How We Count Impact Honestly: Footfall Versus People Screened

There is a temptation in this field that is worth naming out loud: to make the impact numbers as big as they can plausibly be made. Bigger numbers win grants, attract partners, and look better on a slide. We have decided to be deliberately, almost annoyingly, careful about ours — and this post explains why, using a distinction we hold to strictly.

Two very different numbers

A diagnostic centre and its camps see a lot of people. Hundreds pass through on a busy day across our sites for all sorts of reasons — a blood test, a consultation, accompanying a family member, a routine visit. That total, the footfall, is a real and meaningful operational figure. It tells you about reach and activity.

It is not the same as the number of people we can say we screened with our validated tool. That is a smaller, more specific number: the people who actually received the SamaClip screen and, where relevant, had it confirmed. In our validation study, that defensible number is 175 — the adults who completed the full multi-parameter screening and the reference measurements alongside it.

It would be easy, and wrong, to blur these together. To take the daily footfall, multiply it across sites and days, and present a huge "people impacted" figure. The number would be technically derived from something real and still be misleading, because most of those people did not receive the thing we are claiming credit for.

Why we keep them separate

We keep footfall and screened-count strictly apart for a simple reason: they answer different questions, and conflating them turns an honest figure into an inflated one.

When we talk about validated screening impact, we cite the 175. When we talk about operational reach and the population our model touches, we describe footfall and catchment as exactly that — operational metrics, clearly labelled, not dressed up as screening outcomes. The 700,000-plus people in our catchment is a description of the population within reach, not a claim that we have screened them. We say which is which, every time.

Why honesty here is self-interested, not just virtuous

There is a principled reason for this and a practical one.

The principled reason is obvious: claiming impact you did not deliver is a lie, even when it is assembled from true ingredients. People make decisions based on these numbers — funders, partners, the communities themselves. Inflating them corrupts those decisions.

The practical reason is that inflated numbers do not survive scrutiny. Any serious evaluator — a health expert panel, a careful funder, an audit — will pull a big impact claim apart and ask what is actually behind it. If the honest answer is "footfall multiplied optimistically," the whole application loses credibility, and the genuinely strong parts go down with it. A defensible 175, clearly explained, is worth more than an impressive number that collapses the moment someone leans on it.

The standard we hold

So our rule is plain. Validated screening impact is reported as the screened, confirmed count. Operational reach is reported as operational reach, labelled as such. We do not let one borrow the other's clothes. As the screened numbers grow with deployment — and they will — we will report the larger figure honestly, because it will be genuinely earned, not manufactured. Until then, the smaller true number is the one we stand on. It holds weight precisely because it is true.