Tag: long covid prevalence

Long COVID Disability Burden in US Adults: YLDs and NIH Funding Relative to Other Conditions

Abstract:

Background Long COVID (LC) is novel, debilitating and likely chronic. Yet, scant data exist about its disability burden to guide scientific research and public health planning. We estimated Long COVID’s non-fatal disease burden in US adults and its FY2024 actual: burden-commensurate research funding from the National Institutes of Health (NIH) relative to other conditions, and biological sex.

Methods We present YLDs/100,000 for 70 NIH Research, Condition, and Disease Categories (RCDCs). Prevalence of disabling Long COVID was obtained from cross sectional surveys of representative samples of US adults, from September 2022 to August 2023. Disabling Long COVID was defined as incident symptoms persisting more than 3 months post-COVID, that significantly compromise daily activities. We calculated burden-commensurate funding for the top YLD conditions and for female vs. male dominant conditions.

Findings Disabling Long COVID was reported by 1.5% (n= 10,401) of n=757,580 respondents: Compared to the overall sample, those with disabling LC disproportionately identify as female (64.4% vs. 51.4%) and experiencing disability (80.8% vs. 52.9%) anxiety (57.5% vs. 23.8%) and depression (51.3% vs.18.5%). It ranked in the top 25% of YLDs at 320/100,000, between Alzheimer’s (279.4/100,000) and asthma (355.7/100,000) but received just 10% of its actual: YLD-commensurate funding. Only 5 conditions received less actual: burden: commensurate funding, including Myalgic Encephalitis/Chronic Fatigue Syndrome (<1%), another post-viral, female-dominant condition.

Interpretation LC has debilitated 3.8 million (weighted frequency) US adults. Research funding for it, like other female dominant conditions, lags behind its disability burden.

Research in Context Evidence before this study – We analyzed Long-COVID’s (LC) non-fatal disease burden in the US–represented by YLD (years lived with disability= prevalence x disability weight) — and National Institutes of Health (NIH) research 2024 funding relative to other conditions. We searched PubMed through 11/28/2023 for Long COVID prevalence (US), and Long COVID disability and disease burden (not US-specific). The keywords “years lived with disability” + “COVID” yielded n= 38 articles (11/29/23); but most referenced “disability-adjusted life years” (DALYs) in other countries. Similarly, “disease burden” + Long COVID yielded 23 papers, but no US YLD data. See Supplement 1 for meta-analyses, systematic reviews and US studies of Long COVID prevalence and impact.

We instead sourced YLD data from the US Census Bureau’s Household Pulse Survey (HPS) and the Institute for Health Metrics and Evaluation (IHME) /Global Burden of Disease (GBD) Long COVID Study Group. The HPS queries adults about Long COVID-related symptoms and their impact on daily activities. We applied the IHME/GBD’s estimated Long COVID disability weight of 0.21 and harmonized it with our LC case definition from the HPS data in consultation with IHME/GBD researchers. To harmonize IHME/GBD disability weights for non-LC diseases/conditions with the NIH’s terminology, we consulted with NIH staff. LC definition and measurement affects prevalence and burden estimates; our use of high-quality data sources and transparency in reporting how they were applied reduces the risk of biased assumptions.

Added value of this study- Long COVID is a chronic debilitating condition. While there is ample research on COVID’s acute illness and loss of life, there are no population-based data on its disability burden. We provide that data. To guide scientific research and public health planning, we report YLDs associated with disabling Long COVID (i.e., symptoms significantly limit activity), and; compare it to other conditions’ YLDs, NIH funding, and female-vs. male-dominance. It ranked in the top 25% of YLDs at 320/100,000, between Alzheimer’s (279.4/100,000) and asthma (355.7/100,000) but received just 10% of its YLD-commensurate funding. Only 5 conditions received less burden-commensurate funding; 3/5 were female-dominant, including Myalgic Encephalitis/Chronic Fatigue Syndrome (ME/CFS) at <1%, another post-viral condition that shares significant overlap with Long COVID. Overall, median funding/YLD was >= 5 times greater for male-vs. female-dominant conditions.

Implications of all the available evidence-Nearly 4 million US adults (weighted frequency) live with disabling Long COVID. They disproportionately identify as female and as having a disability, anxiety and depression. Yet NIH funding for diagnostic and treatment research for Long COVID hasn’t kept pace with its disability burden.

