Existing and potential infection risk zones of yellow fever worldwide: a modelling analysis
Background Yellow fever cases are under-reported and the exact distribution of the disease is unknown. An effective vaccine is available but more information is needed about which populations within risk zones should be targeted to implement interventions. Substantial outbreaks of yellow fever in A...
| Main Authors: | , , , , , , , , , , , , , , , , , , |
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| Format: | Journal article |
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Elsevier
2018
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| _version_ | 1797087150574927872 |
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| author | Shearer, FM Longbottom, J Browne, AJ Pigott, DM Brady, OJ Kraemer, MUG Marinho, F Yactayo, S de Araujo, VEM da Nobrega, AA Fullman, N Ray, SE Mosser, JF Stanaway, JD Lim, SS Reiner, RC Moyes, CL Hay, SI Golding, N |
| author_facet | Shearer, FM Longbottom, J Browne, AJ Pigott, DM Brady, OJ Kraemer, MUG Marinho, F Yactayo, S de Araujo, VEM da Nobrega, AA Fullman, N Ray, SE Mosser, JF Stanaway, JD Lim, SS Reiner, RC Moyes, CL Hay, SI Golding, N |
| author_sort | Shearer, FM |
| collection | OXFORD |
| description | Background Yellow fever cases are under-reported and the exact distribution of the disease is unknown. An effective vaccine is available but more information is needed about which populations within risk zones should be targeted to implement interventions. Substantial outbreaks of yellow fever in Angola, Democratic Republic of the Congo, and Brazil, coupled with the global expansion of the range of its main urban vector, Aedes aegypti, suggest that yellow fever has the propensity to spread further internationally. The aim of this study was to estimate the disease’s contemporary distribution and potential for spread into new areas to help inform optimal control and prevention strategies. Methods We assembled 1155 geographical records of yellow fever virus infection in people from 1970 to 2016. We used a Poisson point process boosted regression tree model that explicitly incorporated environmental and biological explanatory covariates, vaccination coverage, and spatial variability in disease reporting rates to predict the relative risk of apparent yellow fever virus infection at a 5×5 km resolution across all risk zones (47 countries across the Americas and Africa). We also used the fitted model to predict the receptivity of areas outside at-risk zones to the introduction or reintroduction of yellow fever transmission. By use of previously published estimates of annual national case numbers, we used the model to map subnational variation in incidence of yellow fever across at-risk countries and to estimate the number of cases averted by vaccination worldwide. Findings Substantial international and subnational spatial variation exists in relative risk and incidence of yellow fever as well as varied success of vaccination in reducing incidence in several high-risk regions, including Brazil, Cameroon, and Togo. Areas with the highest predicted average annual case numbers include large parts of Nigeria, the Democratic Republic of the Congo, and South Sudan, where vaccination coverage in 2016 was estimated to be substantially less than the recommended threshold to prevent outbreaks. Overall, we estimated that vaccination coverage levels achieved by 2016 avert between 94 336 and 118 500 cases of yellow fever annually within risk zones, on the basis of conservative and optimistic vaccination scenarios. The areas outside at-risk regions with predicted high receptivity to yellow fever transmission (eg, parts of Malaysia, Indonesia, and Thailand) were less extensive than the distribution of the main urban vector, A aegypti, with low receptivity to yellow fever transmission in southern China, where A aegypti is known to occur. |
| first_indexed | 2024-03-07T02:31:55Z |
| format | Journal article |
| id | oxford-uuid:a786bde3-ef68-4890-967d-0bf251d07ed8 |
| institution | University of Oxford |
| last_indexed | 2024-03-07T02:31:55Z |
| publishDate | 2018 |
| publisher | Elsevier |
| record_format | dspace |
| spelling | oxford-uuid:a786bde3-ef68-4890-967d-0bf251d07ed82022-03-27T02:55:17ZExisting and potential infection risk zones of yellow fever worldwide: a modelling analysisJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:a786bde3-ef68-4890-967d-0bf251d07ed8Symplectic Elements at OxfordElsevier2018Shearer, FMLongbottom, JBrowne, AJPigott, DMBrady, OJKraemer, MUGMarinho, FYactayo, Sde Araujo, VEMda Nobrega, AAFullman, NRay, SEMosser, JFStanaway, JDLim, SSReiner, RCMoyes, CLHay, SIGolding, NBackground Yellow fever cases are under-reported and the exact distribution of the disease is unknown. An effective vaccine is available but more information is needed about which populations within risk zones should be targeted to implement interventions. Substantial outbreaks of yellow fever in Angola, Democratic Republic of the Congo, and Brazil, coupled with the global expansion of the range of its main urban vector, Aedes aegypti, suggest that yellow fever has the propensity to spread further internationally. The aim of this study was to estimate the disease’s contemporary distribution and potential for spread into new areas to help inform optimal control and prevention strategies. Methods We assembled 1155 geographical records of yellow fever virus infection in people from 1970 to 2016. We used a Poisson point process boosted regression tree model that explicitly incorporated environmental and biological explanatory covariates, vaccination coverage, and spatial variability in disease reporting rates to predict the relative risk of apparent yellow fever virus infection at a 5×5 km resolution across all risk zones (47 countries across the Americas and Africa). We also used the fitted model to predict the receptivity of areas outside at-risk zones to the introduction or reintroduction of yellow fever transmission. By use of previously published estimates of annual national case numbers, we used the model to map subnational variation in incidence of yellow fever across at-risk countries and to estimate the number of cases averted by vaccination worldwide. Findings Substantial international and subnational spatial variation exists in relative risk and incidence of yellow fever as well as varied success of vaccination in reducing incidence in several high-risk regions, including Brazil, Cameroon, and Togo. Areas with the highest predicted average annual case numbers include large parts of Nigeria, the Democratic Republic of the Congo, and South Sudan, where vaccination coverage in 2016 was estimated to be substantially less than the recommended threshold to prevent outbreaks. Overall, we estimated that vaccination coverage levels achieved by 2016 avert between 94 336 and 118 500 cases of yellow fever annually within risk zones, on the basis of conservative and optimistic vaccination scenarios. The areas outside at-risk regions with predicted high receptivity to yellow fever transmission (eg, parts of Malaysia, Indonesia, and Thailand) were less extensive than the distribution of the main urban vector, A aegypti, with low receptivity to yellow fever transmission in southern China, where A aegypti is known to occur. |
| spellingShingle | Shearer, FM Longbottom, J Browne, AJ Pigott, DM Brady, OJ Kraemer, MUG Marinho, F Yactayo, S de Araujo, VEM da Nobrega, AA Fullman, N Ray, SE Mosser, JF Stanaway, JD Lim, SS Reiner, RC Moyes, CL Hay, SI Golding, N Existing and potential infection risk zones of yellow fever worldwide: a modelling analysis |
| title | Existing and potential infection risk zones of yellow fever worldwide: a modelling analysis |
| title_full | Existing and potential infection risk zones of yellow fever worldwide: a modelling analysis |
| title_fullStr | Existing and potential infection risk zones of yellow fever worldwide: a modelling analysis |
| title_full_unstemmed | Existing and potential infection risk zones of yellow fever worldwide: a modelling analysis |
| title_short | Existing and potential infection risk zones of yellow fever worldwide: a modelling analysis |
| title_sort | existing and potential infection risk zones of yellow fever worldwide a modelling analysis |
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