The evaluation and implementation of tobacco policies intended to reduce harm to the population as a whole, including tobacco users and non-users, must assess the potential for both intended and unintended consequences associated with those policies. These assessments should be based on the combined dimensions of magnitude, and thus likelihood, of shifts in exposure patterns needed to produce a population benefit or harm, and magnitude of the expected population benefit or harm. To provide researchers and policymakers with a means of conducting such assessments, we developed a dynamic population modeler, DPM(+1), to estimate differences in survival if exposure patterns in the population shift from a higher risk product (e.g. cigarettes) to a modified risk tobacco product (MRTP) in specified ways. Statistical analyses that estimate the effects on all-cause mortality following market introduction of an MRTP that presents 8 % of the risk associated with cigarette smoking indicate that, within a single birth cohort, switching completely from cigarettes to the MRTP is more likely to lead to a population health benefit than initiating tobacco use with the MRTP instead of cigarettes. This is because tobacco initiation rarely occurs beyond young adulthood, whereas continuing smokers exist in all age categories, leading to a greater cumulative effect. In addition, complete and persistent switching to MRTP use among a small proportion of cigarette smokers in each age category offsets the survival deficit likely to occur with unintended shifts in exposure patterns, such as MRTP initiation among never tobacco users followed by transitioning to cigarette smoking and/or cigarette smokers switching to MRTP use instead of quitting. This is because the magnitude of risk reduction among smokers who switch completely from cigarettes to MRTP use far exceeds the risk associated with MRTP use among tobacco non-users, even when employing conservative estimates for unintended exposure patterns.