Frequent　outbreaks　of　respiratory　infectious　diseases,　driven　by　diverse　pathogens,　have　long　posed　significant　threats　to　public　health,　economic　productivity,　and　societal　stability.　Respiratory　infectious　diseases　are　highly　contagious,　characterized　by　short　incubation　periods,　diverse　symptoms,　multiple　transmission　routes,　susceptibility　to　mutations,　and　distinct　seasonality,　contributing　to　their　propensity　for　outbreaks.　The　absence　of　effective　antiviral　treatments　and　the　heightened　vulnerability　of　individuals　with　weakened　immune　systems　make　them　more　susceptible　to　infection,　with　severe　cases　potentially　leading　to　complications　or　death.　This　situation　becomes　particularly　concerning　during　peak　seasons,　such　as　influenza　outbreaks.　Therefore,　early　detection,　diagnosis,　and　treatment　are　critical,　alongside　the　prevention　of　cross-infection,　ensuring　patient　safety,　and　controlling　healthcare　costs.　To　address　these　challenges,　this　review　aims　to　identify　a　comprehensive,　rapid,　safe,　and　cost-effective　diagnostic　approach　for　respiratory　infectious　diseases.　This　approach　is　framed　within　the　existing　hierarchical　healthcare　system,　focusing　on　establishing　diagnostic　capabilities　at　hospitals,　community,　and　home　levels　to　effectively　tackle　the　above　issues.　In　addition　to　PCR　and　isothermal　amplification,　the　review　also　explores　emerging　molecular　diagnostic　strategies　that　may　better　address　the　evolving　needs　of　respiratory　disease　diagnostics.　A　key　focus　is　the　transition　from　amplification　technologies　to　amplification-free　biosensing　approaches,　with　particular　attention　given　to　their　potential　for　home-based　testing.　This　shift　seeks　to　overcome　the　limitations　of　conventional　amplification　methods,　particularly　in　decentralized　and　home　diagnostics,　offering　a　promising　solution　to　enhance　diagnostic　speed　and　safety　during　outbreaks.　In　the　future,　with　the　integration　of　AI　technologies　into　molecular　amplification　technologies,　biosensors,　and　various　application　levels,　the　inclusively　economic,　rapid,　and　safe　respiratory　disease　diagnosis　solutions　will　be　further　optimized,　and　their　accessibility　will　become　more　widespread.　©　2025　by　the　authors.