Forecasting Dengue, Chikungunya and Zika cases in Recife, Brazil: a spatio-temporal approach based on climate conditions, health notifications and machine learning (2021)
- Authors:
- USP affiliated authors: AMBRIZZI, TERCIO - IAG ; MORENO, GISELLE MACHADO MAGALHÃES - IAG ; BORGES, IURI VALERIO GRACIANO - IAG
- Unidade: IAG
- DOI: 10.33448/rsd-v10i12.20804
- Subjects: CLIMA; DENGUE; VÍRUS CHIKUNGUNYA; ZIKA VÍRUS; ARBOVÍRUS; SAÚDE PÚBLICA
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher place: Vargem Grande Paulista
- Date published: 2021
- Source:
- Título: Research, Society and Development
- ISSN: 2525-3409
- Volume/Número/Paginação/Ano: v. 10, n. 12, art. e452101220804, 2021
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
SILVA, Cecilia Cordeiro da et al. Forecasting Dengue, Chikungunya and Zika cases in Recife, Brazil: a spatio-temporal approach based on climate conditions, health notifications and machine learning. Research, Society and Development, v. 10, n. 12, 2021Tradução . . Disponível em: https://doi.org/10.33448/rsd-v10i12.20804. Acesso em: 24 jan. 2026. -
APA
Silva, C. C. da, Moreno, G. M. M., Dutra, L., Ambrizzi, T., & Borges, I. V. G. B. (2021). Forecasting Dengue, Chikungunya and Zika cases in Recife, Brazil: a spatio-temporal approach based on climate conditions, health notifications and machine learning. Research, Society and Development, 10( 12). doi:10.33448/rsd-v10i12.20804 -
NLM
Silva CC da, Moreno GMM, Dutra L, Ambrizzi T, Borges IVGB. Forecasting Dengue, Chikungunya and Zika cases in Recife, Brazil: a spatio-temporal approach based on climate conditions, health notifications and machine learning [Internet]. Research, Society and Development. 2021 ; 10( 12):[citado 2026 jan. 24 ] Available from: https://doi.org/10.33448/rsd-v10i12.20804 -
Vancouver
Silva CC da, Moreno GMM, Dutra L, Ambrizzi T, Borges IVGB. Forecasting Dengue, Chikungunya and Zika cases in Recife, Brazil: a spatio-temporal approach based on climate conditions, health notifications and machine learning [Internet]. Research, Society and Development. 2021 ; 10( 12):[citado 2026 jan. 24 ] Available from: https://doi.org/10.33448/rsd-v10i12.20804 - A review exploring the overarching burden of Zika virus with emphasis on epidemiological case studies from Brazil
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Informações sobre o DOI: 10.33448/rsd-v10i12.20804 (Fonte: oaDOI API)
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