Respiratory epidemics and older people
Bibliographic record
Abstract
Coronavirus disease 2019 (COVID-19) has been particularly severe on older people. Past coronavirus epidemics namely Severe Acute Respiratory Syndrome and the Middle East Respiratory Syndrome have also been severe on older people. These epidemics lasted for only a limited period, however, and have proven short lived in the memories of both the public and public health systems. No lessons were learnt to mitigate the impact of future epidemics of such nature, on older people. This complacency we feel has claimed the lives of many older people during the current COVID-19 global epidemic. The nature of risks associated with acquiring infections and associated mortality among older people in respiratory epidemic situations are varied and of serious concern. Our commentary identifies demographic, biological, behavioural, social and healthcare-related determinants, which increase the vulnerability of older people to respiratory epidemics. We acknowledge that these determinants will likely vary between older people in high- and low-middle income countries. Notwithstanding these variations, we call for urgent action to mitigate the impact of epidemics on older people and preserve their health and dignity. Intersectoral programmes that recognise the special needs of older people and in unique contexts such as care homes must be developed and implemented, with the full participation and agreement of older people. COVID-19 has created upheaval, challenging humanity and threatening the lives, rights, and well-being of older people. We must ensure that we remain an age-friendly society and make the world a better place for all including older people.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".