Suchergebnisse

Abstract Background Due to recent emergence, dengue is becoming one of the major public health problems in Nepal. The numbers of reported dengue cases in general and the area with reported dengue cases are both continuously increasing in recent years. However, spatiotemporal patterns and clusters of dengue have not been investigated yet. This study aims to fill this gap by analyzing spatiotemporal patterns based on monthly surveillance data aggregated at district. Methods Dengue cases from 2010 to 2014 at district level were collected from the Nepal government's health and mapping agencies respectively. GeoDa software was used to map crude incidence, excess hazard and spatially smoothed incidence. Cluster analysis was performed in SaTScan software to explore spatiotemporal clusters of dengue during the above-mentioned time period. Results Spatiotemporal distribution of dengue fever in Nepal from 2010 to 2014 was mapped at district level in terms of crude incidence, excess risk and spatially smoothed incidence. Results show that the distribution of dengue fever was not random but clustered in space and time. Chitwan district was identified as the most likely cluster and Jhapa district was the first secondary cluster in both spatial and spatiotemporal scan. July to September of 2010 was identified as a significant temporal cluster. Conclusion This study assessed and mapped for the first time the spatiotemporal pattern of dengue fever in Nepal. Two districts namely Chitwan and Jhapa were found highly affected by dengue fever. The current study also demonstrated the importance of geospatial approach in epidemiological research. The initial result on dengue patterns and risk of this study may assist institutions and policy makers to develop better preventive strategies.

Abstract. The persistence over space and time of flash flood disasters – flash floods that have caused either economical losses or loss of life or both – is a diagnostic measure of areas subjected to hydrological risk. The concept of persistence can be assessed via clustering analyses, performed here to analyze the national inventory of flash flood disasters in China that occurred in the period 1950–2015. Specifically, we investigated the spatiotemporal pattern distribution of the flash flood disasters and their clustering behavior by using both global and local methods: the first based on Ripley's K function, and the second on scan statistics.
As a result, we could visualize patterns of aggregated events, estimate the cluster duration and make assumptions about their evolution over time, also with respect to the precipitation trend. Due to the large spatial (the whole Chinese territory) and temporal (66 years) scale of the dataset, we were able to capture whether certain clusters gather in specific locations and times but also whether their magnitude tends to increase or decrease. Overall, the eastern regions in China are much more subjected to flash flood disasters compared to the rest of the country. Detected clusters revealed that these phenomena predominantly occur between July and October, a period coinciding with the wet season in China. The number of detected clusters increases with time, but the associated duration drastically decreases in the recent period. This may indicate a change towards triggering mechanisms which are typical of short-duration extreme rainfall events.
Finally, being flash flood disasters directly linked to precipitation and their extreme realization, we indirectly assessed whether the magnitude of the trigger itself has also varied through space and time, enabling considerations in the context of climatic change.

Middle Holocene hunter-gatherers (HG) of the Cis-Baikal, Eastern Siberia, display substantial spatiotemporal variation in adaptive strategies highlighted by several cultural transitions. These transitions are examined focusing on the role of the following factors: (1) changes in the distribution of the boreal forest; (2) technological innovations; (3) intensification of fishing; and (4) their combined impacts on subsistence and social structure. The expansion and retreat of boreal forest was important because it directly affected the distribution and abundance of large and medium terrestrial game, the core of subsistence for all Middle Holocene HG in the region. All other things being equal, expanding forests meant less game while shrinking forest meant more game and more living space for HG. The bow was crucial not only due to its technological superiority over the spear and atlatl as a game hunting weapon but also because its flexibility allowed it to work equally well for groups of any size and in any environment – forest or steppe. The much higher return rates associated with bow hunting freed enough labour to be allocated to other activities such as the intensification of fishing. Fishing and fisheries were important because they worked as a differentiating force: the more intensive the fishing, the more limited its spatial distribution and the greater the micro-regional differences between cultural patterns. Intensive fishing and game hunting pulled the adaptive strategies in two opposing directions: fishing towards differences and hunting towards similarities between groups and micro-regions. Social relations were important because they fine-tuned the social fabric to optimize the general strategy. Together, these factors account for all cultural transitions and variation documented for the Middle Holocene HG of Cis-Baikal: Transition 1 – formation of the Late Mesolithic cultural pattern with incipient formal cemeteries ~8630 cal BP; Transition 2 – replacement of the Late Mesolithic system on the Angara and in Southwest Baikal, but not in the Little Sea or on the Upper Lena, by the Early Neolithic Kitoi pattern with its very large cemeteries ~7560 cal BP; Transition 3 – collapse of the Kitoi by ~6660 cal BP followed by the formation of the Middle Neolithic pattern with no cemeteries; Transition 4 – reappearance of cemeteries ~6060 cal BP and the establishment of the Late Neolithic pattern; Transition 5 – formation of the Early Bronze Age system ~4970 cal BP; and lastly, Transition 6 – the end of the Early Bronze Age socio-economic pattern by ~3470 cal BP.

