mortality and advanced support requirement for patients with cancer with covid19 a mathematical dynamic model for latin america purpose in the midst of a global pandemic evidence suggests that similar to other severe respiratory viral infections patients with cancer are at higher risk of becoming infected by covid19 and have a poorer prognosismethods we have modeled the mortality and the intensive care unit icu requirement for the care of patients with cancer infected with covid19 in latin america a dynamic multistate markov model was constructed transition probabilities were estimated on the basis of published reports for cumulative probability of complications basic reproductive number r0 values were modeled with r using the epiestim package estimations of days of icu requirement and absolute mortality were calculated by imputing number of cumulative cases in the markov modelresults estimated median time of icu requirement was 127 days median time to mortality was 163 days after infection and median time to severe event was 81 days peak icu occupancy for patients with cancer was calculated at 16 days after infection deterministic sensitivity analysis revealed an interval for mortality between 185 and 304 with the actual incidence tendency latin america would be expected to lose approximately 111725 patients with cancer to sarscov2 range 87116143154 patients by the 60th day since the start of the outbreak losses calculated vary between 1 to 176 of all patients with cancer in the regionconclusion cancerrelated cases and deaths attributable to sarscov2 will put a great strain on health care systems in latin america early implementation of interventions on the basis of data given by disease modeling could mitigate both infections and deaths among patients with cancer