1. Introduction
Calculations of disease burden of COVID-19 are used to allocate scarce resources, and generally focus on death and acute illness which are more common in the elderly [
[1]- Undurraga E.A.
- Chowell G.
- Mizumoto K.
COVID-19 case fatality risk by age and gender in a high testing setting in Latin America: Chile, March–August 2020.
]; thus older patients are prioritized for interventions such as vaccination. Less attention is paid to ‘long-COVID’ or long-term morbidity which follows COVID-19 infection in 10% of cases, of which 80% are female
2: this translates to 16% of females and 4% of males.
Parallels have been drawn between long-COVID and chronic fatigue syndrome, CFS [
[2]As their numbers grow, COVID-19 “Long Haulers” stump experts.
]. Post-COVID and CFS are both postinfectious syndromes [
[3]- Bansal AS
- Bradley AS
- Bishop KN
- Kiani-Alikhan S
- Ford B
Chronic fatigue syndrome, the immune system and viral infection.
] whose most common symptoms are fatigue, muscle and body aches, and difficulty concentrating [
[2]As their numbers grow, COVID-19 “Long Haulers” stump experts.
,
]; they also both tend to strike women. Significantly, although CFS has been known for decades it remains poorly understood and medically neglected [
[2]As their numbers grow, COVID-19 “Long Haulers” stump experts.
,
[5]- Dimmock ME Mirin AA
- Jason LA
Estimating the disease burden of ME/CFS in the United States and its relation to research funding.
]. Diagnosis, treatment and services are not easily accessible even to severe cases; little specific treatment is available; and research is sparsely funded relative to the disease burden [
[5]- Dimmock ME Mirin AA
- Jason LA
Estimating the disease burden of ME/CFS in the United States and its relation to research funding.
]. Much of this also is true for long-COVID, whose prevention should thus be a public health priority.
In addition to CFS-type symptoms, many or most COVID-19 cases have clinical sequelae such as damage to the heart [
[6]- Puntmann VO
- Carerj ML
- Wieters I
- Fahim M
- Arendt C
- Hoffmann J
- et al.
Outcomes of cardiovascular magnetic resonance imaging in patients recently recovered from coronavirus disease 2019 (COVID-19).
] and lungs [][
[7]The Writing Committee for the COMEBAC Study Group
Four-month clinical status of a cohort of patients after hospitalization for COVID-19.
], even in those whose symptoms were otherwise mild. This damage may increase mortality risk years or decades later, but has not yet been included in calculations of disease burden or even of mortality.
In this paper I establish a plausible range for total morbidity burden per COVID-19 case that is attributable to CFS-type symptoms; to immediate death; and to delayed death. By doing so I inform allocators of scarce resources and suggest avenues for future research.
4. Discussion
This paper shows that under all but the most optimistic conditions, acute case fatality is likely to contribute only a small share of total COVID-19 morbidity. In most models total burden fell heavily on females and the young. Rather than focusing solely on mortality, allocators of scarce resources should consider all sources of morbidity.
Rather than give a single estimate of the contribution of acute case fatality to total COVID-19 morbidity, this paper provides a plausible range. It is likely that the truth will contain elements of all three models: chronic CFS-type symptoms of varying severity which may resolve, plus elevated mortality in those survivors or others. In determining which scenario is closest to the truth, researchers should establish long-COVID incidence, both overall and in specific populations; its sex ratio; and its clinical course, which may include remission, death, or some mix.
Our model is limited by variation in the estimated incidence and severity of long-COVID and case fatality, as well as their association with population characteristics. Many of these associations, such as that between long-COVID and female gender, are poorly studied; and all have necessarily short followup. However, our model can be easily updated as new data become available.
Since for each age and sex category DALY due to a given cause are computed by multiplying incidence, duration and disability weight, multiplicative changes in each of these are interchangeable. That is, reducing the incidence of long-COVID by half in a given group would have the same effects as halving its disability weight in that group: reducing the total burden of disease, with the largest reduction being found in young people. For example, based on Rubin's data [
[2]As their numbers grow, COVID-19 “Long Haulers” stump experts.
] our models assume that 80% of long-COVID patients are female: if the difference is smaller (for example, due to the predominance of males among COVID-19 myocarditis patients) [
[10]- Sawalha K
- Abozenah M
- Kadado AJ
- Battisha A
- Al-Akchar M
- Salerno C
- et al.
Systematic review of COVID-19 related myocarditis: insights on management and outcome.
] the population-level burden for a given symptom severity and incidence will move towards the models of ‘mild symptoms’ for females and ‘severe symptoms’ for males.
Significant variation exists in estimates of long-COVID incidence, with surveys in the UK estimating its incidence to be as high as 35% of adults and 12% of schoolchildren [
[11]COVID-19 schools infection survey, England: prevalence of ongoing symptoms following coronavirus (COVID-19) infection in school pupils and staff: July 2021.
], or as low as 1.5% of the general population [
[12]- Ayoubkhani D;
- Pawelek P;
- Bosworth M.
Prevalence of ongoing symptoms following coronavirus (COVID-19) infection in the UK: Estimates of the prevalence of self-reported "long COVID" and associated activity limitation, using UK Coronavirus (COVID-19) Infection Survey data.
]. Children, in particular, are not well studied: and because this group has many healthy years to lose, small differences in estimated incidence, severity and duration of long-COVID translate to large differences in estimated outcomes. More generally, estimated long-COVID incidence depends on study setting (population age and comorbidities, reporting of symptoms by self or others, time and type of followup) as well as artifact (incomplete response.) The 10% estimate used here is near the middle of the estimated range, but likely hides significant between-group variation.