Source: Karen Bonuck, Qi Gao, Seth Congdon, Ryung Kim. Long COVID Disability Burden in US Adults: YLDs and NIH Funding Relative to Other Conditions. medRxiv 2024.01.09.24301057; doi: https://doi.org/10.1101/2024.01.09.24301057 https://www.medrxiv.org/content/10.1101/2024.01.09.24301057v1.full-text (Full text)

A Mechanistic Model for Long COVID Dynamics

Abstract:

Long COVID, a long-lasting disorder following an acute infection of COVID-19, represents a significant public health burden at present. In this paper, we propose a new mechanistic model based on differential equations to investigate the population dynamics of long COVID. By connecting long COVID with acute infection at the population level, our modeling framework emphasizes the interplay between COVID-19 transmission, vaccination, and long COVID dynamics. We conducted a detailed mathematical analysis of the model. We also validated the model using numerical simulation with real data from the US state of Tennessee and the UK.

Source: Derrick J, Patterson B, Bai J, Wang J. A Mechanistic Model for Long COVID Dynamics. Mathematics (Basel). 2023 Nov;11(21):4541. doi: 10.3390/math11214541. Epub 2023 Nov 3. PMID: 38111916; PMCID: PMC10727852. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10727852/ (Full text)

Prevalence of covid-19 and long covid in collegiate student athletes from spring 2020 to fall 2021: a retrospective survey

Abstract:

Background: Symptomatic COVID-19 and Long COVID, also referred to as post-acute sequelae of SARS-CoV-2 (PASC) or post-COVID conditions, have been widely reported in young, healthy people, but their prevalence has not yet been determined in student athletes. We sought to estimate the prevalence of reported COVID-19, symptomatic COVID-19, and Long COVID in college athletes in the United States attending 18 schools from spring 2020 to fall 2021.

Methods: We developed an online survey to measure the prevalence of student athletes who tested positive for COVID-19, developed Long COVID, and did not return to their sport during the relevant time period. We surveyed a convenience sample of 18 collegiate school administrators, representing about 7,000 student athletes. Of those schools surveyed, 16 responded regarding the spring 2020 semester, and 18 responded regarding the full academic year of fall 2020 to spring 2021 (both semesters).

Results: According to the survey responses, there were 9.8% of student athletes who tested positive for COVID-19 in spring 2020 and 25.4% who tested positive in the academic year of fall 2020 to spring 2021. About 4% of student athletes who tested positive from spring 2020 to spring 2021 developed Long COVID, defined as new, recurring, or ongoing physical or mental health consequences occurring 4 or more weeks after SARS-CoV-2 infection.

Conclusions: This study highlights that Long COVID occurs among young, healthy athletes and is a real consequence of COVID-19. Understanding the prevalence of Long COVID in this population requires longer follow-up and further study.

Source: Massey D, Saydah S, Adamson B, Lincoln A, Aukerman DF, Berke EM, Sikka R, Krumholz HM. Prevalence of covid-19 and long covid in collegiate student athletes from spring 2020 to fall 2021: a retrospective survey. BMC Infect Dis. 2023 Dec 13;23(1):876. doi: 10.1186/s12879-023-08801-z. PMID: 38093182; PMCID: PMC10717379. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10717379/ (Full text)

Association between SARS-CoV-2 variants and post COVID-19 condition: findings from a longitudinal cohort study in the Belgian adult population

Abstract:

Background: While many studies on the determinants of post-COVID-19 conditions (PCC) have been conducted, little is known about the relationship between SARS-CoV-2 variants and PCC. This study aimed to assess the association between different SARS-CoV-2 variants and the probability of having PCC three months after the infection.

Methods: This study was a longitudinal cohort study conducted between April 2021 and September 2022 in Belgium. In total, 8,238 adults with a confirmed SARS-CoV-2 infection were followed up between the time of their infection and three months later. The primary outcomes were the PCC status three months post infection and seven PCC symptoms categories (neurocognitive, autonomic, gastrointestinal, respiratory, musculoskeletal, anosmia and/or dysgeusia, and other manifestations). The main exposure variable was the type of SARS-CoV-2 variants (i.e. Alpha, Delta, and Omicron), extracted from national surveillance data. The association between the different SARS-CoV-2 variants and PCC as well as PCC symptoms categories was assessed using multivariable logistic regression.

