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3. Fully-automated patient-level malaria assessment on field-prepared thin blood film microscopy images, including Supplementary Information

Author

Delahunt, Charles B., Jaiswal, Mayoore S., Horning, Matthew P., Janko, Samantha, Thompson, Clay M., Kulhare, Sourabh, Hu, Liming, Ostbye, Travis, Yun, Grace, Gebrehiwot, Roman, Wilson, Benjamin K., Long, Earl, Proux, Stephane, Gamboa, Dionicia, Chiodini, Peter, Carter, Jane, Dhorda, Mehul, Isaboke, David, Ogutu, Bernhards, Oyibo, Wellington, Villasis, Elizabeth, Tun, Kyaw Myo, Bachman, Christine, Bell, David, and Mehanian, Courosh

Subjects
Computer Science - Machine Learning, Electrical Engineering and Systems Science - Image and Video Processing, Statistics - Machine Learning, 68T10, I.5.0
Abstract

Malaria is a life-threatening disease affecting millions. Microscopy-based assessment of thin blood films is a standard method to (i) determine malaria species and (ii) quantitate high-parasitemia infections. Full automation of malaria microscopy by machine learning (ML) is a challenging task because field-prepared slides vary widely in quality and presentation, and artifacts often heavily outnumber relatively rare parasites. In this work, we describe a complete, fully-automated framework for thin film malaria analysis that applies ML methods, including convolutional neural nets (CNNs), trained on a large and diverse dataset of field-prepared thin blood films. Quantitation and species identification results are close to sufficiently accurate for the concrete needs of drug resistance monitoring and clinical use-cases on field-prepared samples. We focus our methods and our performance metrics on the field use-case requirements. We discuss key issues and important metrics for the application of ML methods to malaria microscopy., Comment: 16 pages, 13 figures

Published
2019

6. An automated slide scanning system for membrane filter imaging in diagnosis of urogenital schistosomiasis

Author

Oyibo, P.O. (author), Agbana, T.E. (author), van Lieshout, Lisette (author), Oyibo, Wellington (author), Diehl, J.C. (author), Vdovin, Gleb (author), Oyibo, P.O. (author), Agbana, T.E. (author), van Lieshout, Lisette (author), Oyibo, Wellington (author), Diehl, J.C. (author), and Vdovin, Gleb (author)

Abstract

Traditionally, automated slide scanning involves capturing a rectangular grid of field-of-view (FoV) images which can be stitched together to create whole slide images, while the autofocusing algorithm captures a focal stack of images to determine the best in-focus image. However, these methods can be timeconsuming due to the need for X-, Y- and Z-axis movements of the digital microscope while capturing multiple FoV images. In this paper, we propose a solution to minimise these redundancies by presenting an optimal procedure for automated slide scanning of circular membrane filters on a glass slide. We achieve this by following an optimal path in the sample plane, ensuring that only FoVs overlapping the filter membrane are captured. To capture the best infocus FoV image, we utilise a hill-climbing approach that tracks the peak of the mean of Gaussian gradient of the captured FoVs images along the Z-axis. We implemented this procedure to optimise the efficiency of the Schistoscope, an automated digital microscope developed to diagnose urogenital schistosomiasis by imaging Schistosoma haematobium eggs on 13 or 25 mm membrane filters. Our improved method reduces the automated slide scanning time by 63.18%and 72.52% for the respective filter sizes. This advancement greatly supportsthe practicality of the Schistoscope in large-scale schistosomiasis monitoringand evaluation programs in endemic regions. This will save time, resources andalso accelerate generation of data that is critical in achieving the targets for schistosomiasis elimination., Team Michel Verhaegen, Design for Sustainability

Published
2024
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10. Performance of a fully‐automated system on a WHO malaria microscopy evaluation slide set

Author

Horning, Matthew P., Delahunt, Charles B., Bachman, Christine M., Luchavez, Jennifer, Luna, Christian, Hu, Liming, Jaiswal, Mayoore S., Thompson, Clay M., Kulhare, Sourabh, Janko, Samantha, Wilson, Benjamin K., Ostbye, Travis, Mehanian, Martha, Gebrehiwot, Roman, Yun, Grace, Bell, David, Proux, Stephane, Carter, Jane Y., Oyibo, Wellington, Gamboa, Dionicia, Dhorda, Mehul, Vongpromek, Ranitha, Chiodini, Peter L., Ogutu, Bernhards, Long, Earl G., Tun, Kyaw, Burkot, Thomas R., Lilley, Ken, and Mehanian, Courosh

Published
2021
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15. Two-stage automated diagnosis framework for urogenital schistosomiasis in microscopy images from low-resource settings

