REVIEW ARTICLE: EPIDEMIOLOGY OF COVID’19
Bibliographic record
Abstract
Purpose: To carefully review and understand the cause, distribution, progression, determinants and deterrents of COVID-19. Methodology: Peer reviewed data relevant to study was collected from PubMed, Google Scholar, WHO database, Research gate and Wikipedia based on pre-set inclusion and exclusion criteria. Findings: Covid-19 is a principally respiratory illness caused by the novel Corona Virus (SARS-CoV2). It started as an epidemic in Wuhan, China in December 2019, became a pandemic in March 2020 and have now infected almost 22 million people over 216 countries causing about three-quarter of a million deaths. It spreads primarily through droplets, aerosols or contact with contaminated surfaces. Illness is usually mild to moderate flu-like symptoms but can be asymptomatic as well as severe especially in patients with underlying co-morbidities. Testing can either be antigen based through polymerase chain reaction or antibody based. Treatment is generally supportive while the efficacy of diverse pharmacological remains controversial. Public education, early diagnosis and isolation, restriction of gatherings and movements have been the main method used worldwide to tackle this outbreak. Unique contribution to theory, practice and policy: Emphasizes the infectivity of SARS-CoV2 virus and need for health practitioners and general public to adhere strictly to preventive measures in order to avert a global second wave of the pandemic. Conclusion: COVID-19 is an infectious disease that have rapidly spread from china to the world at large. A lot of efforts and policies have been made to prevent and control its spread. There’s need to adhere to guidelines in order to reduce spread and subsequent mortality especially amongst vulnerable groups. As many countries commence protocols to re-open, there’s need to do so in line with lessons learnt during this outbreak to avoid a more devastating second wave.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.018 | 0.005 |
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 source (direct Gemma or distilled Codex), 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".