![](data:image/png;base64,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)
enviesamento das TVs e dos outros meios de comunicação portugueses coloca o Brasil no segundo pior resultado do mundo nos mortos por Covid-19, atrás dos EUA de Donald Trump. Todavia, até hoje, 1-6-2020, o
Portugal marxista do louvado António Costa (e do aliado figurante Marcelo Rebelo de Sousa) tem mais mortos por milhão de habitantes do que o Brasil conservador do fustigado Jair Bolsonaro...
2 comentários:
Nem vale a pena comentar os patetas que desgraçam estas gentes. O tuga é mêmo stupid.
ao
Os únicos números que possuem alguma aproximação à realidade são aqueles de países do primeiro mundo. O Brasil não faz parte desse grupo. Como é evidente devido à pouca testagem o Brasil não faz a mínima ideia que quantos mortos tem por Covid-19 https://sicnoticias.pt/especiais/coronavirus/2020-05-26-Falta-de-testes-a-Covid-19-esconde-o-numero-real-de-mortos-em-Manaus
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