Author

Oyibo, P.O. (author), Meulah, Brice (author), Bengtson, Michel (author), Lieshout, Lisette van (author), Oyibo, Wellington (author), Diehl, J.C. (author), Vdovin, Gleb (author), Agbana, T.E. (author), Oyibo, P.O. (author), Meulah, Brice (author), Bengtson, Michel (author), Lieshout, Lisette van (author), Oyibo, Wellington (author), Diehl, J.C. (author), Vdovin, Gleb (author), and Agbana, T.E. (author)

Abstract

Purpose: Automated diagnosis of urogenital schistosomiasis using digital microscopy images of urine slides is an essential step toward the elimination of schistosomiasis as a disease of public health concern in Sub-Saharan African countries. We create a robust image dataset of urine samples obtained from field settings and develop a two-stage diagnosis framework for urogenital schistosomiasis. Approach: Urine samples obtained from field settings were captured using the Schistoscope device, and S. haematobium eggs present in the images were manually annotated by experts to create the SH dataset. Next, we develop a two-stage diagnosis framework, which consists of semantic segmentation of S. haematobium eggs using the DeepLabv3-MobileNetV3 deep convolutional neural network and a refined segmentation step using ellipse fitting approach to approximate the eggs with an automatically determined number of ellipses. We defined two linear inequality constraints as a function of the overlap coefficient and area of a fitted ellipses. False positive diagnosis resulting from over-segmentation was further minimized using these constraints. We evaluated the performance of our framework on 7605 images from 65 independent urine samples collected from field settings in Nigeria, by deploying our algorithm on an Edge AI system consisting of Raspberry Pi + Coral USB accelerator. Result: The SH dataset contains 12,051 images from 103 independent urine samples and the developed urogenital schistosomiasis diagnosis framework achieved clinical sensitivity, specificity, and precision of 93.8%, 93.9%, and 93.8%, respectively, using results from an experienced microscopist as reference. Conclusion: Our detection framework is a promising tool for the diagnosis of urogenital schistosomiasis as our results meet the World Health Organization target product profile requirements for monitoring and evaluation of schistosomiasis control programs., Team Michel Verhaegen, Design for Sustainability

Published
2023
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16. Pf7: an open dataset of Plasmodium falciparum genome variation in 20,000 worldwide samples

