An interactive explainer
This explainer examines the relationship between malaria transmission intensity and the age distribution of clinical disease. As transmission intensity increases, clinical cases become more concentrated in young children; as it decreases, cases are distributed more evenly across age groups. The pattern is driven by acquired immunity, which builds with cumulative exposure to infectious bites.1
Across African settings, the share of clinical malaria that falls in under-fives rises with transmission intensity: from below a fifth of cases where transmission is low to above three-fifths where it is high.1 Pooled analyses of age-stratified data show broadly consistent shifts, which also vary by clinical syndrome and season.2 Severe disease and death also become concentrated in the youngest children as transmission increases.3
Exposure accumulates with age and with transmission intensity. Where a child receives hundreds of infectious bites a year, they are infected many times before school age; where they receive only a few, the same exposure is spread over decades. The age by which a person has been infected often enough to become protected therefore depends on the rate at which infectious bites are received.
Immunity to malaria is largely acquired through repeated exposure, apart from limited protection passed from the mother in the first months of life, and it develops in stages. In high-transmission areas people continue to be infected throughout life, but with repeated exposure a progressively smaller fraction of those infections becomes clinical illness.15 Clinical immunity does not prevent infection; it prevents infection from causing symptoms.
In the transmission model used here, the probability that a new infection becomes a clinical case declines as acquired immunity builds, following a saturating (diminishing-returns) function of cumulative exposure. Because the response saturates, early exposure has the largest effect: the first infections lead to the largest reductions in the probability of disease. Under intense transmission, older children and adults are far along this curve and largely protected, so the remaining clinical cases are concentrated in young children, who have accumulated less exposure. (Cumulative exposure also builds a separate immunity that modestly reduces the probability that a bite establishes infection, but it is clinical immunity that drives the shift in which ages develop disease.)
When transmission falls, whether over years of control or between neighbouring areas, the burden that remains shifts into older children and adults, who now acquire immunity more slowly.4 The total number of cases can drop while the average age of a case rises.
The age distribution of cases is not fixed; it is determined by transmission intensity, and this has practical consequences. Interventions aimed at young children (such as seasonal chemoprevention, or the current vaccines delivered in early childhood) capture most of the burden where transmission is high, but a smaller share where it is low; and surveillance that only counts young children will increasingly miss cases as transmission falls.
A toy implementation of the Griffin transmission model at equilibrium
Move the slider from low to intense transmission. The top chart shows the distribution of clinical cases across age; the bar below divides those cases into under-5, 5–15 and 15+. As transmission intensity rises, cases become concentrated in the youngest ages and parasite prevalence (a common, more familiar index of transmission) increases.
Clinical malaria by age — per-person risk, and where the cases fall; each curve scaled to its own peak
Share of clinical cases by age group
The bold line is clinical incidence per person, the risk an individual of each age faces: at low transmission it rises with age and is still climbing at 20; at high transmission it peaks in the first years of life. The shaded area is the share of cases by age, that same risk multiplied by how many people are each age; because young children are the largest group, it peaks young at every intensity. Both curves are scaled to their own peak, so compare shapes, not heights; the bar and readouts carry the actual numbers.
The young-child peak is produced by immunity, not by biting. Infectious bites reach all ages (slightly fewer to the very young, who are smaller). What concentrates clinical cases in young children at high transmission is that older individuals have already acquired protection.
Prevalence saturates; the age shift does not. Move the slider through the high end: parasite prevalence changes little once it is high, but the under-5 share continues to rise. Transmission intensity keeps changing which ages develop disease even after it has stopped changing how many people carry the parasite.
Falling transmission shifts the age burden to older age groups. Move the slider from intense to low and the narrow peak broadens into a distribution reaching into adulthood. Lowering transmission does not only reduce the burden; it shifts it to older age groups, which changes who interventions and surveillance should target. Each slider position is a long-run equilibrium, however: it shows where the age pattern settles, not the path taken to reach it.
Severe disease and death concentrate too. This toy tracks uncomplicated clinical cases, but the same shift onto the youngest children, if anything sharper, is seen for severe malaria and malaria deaths as transmission rises.23
Methods. A deliberately simple, illustrative toy that runs the equilibrium solution of the Griffin model of Plasmodium falciparum transmission15 directly in your browser. Because it is an equilibrium solution, each slider position is the steady state a constant transmission intensity settles into; the toy does not capture the dynamics of a changing intensity, where immunity, and so the age distribution, would take years to catch up. It shows the shape of how the age distribution of disease depends on transmission intensity, not a specific place; not to be used for decision making.
References.