Spatial variation in delayed diagnosis of visceral leishmaniasis in Bihar, India

BackgroundVisceral leishmaniasis (VL) is a debilitating disease and without treatment, a fatal disease which burdens the most impoverished communities in northeastern India. Control and ultimately, elimination of VL depends heavily on prompt case detection. However, a proportion of VL cases remain undiagnosed many months after symptom onset. Delay to diagnosis increases the chance of onward transmission, and poses a risk of resurgence in populations with waning immunity. We checked the spatial variation of delayed diagnosis of VL in Bihar, India and aimed to understand the potential driving factors of delayed diagnosis. MethodsThe spatial distribution of diagnostic delays was explored using a Bayesian model fit to geo-located cases using the Integrated Nested Laplace Approximation (INLA) approach, assuming days of delay as Poisson-distributed and adjusting for individual-(age, sex, HIV) and local-level (recent incidence, vector control, health facility access) characteristics. Residual variance was modelled with an explicit spatial structure. Cumulative delays were estimated under different scenarios of active case detection coverage. FindingsThe 4,270 cases analysed were prone to excessive delays outside existing endemic "hot spots", beyond the focus of interventions. Cases diagnosed within recently-affected blocks and villages experienced shorter delays on average (by 13% 95% Credible Interval [2.9% - 21.7%] and 7% [1.3% - 13.1%], respectively) than those in non-recently-affected areas. InterpretationDelays to VL diagnosis when incidence is low could influence whether transmission of the disease could be interrupted or resurges. Prioritising and narrowing surveillance to high-burden areas may increase the likelihood of excessive delays in diagnosis in peripheral areas. Active surveillance driven by observed incidence may lead to missing the risk posed by as-yet-undiagnosed cases in low-endemic areas, and such surveillance could be insufficient for achieving and sustaining elimination. FundingThe Bill and Melinda Gates Foundation.