  We provide a methodology by which an epidemiologist may arrive at an optimal
design for a survey whose goal is to estimate the disease burden in a
population. For serosurveys with a given budget of $C$ rupees, a specified set
of tests with costs, sensitivities, and specificities, we show the existence of
optimal designs in four different contexts, including the well known c-optimal
design. Usefulness of the results are illustrated via numerical examples. Our
results are applicable to a wide range of epidemiological surveys under the
assumptions that the estimate's Fisher-information matrix satisfies a uniform
positive definite criterion.
