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Modelling spatiotemporal patterns of visceral leishmaniasis incidence in two endemic states in India using environment, bioclimatic and demographic data, 2013-2022.

Swaminathan SubramanianRajendran Uma MaheswariGopalakrishnan PrabavathyMashroor Ahmad KhanBalan BrindhaAdinarayanan SrividyaAshwani KumarManju RahiEmily S NightingaleGraham F MedleyMary M CameronNupur RoyPurushothaman Jambulingam
Published in: PLoS neglected tropical diseases (2024)
The spatiotemporal model incorporating environmental, bioclimatic, and demographic factors demonstrated that the KAMIS database of the national programmme can be used for block level predictions of long-term spatial and temporal trends in VL incidence and risk of outbreak / resurgence in endemic and non-endemic settings. The database integrated with the modelling framework and a dashboard facility can facilitate such analysis and predictions. This could aid the programme to monitor progress of VL elimination at least one-year ahead, assess risk of resurgence or outbreak in post-elimination settings, and implement timely and targeted interventions or preventive measures so that the NKAEP meet the target of achieving elimination by 2030.
Keyphrases
  • risk factors
  • adverse drug
  • physical activity
  • electronic health record
  • quality improvement
  • study protocol
  • cancer therapy
  • randomized controlled trial
  • clinical trial
  • machine learning
  • long term care
  • drug delivery