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...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2021-12-01
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| Series: | Malaria Journal |
| Online Access: | https://doi.org/10.1186/s12936-021-03991-w |
| _version_ | 1829465548235210752 |
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| 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 |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-12-13T16:56:04Z |
| format | Article |
| id | doaj.art-38ca299237c645abbb9f4478862530b6 |
| institution | Directory Open Access Journal |
| issn | 1475-2875 |
| language | English |
| last_indexed | 2024-12-13T16:56:04Z |
| publishDate | 2021-12-01 |
| publisher | BMC |
| record_format | Article |
| series | Malaria Journal |
| spelling | doaj.art-38ca299237c645abbb9f4478862530b62022-12-21T23:37:55ZengBMCMalaria Journal1475-28752021-12-0120111310.1186/s12936-021-03991-wGuiding placement of health facilities using multiple malaria criteria and an interactive toolKok Ben Toh0Justin Millar1Paul Psychas2Benjamin Abuaku3Collins Ahorlu4Samuel Oppong5Kwadwo Koram6Denis Valle7School of Natural Resources and Environment, University of FloridaSchool of Forest, Fisheries, and Geomatics Sciences, University of FloridaCenters for Disease Control, US President’s Malaria InitiativeNoguchi Memorial Institute for Medical Research, University of GhanaNoguchi Memorial Institute for Medical Research, University of GhanaNational Malaria Control ProgrammeNoguchi Memorial Institute for Medical Research, University of GhanaSchool of Forest, Fisheries, and Geomatics Sciences, University of FloridaAbstract 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.https://doi.org/10.1186/s12936-021-03991-w |
| spellingShingle | 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 Malaria Journal |
| title | 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_short | 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 |
| url | https://doi.org/10.1186/s12936-021-03991-w |
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