This application investigates the impact of COVID-19 on the transplant system. The first case of COVID-19 in the United States was diagnosed in January 2020 and likely spread throughout American communities during February 2020. The incidence of COVID-19 rapidly increased during the first two weeks of March, and, on March 13, 2020, a national emergency was declared due to the COVID-19 pandemic. Throughout this application, the pre- and post-COVID eras are before and after March 13, 2020, respectively. This application is updated monthly and currently uses data available between March 13, 2019 and March 12, 2021.

This application investigates the impact of COVID-19 on four distinct components of the transplant system:

- Waitlist outcomes
- Offer acceptance
- Posttransplant outcomes
- Donor utilization

For each section, you can select the organ of interest, e.g., waitlist outcomes for kidney transplant candidates. Each section shows descriptive statistics, adjusted analyses, and relevant methodological details.

This section investigates the effect of COVID-19 on waitlist outcomes, e.g., deceased donor transplant and waitlist mortality rate.

The Descriptives section summarizes the state of the waiting list and the unadjusted outcomes during the months before and after the emergence of COVID-19. The Adjusted Analyses provide different perspectives on the effect of COVID-19. The Overall tab summarizes the overall impact of COVID-19, while the Program Effects tab summarizes the geographic variability in the effect. The Time Trend tab illustrates the waitlist outcomes during the months before and after COVID-19. The Subgroup Analyses tab investigates differential effects of COVID-19 over candidate risk-factors.

This section presents descriptive waitlist statistics during the months before and after COVID-19. The descriptive statistics include candidates listed or still on the waiting list between March 13, 2019, and March 12, 2021.

**Figure notes**

- The figure tooltip, which appears when hovering over the figure, specifies the level for the stratification variable (if selected), the value for the current month, the number of months since the emergence of COVID-19, and the start and stop dates for the current period.
- The dashed green vertical line represents the approximate date of the declaration of emergency due to COVID-19 on March 13, 2020.
- When investigating stratification variables, clicking on the groups in the legend will turn the figure lines on and off.
- 0 months since COVID-19 is the month immediately after the declaration of emergency.

This section presents descriptive waitlist statistics across donation service areas (DSAs) before and after COVID-19. The before and after periods are specifically selected to include the same number of days. The before-COVID-19 period includes candidates listed or still on the waiting list between March 14, 2019, and March 12, 2020. The after-COVID-19 period includes candidates listed or still on the waiting list between March 13, 2020, and March 12, 2021.

This section presents the effect of COVID-19 on adjusted waitlist outcomes; i.e., adjusted transplant and waiting list mortality rates. The list of possible outcomes depends on the selected organ. For example, kidney transplant shows a living donor transplant rate but heart transplant does not.

This figure presents the overall effect of COVID-19 on waitlist outcomes; that is, the relative difference in the current outcome of interest after compared with before COVID-19. When the rate ratio is less than 1, the current outcome of interest was lower after COVID-19 than before. Conversely, when the rate ratio is more than 1, the current outcome of interest was higher after COVID-19 than before.

This figure presents the current outcome of interest during the months before and after the emergence of COVID-19. The reference period was March 13, 2019 to April 12, 2019: a year before COVID-19. Thus, when the rate ratio is less than 1, the current outcome of interest was lower during the given month compared with a year before COVID-19. Conversely, when the rate ratio is more than 1, the current outcome of interest was higher during the given month compared with a year before COVID-19.

This figure presents the waitlist outcomes by candidate characteristics before and after COVID-19. The first dropdown selects the characteristic of interest, and the second selects the comparison of interest. The Differences before/after COVID-19 comparison is the primary analysis for determining whether COVID-19 had a differential effect across the characteristic of interest. Thus, when the rate ratio is less than 1, the outcome for the level of interest compared with the reference level was lower after COVID-19 than before. Conversely, when the rate ratio is more than 1, the outcome for the level of interest compared with the reference level was higher after COVID-19 than before.

This section presents the changes in program- and OPO-specific rate ratios for the current outcome of interest before and after COVID-19. The figure labelled 'Differences across transplant programs' shows the program-level rate ratios for the outcome of interest before COVID-19 on the x-axis and after COVID-19 on the y-axis. The figure labelled 'Differences across DSAs' shows the relative change before and after COVID-19 in the outcome of interest for each DSA.

