Exploring the Gap Between Excess Mortality and COVID-19 Deaths in 67 Countries

Francesco Sanmarchi, MD¹; Davide Golinelli, MD¹; Jacopo Lenzi, PhD¹; et alFrancesco Esposito, MD¹; Angelo Capodici, MD¹; Chiara Reno, MD¹; Dino Gibertoni, PhD¹

Author Affiliations Article Information

JAMA Netw Open. 2021;4(7):e2117359. doi:10.1001/jamanetworkopen.2021.17359

Research Letter 

Global Health

July 16, 2021

COVID-19 Resource Center

Introduction

During the SARS-CoV-2 pandemic, a surge in overall deaths has been recorded in many countries, most of them likely attributable to COVID-19. However, COVID-19 confirmed mortality (CCM) is considered an unreliable indicator of COVID-19 deaths because of national health care systems’ different capacities to correctly identify people who actually died of the disease.^1,2 Excess mortality (EM) is a more comprehensive and robust indicator because it relies on all-cause mortality instead of specific causes of death.³ We analyzed the gap between the EM and CCM in 67 countries to determine the extent to which official data on COVID-19 deaths might be considered reliable.

Methods

In this cross-sectional study, we retrieved aggregated country-level data on population and COVID-19 overall confirmed cases, deaths, and testing as of December 31, 2020, from Our World in Data. Data on countries’ overall deaths from 2015 to 2020 were obtained from the World Mortality Data set (eAppendix in the Supplement). This research was based on public use datasets that do not include identifiable personal information and, per the Common Rule, was exempt from Institutional Review Board review and approval. For the same reason, no informed consent was required. This study follows the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.

Negative binomial regression models were used to estimate projected deaths in 2020 using mortality data from 2015 to 2019. Two-sided 95% CIs for country-specific projected deaths were calculated applying the normal approximation to the Poisson distribution. EM in the pandemic period (ie, February 26 to December 31, 2020) was estimated as the difference between cumulative observed deaths and projected deaths. Countries’ testing capacity was assessed with their cumulative test-to-case ratio (eAppendix in the Supplement). The association between country-specific cumulative CCM and EM per 100 000 population of 2020 was displayed using a scatterplot, in which the identity line discriminates countries with EM exceeding CCM from those with EM lower than CCM. A color was assigned to countries based on their decile of testing capacity. All analyses were performed using R version 4.0.4 (R Project for Statistical Computing). Details on the analytic approach are available in the eAppendix in the Supplement.

Results

Most of the 67 countries experienced an increase in mortality during 2020 (Table). Among countries with increased mortality (ie, those located above 0 on the y-axis in the Figure), a small number appeared under the identity line, showing lower-than-expected mortality after subtracting COVID-19 deaths. Countries located above the identity line can be visually classified into 2 groups: 1 with several Latin American and East European countries, which exhibit a large gap between EM and CCM (eg, Mexico, 212 excess deaths vs 96 COVID-19 deaths per 100 000 population); the other, more heterogeneous group showed a moderate EM beyond CCM (eg, Greece, 57 excess deaths vs 45 COVID-19 deaths per 100 000 population). Countries with negative EM also had very low CCM and were mainly located in East Asia. The lowest figures of EM and CCM generally belonged to countries with higher testing capacity (in green) and the largest differences between EM and CCM to countries with poorer testing capacity (in red).

Discussion

This comparison of CCM and EM revealed the different national health systems’ capacity to test and diagnose COVID-19 and their responsiveness to the health crisis. Underreporting of COVID-19 deaths because of strained health care systems’ capacity might explain our findings for countries where EM exceeded CCM.^2,4 In contrast, the effects of nonpharmaceutical interventions on populations’ main causes of deaths, such as the decrease in work and road accidents, could be responsible for the reduction in overall mortality in countries where CCM exceeded EM.⁵ Notably, most of the countries that presented reduced overall mortality during 2020 had extremely high testing capacity and were praised for their effective response measures against the pandemic.⁶

Limitations of our analysis include the lack of stratification by age and sex, the underrepresentation of some areas of the world, and not considering nonpharmaceutical interventions. Despite these drawbacks, our findings corroborate the evidence that in many countries the accuracy in quantifying the death toll of COVID-19 is still a missed target. The global action against the pandemic is being conditioned by diverse responses to the crisis, but reliable evidence should be the pillar on which effective prevention measures are built.

