Malaria Model Reveals Only Combined Nets and Drugs Can Halt Transmission in Nigerian Children

Malaria continues to exact a devastating toll on young children in Nigeria, and nowhere is that burden more pronounced than in the humid, riverine communities of Rivers State in the Niger Delta. A new modelling study published in BMC Public Health has quantified just how far the state remains from interrupting transmission among children under five, and what it would actually take to cross that critical threshold. By building a mathematical model calibrated to real survey data, researchers at the University of Port Harcourt have shown that the current mix of insecticide-treated nets and antimalarial drugs, while valuable, cuts the burden roughly in half yet still leaves the epidemic smouldering. Only a coordinated scale-up of both interventions, they find, can push transmission below the level needed for elimination.

The research team, led by Chisom Chimbundum Adim of the Africa Center of Excellence for Public Health and Toxicological Research, together with Aminanyanaba Onari Asimiea and Ugochi Adaku Okengwu, constructed a deterministic compartmental model of the SEIR-SEI type. In this framework, human hosts move through susceptible, exposed, infectious and recovered states, while mosquito vectors pass through susceptible, exposed and infectious stages. This dual structure captures the essential biology of malaria: the parasite must complete incubation in both a human and an Anopheles mosquito before transmission can continue, and the model tracks those coupled populations simultaneously over time.

Biological parameters governing mosquito longevity, biting behaviour, parasite development rates and recovery times were drawn from the published literature. Crucially, the team anchored their model to reality by calibrating transmission intensity against parasite prevalence among under-five children reported for the study area in the 2021 Nigeria Malaria Indicator Survey. All data cleaning and analysis were performed in the R programming environment, and because the study relied on secondary, anonymised information, the Ethics Research Committee of the University of Port Harcourt approved the work without requiring individual patient consent.

The centrepiece of the analysis is the effective reproduction number, a quantity epidemiologists use to gauge whether an outbreak is growing or shrinking. Derived here using the next-generation-matrix method, the reproduction number represents the average number of secondary infections generated by a single infectious individual in a population where some control measures are already in place. When this number exceeds one, each infection sparks more than one new infection and transmission persists; when it falls below one, the epidemic chain gradually breaks apart.

Under current intervention coverage in Rivers State, the model estimated an effective reproduction number of approximately 2.6, well above the elimination threshold. In other words, even with insecticide-treated nets and artemisinin-based combination therapy deployed at existing levels, every childhood malaria infection is still generating more than two subsequent infections on average. The counterfactual scenario is even starker: without any interventions at all, the reproduction number would climb to roughly 8.5, meaning current programmes are already preventing an enormous volume of transmission, just not enough to turn the tide.

To understand which levers matter most, the researchers performed a sensitivity analysis, systematically varying each model parameter and measuring its influence on transmission. The results were instructive. The mosquito biting rate exerted the strongest positive influence, adding about 1.0 to the reproduction number, followed by the transmission probabilities and the vector-to-host ratio, each contributing roughly 0.5. On the protective side, insecticide-treated-net coverage emerged as the single most powerful brake, subtracting about 1.08, with ITN-induced mosquito mortality and natural mosquito mortality contributing further reductions of 0.42 and 0.35 respectively. The message is clear: anything that reduces how often mosquitoes bite humans, or how long mosquitoes live, delivers outsized epidemiological returns.

Scenario analysis then translated these insights into projections for control policy. At present coverage levels, the combined effect of nets and treatment roughly halves the endemic infection prevalence among under-fives, from an estimated 15.8 percent in the absence of control to about 7.5 percent. That is a substantial public health gain, translating into fewer clinical episodes, fewer hospital admissions and fewer deaths among a group whose immature immune systems leave them uniquely vulnerable to severe malaria. Yet the model shows this gain is epidemiologically fragile: with the reproduction number still near 2.6, prevalence rebounds quickly whenever coverage slips.

The pivotal finding concerns what happens when both interventions are scaled up together. The model projects that raising insecticide-treated-net use to at least 80 percent coverage, combined with expanded effective treatment using artemisinin-based combination therapies, drives the reproduction number down to approximately 0.8, below the critical value of one. At that level, each infection generates fewer than one secondary case, and transmission chains begin to collapse, projecting genuine interruption of malaria transmission in the study population. Importantly, neither intervention alone at currently attainable coverage could achieve this; the synergy arises because nets suppress the vector population and biting rate while effective therapy shortens how long infected children remain infectious, attacking the transmission cycle from both directions simultaneously.

These results carry direct implications for malaria control strategy in Rivers State and, by extension, other highly endemic settings in Nigeria. Rather than pursuing nets and drugs as parallel, independently managed programmes, the findings argue for integrated planning in which coverage targets are set jointly and progress is monitored against the reproduction number rather than prevalence alone. The sensitivity analysis offers a practical prioritisation: investments that push net coverage toward and beyond the 80 percent mark, sustain the insecticidal effect that raises mosquito mortality, and ensure that suspected cases receive prompt, effective artemisinin-based therapy will yield the greatest epidemiological payoff. Conversely, complacency about biting-rate drivers, such as unresolved breeding sites and gaps in vector suppression, risks undermining gains made elsewhere.

The study also demonstrates the value of data-driven modelling as a decision-support tool for public health authorities working with limited resources. By calibrating a mechanistic model to national survey data and then testing intervention scenarios computationally, the researchers could compare futures that would be impossible to test experimentally in the field, estimating in advance which combinations of coverage levels are likely to achieve elimination and which will merely blunt the epidemic. As Nigeria pursues its national malaria elimination ambitions, work of this kind suggests that the path forward in Rivers State runs not through any single silver bullet, but through the disciplined, simultaneous scale-up of the two interventions already in the toolbox, guided by models that can tell programme managers precisely how close they are to the tipping point.

Subject of Research: Mathematical modelling of malaria transmission dynamics and intervention strategies in children under five in Rivers State, Nigeria

Article Title: Data-driven modelling of malaria transmission among under-five children to inform targeted control strategies in Rivers State, Nigeria

Article References: Adim, C. C., Asimiea, A. O., & Okengwu, U. A. (2026). Data-driven modelling of malaria transmission among under-five children to inform targeted control strategies in Rivers State, Nigeria. BMC Public Health. https://doi.org/10.1186/s12889-026-29781-0

Image Credits: AI Generated

DOI: 10.1186/s12889-026-29781-0

Keywords: malaria, mathematical modelling, SEIR-SEI model, effective reproduction number, insecticide-treated nets, artemisinin-based combination therapy, under-five children, Rivers State, Nigeria, transmission dynamics, public health, sensitivity analysis