The relevance of digital health strategies to support tuberculosis services in the COVID-19 pandemic context
Downloads
References
WHO (2020) Global Tuberculosis Report 2020
Sousa GJB, Garces TS, Pereira MLD, Moreira TMM, da Silveira GM (2019) Temporal pattern of tuberculosis cure, mortality, and treatment abandonment in Brazilian capitals. Rev Lat Am Enfermagem 27: . https://doi.org/10.1590/1518-8345.3019.3218
World Health Organization (2020) Tuberculosis and COVID-19: Considerations for tuberculosis care. World Heal Organ 1–11
Stop TB partnership (2020) The Potential Impact of the Covid-19 Response on Tuberculosis in High-Burden Countries: a Modelling Analysis. Dev by Stop TB Partnersh Collab with Imp Coll Avenir Heal Johns Hopkins Univ USAID 1–7
World Health Organization (2015) Digital health for the End TB strategy?: Progress since 2015 and future perspectives. 1–33
World Health Organization (2015) Digital Health for the End Tb Strategy: an Agenda for Action. Who 24
Albano dos Santos LR, Andrade Bernardi F, Prado GCS, Costa Lima V, Crepaldi NY, Marçal MA, Rijo RPCL, Galliez RM, Ruffino-Netto A, Alves D (2019) The perception of health providers about an artificial intelligence applied to Tuberculosis video-based treatment in Brazil: a protocol proposal. Procedia Comput Sci 164:595–601 . https://doi.org/10.1016/j.procs.2019.12.225
Crepaldi NY, Costa Lima V, Andrade Bernardi F, Albano dos Santos LR, Yamaguti VH, Pellison FC, Michelin Sanches TL, Miyoshi NSB, Ruffino Netto A, Rijo RPCL, Alves D (2019) SISTB: an ecosystem for monitoring TB. Procedia Comput Sci 164:587–594 . https://doi.org/10.1016/j.procs.2019.12.224
Pellison FC, Rijo RPCL, Lima VC, Crepaldi NY, Bernardi FA, Galliez RM, Kritski AL, Abhishek K, Alves D (2020) Data Integration in the Brazilian Public Health System for Tuberculosis: Use of the Semantic Web to Establish Interoperability. JMIR Med Informatics 8: . https://doi.org/10.2196/17176
Hokino Yamaguti V, Alves D, Charters Lopes Rijo RP, Brandão Miyoshi NS, Ruffino-Netto A (2020) Development of CART model for prediction of tuberculosis treatment loss to follow up in the state of São Paulo, Brazil: A case–control study. Int J Med Inform 141: . https://doi.org/10.1016/j.ijmedinf.2020.104198
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2021 Journal of Multiprofessional Health Research

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
This work is licensed under a Creative Commons License - Attribution-NonCommercial-NoDerivatives 4.0 International.