The study evaluates the economic costs and benefits of improving tuber
culosis control interventions in Thailand. Provider costs are determin
ed on the basis of marginal treatment costs for varying case numbers a
nd estimates of the cost of required infrastructure changes. Indirect
costs are calculated as income lost due to morbidity and premature mor
tality. An epidemiological model is used to calculate case numbers and
mortality under current control conditions and a scenario of improved
control. An improved control strategy initially leads to a higher num
ber of detected cases. For longer projection periods, the epidemiologi
cal impact of curing a higher proportion of infectious sources results
in lower case numbers than those expected without programme improveme
nt. Model simulations show a reduction of total annual case numbers th
rough improved control measures by an average 45% after a simulation p
eriod of 20 years. The corresponding societal savings in form of reduc
ed indirect costs from the disease are U.S.$2.4 billion. Reductions in
direct provider costs can be expected as a result of decreased number
s of detected cases for longer evaluation periods, as well as a lower
proportion of multi-drug-resistant cases. The mean value of predicted
savings is U.S.$8.3 million. Since this value is likely to be higher t
han the required investment in improved infrastructure, net savings ca
n be expected. The result of an uncertainty analysis shows a wide rang
e of potential additional costs or net savings with respect to direct
provider costs. Indirect cost calculations show net savings for all pa
rameter values. (C) 1997 Elsevier Science Ltd.