The COVID-19 pandemic caused by a novel coronavirus (Sars-CoV-2) has become a major public health challenge. The rapid spread of the disease in different parts of the world has challenged the governments to control the virus transmission and minimize the insufficient supply of resources, besides its economic impact. We aimed to localize field hospitals as well as allocate public intensive care beds, ward beds, and mechanical ventilators to provide the appropriate treatment to patients. For this, firstly we estimated the number of confirmed cases based on ARIMA (Autoregressive Integrated Moving Average) for May 2020; then a set covering model was implemented aiming to attend the whole demand while minimizing the distance traveled by the patient and the costs involved. Data on hospitalization, notification of confirmed cases, beds, and mechanical ventilators was collected from DATASUS and the Rio de Janeiro State Health Department (SES-RJ). Four different scenarios were suggested to decision-makers, seeking to minimize the distance traveled by the patient and the cost of installing hospitals. According to our results, the initial planning of the government of Rio de Janeiro State was over-dimensioned and anticipated more beds than necessary. Our solution could provide the optimal treatment and structure to the population in the face of similar challenges regarding temporary emergencies.