Zhumagali Koshemetov, Yerbol Bulatov, Orazbek Serikbayov, Kuandyk Zhugunissov
In recent years, mpox has emerged as a significant global public health threat. The widespread distribution of the virus, coupled with the legacy of historical smallpox vaccination, has underscored the critical need to serologically distinguish between natural mpox infection and vaccine-induced humoral immune responses. However, the high antigenic similarity among Orthopoxvirus species leads to the production of cross-reactive antibodies, limiting the differentiation capacity of conventional serological assays. This mini-review evaluates current serological approaches aimed at discriminating between mpox infection and vaccine-induced immunity. Specifically, we analyze multiplexed immunoassays, comparative ratios based on orthologous antigens, machine learning-supported serological models, peptide-based platforms, and recombinant protein-based enzyme-linked immunosorbent assay (ELISA) methods. The findings of this review indicate that multiplex immunoassays, orthologous antigen ratio-based approaches, and machine learning algorithms exhibit the highest discriminatory potential for distinguishing natural mpox infection from vaccine-induced immune responses. In addition, MPXV A27L and ATI-N-CPXV antigens may be considered promising candidates for serological differentiation, although their performance requires further investigation.