Vectorial Capacity: The Engine of Transmission
Vectorial capacity is the central concept linking mosquito biology to disease transmission potential. Developed by Garrett-Jones in 1964, it quantifies the daily rate at which future infectious bites arise from a currently infectious host, mediated entirely through the vector population. The formula C = m * a^2 * p^n / (-ln(p)) elegantly captures how vector density, feeding behavior, survival, and parasite development interact to determine transmission intensity.
Dissecting the Formula
Each component of the vectorial capacity equation represents a distinct biological process. The vector-to-host ratio (m) reflects mosquito abundance. The biting rate squared (a^2) appears because the mosquito must bite twice — once to acquire the infection and once to transmit it. The term p^n represents the probability of surviving the extrinsic incubation period, and -1/ln(p) is the expected mosquito lifespan after becoming infectious.
Sensitivity to Survival
The most striking feature of the vectorial capacity equation is its extreme sensitivity to daily survival probability p. Because p is raised to the power n (typically 10-14 for malaria), small reductions in survival produce dramatic reductions in C. Reducing daily survival from 0.9 to 0.8 reduces p^12 from 0.28 to 0.07 — a 75% reduction. This is why interventions targeting adult mosquito survival (insecticide-treated nets, indoor residual spraying) are the most effective malaria control tools.
Applications to Vector Control
Use this simulator to compare the relative impact of different interventions. Reducing vector density (m) through larval source management produces a linear reduction in C. Reducing biting rate (a) through bed nets produces a quadratic effect. Reducing survival (p) through insecticides has an exponential effect. The visualization shows the relative contribution of each parameter and the dramatic nonlinearity of survival's influence.