ReviewPLoS neglected tropical diseases2015
Potential Biases in Estimating Absolute and Relative Case-Fatality Risks during Outbreaks.
Review in PLoS neglected tropical diseases, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 103 papers, 4 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
103 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- The Impact of Diagnostic Delays and Timeliness of Response on Ebola Disease outbreak-level case-fatality Ratios in Uganda (2000-2023): a Rapid Systematic Review and meta-analysis.Journal of epidemiology and global health · 2025Pooled it
- Decoding mpox: a systematic review and meta-analysis of the transmission and severity parameters of the 2022-2023 global outbreak.BMJ global health · 2025Pooled it
- Estimating case fatality risk of severe Yellow Fever cases: systematic literature review and meta-analysis.BMC infectious diseases · 2021Pooled it
- Key questions for modelling COVID-19 exit strategies.Proceedings. Biological sciences · 2020Pooled it
- Lower Mortality Associated With Preemptive Health System Resource Reallocation During COVID-19: A Longitudinal Study in 85 Countries.Disaster medicine and public health preparedness · 2026Article
- Robust Inverse Reconstruction of Time-Varying Transmission Rates Across Model Structures and Incidence Forms.Bulletin of mathematical biology · 2026Article
- The importance of playing the long game when it comes to pandemic surveillance.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Improving case fatality ratio estimates in ongoing pandemics through case-to-death time distribution analysis.Scientific reports · 2025Article
- Surveillance of SARS-CoV-2 prevalence from repeated pooled testing: application to Swiss routine data.Epidemiology and infection · 2024Article
- Estimates of SARS-CoV-2 Hospitalization and Fatality Rates in the Prevaccination Period, United States.Emerging infectious diseases · 2024Article
- Article
- Gender/Sex Disparities in the COVID-19 Cascade From Testing to Mortality: An Intersectional Analysis of Swiss Surveillance Data.International journal of public health · 2024Article
- Disease Burden of Meningitis Caused by Streptococcus pneumoniae Among Under-Fives in China: A Systematic Review and Meta-analysis.Infectious diseases and therapy · 2023Review
- Some principles for using epidemiologic study results to parameterize transmission models.medRxiv : the preprint server for health sciences · 2023Article
- A new method for accurate calculation of case fatality rates during a pandemic: Mathematical deduction based on population-level big data.Infectious medicine · 2023Article
- A new method for the joint estimation of instantaneous reproductive number and serial interval during epidemics.PLoS computational biology · 2023Article
- Evolution of the lethality due to SARS-CoV-2 in Spain according to age group and sex.Scientific reports · 2022Article
- Time-dependent risk of COVID-19 death with overwhelmed health-care capacity in Japan, 2020-2022.BMC infectious diseases · 2022Article
- A novel method to monitor COVID-19 fatality rate in real-time, a key metric to guide public health policy.Scientific reports · 2022Article
- Quantitatively evaluate the impact of domestic aviation control measures on the spread of COVID-19 in China.Scientific reports · 2022Article
43 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
Abstract
Estimating the case-fatality risk (CFR)-the probability that a person dies from an infection given that they are a case-is a high priority in epidemiologic investigation of newly emerging infectious diseases and sometimes in new outbreaks of known infectious diseases. The data available to estimate the overall CFR are often gathered for other purposes (e.g., surveillance) in challenging circumstances. We describe two forms of bias that may affect the estimation of the overall CFR-preferential ascertainment of severe cases and bias from reporting delays-and review solutions that have been proposed and implemented in past epidemics. Also of interest is the estimation of the causal impact of specific interventions (e.g., hospitalization, or hospitalization at a particular hospital) on survival, which can be estimated as a relative CFR for two or more groups. When observational data are used for this purpose, three more sources of bias may arise: confounding, survivorship bias, and selection due to preferential inclusion in surveillance datasets of those who are hospitalized and/or die. We illustrate these biases and caution against causal interpretation of differential CFR among those receiving different interventions in observational datasets. Again, we discuss ways to reduce these biases, particularly by estimating outcomes in smaller but more systematically defined cohorts ascertained before the onset of symptoms, such as those identified by forward contact tracing. Finally, we discuss the circumstances in which these biases may affect non-causal interpretation of risk factors for death among cases.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.