Author

Abdel Hamid, Muzamil Mahdi, Abdelraheem, Mohamed Hassan, Acheampong, Desmond Omane, Ahouidi, Ambroise, Ali, Mozam, Almagro-Garcia, Jacob, Amambua-Ngwa, Alfred, Amaratunga, Chanaki, Amenga-Etego, Lucas, Andagalu, Ben, Anderson, Tim, Andrianaranjaka, Voahangy, Aniebo, Ifeyinwa, Aninagyei, Enoch, Ansah, Felix, Ansah, Patrick, Apinjoh, Tobias, Arnaldo, Paulo, Ashley, Elizabeth, Auburn, Sarah, Awandare, Gordon, Ba, Hampate, Baraka, Vito, Barry, Alyssa, Bejon, Philip, Bertin, Gwladys, Boni, Maciej, Borrmann, Steffen, Bousema, Teun, Bouyou-Akotet, Marielle, Branch, Oralee, Bull, Peter, Cheah, Huch, Chindavongsa, Keobouphaphone, Chookajorn, Thanat, Chotivanich, Kesinee, Claessens, Antoine, Conway, David, Corredor, Vladimir, Courtier, Erin, Craig, Alister, d'Alessandro, Umberto, Dama, Souleymane, Day, Nicholas, Denis, Brigitte, Dhorda, Mehul, Diakite, Mahamadou, Djimde, Abdoulaye, Dolecek, Christiane, Dondorp, Arjen, Doumbia, Seydou, Drakeley, Chris, Drury, Eleanor, Duffy, Patrick, Echeverry, Diego, Egwang, Thomas, Enosse, Sonia Maria Mauricio, Erko, Berhanu, Fairhurst, Rick, Faiz, Abdul, Fanello, Caterina, Fleharty, Mark, Forbes, Matthew, Fukuda, Mark, Gamboa, Dionicia, Ghansah, Anita, Golassa, Lemu, Goncalves, Sonia, Harrison, G, Healy, Sara Anne, Hendry, Jason, Hernandez-Koutoucheva, Anastasia, Hien, Tran Tinh, Hill, Catherine, Hombhanje, Francis, Hott, Amanda, Htut, Ye, Hussein, Mazza, Imwong, Mallika, Ishengoma, Deus, Jackson, Scott, Jacob, Chris, Jeans, Julia, Johnson, Kimberly, Kamaliddin, Claire, Kamau, Edwin, Keatley, Jon, Kochakarn, Theerarat, Konate, Drissa, Konaté, Abibatou, Kone, Aminatou, Kwiatkowski, Dominic, Kyaw, Myat, Kyle, Dennis, Lawniczak, Mara, Lee, Samuel, Lemnge, Martha, Lim, Pharath, Lon, Chanthap, Loua, Kovana, Mandara, Celine, Marfurt, Jutta, Marsh, Kevin, Maude, Richard James, Mayxay, Mayfong, Maïga-Ascofaré, Oumou, Miotto, Olivo, Mita, Toshihiro, Mobegi, Victor, Mohamed, Abdelrahim Osman, Mokuolu, Olugbenga, Montgomery, Jaqui, Morang'A, Collins Misita, Mueller, Ivo, Murie, Kathryn, Newton, Paul, Ngo Duc, Thang, Nguyen, Thuy, Nguyen, Thuy-Nhien, Nguyen Thi Kim, Tuyen, Nguyen Van, Hong, Noedl, Harald, Nosten, François, Noviyanti, Rintis, Ntui, Vincent Ntui-Njock, Nzila, Alexis, Ochola-Oyier, Lynette Isabella, Ocholla, Harold, Oduro, Abraham, Omedo, Irene, Onyamboko, Marie, Ouedraogo, Jean-Bosco, Oyebola, Kolapo, Oyibo, Wellington Aghoghovwia, Pearson, Richard, Peshu, Norbert, Phyo, Aung, Plowe, Christopher, Price, Ric, Pukrittayakamee, Sasithon, Quang, Huynh Hong, Randrianarivelojosia, Milijaona, Rayner, Julian, Ringwald, Pascal, Rosanas-Urgell, Anna, Rovira-Vallbona, Eduard, Ruano-Rubio, Valentin, Ruiz, Lastenia, Saunders, David, Shayo, Alex, Siba, Peter, Simpson, Victoria, Sissoko, Mahamadou, Smith, Christen, Su, Xin-Zhuan, Sutherland, Colin, Takala-Harrison, Shannon, Talman, Arthur, Tavul, Livingstone, Thanh, Ngo Viet, Thathy, Vandana, Thu, Aung Myint, Toure, Mahamoudou, Tshefu, Antoinette, Verra, Federica, Vinetz, Joseph, Wellems, Thomas, Wendler, Jason, White, Nicholas, Whitton, Georgia, Yavo, William, van der Pluijm, Rob, MalariaGEN, University of Khartoum, University of Cape Coast [Ghana], Université Cheikh Anta Diop [Dakar, Sénégal] (UCAD), The Wellcome Trust Sanger Institute [Cambridge], London School of Hygiene and Tropical Medicine [Fajara, Gambia], London School of Hygiene and Tropical Medicine (LSHTM), National Institute of Allergy and Infectious Diseases [Bethesda] (NIAID-NIH), National Institutes of Health [Bethesda] (NIH), West African Centre for Cell Biology of Infectious Pathogens [Legon, Ghana] (WACCBIP), University of Ghana, Navrongo Health Research Centre [Navrongo, Ghana] (NHRC), Kenya Medical Research Institute (KEMRI), Texas Biomedical Research Institute [San Antonio, TX], Université d'Antananarivo, University of Buéa, Instituto Nacional de Saude [Maputo, Mozambique] (INS), Centre for Tropical Medicine and Global Health [Oxford, UK], Nuffield Department of Medicine [Oxford, UK] (Big Data Institute), University of Oxford-University of Oxford, Mahidol Oxford Tropical Medicine Research Unit (MORU), University of Oxford-Mahidol University [Bangkok]-Wellcome Trust, Menzies School of Health Research [Australia], Charles Darwin University [Australia], Nuffield Department of Clinical Medicine [Oxford], University of Oxford, Institut de Recherche pour le Développement (IRD), Laboratory of Pathogen and Host Immunity [Montpellier] (LPHI), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), Maladies infectieuses et vecteurs : écologie, génétique, évolution et contrôle (MIVEGEC), and Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Université de Montpellier (UM)

Subjects
data resource, lnfectious Diseases and Global Health Radboud Institute for Health Sciences [Radboudumc 4], plasmodium falciparum, genomics, malaria, Medicine (miscellaneous), genomic epidemiology, General Biochemistry, Genetics and Molecular Biology, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology
Abstract