**wl_adj_many_periods.txt**

**Cohort definition: ** Most analyses included candidates prevalent on organ transplant waiting lists from March 13, 2019, to March 12, 2021. Candidates were subject to several inclusion and exclusion criteria:

- Candidates were included if their listing date was before March 12, 2021, and their removal date was after March 13, 2019.
- Candidates were excluded if they had no reported listing date.
- Canditates were excluded if they had no reported age at listing.

For the transplant rate analyses, candidate follow-up was censored at removal from the waiting list. For the waitlist mortality rate analyses, candidate follow-up was censored at removal from the waiting list for transplant, transfer, or improvement. Patients were followed after removal from the waiting list for other reasons. Additionally, the adjusted analyses for waitlist mortality only included candidates prevalent on the organ transplant waiting list between March 13, 2019, and December 31, 2020. The adjusted waitlist mortality analyses used an early stop date, because observing at least 95% of patient deaths on the waiting list can take 3 months.

**Time-varying covariates:** Candidate characteristics with time-varying values were updated at the beginning of each month before and after the emergence of COVID-19. For example, the lung allocation score (LAS) constantly changes as the patient becomes more or less sick. Thus, a patient's LAS value at the beginning of each month was the value used for descriptives and adjusted analyses during that entire month. For waitlist mortality analyses, candidates no longer on the waiting list at the beginning of the month use the most recent value.

**Statistical analysis:** Piecewise exponential models (PEMs) estimated the difference in four separate waitlist outcomes before and after the emergence of COVID-19: waitlist mortality, any transplant, deceased donor transplant, and living donor transplant. The time scale for these models was calendar time. PEMs are proportional hazards models with a piecewise constant baseline hazard in *a priori* defined intervals, although the specific parameterization of the baseline hazard depended on the analysis. These analyses adjusted for the effects of each candidate characteristic in the descriptive section, which entered the model as a categorical variable.

**Overall analysis**: This model included two intervals for the baseline hazard: before and after COVID-19. The overall effect of COVID-19 was the difference between these two intervals. The analysis included only overall effects for the candidate characteristics; e.g., the model assumed the same effect for candidate age before and after COVID-19.

**Trend analysis:** This model included a baseline hazard with a separate component, i.e., different effect, for each month before and after the emergence of COVID-19. Similar to the overall analysis, this analysis included only overall effects for the candidate characteristics.

**Subgroup analysis:** This model used the same baseline hazard as the overall analysis. In addition, each candidate characteristic had an interaction with the post-COVID-19 baseline hazard. Thus, the effects for each candidate characteristic differed before compared with after March 13, 2020.

**Program effects analysis** Generalized linear mixed models (GLMM) with no intercept but an effect for the before- and after-COVID-19 periods were estimated. Two separate GLMMs estimated the effects of transplant programs and donation service areas (DSAs). Specifically, random effects for the before- and after-COVID-19 periods estimated the differences across transplant programs or DSAs, and a correlation between the random effects was allowed. To reduce computational burden, the GLMM included an offset equal to the linear predictor of the candidate risk factors from the overall analysis. The offset accounts for the differential risk of the outcome of interest due to candidate factors.

This section investigates the impact of COVID-19 on offer acceptance practices. Broadly, offer acceptance is the likelihood of accepting a deceased donor offer made to an individual candidate on the waiting list, although these analyses included only offers from match runs with an accepted offer. Offer acceptance was investigated only for kidney, liver, lung, and heart transplant.

The Descriptives section summarizes the distribution of offers and unadjusted offer acceptance rates before and after the emergence of COVID-19. The Adjusted Analyses provide different perspectives on the effect of COVID-19. The Overall tab summarizes the overall impact of COVID-19, while the Program Effects tab summarizes the geographic variability in the effect. The Time Trend tab illustrates the adjusted acceptance rates during the months before and after COVID-19. The Subgroup Analyses tab investigates differential effects of COVID-19 by candidate and donor risk-factors.

This section presents descriptive statistics of deceased donor offers during the months before and after COVID-19. The offer number of eventually accepted offers was the number of offers until acceptance. For example, if a kidney was accepted after 5 declines, then the offer number of the accepted offer was 6. The offer acceptance rate was the number of accepted offers divided by the total number of offers.

**Figure notes**

- The figure tooltip, which appears when hovering over the figure, specifies the level for the stratification variable (if selected), the value for the current month, the number of months since the emergence of COVID-19, and the start and stop dates for the current period.
- The dashed green vertical line represents the approximate date of the declaration of emergency due to COVID-19 on March 13, 2020.
- When investigating stratification variables, clicking on the groups in the legend will turn the figure lines on and off.
- 0 months since COVID-19 is the month immediately after the declaration of emergency.

