Bibliographic record
Abstract
Oliver Brady and colleagues (May, 2017)1Brady OJ Slater HC Pemberton-Ross P et al.Role of mass drug administration in elimination of Plasmodium falciparum malaria: a consensus modelling study.Lancet Glob Health. 2017; 5: e680-e687Summary Full Text Full Text PDF PubMed Scopus (69) Google Scholar collaborated with independent modelling groups and reached consensus on a few non-obvious points related to malaria elimination, one of which we find difficult to agree with. They recommend that, in areas close to elimination thresholds, mass drug administration (MDA) is most effective when conducted during the nadir of malaria transmission and prevalence. If the desired outcome of MDA is minimal transmission, the proposed timing during the dry season might be biologically plausible, but it is unlikely to result in success. Unsurprisingly, all modelling groups agree that coverage is essential for success; coverage during the malaria season is critical. MDA during the nadir of malaria transmission only works if the population does not change between administration and malaria transmission season. Under the non-ideal, real-life conditions in which MDA takes place, continued human migration over the months following MDA will reduce the effective coverage below the lower limit of 80% stated by Brady and colleagues as crucial for success. In western Cambodia, roughly a quarter of the human population changes location between the dry and rainy seasons. Our experience during MDA in west Africa was that young people return to their villages to help with planting and harvesting.2von Seidlein L Walraven G Milligan PJ et al.The effect of mass administration of sulfadoxine-pyrimethamine combined with artesunate on malaria incidence: a double-blind, community-randomized, placebo-controlled trial in The Gambia.Trans R Soc Trop Med Hyg. 2003; 97: 217-225Summary Full Text PDF PubMed Scopus (69) Google Scholar Seasonal migration is an important factor to consider during MDA plans, because high coverage of at-risk groups, such as farm and forest workers, is particularly urgent. The asymptomatic reservoir of plasmodium infections is not homogeneously distributed within villages, and foci of transmission could persist. MDA during the dry season might be the most practicable option, and all models have suggested that it has the best chance of interruption of local transmission. However, if this timing of MDA is adopted, then a strategy for the identification and treatment of subsequent migrants into the affected areas will probably be necessary. This course of action highlights the need for empirical data, which will not always support the expectations of modellers, not even multiple modelling groups. We declare no competing interests. Role of mass drug administration in elimination of Plasmodium falciparum malaria: a consensus modelling studyMass drug administration has the potential to reduce transmission for a limited time, but is not an effective replacement for existing vector control. Unless elimination is achieved, mass drug administration has to be repeated regularly for sustained effect. Full-Text PDF Open AccessModel citizen – Authors' replyTom Peto and colleagues point out, reasonably, that the effect of mass drug administration (MDA) on malaria could be affected substantially by patterns of human movement, and that our Article1 does not consider the effects of the specific patterns of movement they observed in Cambodia and west Africa. The purpose of our Article1 was to derive general results about the possible effect of MDA and to test how robust these are to the assumptions in different models, so we avoided assumptions about population movement that are specific to any particular place. Full-Text PDF Open Access
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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 | 0.005 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.409 | 0.248 |
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".