Air pollution is a serious problem in China, and the government has taken a series of steps to solve it. However, it is still u2nclear how the situation has improved after years of atmospheric pollution control. Shandong Province, which has the second largest population and the highest coal consumption in China, was chosen to analyze the spatiotemporal air quality trends. We obtained daily air quality index (AQI) values from 91 stations in the province from 1 January 2014, to 31 December 2019, based on an adaptive data analysis method, empirical mode decomposition (EMD). The distribution of AQI in Shandong Province was heterogeneous at both spatial and temporal scales. All the stations could be divided into four clusters whose AQI trends decreased from 75 to 53, 95 to 68, 128 to 82, and 148 to 82, respectively. The overall trend of pollution became more serious from east to west in the province. The AQI is the largest in winter, followed by spring and autumn, and the smallest index occurs in summer. There are four types of annual trends of the AQI of each city. The overall downward trend indicates that the air quality of each city was improving annually.

This paper analyzes two insect-related sets of agricultural field data. Both comprise spatially referenced count data sampled on a series of occasions. One concerns carabids (ground beetles) in cereals, the other the incidence and spread of an aphid-vectored virus disease of lupins. For both sets, the major objective was to describe and quantify the stability through time of the spatial patterns found for each occasion; this was measured by the spatial association between successive samples. Traditional methods for analyzing count data focus on properties of the frequency distribution of the counts and use little or none of the spatial information in the sample. We used methods that utilized all the spatial information and that, by conditioning on the observed data, provided complementary inferences to the other methods. Our analyses are based on a class of methods termed spatial analysis by distance indices (SADIE). These methods provide indices and formal randomization tests, both for the spatial pattern in a single population and for the spatial association when the patterns of two populations are compared. Our analyses showed considerable aggregation for both the beetles and the infected lupin plants. Furthermore, both populations displayed positive association between successive samples that declined as the temporal lag increased. The beetles were affected greatly by the harvest of the cereal crop. The lupin infections showed maximal association for a 1-week lag despite the fact that the latent period of the virus was a fortnight; it was inferred that the observed pattern of new infections was probably tracking the pattern of the aphid vectors 2 weeks previously. ; Government of Malaysia ; Biotechnology and Biological Sciences Research Council, United Kingdom ; Peer Review

AbstractRoad safety is an essential indicator of quality of life. This study compared the Chand and Alex severity index with the Equivalent Traffic Accident Number's (ETAN) severity index to understand the spatiotemporal pattern of road traffic crashes in Nigeria. Weighting road crash data could help mitigate road crash risk and improve road safety measures. The weighted crash ratios were calculated based on crash data available between 2012 and 2016. Six factors identified from the literature were used as denominators in deriving these ratios. The sum ratios were ranked and mapped for cross‐temporal examination. There was no significant difference between the two methods for assessing accident severity index in this study. Univariate and multivariate spatial analyses were used to detect the hotspot of the weighted crash severity index (WCSI) for the end of the study period. Only the pairwise comparison analysis found a significant difference between the 2012 and 2016 WCSI (p < 0.05). Multivariate regression identified significant associations between youth literacy, speed violation, tyre blowout, and weighted severity index. Geographically weighted regression indicates that their local effects vary across spatial units. Information obtained from this study is essential for developing strategies towards achieving safe roads in Nigeria and contributes to injury epidemiology research.

Historic expeditions are events that are flavored by exploratory, scientific, military or geographic characteristics. Such events are often documented in literature, journey notes or personal diaries. A typical historic expedition involves multiple site visits and their descriptions contain spatiotemporal and attributive contexts. Expeditions involve movements in space that can be represented by triplet features (location, time and description). However, such features are implicit and innate parts of textual documents. Extracting the geospatial information from these documents requires understanding the contextualized entities in the text. To this end, we developed a semi-automated framework that has multiple Information Retrieval and Natural Language Processing components to extract the spatiotemporal information from a two-volume historic expedition gazetteer. Our framework has three basic components, namely, the Text Preprocessor, the Gazetteer Processing Machine and the JAPE (Java Annotation Pattern Engine) Transducer. We used the Brazilian Ornithological Gazetteer as an experimental dataset and extracted the spatial and temporal entities from entries that refer to three expeditioners' site visits (which took place between 1910 and 1926) and mapped the trajectory of each expedition using the extracted information. Finally, one of the mapped trajectories was manually compared with a historical reference map of that expedition to assess the reliability of our framework.

Historic expeditions are events that are flavored by exploratory, scientific, military or geographic characteristics. Such events are often documented in literature, journey notes or personal diaries. A typical historic expedition involves multiple site visits and their descriptions contain spatiotemporal and attributive contexts. Expeditions involve movements in space that can be represented by triplet features (location, time and description). However, such features are implicit and innate parts of textual documents. Extracting the geospatial information from these documents requires understanding the contextualized entities in the text. To this end, we developed a semi-automated framework that has multiple Information Retrieval and Natural Language Processing components to extract the spatiotemporal information from a two-volumes historic expedition gazetteer. Our framework has three basic components, namely, the Text Preprocessor, the Gazetteer Processing Machine and the JAPE (Java Annotation Pattern Engine) Transducer. We used the Brazilian Ornithological Gazetteer as an experimental dataset and extracted the spatial and temporal entities from entries that refer to three expeditioners' site visits and mapped the trajectory of each expedition using the extracted information. Finally, one of the mapped trajectories was manually compared with a historical reference map of that expedition to assess the reliability of our framework. The reference map was manually prepared in previous research work by others.

