Impact of the COVID-19 pandemic on dengue in Brazil: interrupted time series analysis of changes in surveillance and transmission (2024)
- Authors:
- USP affiliated authors: RODRIGUES, FRANCISCO APARECIDO - ICMC ; ROSTER, KIRSTIN INGRID OLIVEIRA - ICMC
- Unidade: ICMC
- DOI: 10.1371/journal.pntd.0012726
- Subjects: DENGUE; ANÁLISE DE SÉRIES TEMPORAIS; APRENDIZADO COMPUTACIONAL
- Language: Inglês
- Imprenta:
- Publisher place: San Francisco
- Date published: 2024
- Source:
- Título: PLoS Neglected Tropical Diseases
- ISSN: 1935-2735
- Volume/Número/Paginação/Ano: v. 18, n. 12, p. 1-14, 2024
- Este periódico é de acesso aberto
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: gold
- Licença: cc-by
-
ABNT
ROSTER, Kirstin Oliveira et al. Impact of the COVID-19 pandemic on dengue in Brazil: interrupted time series analysis of changes in surveillance and transmission. PLoS Neglected Tropical Diseases, v. 18, n. 12, p. 1-14, 2024Tradução . . Disponível em: https://doi.org/10.1371/ journal.pntd.0012726. Acesso em: 01 jan. 2026. -
APA
Roster, K. O., Martinell, T., Connaughton, C., Santillana, M., & Rodrigues, F. A. (2024). Impact of the COVID-19 pandemic on dengue in Brazil: interrupted time series analysis of changes in surveillance and transmission. PLoS Neglected Tropical Diseases, 18( 12), 1-14. doi:10.1371/journal.pntd.0012726 -
NLM
Roster KO, Martinell T, Connaughton C, Santillana M, Rodrigues FA. Impact of the COVID-19 pandemic on dengue in Brazil: interrupted time series analysis of changes in surveillance and transmission [Internet]. PLoS Neglected Tropical Diseases. 2024 ; 18( 12): 1-14.[citado 2026 jan. 01 ] Available from: https://doi.org/10.1371/ journal.pntd.0012726 -
Vancouver
Roster KO, Martinell T, Connaughton C, Santillana M, Rodrigues FA. Impact of the COVID-19 pandemic on dengue in Brazil: interrupted time series analysis of changes in surveillance and transmission [Internet]. PLoS Neglected Tropical Diseases. 2024 ; 18( 12): 1-14.[citado 2026 jan. 01 ] Available from: https://doi.org/10.1371/ journal.pntd.0012726 - Machine-learning-based forecasting of dengue fever in Brazilian cities using epidemiologic and meteorological variables
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- Data science for epidemiology: a case study of dengue in Brazil
- Data-rich modeling helps answer increasingly complex questions on variant and disease interactions [Carta]: comment on "Mathematical models for dengue fever epidemiology: A10-year systematic review" by Aguiar et al.
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- Unfolding the complexity of the global value chain: strength and entropy in the single-layer, multiplex, and multi-layer international trade networks
- On degree–degree correlations in multilayer networks
- Synchronization in clustered random networks
- Analysis of cluster explosive synchronization in complex networks
- Explosive synchronization enhanced by time-delayed coupling
Informações sobre o DOI: 10.1371/journal.pntd.0012726 (Fonte: oaDOI API)
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