Prevalence of aeroallergen sensitization in a polluted and industrialized area: a pilot study in South Africa’s Vaal Triangle
Bibliographic record
Abstract
This pioneering study evaluates the prevalence of aeroallergens reactivity among atopic populations living in the Vaal Triangle Airshed Priority Area (VTAPA), South Africa. A total of 138 volunteers (51 males and 87 females), of African, colored, white, and Asian ethnicity, and with a mean (range) age of 22 (18-56) years were participating in the study. The study was conducted on the North-West University (NWU) campus in Vanderbijlpark/VTAPA. The International Study of Asthma and Allergies in Childhood questionnaire was utilized for pre-screening to identify individuals with probable allergic dispositions. Subsequently, skin prick testing was conducted using commercial aeroallergen extracts for all confirmed participants with allergy symptoms. One hundred six participants were clinically diagnosed with pollen and fungal spore allergies. The highest allergy prevalence was attributed to Cynodon dactylon ((L.) Pers) (Bermuda grass) (41.5%), followed by Lolium perenne (L.) (ryegrass), grass mix, and Zea mays (L.) (maize) (31.1%), respectively. Moreover, among the tree allergens, Olea (L.) (olive tree) was the most prevalent allergen (20; 18.8%), followed by Platanus (L.) (plane tree) (18; 16.9%). Among the weeds, 16 (15.1%) participants were allergic to the weed mix (Artemisia (L.) (wormwood), Chenopodium (Link) (goosefoot), Salsola (L.) (saltwort), Plantago (L.) (plantain), and 11 (10.3%) to Ambrosia (L.) (ragweed)). Regarding the fungal spores, Alternaria (Fr.) (9; 8.5%) followed by Cladosporium (Link) (5; 4.7%) had the highest skin sensitivity. In this pilot study, our findings provide insights into the prevalence of allergic responses in the study population-underlining the strong impact of allergens of exotic plants-and contribute to the existing aerobiological data in South Africa.
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) | 0.000 | 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".