Contains fulltext : 291985.pdf (Publisher’s version ) (Open Access) We describe the MalariaGEN Pf7 data resource, the seventh release of Plasmodium falciparum genome variation data from the MalariaGEN network. It comprises over 20,000 samples from 82 partner studies in 33 countries, including several malaria endemic regions that were previously underrepresented. For the first time we include dried blood spot samples that were sequenced after selective whole genome amplification, necessitating new methods to genotype copy number variations. We identify a large number of newly emerging crt mutations in parts of Southeast Asia, and show examples of heterogeneities in patterns of drug resistance within Africa and within the Indian subcontinent. We describe the profile of variations in the C-terminal of the csp gene and relate this to the sequence used in the RTS,S and R21 malaria vaccines. Pf7 provides high-quality data on genotype calls for 6 million SNPs and short indels, analysis of large deletions that cause failure of rapid diagnostic tests, and systematic characterisation of six major drug resistance loci, all of which can be freely downloaded from the MalariaGEN website.

Published
2023

18. Declining responsiveness of childhood Plasmodium falciparum infections to artemisinin-based combination treatments ten years following deployment as first-line antimalarials in Nigeria

Author

Sowunmi, Akintunde, Ntadom, Godwin, Akano, Kazeem, Ibironke, Folasade O., Ayede, Adejumoke I., Agomo, Chimere, Folarin, Onikepe A., Gbotosho, Grace O., Happi, Christian, Oguche, Stephen, Okafor, Henrietta U., Meremikwu, Martin, Agomo, Philip, Ogala, William, Watila, Ismaila, Mokuolu, Olugbenga, Finomo, Finomo, Ebenebe, Joy C., Jiya, Nma, Ambe, Jose, Wammanda, Robinson, Emechebe, George, Oyibo, Wellington, Useh, Francis, Aderoyeje, Temitope, Dokunmu, Titilope M., Alebiosu, Omobolaji T., Amoo, Sikiru, Basorun, Oluwabunmi K., Wewe, Olubunmi A., Okafor, Chukwuebuka, Akpoborie, Odafe, Fatunmbi, Bayo, Adewoye, Elsie O., Ezeigwe, Nnenna M., and Oduola, Ayoade

Published
2019
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19. Pf7: an open dataset of Plasmodium falciparum genome variation in 20,000 worldwide samples

