Recently, [8] has proposed that heterogeneity of infectiousness (and susceptibility) across individuals in infectious diseases, plays a major role in affecting the Herd Immunity Threshold (HIT). Such heterogeneity has been observed in COVID-19 and is recognized as overdispersion (or "super-spreading"). The model of [8] suggests that super-spreaders contribute significantly to the effective reproduction factor, R, and that they are likely to get infected and immune early in the process. Consequently, under R_0 = 3 (attributed to COVID-19), the Herd Immunity Threshold (HIT) is as low as 5%, in contrast to 67% according to the traditional models [1, 2, 4, 10]. This work follows up on [8] and proposes that heterogeneity of infectiousness (susceptibility) has two "faces" whose mix affects dramatically the HIT: (1) Personal-Trait-, and (2) Event-Based- Infectiousness (Susceptibility). The former is a personal trait of specific individuals (super-spreaders) and is nullified once those individuals are immune (as in [8]). The latter is event-based (e.g cultural super-spreading events) and remains effective throughout the process, even after the super-spreaders immune. We extend [8]'s model to account for these two factors, analyze it and conclude that the HIT is very sensitive to the mix between (1) and (2), and under R_0 = 3 it can vary between 5% and 67%. Preliminary data from COVID-19 suggests that herd immunity is not reached at 5%. We address operational aspects and analyze the effects of lockdown strategies on the spread of a disease. We find that herd immunity (and HIT) is very sensitive to the lockdown type. While some lockdowns affect positively the disease blocking and increase herd immunity, others have adverse effects and reduce the herd immunity.