Identifying the determinants of tuberculosis control in resource-poor countries: insights from a qualitative study in The Gambia

Trans R Soc Trop Med Hyg. 2003 Sep-Oct;97(5):506-10. doi: 10.1016/s0035-9203(03)80007-x.

Abstract

Despite the availability of effective treatment, tuberculosis (TB) remains a major cause of death from an infectious disease in the world, particularly in resource-poor countries. Among the chief reasons for this are deficiencies in case tracing and in adherence to treatment. In order to investigate the contribution of non-biological factors to these deficiencies, we carried out a qualitative study in The Gambia, West Africa, from October 2000 to March 2001. The methods used were focus group discussions, interviews, participant and non-participant observation, and case histories. Four domains were distinctively investigated: the TB patients, the community, the health care providers (including programme staff), and the donors and policy makers. Analysis of the data from all these sources indicated the contribution of a wide range of socio-anthropological factors which influence the success or otherwise of the TB control programme in The Gambia, i.e. gender, urban/rural residence, recourse to traditional healers, adherence to national health policies, knowledge about TB, migration, and socio-economic factors. It is concluded that all these factors must be taken into account in formulating interventions to improve detection of TB cases and patient adherence to treatment within the framework of the national TB control programmes, and proposals have been made for targeted interventions.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Allied Health Personnel / statistics & numerical data
  • Attitude to Health
  • Delivery of Health Care / standards
  • Developing Countries*
  • Emigration and Immigration / statistics & numerical data
  • Female
  • Gambia
  • Health Knowledge, Attitudes, Practice
  • Humans
  • Male
  • Patient Acceptance of Health Care / statistics & numerical data*
  • Patient Compliance / statistics & numerical data*
  • Poverty Areas
  • Residence Characteristics
  • Rural Health
  • Sex Distribution
  • Tuberculosis / prevention & control*
  • Urban Health