Evidence map›Paper›PMID 30917824›Full record

ArticleBMC medicine2019

Profiling the best-performing community medicine distributors for mass drug administration: a comprehensive, data-driven analysis of treatment for schistosomiasis, lymphatic filariasis, and soil-transmitted helminths in Uganda.

Goylette F Chami, Narcis B Kabatereine, Edridah M Tukahebwa

Open access · goldAbstract read
In one paragraph

Article in BMC medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 2 pooled it
2.2field-weighted citation impact, top 14% of its field
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 2 syntheses or guidelines pooled it, 18 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Helminthologia · 2026
    Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 2 countries.

Goylette F ChamiDepartment of Pathology, University of Cambridge, Tennis Ct. Rd., Cambridge, CB2 1QP, UK. gjc36@cam.ac.uk.ORCID 0000-0002-4653-0846
Narcis B KabatereineVector Control Division, Bilharzia and Worm Control Programme, Uganda Ministry of Health, Kampala, Uganda.
Edridah M TukahebwaVector Control Division, Bilharzia and Worm Control Programme, Uganda Ministry of Health, Kampala, Uganda.
Ministry of Health · UGUniversity of Cambridge · GB

Funding

Wellcome TrustWellcome Trust 083931/Z/07/ZWellcome Trust 100891/Z/13/Z
6 · The paper itself

Abstract

backgroundThe most prevalent neglected tropical diseases are treated through blanket drug distribution that is reliant on lay community medicine distributors (CMDs). Yet, treatment rates achieved by CMDs vary widely and it is not known which CMDs treat the most people.

methodsIn Mayuge District, Uganda, we tracked 6779 individuals (aged 1+ years) in 1238 households across 31 villages. Routine, community-based mass drug administration (MDA) was implemented for schistosomiasis, lymphatic filariasis, and soil-transmitted helminths. For each CMD, the percentage of eligible individuals treated (offered and ingested medicines) with at least one drug of praziquantel, albendazole, or ivermectin was examined. CMD attributes (more than 25) were measured, ranging from altruistic tendencies to socioeconomic characteristics to MDA-specific variables. The predictors of treatment rates achieved by CMDs were selected with least absolute shrinkage and selection operators and then analyzed in ordinary least squares regression with standard errors clustered by village. The influences of participant compliance and the ordering of drugs offered also were examined for the treatment rates achieved by CMDs.

resultsOverall, only 44.89% (3043/6779) of eligible individuals were treated with at least one drug. Treatment rates varied amongst CMDs from 0% to 84.25%. Treatment rate increases were associated (p value< 0.05) with CMDs who displayed altruistic biases towards their friends (13.88%), had friends who helped with MDA (8.43%), were male (11.96%), worked as fishermen/fishmongers (14.93%), and used protected drinking water sources (13.43%). Only 0.24% (16/6779) of all eligible individuals were noncompliant by refusing to ingest all offered drugs. Distributing praziquantel first was strongly, positively correlated (p value < 0.0001) with treatment rates for albendazole and ivermectin.

conclusionsThese findings profile CMDs who treat the most people during routine MDA. Criteria currently used to select CMDs-community-wide meetings, educational attainment, age, years as a CMD, etc.-were uninformative. Participant noncompliance and the provision of praziquantel before albendazole and ivermectin did not negatively impact treatment rates achieved by CMDs. Engaging CMD friend groups with MDA, selecting CMDs who practise good preventative health behaviours, and including CMDs with high-risk occupations for endemic infections may improve MDA treatment rates. Evidence-based guidelines are needed to improve the monitoring, selection, and replacement of CMDs during MDA.

Indexed as

Mass Drug AdministrationAdolescentAdultAgedAged, 80 and overAnimalsAntiparasitic AgentsChildChild, PreschoolCommunity MedicineDelivery of Health CareEfficiency, OrganizationalElephantiasis, FilarialFemaleHelminthiasisHumansAntiparasitic AgentsSoilAlbendazoleComplianceCoverageIvermectinLymphatic filariasisMass drug administrationPraziquantelSchistosomiasisSoil-transmitted helminthsSub-Saharan Africa

Identifiers

PMID30917824
PMCPMC6437990
OpenAlexW2942804477

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.