Predicting the environmental suitability for onchocerciasis in Africa as an aid to elimination planning

dc.contributor.authorAhmadpour, Ehsan
dc.contributor.authorBeshir Ahmed, Muktar
dc.contributor.authorAkalu, Temesgen Yihunie
dc.contributor.authorAl- Aly, Ziyad
dc.contributor.authorAlanezi, Fahad Mashhour
dc.contributor.authorAlanzi, Turki M.
dc.contributor.authorAlipour, Vahid
dc.contributor.authorAndrei, Catalina Liliana
dc.contributor.authorAnsari, Fereshteh
dc.contributor.authorAnsha, Mustafa Geleto
dc.contributor.authorAnvari, Davood
dc.contributor.authorAppiah, Seth Christopher Yaw
dc.contributor.authorArabloo, Jalal
dc.contributor.authorArnold, Benjamin F.
dc.contributor.authorAusloos, Marcel
dc.contributor.authorAyanore, Martin Amogre
dc.contributor.authorBaig, Atif Amin
dc.contributor.authorBanach, Maciej
dc.contributor.authorBarac, Aleksandra
dc.contributor.authorBarnighausen, Till Winfried
dc.contributor.authorBayati, Mohsen
dc.contributor.authorBhattacharyya, Krittika
dc.contributor.authorBhutta, Zulfiqar A.
dc.contributor.authorBibi, Sadia
dc.contributor.authorBijani, Ali
dc.contributor.authorBohlouli, Somayeh
dc.contributor.authorBohluli, Mahdi
dc.contributor.authorBrady, Oliver J.
dc.contributor.authorBragazzi, Nicola Luigi
dc.contributor.authorButt, Zahid A.
dc.contributor.authorCarvalho, Felix
dc.contributor.authorChatterjee, Souranshu
dc.contributor.authorChattu, Vijay Kumar
dc.contributor.authorChattu, Soosanna Kumary
dc.contributor.authorCormier, Natalie Maria
dc.contributor.authorDahlawi, Saad M.A.
dc.contributor.authorDamiani, Giovanni
dc.contributor.authorDaoud, Farah
dc.contributor.authorDarwesh, Aso Mohammad
dc.contributor.authorDaryani, Ahmad
dc.contributor.authorDeribe, Kebede
dc.contributor.authorDharmaratne, Samath Dhamminda
dc.contributor.authorDiaz, Daniel
dc.contributor.authorDo, Hoa Thi
dc.contributor.authorZaki, Maysaa El Sayed
dc.contributor.authorTantawi, Maha El
dc.contributor.authorElemineh, Demelash Abewa
dc.contributor.authorFaraj, Anwar
dc.contributor.authorHarandi, Majid Fasihi
dc.contributor.authorFatahi, Yousef
dc.contributor.authorFeigin, Valery L.
dc.contributor.authorFernandes, Eduarda
dc.contributor.authorFoigt, Nataliya A.
dc.contributor.authorForoutan, Masoud
dc.contributor.authorFranklin, Richard Charles
dc.contributor.authorGubari, Mohammed Ibrahim Mohialdeen
dc.contributor.authorGuido, Davide
dc.contributor.authorGuo, Yuming
dc.contributor.authorHaj-Mirzaian, Arvin
dc.contributor.authorAbdullah, Kanaan Hamagharib
dc.contributor.authorHamidi, Samer
dc.contributor.authorHerteliu, Claudiu
dc.contributor.authorDe Hidru, Hagos Degefa
dc.contributor.authorHigazi, Tarig B.
dc.contributor.authorHossain, Naznin
dc.contributor.authorHosseinzadeh, Mehdi
dc.contributor.authorHouseh, Mowafa
dc.contributor.authorIlesanmi, Olayinka Stephen
dc.contributor.authorIlic, Milena D.
dc.contributor.authorIlic, Irena M.
dc.contributor.authorIqbal, Usman
dc.contributor.authorIrvani, Seyed Sina Naghibi
dc.contributor.authorJha, Ravi Prakash
dc.contributor.authorJoukar, Farahnaz
dc.contributor.authorJozwiak, Jacek Jerzy
dc.contributor.authorKabir, Zubair
dc.contributor.authorKalankesh, Leila R.
dc.contributor.authorKalhor, Rohollah
dc.contributor.authorMatin, Behzad Karami
dc.contributor.authorKarimi, Salah Eddin
dc.contributor.authorKasaeian, Amir
dc.contributor.authorKavetskyy, Taras
dc.contributor.authorKayode, Gbenga A.
