A spatio-temporal approach to short-term prediction of visceral leishmaniasis diagnoses in India.

ABSTRACT:

Background

The elimination programme for visceral leishmaniasis (VL) in India has seen great progress, with total cases decreasing by over 80% since 2010 and many blocks now reporting zero cases from year to year. Prompt diagnosis and treatment is critical to continue progress and avoid epidemics in the increasingly susceptible population. Short-term forecasts could be used to highlight anomalies in incidence and support health service logistics. The model which best fits the data is not necessarily most useful for prediction, yet little empirical work has been done to investigate the balance between fit and predictive performance.

Methodology/principal findings

We developed statistical models of monthly VL case counts at block level. By evaluating a set of randomly-generate

SUBMITTER: Nightingale ES 

PROVIDER: S-EPMC7373294 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature