Skip to main content

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

 OwnershipThe modelling should be led by the Ministry of Health through the NMCP while including all other key stakeholdersCoordination of partners and activities centred around country needs and country-specific questions
 Aim & purposeThe aim of the modelling application should be clear to all stakeholders involved with defined deliverablesEstablishment of transparent and shared expectations of modelling output and impact
 Data sharing & accessibilityRelevant data from local research or governmental institutions should be made available to programme managers and modelling teamReinforcement of country-ownership and enhanced use of data
 Data quantity & qualityData quality and suitability to inform the models need to be assessed, and if necessary, proper adjustments should be made, in consultation with the programmeImprovement of model accuracy and usefulness of predictions
 TimelinessTimelines need to be set by the programme and need to be sufficient for completion of programmatic as well as modelling tasksFeasibility of timely deliverables for a successful and efficient strategic planning process
 ConsistencyA systematic workflow should be developed and consistently be used throughout the projectReproducibility of modelling results facilitates potential evaluation of applied modelling
 IntegrationThe outputs from programme activities should feed into the modelling process, which in turn should inform the next programmatic activityUtilization of modelling results by the programme and prevention of unnecessary additional modelling iterations
 MonitoringThe modelling outputs should be compared to the parallel activities at the NMCPUsefulness of modelling targeted to relevant and current country needs in consideration of latest available data
 Dissemination &  DiscussionModelling process and results should be presented to relevant stakeholders and at the end, final reports and documentation should be made availableProvision of a discussion platform for exchange and knowledge transfer between partners, essential for impactful application of modelling
 Engagement, commitment & responsibilityAll parties involved should actively participate in the discussions and maintain constant commitmentOpportunity of achieving highest benefit for all partners involved
 UnderstandingKnowledge transfer (in all directions), and capacity building should be a fixed part of the modellingGrowths of mutual understanding and capacity despite substantial differences in disciplines and technical level between stakeholders
 TransparencyThe strengths and limitations of modelling need to be transparentConsideration of modelling as a thinking tool with sensible interpretation of results
 Parameterization & calibrationAvailable data should be used to identify and inform setting specific model parameter and the calibration methodology should account for the historical trends in malariaSimulation of data-driven impact predictions specific to local settings
 ValidationThe predictions need to be compared with data not included in the modelling, especially when developing or using new models and parameterizationsAlignment between modelled and observed data earns credibility, whereas discrepancies can be helpful for the identification of knowledge gaps or model improvements
 ComplexityThe 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
 FlexibilityThe modelling workflow needs to be flexible enough to be able to respond to current country needs and questions as they come upPrevention of unnecessary modelling iterations and strengthening the potential of modelling as a routine tool integrated into strategic planning processes