Results: The proportion of PCC among participants infected during the Alpha, Delta, and Omicron-dominant periods was significantly different and respectively 50%, 50%, and 37%. Participants infected during the Alpha- and Delta-dominant periods had a significantly higher odds of having PCC than those infected during the Omicron-dominant period (OR = 1.61, 95% confidence interval [CI] = 1.33-1.96 and OR = 1.73, 95%CI = 1.54-1.93, respectively). Participants infected during the Alpha and Delta-dominant periods were more likely to report neurocognitive, respiratory, and anosmia/dysgeusia symptoms of PCC.

Conclusions: People infected during the Alpha- and Delta-dominant periods had a higher probability of having PCC three months after infection than those infected during the Omicron-dominant period. The lower probability of PCC with the Omicron variant must also be interpreted in absolute figures. Indeed, the number of infections with the Omicron variant being higher than with the Alpha and Delta variants, it is possible that the overall prevalence of PCC in the population increases, even if the probability of having a PCC decreases.

Source: Thi Khanh HN, Cornelissen L, Castanares-Zapatero D, De Pauw R, Van Cauteren D, Demarest S, Drieskens S, Devleesschauwer B, De Ridder K, Charafeddine R, Smith P. Association between SARS-CoV-2 variants and post COVID-19 condition: findings from a longitudinal cohort study in the Belgian adult population. BMC Infect Dis. 2023 Nov 8;23(1):774. doi: 10.1186/s12879-023-08787-8. PMID: 37940843; PMCID: PMC10634063. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10634063/ (Full text)

Prevalence of Symptoms ≤12 Months After Acute Illness, by COVID-19 Testing Status Among Adults — United States, December 2020–March 2023

Summary:

What is already known about this topic? Post-COVID conditions, or long COVID, can persist for months or years after an acute COVID-19 illness and can include emergence of new symptoms or the occurrence of symptoms that come and go.

What is added by this report? In a multicenter study of adults with a COVID-like illness, symptom prevalence decreased over time after the acute illness. Approximately 16% of adults with COVID-like symptoms reported persistent symptoms 12 months after a positive or negative SARS-CoV-2 test result. At 3, 6, 9, and 12 months after testing, some symptomatic persons had ongoing symptoms, and others had emerging symptoms not reported during the previous period.

What are the implications for public health practice? Health care providers should be aware that symptoms can persist, emerge, reemerge, or resolve after COVID-like illness and are not unique to COVID-19 or to post-COVID conditions.

Abstract:

To further the understanding of post-COVID conditions, and provide a more nuanced description of symptom progression, resolution, emergence, and reemergence after SARS-CoV-2 infection or COVID-like illness, analysts examined data from the Innovative Support for Patients with SARS-CoV-2 Infections Registry (INSPIRE), a prospective multicenter cohort study. This report includes analysis of data on self-reported symptoms collected from 1,296 adults with COVID-like illness who were tested for SARS-CoV-2 using a Food and Drug Administration–approved polymerase chain reaction or antigen test at the time of enrollment and reported symptoms at 3-month intervals for 12 months.

Prevalence of any symptom decreased substantially between baseline and the 3-month follow-up, from 98.4% to 48.2% for persons who received a positive SARS-CoV-2 test results (COVID test–positive participants) and from 88.2% to 36.6% for persons who received negative SARS-CoV-2 test results (COVID test–negative participants).

Persistent symptoms decreased through 12 months; no difference between the groups was observed at 12 months (prevalence among COVID test–positive and COVID test–negative participants = 18.3% and 16.1%, respectively; p>0.05).

Both groups reported symptoms that emerged or reemerged at 6, 9, and 12 months. Thus, these symptoms are not unique to COVID-19 or to post-COVID conditions. Awareness that symptoms might persist for up to 12 months, and that many symptoms might emerge or reemerge in the year after COVID-like illness, can assist health care providers in understanding the clinical signs and symptoms associated with post-COVID–like conditions.