dc.contributor.authorKaryani, Ali Kazemi
dc.contributor.authorKelbore, Abraham Getachew
dc.contributor.authorKeramati, Maryam
dc.contributor.authorKhalilov, Rovshan
dc.contributor.authorKhan, Ejaz Ahmad
dc.contributor.authorKhan, Md Nuruzzaman Nuruzzaman
dc.contributor.authorKhatab, Khaled
dc.contributor.authorKhater, Mona M.
dc.contributor.authorKianipour, Neda
dc.contributor.authorKibret, Kelemu Tilahun
dc.contributor.authorKim, Yun Jin
dc.contributor.authorKosen, Soewarta
dc.contributor.authorKrohn, Kris J.
dc.contributor.authorKusuma, Dian
dc.contributor.authorLa Vecchia, Carlo
dc.contributor.authorLansingh, Charles
dc.contributor.authorLee, Paul H.
dc.contributor.authorLeGrand, Kate E.
dc.contributor.authorLi, Shanshan
dc.contributor.authorLongbottom, Joshua
dc.contributor.authorAbd El Razek, Hassan Magdy
dc.contributor.authorAbd El Razek, Muhammed Magdy
dc.contributor.authorMaleki, Afshin
dc.contributor.authorMamun, Abdullah A.
dc.contributor.authorManafi, Ali
dc.contributor.authorManafi, Navid
dc.contributor.authorMansournia, Mohammad Ali
dc.contributor.authorMartins- Melo, Francisco Rogerlandio
dc.contributor.authorMazidi, Mohsen
dc.contributor.authorMcAlinden, Colm
dc.contributor.authorMeharie, Birhanu Geta
dc.contributor.authorMendoza, Walter
dc.contributor.authorMengesha, Endalkachew Worku
dc.contributor.authorMengistu, Desalegn Tadese
dc.contributor.authorMereta, Seid Tiku
dc.contributor.authorMestrovic, Tomislav
dc.contributor.authorMiller, Ted R.
dc.contributor.authorMiri, Mohammad
dc.contributor.authorMoghadaszadeh, Masoud
dc.contributor.authorMohammadian-Hafshejani, Abdollah
dc.contributor.authorMohammadpourhodki, Reza
dc.contributor.authorMohammed, Shafiu
dc.contributor.authorMohammed, Salahuddin
dc.contributor.authorMoradi, Masoud
dc.contributor.authorMoradzadeh, Rahmatollah
dc.contributor.authorMoraga, Paula
dc.contributor.authorMosser, Jonathan F.
dc.contributor.authorNaderi, Mehdi
dc.contributor.authorNagarajan, Ahamarshan Jayaraman
dc.contributor.authorNaik, Gurudatta
dc.contributor.authorNegoi, Ionut
dc.contributor.authorNguyen, Cuong Tat
dc.contributor.authorNguyen, Huong Lan Thi
dc.contributor.authorNguyen, Trang Huyen
dc.contributor.authorNikbakhsh, Rajan
dc.contributor.authorOancea, Bogdan
dc.contributor.authorOlagunju, Tinuke O.
dc.contributor.authorOlagunju, Andrew T.
dc.contributor.authorBali, Ahmed Omar
dc.contributor.authorOnwujekwe, Obinna E.
dc.contributor.authorPana, Adrian
dc.contributor.authorPourjafar, Hadi
dc.contributor.authorRahim, Fakher
dc.contributor.authorRahman, Mohammad Hifz Ur
dc.contributor.authorRathi, Priya
dc.contributor.authorRawaf, Salman
dc.contributor.authorRawaf, David Laith
dc.contributor.authorRawassizadeh, Reza
dc.contributor.authorResnikoff, Serge
dc.contributor.authorReta, Melese Abate
dc.contributor.authorRezapour, Aziz
dc.contributor.authorRubagotti, Enrico
dc.contributor.authorRubino, Salvatore
dc.contributor.authorSadeghi, Ehsan
dc.contributor.authorSaghafipour, Abedin
dc.contributor.authorSajadi, S. Mohammad
dc.date.accessioned2022-12-14T04:46:33Z
dc.date.available2022-12-14T04:46:33Z
dc.date.issued2021-07-28
dc.descriptionSUPPORTING INFORMATION : FIGURE S1. Data coverage by year. Here we visualise the volume of data used in the analysis by country and year. Larger circles indicate more data inputs. ‘NA’ indicates records for which no year was reported (eg, ‘pre-2000’). https://doi.org/10.1371/journal.pntd.0008824.s001en_US
dc.descriptionFIGURE S2. Illustration of covariate values for year 2000. Maps were produced using ArcGIS Desktop 10.6. https://doi.org/10.1371/journal.pntd.0008824.s002en_US
dc.descriptionFIGURE S3. Environmental suitability of onchocerciasis including locations that have received MDA for which no pre-intervention data are available. This plot shows suitability predictions from green (low = 0%) to pink (high = 100%), representing those areas where environmental conditions are most similar to prior pathogen detections. Countries in grey with hatch marks were excluded from the analysis based on a review of national endemicity status. Areas in grey only represent locations masked due to sparse population. Maps were produced using ArcGIS Desktop 10.6 and shapefiles to visualize administrative units are available at https://espen.afro.who.int/tools-resources/cartography-database. https://doi.org/10.1371/journal.pntd.0008824.s003en_US