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Article Information

Accepted for Publication: May 13, 2021.

Published: July 16, 2021. doi:10.1001/jamanetworkopen.2021.17359

Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2021 Sanmarchi F et al. JAMA Network Open.

Corresponding Author: Davide Golinelli, MD, Department of Biomedical and Neuromotor Sciences, Alma Mater Studiorum–University of Bologna, Via San Giacomo 12, 40126 Bologna, Italy (davide.golinelli@unibo.it).

Author Contributions: Dr Sanmarchi had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Sanmarchi, Golinelli, Capodici, Gibertoni.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Sanmarchi, Golinelli, Capodici.

Critical revision of the manuscript for important intellectual content: Sanmarchi, Golinelli, Lenzi, Esposito, Reno, Gibertoni.

Statistical analysis: Sanmarchi, Lenzi, Capodici, Gibertoni.

Supervision: Golinelli, Gibertoni.

Conflict of Interest Disclosures: None reported.

References

1.

Bilinski  A, Emanuel  EJ.  COVID-19 and excess all-cause mortality in the US and 18 comparison countries.   JAMA. 2020;324(20):2100-2102. doi:10.1001/jama.2020.20717
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2.

Karanikolos  M, McKee  M; European Observatory on Health Systems and Policies. How comparable is COVID-19 mortality across countries? Eurohealth. 2020;26(‎2):45-50. Accessed June 12, 2021. https://apps.who.int/iris/handle/10665/336295

3.

Garber  AM.  Learning from excess pandemic deaths.   JAMA. 2021. Published online April 02, 2021. doi:10.1001/jama.2021.5120
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4.

Woolf  SH, Chapman  DA, Sabo  RT, Zimmerman  EB.  Excess deaths from COVID-19 and other causes in the US, March 1, 2020, to January 2, 2021.   JAMA. 2021;325(17):1729-1730. doi:10.1001/jama.2021.5199
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5.

Davies  NG, Kucharski  AJ, Eggo  RM, Gimma  A, Edmunds  WJ; Centre for the Mathematical Modelling of Infectious Diseases COVID-19 working group.  Effects of non-pharmaceutical interventions on COVID-19 cases, deaths, and demand for hospital services in the UK: a modelling study.   Lancet Public Health. 2020;5(7):e375-e385. doi:10.1016/S2468-2667(20)30133-XPubMedGoogle ScholarCrossref

6.

Wang  CJ, Ng  CY, Brook  RH.  Response to COVID-19 in Taiwan: big data analytics, new technology, and proactive testing.   JAMA. 2020;323(14):1341-1342. doi:10.1001/jama.2020.3151
ArticlePubMedGoogle ScholarCrossref

 

Variations in Processes of Care and Outcomes for Hospitalized General Medicine Patients Treated by Female vs Male Physicians

Anjali Sergeant, BASc¹; Sudipta Saha, SM²; Saeha Shin, MPH³; et alAdina Weinerman, MD⁴; Janice L. Kwan, MD, MPH⁵; Lauren Lapointe-Shaw, MD, PhD⁵; Terence Tang, MD⁵; Gillian Hawker, MD, MSc⁵; Paula A. Rochon, MD, MPH⁶; Amol A. Verma, MD, MPhil⁵; Fahad Razak, MD, MSc⁵

Author Affiliations Article Information

JAMA Health Forum. 2021;2(7):e211615. doi:10.1001/jamahealthforum.2021.1615

Key Points

Question  Is physician gender associated with mortality and other patient outcomes in a general internal medicine inpatient setting?

Findings  In this cross-sectional study of 171 625 hospitalized patients, patients cared for by female physicians had lower in-hospital mortality after adjustment for hospital and for patient characteristics, but this was no longer statistically different after adjustment for physician characteristics.

