Loading…
Challenges of using modelling evidence in the visceral leishmaniasis elimination programme in India
As India comes closer to the elimination of visceral leishmaniasis (VL) as a public health problem, surveillance efforts and elimination targets must be continuously revised and strengthened. Mathematical modelling is a compelling research discipline for informing policy and programme design in its...
Saved in:
Published in: | PLOS global public health 2022, Vol.2 (11), p.e0001049 |
---|---|
Main Authors: | , , , , |
Format: | Article |
Language: | English |
Citations: | Items that this one cites |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Summary: | As India comes closer to the elimination of visceral leishmaniasis (VL) as a public health problem, surveillance efforts and elimination targets must be continuously revised and strengthened. Mathematical modelling is a compelling research discipline for informing policy and programme design in its capacity to project incidence across space and time, the likelihood of achieving benchmarks, and the impact of different interventions. To gauge the extent to which modelling informs policy in India, this qualitative analysis explores how and whether policy makers understand, value, and reference recently produced VL modelling research. Sixteen semi-structured interviews were carried out with both users- and producers- of VL modelling research, guided by a knowledge utilisation framework grounded in knowledge translation theory. Participants reported that barriers to knowledge utilisation include 1) scepticism that models accurately reflect transmission dynamics, 2) failure of modellers to apply their analyses to specific programme operations, and 3) lack of accountability in the process of translating knowledge to policy. Political trust and support are needed to translate knowledge into programme activities, and employment of a communication intermediary may be a necessary approach to improve this process. |
---|---|
ISSN: | 2767-3375 2767-3375 |
DOI: | 10.1371/journal.pgph.0001049 |