dc.descriptionFIGURE S4. Environmental suitability prediction uncertainty including locations that have received MDA for which no pre-intervention data are available. This plot shows uncertainty associated with environmental suitability predictions colored from blue to red (least to most uncertain). Countries in grey with hatch marks were excluded from the analysis based on a review of national endemicity status. Areas in grey only represent locations masked due to sparse population. Maps were produced using ArcGIS Desktop 10.6 and shapefiles to visualize administrative units are available at https://espen.afro.who.int/tools-resources/cartography-database. https://doi.org/10.1371/journal.pntd.0008824.s004en_US
dc.descriptionFIGURE S5. Environmental suitability of onchocerciasis excluding morbidity data. This plot shows suitability predictions from green (low = 0%) to pink (high = 100%), representing those areas where environmental conditions are most similar to prior pathogen detections. Countries in grey with hatch marks were excluded from the analysis based on a review of national endemicity status. Areas in grey only represent locations masked due to sparse population. Maps were produced using ArcGIS Desktop 10.6 and shapefiles to visualize administrative units are available at https://espen.afro.who.int/tools-resources/cartography-database. https://doi.org/10.1371/journal.pntd.0008824.s005en_US
dc.descriptionFIGURE S6. Environmental suitability prediction uncertainty excluding morbidity data. This plot shows uncertainty associated with environmental suitability predictions colored from blue to red (least to most uncertain). Countries in grey with hatch marks were excluded from the analysis based on a review of national endemicity status. Areas in grey only represent locations masked due to sparse population. https://doi.org/10.1371/journal.pntd.0008824.s006en_US
dc.descriptionFIGURE S7. Covariate Effect Curves for all onchocerciasis occurrences (measures of infection prevalence and disability). On the right set of axes we show the frequency density of the occurrences taking covariate values over 20 bins of the horizontal axis. The left set of axes shows the effect of each on the model, where the mean effect is plotted on the black line and its uncertainty is represented by the upper and lower confidence interval bounds plotted in dark grey. The figures show the fit per covariate relative to the data that correspond to specific values of the covariate. https://doi.org/10.1371/journal.pntd.0008824.s007en_US
dc.descriptionFIGURE S8. Covariate Effect Curves for all onchocerciasis occurrences (measures of infection prevalence and disability). On the right set of axes we show the frequency density of the occurrences taking covariate values over 20 bins of the horizontal axis. The left set of axes shows the effect of each on the model, where the mean effect is plotted on the black line and its uncertainty is represented by the upper and lower confidence interval bounds plotted in dark grey. https://doi.org/10.1371/journal.pntd.0008824.s008en_US
dc.descriptionFIGURE S9. ROC analysis for threshold. Results of the area under the receiver operating characteristic (ROC) curve analysis are presented below, with false positive rate (FPR) on the x-axis and true positive rate (TPR) on the y-axis. The red dot on the curve represents the location on the curve that corresponds to a threshold that most closely agreed with the input data. For each of the 100 BRT models, we estimated the optimal threshold that maximised agreement between occurrence inputs (considered true positives) and the mean model predictions as 0·71. https://doi.org/10.1371/journal.pntd.0008824.s009en_US
dc.descriptionTABLE S1. Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER) checklist. https://doi.org/10.1371/journal.pntd.0008824.s010en_US
dc.descriptionTABLE S2. Total number of occurrence data classified as point and polygon inputs by diagnostic. We present the total number of occurrence points extracted from the input data sources by diagnostic type. ‘Other diagnostics’ include: DEC Patch test; Knott’s Method (Mazotti Test); 2 types of LAMP; blood smears; and urine tests. https://doi.org/10.1371/journal.pntd.0008824.s011en_US
dc.descriptionTABLE S3. Total number of occurrence data classified as point and polygon inputs by location. https://doi.org/10.1371/journal.pntd.0008824.s012en_US
dc.descriptionTABLE S4. Covariate information. https://doi.org/10.1371/journal.pntd.0008824.s013en_US
dc.descriptionTEXT S1. Details outlining construction of occurrence dataset. https://doi.org/10.1371/journal.pntd.0008824.s014en_US
dc.descriptionTEXT S2. Covariate rationale. https://doi.org/10.1371/journal.pntd.0008824.s015en_US
dc.descriptionTEXT S3. Boosted regression tree methodology additional details. https://doi.org/10.1371/journal.pntd.0008824.s016en_US
