The Wood equation allows consistent fitting of individual antibody-response profiles of Zika virus or SARS-CoV-2 infected patients

Abstract

Antibody kinetic curves obtained during a viral infection are often fitted using aggregated patient data, hiding the heterogeneity of individual humoral immune responses. Individual antibody responses can be modeled using the Wood equation and grouped according to their profile. Such modeling takes into account several important kinetic parameters, such as the day when antibody detection becomes positive [daypos], the day of the maximal response [daymax], the maximum antibody level [levelmax], and the day when antibody detection becomes negative [dayneg]. Potential associations between these profiles and studied factors can then be tested.

Keywords

• Humoral immune response
• Curve fit
• Zika virus
• SARS-CoV-2
• Kinetic
• Wood equation