Author

MalariaGEN, Abdel Hamid, Muzamil Mahdi, Abdelraheem, Mohamed Hassan, Acheampong, Desmond Omane, Ahouidi, Ambroise, Ali, Mozam, Almagro-Garcia, Jacob, Amambua-Ngwa, Alfred, Amaratunga, Chanaki, Amenga-Etego, Lucas, Andagalu, Ben, Anderson, Tim, Andrianaranjaka, Voahangy, Aniebo, Ifeyinwa, Aninagyei, Enoch, Ansah, Felix, Ansah, Patrick O, Apinjoh, Tobias, Arnaldo, Paulo, Ashley, Elizabeth, Auburn, Sarah, Awandare, Gordon A, Ba, Hampate, Baraka, Vito, Barry, Alyssa, Bejon, Philip, Bertin, Gwladys I, Boni, Maciej F, Borrmann, Steffen, Bousema, Teun, Bouyou-Akotet, Marielle, Branch, Oralee, Bull, Peter C, Cheah, Huch, Chindavongsa, Keobouphaphone, Chookajorn, Thanat, Chotivanich, Kesinee, Claessens, Antoine, Conway, David J, Corredor, Vladimir, Courtier, Erin, Craig, Alister, D'Alessandro, Umberto, Dama, Souleymane, Day, Nicholas, Denis, Brigitte, Dhorda, Mehul, Diakite, Mahamadou, Djimde, Abdoulaye, Dolecek, Christiane, Dondorp, Arjen, Doumbia, Seydou, Drakeley, Chris, Drury, Eleanor, Duffy, Patrick, Echeverry, Diego F, Egwang, Thomas G, Enosse, Sonia Maria Mauricio, Erko, Berhanu, Fairhurst, Rick M, Faiz, Abdul, Fanello, Caterina A, Fleharty, Mark, Forbes, Matthew, Fukuda, Mark, Gamboa, Dionicia, Ghansah, Anita, Golassa, Lemu, Goncalves, Sonia, Harrison, GL Abby, Healy, Sara Anne, Hendry, Jason A, Hernandez-Koutoucheva, Anastasia, Hien, Tran Tinh, Hill, Catherine A, Hombhanje, Francis, Hott, Amanda, Htut, Ye, Hussein, Mazza, Imwong, Mallika, Ishengoma, Deus, Jackson, Scott A, Jacob, Chris G, Jeans, Julia, Johnson, Kimberly J, Kamaliddin, Claire, Kamau, Edwin, Keatley, Jon, Kochakarn, Theerarat, Konate, Drissa S, Konaté, Abibatou, Kone, Aminatou, Kwiatkowski, Dominic P, Kyaw, Myat P, Kyle, Dennis, Lawniczak, Mara, Lee, Samuel K, Lemnge, Martha, Lim, Pharath, Lon, Chanthap, Loua, Kovana M, Mandara, Celine I, Marfurt, Jutta, Marsh, Kevin, Maude, Richard James, Mayxay, Mayfong, Maïga-Ascofaré, Oumou, Miotto, Olivo, Mita, Toshihiro, Mobegi, Victor, Mohamed, Abdelrahim Osman, Mokuolu, Olugbenga A, Montgomery, Jaqui, Morang'a, Collins Misita, Mueller, Ivo, Murie, Kathryn, Newton, Paul N, Ngo Duc, Thang, Nguyen, Thuy, Nguyen, Thuy-Nhien, Nguyen Thi Kim, Tuyen, Nguyen Van, Hong, Noedl, Harald, Nosten, Francois, Noviyanti, Rintis, Ntui, Vincent Ntui-Njock, Nzila, Alexis, Ochola-Oyier, Lynette Isabella, Ocholla, Harold, Oduro, Abraham, Omedo, Irene, Onyamboko, Marie A, Ouedraogo, Jean-Bosco, Oyebola, Kolapo, Oyibo, Wellington Aghoghovwia, Pearson, Richard, Peshu, Norbert, Phyo, Aung P, Plowe, Christopher V, Price, Ric N, Pukrittayakamee, Sasithon, Quang, Huynh Hong, Randrianarivelojosia, Milijaona, Rayner, Julian C, Ringwald, Pascal, Rosanas-Urgell, Anna, Rovira-Vallbona, Eduard, Ruano-Rubio, Valentin, Ruiz, Lastenia, Saunders, David, Shayo, Alex, Siba, Peter, Simpson, Victoria J, Sissoko, Mahamadou S, Smith, Christen, Su, Xin-Zhuan, Sutherland, Colin, Takala-Harrison, Shannon, Talman, Arthur, Tavul, Livingstone, Thanh, Ngo Viet, Thathy, Vandana, Thu, Aung Myint, Toure, Mahamoudou, Tshefu, Antoinette, Verra, Federica, Vinetz, Joseph, Wellems, Thomas E, Wendler, Jason, White, Nicholas J, Whitton, Georgia, Yavo, William, Van Der Pluijm, Rob W, Amenga-Etego, Lucas [0000-0003-4468-0506], Anderson, Tim [0000-0002-0191-0204], Ansah, Patrick O [0000-0002-3214-5621], Ashley, Elizabeth [0000-0002-7620-4822], Ba, Hampate [0000-0002-9299-5775], Baraka, Vito [0000-0001-9694-9293], Bejon, Philip [0000-0002-2135-7549], Bertin, Gwladys I [0000-0002-2218-9591], Boni, Maciej F [0000-0002-0830-9630], Bousema, Teun [0000-0003-2666-094X], Chookajorn, Thanat [0000-0003-2876-6203], Claessens, Antoine [0000-0002-4277-0914], Conway, David J [0000-0002-8711-3037], Craig, Alister [0000-0003-0914-6164], D'Alessandro, Umberto [0000-0001-6341-5009], Day, Nicholas [0000-0003-2309-1171], Diakite, Mahamadou [0000-0002-4268-8857], Djimde, Abdoulaye [0000-0003-0062-2283], Dondorp, Arjen [0000-0001-5190-2395], Drakeley, Chris [0000-0003-4863-075X], Echeverry, Diego F [0000-0003-0301-4478], Erko, Berhanu [0000-0003-1685-752X], Faiz, Abdul [0000-0002-3460-7535], Fanello, Caterina A [0000-0003-1932-9562], Gamboa, Dionicia [0000-0002-1420-7729], Golassa, Lemu [0000-0002-1216-8711], Healy, Sara Anne [0000-0003-3078-6094], Ishengoma, Deus [0000-0003-2040-3416], Jackson, Scott A [0000-0002-3172-1607], Kamaliddin, Claire [0000-0001-8198-6235], Kamau, Edwin [0000-0002-5761-7883], Konate, Drissa S [0000-0002-4177-9642], Kwiatkowski, Dominic P [0000-0002-5023-0176], Kyle, Dennis [0000-0002-0238-965X], Lawniczak, Mara [0000-0002-3006-2080], Loua, Kovana M [0000-0003-0571-0944], Marsh, Kevin [0000-0001-8377-5466], Mayxay, Mayfong [0000-0002-6056-4516], Miotto, Olivo [0000-0001-8060-6771], Mita, Toshihiro [0000-0001-8180-2344], Mobegi, Victor [0000-0002-1962-5583], Morang'a, Collins Misita [0000-0002-6988-150X], Nguyen, Thuy-Nhien [0000-0002-4101-5706], Nosten, Francois [0000-0002-7951-0745], Ntui, Vincent Ntui-Njock [0000-0002-7532-9930], Oduro, Abraham [0000-0002-4191-7419], Onyamboko, Marie A [0000-0002-7501-5931], Ouedraogo, Jean-Bosco [0000-0003-0412-8733], Oyebola, Kolapo [0000-0002-1003-2570], Pearson, Richard [0000-0002-7386-3566], Phyo, Aung P [0000-0002-0383-9624], Price, Ric N [0000-0003-2000-2874], Rayner, Julian C [0000-0002-9835-1014], Rosanas-Urgell, Anna [0000-0002-0432-5203], Shayo, Alex [0000-0002-7099-8537], Su, Xin-Zhuan [0000-0003-3246-3248], Vinetz, Joseph [0000-0001-8344-2004], Wellems, Thomas E [0000-0003-3899-8454], and Apollo - University of Cambridge Repository

