ArticlePLoS neglected tropical diseases2021
Strengthening data collection for neglected tropical diseases: What data are needed for models to better inform tailored intervention programmes?
Article in PLoS neglected tropical diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.
- Associations of water contact frequency, duration, and activities with schistosome infection risk: A systematic review and meta-analysis.PLoS neglected tropical diseases · 2023Pooled it
- Integrated action for skin NTDs: Deconstructing transmission, addressing knowledge gaps, and championing one health strategies.Nature communications · 2026Review
- Modelling the cost of engage & treat and test & treat strategies towards the elimination of lymphatic filariasis in Ghana.PLoS neglected tropical diseases · 2024Article
- Efficacy of Single-Dose Azithromycin for Ocular Chlamydial Infection: A Longitudinal Study.The American journal of tropical medicine and hygiene · 2024Article
- Knowledge of tropical diseases and response capabilities of healthcare providers in Kaduna State, Nigeria.International health · 2024Article
- Article
- "Our interventions are still here to support communities during the pandemic": Resuming mass drug administration for neglected tropical diseases after COVID-19 implementation delays.PLoS neglected tropical diseases · 2023Article
- A game-theoretic model of lymphatic filariasis prevention.PLoS neglected tropical diseases · 2022Article
- How modelling can help steer the course set by the World Health Organization 2021-2030 roadmap on neglected tropical diseases.Gates open research · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 8 institutions in 4 countries.
Funding
Abstract
Locally tailored interventions for neglected tropical diseases (NTDs) are becoming increasingly important for ensuring that the World Health Organization (WHO) goals for control and elimination are reached. Mathematical models, such as those developed by the NTD Modelling Consortium, are able to offer recommendations on interventions but remain constrained by the data currently available. Data collection for NTDs needs to be strengthened as better data are required to indirectly inform transmission in an area. Addressing specific data needs will improve our modelling recommendations, enabling more accurate tailoring of interventions and assessment of their progress. In this collection, we discuss the data needs for several NTDs, specifically gambiense human African trypanosomiasis, lymphatic filariasis, onchocerciasis, schistosomiasis, soil-transmitted helminths (STH), trachoma, and visceral leishmaniasis. Similarities in the data needs for these NTDs highlight the potential for integration across these diseases and where possible, a wider spectrum of diseases.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.