The role of geospatial hotspots in the spatial spread of tuberculosis in rural Ethiopia: a mathematical model
Geospatial tuberculosis (TB) hotspots are hubs of TB transmission both within and across community groups. We aimed to quantify the extent to which these hotspots account for the spatial spread of TB in a high-burden setting. We developed spatially coupled models to quantify the spread of TB from ge...
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| Format: | Article |
| Language: | English |
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The Royal Society
2018-01-01
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| Series: | Royal Society Open Science |
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| Online Access: | https://royalsocietypublishing.org/doi/pdf/10.1098/rsos.180887 |
| _version_ | 1819006340013490176 |
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| author | Debebe Shaweno James M. Trauer Justin T. Denholm Emma S. McBryde |
| author_facet | Debebe Shaweno James M. Trauer Justin T. Denholm Emma S. McBryde |
| author_sort | Debebe Shaweno |
| collection | DOAJ |
| description | Geospatial tuberculosis (TB) hotspots are hubs of TB transmission both within and across community groups. We aimed to quantify the extent to which these hotspots account for the spatial spread of TB in a high-burden setting. We developed spatially coupled models to quantify the spread of TB from geographical hotspots to distant regions in rural Ethiopia. The population was divided into three ‘patches’ based on their proximity to transmission hotspots, namely hotspots, adjacent regions and remote regions. The models were fitted to 5-year notification data aggregated by the metapopulation structure. Model fitting was achieved with a Metropolis–Hastings algorithm using a Poisson likelihood to compare model-estimated notification rate with observed notification rates. A cross-coupled metapopulation model with assortative mixing by region closely fit to notification data as assessed by the deviance information criterion. We estimated 45 hotspot-to-adjacent regions transmission events and 2 hotspot-to-remote regions transmission events occurred for every 1000 hotspot-to-hotspot transmission events. Although the degree of spatial coupling was weak, the proportion of infections in the adjacent region that resulted from mixing with hotspots was high due to the high prevalence of TB cases in a hotspot region, with approximately 75% of infections attributable to hotspot contact. Our results suggest that the role of hotspots in the geospatial spread of TB in rural Ethiopia is limited, implying that TB transmission is primarily locally driven. |
| first_indexed | 2024-12-21T00:07:07Z |
| format | Article |
| id | doaj.art-f23906362cf1448193107fb1da6f667d |
| institution | Directory Open Access Journal |
| issn | 2054-5703 |
| language | English |
| last_indexed | 2024-12-21T00:07:07Z |
| publishDate | 2018-01-01 |
| publisher | The Royal Society |
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| series | Royal Society Open Science |
| spelling | doaj.art-f23906362cf1448193107fb1da6f667d2022-12-21T19:22:27ZengThe Royal SocietyRoyal Society Open Science2054-57032018-01-015910.1098/rsos.180887180887The role of geospatial hotspots in the spatial spread of tuberculosis in rural Ethiopia: a mathematical modelDebebe ShawenoJames M. TrauerJustin T. DenholmEmma S. McBrydeGeospatial tuberculosis (TB) hotspots are hubs of TB transmission both within and across community groups. We aimed to quantify the extent to which these hotspots account for the spatial spread of TB in a high-burden setting. We developed spatially coupled models to quantify the spread of TB from geographical hotspots to distant regions in rural Ethiopia. The population was divided into three ‘patches’ based on their proximity to transmission hotspots, namely hotspots, adjacent regions and remote regions. The models were fitted to 5-year notification data aggregated by the metapopulation structure. Model fitting was achieved with a Metropolis–Hastings algorithm using a Poisson likelihood to compare model-estimated notification rate with observed notification rates. A cross-coupled metapopulation model with assortative mixing by region closely fit to notification data as assessed by the deviance information criterion. We estimated 45 hotspot-to-adjacent regions transmission events and 2 hotspot-to-remote regions transmission events occurred for every 1000 hotspot-to-hotspot transmission events. Although the degree of spatial coupling was weak, the proportion of infections in the adjacent region that resulted from mixing with hotspots was high due to the high prevalence of TB cases in a hotspot region, with approximately 75% of infections attributable to hotspot contact. Our results suggest that the role of hotspots in the geospatial spread of TB in rural Ethiopia is limited, implying that TB transmission is primarily locally driven.https://royalsocietypublishing.org/doi/pdf/10.1098/rsos.180887hotspotstransmissionspatial analysistuberculosismetapopulation models |
| spellingShingle | Debebe Shaweno James M. Trauer Justin T. Denholm Emma S. McBryde The role of geospatial hotspots in the spatial spread of tuberculosis in rural Ethiopia: a mathematical model Royal Society Open Science hotspots transmission spatial analysis tuberculosis metapopulation models |
| title | The role of geospatial hotspots in the spatial spread of tuberculosis in rural Ethiopia: a mathematical model |
| title_full | The role of geospatial hotspots in the spatial spread of tuberculosis in rural Ethiopia: a mathematical model |
| title_fullStr | The role of geospatial hotspots in the spatial spread of tuberculosis in rural Ethiopia: a mathematical model |
| title_full_unstemmed | The role of geospatial hotspots in the spatial spread of tuberculosis in rural Ethiopia: a mathematical model |
| title_short | The role of geospatial hotspots in the spatial spread of tuberculosis in rural Ethiopia: a mathematical model |
| title_sort | role of geospatial hotspots in the spatial spread of tuberculosis in rural ethiopia a mathematical model |
| topic | hotspots transmission spatial analysis tuberculosis metapopulation models |
| url | https://royalsocietypublishing.org/doi/pdf/10.1098/rsos.180887 |
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