Kümelenme analizine genel bir bakış

Year 2022, Volume: 33 Issue: 2, 79 - 84, 23.12.2022

İpek Keskin

https://doi.org/10.35864/evmd.1056351

Abstract

Halk sağlığını etkileyen hastalıkların ortaya çıkmasında etkili olan özelliklerin tanımlanması, hastalıkların daha iyi anlaşılmasına ve kontrol altına alınmasına katkı sağlamaktadır. Bir olayın gerçekleştiği yer, söz konusu olayın neden gerçekleştiğine dair bazı göstergeler sağlayabilmektedir. Hastalıkların yer ve zaman verilerini analiz etmek için spesifik istatistik testler bulunmaktadır. Son 20 yıldır yer ve yer-zaman tarama istatistikleri hastalık kümelenmelerinin belirlenmesi, değerlendirilmesi ve hastalık sürveyansı amacıyla yaygın olarak kullanılmaktadır. Yer ve yer-zaman analizleri bulaşıcı hastalıklarda özellikle de zoonozlarda, hastalık riski veya insidansındaki mekansal ve zamansal çeşitliliğin nedenlerini ve sonuçlarını incelemektedir. Bu derlemede yer ve/veya zamanda beklenenden daha fazla vakaya sahip hastalık kümelerinin tespitinde yaygın olarak kullanılan mekansal tarama istatistiği olan SaTScan yazılımı ve Yer-Zaman Permutasyon Model hakkında bilgiler bir araya getirilmiştir.

Keywords

Halk sağlığı, kümelenme analizi, mekansal epidemiyoloji, SaTScan, yer-zaman permutasyon model

An overview of cluster analysis

Abstract

Identification of the characteristics that are effective in the emergence of diseases that affect public health contributes to a better understanding and control of diseases. The space where an event occurred can provide some indication of why that event occurred. There are specific statistical tests to analyze the space and time of diseases. For the last 20 years, space and space-time screening statistics have been widely used for the identification and evaluation of disease clusters and disease surveillance. Space and space-time analysis examine the causes and consequences of spatial and temporal variation in disease risk or incidence in infectious diseases, particularly zoonoses. In this review, information about the Space-Time Permutation Model and the SaTScan software, which is a spatial scanning statistic that is widely used in the detection of disease clusters with more cases than expected in space and/or time, has been brought together.

Keywords

Cluster analysis, public health, spatial epidemiology, SaTScan, space-time permutation model

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