Dataset Information

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

ABSTRACT: Early reports suggest the fatality rate from COVID-19 varies greatly across countries, but non-random testing and incomplete vital registration systems render it impossible to directly estimate the infection fatality rate (IFR) in many low- and middle-income countries. To fill this gap, we estimate the adjustments required to extrapolate estimates of the IFR from high-income to lower-income regions. Accounting for differences in the distribution of age, sex and relevant comorbidities yields substantial differences in the predicted IFR across 21 world regions, ranging from 0.11% in Western Sub-Saharan Africa to 1.07% for high-income Asia Pacific. However, these predictions must be treated as lower bounds in low- and middle-income countries as they are grounded in fatality rates from countries with advanced health systems. To adjust for health system capacity, we incorporate regional differences in the relative odds of infection fatality from childhood respiratory syncytial virus. This adjustment greatly diminishes but does not entirely erase the demography-based advantage predicted in the lowest income settings, with regional estimates of the predicted COVID-19 IFR ranging from 0.37% in Western Sub-Saharan Africa to 1.45% for Eastern Europe.

SUBMITTER: Ghisolfi S

PROVIDER: S-EPMC7482102 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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

Ghisolfi Selene S Almås Ingvild I Sandefur Justin C JC von Carnap Tillman T Heitner Jesse J Bold Tessa T

BMJ global health 20200901 9

Early reports suggest the fatality rate from COVID-19 varies greatly across countries, but non-random testing and incomplete vital registration systems render it impossible to directly estimate the infection fatality rate (IFR) in many low- and middle-income countries. To fill this gap, we estimate the adjustments required to extrapolate estimates of the IFR from high-income to lower-income regions. Accounting for differences in the distribution of age, sex and relevant comorbidities yields subs ...[more]

PMID: 32912856

Similar Datasets

Project description:BackgroundNeurological involvement in Coronavirus disease-2019 (COVID-19) is widely recognized. However, the role of pre-existing neurological comorbidities in modulating COVID-19-related mortality still remains unclear. This cohort study evaluates the COVID-19-related case fatality rate (CFR) of patients with pre-existing neurological diseases.MethodsWe retrospectively evaluated all patients consecutively admitted to our hospital with a diagnosis of COVID-19 between March and April 2020. We used a multivariate regression analysis to estimate the association between pre-existing neurological diseases and COVID-19-related mortality. Then, we compared the CFR and survival curves of two cohorts (patients suffering vs. those not suffering from pre-existing neurological disease), matched trough the propensity score (PS). Age and other comorbidities were considered for PS calculation. We applied a 1:1 matching for the entire neurological cohort and, separately, for cerebrovascular, neurodegenerative, and other neurological diseases.ResultsAmong 332 patients, 75 (22.6%) were affected by pre-existing neurological disease (n = 29 cerebrovascular, n = 26 neurodegenerative, n = 20 others). From the multivariate regression analysis, they resulted with a significant increase of COVID-19-related mortality (OR:2.559; 95%CI 1.181-5.545; p < 0.017). From the cohort analysis, CFR resulted 2-fold higher in patients with neurological disease (48.0% vs. 24.0%; p = 0.002). CFR was significantly higher in patients with neurodegenerative diseases compared to matched individuals (73.9% vs. 39.1%; p = 0.017), while CFR increase in patients with cerebrovascular diseases did not reach statistical significance (48.3% vs. 41.4%; p = 0.597).ConclusionsPre-existing neurological comorbidities, in particular neurodegenerative diseases, increase significantly COVID-19-related case fatality, indicating a clear priority for viral screening, access to care facilities and vaccination in these populations.

Dataset Information

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

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets