Tuberculosis death rate is the estimated number of deaths from tuberculosis among HIV-negative people, expressed as the rate per 100,000 population. Estimates for all years are recalculated as new information becomes available and techniques are refined, so they may differ from those published previously.

BACKGROUND: Tuberculosis (TB) has killed more people than any other infection since records began. The Sustainable Development Goals and the World Health Organisation “End TB” Strategy prioritise key targets for reducing mortality due to TB. However, there seems to be limited research evidence available to inform how this target of reducing TB mortality may best be achieved. OBJECTIVES: We aim to describe and categorise the published literature concerning mortality due to TB and then to review, critically appraise and synthesise the evidence that interventions decrease mortality due to TB. METHODS: The Pubmed database will be searched. Screening and selection of eligible publications will be made by 2 independent reviewers and a third will be asked to resolve any discrepancies. Key information from selected publications will be extracted using a shared cloud-based spreadsheet. Quantitative assessments of the impacts of trial interventions on TB mortality will be extracted and synthesised using meta-analysis, if possible. When appropriate, the quality of trial evidence will be assessed.This systematic review and meta-analysis is registered with the PROSPERO database (CRD42023387877). CONCLUSIONS: We will review the current published evidence concerning TB mortality and how it may best be prevented. We aim to clarify research gaps and also to synthesise evidence in order to guide future policy and research.

This is the microdataset used in the paper "SMS nudges as a tool to reduce Tuberculosis treatment delay and pretreatment loss to follow-up. A randomized controlled trial". We fielded two SMS interventions in three Cape Town clinics to see their effects on whether people returned to clinic, and how quickly. One was a simple reminder; the other aimed to overcome “optimism bias” by reminding people TB is curable and many millions die unnecessarily from it. Recruits were randomly assigned at the clinic level to a control group or one of the two SMS groups (1:2:2). In addition to estimating effects on the full sample, we also estimated effects on HIV-positive patients.

Geographic coverage

The survey was conducted in two local communities in the Free State province, one urban (Welkom) and one rural (Qwaqwa), in which the HIV/AIDS epidemic is particularly rife. Welkom and Qwaqwa are situated in the Lejweleputswa and Thabo Mofutsanyane districts of the Free State province.

Analysis unit

Households

Universe

All memebers of the Household

Kind of data

Sample survey data [ssd]

Sampling procedure

The household impact of HIV/AIDS was assessed by means of a cohort study of households affected by the disease. The survey was conducted in two local communities in the Free State province, one urban (Welkom) and one rural (Qwaqwa), in which the HIV/AIDS epidemic is particularly rife. Welkom and Qwaqwa are situated in the Lejweleputswa and Thabo Mofutsanyane districts of the Free State province.

Affected households were sampled purposively via NGOs and other organizations involved in AIDS counselling and care and at baseline included at least one person known to be HIV-positive or known to have died from AIDS in the past six months. Informed consent was obtained from the infected individual(s) or their caregivers (in the case of minors). In order to explore the socio-economic impact on affected households of repeated occurrences of HIV/AIDS-related morbidity or mortality, a distinction is made between affected households in general and affected households that have experienced morbidity or mortality more frequently. Non-affected households represent households living in close proximity to affected households. These households at baseline did not include persons suffering from tuberculosis or pneumonia. The incidence of morbidity and mortality is considerably higher in affected households.

Affected households were sampled purposively via NGOs and other organizations involved in AIDS counselling and care and at baseline included at least one person known to be HIV-positive or known to have died from AIDS in the past six months. Informed consent was obtained from the infected individual(s) or their caregivers (in the case of minors). In order to explore the socio-economic impact on affected households of repeated occurrences of HIV/AIDS-related morbidity or mortality, a distinction is made between affected households in general and affected households that have experienced morbidity or mortality more frequently. Non-affected households represent households living in close proximity to affected households. These households at baseline did not include persons suffering from tuberculosis or pneumonia. The incidence of morbidity and mortality is considerably higher in affected households.

Mode of data collection

Face-to-face [f2f]

Research instrument

Household Questionnaire

Response rate

During the first wave of interviews a total of 404 interviews were conducted. During the second wave of data collection, interviews were conducted with 385 households, which translates into an attrition rate of 4.7% (19 households). During wave III, a total of 354 households were interviewed, with 31 households not being reinterviewed (7.7% of the original sample). In wave IV, 55 new households wererecruited into the study, with particular emphasis on an effort to recruit child-headed households into the survey insofar as the sample to date did not include any such households. During waves IV, V and VI a total of 3, 13 and 9 households respectively could not be re-interviewed.

The payment of a minimal participation fee (R150 per household per survey visit) to those households interviewed in each wave, following the interview and distributed in the form of food parcels, contributed to ensuring sustainability of the sample over the three-year period. The dataset includes data for 331 households interviewed in each of the six rounds of interviews. In almost 90 percent of cases the reasons for attrition are related to migration, given that this study did not intend to follow those households that move outside of the two immediate study areas, i.e. Welkom and Qwaqwa. In the majority of cases, attrition can be ascribed to the failure to establish the current whereabouts of the particular household during follow-up, while in a third of cases it could be established that the household had moved to another country, another province, or another town in the Free State province. Less than ten percent of households had refused to participate in subsequent waves. The reasons for attrition in the original sample illustrate the manner in which migration and the disintegration of households, which are important effects of the epidemic, can act to erode the sample population.