The　Coronavirus　Disease　2019　(COVID-19)　has　popularized　since　late　December　2019.　In　present,　it　is　still　highly　transmissible　and　has　severe　impact　on　the　public　health　and　global　economy.　Due　to　the　lack　of　specific　drug　and　the　appearance　of　different　variants,　the　selection　of　the　antiviral　therapy　to　treat　the　patients　with　mild　symptom　is　of　vital　importance.　Hence,　in　this　paper,　we　propose　a　novel　behavioral　Three-Way　Decision　(3WD)　model　and　apply　it　to　the　medicine　selection　decision.　First,　a　new　relative　utility　function　is　constructed　by　considering　the　risk-aversion　behavior　and　regret-aversion　behavior　of　human　beings.　Second,　based　on　the　relative　utility　function,　some　new　rules　are　defined　to　calculate　the　thresholds　and　conditional　probabilities　in　3WD　and　some　corresponding　theorems　are　explored　and　proved.　Next,　a　new　information　fusion　mechanism　in　the　framework　of　evidential　reasoning　algorithm　is　developed.　Then,　the　decision　results　are　obtained　based　on　the　Bayesian　decision　procedure　and　the　principle　of　maximum　utility.　Finally,　an　example　with　large-scale　data　set　and　an　example　about　medicine　selection　for　COVID-19　are　provided　to　show　the　implementation　process　and　effectiveness　of　the　proposed　method.　Comparative　analysis　and　sensitivity　analysis　are　also　performed　to　illustrate　the　superiority　and　the　robustness　of　the　current　proposal.　©　2022　Elsevier　B.V.