Predicted COVID-19 fatality rates based on age, sex, comorbidities, and health system capacity

Ghisolfi, Selene; Almås, Ingvild; Sandefur, Justin; Carnap, Tillman von; Heitner, Jesse; Bold, Tessa

doi:10.1101/2020.06.05.20123489

Cited by 36 publications

(50 citation statements)

References 17 publications

(44 reference statements)

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“…Anticipating the trajectory of ongoing outbreaks in SSA requires considering variability in known drivers, and how they may interact to increase or decrease risk across populations in SSA and relative to non-SSA settings ( Figure 1 ). For example, while most countries in SSA have ‘young’ populations, suggesting a decreased burden (since SARS-CoV-2 morbidity and mortality increase with age 2 - 4 ), prevalent infectious and non-communicable comorbidities may counterbalance this demographic ‘advantage’ 14 , 17 - 19 . Similarly, SSA countries have health systems that vary greatly in their infrastructure, and dense, resource-limited urban populations may have fewer options for social distancing 20 .…”

Section: Factors Expected To Increase and Decrease Sars-cov-2 Risk Inmentioning

confidence: 99%

High variation expected in the pace and burden of SARS-CoV-2 outbreaks across sub-Saharan Africa

Rice

Annapragada

Baker

et al. 2020

Preprint

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A surprising feature of the SARS-CoV-2 pandemic to date is the low burdens reported in sub-Saharan Africa (SSA) countries relative to other global regions. Potential explanations (e.g., warmer environments [1], younger populations [2,3,4]) have yet to be framed within a comprehensive analysis accounting for factors that may offset the effects of climate and demography. Here, we synthesize factors hypothesized to shape the pace of this pandemic and its burden as it moves across SSA, encompassing demographic, comorbidity, climatic, healthcare and intervention capacity, and human mobility dimensions of risk. We find large scale diversity in probable drivers, such that outcomes are likely to be highly variable among SSA countries. While simulation shows that extensive climatic variation among SSA population centers has little effect on early outbreak trajectories, heterogeneity in connectivity is likely to play a large role in shaping the pace of viral spread. The prolonged, asynchronous outbreaks expected in weakly connected settings may result in extended stress to health systems. In addition, the observed variability in comorbidities and access to care will likely modulate the severity of infection: We show that even small shifts in the infection fatality ratio towards younger ages, which are likely in high risk settings, can eliminate the protective effect of younger populations. We highlight countries with elevated risk of slow pace, high burden outbreaks. Empirical data on the spatial extent of outbreaks within SSA countries, their patterns in severity over age, and the relationship between epidemic pace and health system disruptions are urgently needed to guide efforts to mitigate the high burden scenarios explored here.

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Section: Factors Expected To Increase and Decrease Sars-cov-2 Risk Inmentioning

confidence: 99%

High variation expected in the pace and burden of SARS-CoV-2 outbreaks across sub-Saharan Africa

Rice

Annapragada

Baker

et al. 2020

Preprint

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“…The COVID-19 mortality rate in children under 19 years old in Sergipe is 37 times higher than that reported from the United States and the UK (0.13 deaths per 100 000 population under 19 years old for both) and 3.7 times higher than in other areas of Brazil (1.3 deaths per 100 000 population under 19 years old) [8,13,14] UNICEF reported scarce data on mortality among children and adolescents from low-and middle-income countries due to the later emergence of the COVID-19 pandemic in these settings and lack of resources to conduct epidemiological and clinical studies [15] However, differences in fatality rates from COVID-19 by age between low-, middle-and high-income countries are predicted [16] Although Sergipe State has an adequate number of adult ICU beds and deployed a further 88 adults' ICU beds since the start of the pandemic, Sergipe has a 41% deficit in paediatric ICU beds [11,17], with only seven in its neonatal ICU, and no additional paediatric ICU beds deployed during the epidemic [9] Moreover, none of the paediatric ICU beds are ring-fenced for COVID-19 and children often experience long waiting times before ICU admission. Another Brazilian study during the pandemic also described similar difficulties accessing ICU beds for pregnant women [18] Seven of the deaths occurred in neonates and infants with neonatal-related problems.…”

Section: Discussionmentioning

confidence: 99%

“…UNICEF reported scarce data on mortality among children and adolescents from low‐ and middle‐income countries due to the later emergence of the COVID‐19 pandemic in these settings and lack of resources to conduct epidemiological and clinical studies [15] However, differences in fatality rates from COVID‐19 by age between low‐, middle‐ and high‐income countries are predicted [16]…”

Section: Discussionmentioning

confidence: 99%

Coronavirus disease‐19 deaths among children and adolescents in an area of Northeast, Brazil: why so many?

