Canadian contributions to research on neglected tropical diseases
Bibliographic record
Abstract
BACKGROUND: The World Health Organization's (WHO) Neglected Tropical Disease (NTD) Road Map for 2021-2030 was recently endorsed by all member states at the World Health Assembly in November 2020. Although only 3 of the 20 NTDs are endemic in Canada (i.e., echinococcosis, rabies, and scabies), the Canadian research community has contributed to advancing the knowledge base of all 20 NTDs. Previous research comprehensively detailed Canadian research on 11 NTDs between 1950 and 2010 using a network analysis approach. The specific objective of the present analysis was to update the publication record over the last decade (2010-2019) to include all 20 NTDs. MATERIALS AND METHODS: A bibliometric analysis was conducted in Scopus and Web of Science databases (for English or French articles published between January 1, 2010 and December 31, 2019) using appropriate search terms for each of the 20 NTDs and where at least 1 of the authors had a Canadian institution address. A 21st search was added to include publications including multiple NTDs or a discussion of NTDs in general. Following assessment of inclusion and exclusion criteria, 2 reviewers independently screened all abstracts, with discordant observations rereviewed to arrive at an agreement. Duplicates were removed. RESULTS: A total of 1,790 publications were retrieved (1,738 with a disease-specific NTD focus and 52 with a general NTD focus, resulting in 1,659 unique publications), giving an average of over 160 articles per year. Over 80% were classified as full-length research articles. The top 3 journals in terms of frequency were PLOS Neglected Tropical Diseases, PLOS ONE, and the American Journal of Tropical Medicine and Hygiene. Authors' institutions were from all Canadian provinces. While all 20 NTDs were addressed in these publications, the 5 most commonly studied were leishmaniasis, dengue fever and chikungunya, Chagas disease, soil-transmitted helminthiases, and rabies. CONCLUSIONS: Canadian researchers across the country have contributed to the evidence base of all 20 NTDs, publishing an average of over 160 publications per year between 2010 and 2019. As WHO NTD Road Map 2021-2030 rolls out globally, the Canadian research community, in collaboration with its partners and in solidarity with people living in vulnerable circumstances in endemic regions worldwide, is well positioned to meet future research challenges so that the goal of eliminating the disease burden attributable to NTDs can be achieved.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.008 |
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; both teacher heads agree on what is shown here.
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".