However, it does appear that long-COVID risk increases with patient age and/or with severity of the initial infection. Persistent symptoms have been reported in about a third [
[11]COVID-19 schools infection survey, England: prevalence of ongoing symptoms following coronavirus (COVID-19) infection in school pupils and staff: July 2021.
,
[13]- Logue JK
- Franko NM
- McCulloch DJ
- McDonald D
- Magedson A
- Wolf CR
- et al.
Sequelae in adults at 6 months after COVID-19 infection.
] of adults, including some whose initial infection was asymptomatic; and in half, or more than half, of adults who had been hospitalized [
[7]The Writing Committee for the COMEBAC Study Group
Four-month clinical status of a cohort of patients after hospitalization for COVID-19.
,
[14]- Carfì A
- Bernabei R
- Landi F
For the gemelli against COVID-19 post-acute care study group. persistent symptoms in patients after acute COVID-19.
]. Risk was lower in children, regardless of infection severity: 24% of children formerly hospitalized for COVID-19 had parent-reported persistent symptoms [
[15]- Osmanov IM
- Spiridonova E
- Bobkova P
- Gamirova A
- Shikhaleva A
- Andreeva M
- et al.
Risk factors for long covid in previously hospitalised children using the ISARIC Global follow-up protocol: A prospective cohort study.
], and between 2% and 5% [
[16]Results of the long-COVID survey among children in Israel.
] and 12% [
[11]COVID-19 schools infection survey, England: prevalence of ongoing symptoms following coronavirus (COVID-19) infection in school pupils and staff: July 2021.
] of all pediatric cases did. Risk was higher in older children, consistent with an age effect. If the risk and/or severity of long-COVID does in fact increase with age, burden of morbidity is likely to shift away from children and towards middle-aged adults, who would then combine a relatively high incidence of long-COVID with many healthy years to lose. The shape of the morbidity curve is likely to depend on precise age-specific incidence rates, as well as age-related variations in long-COVID symptom severity.
A related issue is that estimates of COVID-19 case fatality have steadily dropped [
[17]Why do COVID death rates seem to be falling?.
] since the beginning of the pandemic, for reasons which may include changes in patient demographics, improvements in treatment [
[17]Why do COVID death rates seem to be falling?.
], or artifact of improved ascertainment [
[18]Role of ascertainment bias in determining case fatality rate of COVID-19.
].Thus the current models likely overestimate morbidity due to death and thus share of morbidity borne by the old; and since case fatality is higher in males [
[1]- Undurraga E.A.
- Chowell G.
- Mizumoto K.
COVID-19 case fatality risk by age and gender in a high testing setting in Latin America: Chile, March–August 2020.
], of share of morbidity borne by males.
Secondly, our models used disability weights for CFS since none exist for long-COVID. However long-COVID has symptoms that CFS does not, leading to systematic underestimation of the true disability weight of long-COVID. For each additional symptom, the number of DALY lost per case at a given symptom severity increases such that the situation becomes similar to that for a higher symptom severity.
Thirdly, the shape of the long-COVID morbidity curve with age is sensitive to the clinical course of the disease. Under most situations the curve was U-shaped (morbidity high in young and old, lower in middle age) or L-shaped (morbidity highest in the young.) These were the situations if long-COVID caused lifelong disability that was other than mild; increased mortality; or both.
However, there was one model in which the mortality curve was J-shaped and burden of morbidity was borne by the elderly (the situation assumed by current public-health guidelines.) For this to occur, non-mild symptoms must be time-limited, resolving either spontaneously or due to medical advances. For either of these to occur, long-COVID would have to be atypical of postinfectious conditions such as CFS. Full recovery from these conditions is rare:[
[5]- Dimmock ME Mirin AA
- Jason LA
Estimating the disease burden of ME/CFS in the United States and its relation to research funding.
] most patients experience fluctuating symptoms, with periods of low and high functioning [
[9]CDC US. Myalgic encephalomyelitis/chronic fatigue syndrome: what is ME/CFS? In: Services HaH, editor.; 2018.
,
[19]- Adamowicz JL
- Caikauskaite I
- Friedberg F
Defining recovery in chronic fatigue syndrome: a critical review.
], and some deteriorate further. Furthermore ‘recovery’ is often defined relative to the disease state rather than relative to fully restored health: even those reported as recovered often have persistent disability [
[19]- Adamowicz JL
- Caikauskaite I
- Friedberg F
Defining recovery in chronic fatigue syndrome: a critical review.
]. Thus, while long-COVID patients may experience improvements in symptoms, it seems likely that some disability will remain.
It is also possible that medical advances will improve the long-COVID prognosis. This would require a significant change in current priorities: relative to its disease burden CFS is deprioritized for research funding [
[5]- Dimmock ME Mirin AA
- Jason LA
Estimating the disease burden of ME/CFS in the United States and its relation to research funding.
] and although it has been documented for almost a century, many patients have difficulty accessing diagnosis, treatment or services. The same is true for long-COVID [
]. Thus, while it is not impossible that long-COVID will become treatable, this scenario is unlikely under current priorities.
To conclude, these findings establish plausible outer bounds for the sex and age bias of total disease burden of COVID-19. In most situations, most morbidity is in female survivors and in young people. However, these estimates are imprecise and based on incomplete data. Future research should collect and publish better data to allow fair distribution of resources for prevention of COVID-19 infection; and decisionmakers should allocate those resources to minimize total morbidity, according to the best available knowledge.