Source: Montoy JC, Ford J, Yu H, et al. Prevalence of Symptoms ≤12 Months After Acute Illness, by COVID-19 Testing Status Among Adults — United States, December 2020–March 2023. MMWR Morb Mortal Wkly Rep 2023;72:859–865. DOI: http://dx.doi.org/10.15585/mmwr.mm7232a2 (Full text)

Long COVID and Significant Activity Limitation Among Adults, by Age — United States, June 1–13, 2022, to June 7–19, 2023

Summary:

What is already known about this topic? Long COVID includes a wide range of ongoing symptoms that can last for weeks, months, or years following SARS-CoV-2 infection.

What is added by this report? Prevalence of long COVID among noninstitutionalized U.S. adults aged ≥18 years decreased from 7.5% (95% CI = 7.1–7.9) during June 1–13, 2022 to 6.0% (95% CI = 5.7–6.3) during June 7–19, 2023 and from 18.9% (95% CI = 17.9–19.8) to 11.0% (95% CI = 10.4–11.6) among adults reporting previous COVID-19. After an initial decline, prevalence remained unchanged beginning January 4–16, 2023. Approximately one quarter of adults with long COVID report significant activity limitations.

What are the implications for public health practice? COVID-19 prevention efforts, including staying up to date with recommended COVID-19 vaccination and planning for long COVID symptom management and health care service needs, remain important.

Abstract:

Long COVID is a condition encompassing a wide range of health problems that emerge, persist, or return following COVID-19. CDC analyzed national repeat cross-sectional Household Pulse Survey data to estimate the prevalence of long COVID and significant related activity limitation among U.S. adults aged ≥18 years by age group.

Data from surveys completed between June 1–13, 2022, and June 7–19, 2023, indicated that long COVID prevalence decreased from 7.5% (95% CI = 7.1–7.9) to 6.0% (95% CI = 5.7–6.3) among the overall U.S. adult population, irrespective of history of previous COVID-19, and from 18.9% (95% CI = 17.9–19.8) to 11.0% (95% CI = 10.4–11.6) among U.S. adults reporting previous COVID-19. Among both groups, prevalence decreased from June 1–13, 2022, through January 4–16, 2023, before stabilizing.

When stratified by age, only adults aged <60 years experienced significant rates of decline (p<0.01). Among adults reporting previous COVID-19, prevalence decreased among those aged 30–79 years through fall or winter and then stabilized.

During June 7–19, 2023, 26.4% (95% CI = 24.0–28.9) of adults with long COVID reported significant activity limitation, the prevalence of which did not change over time.

These findings help guide the ongoing COVID-19 prevention efforts and planning for long COVID symptom management and future health care service needs.

Source:  Ford ND, Slaughter D, Edwards D, et al. Long COVID and Significant Activity Limitation Among Adults, by Age — United States, June 1–13, 2022, to June 7–19, 2023. MMWR Morb Mortal Wkly Rep 2023;72:866–870. DOI: http://dx.doi.org/10.15585/mmwr.mm7232a3 (Full text)

Treatment of Brain Fog of Long COVID Syndrome: A Hypothesis

Abstract:

The emergence of the SARS-CoV-2 (COVID-19) virus has exacted a significant toll on the global population in terms of fatalities, health consequences, and economics. As of February 2023, there have been almost 800 million confirmed cases of the disorder reported to the WHO [1], although the actual case-positive rate is estimated to be much higher.

While many cases recover, the mortality rate associated with the illness is about 1% (based on the WHO data). Most patients experience the illness as a mild to moderate disorder and recover without significant sequelae. However, as the COVID-19 pandemic has continued, there has emerged a significant group of COVID-19 survivors who experience persistent symptoms beyond the acute course of the illness.

As many as one in eight patients report persistent symptoms 90 to 150 days after the initial infection [2]. These so-called Long COVID or post-COVID syndrome patients are mostly drawn from those who were hospitalised for the disorder, but both non-hospitalised and vaccinated subjects may also experience the syndrome [3]. While an agreed definition of Long COVID is yet to be settled, a multiplicity of symptoms affecting most major organ systems has been reported in patients.

Common Long COVID symptoms include fatigue, dyspnoea, headaches, myalgia, anosmia, dysgeusia, cognitive symptoms, and mental disorders such as depression and anxiety [4]. It is estimated that approximately a third of patients with Long COVID exhibit either fatigue, cognitive impairment, or both up to 12 weeks after a confirmed diagnosis of COVID-19 [5].

