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Spatial epidemiology of bacterial meningitis in the Upper West Region of Ghana: Analysis of disease surveillance data 2018–2020
BACKGROUND: The use of a Geographic Information System in identifying meningitis hotspots in the Upper West Region (UWR) remains underutilized, making spatial targeting of meningitis hotspots difficult. We therefore utilized surveillance data enabled with GIS technology to target meningitis outbreak...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10189849/ https://www.ncbi.nlm.nih.gov/pubmed/37206902 http://dx.doi.org/10.1016/j.clinpr.2022.100160 |
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author | Ali, Musah Moses, Asori Nakua, Emmanuel Kweku Punguyire, Damien Cheabu, Benjamin Spears Ngmekpele Avevor, Patrick Mawupemor Basit, Kassim Abdul |
author_facet | Ali, Musah Moses, Asori Nakua, Emmanuel Kweku Punguyire, Damien Cheabu, Benjamin Spears Ngmekpele Avevor, Patrick Mawupemor Basit, Kassim Abdul |
author_sort | Ali, Musah |
collection | PubMed |
description | BACKGROUND: The use of a Geographic Information System in identifying meningitis hotspots in the Upper West Region (UWR) remains underutilized, making spatial targeting of meningitis hotspots difficult. We therefore utilized surveillance data enabled with GIS technology to target meningitis outbreaks in the UWR. METHODS: Secondary data analysis was conducted in the study. The dynamics of bacterial meningitis in space and time were studied using epidemiological data from 2018 to 2020. Spot map and choropleths were used to depict the distribution of cases in the region. Moran's I statistics were used to assess spatial autocorrelation. Getis-Ord Gi*(d) and Anselin Local Moran’s statistics were used to identify hotspots and spatial outliers within the study area. A Geographic Weighted Regression model was also used to examine how socio bio-climatic conditions influence the spread of meningitis. RESULTS: There were 1176 cases of bacterial meningitis, 118 deaths, and 1058 survivors between 2018 and 2020. Nandom municipality had the highest Attack Rate (AR) at 492/100,000 persons, followed by Nadowli-Kaleo district at 314/100,000 persons. Jirapa had the highest case fatality rate (CFR) at 17%. The spatio-temporal analysis showed spatial diffusion of meningitis prevalence from the western half of the UWR to the east with a significant number of hotpots and cluster outliers. CONCLUSION: Bacterial meningitis does not occur at random. Populations (10.9%) under sub-districts identified as hotspots are exceptionally at higher risk of outbreaks. Targeted interventions should be directed towards clustered hotspots, focusing on zones with low prevalence fenced off by high prevalence zones. |
format | Online Article Text |
id | pubmed-10189849 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-101898492023-05-18 Spatial epidemiology of bacterial meningitis in the Upper West Region of Ghana: Analysis of disease surveillance data 2018–2020 Ali, Musah Moses, Asori Nakua, Emmanuel Kweku Punguyire, Damien Cheabu, Benjamin Spears Ngmekpele Avevor, Patrick Mawupemor Basit, Kassim Abdul Clin Infect Pract Clinical Audits/Service improvements BACKGROUND: The use of a Geographic Information System in identifying meningitis hotspots in the Upper West Region (UWR) remains underutilized, making spatial targeting of meningitis hotspots difficult. We therefore utilized surveillance data enabled with GIS technology to target meningitis outbreaks in the UWR. METHODS: Secondary data analysis was conducted in the study. The dynamics of bacterial meningitis in space and time were studied using epidemiological data from 2018 to 2020. Spot map and choropleths were used to depict the distribution of cases in the region. Moran's I statistics were used to assess spatial autocorrelation. Getis-Ord Gi*(d) and Anselin Local Moran’s statistics were used to identify hotspots and spatial outliers within the study area. A Geographic Weighted Regression model was also used to examine how socio bio-climatic conditions influence the spread of meningitis. RESULTS: There were 1176 cases of bacterial meningitis, 118 deaths, and 1058 survivors between 2018 and 2020. Nandom municipality had the highest Attack Rate (AR) at 492/100,000 persons, followed by Nadowli-Kaleo district at 314/100,000 persons. Jirapa had the highest case fatality rate (CFR) at 17%. The spatio-temporal analysis showed spatial diffusion of meningitis prevalence from the western half of the UWR to the east with a significant number of hotpots and cluster outliers. CONCLUSION: Bacterial meningitis does not occur at random. Populations (10.9%) under sub-districts identified as hotspots are exceptionally at higher risk of outbreaks. Targeted interventions should be directed towards clustered hotspots, focusing on zones with low prevalence fenced off by high prevalence zones. Elsevier Ltd 2022-11 /pmc/articles/PMC10189849/ /pubmed/37206902 http://dx.doi.org/10.1016/j.clinpr.2022.100160 Text en © 2022 Published by Elsevier Ltd on behalf of British Infection Association. https://creativecommons.org/licenses/by-nc-nd/3.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/). |
spellingShingle | Clinical Audits/Service improvements Ali, Musah Moses, Asori Nakua, Emmanuel Kweku Punguyire, Damien Cheabu, Benjamin Spears Ngmekpele Avevor, Patrick Mawupemor Basit, Kassim Abdul Spatial epidemiology of bacterial meningitis in the Upper West Region of Ghana: Analysis of disease surveillance data 2018–2020 |
title | Spatial epidemiology of bacterial meningitis in the Upper West Region of Ghana: Analysis of disease surveillance data 2018–2020 |
title_full | Spatial epidemiology of bacterial meningitis in the Upper West Region of Ghana: Analysis of disease surveillance data 2018–2020 |
title_fullStr | Spatial epidemiology of bacterial meningitis in the Upper West Region of Ghana: Analysis of disease surveillance data 2018–2020 |
title_full_unstemmed | Spatial epidemiology of bacterial meningitis in the Upper West Region of Ghana: Analysis of disease surveillance data 2018–2020 |
title_short | Spatial epidemiology of bacterial meningitis in the Upper West Region of Ghana: Analysis of disease surveillance data 2018–2020 |
title_sort | spatial epidemiology of bacterial meningitis in the upper west region of ghana: analysis of disease surveillance data 2018–2020 |
topic | Clinical Audits/Service improvements |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10189849/ https://www.ncbi.nlm.nih.gov/pubmed/37206902 http://dx.doi.org/10.1016/j.clinpr.2022.100160 |
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