Contextual determinants of mass drug administration performance: Modelling fourteen years of lymphatic filariasis treatments in West Africa.


Journal

PLoS neglected tropical diseases
ISSN: 1935-2735
Titre abrégé: PLoS Negl Trop Dis
Pays: United States
ID NLM: 101291488

Informations de publication

Date de publication:
02 2023
Historique:
received: 09 06 2022
accepted: 06 02 2023
revised: 08 03 2023
pubmed: 25 2 2023
medline: 11 3 2023
entrez: 24 2 2023
Statut: epublish

Résumé

Effective mass drug administration (MDA) is the cornerstone in the elimination of lymphatic filariasis (LF) and a critical component in combatting all neglected tropical diseases for which preventative chemotherapy is recommended (PC-NTDs). Despite its importance, MDA coverage, however defined, is rarely investigated systematically across time and geography. Most commonly, investigations into coverage react to unsatisfactory outcomes and tend to focus on a single year and health district. Such investigations omit more macro-level influences including sociological, environmental, and programmatic factors. The USAID NTD database contains measures of performance from thousands of district-level LF MDA campaigns across 14 years and 10 West African countries. Specifically, performance was measured as an MDA's epidemiological coverage, calculated as persons treated divided by persons at risk. This analysis aims to explain MDA coverage across time and geography in West Africa using sociological, environmental, and programmatic factors. The analysis links epidemiological coverage data from 3,880 LF MDAs with contextual, non-NTD data via location (each MDA was specific to a health district) and time (MDA month, year). Contextual data included rainfall, temperature, violence or social unrest, COVID-19, the 2014 Ebola outbreak, road access/isolation, population density, observance of Ramadan, and the number of previously completed MDAs. We fit a hierarchical linear regression model with coverage as the dependent variable and performed sensitivity analyses to confirm the selection of the explanatory factors. Above average rainfall, COVID-19, Ebola, violence and social unrest were all significantly associated with lower coverage. Years of prior experience in a district and above average temperature were significantly associated with higher coverage. These generalized and context-focused findings supplement current literature on coverage dynamics and MDA performance. Findings may be used to quantify typically anecdotal considerations in MDA planning. The model and methodology are offered as a tool for further investigation.

Sections du résumé

BACKGROUND
Effective mass drug administration (MDA) is the cornerstone in the elimination of lymphatic filariasis (LF) and a critical component in combatting all neglected tropical diseases for which preventative chemotherapy is recommended (PC-NTDs). Despite its importance, MDA coverage, however defined, is rarely investigated systematically across time and geography. Most commonly, investigations into coverage react to unsatisfactory outcomes and tend to focus on a single year and health district. Such investigations omit more macro-level influences including sociological, environmental, and programmatic factors. The USAID NTD database contains measures of performance from thousands of district-level LF MDA campaigns across 14 years and 10 West African countries. Specifically, performance was measured as an MDA's epidemiological coverage, calculated as persons treated divided by persons at risk. This analysis aims to explain MDA coverage across time and geography in West Africa using sociological, environmental, and programmatic factors.
METHODOLOGY
The analysis links epidemiological coverage data from 3,880 LF MDAs with contextual, non-NTD data via location (each MDA was specific to a health district) and time (MDA month, year). Contextual data included rainfall, temperature, violence or social unrest, COVID-19, the 2014 Ebola outbreak, road access/isolation, population density, observance of Ramadan, and the number of previously completed MDAs.
PRINCIPAL FINDINGS
We fit a hierarchical linear regression model with coverage as the dependent variable and performed sensitivity analyses to confirm the selection of the explanatory factors. Above average rainfall, COVID-19, Ebola, violence and social unrest were all significantly associated with lower coverage. Years of prior experience in a district and above average temperature were significantly associated with higher coverage.
CONCLUSIONS/SIGNIFICANCE
These generalized and context-focused findings supplement current literature on coverage dynamics and MDA performance. Findings may be used to quantify typically anecdotal considerations in MDA planning. The model and methodology are offered as a tool for further investigation.

Identifiants

pubmed: 36827450
doi: 10.1371/journal.pntd.0011146
pii: PNTD-D-22-00773
pmc: PMC9994721
doi:

Substances chimiques

Filaricides 0
3,4-Methylenedioxyamphetamine 4764-17-4

Types de publication

Journal Article Research Support, U.S. Gov't, Non-P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0011146

Informations de copyright

Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

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Auteurs

Brian B Fuller (BB)

Helen Keller International, Washington, District of Columbia, United States of America.

Vance Harris (V)

FHI 360, Denver, Colorado, United States of America.

Caleb Parker (C)

FHI 360, Durham, North Carolina, United States of America.

Andres Martinez (A)

FHI 360, Durham, North Carolina, United States of America.

Emily Toubali (E)

Division of Neglected Tropical Diseases, Office of Infectious Diseases, Bureau for Global Health, USAID, Washington, District of Columbia, United States of America.

Blandine Clarisse Ebene (BC)

National Programme for Onchocerciasis and Lymphatic Filariasis Control, Ministry of Public Health, Yaoundé, Cameroon.

Kofi Asemanyi-Mensah (K)

Neglected Tropical Diseases Programme, Disease Control and Prevention Department, Ghana Health Service, Public Health Division, Accra, Ghana.

Massitan Dembele (M)

National Programme for the Elimination of LF, Ministry of Health, Bamako, Mali.

Adamou Bacthiri Salissou (AB)

Programme Onchocercose et Filariose Lymphatique, Ministry of Health, Niamey, Niger.

Cathérine Kabré (C)

Programme national de lutte contre les maladies tropicales négligées, Ministry of Health, Ouagadougou, Burkina Faso.

Aboulaye Meite (A)

Programme national de lutte contre les maladies tropicales négligées à chimiothérapie préventive, Ministry of Health, Abidjan, Côte d'Ivoire.

Ndeye Mbacke Kane (NM)

National Neglected Tropical Diseases Control Program, Ministry of Health, Dakar, Senegal.

Ibrahim Kargbo-Labour (I)

Neglected Tropical Disease Programme, Ministry of Health and Sanitation, Freetown, Sierra Leone.

Wilfrid Batcho (W)

Programme National de Lutte contre les Maladies Transmissibles, Ministry of Health, Cotonou, Benin.

Aissatou Diaby (A)

National Neglected Tropical Diseases Control Program, Ministry of Health, Conakry, Guinea.

Violetta Yevstigneyeva (V)

Division of Neglected Tropical Diseases, Office of Infectious Diseases, Bureau for Global Health, USAID, Washington, District of Columbia, United States of America.

Diana Maria Stukel (DM)

Act to End NTDs | West, FHI 360, Washington, District of Columbia, United States of America.

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Classifications MeSH