Meaning  The lower mortality rate in patients cared for by female physicians may be partially explained by differences in physician characteristics.

Abstract

Importance  Hospitalized medical patients cared for by female physicians may have decreased mortality rates compared with patients of male physicians. However, this association has yet to be assessed outside of the US, and little is known about factors that may explain this difference.

Objective  To determine whether mortality, other hospital outcomes, and processes of care differed between the patients cared for by female and male physicians.

Design, Setting, and Participants  This retrospective cross-sectional study included patients admitted to general medical wards at 7 hospitals in Ontario, Canada, between April 1, 2010, and October 31, 2017. The association of physician gender with patient outcomes was examined while adjusting for hospital fixed effects, patient characteristics, physician characteristics, and processes of care. All patients were admitted to a general internal medicine service through the emergency department and were cared for by a general internist or family physician-hospitalist. Patients were excluded if length of stay was greater than 30 days or if the attending physician cared for less than 100 hospitalized general medicine patients over the study period. Statistical analyses were performed from October 15, 2020, to May 8, 2021.

Main Outcomes and Measures  In-hospital mortality, length of stay, intensive care unit admission, 30-day readmissions, and process-of-care measures (blood tests, medications, imaging, endoscopy, and interventional radiology services).

Results  A total of 171 625 hospitalized patients with a median age of 73 years (interquartile range, 56-84 years) were included (84 221 men [49.1%], 87 402 women [50.9%], and 2 patients with unspecified sex). Patients were cared for by 172 attending physicians (54 female physicians [31.4%] and 118 male physicians [68.6%]). In fully adjusted models, female physicians ordered more imaging tests, including computed tomography (adjusted difference, −1.70%; 95% CI, −2.78% to −0.61%; P = .002), magnetic resonance imaging (−0.88%; 95% CI, −1.37% to −0.38%; P = .001), and ultrasonography (−1.90%; 95% CI, −3.21% to −0.59%; P = .005). Patients treated by female physicians had lower in-hospital mortality (2256 of 46 772 patients [4.8%] vs 6452 of 124 853 patients [5.2%]). This difference persisted after adjustment for patient characteristics but was no longer statistically different after adjustment for other physician characteristics (adjusted difference, 0.29%; 95% CI, −0.08% to 0.65%; P = .12). The difference was similar after further adjustment for processes of care.

Conclusions and Relevance  In this cross-sectional study of patients admitted to general medical units in Canada, patients cared for by female physicians had lower mortality rates than those treated by male physicians, adjusting for patient characteristics. This finding was nonsignificant after adjustment for other physician characteristics.

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JAMA Health Forum – Health Policy, Health Care Reform, Health Affairs | JAMA Health Forum | JAMA Network

 PRIVATIZED MEDICINE USA

Association Between Primary Care Payment Model and Telemedicine Use for Medicare Advantage Enrollees During the COVID-19 Pandemic

Brian W. Powers, MD¹; Dana Drzayich Antol, MS¹; Yongming Zhao, PhD¹; et alGilbert S. Haugh, MS¹; Oraida Roman, MHA¹; William H. Shrank, MD¹; Niteesh K. Choudhry, MD, PhD²

Author Affiliations Article Information

JAMA Health Forum. 2021;2(7):e211597. doi:10.1001/jamahealthforum.2021.1597

COVID-19 Resource Center

Introduction

Patterns of outpatient care shifted dramatically during the early stages of the COVID-19 pandemic,¹ with deferred in-person care leading to substantial revenue losses for primary care organizations.² This shift created a strong financial incentive to move visits to telemedicine, especially among organizations reimbursed under fee-for-service payment models. Primary care organizations reimbursed under value-based payment models did not experience the same near-term financial incentives but may have found it easier to expand telemedicine access given underlying technology and infrastructure investments.³ To better understand these dynamics, we examined the association between the primary care payment model and telemedicine use for Medicare Advantage enrollees during the COVID-19 pandemic.

