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