RESUMO
Objective: To estimate the incidence, mortality and lethality rates of COVID-19 among Indigenous Peoples in the Brazilian Amazon. Additionally, to analyze how external threats can contribute to spread the disease in Indigenous Lands (IL). Methods: The Brazilian Amazon is home to nearly half a million Indigenous persons, representing more than 170 ethnic groups. As a pioneer in heading Indigenous community-based surveillance (I-CBS) in Brazil, the Coordination of the Indigenous Organizations of the Brazilian Amazon (COIAB) started to monitor Indigenous COVID-19 cases in March of 2020. Brazil's Ministry of Health (MOH) was the main source of data regarding non-Indigenous cases and deaths; to contrast the government's tally, we used the information collected by I-CBS covering 25 Special Indigenous Sanitary Districts (DSEI) in the Brazilian Amazon. The incidence and mortality rates of COVID-19 were calculated using the total number of new cases and deaths accumulated between the 9th and 40th epidemiological weeks. We studied (a) the availability of health care facilities to attend to Indigenous Peoples; (b) illegal mines, land grabbing, and deforestation to perform a geospatial analysis to assess how external threats affect Indigenous incidence and mortality rates. We used the Generalized Linear Model (GLM) with Poisson regression to show the results. Results: MOH registered 22,127 cases and 330 deaths, while COIAB's survey recorded 25,356 confirmed cases and 670 deaths, indicating an under-reporting of 14 and 103%, respectively. Likewise, the incidence and mortality rates were 136 and 110% higher among Indigenous when compared with the national average. In terms of mortality, the most critical DSEIs were Alto Rio Solimões, Cuiabá, Xavante, Vilhena and Kaiapó do Pará. The GLM model reveals a direct correlation between deforestation, land grabbing and mining, and the incidence of cases among the Indigenous. Conclusion: Through this investigation it was possible to verify that not only the incidence and mortality rates due to COVID-19 among Indigenous Peoples are higher than those observed in the general population, but also that the data presented by the federal government are underreported. Additionally, it was evident that the presence of illegal economic activities increased the risk of spreading COVID-19 in ILs.
RESUMO
Although marine protected areas can simultaneously contribute to biodiversity conservation and fisheries management, the global network is biased toward particular ecosystem types because they have been established primarily in an ad hoc fashion. The optimization of trade-offs between biodiversity benefits and socioeconomic values increases success of protected areas and minimizes enforcement costs in the long run, but it is often neglected in marine spatial planning (MSP). Although the acquisition of spatially explicit socioeconomic data is perceived as a costly or secondary step in MSP, it is critical to account for lost opportunities by people whose activities will be restricted, especially fishers. We developed an easily reproduced habitat-based approach to estimate the spatial distribution of opportunity cost to fishers in data-poor regions. We assumed the most accessible areas have higher economic and conservation values than less accessible areas and their designation as no-take zones represents a loss of fishing opportunities. We estimated potential distribution of fishing resources from bathymetric ranges and benthic habitat distribution and the relative importance of the different resources for each port of total catches, revenues, and stakeholder perception. In our model, we combined different cost layers to produce a comprehensive cost layer so that we could evaluate of trade-offs. Our approach directly supports conservation planning, can be applied generally, and is expected to facilitate stakeholder input and community acceptance of conservation.