Methods

For this cohort study, we identified beneficiaries continuously enrolled in Medicare Advantage health maintenance organization (HMO) plans offered by Humana, Inc, from January 1, 2019, to September 30, 2020. Enrollees in HMO plans are required to select a primary care clinician, which we used to attribute patients to a primary care organization. We then used contract data to identify the payment model under which the organization was reimbursed for the patients’ care and classified those payment models according to the following taxonomy: fee-for-service; shared savings with upside-only financial risk; shared savings with downside financial risk; or capitation, as described in the eMethods of the Supplement. We considered shared savings with downside financial risk and capitation to represent advanced value-based payment models.

Next, we identified audiovisual and audio-only telemedicine visits with the attributed primary care organization from January 1, 2020, to September 30, 2020, using paid outpatient claims, as described in the eMethods of the Supplement. We then assessed changes in weekly rates of telemedicine utilization, stratified by primary care payment model. Finally, we estimated the association between telemedicine use and primary care payment model using a patient-level negative binomial regression model that adjusted for patient age, sex, race/ethnicity, Medicare eligibility criteria, comorbidity,⁴ and practice size, and included hospital referral region fixed effects. Race/ethnicity was assessed according to the Centers for Medicare & Medicaid Services beneficiary race code, which reflects data self-reported to the Social Security Administration.

An Advarra institutional review board deemed the study exempt and waived informed consent because it used only retrospective deidentified data and did not meet the criteria found in the Regulations for the Protection of Human Subjects (45 CFR §46). Data analyses were performed from December 30, 2020, to May 14, 2021, using SAS Enterprise Guide, version 8.2 (SAS Inc). P values were 2-tailed and statistical significance was defined as P < .05. The study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.

Results

The study population of 1 125 946 patients (mean [SD] age, 74.7 [6.7] years; 645 489 [57.3%] women) comprised 28 508 (2.5%) Asian, 228 105 (20.3%) Black, 121 016 (10.8%) Hispanic, 1732 (0.2%) Native American, and 733 803 (65.2%) White individuals. Telemedicine use rose faster and reached higher absolute levels among those patients attributed to primary care organizations reimbursed via advanced value-based payment models compared with those reimbursed via fee-for-service (Figure). In multivariable analyses of cumulative telemedicine visits from March 1, 2020, to September 30, 2020, primary care payment model was significantly associated with telemedicine utilization (Table). Compared with patients attributed to organizations reimbursed under fee-for-service, the marginal effects of primary care payment model on telemedicine visits per 1000 patients were −12.9 (95% CI, −17.4 to −8.4) for shared savings with upside-only financial risk, 71.5 (95% CI, 66.9 to 76.1) for shared savings with downside financial risk, and 105.6 (95% CI, 96.1 to 115.1) for capitation.

Discussion

In this cohort study of Medicare Advantage enrollees during the COVID-19 pandemic, we found that the primary care payment model was significantly associated with telemedicine use. The patients attributed to the primary care organizations reimbursed under advanced value-based payment models used telemedicine services at the highest rates. Rates of telemedicine utilization were lower among patients attributed to organizations reimbursed under fee-for-service, despite those organizations facing the strongest near-term financial incentive to increase telemedicine utilization.² This suggests that accountability for cost, quality, and disease management under value-based payment models—and the infrastructure, technology, and management systems of organizations engaging in these models—may have been a stronger catalyst for telemedicine adoption than recouping revenue from deferred in-person visits.

A limitation of this study was the inability to observe practice characteristics beyond payment model and size that may be associated with telemedicine adoption. Further research is needed to better understand the specific drivers of telemedicine adoption within physician organizations, especially as payers and policy makers consider approaches to ensure adequate, equitable, and sustainable access to telemedicine in the postpandemic era.

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Article Information

Accepted for Publication: May 17, 2021.

Published: July 16, 2021. doi:10.1001/jamahealthforum.2021.1597

Open Access: This is an open access article distributed under the terms of the CC-BY-NC-ND License. © 2021 Powers BW et al. JAMA Health Forum.

Corresponding Author: Brian W. Powers, MD, MBA, Humana Inc, 500 W Main St, Louisville, KY 40202 (bpowers5@humana.com).

Author Contributions: Dr Powers had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: All authors.