The coronavirus disease of 2019 (COVID-19) pandemic is currently a global challenge, with 210 countries, including Indonesia, seeking to minimize its spread. Therefore, this study aims to determine the spatiotemporal spread pattern of this virus in Surabaya using various data on confirmed cases from 28 April to 26 October 2021. It also aims to determine the relationship between pollutant parameters, such as carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3), as well as the government's high social restrictions policy in Java-Bali. Several methods, such as the weighted mean center, directional distribution, Getis–Ord Gi*, Moran's I, and geographically weighted regression, were used to identify the spatial spread pattern of the virus. The weighted mean center indicated that the epicenter location of the outbreak moved randomly. The directional distribution demonstrated a decrease of 21 km2 at the end of the study phase, which proved that its spread has significantly reduced in Surabaya. Meanwhile, the Getis–Ord Gi* results demonstrated that the eastern and southern parts of the study region were highly infected. Moran's I demonstrate that COVID-19 cases clustered during the spike. The geographically weighted regression model indicated a number of influence zones in the northeast, northwest, and a few in the southwest parts at the peak of R2 0.55. The relationship between COVID-19 cases and air pollution parameters proved that people living at the outbreak's center have low pollution levels due to lockdown. Furthermore, the lockdown policy reduced CO, NO2, SO2, and O3. In addition, increase in air pollutants; namely, NO2, CO, SO2 and O3, was recorded after 7 weeks of lockdown implementation (started from 18 August).

As it is the second-largest freshwater lake downstream of the Three Gorges Dam and an important international wetland for migratory birds, there have been concerns about the ecological water health of Dongting Lake for a long time. In the present study, we studied the evolutionary characteristics of water quality in Dongting Lake in three recent years. Moreover, the evolution rules and dominant groups of the phytoplankton community were explored, and the major influencing factors of phytoplankton and their distribution were assessed based on the field survey and detection data from 2017 to 2019. The results indicated that the water quality of Dongting Lake improved in recent years. The concentration of dissolved oxygen (DO) increased by 6.91%, whereas the concentrations of the five-day biochemical oxygen demand (BOD5), chemical oxygen demand (CODCr), ammonia nitrogen (NH4+–N), total phosphorus (TP), and total nitrogen (TN) decreased by 17.5%, 13.0%, 33.8%, 7.6%, and 13.3%, respectively. The mean phytoplankton density reached 4.15 × 105 cells·L−1 in September 2017, whereas it was only 1.62 × 105 cells·L−1 in December 2018. There were 15 dominant species belonging to Cyanobacteria, Chlorophyta, Bacillariophyta, Cryptophyta, and Miozoa. Moreover, Fragilaria radians (Kützing) D.M.Williams & Round and Aulacoseiragranulata (Ehrenberg) Simonsen were the dominant populations in all seasons. The Pearson and linear regression analysis also indicated that the composition and distribution of phytoplankton in Dongting Lake were mainly affected by electrical conductivity (Cond), BOD5, potassium permanganate (CODMn), and CODCr, especially in Eastern Dongting Lake. Of course, NH4+–N, TN, and TP were also the main factors affecting the density and species of the phytoplankton community, especially in Western Dongting Lake. Finally, we suggested that local government could take "The relationship between Yangtze River and Dongting Lake", "The relationship between the seven fed rivers and Dongting Lake", and "The relationship ...

Abstract
There is worldwide concern about how climate change —which involves rising temperatures— may increase the risk of contracting and developing diseases, reducing the quality of life. This study provides new research that takes into account parameters such as land surface temperature (LST), surface urban heat island (SUHI), urban hotspot (UHS), air pollution (SO2, NO2, CO, O3 and aerosols), the normalized difference vegetation index (NDVI), the normalized difference building index (NDBI) and the proportion of vegetation (PV) that allows evaluating environmental quality and establishes mitigation measures in future urban developments that could improve the quality of life of a given population. With the help of Sentinel 3 and 5P satellite images, we studied these variables in the context of Granada (Spain) during the year 2021 to assess how they may affect the risk of developing diseases (stomach, colorectal, lung, prostate and bladder cancer, dementia, cerebrovascular disease, liver disease and suicide). The results, corroborated by the statistical analysis using the Data Panel technique, indicate that the variables LST, SUHI and daytime UHS, NO2, SO2 and NDBI have important positive correlations above 99% (p value: 0.000) with an excess risk of developing these diseases. Hence, the importance of this study for the formulation of healthy policies in cities and future research that minimizes the excess risk of diseases.