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Data · dataset · 2022

Exploring the spatial relationship between exposure to agrochemicals with Covid-19 infection using a Geographically Weighted Regression model: A case study of East-Azarbayjan, Iran

Listed in Teesside University Research Data Repository

This Geodatabase consists two Feature Datasets including RawData and Results.

Description

The RawData contains some Feature classes storing the COVID-19 infection, Mortality due to infection, and Mortality To Infection Ratio during 1 April 2020 to 28 February 2022 (monthly) in addition Agrochemicals used during 2000 to 2018 (yearly) in the East-Azerbaijan province in Iran. Moreover the feature dataset contains the population data in the province.

Furthermore, all of the variables are stored in a feature class. Additionally, the Results feature dataset contains the results of GWR model separately for Pesticides and Fertilizers relationships with COVID-19.

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Where it is published

Catalogue records · 1

Topics

Provenance · 1 source records, 7 field assertions
SourceKeyLast seenRaw
Teesside University Research Data Repositoryoai:data.mendeley.com/vmyw6nwn7p.116 h agoJSON v1
FieldAssertionExtractorEvidence
access_levelsource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
concepts[field].local:field:earth-environmentalmapping · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
concepts[field].local:field:medicine-healthmapping · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
descriptionsource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0/metadata/dc/description
licensesource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0/metadata/dc/rights
publication_datesource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
titlesource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0/metadata/dc/title