This section presents descriptive statistics of deceased donor offers across donation service areas (DSAs) before and after COVID-19. The periods before and after COVID-19 were specifically designed to include the same number of days. The before-COVID-19 period includes deceased donor offers from donors recovered between March 14, 2019, and March 12, 2020. The after-COVID-19 period includes deceased donor offers from donors recovered between March 13, 2020, and March 12, 2021.

This figure presents the overall effect of COVID-19 on offer acceptance, i.e., the relative difference in the offer acceptance rate after compared with before COVID-19. When the offer acceptance ratio is less than 1, the offer acceptance rates were lower after COVID-19 than before. Conversely, when the offer acceptance ratio is more than 1, the offer acceptance rates were higher after COVID-19 than before.

This figure presents the offer acceptance ratios during the months before and after the emergence of COVID-19. The reference period was the month 1 year before COVID-19. Thus, when the offer acceptance ratio is less than 1, the offer acceptance rates were lower during the given month compared with a year before COVID-19. Conversely, when the offer acceptance ratio is more than 1, the offer acceptance rates were higher during the given month compared with a year before COVID-19.

This figure presents the offer acceptance ratios by candidate and donor characteristics before and after COVID-19. The first dropdown list selects the characteristic of interest, and the second selects the comparison of interest. The Differences before/after COVID-19 comparison is the primary comparison for investigating whether offer acceptance rates differed after COVID-19 compared with before across the levels of the characteristic of interest. When the offer acceptance ratio is less than 1, the offer acceptance rate was lower after COVID-19 than before for the level of interest compared with the reference level. Conversely, when the offer acceptance ratio is more than 1, the offer acceptance rate was higher after COVID-19 than before for the level of interest compared with the reference level.

This section presents the changes in program- and OPO-specific offer acceptance ratios before and after COVID-19. The figure labelled 'Differences across transplant programs' shows the program-specific offer acceptance ratios before and after COVID-19. Offer acceptance ratios for the programs on the bottom right of the figure were lower after COVID-19 compared than before. In contrast, offer acceptance ratios for the programs on the top left of the figure were higher after COVID-19 than before. The figure labelled 'Differences across DSAs' shows the offer acceptance ratios for the DSAs for the time period of interest. The Differences before/after COVID-19 comparison illustrates the change in offer acceptance from before to after COVID-19 in the DSA.

oa_adj_many_periods.txt

**Cohort definition: ** The analyses included offers from deceased donors recovered between March 13, 2019, and March 12, 2021. The offers in the match runs were subject to several inclusion and exclusion criteria:

- Offers with missing or bypassed responses were excluded.
- Only match runs with an acceptance were included, and only the offers up to and including the acceptances.
- Multiple match runs from the same donor were combined, and duplicated offers were excluded.

Acceptances that did not result in transplant were considered declined offers. For non-kidney organs, only offers to single organ candidates were included (e.g., liver-alone offers). For kidney offers, only those to kidney-alone and kidney-pancreas candidates were included because kidney-pancreas candidates explicitly opt into receiving kidney-alone offers.

**Statistical analysis:** Logistic regressions estimated the effect of COVID-19, while adjusting for candidate and donor characteristics (listed in the Descriptive section). Each candidate and donor risk factor entered the model as a categorical variable. Additionally, the regressions adjusted for the effect of offer number, or the number of previous offers. Offer number entered the model as right-hand linear splines on the log base 2 scale with knots (on log base 2) at 0, 1, 2, 3, 4, 5, 6, 8, 10, and 12. Splines with fewer than 5 acceptances after the corresponding knot were removed. For example, a knot of 10 corresponds to an offer number of 1024 and, if less than 5 offers were accepted after offer number 1024, the spline was removed.

**Overall analysis:** The overall effect of COVID-19 was estimated through a binary variable for offers from donors recovered on or after March 13, 2020. The analysis included only overall effects for the candidate and donor characteristics; e.g., the model assumed the same effect for candidate age before and after COVID-19.

**Trend analysis:** The temporal trends in the months before and after COVID-19 were estimated with a categorical variable for the month of recovery before and after COVID-19 for a given offer. Similar to the overall analysis, the trend analysis included only overall effects for the candidate and donor characteristics.

**Subgroup analysis:** The subgroup analysis was similar to the overall analysis but included an interaction between each candidate and donor characteristic with the binary variable for offers from donors recovered on or after March 13, 2020. Thus, candidate and donor characteristics had different effects before and after COVID-19.

