George Bates, Philip C Hill, Isireli Koroituku, Donald Wilson, Mun Reddy, Mike Kama
{"title":"在斐济采用以消除结核病为重点的地理空间方法，优化基因Xpert诊断仪的使用。","authors":"George Bates, Philip C Hill, Isireli Koroituku, Donald Wilson, Mun Reddy, Mike Kama","doi":"10.1111/tmi.14023","DOIUrl":null,"url":null,"abstract":"<p><strong>Objectives: </strong>Fiji could be the first country to eliminate tuberculosis. To inform this strategy, we aimed to identify how many GeneXpert® machines are required to enable over 90% of Fijians to be within one-hour easy access.</p><p><strong>Methods: </strong>We used Geographic Information System (Quantum GIS; QGIS), OpenStreetMap and population data (Kontur) to map possible facilities in relation to QGIS generated 60-min drive-time isochrones, with correction for missing road data. For outer islands, we calculated a distance to nearest hub operation.</p><p><strong>Results: </strong>The solution comprised 24 GeneXpert® machines, allocating 7 GeneXpert® to Viti Levu, 6 GeneXpert® to Vanua Levu and 11 to other islands. This resulted in 827,810 people, 93.6% of Fiji's population, being within 1 h of a machine. Twenty-one thousand four hundred seventy-nine people on outer islands were an average of 43 km by water from the nearest facility.</p><p><strong>Conclusions: </strong>We conclude that over 90% of Fijians could be within an hour of a GeneXpert® machine with placement of 24 machines.</p>","PeriodicalId":23962,"journal":{"name":"Tropical Medicine & International Health","volume":" ","pages":"715-722"},"PeriodicalIF":2.6000,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A tuberculosis elimination-focused geospatial approach to optimising access to diagnostic GeneXpert machines in Fiji.\",\"authors\":\"George Bates, Philip C Hill, Isireli Koroituku, Donald Wilson, Mun Reddy, Mike Kama\",\"doi\":\"10.1111/tmi.14023\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objectives: </strong>Fiji could be the first country to eliminate tuberculosis. To inform this strategy, we aimed to identify how many GeneXpert® machines are required to enable over 90% of Fijians to be within one-hour easy access.</p><p><strong>Methods: </strong>We used Geographic Information System (Quantum GIS; QGIS), OpenStreetMap and population data (Kontur) to map possible facilities in relation to QGIS generated 60-min drive-time isochrones, with correction for missing road data. For outer islands, we calculated a distance to nearest hub operation.</p><p><strong>Results: </strong>The solution comprised 24 GeneXpert® machines, allocating 7 GeneXpert® to Viti Levu, 6 GeneXpert® to Vanua Levu and 11 to other islands. This resulted in 827,810 people, 93.6% of Fiji's population, being within 1 h of a machine. Twenty-one thousand four hundred seventy-nine people on outer islands were an average of 43 km by water from the nearest facility.</p><p><strong>Conclusions: </strong>We conclude that over 90% of Fijians could be within an hour of a GeneXpert® machine with placement of 24 machines.</p>\",\"PeriodicalId\":23962,\"journal\":{\"name\":\"Tropical Medicine & International Health\",\"volume\":\" \",\"pages\":\"715-722\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2024-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Tropical Medicine & International Health\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1111/tmi.14023\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/6/4 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Tropical Medicine & International Health","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1111/tmi.14023","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/6/4 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
A tuberculosis elimination-focused geospatial approach to optimising access to diagnostic GeneXpert machines in Fiji.
Objectives: Fiji could be the first country to eliminate tuberculosis. To inform this strategy, we aimed to identify how many GeneXpert® machines are required to enable over 90% of Fijians to be within one-hour easy access.
Methods: We used Geographic Information System (Quantum GIS; QGIS), OpenStreetMap and population data (Kontur) to map possible facilities in relation to QGIS generated 60-min drive-time isochrones, with correction for missing road data. For outer islands, we calculated a distance to nearest hub operation.
Results: The solution comprised 24 GeneXpert® machines, allocating 7 GeneXpert® to Viti Levu, 6 GeneXpert® to Vanua Levu and 11 to other islands. This resulted in 827,810 people, 93.6% of Fiji's population, being within 1 h of a machine. Twenty-one thousand four hundred seventy-nine people on outer islands were an average of 43 km by water from the nearest facility.
Conclusions: We conclude that over 90% of Fijians could be within an hour of a GeneXpert® machine with placement of 24 machines.
期刊介绍：
Tropical Medicine & International Health is published on behalf of the London School of Hygiene and Tropical Medicine, Swiss Tropical and Public Health Institute, Foundation Tropical Medicine and International Health, Belgian Institute of Tropical Medicine and Bernhard-Nocht-Institute for Tropical Medicine. Tropical Medicine & International Health is the official journal of the Federation of European Societies for Tropical Medicine and International Health (FESTMIH).
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