A sensor capable of quantifying both anti-SARS-CoV-2 spike receptor-binding domain (RBD) antibody levels and the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus in saliva and serum was developed. This was accomplished by exploiting the enzymatic reaction of maltose and orthophosphate (PO43-) in the presence of maltose phosphorylase to generate an equivalent amount of glucose that was detected using a commercial glucometer test strip and a potentiostat. Important for this approach is the ability to generate PO43- in an amount that is directly related to the concentration of the analytes. RBD-modified magnetic microparticles were used to capture anti-SARS-CoV-2 spike RBD antibodies, while particles modified with anti-SARS-CoV-2 nucleocapsid antibodies were used to capture SARS-CoV-2 nucleocapsid protein from inactivated virus samples. A magnet was used to isolate and purify the magnetic microparticles (with analyte attached), and alkaline phosphatase-conjugated secondary antibodies were bound to the analytes attached to the respective magnetic microparticles. Finally, through enzymatic reactions, specific amounts of PO43- (and subsequently glucose) were generated in proportion to the analyte concentration, which was then quantified using a commercial glucometer test strip. Utilizing glucose test strips makes the sensor relatively inexpensive, with a cost per test of ∼US $7 and ∼US $12 for quantifying anti-SARS-CoV-2 spike RBD antibody and SARS-CoV-2, respectively. Our sensor exhibited a limit of detection of 0.42 ng/mL for anti-SARS-CoV-2 spike RBD antibody, which is sensitive enough to quantify typical concentrations of antibodies in COVID-19-infected or vaccinated individuals (>1 μg/mL). The limit of detection for the SARS-CoV-2 virus is 300 pfu/mL (5.4 × 106 RNA copies/mL), which exceeds the performance recommended by the WHO (500 pfu/mL). In addition, the sensor exhibited good selectivity when challenged with competing analytes and could be used to quantify analytes in saliva and serum matrices with an accuracy of >94% compared to RT-qPCR.