Datasets for investigating the relationship between leptospirosis and moyamoya disease in Hubei, China

Published: 16 September 2021| Version 2 | DOI: 10.17632/k85f6rj28f.2
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Description

The datasets of manuscript "An ecological comparison study on the causal association between leptospirosis and moyamoya disease (MMD) in Hubei, China, 2017-2019" which was submitted to the journal Clinical Neurology and Neurosurgery. Figure 1. Map of the study area. A. The administrative division of Hubei province at both county and city level. B. The geographic feature of the province. DEM (digital elevation model), which represents the diverse landforms: hills in the east, mountains in the west, and plain in the south-central. Figure 2. The annual surveillance data of leptospirosis in Hubei province (1960-2020). The data was collected from the Hubei province health statistics yearbook written by Hubei CDC. Figure 3. Average annual incidence of MMD by sex and age from 2017 to 2019. “Total” represents sex adjusted incidence in different age groups. Figure 4. Age-adjusted incidence rate (AAIR) and hot-spot analysis mapped by county in 2017 (A and B), 2018 (C and D), and 2019 (E and F). The AAIR at the county-level was divided into 5 groups and displayed in different colors, deeper color represents higher MMD incidence. The result of hot spot analysis includes 7 groups from -3 to 3. The value of -3, -2, and -1 represents 99%, 95%, and 90% confidence of cold spot, respectively; The value of 3, 2, and 1 represents 99%, 95%, and 90% confidence of hot spot, respectively; The value of 0 represents not cluster. Table 1. The basic characteristics of MMD in Hubei province from 2017 to 2019. Table 2. Comparison of the AAIR and the variables between hot and cold spots.

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Steps to reproduce

Annual Incidence was adjusted by sex and age with standard population (2010). County-level annual age adjusted incidence rate (AAIR) was used to spatial analysis with software ArcGIS (10.7 ESRI, Redlands, CA, USA). To examine the hot and cold spots of MMD, we applied the spatial statistical method of Getis-Ord Gi*. The annual AAIR and socioeconomic and environmental variables in hot and cold spots were shown as the median (IQR) and were compared using the Wilcoxon rank-sum test.

Categories

Environmental Epidemiology, Stroke, Bacterial Pathogen, Causal Inference, Ecological Analysis

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