## 2 Materials and Methods  
### Data  
We examined U.S. national COVID-19 mortality data from the National Center for Health Statistics (NCHS) summarized as cumulative death counts (ICD-10 code U07.1 [20] as an underlying or multiple cause of death) within age intervals stratified by state (as well as D.C. and Puerto Rico) and sex [21]. The sex categories are male and female, and the following set of mutually exclusive, collectively exhaustive, and chronologically ordered age groups are used: \(<\)1, 1-4, 5-14, 5-14, 5-24, 25-34, 35-54, 45-54, 55-54, 55-54, 55-56, 65-74, 65-84 and 85+. Death counts between 1 and 9 are suppressed in the NCHS data due to patient privacy laws. However, the NCHS data additionally provides the total number of male and female deaths in each jurisdiction. Therefore, for each state and sex, we know the total number of deaths that are within the union of age groups with suppressed death counts, each of which contains between 1 and 9 deaths. The NCHS data also provide non-suppressed death counts within these same age groups stratified by sex for the U.S. overall. See File S1 in the Supplementary Materials for the NCHS data as of 31 March 2021 (reflecting all COVID-19 deaths reported to and processed by the NCHS as of 27 March 2021), which comprises 533,291 total deaths. A total of 111 male age groups and 113 female age groups have suppressed death counts across the 50 states and the District of Columbia (D.C.). To standardize estimates by age, we used the 2019 U.S. Census Bureau estimates of the population age distribution in each state (and D.C.) stratified by sex [22], defined over integer ages from 0 to 84 and a catch-all 85+ age group for the remaining ages. See File S2 in the Supplementary Materials for the U.S. Census Bureau data. Previous Work Quantifying Male-Female Disparities in COVID-19-Attributable YPLL in the United States  
YPLL has been used in diverse contexts to quantify and contrast the impact of premature mortality by sex (e.g., [23; 24; 25; 26; 27; 28; 29; 30; 31; 32]), and it has been used as a quantitative measure of mortality burden in the context of COVID-19 (e.g., [33; 34; 35; 36; 37; 38; 39; 40]). In particular, [PERSON] et al. (2021) [41] analyzed the NCHS data as of 3 February 2021 (reflecting all COVID-19 deaths reported to the NCHS and processed as of 31 January 2021), which served as a rough approximation of U.S. COVID-19 deaths during the first year of the pandemic, estimating total YPLL and crude YPLL rates by sex in each U.S. state using the sex-specific remaining life expectancy method [42] to define YPLL, meaning that YPLL for each decedent is defined as the expected number of remaining years of life conditional on sex and survival to the observed age at death with respect to the overall U.S. population according to actuarial life tables. While their paper serves as a useful initial analysis contrasting COVID-19-attributable YPLL by sex, there are a number of methodological shortcomings in their study that we aim to address in our analysis. First, [PERSON] et al. did not quantify the uncertainty of their state-level estimates of total YPLL and crude YPLL rates due to the administrative interval censoring of ages at death in the NCHS data. [PERSON] et al. focused exclusively on point estimation, assuming for the purposes of calculation that ages at death among decedents in a given age group all occurred at a fixed age, usually the age group midpoint (i.e., assuming that decedents in age group 60-69 died at age 65). For the 85+ age group in particular, because the ages at deaths are right-censored, they assumed all of these deaths occurred at age 90, an arbitrary assumption made out of analytical convenience to compute YPLL for these decedents. Second, [PERSON] et al. handled the suppressed death counts in the NCHS data by excluding them from their analysis, analogous to a \"complete-case analysis\" in the missing data literature [43].