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Linking market authorizations of medicines with disease burden in South Africa

BACKGROUND: Sub-Saharan Africa is going through an epidemiological transition, including an impressive increase in non-communicable diseases. The introduction of medicines has not kept pace with the needs in developing countries. The objectives of this study were to (i) examine the correlation betwe...

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Detalles Bibliográficos
Autores principales: Narsai, K., Leufkens, H. G. M., Mantel-Teeuwisse, A. K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8017838/
https://www.ncbi.nlm.nih.gov/pubmed/33795015
http://dx.doi.org/10.1186/s40545-021-00314-x
Descripción
Sumario:BACKGROUND: Sub-Saharan Africa is going through an epidemiological transition, including an impressive increase in non-communicable diseases. The introduction of medicines has not kept pace with the needs in developing countries. The objectives of this study were to (i) examine the correlation between the number of medicine approvals and disease burden and (ii) compare approval timelines of medicines with disease burden in South Africa in the period 2012–2017. METHODS: The dataset was compiled from publicly available data on medicines registered in South Africa between 2012 and 2017. A correlation analysis was conducted to determine the level of alignment between the number and nature of medicines registered, as determined by the WHO ATC Classification and the Lancet Global Burden of Disease data. Median registration timelines were determined to assess whether medicines for diseases of higher burden were registered faster. RESULTS: A total of 3059 registered medicines were included in the study, including 2779 generic medicines, 267 new chemical entities and 13 vaccines. There was a high level of alignment between the number of medicines registered to treat diseases with higher disease burden levels more effectively, except for lower respiratory tract infections and HIV/AIDS which showed less medicines registered as compared to expectations based on disease burden, respectively. HIV/AIDS showed a lower level of correlation with a much higher disease burden compared to number of medicines registered, but simultaneously also a much shorter median registration timeline (32 months) compared to the other disease areas. CONCLUSIONS: There was generally a high level of alignment between disease burden and number of medicines authorised, except for HIV/AIDS and lower respiratory tract infections. Regulatory authorities should continue to consider burden of disease data to ensure that public health needs are met.