Lopes

Vieira

Porto

et al. 2020

Tropical Med Int Health

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objective To describe COVID-19 deaths among children and adolescents in Sergipe, Brazil. methods Ecological study of all COVID-19 reported cases and deaths occurring in children and adolescents < 19 years of age in Sergipe reported by the health surveillance and mortality information systems of Sergipe's Health Secretary and hospital records. results Of 37 deaths of children < 19 years old were reported up to 30 September 2020, corresponding to 4.87 deaths for 100 000 population < 19 years old. Most deaths occurred among infants (44.1/100 000), and this age group had the highest case fatality rate (15.3 %). Most children had comorbidities such as chronic neurological diseases (n = 7; 19%) and prematurity (n = 4; 11%). Most children who died (n = 18; 49%) were not admitted to intensive care units (ICUs). conclusion COVID-19 mortality in children and adolescents in Sergipe was higher than in other Brazilian states and in high-income countries. A large proportion of the deaths occurred among children with comorbidities and a minority of children were admitted to ICU, reflecting the limited provision of such beds in the State. Newborns and infants are a high-risk group that must have priority in health public policy.

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“…The copyright holder for this this version posted August 20, 2020. ; https://doi.org/10.1101/2020.08.10.20171454 doi: medRxiv preprint very crude estimate of I 0 ≈ 1400 can be obtained given approximately an average of 2 deaths per day (2nd Aug → 9th Aug), an infection fatality rate of η ≈ 0.01, 23,27 and 1/γ = 7 days. The rate of decline of infections is estimated to have a wide range ρ e = 0.01 → 0.08 29 , so taking a central estimate of ρ e = 0.045 (R e = 0.685, 1/γ = 7 days), we arrive at mean extinction time prediction of 148 ± 29 days (95% CI: (106, 217) days); if the rate of decline is increased to ρ e = 0.086 (R e = 0.4) then this reduces to 85 ± 15 days (95% CI: (63, 121) days).…”

Section: Discussionmentioning

confidence: 99%

A simple stochastic theory of extinction shows rapid elimination of a Sars-like pandemic

Khatri

2020

Preprint

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Worldwide, we are currently in an unprecedented situation with regard to the SARS-Cov-2 epidemic, where countries are using isolation and lock-down measures to control the spread of infection. This is a scenario generally not much anticipated by previous theory, and in particular, there has been little attention paid to the question of extinction as a means to eradicate the virus; the prevailing view appears to be that this is unfeasible without a vaccine. We use a simple well-mixed stochastic SIR model as a basis for our considerations, and calculate a new result, using branching process theory, for the distribution of times to extinction. Surprisingly, the distribution is an extreme value distribution of the Gumbel type, and we show that the key parameter determining its mean and standard deviation is the expected rate of decline Re = γ(1-Re) of infections, where γ is the rate of recovery from infection and Re is the usual effective reproductive number. The result also reveals a critical threshold number of infected I&#134 = 1/(1-Re), below which stochastic forces dominate and need be considered for accurate predictions. As this theory ignores migration between populations, we compare against a realistic spatial epidemic simulator and simple stochastic simulations of sub-divided populations with global migration, to find very comparable results to our simple predictions; in particular, we find global migration has the effect of a simple upwards rescaling of Re with the same Gumbel extinction time distribution we derive from our non-spatial model. Within the UK, using recent estimates of I0≈37000 infected and Re= 0.9, this model predicts a mean extinction time of 616±90 days or approximately ~2 years, but could be as short as 123±15 days, or roughly 4 months for Re = 0.4. Globally, the theory predicts extinction in less than 200 days, if the reproductive number is restricted to Re < 0.5. Overall, these results highlight the extreme sensitivity of extinction times when Re approaches 1 and the necessity of reducing the effective reproductive number significantly (Re<≈0.5) for relatively rapid extinction of an epidemic or pandemic.

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Predicted COVID-19 fatality rates based on age, sex, comorbidities, and health system capacity

Cited by 36 publications

References 17 publications

High variation expected in the pace and burden of SARS-CoV-2 outbreaks across sub-Saharan Africa

High variation expected in the pace and burden of SARS-CoV-2 outbreaks across sub-Saharan Africa

Coronavirus disease‐19 deaths among children and adolescents in an area of Northeast, Brazil: why so many?

A simple stochastic theory of extinction shows rapid elimination of a Sars-like pandemic

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