Table 2 Future research priorities in network-based malaria transmission modelling
Inference of transmission networks | · Incorporating partial surveillance data over time, i.e., the temporal-spatial distributions of cases of infection |
|  | · Constructing specific infection models of malaria, while incorporating additional information, such as geographic, environmental, climatic, demographic, clinical, and behavioural information |
|  | · Developing computational tractable probabilistic methods, as well as extending the existing models proposed in computer science (e.g., independent cascading models) |
Use of transmission networks | · Validating inferred transmission networks by testing them with available malaria data |
|  | · Predicting and analyzing the impact of malaria transmission and their underlying factors over time and space through constructing and comparing a series of transmission networks |
|  | · Evaluating existing intervention or eradication strategies and guiding new control efforts |