Evaluating the plausibility of the method of using both the civil registration and census data in estimating adult mortality at district level in South Africa, circa 2011

The challenge in estimating mortality, both at national and sub-national levels, in developing countries such as South Africa is that neither of the death data sources (vital registration and census) are one hundred percent complete, that is, vital registration data is prone to incompleteness and deaths reported by household are subject to over- or under-reporting which may vary by age. Also, apart from issues with data sources, there is no method that estimates mortality accurately at subnational level and the methods for estimating the level of completeness of reporting of deaths cannot be applied at subnational level (due to issues with migration). Thus, measuring mortality rates at subnational level is a challenge. This research seeks to employ a method used by Dorrington, Moultrie and Timæus (2004) that makes use of both data sources in combination so as to overcome the weakness and makes use of the strength of each data source. To estimate the level of completeness in the year prior to the 2011 Census (to correct the number of deaths registered), first, the Death Distribution Methods (Synthetic Extinct Generations +delta and General Growth Balance method) are used to estimate the level of completeness of the vital registration deaths for the intercensal period 2001-2011 by population group. Thereafter, the level of completeness for each of the years in the intercensal period is estimated by fitting a logistic curve to the level of completeness for the intercensal period of 1996-2001 and 2001-2011 (derived by both Chinogurei (2017) and Richman (2017)). Thus, the number of deaths registered in the year prior to the 2011 census are then corrected for either under- or over-reporting using the estimates of completeness to obtain the true number of deaths by population group and age group for each sex. The corrected true numbers of registered deaths are then used to determine the age-specific correction factors by population group for correcting the household reported deaths at district level and thereafter estimates of mortality at district level are determined. Comparison of estimates derived in this study to estimates by other studies indicated that the method produces plausible estimates at district level, thus, findings in this research strengthens the reasonability of the method

Screening for post-TB lung disease at TB treatment completion: Are symptoms sufficient?

Pulmonary TB survivors face a high burden of post-TB lung disease (PTLD) after TB treatment completion. In this secondary data analysis we investigate the performance of parameters measured at TB treatment completion in predicting morbidity over the subsequent year, to inform programmatic approaches to PTLD screening in low-resource settings. Cohort data from urban Blantyre, Malawi were used to construct regression models for five morbidity outcomes (chronic respiratory symptoms or functional limitation, ongoing health seeking, spirometry decline, self-reported financial impact of TB disease, and death) in the year after PTB treatment, using three modelling approaches: logistic regression; penalised regression with pre-selected predictors; elastic net penalised regression using the full parent dataset. Predictors included demographic, clinical, symptom, spirometry and chest x-ray variables. The predictive performance of models were examined using the area under the receiver-operator curve (ROC AUC) values. Key predictors were identified, and their positive and negative predictive values (NPV) determined. The presence of respiratory symptoms at TB treatment completion was the strongest predictor of morbidity outcomes. TB survivors reporting breathlessness had higher odds of spirometry decline (aOR 20.5, 95%CI:3–199.1), health seeking (aOR 10.2, 2.4–50), and symptoms or functional limitation at 1-year (aOR 16.7, 3.3–133.4). Those reporting activity limitation were more likely to report symptoms or functional limitation at 1-year (aOR 4.2, 1.8–10.3), or severe financial impact of TB disease (aOR2.3, 1.0–5.0). Models were not significantly improved by including spirometry or imaging parameters. ROC AUCs were between 0.65–0.77 for the morbidity outcomes. Activity limitation at treatment completion had a NPV value of 78–98% for adverse outcomes. Our data suggest that whilst challenging to predict the development of post-TB morbidity, the use of symptom screening tools at TB treatment completion to prioritise post-TB care should be explored. We identified little benefit from the additional use of spirometry or CXR imaging