Reach measures the breadth and inclusivity of a programme’s connection with people; both those directly served and those who benefit indirectly through strengthened systems or awareness. A robust reach plan defines the target population, explains why it matters, and quantifies how many individuals or institutions will be connected to services.

This includes both direct beneficiaries (e.g., patients screened or treated) and indirect beneficiaries (e.g., health workers trained, policies influenced).

Strong reach indicators include coverage rate among eligible populations, equity disaggregation (gender, rural/urban, socio-economic status), and institutional reach (percentage of facilities participating). Applicants should also describe data verification methods and reporting frequency.

Quality assurance for reach data is essential; numbers should come from verifiable registries, not estimates.

Impact reflects measurable improvements in individual or population health outcomes. It links what the programme does to the actual change experienced by people. We define specific, time-bound, and measurable outcomes, supported by a credible monitoring plan. Examples include reduction in disease prevalence, improved treatment adherence, or increased survival after a defined period.

Impact indicators may include reductions in complications, control rates for chronic diseases, increased early diagnosis, or improved patient satisfaction.

Projects always establish a baseline before implementation and provide a plan for follow-up measurement. Where long-term outcomes exceed the project horizon, surrogate indicators may be used with clear justification.

Public Health Impact measures the projected long-term effect of the intervention on survival, morbidity reduction, and public-health benefit.

We estimate and measure health gains such as life-years saved or DALYs averted based on evidence or validated models. This approach helps translate achievements into a public-health perspective.

To quantify life-years saved, we may use existing epidemiological data or established WHO/World Bank models. Assumptions must be transparent, and the causal pathway from activity to population impact should be clear.

Examples of relevant metrics include estimated DALYs averted per 1,000 beneficiaries or mortality reduction among high-risk groups.

Health-Economics assesses whether the intervention delivers value for money by achieving strong outcomes with efficient use of resources. Calculations include expected costs, resource requirements, and efficiency mechanisms. Cost transparency is a prerequisite for sustainability.

Key indicators may include cost per person screened or treated, incremental cost-effectiveness ratios (ICER), or budget impact analyses. Cost savings are achieved through process optimization, prevention of advanced disease, or digital efficiencies.

Economic evaluation helps policymakers assess feasibility for long-term integration into public financing.

System Integration examines how a project aligns with and strengthens existing health systems.

Integration ensures continuity, data visibility, and national ownership. Applicants must describe interoperability with government platforms, use of digital identifiers, and compliance with data regulations.

Strong integration plans can include training local staff in data management, ensuring that systems feed into national reporting platforms, and maintaining privacy protections aligned with GDPR or local equivalents. Typical indicators include the proportion of facilities linked to national systems, percentage of patients tracked longitudinally, and data completeness rates.