deletions | additions       diff --git a/section_Estimation_of_uncertainty_There__.tex b/section_Estimation_of_uncertainty_There__.tex  index 1d8ed6a..ba3d188 100644  --- a/section_Estimation_of_uncertainty_There__.tex  +++ b/section_Estimation_of_uncertainty_There__.tex 
...
There are many potential sources of uncertainty associated with estimates of TB incidence, prevalence and mortality, as well as estimates of the burden of HIV-associated TB and MDR-TB. These include uncertainties in input data, in parameter values, in extrapolations used to impute missing data, and in the models used.   We used fixed population values from the UNPD. We did not account for any uncertainty in these values.   Notification data are of uneven quality. Cases may be underreported under-reported  (for example, missing quarterly reports from remote administrative areas are not uncommon), misclassified (in particular, misclassification of recurrent cases in the category of new cases is common), or overreported over-reported  as a result of duplicated entries in TB information systems. The latter two issues can only be addressed efficiently in countries with case-based nationwide TB databases that include patient identifiers. Sudden changes in notifications over time are often the result of errors or inconsistencies in reporting, but may sometimes reflect abrupt changes in TB epidemiology (for example, resulting from a rapid influx of migrants from countries with a high burden of TB, or from rapid improvement in case-finding efforts). Missing national aggregates of new and recurrent cases were imputed by interpolation. Notification trajectories were smoothed using a penalized cubic splines function with parameters based on the data. Attempts to obtain corrections for historical data are made every year, but only rarely do countries provide appropriate data corrections.