Table 1.

A summary of key concepts, representative examples, and corresponding references

Key concepts and considerations	Representative examples	References
1. Temporal-spatial characterization	Scan statistics-based clustering	[11]
	Scan software tools	[12-15]
	Other applications (active foci or hotspots)	[16]
Related factors	Biology, environment, and socio-economy affecting interactions among hosts, vectors, and parasites at various scales	[17-19]
	Entomological inoculation rates, vector capacity, or force of infection	[20]
	A combination of epidemiological, geographical, and demographic factors	[21]
2. Modelling disease and/or information dynamics on networks	Dynamics of infectious diseases on regular, small-world, or scale-free networks	[22-27]
	Critical value analysis of typical epidemics on complex network	[28-33]
	Diffusion of rumours or innovation on social networks	[34-36]
	Viral marketing and recommendation strategies	[37-39]
	Cascading in virtual blog spaces, and their propagation trends	[10,40-43]
Related factors	Alternative spatial representations	[44]
	Effects of human mobility on the dynamics of disease transmission	[45]
3. Understanding the structures of underlying transmission networks via indirect means	Population travelling and mobility patterns	[46,47]
	Social contact activities	[48-50]
	Sexual relationships	[51]
4. Inferring transmission parameters from data	EM-based estimation algorithm to infer daily transmission rate between households	[52]
	Markov Chain Monte Carlo (MCMC) method to estimate transmission parameters	[53]
5. Inferring an underlying network from data	Social networks based on the interpersonal interaction records	[54-58]
	Interaction networks between proteins in a cell	[59,60]
	Supervised classification	[7]
	Expectation-maximization (EM)-like algorithm	[10]
	Narrow and deep tree-like structure analysis	[8]
	Likelihood-maximization	[9]
	Independent cascading models	[41]
6. Computational issues	Conventional optimization methods	[61]
	Potentially large-scale and/or dynamically-evolving surveillance data, e.g., over decades of temporal intervals	[62-64]
	Different levels of spatial categories	[62,63]
	Multiple environmental or biological factors incorporated	[19,64]
	Alternative AOC methods	[65-67]