Source: Norman TR. Treatment of Brain Fog of Long COVID Syndrome: A Hypothesis. Psychiatry International. 2023; 4(3):242-245. https://doi.org/10.3390/psychiatryint4030024 https://www.mdpi.com/2673-5318/4/3/24 (Full text)

Prevalence of Post-Acute COVID-19 Sequalae and Average Time to Diagnosis Among Persons Living With HIV

Abstract:

Aims: The aims of this meta-analysis were to assess: the prevalence of Post-Acute COVID-19 sequalae in HIV positive patients; average time of diagnosis; and meta-regress for possible moderators of PACS.
Methods: A standard search strategy was used in PubMed, and then later modified according to each specific database to get the best relevant results. These included Medline indexed journals; PubMed Central; NCBI Bookshelf and publishers’ Web sites in line with the Preferred Reporting Items for Systematic Review and Meta-Analysis statement. Search terms included “long COVID-19 or post-acute COVID-19 syndrome/sequalae”, “persons living with HIV or HIV. The criteria for inclusion were published clinical articles reporting HIV in association with long COVID-19, further, the average time to an event of post-acute COVID-19 sequelae among primary infected patients with COVID-19. Random-effects model was used. Rank Correlation and Egger’s tests were used to ascertain publication bias. Sub-group, sensitivity and meta-regression analysis were conducted. A 95% confidence intervals were presented and a p-value < 0.05 was considered statistically significant. Review Manager 5.4 and comprehensive meta-analysis version 4 (CMA V4) were used for the analysis. The review/trial was PROSPERO registered (CRD42022328509).
Results: A total of 43 studies reported post-acute COVID-19 syndrome. Of those, five reported post-acute COVID-19 sequalae in PLHIV. Prevalence of post-acute COVID-19 sequalae was 43.1% (95% CI 20.5% to 68.9%) in persons living with HIV (PLWH). The average time to PACS diagnosis was 4 months at 64% [0.64 (95% CI 0.230, 0.913) (P < 0.0000), I2= 93%] and at one year to PACS diagnosis was at 70 %, however with non-significant correlation (P > 0.05). On comorbidities, asthenia was associated with PACS at 17.6 % [0.176 (95% CI 0.067, 0.385) (P = 0.008), I2= 86%] while fatigue at 82%, however not related with PACS event incidence (P < 0.05). Americas, Asian and European regions showed PACS events rates of 82%, 43% and 19 % respectively (P<0.05) relative to HIV infection.
Conclusion: PACS prevalence in PLWH was 43% occurring at an average time of 4 months at 64% and 70 % at 12 months however non-significant with PACS. Asthenia was significantly associated with PACS at 17.6 % while fatigue at 82%, however not related with PACS event incidence. Americas recorded the highest PACS event rates in PLWH.
Source: Muthuka, J.; Nyamai, E.; Onyango, C.; Oluoch, K.; Nabaweesi, R. Prevalence of Post-Acute COVID-19 Sequalae and Average Time to Diagnosis Among Persons Living With HIV. Preprints 2023, 2023081633. https://doi.org/10.20944/preprints202308.1633.v1 https://www.preprints.org/manuscript/202308.1633/v1 (Full text available as PDF file)

Long COVID in a highly vaccinated population infected during a SARS-CoV-2 Omicron wave – Australia, 2022

Abstract:

Objective To characterise Long COVID in a highly vaccinated population infected by Omicron.

Design Follow-up survey of persons testing positive for SARS-CoV-2 in Western Australia, 16 July-3 August 2022.

Setting Community

Participants 22,744 persons with COVID-19 who had agreed to participate in research at the time of diagnosis were texted a survey link 90 days later; non-responders were telephoned. Post stratification weights were applied to responses from 11,697 (51.4%) participants, 94.0% of whom had received >= 3 vaccine doses.

Main outcome measures Prevalence of ‘Long COVID’ – defined as reporting new or ongoing COVID-19 illness-related symptoms or health issues 90 days post diagnosis; associated health care utilisation, reductions in work/study and risk factors were assessed using log-binomial regression.