Subjects
data resource, plasmodium falciparum, genomics, malaria, genomic epidemiology
Abstract

We describe the MalariaGEN Pf7 data resource, the seventh release of Plasmodium falciparum genome variation data from the MalariaGEN network. It comprises over 20,000 samples from 82 partner studies in 33 countries, including several malaria endemic regions that were previously underrepresented. For the first time we include dried blood spot samples that were sequenced after selective whole genome amplification, necessitating new methods to genotype copy number variations. We identify a large number of newly emerging crt mutations in parts of Southeast Asia, and show examples of heterogeneities in patterns of drug resistance within Africa and within the Indian subcontinent. We describe the profile of variations in the C-terminal of the csp gene and relate this to the sequence used in the RTS,S and R21 malaria vaccines. Pf7 provides high-quality data on genotype calls for 6 million SNPs and short indels, analysis of large deletions that cause failure of rapid diagnostic tests, and systematic characterisation of six major drug resistance loci, all of which can be freely downloaded from the MalariaGEN website.

Published
2023

20. Performance Evaluation of the Schistoscope 5.0 for (Semi-)automated Digital Detection and Quantification of Schistosoma haematobium Eggs in Urine: A Field-based Study in Nigeria

Author

Meulah, Brice, primary, Oyibo, Prosper, additional, Bengtson, Michel, additional, Agbana, Temitope, additional, Lontchi, Roméo Aimé Laclong, additional, Adegnika, Ayola Akim, additional, Oyibo, Wellington, additional, Hokke, Cornelis Hendrik, additional, Diehl, Jan Carel, additional, and van Lieshout, Lisette, additional

Published
2022
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21. Malaria parasite density and detailed qualitative microscopy enhances large-scale profiling of infection endemicity in Nigeria

Author

Oyibo, Wellington, primary, Latham, Victoria, additional, Oladipo, Oladosu, additional, Ntadom, Godwin, additional, Uhomoibhi, Perpetua, additional, Ogbulafor, Nnnena, additional, Okoronkwo, Chukwu, additional, Okoh, Festus, additional, Mahmoud, Aminu, additional, Shekarau, Emmanuel, additional, Oresanya, Olusola, additional, Cherima, Yakubu Joel, additional, Jalingo, Innua, additional, Abba, Bintu, additional, Audu, Mohammed, additional, and Conway, David J., additional

Published
2022
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24. Schistoscope: An Automated Microscope with Artificial Intelligence for Detection of Schistosoma haematobium Eggs in Resource-Limited Settings

Author

Oyibo, Prosper, primary, Jujjavarapu, Satyajith, additional, Meulah, Brice, additional, Agbana, Tope, additional, Braakman, Ingeborg, additional, van Diepen, Angela, additional, Bengtson, Michel, additional, van Lieshout, Lisette, additional, Oyibo, Wellington, additional, Vdovine, Gleb, additional, and Diehl, Jan-Carel, additional

Published
2022
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31. Geographical and temporal variation in reduction of malaria infection among children under 5 years of age throughout Nigeria