Acquisition, analysis, or interpretation of data: Powers, Drzayich Antol, Zhao, Haugh, Shrank, Choudhry.

Drafting of the manuscript: Powers, Shrank.

Critical revision of the manuscript for important intellectual content: Powers, Drzayich Antol, Zhao, Haugh, Roman, Choudhry.

Statistical analysis: Zhao, Haugh, Shrank.

Administrative, technical, or material support: Powers, Drzayich Antol, Roman, Shrank.

Supervision: Powers, Haugh, Shrank.

Conflict of Interest Disclosures: Dr Powers, Ms Drzayich Antol, and Ms Roman report equity in Humana, outside of the submitted work. Dr Shrank reports equity in Humana and serving as a Director at GetWellNetwork, outside the submitted work. Dr Choudhry reports grants from Humana, outside the submitted work. No other disclosures were reported.

Additional Contributions: We would like to thank Yong Li, PhD, Humana Inc, and Adrianne Casebeer, PhD, Humana Inc, for their contributions to the study design, data analysis, and results interpretation. They were not compensated beyond their regular salaries.

References

1.

Patel  SY, Mehrotra  A, Huskamp  HA, Uscher-Pines  L, Ganguli  I, Barnett  ML.  Trends in outpatient care delivery and telemedicine during the COVID-19 pandemic in the US.   JAMA Intern Med. 2021;181(3):388-391. doi:10.1001/jamainternmed.2020.5928
ArticlePubMedGoogle ScholarCrossref

2.

Basu  S, Phillips  RS, Phillips  R, Peterson  LE, Landon  BE.  Primary care practice finances in the United States amid the COVID-19 pandemic.   Health Aff (Millwood). 2020;39(9):1605-1614. doi:10.1377/hlthaff.2020.00794PubMedGoogle ScholarCrossref

3.

American Academy of Family Physicians. Value-based payment study. Accessed March 1, 2021. https://valuebasedcare.humana.com/wp-content/uploads/2018/02/2017-Value-Based-Payment-Study-External.pdf

4.

Quan  H, Sundararajan  V, Halfon  P,  et al.  Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data.   Med Care. 2005;43(11):1130-1139. doi:10.1097/01.mlr.0000182534.19832.83PubMedGoogle ScholarCrossref

No sign of COVID-19 vaccine in breast milk

Small UCSF study indicates vaccine safety for pregnant and lactating women

UNIVERSITY OF CALIFORNIA - SAN FRANCISCO

Research News

Messenger RNA vaccines against COVID-19 were not detected in human milk, according to a small study by UC San Francisco, providing early evidence that the vaccine mRNA is not transferred to the infant.

The study, which analyzed the breast milk of seven women after they received the mRNA vaccines and found no trace of the vaccine, offers the first direct data of vaccine safety during breastfeeding and could allay concerns among those who have declined vaccination or discontinued breastfeeding due to concern that vaccination might alter human milk. The paper appears in JAMA Pediatrics.

Research has demonstrated that vaccines with mRNA inhibit transmission of the virus that causes COVID-19. The study analyzed the Pfizer and Moderna vaccines, both of which contain mRNA.

The World Health Organization recommends that breastfeeding people be vaccinated, and the Academy of Breastfeeding Medicine has said there is little risk of vaccine nanoparticles or mRNA entering breast tissue or being transferred to milk, which theoretically could affect infant immunity.

"The results strengthen current recommendations that the mRNA vaccines are safe in lactation, and that lactating individuals who receive the COVID vaccine should not stop breastfeeding," said corresponding author Stephanie L. Gaw, MD, PhD, assistant professor of Maternal-Fetal Medicine at UCSF.

"We didn't detect the vaccine associated mRNA in any of the milk samples tested," said lead author Yarden Golan, PhD, a postdoctoral fellow at UCSF. "These findings provide an experimental evidence regarding the safety of the use of mRNA-based vaccines during lactation."

The study was conducted from December 2020 to February 2021. The mothers' mean age was 37.8 years and their children ranged in age from one month to three years. Milk samples were collected prior to vaccination and at various times up to 48 hours after vaccination.

Researchers found that none of the samples showed detectable levels of vaccine mRNA in any component of the milk.