Results 18.2% (n=2,130) of respondents met case definition for Long COVID. Female sex, being 50-69 years of age, pre-existing health issues, residing in a rural or remote area, and receiving fewer vaccine doses were significant independent predictors of Long COVID (p < 0.05). Persons with Long COVID reported a median of 6 symptoms, most commonly fatigue (70.6%) and difficulty concentrating (59.6%); 38.2% consulted a GP and 1.6% reported hospitalisation in the month prior to the survey due to ongoing symptoms. Of 1,778 respondents with Long COVID who were working/studying before their COVID-19 diagnosis, 17.9% reported reducing/discontinuing work/study.

Conclusion 90 days post Omicron infection, almost 1 in 5 respondents reported Long COVID symptoms; 1 in 15 of all persons with COVID-19 sought healthcare for associated health concerns >=2 months after the acute illness.

The known The prevalence of Long COVID varies widely across studies conducted in diverse settings globally (range: 9%-81%).

The new In a highly vaccinated population (94% with >=3 vaccine doses), almost 20% of persons infected with the SARS-CoV-2 Omicron variant reported symptoms consistent with Long COVID 90 days post diagnosis. Long COVID was associated with sustained negative impacts on work/study and a substantial utilisation of GP services 2-3 months after the acute illness; however, ED presentations and hospitalisations for Long COVID were rare.

The implications GP clinics play a significant role in managing the burden of Long COVID in Australia.

Source: Mulu Woldegiorgis, Gemma Cadby, Sera Ngeh, Rosemary Korda, Paul Armstrong, Jelena Maticevic, Paul Knight, Andrew Jardine, Lauren Bloomfield, Paul Effler. Long COVID in a highly vaccinated population infected during a SARS-CoV-2 Omicron wave – Australia, 2022. medRxiv 2023.08.06.23293706; doi: https://doi.org/10.1101/2023.08.06.23293706 https://www.medrxiv.org/content/10.1101/2023.08.06.23293706v1.full-text (Full text)

A retrospective cohort analysis leveraging augmented intelligence to characterize long COVID in the electronic health record: A precision medicine framework

Abstract:

Physical and psychological symptoms lasting months following an acute COVID-19 infection are now recognized as post-acute sequelae of COVID-19 (PASC). Accurate tools for identifying such patients could enhance screening capabilities for the recruitment for clinical trials, improve the reliability of disease estimates, and allow for more accurate downstream cohort analysis.

In this retrospective cohort study, we analyzed the EHR of hospitalized COVID-19 patients across three healthcare systems to develop a pipeline for better identifying patients with persistent PASC symptoms (dyspnea, fatigue, or joint pain) after their SARS-CoV-2 infection. We implemented distributed representation learning powered by the Machine Learning for modeling Health Outcomes (MLHO) to identify novel EHR features that could suggest PASC symptoms outside of typical diagnosis codes. MLHO applies an entropy-based feature selection and boosting algorithms for representation mining. These improved definitions were then used for estimating PASC among hospitalized patients.

30,422 hospitalized patients were diagnosed with COVID-19 across three healthcare systems between March 13, 2020 and February 28, 2021. The mean age of the population was 62.3 years (SD, 21.0 years) and 15,124 (49.7%) were female.

We implemented the distributed representation learning technique to augment PASC definitions. These definitions were found to have positive predictive values of 0.73, 0.74, and 0.91 for dyspnea, fatigue, and joint pain, respectively.

We estimated that 25 percent (CI 95%: 6-48), 11 percent (CI 95%: 6-15), and 13 percent (CI 95%: 8-17) of hospitalized COVID-19 patients will have dyspnea, fatigue, and joint pain, respectively, 3 months or longer after a COVID-19 diagnosis. We present a validated framework for screening and identifying patients with PASC in the EHR and then use the tool to estimate its prevalence among hospitalized COVID-19 patients.

Source: Strasser ZH, Dagliati A, Shakeri Hossein Abad Z, Klann JG, Wagholikar KB, Mesa R, Visweswaran S, Morris M, Luo Y, Henderson DW, Samayamuthu MJ; Consortium for Clinical Characterization of COVID-19 by EHR (4CE); Omenn GS, Xia Z, Holmes JH, Estiri H, Murphy SN. A retrospective cohort analysis leveraging augmented intelligence to characterize long COVID in the electronic health record: A precision medicine framework. PLOS Digit Health. 2023 Jul 25;2(7):e0000301. doi: 10.1371/journal.pdig.0000301. PMID: 37490472; PMCID: PMC10368277. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10368277/ (Full text)