Author

Oyibo, Wellington, primary, Ntadom, Godwin, additional, Uhomoibhi, Perpetua, additional, Oresanya, Olusola, additional, Ogbulafor, Nnenna, additional, Ajumobi, Olufemi, additional, Okoh, Festus, additional, Maxwell, Kolawole, additional, Ezeiru, Sonachi, additional, Nwokolo, Ernest, additional, Amajoh, Chioma, additional, Ezeigwe, Nnenna, additional, Audu, Mohammed, additional, and Conway, David, additional

Published
2021
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32. Geographical and temporal variation in reduction of malaria infection among children under five years of age throughout Nigeria

Author

Oyibo, Wellington, primary, Ntadom, Godwin, additional, Uhomoibhi, Perpetua, additional, Oresanya, Olusola, additional, Ogbulafor, Nnenna, additional, Ajumobi, Olufemi, additional, Okoh, Festus, additional, Maxwell, Kolawole, additional, Ezeiru, Sonachi, additional, Nwokolo, Ernest, additional, Amajoh, Chioma, additional, Ezeigwe, Nnenna, additional, Audu, Mohammed, additional, and Conway, David J., additional

Published
2021
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35. Fully-automated patient-level malaria assessment on field-prepared thin blood film microscopy images

Author

Delahunt, Charles B., primary, Jaiswal, Mayoore S., additional, Horning, Matthew P., additional, Janko, Samantha, additional, Thompson, Clay M., additional, Kulhare, Sourabh, additional, Hu, Liming, additional, Ostbye, Travis, additional, Yun, Grace, additional, Gebrehiwot, Roman, additional, Wilson, Benjamin K., additional, Long, Earl, additional, Proux, Stephane, additional, Gamboa, Dionicia, additional, Chiodini, Peter, additional, Carter, Jane, additional, Dhorda, Mehul, additional, Isaboke, David, additional, Ogutu, Bernhards, additional, Oyibo, Wellington, additional, Villasis, Elizabeth, additional, Tun, Kyaw Myo, additional, Bachman, Christine, additional, Bell, David, additional, and Mehanian, Courosh, additional

Published
2019
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37. Quantification of malaria antigens PfHRP2 and pLDH by quantitative suspension array technology in whole blood, dried blood spot and plasma

Author

Martiáñez-Vendrell, Xavier, primary, Jiménez, Alfons, additional, Vásquez, Ana, additional, Campillo, Ana, additional, Incardona, Sandra, additional, González, Raquel, additional, Gamboa, Dionicia, additional, Torres, Katherine, additional, Oyibo, Wellington, additional, Faye, Babacar, additional, Macete, Eusebio, additional, Menéndez, Clara, additional, Ding, Xavier C., additional, and Mayor, Alfredo, additional

Published
2019
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41. Blood transfer devices for malaria rapid diagnostic tests: evaluation of accuracy, safety and ease of use

Author

Albertini Audrey, Asiimwe Caroline, Mationg Mary, Luchavez Jennifer, Oyibo Wellington, Hopkins Heidi, González Iveth J, Gatton Michelle L, and Bell David

Subjects
Arctic medicine. Tropical medicine, RC955-962, Infectious and parasitic diseases, RC109-216
Abstract

Abstract Background Malaria rapid diagnostic tests (RDTs) are increasingly used by remote health personnel with minimal training in laboratory techniques. RDTs must, therefore, be as simple, safe and reliable as possible. Transfer of blood from the patient to the RDT is critical to safety and accuracy, and poses a significant challenge to many users. Blood transfer devices were evaluated for accuracy and precision of volume transferred, safety and ease of use, to identify the most appropriate devices for use with RDTs in routine clinical care. Methods Five devices, a loop, straw-pipette, calibrated pipette, glass capillary tube, and a new inverted cup device, were evaluated in Nigeria, the Philippines and Uganda. The 227 participating health workers used each device to transfer blood from a simulated finger-prick site to filter paper. For each transfer, the number of attempts required to collect and deposit blood and any spilling of blood during transfer were recorded. Perceptions of ease of use and safety of each device were recorded for each participant. Blood volume transferred was calculated from the area of blood spots deposited on filter paper. Results The overall mean volumes transferred by devices differed significantly from the target volume of 5 microliters (p < 0.001). The inverted cup (4.6 microliters) most closely approximated the target volume. The glass capillary was excluded from volume analysis as the estimation method used is not compatible with this device. The calibrated pipette accounted for the largest proportion of blood exposures (23/225, 10%); exposures ranged from 2% to 6% for the other four devices. The inverted cup was considered easiest to use in blood collection (206/226, 91%); the straw-pipette and calibrated pipette were rated lowest (143/225 [64%] and 135/225 [60%] respectively). Overall, the inverted cup was the most preferred device (72%, 163/227), followed by the loop (61%, 138/227). Conclusions The performance of blood transfer devices varied in this evaluation of accuracy, blood safety, ease of use, and user preference. The inverted cup design achieved the highest overall performance, while the loop also performed well. These findings have relevance for any point-of-care diagnostics that require blood sampling.

