Spatial distribution is an important property of insect populations and an important premise to provide dynamic information for pest control. A large number of papers have studied the aggregation index of various insects and mite species populations and described their spatial distributions. Most of these results indicated a similar pheromone that the behaviours of populations tend to fluctuate either from aggregation to diffusion or from diffusion to aggregation. Regarding these general phenomena of organisms′ aggregation pattern, many researchers have set up Fourier models and damp vibration models to capture the spatio-temporal distribution dynamics of populations. However, these models could not clearly describe the distributions of insect and mite populations because they ignored the constraints of resources and spaces. In this paper, we proposed a novel model based on previous studies and the aggregation-diffusion behaviours of aphids. The amplitude and cycle in this model were variable (y=Ae-nt\[sin(w0emtt+)+b\]+c). The model was utilised to express the spatio-temporal distribution dynamics of aphid populations with patchiness index as a dependent variable. We applied this model to fit with the experimental data from English green aphid (Sitobion avenae Fabricius), greenbug (Schizaphis graminum Rondani), oat bird-cherry aphid (Rhopalosiphum padi Linnaeus), corn leaf aphid (Rhopalosiphum maidis Fitch), grasshopper, and Tetranychus viennensis Zacher respectively. The fitting results of the four aphid populations showed that the dynamics of wheat aphid populations and maize aphid population were different. Decreasing amplitude and decreasing cycle were a common characteristic of all the distribution trends of the three wheat aphid species′ populations. The trends of the maize aphid population, on the other hand, showed a different characteristic: decreasing amplitude and increasing cycle. Meanwhile, according to all experimental results, we also showed the advantages of our novel model over the existing ones. First, it implied clearer biological significance, because each parameter in this model had a definite biological meaning. Second, it gave satisfying data fitting results (R2>0.942, SSE<2.6). Finally, the application fields of this model could be extended to describe the spatio-temporal dynamics of other insects and mite populations, including populations of different age-phases and populations of different positions on the same host plant. For example, the model can be used to study the spatial dynamic relationships of insect pest aphids and their natural enemies as well as to identify the dominant species of natural enemies and the competition mechanism with their enemies. Furthermore, the competition of different aphid populations on a certain plant can also be studied with this model. This will be helpful for us to demonstrate their competitive relation and find the dominant insect pest species at different periods. All these applications can provide guidance for the agricultural workers in the management of insect pest, laying a foundation for integrated pest management. The model can also be applied to describe the aggregation-diffusion behaviours of the population of a certain aphid species on wheat of different resistance varieties at the same period, which will help people to select the wheat cultivar resistant to the aphid.