**Program effects analysis** Two separate generalized linear mixed models (GLMM) with no intercept but an effect for the before- and after-COVID-19 periods estimated the effects of transplant programs and donation service areas (DSAs). Specifically, random effects for the before- and after-COVID-19 periods estimated the differences across transplant programs or DSAs, and a correlation between the random effects was allowed. To reduce computational burden, an offset from the overall analysis accounted for the effect of candidate and donor risk factors.

This section investigates the effect of COVID-19 on posttransplant graft failure. Because transplant recipients are at high risk for infectious diseases, we focused on determining the effect of COVID-19 on the graft failure rate regardless of whether the recipient underwent transplant before or after the emergence of COVID-19. However, recipients who underwent transplant after the emergence of COVID-19, especially immediately after, likely have a higher risk of exposure to COVID-19. Thus, some of the analyses investigate whether the effect of COVID-19 depended on the time since transplant.

This section presents descriptive statistics for transplant recipients and unadjusted outcomes during the months before and after COVID-19. 30-day graft failure is the rate of graft failures per 100 person-years during the first 30 days after transplant. The figures showing numbers and percentages of recipients used transplants performed during the corresponding period, while the figures showing graft failure rates used recipients with a functioning graft within 30 days of transplant during the corresponding period. The before-COVID-19 period was March 13, 2019, through March 12, 2020. The after-COVID-19 period was March 13, 2020, through March 12, 2021.

**Figure notes**

- The figure tooltip, which appears when hovering over the figure, specifies the level for the stratification variable (if selected), the value for the current month, the number of months since the emergence of COVID-19, and the start and stop dates for the current period.
- The dashed green vertical line represents the approximate date of the declaration of emergency due to COVID-19 on March 13, 2020.
- When investigating stratification variables, clicking on the groups in the legend will turn the figure lines on and off.
- 0 months since COVID-19 is the month immediately after the declaration of emergency.

This section presents descriptive statistics of transplant recipients across donation service areas (DSAs) before and after COVID-19. 30-day graft failure is the rate of graft failures per 100 person-years during the first 30 days after transplant. The before- and after-COVID-19 periods were specifically designed to include the same number of days. The figure showing the number of recipients used transplants performed during the corresponding period, and the figure showing the graft failure rate used recipients with a functioning graft within 30-days of transplant during the corresponding period. The before-COVID-19 period was March 14, 2019, through March 12, 2020. The after-COVID-19 period was March 13, 2020, through March 12, 2021.

This section presents the overall effect of COVID-19 on posttransplant graft failure. For example, the overall hazard ratio is the relative difference in the rate of graft failure for all transplants performed after COVID-19 compared with before COVID-19. Thus, when the hazard ratio is less than 1, the hazard of graft failure was lower after the emergence of COVID-19 than before regardless of time from transplant. Conversely, when the hazard ratio is more than 1, the overall hazard of graft failure was higher after the emergence of COVID-19 than before regardless of time from transplant.

The overall effect of COVID-19 was split into four separate effects for different periods of time since transplant: 0-90 days, 90 days-1 year, 1-5 years, and more than 5 years. These effects may differ because recipients who underwent transplant during the COVID-19 era have the increased risk of immunosuppression and, in addition, increased risk of exposure in the hospital. The 0-90 days posttransplant period is most likely to involve the additional risk of exposure in the hospital, while the other periods will likely mostly involve the increased risk of immunosuppression for patients with long-term graft function.

This section presents the effect of COVID-19 on posttransplant graft failure during the months before and after its emergence. The reference period was 1-year before COVID-19. Thus, when the hazard ratio is less than 1, the hazard of graft failure was lower during the given month compared with a year before COVID-19. Conversely, when the hazard ratio is more than 1, the hazard of graft failure was higher during the given month compared with a year before COVID-19.

Similar to the Overall section, this section splits the effect of COVID-19 over time into four separate effects for different periods of time since transplant: 0-90 days, 90 days-1 year, 1-5 years, and more than 5 years. These effects may differ because recipients who underwent transplant during the COVID-19 era have the increased risk of immunosuppression and, in addition, increased risk of exposure to COVID-19 in the hospital. The 0-90 days posttransplant period is most likely to involve the additional risk of exposure in the hospital, while the other periods will likely mostly involve the increased risk of immunosuppression.

