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Article . 2024
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DIGITAL.CSIC
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Compilation of open access time-series datasets for studying temperature-mortality association

Authors: Aurelio Tobias; Chris Fook Sheng Ng; Yoonhee Kim; Masahiro Hashizume; Lina Madaniyazi;

Compilation of open access time-series datasets for studying temperature-mortality association

Abstract

In this article, we present a comprehensive compilation of open access daily time-series datasets tailored to assess the temperature-mortality association. The data consists of daily mortality counts and average ambient temperature at various levels of geographic aggregation, including data from four cities, ten regions, and two counties, which have been utilised in previously published studies. These datasets are applicable for time-series regression analysis to estimate location-specific temperature-mortality associations. Additionally, the availability of data from multiple geographical locations enabled the exploration of geographical differences by pooling associations using meta-analysis. This compilation aims to serve as a valuable resource for researchers, educators, and students, facilitating their application of time-series regression modelling for research endeavours and training activities.

Country
Spain
Keywords

Take urgent action to combat climate change and its impacts, Science (General), Computer applications to medicine. Medical informatics, R858-859.7, http://metadata.un.org/sdg/3, Q1-390, Environmental health, Multi-location studies, Climate change, Environmental epidemiology, http://metadata.un.org/sdg/13, Time-series regression, Ensure healthy lives and promote well-being for all at all ages, Data Article

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
2
Top 10%
Average
Average
34
47
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gold