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Epidemiological Characteristics of COVID-19 Deaths In China: An Analysis of Environmental Factors (preprint)
researchsquare; 2021.
Preprint in English | PREPRINT-RESEARCHSQUARE | ID: ppzbmed-10.21203.rs.3.rs-757532.v2
ABSTRACT

Background:

As of April 2020, most of the confirmed cases outside Hubei province have been cured or confirmed dead in China. We aimed to understand environmental factors leading to COVID-19-related mortality in non-Hubei region.

Methods:

We collected spatial-temporal and environmental data of 99 cases of COVID-19-related deaths outside of Hubei province in Mainland China between January 22, 2020 and April 6, 2020. A descriptive analysis, including a spatial-temporal distribution of daily reported diagnosed cases and related deaths, was conducted. We analyzed the possible environmental factors that affect the provincial-level case fatality rate (CFR) of COVID-19 outside Hubei, China.

Results:

Among the 99 reported deaths, 59 (59.6%) were male and 40 (40.4%) were female. The mean age at death was 71.30 (SD 12.98) years and 74 deaths were among those 65 years or older. The CFR was negatively correlated with temperature (r=-0.679, P <0.001) and humidity (r=-0.607, P =0.002), while latitude was positively correlated with the CFR (r=0.636, P =0.001). There were no statistically significant associations between CFR and the social environment factors.

Conclusion:

Higher CFR of COVID-19 was associated with lower temperature, lower humidity, and higher latitude. Continual analysis of daily reported diagnoses and mortality data can help healthcare professionals and policy makers understand the trends within a country in order to better prepare nationwide prevention and care guidelines, along with adequately appropriate funds accordingly.
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Full text: Available Collection: Preprints Database: PREPRINT-RESEARCHSQUARE Main subject: COVID-19 Language: English Year: 2021 Document Type: Preprint

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Full text: Available Collection: Preprints Database: PREPRINT-RESEARCHSQUARE Main subject: COVID-19 Language: English Year: 2021 Document Type: Preprint