Modelling spatiotemporal variation in under-five malaria risk in Ghana in 2016–2021
Abstract Background Ghana is among the top 10 highest malaria burden countries, with about 20,000 children dying annually, 25% of which were under five years. This study aimed to produce interactive web-based disease spatial maps and identify the high-burden malaria districts in Ghana. Methods The s...
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ftdoajarticles:oai:doaj.org/article:358831ffe93e450c988053b7501d7744 2024-09-09T19:28:27+00:00 Modelling spatiotemporal variation in under-five malaria risk in Ghana in 2016–2021 Justice Moses K. Aheto Lynette J. Menezes Wisdom Takramah Liwang Cui 2024-04-01T00:00:00Z https://doi.org/10.1186/s12936-024-04918-x https://doaj.org/article/358831ffe93e450c988053b7501d7744 EN eng BMC https://doi.org/10.1186/s12936-024-04918-x https://doaj.org/toc/1475-2875 doi:10.1186/s12936-024-04918-x 1475-2875 https://doaj.org/article/358831ffe93e450c988053b7501d7744 Malaria Journal, Vol 23, Iss 1, Pp 1-12 (2024) Malaria Under-five malaria Mapping malaria risk Bayesian methods Spatio-temporal methods Integrated Nested Laplace Approximation Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 article 2024 ftdoajarticles https://doi.org/10.1186/s12936-024-04918-x 2024-08-05T17:49:36Z Abstract Background Ghana is among the top 10 highest malaria burden countries, with about 20,000 children dying annually, 25% of which were under five years. This study aimed to produce interactive web-based disease spatial maps and identify the high-burden malaria districts in Ghana. Methods The study used 2016–2021 data extracted from the routine health service nationally representative and comprehensive District Health Information Management System II (DHIMS2) implemented by the Ghana Health Service. Bayesian geospatial modelling and interactive web-based spatial disease mapping methods were employed to quantify spatial variations and clustering in malaria risk across 260 districts. For each district, the study simultaneously mapped the observed malaria counts, district name, standardized incidence rate, and predicted relative risk and their associated standard errors using interactive web-based visualization methods. Results A total of 32,659,240 malaria cases were reported among children < 5 years from 2016 to 2021. For every 10% increase in the number of children, malaria risk increased by 0.039 (log-mean 0.95, 95% credible interval = − 13.82–15.73) and for every 10% increase in the number of males, malaria risk decreased by 0.075, albeit not statistically significant (log-mean − 1.82, 95% credible interval = − 16.59–12.95). The study found substantial spatial and temporal differences in malaria risk across the 260 districts. The predicted national relative risk was 1.25 (95% credible interval = 1.23, 1.27). The malaria risk is relatively the same over the entire year. However, a slightly higher relative risk was recorded in 2019 while in 2021, residing in Keta, Abuakwa South, Jomoro, Ahafo Ano South East, Tain, Nanumba North, and Tatale Sanguli districts was associated with the highest malaria risk ranging from a relative risk of 3.00 to 4.83. The district-level spatial patterns of malaria risks changed over time. Conclusion This study identified high malaria risk districts in Ghana where urgent and ... Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic Keta ENVELOPE(-19.455,-19.455,65.656,65.656) Laplace ENVELOPE(141.467,141.467,-66.782,-66.782) Malaria Journal 23 1 |
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Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Malaria Under-five malaria Mapping malaria risk Bayesian methods Spatio-temporal methods Integrated Nested Laplace Approximation Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 |
spellingShingle |
Malaria Under-five malaria Mapping malaria risk Bayesian methods Spatio-temporal methods Integrated Nested Laplace Approximation Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 Justice Moses K. Aheto Lynette J. Menezes Wisdom Takramah Liwang Cui Modelling spatiotemporal variation in under-five malaria risk in Ghana in 2016–2021 |
topic_facet |
Malaria Under-five malaria Mapping malaria risk Bayesian methods Spatio-temporal methods Integrated Nested Laplace Approximation Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 |
description |
Abstract Background Ghana is among the top 10 highest malaria burden countries, with about 20,000 children dying annually, 25% of which were under five years. This study aimed to produce interactive web-based disease spatial maps and identify the high-burden malaria districts in Ghana. Methods The study used 2016–2021 data extracted from the routine health service nationally representative and comprehensive District Health Information Management System II (DHIMS2) implemented by the Ghana Health Service. Bayesian geospatial modelling and interactive web-based spatial disease mapping methods were employed to quantify spatial variations and clustering in malaria risk across 260 districts. For each district, the study simultaneously mapped the observed malaria counts, district name, standardized incidence rate, and predicted relative risk and their associated standard errors using interactive web-based visualization methods. Results A total of 32,659,240 malaria cases were reported among children < 5 years from 2016 to 2021. For every 10% increase in the number of children, malaria risk increased by 0.039 (log-mean 0.95, 95% credible interval = − 13.82–15.73) and for every 10% increase in the number of males, malaria risk decreased by 0.075, albeit not statistically significant (log-mean − 1.82, 95% credible interval = − 16.59–12.95). The study found substantial spatial and temporal differences in malaria risk across the 260 districts. The predicted national relative risk was 1.25 (95% credible interval = 1.23, 1.27). The malaria risk is relatively the same over the entire year. However, a slightly higher relative risk was recorded in 2019 while in 2021, residing in Keta, Abuakwa South, Jomoro, Ahafo Ano South East, Tain, Nanumba North, and Tatale Sanguli districts was associated with the highest malaria risk ranging from a relative risk of 3.00 to 4.83. The district-level spatial patterns of malaria risks changed over time. Conclusion This study identified high malaria risk districts in Ghana where urgent and ... |
format |
Article in Journal/Newspaper |
author |
Justice Moses K. Aheto Lynette J. Menezes Wisdom Takramah Liwang Cui |
author_facet |
Justice Moses K. Aheto Lynette J. Menezes Wisdom Takramah Liwang Cui |
author_sort |
Justice Moses K. Aheto |
title |
Modelling spatiotemporal variation in under-five malaria risk in Ghana in 2016–2021 |
title_short |
Modelling spatiotemporal variation in under-five malaria risk in Ghana in 2016–2021 |
title_full |
Modelling spatiotemporal variation in under-five malaria risk in Ghana in 2016–2021 |
title_fullStr |
Modelling spatiotemporal variation in under-five malaria risk in Ghana in 2016–2021 |
title_full_unstemmed |
Modelling spatiotemporal variation in under-five malaria risk in Ghana in 2016–2021 |
title_sort |
modelling spatiotemporal variation in under-five malaria risk in ghana in 2016–2021 |
publisher |
BMC |
publishDate |
2024 |
url |
https://doi.org/10.1186/s12936-024-04918-x https://doaj.org/article/358831ffe93e450c988053b7501d7744 |
long_lat |
ENVELOPE(-19.455,-19.455,65.656,65.656) ENVELOPE(141.467,141.467,-66.782,-66.782) |
geographic |
Arctic Keta Laplace |
geographic_facet |
Arctic Keta Laplace |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
Malaria Journal, Vol 23, Iss 1, Pp 1-12 (2024) |
op_relation |
https://doi.org/10.1186/s12936-024-04918-x https://doaj.org/toc/1475-2875 doi:10.1186/s12936-024-04918-x 1475-2875 https://doaj.org/article/358831ffe93e450c988053b7501d7744 |
op_doi |
https://doi.org/10.1186/s12936-024-04918-x |
container_title |
Malaria Journal |
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23 |
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1 |
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1809897776892346368 |