes it a complex system to study. The quality of the material that constitutes the beach, as well as the choice of appropriate materials for its nourishment are two of the main ones. Therefore, to make future nourishment projects more sustainable and durable, this work proposes a sediment quality classification based on the physical properties and wear process obtained through laboratory tests. The study of these variables, using principal component analysis, discriminant analysis and ANOVA, has divided the quality of 70 samples into three main groups. A Sediment Quality Classification Index (SQCI) is proposed, which categorizes the quality of the material into poor, regular or good, providing the coastal engineer with a simple tool to ensure more sustainable beach nourishments.

Predictors of health-related quality of life in musculoskeletal disease patients: a longitudinal analysis

Introduction: Rheumatic and musculoskeletal diseases (RMDs) have a significant impact on patients’ health-related quality of life (HRQoL) exacerbating disability, reducing independence and work capacity, among others. Predictors’ identification affecting HRQoL could help to place efforts that minimize the deleterious impact of these conditions on patients’ wellbeing. This study evaluates the influence of demographic and clinical predictors on the HRQoL of a cohort of RMD patients, measured using the Rosser classification index (RCI). Methods: We included patients attending the Hospital Clínico San Carlos (HCSC) rheumatology outpatient clinic from 1 April 2007 to 30 November 2017. The primary outcome was the HRQoL assessed in each of the patient’s visits using the RCI. Demographic and clinical variables extracted from a departmental electronic health record (EHR) were used as predictors: RMD diagnoses, treatments, comorbidities, and averaged HRQoL values from previous periods (for this last variable, values were imputed if no information was available). Association between predictors and HRQoL was analyzed using penalized generalized estimating equations (PGEEs). To account for imputation bias, the PGEE model was repeated excluding averaged HRQoL predictors, and common predictors were considered. Discussion: A total of 18,187 outpatients with 95,960 visits were included. From 410 initial predictors, 19 were independently associated with patients’ HRQoL in both PGEE models. Chronic kidney disease (CKD), an episode of prescription of third level analgesics, monoarthritis, and fibromyalgia diagnoses were associated with worse HRQoL. Conversely, the prescription in the previous visit of acid-lowering medication, colchicine, and third level analgesics was associated with better HRQoL. Conclusion: We have identified several diagnoses, treatments, and comorbidities independently associated with HRQoL in a cohort of outpatients attending a rheumatology clinic.

Socio-еconomic transformation of Sumadija district (Serbia)

The paper starts from the hypothesis that the examined area is characterized by a process of intensive functional transformation accompanied by certain population changes. The transformation of the settlement structure is shown in the area of Sumadija district. The trend of demographic and economic development was observed with a historical overview. It was upgraded with quantitative analyzes (chain index, population change index, functional classification, index of specialization and localization) for the period 1971-2011. The aim was to determine the degree of socio-economic transformation of Sumadija district and the regularities according to which these changes took place. Industrialization generally brings changes in the functional orientation and redistribution of the population. The deagrarianization was one of the main features, with parallel emigration of the rural population. These changes were intensive in 1961-1981, when the peak of employment in secondary activities was registered. Since then, significant spatial transformation in Sumadija district was visible. Special analyzes were used to confirm the assumption that Kragujevac is a dominant labor center, an administrative and service nucleus, which has a propulsive influence on the development of its immediate surroundings (suburban belt) and the wider area (Sumadija district). The contribution of this paper is in the understanding of the scope, spatial distribution, and intensity of changes that have occurred in Sumadija district. It introduces the historical circumstances and quantitative research into a broader concept as a basis for understanding the trajectories of spatial and socio-economic development, and responds to many social challenges specific for this territory.