Challenges and motivating factors for integrating geostatistical models in targeted schistosomiasis control: A qualitative case study in Northwestern Tanzania.

<h4>Introduction</h4>To address problems of over- and under-treatment with preventive chemotherapy resulting in ongoing transmission of schistosomiasis, the World Health Organization (WHO) recommends targeted mass drug administration (MDA) interventions at a sub-district level. In Tanzan...

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Main Authors: Jake D Mathewson, Linda van der Spek, Dunstan J Matungwa, Anna Samson, Harry L S Coleman, Ente J J Rood
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2024-12-01
Series:PLoS Neglected Tropical Diseases
Online Access:https://doi.org/10.1371/journal.pntd.0012770
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author Jake D Mathewson
Linda van der Spek
Dunstan J Matungwa
Anna Samson
Harry L S Coleman
Ente J J Rood
author_facet Jake D Mathewson
Linda van der Spek
Dunstan J Matungwa
Anna Samson
Harry L S Coleman
Ente J J Rood
author_sort Jake D Mathewson
collection DOAJ
description <h4>Introduction</h4>To address problems of over- and under-treatment with preventive chemotherapy resulting in ongoing transmission of schistosomiasis, the World Health Organization (WHO) recommends targeted mass drug administration (MDA) interventions at a sub-district level. In Tanzania, the lack of sub-district (ward) prevalence data has inhibited a transition to targeted treatment. Model-based prevalence estimation combined with routine surveillance data can be used to overcome this gap. We created a geostatistical model to estimate parasitological prevalence in the wards of the Lake Zone regions of Tanzania to investigate opportunities for enabling targeted MDA for schistosomiasis. With no precedent on how outputs from a geostatistical model could be used to inform decision-making in Tanzania, this qualitative study explores perceptions on what may challenge and motivate program staff in Tanzania's national schistosomiasis control program to integrate the models into routine planning to guide disease control interventions.<h4>Methods</h4>Seven semi-structured, key informant interviews were conducted in 2022 examining perceived programmatic challenges and motivations of integrating the geostatistical model into current programming through various thematic areas: information systems, financing, services and operational capacity, policy and planning, and coordination. Key informants included decision-making staff in the Ministry of Health's neglected tropical diseases (NTD) control program, WHO NTD staff, schistosomiasis MDA implementing partners, academic experts studying the control of schistosomiasis, and central-level NTD coordinators.<h4>Results</h4>Informants unanimously acknowledged that the geostatistical model could be useful in guiding targeted interventions, and found several factors that may motivate programmatic uptake including providing a financially feasible method to comprehensive prevalence estimates, facilitation of essential implementation tasks like site selection for MDA and screening, as well as annual calculation of treatments required for requesting medicine. Key challenges to integration were seen in limitation of existing modeling expertise, sensitization, and most importantly in the lack of WHO recommendations surrounding model use, as national disease control strategies and policies are built around WHO guidelines.<h4>Conclusions</h4>Geostatistical models like the one presented can feasibly be integrated in decision-making for targeted interventions based on domestic capacity, financial availability and readiness. However, the lack of WHO guidance on the use of these tools calls for action to translate the potential of such models into recommendations that encourage routine integration from national programs. Overcoming this key inhibiting factor will be a crucial first step toward the integration of such models.
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spelling doaj-art-6e130476e45d4d3598bff82403c7de702025-01-17T05:32:31ZengPublic Library of Science (PLoS)PLoS Neglected Tropical Diseases1935-27271935-27352024-12-011812e001277010.1371/journal.pntd.0012770Challenges and motivating factors for integrating geostatistical models in targeted schistosomiasis control: A qualitative case study in Northwestern Tanzania.Jake D MathewsonLinda van der SpekDunstan J MatungwaAnna SamsonHarry L S ColemanEnte J J Rood<h4>Introduction</h4>To address problems of over- and under-treatment with preventive chemotherapy resulting in ongoing transmission of schistosomiasis, the World Health Organization (WHO) recommends targeted mass drug administration (MDA) interventions at a sub-district level. In Tanzania, the lack of sub-district (ward) prevalence data has inhibited a transition to targeted treatment. Model-based prevalence estimation combined with routine surveillance data can be used to overcome this gap. We created a geostatistical model to estimate parasitological prevalence in the wards of the Lake Zone regions of Tanzania to investigate opportunities for enabling targeted MDA for schistosomiasis. With no precedent on how outputs from a geostatistical model could be used to inform decision-making in Tanzania, this qualitative study explores perceptions on what may challenge and motivate program staff in Tanzania's national schistosomiasis control program to integrate the models into routine planning to guide disease control interventions.<h4>Methods</h4>Seven semi-structured, key informant interviews were conducted in 2022 examining perceived programmatic challenges and motivations of integrating the geostatistical model into current programming through various thematic areas: information systems, financing, services and operational capacity, policy and planning, and coordination. Key informants included decision-making staff in the Ministry of Health's neglected tropical diseases (NTD) control program, WHO NTD staff, schistosomiasis MDA implementing partners, academic experts studying the control of schistosomiasis, and central-level NTD coordinators.<h4>Results</h4>Informants unanimously acknowledged that the geostatistical model could be useful in guiding targeted interventions, and found several factors that may motivate programmatic uptake including providing a financially feasible method to comprehensive prevalence estimates, facilitation of essential implementation tasks like site selection for MDA and screening, as well as annual calculation of treatments required for requesting medicine. Key challenges to integration were seen in limitation of existing modeling expertise, sensitization, and most importantly in the lack of WHO recommendations surrounding model use, as national disease control strategies and policies are built around WHO guidelines.<h4>Conclusions</h4>Geostatistical models like the one presented can feasibly be integrated in decision-making for targeted interventions based on domestic capacity, financial availability and readiness. However, the lack of WHO guidance on the use of these tools calls for action to translate the potential of such models into recommendations that encourage routine integration from national programs. Overcoming this key inhibiting factor will be a crucial first step toward the integration of such models.https://doi.org/10.1371/journal.pntd.0012770
spellingShingle Jake D Mathewson
Linda van der Spek
Dunstan J Matungwa
Anna Samson
Harry L S Coleman
Ente J J Rood
Challenges and motivating factors for integrating geostatistical models in targeted schistosomiasis control: A qualitative case study in Northwestern Tanzania.
PLoS Neglected Tropical Diseases
title Challenges and motivating factors for integrating geostatistical models in targeted schistosomiasis control: A qualitative case study in Northwestern Tanzania.
title_full Challenges and motivating factors for integrating geostatistical models in targeted schistosomiasis control: A qualitative case study in Northwestern Tanzania.
title_fullStr Challenges and motivating factors for integrating geostatistical models in targeted schistosomiasis control: A qualitative case study in Northwestern Tanzania.
title_full_unstemmed Challenges and motivating factors for integrating geostatistical models in targeted schistosomiasis control: A qualitative case study in Northwestern Tanzania.
title_short Challenges and motivating factors for integrating geostatistical models in targeted schistosomiasis control: A qualitative case study in Northwestern Tanzania.
title_sort challenges and motivating factors for integrating geostatistical models in targeted schistosomiasis control a qualitative case study in northwestern tanzania
url https://doi.org/10.1371/journal.pntd.0012770
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