MODELING MALARIA TRANSMISSION TO OPTIMIZE TREATMENT AND CONTROL STRATEGIES IN RIVERS STATE, NIGERIA
Abstract
Nigeria accounts for 31.3% of global malaria deaths and 26.6% of cases, with low insecticide-
treated net (ITN) coverage, limited artemisinin-based combination therapy (ACT) use due to
financial barriers, and poor preventive chemotherapy uptake. Rivers State, with its high burden
and intervention gaps, is ideal for evaluating transmission dynamics and control.
This study developed a deterministic compartmental model comprises of humans: Susceptible,
Infected, Treated, Recovered (SITR) and vectors: Susceptible, Infected (SI), using parameters
from national reports and literature. Ordinary differential equations assessed intervention impacts
via sensitivity and scenario analyses on the basic (R0) and effective (Re) reproduction number.
Under the current coverage(10% ACT treatment, 15% ITN coverage, 32% IPTp-SP uptake) Re
was estimated at1.90. Further scenario analysis showed that increasing ITN and ACT treatment
coverage to 40% reduced Re to 0.71. Sensitivity analysis identified transmission (0.5) and cost-
driven treatment avoidance (0.08) as key drivers
The findings suggest that scaling ITN and ACT coverage to about 40% could lower the effective
reproduction number towards or below one, indicating reduced malaria transmission.
Policymakers may therefore prioritize expanding affordable access to these interventions in high-
burden settings, while noting that simplifying assumptions in the model limit generalizability.
Keywords: Malaria modeling, SITR–SI model, IPTp-SP, ITN effectiveness, ACT treatment.
