Q2. What are the future works mentioned in the paper "Global and regional mortality from 235 causes of death for 20 age- groups in 1990 and 2010: a systematic analysis" ?
Improved estimation of mortality from HIV/AIDS including uncertainty in the future will come both from continued progress in the estimation of the time course of the HIV epidemic by UNAIDS as well as further data on the levels of adult mortality in some key countries such as Nigeria. These are important both for the prioritization of existing treatments, such as rotavirus or pneumococcal vaccines, but also for the development of future technologies. When large multi-center studies such as GEMS publish their results this will be an important addition to the analysis ; future revisions of the GBD should make use of these results as they become available. The authors believe that for causes where the magnitude of these corrections is comparatively large, future research should be targeted to trying to build a better understanding of the strengths and weaknesses of the various data sources, whether epidemiological or demographic.
Q3. Why do the authors use only information on the fraction of injuries due to specific sub-causes?
Because of known bias in the epidemiological composition of burial and mortuary data, the authors only use information on the fraction of injuries due to specific sub-causes from these sources.
Q4. What could be learned about causes of death in countries where death certification is poor?
Much could be learned about causes of death in countries where death certification is poor through the more widespread testing and application of recent advances in verbal autopsy methods which greatly reduce heterogeneity in diagnostic practices across populations where VA is currently used.
Q5. What causes of death are dominated by by the post-neonatal period?
By the post-neonatal period, causes of death are dominated by diarrhea, LRI, and other infectious diseases such as measles, among others.
Q6. Why are the causes of death assessments subject to debate?
Because of the variety of data sources and their associated biases, cause of death assessments are inherently uncertain and subject to vigorous debate.
Q7. How many countries had to make decisions about data sources, quality adjustments and modeling strategies?
The ambition to estimate mortality from 235 causes with uncertainty for 187 countries over time from 1980 to 2010 means that many choices about data sources, quality adjustments to data and modeling strategies had to be made.
Q8. Why do the authors include more disaggregated causes in the ranking list?
Although the authors report more disaggregated causes, because of considerations related to public health programs, the authors have chosen to include diarrheal diseases, lower respiratory infections, maternal causes, cerebrovascular disease, liver cancer, cirrhosis, drug use, road injury, exposure to mechanical forces, animal contact, homicide, and congenital causes in the ranking list.
Q9. What are the four families of statistical models developed using covariates?
In addition, four families of statistical models are developed using covariates: mixed effects linear models of the log of the death rate, mixed effects linear models of the logit of the cause fraction, spatial-temporal Gaussian process regression (ST-GPR) models of the log of the death rate, and ST-GPR of the logit of the cause fraction.
Q10. How many empirical observations are used to estimate the relationships between under-five and adult mortality?
60–62The relationships between under-five mortality and adult mortality and the disaster and collective violence covariates are estimated using 43 empirical observations for disasters and 206 empirical observations for collective violence (only years with over 1 per 10,000 crude death rate from shocks are kept in this analysis).
Q11. How many causes are too low to generate stable estimates of out-of-sample predictive?
For 13 causes, the number of deaths observed in the database is too low to generate stable estimates of out-of-sample predictive validity.
Q12. What are the opportunities for improving cause of death data?
Opportunities for strengthening death registration, cause of death certification, and the more widespread use of verbal autopsy exist.
Q13. What are the coefficients used to predict excess deaths from these two causes?
The coefficients from these regressions and the disaster and collective violence covariates are used to predict excess deaths from these two causes.
Q14. What are the reasons to be concerned about the bias in the data?
There are reasons, however, to also be concerned that deaths recorded in systems with low coverage may be biased towards selected causes that are more likely to occur in hospital.
Q15. What is the effect of CoDCorrect on the size of more certain causes?
Although at the draw level the same scalar is applied to all causes, the net effect of CoDCorrect is to change the size of more uncertain causes by more than is done for more certain causes, a desirable property.