Epidemiological characteristics of major respiratory infectious diseases in Baiyin, China, from 2014 to 2023: a descriptive epidemiological study
Bibliographic record
Abstract
OBJECTIVE: To analyse temporal trends of respiratory infectious diseases (RIDs) in Baiyin City from 2014 to 2023, aiming to explore the epidemiological patterns of these diseases (tuberculosis, scarlet fever, pertussis, measles, influenza, mumps, varicella and rubella) and provide evidence for developing effective prevention and control strategies. DESIGN AND SETTING: A descriptive epidemiological study was conducted to analyse the incidence of tuberculosis, scarlet fever, pertussis, measles, influenza, mumps, varicella and rubella in Baiyin City, China, from 2014 to 2023, using data from the national notifiable disease reporting system. PARTICIPANTS: All reported cases of eight notifiable RIDs in Baiyin City between 2014 and 2023 were included in the analysis. Data were categorised by age and sex. METHODS: Joinpoint Regression Software was employed to estimate both the annual percentage change in incidence and the average annual percentage change, facilitating a phased comparison of incidence trends. RESULTS: Between 2014 and 2023, the annual incidence of major bacterial RIDs (tuberculosis, scarlet fever and pertussis) in Baiyin City fluctuated between 52.69 and 87.94 per 100 000 population, demonstrating an overall declining trend. Specifically, the annual decrease rates for the age groups of 0-14 years, 15-59 years and ≥60 years were 11.62% (95% CI -20.26% to -2.16%), 6.44% (95% CI -10.37% to -2.46%) and 5.15% (95% CI -9.12% to -1.07%), respectively. The annual incidence of major viral RIDs (measles, influenza, mumps, varicella and rubella) fluctuated between 111.70 per 100 000 and 541.12 per 100 000. No significant temporal trend was observed for major viral RIDs in Baiyin City. With the exception of pertussis, measles and rubella, the overall incidence rate was significantly higher in males than in females (p<0.01). The major viral RIDs predominantly affected children aged 0-14 years, while the major bacterial RIDs were primarily observed in individuals aged 60 years and older. CONCLUSION: From 2014 to 2023, the annual incidence of major bacterial RIDs in Baiyin City showed an overall decline, mainly due to a reduction in tuberculosis incidence, whereas the annual incidence of major viral RIDs fluctuated and rose sharply in 2023. The overall incidence of both major bacterial and viral RIDs was consistently higher in males, with major viral RIDs occurring predominantly in children aged 0-14 years and major bacterial RIDs being more common in older adults aged ≥60 years. Further efforts are needed to monitor the epidemiological patterns and develop strategies to reduce the incidence of major viral RIDs, particularly among children aged 0-14 years.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".