Several aspects of a person’s speech can be influenced by Parkinson’s Disease (PD), namely, phonatory, articulatory, prosodic, and cognitive-linguistic aspects. Several studies in literature extract information about these aspects to automatically detect or assess PD employing corpora containing different speech tasks from patients and control subjects. In this review, we analyze the influence of PD in the prosodic aspect and the potential use of prosody-related features in automatic detection and assessment of PD. Moreover, a list of corpora identified during the review, and an analysis of their characteristics are included in this article. As a conclusion of the review, we observe that the use of only prosody-related features in automatic detectors is uncommon in contrast to other aspects such as the phonatory and articulatory. Moreover, despite the clear evidence of the influence of PD in prosody, most of the proposed objective biomarkers or measures are not employed in the clinical practice to detect PD since a high percentage of the studies in literature only show trends and do not establish normative data for PD detection.