01576nas a2200277   4500000000100000008004100001653001400042653001600056653002600072653001100098653002200109100001300131700001200144700001200156700002100168700001500189700001800204700001200222700001700234245005800251856006500309300001400374490000700388520088900395022001401284       2018                            d10adiagnosis10aElimination10aMathematical modeling10aPolicy10aKeywords: leprosy1 aMedley G1 aBlok DJ1 aCrump R1 aHollingsworth DT1 aGalvani AP1 aNdeffo-Mbah M1 aPorco T1 aRichardus JH00aPolicy lessons from quantitative modeling of leprosy.  uhttps://academic.oup.com/cid/article/66/suppl_4/S281/5020606  aS281-S2850 v663 a<p>Recent mathematical and statistical modeling of leprosy incidence data provides estimates of the current undiagnosed population and projections of diagnosed cases, as well as ongoing transmission. Furthermore, modeling studies have been used to evaluate the effectiveness of proposed intervention strategies, such as postleprosy exposure prophylaxis and novel diagnostics, relative to current approaches. Such modeling studies have revealed both a slow decline of new cases and a substantial pool of undiagnosed infections. These findings highlight the need for active case detection, particularly targeting leprosy foci, as well as for continued research into innovative accurate, rapid, and cost-effective diagnostics. As leprosy incidence continues to decline, targeted active case detection primarily in foci and connected areas will likely become increasingly important.</p>
  a1537-6591