dc.descriptionAPPENDIX S1. Country-level maps and data results. Maps were produced using ArcGIS Desktop 10.6 and shapefiles to visualize administrative units are available at https://espen.afro.who.int/tools-resources/cartography-database. https://doi.org/10.1371/journal.pntd.0008824.s017en_US
dc.description.abstractRecent evidence suggests that, in some foci, elimination of onchocerciasis from Africa may be feasible with mass drug administration (MDA) of ivermectin. To achieve continental elimination of transmission, mapping surveys will need to be conducted across all implementation units (IUs) for which endemicity status is currently unknown. Using boosted regression tree models with optimised hyperparameter selection, we estimated environmental suitability for onchocerciasis at the 5 × 5-km resolution across Africa. In order to classify IUs that include locations that are environmentally suitable, we used receiver operating characteristic (ROC) analysis to identify an optimal threshold for suitability concordant with locations where onchocerciasis has been previously detected. This threshold value was then used to classify IUs (more suitable or less suitable) based on the location within the IU with the largest mean prediction. Mean estimates of environmental suitability suggest large areas across West and Central Africa, as well as focal areas of East Africa, are suitable for onchocerciasis transmission, consistent with the presence of current control and elimination of transmission efforts. The ROC analysis identified a mean environmental suitability index of 071 as a threshold to classify based on the location with the largest mean prediction within the IU. Of the IUs considered for mapping surveys, 502% exceed this threshold for suitability in at least one 5 × 5-km location. The formidable scale of data collection required to map onchocerciasis endemicity across the African continent presents an opportunity to use spatial data to identify areas likely to be suitable for onchocerciasis transmission. National onchocerciasis elimination programmes may wish to consider prioritising these IUs for mapping surveys as human resources, laboratory capacity, and programmatic schedules may constrain survey implementation, and possibly delaying MDA initiation in areas that would ultimately qualify.en_US
dc.description.departmentMedical Microbiologyen_US
dc.description.librarianam2022en_US
dc.description.sponsorshipThis work was primarily supported by a grant from the Bill & Melinda Gates Foundation OPP1132415 (SIH). Financial support from the Neglected Tropical Disease Modelling Consortium (https://www.ntdmodelling.org/), which is funded by the Bill & Melinda Gates Foundation (grants No. OPP1184344 and OPP1186851), and joint centre funding (grant No. MR/R015600/1) by the UK Medical Research Council (MRC) and the UK Department for International Development (DFID) under the MRC/DFID Concordat agreement which is also part of the EDCTP2 programme supported by the European Union (MGB).en_US
dc.description.sponsorshipThe Neglected Tropical Disease Modelling Consortium which is funded by the Bill & Melinda Gates Foundation, the UK Medical Research Council (MRC) and the UK Department for International Development (DFID) under the MRC/DFID Concordat agreement which is also part of the EDCTP2 programme supported by the European Union (MGB).en_US
dc.description.urihttp://www.plosNTDS.orgen_US
dc.identifier.citationCromwell, E.A., Osborne, J.C.P., Unnasch, T.R., Basáñez, M.-G., Gass, K.M., Barbre, K.A., et al. (2021) Predicting the environmental suitability for onchocerciasis in Africa as an aid to elimination planning. PLoS Neglected Tropical Diseases 15(7): e0008824. https://DOI.org/10.1371/journal.pntd.0008824.en_US
dc.identifier.issn1935-2735 (print)
dc.identifier.issn1935-2727 (online)
dc.identifier.other10.1371/journal.pntd.0008824
dc.identifier.urihttps://repository.up.ac.za/handle/2263/88775
dc.language.isoenen_US
dc.publisherPublic Library of Scienceen_US
dc.rightsThe work is made available under the Creative Commons CC0.en_US
dc.subjectFocien_US
dc.subjectAfricaen_US
dc.subjectTransmissionen_US
dc.subjectMass drug administration (MDA)en_US
dc.subjectIvermectinen_US
dc.subjectImplementation units (IUs)en_US
dc.subjectElimination of transmissionen_US
dc.subjectReceiver operating characteristic (ROC)en_US
dc.titlePredicting the environmental suitability for onchocerciasis in Africa as an aid to elimination planningen_US
dc.typeArticleen_US

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