With　the　rapid　outbreak　of　COVID-19,　most　people　are　facing　antivirus　mask　shortages.　Therefore,　it　is　necessary　to　reasonably　select　antivirus　masks　and　optimize　the　use　of　them　for　everyone.　However,　the　uncertainty　of　the　effects　of　COVID-19　and　limits　of　human　cognition　add　to　the　difficulty　for　decision　makers　to　perfectly　realize　the　purpose.　To　maximize　the　utility　of　the　antivirus　mask,　we　proposed　a　decision　support　algorithm　based　on　the　novel　concept　of　the　spherical　normal　fuzzy　(SpNoF)　set.　In　it,　firstly,　we　analyzed　the　new　score　and　accuracy　function,　improved　operational　rules,　and　their　properties.　Then,　in　line　with　these　operations,　we　developed　the　SpNoF　Bonferroni　mean　operator　and　the　weighted　Bonferroni　mean　operator,　some　properties　of　which　are　also　examined.　Furthermore,　we　established　a　multi-criteria　decision-making　method,　based　on　the　proposed　operators,　with　SpNoF　information.　Finally,　a　numerical　example　on　antivirus　mask　selection　over　the　COVID-19　pandemic　was　given　to　verify　the　practicability　of　the　proposed　method,　which　the　sensitive　and　comparative　analysis　was　based　on　and　was　conducted　to　demonstrate　the　availability　and　superiority　of　our　method.