Published
2011
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42. Global sequence variation in the histidine-rich proteins 2 and 3 of Plasmodium falciparum: implications for the performance of malaria rapid diagnostic tests

Author

Gamboa Dionicia, Echeverry Diego F, Djalle Djibrine, Cunningham Jane, Bell David, Barnwell John, Ariey Frederic, Albertini Audrey, Abdullah Salim, Chen Nanhua, Gatton Michelle, Pelecanos Anita, Ho Mei-Fong, Baker Joanne, Hii Jeffery, Kyaw Myat, Luchavez Jennifer, Membi Christopher, Menard Didier, Murillo Claribel, Nhem Sina, Ogutu Bernhards, Onyor Pamela, Oyibo Wellington, Wang Shan, McCarthy James, and Cheng Qin

Subjects
Arctic medicine. Tropical medicine, RC955-962, Infectious and parasitic diseases, RC109-216
Abstract

Abstract Background Accurate diagnosis is essential for prompt and appropriate treatment of malaria. While rapid diagnostic tests (RDTs) offer great potential to improve malaria diagnosis, the sensitivity of RDTs has been reported to be highly variable. One possible factor contributing to variable test performance is the diversity of parasite antigens. This is of particular concern for Plasmodium falciparum histidine-rich protein 2 (PfHRP2)-detecting RDTs since PfHRP2 has been reported to be highly variable in isolates of the Asia-Pacific region. Methods The pfhrp2 exon 2 fragment from 458 isolates of P. falciparum collected from 38 countries was amplified and sequenced. For a subset of 80 isolates, the exon 2 fragment of histidine-rich protein 3 (pfhrp3) was also amplified and sequenced. DNA sequence and statistical analysis of the variation observed in these genes was conducted. The potential impact of the pfhrp2 variation on RDT detection rates was examined by analysing the relationship between sequence characteristics of this gene and the results of the WHO product testing of malaria RDTs: Round 1 (2008), for 34 PfHRP2-detecting RDTs. Results Sequence analysis revealed extensive variations in the number and arrangement of various repeats encoded by the genes in parasite populations world-wide. However, no statistically robust correlation between gene structure and RDT detection rate for P. falciparum parasites at 200 parasites per microlitre was identified. Conclusions The results suggest that despite extreme sequence variation, diversity of PfHRP2 does not appear to be a major cause of RDT sensitivity variation.

Published
2010
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48. Factors contributing to anaemia after uncomplicated falciparum malaria in under five year-old Nigerian children ten years following adoption of artemisinin-based combination therapies as first-line antimalarials

Author

Sowunmi, Akintunde, primary, Fatunmbi, Bayo, additional, Akano, Kazeem, additional, Wewe, Olubunmi A., additional, Agomo, Chimere, additional, Finomo, Finomo, additional, Ebenebe, Joy, additional, Jiya, Nma, additional, Ambe, Jose, additional, Wammanda, Robinson, additional, Ntadom, Godwin, additional, Mokuolu, Olugbenga, additional, Emechebe, George, additional, Ezeigwe, Nnenna, additional, Ayede, Adejumoke I., additional, Adewoye, Elsie O., additional, Gbotosho, Grace O., additional, Folarin, Onikepe A., additional, Happi, Christian T., additional, Oguche, Stephen, additional, Oyibo, Wellington A., additional, and Useh, Francis, additional

Published
2017
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50. Computer-Automated Malaria Diagnosis and Quantitation Using Convolutional Neural Networks

Author

Mehanian, Courosh, primary, Jaiswal, Mayoore, additional, Delahunt, Charles, additional, Thompson, Clay, additional, Horning, Matt, additional, Hu, Liming, additional, McGuire, Shawn, additional, Ostbye, Travis, additional, Mehanian, Martha, additional, Wilson, Ben, additional, Champlin, Cary, additional, Long, Earl, additional, Proux, Stephane, additional, Gamboa, Dionicia, additional, Chiodini, Peter, additional, Carter, Jane, additional, Dhorda, Mehul, additional, Isaboke, David, additional, Ogutu, Bernhards, additional, Oyibo, Wellington, additional, Villasis, Elizabeth, additional, Tun, Kyaw Myo, additional, Bachman, Christine, additional, and Bell, David, additional

Published
2017
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