This section presents the hazard ratios for posttransplant graft failure by candidate and donor characteristics before and after COVID-19. The first dropdown list selects the characteristic of interest, and the second selects the comparison of interest. The Differences before/after COVID-19 comparison is the primary comparison of whether posttransplant graft failure rates differed after COVID-19 compared with before across the different levels of the characteristic of interest. When the hazard ratio is less than 1, the hazard of graft failure for the level of interest compared with the reference level was lower after than before COVID-19. Conversely, when the hazard ratio is more than 1, the hazard of graft failure for the level of interest compared with the reference level was higher after than before COVID-19.

Unlike the overall and time trend sections, the subgroup analyses present only the overall effect of COVID-19. The subgroup analyses use significantly larger models and therefore require more graft failures for accurate estimation. Thus, we did not attempt estimation of a model with subgroup effects for the different periods of posttransplant follow-up.

This section presents the changes in program- and OPO-specific hazard ratios for posttransplant graft failure before and after COVID-19. The figure labelled 'Differences across transplant programs' shows the program-specific hazard ratios before and after COVID-19. The programs in the top left of the figure had higher graft failure hazard ratios after COVID-19 than before. In contrast, the programs on the bottom right had lower graft failure hazard ratios after COVID-19 than before. The figure labelled 'Differences across DSAs' shows the hazard ratios for the DSAs for the time period of interest. The Differences before/after COVID-19 comparison illustrates the change in the graft failure hazard ratios from before to after COVID-19 in the DSA.

Unlike the overall and time trend sections, the subgroup analyses present only the overall effect of COVID-19. The analyses of program- and DSA-level effects use significantly larger models and therefore require more graft failures for accurate estimation. Thus, we did not attempt estimation of a model with program- and DSA-level effects for the different periods of posttransplant follow-up.

ptx_adj_many_periods

**Cohort definition:** The cohorts differed for the descriptive and adjusted analyses. The descriptive analyses used transplants performed and recipients with follow-up within 30 days of transplant from March 13, 2019, through March 12, 2021. In contrast, the adjusted analyses used a period prevalent cohort of recipients from March 13, 2019, through December 31, 2020. Specifically, recipients were included if they (1) underwent transplant from March 13, 2019, through December 31, 2020, or (2) had a functioning graft on March 13, 2019. Additionally, the adjusted analyses included only recipients who underwent transplant on or after January 1, 2000. The adjusted analyses used an earlier stop date because observing 95% of patient deaths in the SRTR database can take at least 3 months.

**Statistical analysis:** Piecewise exponential models (PEMs) estimated the difference in posttransplant graft failure rates before and after the emergence of COVID-19. PEMs are proportional hazards models with a piecewise constant baseline hazard in *a priori* defined intervals. The time scale was time since transplant, and the intervals were narrower immediately after transplant and wider longer after transplant due a higher hazard of graft failure immediately after transplant. The specific intervals after transplant were 0-7 days, 8-14 days, 15 days-1 month, 1-2 months, 2-3 months, 3-4 months, 4-5 months, 5-6 months, 6 months-1 year, 1-3 years, 3-5 years, 5-10 years, 10-15 years, and more than 15 years. The regressions adjusted for the candidate and donor characteristics shown in the descriptive section. Each candidate and donor risk factor entered the model as a categorical variable.

**Overall analysis**: The overall effect of COVID-19 was estimated through a time-varying binary variable for posttransplant time on or after March 13, 2020. That is, the time-varying variable was 0 before March 13, 2020 and 1 on and after March 13, 2020. The analysis considered different effects on COVID-19 on the time since transplant: (1) 0-90 days, (2) 90 days-1 year, (3) 1-5 years, and (4) more than 5 years. The different effects account for potentially different effects of patients undergoing transplant and therefore at elevated risk of exposure during the COVID-19 pandemic versus patients at elevated risk of complications from COVID-19 due to immunosuppression and comorbidity. For comparison purposes, the time-invariant overall effect of COVID-19, i.e., constant over time since transplant, was also included. The time-invariant and time-varying effects were estimated in separate models. Lasly, the analysis included only overall effects for the candidate and donor characteristics; e.g., the model assumed the same effect for candidate age before and after COVID-19.

**Trend analysis:** The temporal trends in the months before and after COVID-19 were estimated with a time-varying categorical variable for the current month before and after COVID-19. Similar to the overall analysis, the trend analysis considered time-varying effects of COVID-19 dependent on the time since transplant. Additionally, the analysis included only overall effects of the candidate and donor characteristics.

