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      Epidemiology, Biodiversity, and Technological Trajectories in the Brazilian Amazon: From Malaria to COVID-19

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          Abstract

          The Amazon biome is under severe threat due to increasing deforestation rates and loss of biodiversity and ecosystem services while sustaining a high burden of neglected tropical diseases. Approximately two thirds of this biome are located within Brazilian territory. There, socio-economic and environmental landscape transformations are linked to the regional agrarian economy dynamics, which has developed into six techno-productive trajectories (TTs). These TTs are the product of the historical interaction between Peasant and Farmer and Rancher practices, technologies and rationalities. This article investigates the distribution of the dominant Brazilian Amazon TTs and their association with environmental degradation and vulnerability to neglected tropical diseases. The goal is to provide a framework for the joint debate of the local economic, environmental and health dimensions. We calculated the dominant TT for each municipality in 2017. Peasant trajectories (TT1, TT2, and TT3) are dominant in ca. fifty percent of the Amazon territory, mostly concentrated in areas covered by continuous forest where malaria is an important morbidity and mortality cause. Cattle raising trajectories are associated with higher deforestation rates. Meanwhile, Farmer and Rancher economies are becoming dominant trajectories, comprising large scale cattle and grain production. These trajectories are associated with rapid biodiversity loss and a high prevalence of neglected tropical diseases, such as leishmaniasis, Aedes-borne diseases and Chagas disease. Overall, these results defy simplistic views that the dominant development trajectory for the Amazon will optimize economic, health and environmental indicators. This approach lays the groundwork for a more integrated narrative consistent with the economic history of the Brazilian Amazon.

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          Most cited references 87

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          Global trends in emerging infectious diseases

          The next new disease Emerging infectious diseases are a major threat to health: AIDS, SARS, drug-resistant bacteria and Ebola virus are among the more recent examples. By identifying emerging disease 'hotspots', the thinking goes, it should be possible to spot health risks at an early stage and prepare containment strategies. An analysis of over 300 examples of disease emerging between 1940 and 2004 suggests that these hotspots can be accurately mapped based on socio-economic, environmental and ecological factors. The data show that the surveillance effort, and much current research spending, is concentrated in developed economies, yet the risk maps point to developing countries as the more likely source of new diseases. Supplementary information The online version of this article (doi:10.1038/nature06536) contains supplementary material, which is available to authorized users.
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            Biodiversity loss and its impact on humanity.

            The most unique feature of Earth is the existence of life, and the most extraordinary feature of life is its diversity. Approximately 9 million types of plants, animals, protists and fungi inhabit the Earth. So, too, do 7 billion people. Two decades ago, at the first Earth Summit, the vast majority of the world's nations declared that human actions were dismantling the Earth's ecosystems, eliminating genes, species and biological traits at an alarming rate. This observation led to the question of how such loss of biological diversity will alter the functioning of ecosystems and their ability to provide society with the goods and services needed to prosper.
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              Emergence and potential for spread of Chikungunya virus in Brazil

              Background In December 2013, an outbreak of Chikungunya virus (CHIKV) caused by the Asian genotype was notified in the Caribbean. The outbreak has since spread to 38 regions in the Americas. By September 2014, the first autochthonous CHIKV infections were confirmed in Oiapoque, North Brazil, and in Feira de Santana, Northeast Brazil. Methods We compiled epidemiological and clinical data on suspected CHIKV cases in Brazil and polymerase-chain-reaction-based diagnostic was conducted on 68 serum samples from patients with symptom onset between April and September 2014. Two imported and four autochthonous cases were selected for virus propagation, RNA isolation, full-length genome sequencing, and phylogenetic analysis. We then followed CDC/PAHO guidelines to estimate the risk of establishment of CHIKV in Brazilian municipalities. Results We detected 41 CHIKV importations and 27 autochthonous cases in Brazil. Epidemiological and phylogenetic analyses indicated local transmission of the Asian CHIKV genotype in Oiapoque. Unexpectedly, we also discovered that the ECSA genotype is circulating in Feira de Santana. The presumed index case of the ECSA genotype was an individual who had recently returned from Angola and developed symptoms in Feira de Santana. We estimate that, if CHIKV becomes established in Brazil, transmission could occur in 94% of municipalities in the country and provide maps of the risk of importation of each strain of CHIKV in Brazil. Conclusions The etiological strains associated with the early-phase CHIKV outbreaks in Brazil belong to the Asian and ECSA genotypes. Continued surveillance and vector mitigation strategies are needed to reduce the future public health impact of CHIKV in the Americas. Electronic supplementary material The online version of this article (doi:10.1186/s12916-015-0348-x) contains supplementary material, which is available to authorized users.
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                Author and article information

                Contributors
                Journal
                Front Public Health
                Front Public Health
                Front. Public Health
                Frontiers in Public Health
                Frontiers Media S.A.
                2296-2565
                13 July 2021
                2021
                13 July 2021
                : 9
                Affiliations
                1Programa de Computação Científica, Fundação Oswaldo Cruz , Rio de Janeiro, Brazil
                2Laboratório de Investigação em Sistemas Socioambientais, Instituto Nacional de Pesquisas Espaciais , Sao Jose dos Campos, Brazil
                3Centro de Ciência do Sistema Terrestre, Instituto Nacional de Pesquisas Espaciais , Sao Jose dos Campos, Brazil
                4Laboratório de Biologia e Parasitologia de Mamíferos Silvestres Reservatórios, Instituto Oswaldo Cruz, Fundação Oswaldo Cruz , Rio de Janeiro, Brazil
                5Ecologia Evolutiva e Biodiversidade, DGEE, Universidade Federal de Minas Gerais , Belo Horizonte, Brazil
                6Instituto de Ciências Sociais Aplicadas e Núcleo de Altos Estudos Amazônicos, Universidade Federal do Pará , Belem, Brazil
                7Instituto de Estudos em Desenvolvimento Agrário e Regional, Universidade Federal do Sul e Sudeste do Pará , Maraba, Brazil
                8Laboratório de Mosquitos Transmissores de Hematozoários, Instituto Oswaldo Cruz, Fundação Oswaldo Cruz , Rio de Janeiro, Brazil
                9Universidade Federal do Acre , Rio Branco, Brazil
                10Laboratório de Produtos Florestais, Serviço Florestal Brasileiro , Brasília, Brazil
                11Escola de Matemática Aplicada, Fundação Getúlio Vargas , Rio de Janeiro, Brazil
                Author notes

                Edited by: Giulio De Leo, Stanford University, United States

                Reviewed by: Simon Rodrigo Rüegg, University of Zurich, Switzerland; Maquins Odhiambo Sewe, Umeå University, Sweden

                *Correspondence: Claudia T. Codeço claudia.codeco@ 123456fiocruz.br

                This article was submitted to Planetary Health, a section of the journal Frontiers in Public Health

                Article
                10.3389/fpubh.2021.647754
                8314010
                34327184
                Copyright © 2021 Codeço, Dal'Asta, Rorato, Lana, Neves, Andreazzi, Barbosa, Escada, Fernandes, Rodrigues, Reis, Silva-Nunes, Gontijo, Coelho and Monteiro.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                Page count
                Figures: 3, Tables: 2, Equations: 0, References: 94, Pages: 14, Words: 11140
                Funding
                Funded by: Conselho Nacional de Desenvolvimento Científico e Tecnológico 10.13039/501100003593
                Categories
                Public Health
                Hypothesis and Theory

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