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...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2022-11-01
|
| Series: | Clinical Infection in Practice |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590170222000280 |
| _version_ | 1797991872967213056 |
|---|---|
| author | Musah Ali Asori Moses Emmanuel Kweku Nakua Damien Punguyire Benjamin Spears Ngmekpele Cheabu Patrick Mawupemor Avevor Kassim Abdul Basit |
| author_facet | Musah Ali Asori Moses Emmanuel Kweku Nakua Damien Punguyire Benjamin Spears Ngmekpele Cheabu Patrick Mawupemor Avevor Kassim Abdul Basit |
| author_sort | Musah Ali |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-04-11T08:59:11Z |
| format | Article |
| id | doaj.art-22a70aa97471457281b2ee4fae99948c |
| institution | Directory Open Access Journal |
| issn | 2590-1702 |
| language | English |
| last_indexed | 2024-04-11T08:59:11Z |
| publishDate | 2022-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Clinical Infection in Practice |
| spelling | doaj.art-22a70aa97471457281b2ee4fae99948c2022-12-22T04:32:50ZengElsevierClinical Infection in Practice2590-17022022-11-0116100160Spatial epidemiology of bacterial meningitis in the Upper West Region of Ghana: Analysis of disease surveillance data 2018–2020Musah Ali0Asori Moses1Emmanuel Kweku Nakua2Damien Punguyire3Benjamin Spears Ngmekpele Cheabu4Patrick Mawupemor Avevor5Kassim Abdul Basit6Kwame Nkrumah University of Science and Technology, Department of Epidemiology and Biostatistics, Kumasi, Ghana; Corresponding author at: Department of Epidemiology and Biostatistics, Kwame Nkrumah University of Science and Technology, Private Mail Bag, KNUST, Kumasi, Ghana.University of North Carolina, Department of Geography, Charlotte, United StatesKwame Nkrumah University of Science and Technology, Department of Epidemiology and Biostatistics, Kumasi, GhanaGhana Health Service, Upper West Regional Health Directorate, Wa, GhanaQueen’s University, Faculty of Health Sciences, Health Quality Programs, Kingston, CanadaWorld Health Organisation, Country Office, Accra, GhanaJapan International Cooperation Agency, Tamale, GhanaBackground: 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.http://www.sciencedirect.com/science/article/pii/S2590170222000280Spatial epidemiologyBacterial meningitisGeospatial analysisGhanaUpper West Region |
| spellingShingle | Musah Ali Asori Moses Emmanuel Kweku Nakua Damien Punguyire Benjamin Spears Ngmekpele Cheabu Patrick Mawupemor Avevor Kassim Abdul Basit Spatial epidemiology of bacterial meningitis in the Upper West Region of Ghana: Analysis of disease surveillance data 2018–2020 Clinical Infection in Practice Spatial epidemiology Bacterial meningitis Geospatial analysis Ghana Upper West Region |
| 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 | Spatial epidemiology Bacterial meningitis Geospatial analysis Ghana Upper West Region |
| url | http://www.sciencedirect.com/science/article/pii/S2590170222000280 |
| work_keys_str_mv | AT musahali spatialepidemiologyofbacterialmeningitisintheupperwestregionofghanaanalysisofdiseasesurveillancedata20182020 AT asorimoses spatialepidemiologyofbacterialmeningitisintheupperwestregionofghanaanalysisofdiseasesurveillancedata20182020 AT emmanuelkwekunakua spatialepidemiologyofbacterialmeningitisintheupperwestregionofghanaanalysisofdiseasesurveillancedata20182020 AT damienpunguyire spatialepidemiologyofbacterialmeningitisintheupperwestregionofghanaanalysisofdiseasesurveillancedata20182020 AT benjaminspearsngmekpelecheabu spatialepidemiologyofbacterialmeningitisintheupperwestregionofghanaanalysisofdiseasesurveillancedata20182020 AT patrickmawupemoravevor spatialepidemiologyofbacterialmeningitisintheupperwestregionofghanaanalysisofdiseasesurveillancedata20182020 AT kassimabdulbasit spatialepidemiologyofbacterialmeningitisintheupperwestregionofghanaanalysisofdiseasesurveillancedata20182020 |