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Table 3 Key components for successful modelling use in strategic planning at country level

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

Component

Recommendation

Relevance

Context

 Ownership

The modelling should be led by the Ministry of Health through the NMCP while including all other key stakeholders

Coordination of partners and activities centred around country needs and country-specific questions

 Aim & purpose

The aim of the modelling application should be clear to all stakeholders involved with defined deliverables

Establishment of transparent and shared expectations of modelling output and impact

 Data sharing & accessibility

Relevant data from local research or governmental institutions should be made available to programme managers and modelling team

Reinforcement of country-ownership and enhanced use of data

 Data quantity & quality

Data quality and suitability to inform the models need to be assessed, and if necessary, proper adjustments should be made, in consultation with the programme

Improvement of model accuracy and usefulness of predictions

Process

 Timeliness

Timelines need to be set by the programme and need to be sufficient for completion of programmatic as well as modelling tasks

Feasibility of timely deliverables for a successful and efficient strategic planning process

 Consistency

A systematic workflow should be developed and consistently be used throughout the project

Reproducibility of modelling results facilitates potential evaluation of applied modelling

 Integration

The outputs from programme activities should feed into the modelling process, which in turn should inform the next programmatic activity

Utilization of modelling results by the programme and prevention of unnecessary additional modelling iterations

 Monitoring

The modelling outputs should be compared to the parallel activities at the NMCP

Usefulness of modelling targeted to relevant and current country needs in consideration of latest available data

Communication

  

 Dissemination &  Discussion

Modelling process and results should be presented to relevant stakeholders and at the end, final reports and documentation should be made available

Provision of a discussion platform for exchange and knowledge transfer between partners, essential for impactful application of modelling

 Engagement, commitment & responsibility

All parties involved should actively participate in the discussions and maintain constant commitment

Opportunity of achieving highest benefit for all partners involved

 Understanding

Knowledge transfer (in all directions), and capacity building should be a fixed part of the modelling

Growths of mutual understanding and capacity despite substantial differences in disciplines and technical level between stakeholders

 Transparency

The strengths and limitations of modelling need to be transparent

Consideration of modelling as a thinking tool with sensible interpretation of results

Modelling

  

 Parameterization & calibration

Available data should be used to identify and inform setting specific model parameter and the calibration methodology should account for the historical trends in malaria

Simulation of data-driven impact predictions specific to local settings

 Validation

The predictions need to be compared with data not included in the modelling, especially when developing or using new models and parameterizations

Alignment between modelled and observed data earns credibility, whereas discrepancies can be helpful for the identification of knowledge gaps or model improvements

 Complexity

The model complexity should be appropriate for the questions asked (“as complex as necessary but as simple as possible”)

Reduction of computational efforts and simplified interpretation of modelling results

 Flexibility

The modelling workflow needs to be flexible enough to be able to respond to current country needs and questions as they come up

Prevention of unnecessary modelling iterations and strengthening the potential of modelling as a routine tool integrated into strategic planning processes