Guiding placement of health facilities using multiple malaria criteria and an interactive tool

Abstract Background Access to healthcare is important in controlling malaria burden and, as a result, distance or travel time to health facilities is often a significant predictor in modelling malaria prevalence. Adding new health facilities may reduce overall travel time to health facilities and ma...

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Autores principales:	Kok Ben Toh, Justin Millar, Paul Psychas, Benjamin Abuaku, Collins Ahorlu, Samuel Oppong, Kwadwo Koram, Denis Valle
Formato:	article
Lenguaje:	EN
Publicado:	BMC 2021
Materias:	Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216
Acceso en línea:	https://doaj.org/article/38ca299237c645abbb9f4478862530b6
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spelling	oai:doaj.org-article:38ca299237c645abbb9f4478862530b62021-12-05T12:21:37ZGuiding placement of health facilities using multiple malaria criteria and an interactive tool10.1186/s12936-021-03991-w1475-2875https://doaj.org/article/38ca299237c645abbb9f4478862530b62021-12-01T00:00:00Zhttps://doi.org/10.1186/s12936-021-03991-whttps://doaj.org/toc/1475-2875Abstract Background Access to healthcare is important in controlling malaria burden and, as a result, distance or travel time to health facilities is often a significant predictor in modelling malaria prevalence. Adding new health facilities may reduce overall travel time to health facilities and may decrease malaria transmission. To help guide local decision-makers as they scale up community-based accessibility, the influence of the spatial allocation of new health facilities on malaria prevalence is evaluated in Bunkpurugu-Yunyoo district in northern Ghana. A location-allocation analysis is performed to find optimal locations of new health facilities by separately minimizing three district-wide objectives: malaria prevalence, malaria incidence, and average travel time to health facilities. Methods Generalized additive models was used to estimate the relationship between malaria prevalence and travel time to the nearest health facility and other geospatial covariates. The model predictions are then used to calculate the optimisation criteria for the location-allocation analysis. This analysis was performed for two scenarios: adding new health facilities to the existing ones, and a hypothetical scenario in which the community-based healthcare facilities would be allocated anew. An interactive web application was created to facilitate efficient presentation of this analysis and allow users to experiment with their choice of health facility location and optimisation criteria. Results Using malaria prevalence and travel time as optimisation criteria, two locations that would benefit from new health facilities were identified, regardless of scenarios. Due to the non-linear relationship between malaria incidence and prevalence, the optimal locations chosen based on the incidence criterion tended to be inequitable and was different from those based on the other optimisation criteria. Conclusions This study findings underscore the importance of using multiple optimisation criteria in the decision-making process. This analysis and the interactive application can be repurposed for other regions and criteria, bridging the gap between science, models and decisions.Kok Ben TohJustin MillarPaul PsychasBenjamin AbuakuCollins AhorluSamuel OppongKwadwo KoramDenis ValleBMCarticleArctic medicine. Tropical medicineRC955-962Infectious and parasitic diseasesRC109-216ENMalaria Journal, Vol 20, Iss 1, Pp 1-13 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216
spellingShingle	Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 Kok Ben Toh Justin Millar Paul Psychas Benjamin Abuaku Collins Ahorlu Samuel Oppong Kwadwo Koram Denis Valle Guiding placement of health facilities using multiple malaria criteria and an interactive tool
description	Abstract Background Access to healthcare is important in controlling malaria burden and, as a result, distance or travel time to health facilities is often a significant predictor in modelling malaria prevalence. Adding new health facilities may reduce overall travel time to health facilities and may decrease malaria transmission. To help guide local decision-makers as they scale up community-based accessibility, the influence of the spatial allocation of new health facilities on malaria prevalence is evaluated in Bunkpurugu-Yunyoo district in northern Ghana. A location-allocation analysis is performed to find optimal locations of new health facilities by separately minimizing three district-wide objectives: malaria prevalence, malaria incidence, and average travel time to health facilities. Methods Generalized additive models was used to estimate the relationship between malaria prevalence and travel time to the nearest health facility and other geospatial covariates. The model predictions are then used to calculate the optimisation criteria for the location-allocation analysis. This analysis was performed for two scenarios: adding new health facilities to the existing ones, and a hypothetical scenario in which the community-based healthcare facilities would be allocated anew. An interactive web application was created to facilitate efficient presentation of this analysis and allow users to experiment with their choice of health facility location and optimisation criteria. Results Using malaria prevalence and travel time as optimisation criteria, two locations that would benefit from new health facilities were identified, regardless of scenarios. Due to the non-linear relationship between malaria incidence and prevalence, the optimal locations chosen based on the incidence criterion tended to be inequitable and was different from those based on the other optimisation criteria. Conclusions This study findings underscore the importance of using multiple optimisation criteria in the decision-making process. This analysis and the interactive application can be repurposed for other regions and criteria, bridging the gap between science, models and decisions.
format	article
author	Kok Ben Toh Justin Millar Paul Psychas Benjamin Abuaku Collins Ahorlu Samuel Oppong Kwadwo Koram Denis Valle
author_facet	Kok Ben Toh Justin Millar Paul Psychas Benjamin Abuaku Collins Ahorlu Samuel Oppong Kwadwo Koram Denis Valle
author_sort	Kok Ben Toh
title	Guiding placement of health facilities using multiple malaria criteria and an interactive tool
title_short	Guiding placement of health facilities using multiple malaria criteria and an interactive tool
title_full	Guiding placement of health facilities using multiple malaria criteria and an interactive tool
title_fullStr	Guiding placement of health facilities using multiple malaria criteria and an interactive tool
title_full_unstemmed	Guiding placement of health facilities using multiple malaria criteria and an interactive tool
title_sort	guiding placement of health facilities using multiple malaria criteria and an interactive tool
publisher	BMC
publishDate	2021
url	https://doaj.org/article/38ca299237c645abbb9f4478862530b6
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Guiding placement of health facilities using multiple malaria criteria and an interactive tool

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