Agent-based simulation (ABS) continues to grow in popularity and in its fast-expanding application in various fields. Despite the increased interest, however, a common protocol or standard curriculum for development and analysis of ABS models hardly exists. As originally discrete-event simulation (DES) modelers, self-taught and still new to the world of ABS modeling, we have occasionally observed a gap between traditional simulation theory and current practices of ABS in the literature. This points to great unevenness among existing ABS applications in terms of concepts and design, quantitative and computational techniques used in analysis of models, as well as domain-specific issues in different fields. In this paper, we review a number of important topics and issues in the design and analysis of ABS models that deserve attention. Our discussion is supported by some illustrative examples from ABS models of disease epidemics, but it's applicable to a fairly general class of ABS models.