This study provides a comprehensive review and analysis of virus mutation rates, establishing criteria for comparative studies. Mutation rates for 23 viruses are presented as substitutions per nucleotide per cell infection (s/n/c), corrected for selection bias using a new statistical method. Rates range from 10⁻⁸ to 10⁻⁶ s/n/c for DNA viruses and 10⁻⁶ to 10⁻⁴ s/n/c for RNA viruses. RNA viruses show a negative correlation between mutation rate and genome size, though further testing is needed. Retroviruses have mutation rates similar to other RNA viruses. Nucleotide substitutions are four times more common than insertions/deletions (indels). Mutation rates per nucleotide per strand copying are lower due to multiple copying cycles per cell, especially in double-stranded DNA viruses. A regularly updated virus mutation rate dataset is available online. The mutation rate is critical for understanding viral evolution and has practical implications. For example, HIV-1 mutation rates suggest that drug resistance mutations occur within a day, necessitating combination therapy. High mutation rates could be combated by mutagens, which have shown effectiveness against several RNA viruses. Mutation rates also influence vaccination strategies and the stability of live attenuated vaccines. They play a role in assessing the risk of emerging infectious diseases. The study addresses two main issues: units of measurement and selection bias. Viruses use different replication modes, leading to different definitions of mutation rates. Selection bias affects mutation rate estimates, as deleterious mutations are often eliminated. The study provides a method to correct for selection bias using empirical data on mutational fitness effects. The study also discusses the implications of mutation rates for viral evolution, including the role of replication modes, the frequency of indels versus substitutions, and the impact of mutation rates on viral fitness and virulence. The study highlights the importance of accurate mutation rate estimates for understanding viral evolution and developing effective strategies to combat viruses. The study concludes that future mutation rate studies should use low cell infection cycles, large mutational targets, and neutral or lethal mutations to minimize selection bias. The study provides a detailed analysis of mutation rates for various viruses, including bacteriophages, RNA viruses, and DNA viruses, and discusses the implications of these rates for viral evolution and disease control.This study provides a comprehensive review and analysis of virus mutation rates, establishing criteria for comparative studies. Mutation rates for 23 viruses are presented as substitutions per nucleotide per cell infection (s/n/c), corrected for selection bias using a new statistical method. Rates range from 10⁻⁸ to 10⁻⁶ s/n/c for DNA viruses and 10⁻⁶ to 10⁻⁴ s/n/c for RNA viruses. RNA viruses show a negative correlation between mutation rate and genome size, though further testing is needed. Retroviruses have mutation rates similar to other RNA viruses. Nucleotide substitutions are four times more common than insertions/deletions (indels). Mutation rates per nucleotide per strand copying are lower due to multiple copying cycles per cell, especially in double-stranded DNA viruses. A regularly updated virus mutation rate dataset is available online. The mutation rate is critical for understanding viral evolution and has practical implications. For example, HIV-1 mutation rates suggest that drug resistance mutations occur within a day, necessitating combination therapy. High mutation rates could be combated by mutagens, which have shown effectiveness against several RNA viruses. Mutation rates also influence vaccination strategies and the stability of live attenuated vaccines. They play a role in assessing the risk of emerging infectious diseases. The study addresses two main issues: units of measurement and selection bias. Viruses use different replication modes, leading to different definitions of mutation rates. Selection bias affects mutation rate estimates, as deleterious mutations are often eliminated. The study provides a method to correct for selection bias using empirical data on mutational fitness effects. The study also discusses the implications of mutation rates for viral evolution, including the role of replication modes, the frequency of indels versus substitutions, and the impact of mutation rates on viral fitness and virulence. The study highlights the importance of accurate mutation rate estimates for understanding viral evolution and developing effective strategies to combat viruses. The study concludes that future mutation rate studies should use low cell infection cycles, large mutational targets, and neutral or lethal mutations to minimize selection bias. The study provides a detailed analysis of mutation rates for various viruses, including bacteriophages, RNA viruses, and DNA viruses, and discusses the implications of these rates for viral evolution and disease control.