**Subgroup analysis:** The subgroup analysis considered only a time-invariant effect of COVID-19 and included an interaction between each candidate and donor characteristic with the time-varying binary COVID-19 variable time on or after March 13, 2020. That is, each candidate and donor characteristic had different effects before versus after COVID-19.

**Program effects analysis** Generalized linear mixed models (GLMM) with no intercept but an effect for the before- and after-COVID-19 periods were estimated. These analyses considered only time-invariant effects for COVID-19. Two separate GLMMs estimated the effects of transplant programs and donation service areas (DSAs). Specifically, random effects for the before- and after-COVID-19 periods estimated the differences across transplant programs or DSAs, and a correlation between the random effects was allowed. To reduce computational burden, the GLMM included an offset equal to the linear predictor of the candidate and donor risk factors from the overall analysis. The offset accounts for the differential risk of posttransplant outcomes due to candidate and donor factors.

This section investigates the effect of COVID-19 on deceased donor referrals and organ yield, nationally and at the DSA level. We investigate changes over time and provide pre-COVID versus post-COVID analyses.

The referrals analysis consists of (1) national- and DSA-level referral counts in the 12 months prior to COVID-19 through post-COVID-19; and (2) eligible death rates at the national- and DSA levels, i.e., the proportion of referrals that were eligible deaths, as noted by each OPO.

The figures below display the time trend of monthly counts of referrals and eligible death rates over time, starting with 12 months prior to the emergence of COVID-19 through the most recently available data.

**Figure notes**

- The figure tooltip, which appears when hovering over the figure, specifies the value for the current month, the number of months since the emergence of COVID-19, and the start and stop dates for the current period.
- In contrast to other descriptive trend figures, the referral figures do not include the most recent 6 weeks of data due to delays in finalizing the data.
- 0 months since COVID-19 is the month immediately after the declaration of emergency.

The figures below display the time trend of monthly counts of referrals and eligible death rates over time for the selected OPO, starting with 12 months prior to the emergence of COVID-19 through the most recently available data.

**Figure notes**

- The figure tooltip, which appears when hovering over the figure, specifies the value for the current month, the number of months since the emergence of COVID-19, and the start and stop dates for the current period.
- In contrast to other descriptive trend figures, the referral figures do not include the most recent 6 weeks of data due to delays in finalizing the data.
- 0 months since COVID-19 is the month immediately after the declaration of emergency.

This section investigates the effect of COVID-19 on eligible deaths and eligible death donation rates. The effect of COVID-19 on eligible deaths is important because decedents diagnosed with COVID-19 cannot be eligible deaths. Additionally, the effect of COVID-19 on the eligible death donation rate may vary in different regions of the country. Comparisons of eligible deaths and eligible death donation rates are given before and after the emergence of COVID-19.

This section presents descriptive statistics for eligible deaths and related metrics over time, starting with 12 months prior to the emergence of COVID-19. Descriptive statistics include eligible deaths, all deceased donors, deceased donors meeting eligible death criteria, and the observed donation rate (per 100 eligible deaths).

**Figure notes**

- 0 months since COVID-19 is the month immediately after the declaration of emergency.

This section presents descriptive statistics of eligible deaths and related metrics by DSA before- and after-COVID-19. Descriptive statistics include eligible deaths, all deceased donors, deceased donors meeting eligible death criteria, and the observed donation rate (per 100 eligible deaths).

This section presents the overall effect of COVID-19 on eligible death donations. For example, the overall odds ratio is the relative difference in the rate of eligible death donation after COVID-19 with before. Thus, when the odds ratio is less than 1, the odds of donation were lower after the emergence of COVID-19 than before. Conversely, when the odds ratio is more than 1, the overall odds of donation were higher after the emergence of COVID-19 than before.

This section presents the effect of COVID-19 on the eligible death donation rate during the months before and after the emergence of COVID-19. The reference period was 1 year before COVID-19. Thus, when the odds ratio is less than 1, the odds of donation were lower during the given month than a year before COVID-19. Conversely, when the odds ratio is more than 1, the odds of donation were higher during the given month than a year before COVID-19.

This section presents the odds ratios for eligible death donations across donor characteristics before and after COVID-19. The first dropdown list selects the characteristic of interest, and the second selects the comparison of interest. The Differences before/after COVID-19 comparison illustrates whether donation rates were higher or lower after COVID-19 compared with before across the different levels of the characteristic of interest. Each characteristic has a reference level. Thus, when the odds ratio is less than 1, the odds of donation for the level of interest compared with the reference level were lower after than before COVID-19. Conversely, when the odds ratio is more than 1, the odds of donation for the level of interest compared with the reference level were higher after than before COVID-19.

