Community benefits of mass distribution of three types of dual-active-ingredient long-lasting insecticidal nets against malaria prevalence in Tanzania: evidence from a 3-year cluster-randomized controlled trial
Notice bibliographique
Résumé
Abstract Background Long-lasting insecticidal nets (LLINs) were once fully effective for the prevention of malaria; however, mosquitoes have developed resistance to pyrethroids, the main class of insecticides used on nets. Dual active ingredient LLINs (dual-AI LLINs) have been rolled out as an alternative to pyrethroid (PY)-only LLINs to counteract this. Understanding the minimum community usage at which these novel nets generate an effect that also benefits non-net users against malaria infection is vital for planning net distribution strategies and mobilization campaigns. Methods We conducted a secondary analysis of a 3-year randomized controlled trial (RCT) in 84 clusters in North-western Tanzania to evaluate the effectiveness of three dual-AI LLINs: pyriproxyfen and alpha(α)-cypermethrin (pyriproxyfen-PY), chlorfenapyr and α-cypermethrin (chlorfenapyr-PY), and the synergist piperonyl-butoxide and permethrin (PBO-PY) compared to α-cypermethrin only nets (PY-only). We measured malaria infection prevalence using 5 cross-sectional surveys between 2020 and 2022. We assessed net usage at the cluster level and malaria infection in up to two children aged between 6 months and 14 years in 45 households per cluster and compared infection prevalence between net users and non-users with the different net types and usage levels. Findings A total of 22,479 children from 12,654 households were tested for malaria using rapid diagnostic tests in January 2020, 2021, & 2022 and July 2020 & 2021. In all surveys combined, 23% (5,062/22,479) of children reported not using a net the night before the surveys. The proportion of non-net users was highest in the later surveys. Across all study arms and at each time point, users of nets had significantly lower malaria infection than non-users. Overall, malaria prevalence was 52% (2649/5062) among non-net users and 32% (5572/11845) among users (of any net). Among non-net users, community-level usage of >40% of dual-AI LLIN was significantly associated with protection against malaria infection: chlorfenapyr-PY (OR: 0.44 (95% CI: 0.27-0.71), p=0.0009), PBO-PY (OR: 0.55 (95% CI: 0.33-0.94), p=0.0277) and pyriproxyfen-PY (OR: 0.61 (95% CI: 0.37-0.99), p=0.0470) compared with non-users in clusters with >40% usage of PY-only LLINs. There was weak evidence of protection against malaria infection to non-net users in the chlorfenapyr-PY arm when community-level usage was ≤40% (OR: 0.65 (95% CI: 0.42-1.01), p=0.0528) compared to those living in clusters with >40% usage of pyrethroid-only LLINs. The study was limited to non-users which were defined as participants who did not sleep under any net the night before. This might not capture occasional net usage during the week. Conclusion Our study demonstrated that at a community usage of 40% or more of dual-AI LLINs, non-net users benefited from the presence of these nets. Noticeably, even when usage was ≤40% in the chlorfenapyr-PY arm, non-users were better protected than non-users in the higher coverage PY-only arm. The greater difference in malaria risk observed between users and non-users across all study arms indicates that nets play a crucial role in providing personal protection against malaria infection for the people using the net and that net usage needs to be maximized to realize the full potential of all nets. Funding Department for International Development, UK Medical Research Council, Wellcome Trust, and Department of Health and Social Care (#MR/R006040/1). The Bill and Melinda Gates Foundation via the Innovative Vector Control Consortium (IVCC).
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,008 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,004 | 0,005 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».