The authors noted that the study was limited by the small sample size and said that further clinical data from larger populations were needed to better estimate the effect of the vaccines on lactation outcomes.

###

Co-authors are Mary Prahl, MD; Arianna Cassidy, MD; Christine Y. Lin, BA; Nadav Ahituv, PhD; and Valerie J. Flaherman, MD, MPH, all of UCSF.

The study was supported by the Marino Family Foundation; the National Institutes of Health (grant numbers K23AI127886 and K08AI141728); the Weizmann Institute of Science-National Postdoctoral Award Program for Advancing Women in Science; the International Society for Research in Human Milk and Lactation Trainee Bridge Fund; and the Human Frontier Science Program. Disclosures can be found in the paper.

About UCSF Health: UCSF Health is recognized worldwide for its innovative patient care, reflecting the latest medical knowledge, advanced technologies and pioneering research. It includes the flagship UCSF Medical Center, which is ranked among the top 10 hospitals nationwide, as well as UCSF Benioff Children's Hospitals, with campuses in San Francisco and Oakland, Langley Porter Psychiatric Hospital and Clinics, UCSF Benioff Children's Physicians and the UCSF Faculty Practice. These hospitals serve as the academic medical center of the University of California, San Francisco, which is world-renowned for its graduate-level health sciences education and biomedical research. UCSF Health has affiliations with hospitals and health organizations throughout the Bay Area. Visit http://www.ucsfhealth.org/. Follow UCSF Health on Facebook or on Twitter

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Watching the ultrafast dance moves of a laser plasma

TATA INSTITUTE OF FUNDAMENTAL RESEARCH

VIDEO: THE MOTION OF A HOT, DENSE PLASMA CREATED ON A SOLID TARGET SURFACE BY AN ULTRAHIGH INTENSITY LASER. THE MOVIE SHOWS DIFFERENT REGIONS OF A PLASMA MOVING IN AND OUT... view more 

CREDIT: ANKIT DULAT

Great leaps in science and technology have been propelled by recent advances in seeing fast evolving physical phenomena, as they happen. Femtosecond lasers from the infrared to the X-ray region have enabled us to 'watch', in real time, atoms dance in molecules and solids on femtosecond and picosecond timescales. Watching such fascinating motions not just in real time but at the spatial locations where they happen, is a bigger challenge.

It is precisely this advance that has been made by a team of researchers at the Tata Institute of Fundamental Research, Mumbai, York University and the Rutherford Appleton Laboratories, UK [1]. They exploded a solid surface with an ultrahigh intensity (10^19 W/sq.cm), 25 femtosecond laser pulse (pump) creating a hot, dense plasma and monitored its ultra-rapid motion by reflecting a weak second femtosecond pulse (probe). The Doppler shifts in the wavelength imposed on the reflected probe pulse by the fast evolving plasma give away the outward (blue shift) and inward (red shift) motions of the plasma.

No previous study captured the motion on the entire plasma surface -- the 'dance floor' -- in a single experiment. This team coupled femtosecond time resolution with micrometre space resolution, thereby capturing the ultra-rapid twists and turns of the plasma at different transverse locations.

The experiments devised a novel 2-D Doppler monitor with sixteen independent, single shot, high resolution spectrometers all triggered by the pump laser pulse and capturing the instantaneous velocity of the plasma at different spatial locations. They show that different portions of the plasma move in and out at different times, contrary to the usual expectation of a somewhat uniform motion. This new method can prove very useful for tracking the flow of heat and energy along the surface and watching the growth of plasma instabilities, very important for understanding laser plasma science and pushing forward applications of high intensity, femtosecond laser driven laser plasmas in imaging and laser fusion.

CAPTION

A two-dimensional Doppler spectrometer captures the motions of a high intensity, femtosecond laser induced hot, dense plasma at different locations on a solid surface.

CREDIT

K. Jana and Amit Lad

[1] Femtosecond, two-dimensional spatial Doppler mapping of ultraintense laser-solid target interaction, PHYSICAL REVIEW RESEARCH 3, 033034 (2021)