This section presents the changes in OPO-specific odds ratios for eligible death donation before and after COVID-19.

edr_adj_many_periods

**Cohort definition:** The analyses used a cohort of eligible deaths from March 13, 2019, through March 12, 2021. Specifically, eligible deaths were included if they were referred by the hospital between March 13, 2019, and March 12, 2021.

**Statistical analysis:** Logistic regression (LR) models estimated the difference in eligible death donation rates before and after the emergence of COVID-19. The LR models adjusted for the donor characteristics listed in the descriptive section. Each donor characteristic entered the model as a categorical variable.

**Overall analysis**: The overall effect of COVID-19 was estimated through a binary variable for donor referral on or after March 13, 2020. That is, the variable was 0 before March 13, 2020, and 1 on and after March 13, 2020. The analysis included only overall effects for the donor characteristics; e.g., the model assumed the same effect for donor age before and after COVID-19.

**Trend analysis:** The temporal trends in the months before and after COVID-19 were estimated with a time-varying categorical variable for the current month before and after COVID-19. Similar to the overall analysis, the analysis included only overall effects for the donor characteristics.

**Subgroup analysis:** The subgroup analysis considered only a time-invariant effect for COVID-19 and included an interaction between each donor characteristic with the time-varying binary COVID-19 variable time on or after March 13, 2020.

**OPO effects analysis** Generalized linear mixed models (GLMM) with no intercept but an effect for the before and after periods of COVID-19 were estimated. These analyses considered only time-invariant effects for COVID-19. A single GLMM estimated the effects of donation service areas (DSAs). Specifically, random effects for the before- and after-COVID-19 periods estimated the differences across DSAs, and a correlation between the random effects was allowed. To reduce computational burden, the GLMM included an offset equal to the linear predictor of the donor characteristics from the Overall analysis. The offset accounts for the differential donation rate due to donor factors.

This section investigates the effect of COVID-19 on deceased donor organ yield. Since the underlying donor population may change during the COVID-19 era, organ yield may be differentially affected, and the effect of COVID-19 on organ yield may vary in different regions of the country. Comparisons of deceased donor organ yield are given before and after the emergence of COVID-19.

This section presents descriptive statistics for deceased donor organ yield over time, starting with 12 months prior to the emergence of COVID-19. Descriptive statistics include number of donors, donor percentage, and organs transplanted per donor. Select an overall summary or summaries stratified by various donor characteristics of interest.

**Figure notes**

- 0 months since COVID-19 is the month immediately after the declaration of emergency.

This section presents descriptive statistics of deceased donor organ yield by DSA before- and after-COVID-19.

This section presents the overall effect of COVID-19 on deceased donor organ yield. For example, the overall odds ratio is the relative difference in organ donation after compared with before COVID-19. Thus, when the odds ratio is less than 1, the odds of organ donation were lower after the emergence of COVID-19 than before. Conversely, when the odds ratio is more than 1, the overall odds of organ donation were higher after the emergence of COVID-19 than before.

This section presents the effect of COVID-19 on the deceased donor organ yield during the months before and after the emergence of COVID-19. The reference period was a year before COVID-19. Thus, when the odds ratio is less than 1, the odds of organ donation were lower during the given month compared with a year before COVID-19. Conversely, when the odds ratio is more than 1, the odds of organ donation were higher during the given month compared with a year before COVID-19.

This section presents the odds ratios for deceased donor organ yield by donor characteristics before and after COVID-19. The first dropdown list selects the donor characteristic of interest, and the second selects the comparison of interest. The Differences before/after COVID-19 comparison illustrates whether organ donation rates were higher or lower after COVID-19 compared with before across the different levels of the characteristic of interest. Each characteristic has a reference level. Thus, when the odds ratio is less than 1, the odds of organ donation for the level of interest compared with the reference level were lower after than before COVID-19. Conversely, when the odds ratio is more than 1, the odds of organ donation for the level of interest compared with the reference level were higher after than before COVID-19.

This section presents the changes in OPO-specific odds ratios for deceased donor organ yield before and after COVID-19.

dyr_adj_many_periods.txt

**Cohort definition:** The analyses used a cohort of deceased donors from March 13, 2019, through March 12, 2021. Specifically, deceased donors were included if at least one organ was recovered for transplant between March 13, 2019, and March 12, 2021.

