In plant-virus disease epidemiology, dynamical models have invariably incor
porated a bilinear inoculation rate that is directly proportional to both t
he abundance of healthy (susceptible) hosts and the abundance of infective
vectors. Similarly, the acquisition rate is usually assumed to be directly
proportional to the abundance of nonviruliferous vectors and that of infect
ious hosts. These bilinear assumptions have been questioned for certain hum
an diseases, and infection rates that incorporate power parameters of the v
ariables have been proposed. Here, infection rates for plant-virus diseases
that are of a more general form than the familiar bilinear terms are exami
ned. For such diseases, the power parameter can be regarded as a measure of
the spatial aggregation of the vectors or as a coefficient of interference
between them, depending on the context.
Field data of cassava mosaic virus disease (CMD) incidence were examined. W
hen vector population density and disease incidence were high, disease prog
ress curves over the first 6 months from planting could not be explained us
ing models with bilinear infection rates. Incorporation of the new infectio
n terms allowed the range of observed disease progress curve types to be de
scribed. New evidence of a mutually beneficial interaction between the viru
ses causing CMD and the whitefly vector, Bemisia tabaci, has shown that spa
tial aggregation of the vectors is an inevitable consequence of infection,
particularly with a severe virus strain or a sensitive host. Virus infectio
n increases both vector fecundity and the density of vectors on diseased pl
ants. It is postulated that this enhances disease spread by causing an incr
eased emigration rate of infective vectors to other crops. Paradoxically, w
ithin the infected crop, vector aggregation reduces the effective contact r
ate between vector and host and therefore the predicted disease incidence i
s less than when a bilinear contact rate is used.