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Table 2 Challenges and their potential implications for a productive interaction between modelling teams and NMCP staff

From: Applied mathematical modelling to inform national malaria policies, strategies and operations in Tanzania

ChallengesImplications
No previous experience with country modelling at that level of detail, hence need to create process
Short timelines especially by external donors
Insufficient time of NMCP staff for required activities
Delays by NMCP in data sharing
Delays by modellers in getting a clear understanding of the available data in order to increase accuracy of model parameters based on the available data
Use of a complex transmission model and long processing time of simulations
Need for NMCP to invest required time in interactions—depending critical on NMCP understanding value of modelling and the process of interactions
Prolonged time for model set up and calibration
Delays in modelling deliverables and missed opportunities to inform key decisions
Additional resources needed to extend the project period in order to adequately improve technical aspect and standardize processes to provide timely deliverables
Low spatial resolution for most indicators and temporal data gaps
Use of most of the available data to inform the model while reducing the number of assumptions made
Inclusion of model complexities and uncertainties while simplifying the model to shorten simulation time
Increased uncertainty in model parameters and predictions and impossibility to use model predictions at a higher resolution
Undermining of model usefulness and credibility and potential reluctance towards future modelling applications
Maintaining communication between in-country visits between modelling team and NMCP
Need to use a simplified language without leaving out relevant technical details
Transparency on model limitations and uncertainty without undermining perceived modelling value
Negative perception towards modelling by some stakeholders
Misunderstanding the role of modelling as a replacement instead of an addition to data
Loss of interest in modelling process that could potentially lead to a negative perception of its use.
Constant need to highlight the practical contribution made by models and the process of interaction with NMCP
Conflicting deadlines for activities at the NMCP level
Difficulty to find in-country personnel to train for taking over the methodology
Project funding with a focus on short term deliverables rather than long-term support
Dependency on external modeller and temporary project funds that prevent sustained effort and gains of the initiative
Missed opportunity for improvements and refinements to shape the model into a truly setting specific tool and use of its maximum potential