In 2020, the SARS-CoV-2 virus rapidly spread worldwide, triggering the COVID-19 pandemic and creating an urgent need for structured health information. As the pandemic progressed, researchers collected substantial data on symptoms, treatments, vaccines, and diagnostics. Although several teams developed ontologies to organize COVID-19 information, most created them in English and designed them for global contexts, which lack the localization necessary for effective regional health management. In this work, we propose a COVID-19 ontology in Spanish, specifically tailored to the Mexican context. We developed the ontology following the Grüninger and Fox methodology and implemented it using Protégé. We incorporated thirteen competency questions and translated them into SWRL rules to enable semantic reasoning over COVID-19 data. The resulting model represents essential concepts, object properties, and instances relevant to the pandemic, allowing users to query health information effectively. Compared to existing ontologies, our localized model aims to enhance communication, minimize risks of misinterpretation, and support data-driven decision-making for healthcare authorities and researchers in Mexico.