(If you're looking for the report: Tramadol in Africa - Scarcity and excess of pain medication in a poorly regulated market, please click here. Apologies for the confusion)

In the mid-2000s, West Africa became a major transit hub for heroin and cocaine trafficking, facilitating the emergence of local markets and resulting in an increase in people who use drugs (PWUD). Cannabis, heroin and cocaine, usually inhaled, are the most commonly used drugs in Côte d’Ivoire. Abidjan, the country’s economic capital, has illegal drug consumption areas (known as ‘smoking spots’) in various locations, where drugs are purchased and used. Abidjan’s estimated 6,000 PWUD are known to have specific health issues, particularly tuberculosis.

With 10.4 million new cases and 1.7 million deaths worldwide in 2016, tuberculosis (TB) is still a major public health challenge. It is the leading cause of death from a single infectious agent, ahead of HIV/AIDS. As the incidence of TB declines, the burden of the disease is increasingly borne by urban subpopulations living in harsh conditions, such as PWUD.

The World Health Organization estimated there were 36,000 new cases of tuberculosis in Côte d’Ivoire in 2016, i.e. a prevalence rate of 0.2% among the general population. In 2017, 21,307 cases that included all forms of tuberculosis were reported to the National Tuberculosis Control Programme, i.e. 59% of the total estimated number of cases. Although PWUD are a particularly at-risk group for TB and field experience suggests a high prevalence among this population, there is virtually no data on TB prevalence. The aim of the survey was thus to estimate the prevalence of pulmonary TB among PWUD in Abidjan and assess the cascade of care available to PWUD with confirmed pulmonary tuberculosis (TB+) participating in a community-based support programme.

The two-part survey targeted people over the age of 18 years who had used heroin and/or cocaine/crack in the previous six months, regardless of the method employed. The first part, which covered diagnosis, consisted in a cross-sectional prevalence estimation survey with systematic testing available in mobile units near the smoking spots. The survey was made available to all PWUD present in two smoking spots in Abidjan districts Yopougon and Treichville at the time of its implementation. The second part, which covered treatment, was a prospective survey. Thus, all people who tested positive for pulmonary TB and who agreed to start TB treatment were offered follow-up for the duration of their treatment. They were also invited to participate in a community-based support programme proposing various activities, e.g. family mediation visits, selfhelp groups, personalised follow-up interviews, nutritional and financial support.

On their inclusion in the survey, the following data was collected: a face-to-face socio-behavioural questionnaire, rapid diagnostic tests (RDTs) for HIV, a clinical examination, sputum collection and chest x-rays for pulmonary TB testing. Direct microscopic examination and Xpert MTB/RIF® analyses were performed on sputum. Those who tested positive for Xpert MTB/RIF® were considered to have confirmed pulmonary TB (TB+). If the rifampicin test was positive, individuals were considered to have rifampicin-resistant pulmonary TB (RIF-TB). The questionnaire collected data on: socio-demographic situation, drug use, imprisonment, sexual practices, knowledge of TB, access to TB and HIV testing and care, stigma and discrimination. After a descriptive analysis, TB, RR-TB, TB/HIV co-infection and HIV prevalence were calculated on the basis of the total number of participants for whom test results were available. A multivariate logistic regression was performed to determine the factors associated with TB infection, with adjustments for smoking spots, gender and age. A significance level of 5% was considered for the final multivariate model. In the case of testing algorithms, the algorithm used as reference was systematic testing with Xpert MTB/ RIF®. Only participants with results from all the tests were taken into account in this algorithm analysis. To compare with the reference algorithm, the main indicator was the sensitivity of the algorithm (ability to detect TB+ cases among participants). To evaluate the effectiveness of the treatment, participants were considered at the end of their treatment as having been successfully treated if they were registered as “cured”, “treatment finished” or “treatment completed” in the follow-up booklets provided by the AntiTuberculosis Centre. R software (version 3.4.3) was used to perform the analyses.