Spatiotemporal Dengue Disease Clustering by Means Local Spatiotemporal Moran’s Index

Jaya, I Gede Nyoman Mindra; Andriyana, Yudhie; Tantular, Bertho; Zulhanif,; Ruchjana, Budi Nurani

doi:10.1088/1757-899x/621/1/012017

Cited by 11 publications

(4 citation statements)

References 6 publications

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“…To judge the specific location where aggregation occurs, the local Moran's I index and LISA cluster map were used to visualize the differences between adjacent regions [36]. The formula used is as follows:…”

Section: Spatial Correlation Analysismentioning

confidence: 99%

Landscape Ecological Risk Assessment and Analysis of Influencing Factors in Selenga River Basin

Li,

Lin,

Hao

et al. 2023

Remote Sensing

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Land degradation under the influence of global warming and ecological environmental destruction due to poor land management is the main challenge facing the Mongolian Plateau, and its future ecological risk change trends and drivers are also unclear. Therefore, to address the context relevant to this challenge, planning based on measured information from land use patterns is required. Based on land use and land cover (LULC), this study evaluates the landscape ecological risk (LER) of the Selenga River Basin by calculating the landscape pattern index. The spatiotemporal pattern and influencing factors of landscape ecological risk in the Selenga River Basin from 1990 to 2040 were analyzed. According to the results of LULC analysis, forest and grassland were the primary land use types in the Selenga River Basin. The built area, forest, and cropland showed an increasing trend, while the grassland area showed a fluctuating decreasing trend. From 1990 to 2010, the comprehensive land use dynamic degree showed a trend of rising first and then falling, specifically from 0.13% in 1990 to 0.29% in 2010, and will drop to 0.06% by 2040, indicating that the range of land use change is becoming more and more stable. The landscape ecological risk assessment shows a distribution pattern of “low at the edge and high in the middle”. The landscape ecological risk index (LER) first increases and then decreases, with the peak value in 2010 (0.085). By calculating the spatial aggregation of LER and the partial correlation with climate, we found that the Moran’s I index showed an “anti-V”-shaped change trend from 1990 to 2040, and the average landscape ecological risk presents positive spatial correlation, primarily with high-value aggregation, and peaked in 2010. Precipitation had a negative correlation with landscape ecological risk controlling for temperature, while there was a positive relationship between temperature and landscape ecological risk under the influence of controlling precipitation. This study provides a scientific basis for LULC planning in the Selenga River Basin, and is of great significance for maintaining the ecological security of the Mongolian Plateau.

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Section: Spatial Correlation Analysismentioning

confidence: 99%

Landscape Ecological Risk Assessment and Analysis of Influencing Factors in Selenga River Basin

Li,

Lin,

Hao

et al. 2023

Remote Sensing

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“…65 < Z < 1. 65 means that the types of medicinal plant resources in Inner Mongolia are not related to spatial distribution and are distributed randomly in space ( Jaya et al, 2019 ). The spatial weights were row normalized during the spatial calculations to prevent the possibility of global Moran’s I index being outside (-1-1) ( Bivand and Wong 2018 ).…”

Section: Methodsmentioning

confidence: 99%

Complex ecological and socioeconomic impacts on medicinal plant diversity

Zhang

Chen²,

Guo³

et al. 2022

Front. Pharmacol.

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Medicinal plant diversity (MPD) is an important component of plant diversity. Over-collection based on medicinal and economic value has the potential to damage the stability of the regional ecosystem. It is important to understand the current distribution of MPD and the factors influencing it. However, it is still unclear whether environmental and socioeconomic conditions have an impact on their distribution. We selected the Inner Mongolia as a representative study area which covers a wide area, accounting for 12.29% of China’s national land area and 0.79% of the world’s land area. At the same time, the region is a long-standing traditional medicinal area for Mongolians in China. Therefore, the region is significantly influenced by changes in environmental factors and socio-economic factors. We used 9-years field survey of the distribution of medicinal plants in Inner Mongolia for assessing the distribution of MPD as influenced by environmental and socioeconomic activities by combining spatial analyses, species distribution models, and generalized additive models. The results from the spatial analysis show that the western region of Inner Mongolia is the main cold spot area of the MPD, and the central-eastern and northeastern regions of Inner Mongolia are the main hot spot areas of the MPD. At the same time, the distribution of cold spots and hot spots of MPD is more obvious at large spatial scales, and with the refinement of spatial scales, the cold spots in scattered areas are gradually revealed, which is indicative for the conservation and development of MPD at different spatial scales. Under the future climate change of shared socioeconomic pathways (SSP), areas with high habitat suitability for medicinal plants remain mainly dominated by the Yellow River, Yin Mountains, and Greater Khingan Range. Notably, the SSP245 development pathway remains the most significant concern in either long- or short-term development. The nonlinear relationship between the driving factors of MPD at different spatial scales shows that temperature, precipitation and socioeconomic development do have complex effects on MPD. The presence of a certain temperature, altitude, and precipitation range has an optimal facilitation effect on MPD, rather than a single facilitation effect. This complex nonlinear correlation provides a reference for further studies on plant diversity and sustainable development and management. In this study, the spatial distribution of medicinal plant resources and the extent to which they are driven by ecological and socioeconomic factors were analyzed through a macroscopic approach. This provides a reference for larger-scale studies on the environmental and socioeconomic influences on the distribution of plant resources.

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“…In (1), where N represents total number of spatial units, ∑ is the summation of the attributes, Xi and Xj are the values of attributes in areas i and j, x is the mean value of the observations in n municipalities, and wij is the matrix for the spatial weights. 27,[30][31][32] The analysis of the simultaneous presence (coexis-…”

Section: Artículo Originalmentioning

confidence: 99%

Spatiotemporal patterns of dengue and Zika incidence during the 2015-2018 outbreak of Zika in Mexico

et al. 2022

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Objective. Evaluate spatially and temporally simultaneous presence of clusters of dengue and Zika clinical cases and their relationship with expected dengue transmission risk. Materials and methods. A classification of dengue risk transmission was carried out for whole country, and spatial autocorrelation analyses to identify clusters of confirmed clinical cases of dengue and Zika from 2015 to 2018 was conducted using Moran’s Index statistics. Results. Clusters of both diseases were identified in dengue-high risk municipalities at the beginning of the outbreak, but, at the end of the outbreak, Zika clusters occurred in dengue low-risk municipalities. Conclusion. This study identified Zika clusters in low-risk dengue areas suggesting participation of several factors that favor virus introduction and dissemination, such as differences in entomological and control interventions, and the possibility of cross-immunity in the population.

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Spatiotemporal Dengue Disease Clustering by Means Local Spatiotemporal Moran’s Index

Cited by 11 publications

References 6 publications

Landscape Ecological Risk Assessment and Analysis of Influencing Factors in Selenga River Basin

Landscape Ecological Risk Assessment and Analysis of Influencing Factors in Selenga River Basin

Complex ecological and socioeconomic impacts on medicinal plant diversity

Spatiotemporal patterns of dengue and Zika incidence during the 2015-2018 outbreak of Zika in Mexico

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