Overview of malaria in SSA |
Describes epidemiology of malaria in SSA, burden of malaria, global efforts for control, pre-elimination, and elimination, and various types of interventions. Module updated annually to reflect current data from annual World Malaria Reports |
Provides knowledge of malaria epidemiology, current global targets and new trends and interventions |
Basic concepts of M&E |
Defines programme components, key concepts, and purpose of M&E |
Provides correct understanding of malaria M&E malaria terminology |
Role of data in decision making |
Raises awareness of importance of using data to inform decisions, discussed strategies for overcoming barriers for decision-making, learned strategies for using data in programme management, implementation, and decision-making |
Provides practical explanation of the importance and usefulness of M&E for a malaria programme |
Designing and implementing an M&E plan |
Describes functions and main elements of an M&E plan. Describes the process and implementation of a plan and discusses well-known challenges |
Delivers tools and resources for designing an M&E plan |
Frameworks |
Identifies conceptual, results, and logical frameworks, and logic models. Defines goals and objectives for specific intervention programmes. Designs frameworks and discusses how they are used |
Provides the importance and usefulness of various frameworks |
Indicators |
Discusses design of good quality indicators. Teaches how to critique indicators. Links indicators to frameworks and introduces indicator reference sheets |
Provides the importance of indicators and how they fit in the broad view of malaria M&E |
Data sources and systems |
Identifies various types of data sources, including routine and non-routine sources. Discusses strengths and weaknesses of data sources, linking sources, and recognizing appropriate sources for measuring malaria intervention coverage and impact |
Explains various data sources and their importance and usefulness |
Data quality |
Identifies data quality issues at each step of a data management system. Highlights key criteria used to assess data quality and identifies steps for ensuring data quality at all levels of the data management system. Discusses key elements of a data quality assessment |
Explains the importance of data quality in the improvement of the health information system |
Evaluation designs |
Describes evaluation terminology, causality, internal and external validity. Teaches various types of evaluations and discusses strengths and limitations of study designs. Teaches participants how to develop an evaluation framework and select a study design that fits the purpose of a given evaluation. Includes current examples of evaluations conducted by facilitators |
Offers various evaluation methods and detailed examples of current evaluations |
Data management |
Identifies general rules of data management. Defines roles and responsibilities and utilizes information to implement a system for good data management |
Provides tools for correctly managing a health information system |
Data presentation, interpretation and use |
Discusses different ways to summarize data and choose the best graphic for the audience. Focuses on ensuring graphics are self-explanatory, clear, concise, and attractive, so data is easily interpreted and used |
Teaches practical techniques for presenting, interpreting and using data |