Abstract:
:The geographical distribution of COVID-19 through Geographic Information Systems resources is hardly explored. We aimed to analyze the distribution of COVID-19 cases and the exclusive intensive care beds in the state of Ceará, Brazil. This is an ecological study with the geographic distribution of the case detection coefficient in 184 municipalities. Maps of crude and estimated values (global and local Bayesian method) were developed, calculating the Moran index and using BoxMap and MoranMap. Intensive care beds were distributed through geolocalized points. In total, 3,000 cases and 459 beds were studied. The highest rates were found in the capital Fortaleza, the Metropolitan Region (MR), and the south of this region. A positive spatial autocorrelation has been identified in the local Bayesian rate (I = 0.66). The distribution of beds superimposed on the BoxMap shows clusters with a High-High pattern of number of beds (capital, MR, northwestern part). However, a similar pattern is found in the far east or transition areas with insufficient beds. The MoranMap shows clusters statistically significant in the state. COVID-19 interiorization in Ceará requires contingency measures geared to the distribution of specific intensive care beds for COVID-19 cases in order to meet the demand. :A distribuição geográfica da COVID-19 por meio de recursos de Sistemas de Informação Geográfica é pouco explorada. O objetivo foi analisar a distribuição de casos da COVID-19 e de leitos de terapia intensiva exclusivos para a doença no estado do Ceará, Brasil. Estudo ecológico, com distribuição geográfica do coeficiente de detecção de casos da doença em 184 municípios. Construíram-se mapas dos valores brutos e estimados (método bayesiano global e local), com cálculo do índice de Moran e utilização do “BoxMap” e “MoranMap” Os leitos foram distribuídos por meio de pontos geolocalizados. Estudaram-se 3.000 casos e 459 leitos. As maiores taxas encontram-se na capital Fortaleza, região metropolitana (RM) e ao sul dessa região. Há autocorrelação espacial positiva na taxa bayesiana local (I = 0,66). A distribuição dos leitos de terapia intensiva sobreposta ao “BoxMap” evidenciou aglomerados com padrão Alto-Alto apresentando número de leitos (capital, RM, porção noroeste); porém, há o mesmo padrão (extremo leste) e em áreas de transição com insuficiência de leito. O “MoranMap” evidenciou “clusters” estatisticamente significativos no estado. A interiorização da COVID-19 no Ceará demanda medidas de contingência voltadas à distribuição dos leitos de terapia intensiva específicos para casos de COVID19 para atender à demanda.
journal_name
Cien Saude Coletjournal_title
Ciencia & saude coletivaauthors
Pedrosa NL,Albuquerque NLSdoi
10.1590/1413-81232020256.1.10952020subject
Has Abstractpub_date
2020-06-01 00:00:00pages
2461-2468issue
suppl 1eissn
1413-8123issn
1678-4561pii
S1413-81232020006702461journal_volume
25pub_type
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journal_title:Ciencia & saude coletiva
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doi:10.1590/1413-81232018232.03462016
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doi:10.1590/1413-81232015204.00362014
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journal_title:Ciencia & saude coletiva
pub_type: 杂志文章
doi:10.1590/s1413-81232008000900021
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journal_title:Ciencia & saude coletiva
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journal_title:Ciencia & saude coletiva
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journal_title:Ciencia & saude coletiva
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doi:10.1590/1413-81232020256.23252018
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