Amazonian biodiversity is increasingly threatened due to the weakening of policies for combating deforestation, especially in Brazil. Loss of animal and plant species, many not yet known to science, is just one among many negative consequences of Amazon deforestation. Deforestation affects indigenous communities, riverside as well as urban populations, and even planetary health. Amazonia has a prominent role in regulating the Earth's climate, with forest loss contributing to rising regional and global temperatures and intensification of extreme weather events. These climatic conditions are important drivers of emerging infectious diseases, and activities associated with deforestation contribute to the spread of disease vectors. This review presents the main impacts of Amazon deforestation on infectious-disease dynamics and public health from a One Health perspective. Because Brazil holds the largest area of Amazon rainforest, emphasis is given to the Brazilian scenario. Finally, potential solutions to mitigate deforestation and emerging infectious diseases are presented from the perspectives of researchers in different fields.

Genomic sequencing is essential to track the evolution and spread of SARS-CoV-2, optimize molecular tests, treatments, vaccines, and guide public health responses. To investigate the global SARS-CoV-2 genomic surveillance, we used sequences shared via GISAID to estimate the impact of sequencing intensity and turnaround times on variant detection in 189 countries. In the first two years of the pandemic, 78% of high-income countries sequenced >0.5% of their COVID-19 cases, while 42% of low- and middle-income countries reached that mark. Around 25% of the genomes from high income countries were submitted within 21 days, a pattern observed in 5% of the genomes from low- and middle-income countries. We found that sequencing around 0.5% of the cases, with a turnaround time <21 days, could provide a benchmark for SARS-CoV-2 genomic surveillance. Socioeconomic inequalities undermine the global pandemic preparedness, and efforts must be made to support low- and middle-income countries improve their local sequencing capacity.

Mutations accrued by SARS-CoV-2 lineage P.1—first detected in Brazil in early January, 2021—include amino acid changes in the receptor-binding domain of the viral spike protein that also are reported in other variants of concern, including B.1.1.7 and B.1.351. We aimed to investigate whether isolates of wild-type P.1 lineage SARS-CoV-2 can escape from neutralising antibodies generated by a polyclonal immune response. We did an immunological study to assess the neutralising effects of antibodies on lineage P.1 and lineage B isolates of SARS-CoV-2, using plasma samples from patients previously infected with or vaccinated against SARS-CoV-2. Two specimens (P.1/28 and P.1/30) containing SARS-CoV-2 lineage P.1 (as confirmed by viral genome sequencing) were obtained from nasopharyngeal and bronchoalveolar lavage samples collected from patients in Manaus, Brazil, and compared against an isolate of SARS-CoV-2 lineage B (SARS.CoV2/SP02.2020) recovered from a patient in Brazil in February, 2020. Isolates were incubated with plasma samples from 21 blood donors who had previously had COVID-19 and from a total of 53 recipients of the chemically inactivated SARS-CoV-2 vaccine CoronaVac: 18 individuals after receipt of a single dose and an additional 20 individuals (38 in total) after receipt of two doses (collected 17–38 days after the most recent dose); and 15 individuals who received two doses during the phase 3 trial of the vaccine (collected 134–230 days after the second dose). Antibody neutralisation of P.1/28, P.1/30, and B isolates by plasma samples were compared in terms of median virus neutralisation titre (VNT50, defined as the reciprocal value of the sample dilution that showed 50% protection against cytopathic effects). In terms of VNT50, plasma from individuals previously infected with SARS-CoV-2 had an 8·6 times lower neutralising capacity against the P.1 isolates (median VNT50 30 [IQR <20–45] for P.1/28 and 30 [<20–40] for P.1/30) than against the lineage B isolate (260 [160–400]), with a binominal model showing significant reductions in lineage P.1 isolates compared with the lineage B isolate (p≤0·0001). Efficient neutralisation of P.1 isolates was not seen with plasma samples collected from individuals vaccinated with a first dose of CoronaVac 20–23 days earlier (VNT50s below the limit of detection [<20] for most plasma samples), a second dose 17–38 days earlier (median VNT50 24 [IQR <20–25] for P.1/28 and 28 [<20–25] for P.1/30), or a second dose 134–260 days earlier (all VNT50s below limit of detection). Median VNT50s against the lineage B isolate were 20 (IQR 20–30) after a first dose of CoronaVac 20–23 days earlier, 75 (<20–263) after a second dose 17–38 days earlier, and 20 (<20–30) after a second dose 134–260 days earlier. In plasma collected 17–38 days after a second dose of CoronaVac, neutralising capacity against both P.1 isolates was significantly decreased (p=0·0051 for P.1/28 and p=0·0336 for P.1/30) compared with that against the lineage B isolate. All data were corroborated by results obtained through plaque reduction neutralisation tests. SARS-CoV-2 lineage P.1 might escape neutralisation by antibodies generated in response to polyclonal stimulation against previously circulating variants of SARS-CoV-2. Continuous genomic surveillance of SARS-CoV-2 combined with antibody neutralisation assays could help to guide national immunisation programmes. São Paulo Research Foundation, Brazilian Ministry of Science, Technology and Innovation and Funding Authority for Studies, Medical Research Council, National Council for Scientific and Technological Development, National Institutes of Health. For the Portuguese translation of the abstract see Supplementary Materials section.

The COVID-19 pandemic has revealed the importance of virus genome sequencing to guide public health interventions to control virus transmission and understand SARS-CoV-2 evolution. As of July 20th, 2021, >2 million SARS-CoV-2 genomes have been submitted to GISAID, 94% from high income and 6% from low and middle income countries. Here, we analyse the spatial and temporal heterogeneity in SARS-CoV-2 global genomic surveillance efforts. We report a comprehensive analysis of virus lineage diversity and genomic surveillance strategies adopted globally, and investigate their impact on the detection of known SARS-CoV-2 virus lineages and variants of concern. Our study provides a perspective on the global disparities surrounding SARS-CoV-2 genomic surveillance, their causes and consequences, and possible solutions to maximize the impact of pathogen genome sequencing for efforts on public health. One-Sentence Summary The causes, consequences and possible solutions for disparities in genomic surveillance observed in the COVID-19 pandemic.