**Statistical analysis:** Ordinal and logistic regression (OR and LR) models estimated the expected organ yield before and after the emergence of COVID-19. The OR model was used for kidneys, since 0, 1, or 2 kidneys can be recovered, and the LR model was used for all other organs. The OR and LR models adjusted for the donor characteristics listed in the descriptive section. Each donor characteristic entered the model as a categorical variable.

**Overall analysis**: The overall effect of COVID-19 was estimated through a binary variable for recovered for transplant on or after March 13, 2020. That is, the variable was 0 before March 13, 2020 and 1 on and after March 13, 2020. The analysis includedonly overall effects for the donor characteristics; i.e., the model assumed the same effect for donor age before and after COVID-19.

**Trend analysis:** The temporal trends in the months before and after COVID-19 were estimated with a time-varying categorical variable for the current month before and after COVID-19. Similar to the overall analysis, the analysis included only overall effects for the donor characteristics.

**Subgroup analysis:** The subgroup analysis considered only a time-invariant effect for COVID-19 and included an interaction between each donor characteristic with the time-varying binary COVID-19 variable time on or after March 13, 2020.

**OPO effects analysis** Generalized linear mixed models (GLMM) with no intercept but an effect for the before- and after-COVID-19 periods were estimated. These analyses considered only time-invariant effects for COVID-19. A single GLMM estimated the effects of donation service areas (DSAs). Specifically, random effects for the before- and after-COVID-19 periods estimated the differences across DSAs, and a correlation between the random effects was allowed. To reduce computational burden, the GLMM included an offset equal to the linear predictor of the donor characteristics from the overall analysis. The offset accounts for the differential donation rate due to donor factors.

This page provides definitions for terms and abbreviations used throughout the application:

**CPRA:**Calculated panel-reactive antibodies.**Deceased donor transplant rate:**The number of deceased donor transplants per person-year.**DSAs:**Donation service areas, geographic units originally created for the recovery of organs from deceased donors. They were historically used as units of allocation in the transplant system.**HCC:**Hepatocellular carcinoma.**LAS:**Lung allocation score, the primary measure of allocation priority in lung allocation.**Living donor transplant rate:**The number of living donor transplants per person-year.**MELD:**Model for end-stage liver disease. The primary measure of allocation priority in liver allocation.**Offer number:**The location of an offer on the match run, or the rank ordering of candidates for allocation. For example, an offer number of 1 is the first offer of an organ, and an offer number of 10 is the tenth offer of an organ, etc.**OPO:**Organ procurement organization, the organizations responsible for recovering deceased donors in DSAs.**Overall transplant rate:**The number of living and deceased donor transplants per person-year.**PEM:**Piecewise exponential model, aproportional hazards model with a piecewise constant baseline hazard.**VAD:**Ventricular assist device.**Waitlist mortality rate:**The number of deaths on the waiting list but before transplant per person-year.**Urbanicity variable:**The analyses include an urbanicity variable, which is defined by rural-urban commuting areas (RUCA) codes for ZIP codes.

The cohorts for each analysis are updated every month. This tab only describes changes beyond the updated cohorts.

**October 2020**- Donor weight variable in the deceased donor section: The 150-200 and 200 or more categories were collapsed into a single 150 or more category because almost no donors were 200 or more kilograms.
- Subsection headers in donation section: The subsection headers better align with the populations used in each analysis.
- Referral analysis in donation section: The date of referral is now the month and year of referral. Previously, it was the date the referral information was 'completed'. The number of referrals within a period uses the average number of referrals per day during the month and the number of days in the month for the given period.

**November 2020**- Follow-up for waitlist mortality: The waitlist mortality rate analyses now follow candidates after removal from the waiting list for reasons other than transplant, transfer, or improvement. Patterns in waitlist removal could change before and after COVID-19, potentially affecting the analyses of waitlist mortality rates.
- Descriptive trend figures: The line for the last month on descriptive trend figures is now dotted, better distinguishing the partial month of follow-up from the rest of the figure.

**January 2021**- DSA-level maps for adjusted analyses: Previously, if a metric had little-to-no variability before and after COVID-19, the categories would be very narrow, magnifying small differences across DSAs. Thus, the categories now include, at a minimum, 0.9 and 1.1.

**March 2021**- MAOB and CTOP merged into a single DSA in January 2021. The data before and after January 2021 was updated to accurately reflect the merger.

**May 2021**- For all analyses, the follow-up ends on March 12, 2021. Regular updates will continue until, at a minimum, July 2021. However, the last month on descriptive figures is no longer dotted, signifying complete follow-up during the last month.