This study aimed to analyse the geographical distribution of COVID-19 and to identify highrisk areas in space and time for the occurrence of cases and deaths in the indigenous population of Brazil. This is an ecological study carried out between 24 March and 26 October 2020 whose units of analysis were the Special Indigenous Sanitary Districts. The Getis-Ord General G and Getis-Ord Gi* techniques were used to verify the spatial association of the phenomena and a retrospective space−time scan was performed. There were 32041 confirmed cases of COVID-19 and 471 deaths. The non-randomness of cases (z score = 5.40; p <0.001) and deaths (z score = 3.83; p <0.001) were confirmed. Hotspots were identified for cases and deaths in the north and midwest regions of Brazil. Sixteen high-risk space−time clusters were identified for the occurrence of cases with a higher RR=21.23 (p <0.001) and four risk clusters for deaths with a higher RR=80.33 (p <0.001). These clusters were identified from 22 May and were active until 10 October 2020. The results indicate critical areas in the indigenous territories of Brazil and contribute to better directing the actions of control of COVID-19 in this population.
SUMMARYThis study aimed to analyze the geographical distribution of COVID-19 and to identify highrisk areas for the occurrence of cases and deaths from the disease in the indigenous population of Brazil. This is an ecological study whose units of analysis were the Special Indigenous Sanitary Districts. Cases and deaths by COVID-19 notified by the Special Secretariat for Indigenous Health between March and October 2020 were included. To verify the spatial association, the Getis-Ord General G and Getis-Ord Gi * techniques were used. High spatial risk clusters have been identified by the scan statistics technique. 32,041 cases of COVID-19 and 471 deaths were reported. The incidence and mortality rates were between 758.14 and 18530.56 cases and 5.96 and 265.37 deaths per 100 thousand inhabitants, respectively. The non-randomness of cases (z-score = 5.40; p <0.001) and deaths (z-score = 3.83; p <0.001) was confirmed. Hotspots were evidenced for both events with confidence levels of 90, 95 and 99% concentrated in the North and Midwest regions of the country. Eight high-risk spatial clusters for cases with a relative risk (RR) between 1.08 and 4.11 (p <0.05) and two risk clusters for deaths with RR between 3.08 and 3.97 (p <0.05) were identified. The results indicate critical areas in the indigenous territories of Brazil and contribute to better targeting the control actions of COVID-19 in this population.
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