Latent Class Analysis of COVID-19 Deaths by Comorbidities, United States, February-May 2020

Purpose: Risk factors for coronavirus disease 2019 (COVID-19) mortality include older age, cardiovascular disease, diabetes, and other comorbidities. Latent class analysis (LCA) can identify unrecognized morbidity patterns for decedents with COVID-19. Methods: Data were collected from 23 U.S. jurisdictions about decedents with COVID-19 early in the COVID-19 pandemic (February 12-May 12, 2020). LCA identified groups of individuals based upon pre-existing comorbidities: cardiovascular, renal, lung, neurologic, and liver disease; obesity; diabetes; and immunocompromised state. Results were stratified by sex, age, race/ethnicity, and location of death. Results: Of 12,340 decedents, LCA identified three classes, which included classes with prominent cardiovascular disease and diabetes (32%), prominent cardiovascular disease without diabetes (19%), and a minimal prevalence class (49%) with a low frequency of comorbidities. Individuals in the minimal prevalence class had risk factors in <2 comorbidity groups, where cardiovascular disease was the most common for individuals with a single comorbidity. Conclusions: LCA analysis reaffirms the importance of diabetes and cardiovascular disease as risk factors for COVID-19 mortality and indicates that about half of decedents were in the minimal prevalence group. Results could guide vaccination and treatment messaging to groups with no or few underlying conditions. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study did not receive any funding. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: This activity was reviewed by CDC and was conducted consistent with applicable federal law and CDC policy. See manuscript text for further details. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Underlying data are not publicly available with personal identifiable information due to privacy and legal restrictions.