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Assessing spatial distribution of COVID-19 prevalence in Brazil using decentralised sewage monitoring

Brazil has become one of the epicentres of the COVID-19 pandemic, with cases heavily concentrated in large cities. Testing data is extremely limited and unreliable, which restricts health authorities’ ability to deal with the pandemic. Given the stark demographic, social and economic heterogeneities...

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Detalles Bibliográficos
Autores principales: Mota, Cesar R., Bressani-Ribeiro, Thiago, Araújo, Juliana C., Leal, Cíntia D., Leroy-Freitas, Deborah, Machado, Elayne C., Espinosa, Maria Fernanda, Fernandes, Luyara, Leão, Thiago L., Chamhum-Silva, Lucas, Azevedo, Lariza, Morandi, Thiago, Freitas, Gabriel Tadeu O., Costa, Michelle S., Carvalho, Beatriz O., Reis, Marcus Tulius P., Melo, Marília C., Ayrimoraes, Sergio R., Chernicharo, Carlos A.L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8666095/
https://www.ncbi.nlm.nih.gov/pubmed/34229195
http://dx.doi.org/10.1016/j.watres.2021.117388
Descripción
Sumario:Brazil has become one of the epicentres of the COVID-19 pandemic, with cases heavily concentrated in large cities. Testing data is extremely limited and unreliable, which restricts health authorities’ ability to deal with the pandemic. Given the stark demographic, social and economic heterogeneities within Brazilian cities, it is important to identify hotspots so that the limited resources available can have the greatest impact. This study shows that decentralised monitoring of SARS-CoV-2 RNA in sewage can be used to assess the distribution of COVID-19 prevalence in the city. The methodology developed in this study allowed the identification of hotspots by comprehensively monitoring sewers distributed through Belo Horizonte, Brazil's third largest city. Our results show that the most vulnerable neighbourhoods in the city were the hardest hit by the pandemic, indicating that, for many Brazilians, the situation is much worse than reported by official figures.