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. 2021 Apr 12;43(1):98-106.
doi: 10.1093/pubmed/fdaa140.

A first insight about spatial dimension of COVID-19: analysis at municipality level

Josep-Maria Arauzo-Carod  1
Affiliations

A first insight about spatial dimension of COVID-19: analysis at municipality level

Josep-Maria Arauzo-Carod. J Public Health (Oxf). .

Abstract

Background: This paper is about spatial patterns of by corona virus disease-2019 (COVID-19).

Methods: Using data for the first 21 weeks from municipalities in Catalonia, we analyse whether reported positive cases appear randomly or following some kind of spatial dependence. Global and local measures of spatial autocorrelation are used.

Results: There are some clusters alongside Catalan municipalities that change over time.

Conclusions: Use of spatial analysis techniques is suggested to identify spatial disease patterns and to provide spatially disaggregated public health policy recommendations.

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Figures

Fig. 1
Fig. 1
Spatial linkages between positive cases of COVID-19 and population. Note: population refers to total inhabitants in 2019; density of positive cases is calculated as number of case per 100 000 inhabitants.
Fig. 2
Fig. 2
Total positive case of COVID-19 reported per 100 000 inhabitants (weekly). Note: density of positive cases is calculated as number of cases per 100 000 inhabitants (according to population data of 2019).
Fig. 2
Fig. 2
Total positive case of COVID-19 reported per 100 000 inhabitants (weekly). Note: density of positive cases is calculated as number of cases per 100 000 inhabitants (according to population data of 2019).
Fig. 3
Fig. 3
LISA of reported positive cases. Note: density of positive cases is calculated as number of cases per 100 000 inhabitants (according to population data of 2019).
Fig. 4
Fig. 4
LISA of reported positive cases (Weekly data, density). Note: density of positive cases is calculated as number of cases per 100 000 inhabitants (according to population data of 2019).
Fig. 4
Fig. 4
LISA of reported positive cases (Weekly data, density). Note: density of positive cases is calculated as number of cases per 100 000 inhabitants (according to population data of 2019).
See this image and copyright information in PMC

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