Background Research has shown that traditional medicine and Traditional Health Practitioners (THPs) represent the first line of healthcare for the majority in sub-Saharan Africa (SSA). In this context, understanding traditional beliefs is critical, if we are to design effective health messages and improve health outcomes. The aim of this study was to identify and understand how traditional knowledge and beliefs influence explanatory models of disease and patient actions to avoid risk of HIV and STI infection.

Methods An exploratory qualitative study involving THPs and their patients was conducted in 2011 at five sites in provinces Gauteng and KwaZulu-Natal. THPs (n = 54) were recruited through local forums and patients (n = 48) recruited by their THP. Diviners, herbalists, traditional birth attendants and traditional surgeons were all represented. Data were analysed using NVivo 9.

Results THPs provide a holistic ‘catch all’ service that would involve multiple providers within the allopathic sector. Whilst participants acknowledged allopathic risk factors and modes of transmission, beliefs around aetiology were generally located in the spiritual dimension with infection often blamed on lack of respect for/non-adherence to traditional practises resulting in ‘pollution’ and ‘dirt in the blood’. THPs demonstrated a willingness to refer patients to clinics for diagnosis and treatment, recognised benefits of circumcision, and encouraged patients on ARVs to continue treatment. However, protective and preventive properties of traditional medicines were frequently highlighted.

Conclusion It was clear from this study that for many in South Africa traditional beliefs are often held alongside an acknowledgement of some aspects of germ theory. Given the pervasive traditional belief-based explanatory model of disease, health messaging and interactions that do not acknowledge this are likely to fail. It is critical that the allopathic/western system understands these core beliefs of patients accessing their services so as to optimise health messages, treatments, behaviours and clinical outcomes in SSA.