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 |