Geospatial clustering of childhood IgA vasculitis and IgA vasculitis-associated nephritis

2020 ◽  
pp. annrheumdis-2020-218649
Author(s):  
Matej Sapina ◽  
Marijan Frkovic ◽  
Mario Sestan ◽  
Sasa Srsen ◽  
Aleksandar Ovuka ◽  
...  

ObjectivesResearch on spatial variability of the incidence of IgA vasculitis (IgAV) in children and its potential implications for elucidation of the multifactorial aetiology and pathogenesis is limited. We intended to observe spatial variability of the incidence of IgAV and IgA vasculitis-associated nephritis (IgAVN) using modern geostatistical methods, and hypothesised that their spatial distribution may be spatially clustered.MethodsPatients' data were retrospectively collected from 2009 to 2019 in five Croatian University Hospital Centres for paediatric rheumatology, and census data were used to calculate the incidence of IgAV. Using spatial empirical Bayesian smoothing, local Morans’ I and local indicator of spatial autocorrelation (LISA), we performed spatial statistical analysis.Results596 children diagnosed with IgAV were included in this study, of which 313 (52.52%) were male. The average annual incidence proportion was estimated to be 6.79 per 100 000 children, and the prevalence of IgAVN was 19.6%. Existence of spatial autocorrelation was observed in both IgAV and IgAVN; however, clustering distribution differed. While IgAV showed clustering in Mediterranean and west continental part around cities, IgAVN was clustered in the northern Mediterranean and eastern continental part, where a linear cluster following the Drava and Danube river was observed.ConclusionIgAV incidence in Croatia is similar to other European countries. Spatial statistical analysis showed a non-random distribution of IgAV and IgAVN. Although aetiological associations cannot be inferred, spatial analytical techniques may help in investigating and generating new hypotheses in non-communicable diseases considering possible environmental risk factors and identification of potential genetic or epigenetic diversity.

2021 ◽  
Vol 21 (2) ◽  
pp. 75-87
Author(s):  
Muzahem Al-Hashimi ◽  
Edrees M. Nori Mahmood

The spatial statistical analysis of breast cancer incidences across Iraq has not been explored in Iraq. This paper aimed to explore the spatial pattern and risk clusters of female breast cancer incidence from 2000 to 2015 in Iraq (except the Kurdish region). To enhance statistical stability and to access the changes over time, we split the data according to the geographical district into three periods (2000-2004, 2005-2009, and 2010-2015). The age-standardized incidence rates (ASRs) were calculated using the world standard population. Having obtained estimates ASRs, the global index of spatial autocorrelation (Moran’s  statistic) was used to assess spatial dependence across districts for ASRs. Anselin local Moran’s  statistic was used to identify spatial outliers. Additionally, we used Getis-Ord  statistic to detect hotspots and coldspots over entire Iraq that represent clusters of districts with significantly high or low ASRs. A total of 44,496 cases were reported in 2000-2015 in Iraq, with an ASR of incidence of (32.81/100,000). The ASR incidence of breast cancer showed a significant average percentage change of 5.40% from 2002 to 2015. The spatial autocorrelation analysis showed insignificant positive spatial autocorrelation in 2000-2004, and significant positive spatial autocorrelation in 2005-2009, and in 2010-2015. This study identified four districts as high-risk areas for breast cancer during the two periods 2005-2009 and 2010-2015, including Al-Karkh, Al-Adhamia, Al-Rissafa, and Al-Sadir. This information can assist the allocation of health care resources and expand cancer prevention efforts.


1989 ◽  
Vol 51 (2) ◽  
pp. 304-309
Author(s):  
Noriko SATO ◽  
Okitaka MAIE ◽  
Toshiko MASAHASHI ◽  
Hironobu MURAI ◽  
Yuhei TADA ◽  
...  

2021 ◽  
Vol 9 (4) ◽  
pp. 378
Author(s):  
Jong Kwan Kim

As high vessel traffic in fairways is likely to cause frequent marine accidents, understanding vessel traffic flow characteristics is necessary to prevent marine accidents in fairways. Therefore, this study conducted semi-continuous spatial statistical analysis tests (the normal distribution test, kurtosis test and skewness test) to understand vessel traffic flow characteristics. First, a vessel traffic survey was conducted in a designated area (Busan North Port) for seven days. The data were collected using an automatic identification system and subsequently converted using semi-continuous processing methods. Thereafter, the converted data were used to conduct three methods of spatial statistical analysis. The analysis results revealed the vessel traffic distribution and its characteristics, such as the degree of use and lateral positioning on the fairway based on the size of the vessel. In addition, the generalization of the results of this study along with that of further studies will aid in deriving the traffic characteristics of vessels on the fairway. Moreover, these characteristics will reduce maritime accidents on the fairway, in addition to establishing the foundation for research on autonomous ships.


2018 ◽  
Vol 10 (1) ◽  
pp. 64-78 ◽  
Author(s):  
Balázs Trásy ◽  
Tamás Garamhegyi ◽  
Péter Laczkó-Dobos ◽  
József Kovács ◽  
István Gábor Hatvani

Abstract The efficient operation of shallow groundwater (SGW) monitoring networks is crucial to water supply, in-land water protection, agriculture and nature conservation. In the present study, the spatial representativity of such a monitoring network in an area that has been thoroughly impacted by anthropogenic activity (river diversion/damming) is assessed, namely the Szigetköz adjacent to the River Danube. The main aims were to assess the spatial representativity of the SGW monitoring network in different discharge scenarios, and investigate the directional characteristics of this representativity, i.e. establish whether geostatistical anisotropy is present, and investigate how this changes with flooding. After the subtraction of a spatial trend from the time series of 85 shallow groundwater monitoring wells tracking flood events from 2006, 2009 and 2013, variography was conducted on the residuals, and the degree of anisotropy was assessed to explore the spatial autocorrelation structure of the network. Since the raw data proved to be insufficient, an interpolated grid was derived, and the final results were scaled to be representative of the original raw data. It was found that during floods the main direction of the spatial variance of the shallow groundwater monitoring wells alters, from perpendicular to the river to parallel with it for over a period of about two week. However, witht the passing of the flood, this returns to its original orientation in ~2 months. It is likely that this process is related first to the fast removal of clogged riverbed strata by the flood, then to their slower replacement. In addition, the study highlights the importance of assessing the direction of the spatial autocorrelation structure of shallow groundwater monitoring networks, especially if the aim is to derive interpolated maps for the further investigation or modeling of flow.


2010 ◽  
Vol 74 (1) ◽  
pp. 74-86 ◽  
Author(s):  
Roberto Baigorri ◽  
Marta Fuentes ◽  
Francisco J. González-Vila ◽  
José M. García-Mina

2019 ◽  
Vol 13 (2) ◽  
pp. 1021-1034 ◽  
Author(s):  
Takuya Takahashi ◽  
Koji Matsushita ◽  
Yoshio Yoshida ◽  
Tetsuji Senda

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