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1. Use of digital assessment tools to measure health facility readiness to provide the WHO recommended package of care for lymphatic filariasis morbidity.

Author

Bougma, Windtaré Roland, Aiogalé, Victorino Martinho, Attoumbre, Bienvenu Yao, Bartlett, Sarah, Brahima, Kouma, Coulibaly, Mamadou, Coulibaly, Yaya Ibrahim, Dicko, Boubacar Morou, D'Souza, Susan, Doumbia, Salif Seriba, Gargannah, Gar Mondyu, Musa, Balla, Ngom, Babacar, Norbert, Dje N'Goran, Nwosu, Christian, Papique, Alberto Luis, Rogers, Emerson J., Sarr, Astou, and Downs, Philip

Published
2024
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2. Impact Survey Results after SAFE Strategy Implementation in 15 Local Government Areas of Kebbi, Sokoto and Zamfara States, Nigeria

Author

Mpyet, Caleb, Muhammad, Nasiru, Adamu, Mohammed Dantani, Ladan, Mohammad, Willis, Rebecca, Umar, Murtala Muhammad, Alada, Joel, Aliero, Aliyu Attahiru, Bakhtiari, Ana, Flueckiger, Rebecca Mann, Olobio, Nicholas, Nwosu, Christian, Damina, Marthe, Gwom, Anita, Labbo, Abdullahi A, Boisson, Sophie, Isiyaku, Sunday, William, Adamani, Rabiu, Mansur M, Pavluck, Alexandre L, Gordon, Bruce A, Solomon, Anthony W, and Project, for the Global Trachoma Mapping

Subjects
Biomedical and Clinical Sciences, Ophthalmology and Optometry, Pediatric, Good Health and Well Being, Clean Water and Sanitation, Adolescent, Adult, Aged, Anti-Bacterial Agents, Child, Child, Preschool, Cross-Sectional Studies, Female, Humans, Hygiene, Infant, Male, Middle Aged, Nigeria, Prevalence, Risk Factors, Sanitation, Trachoma, Trichiasis, Water Supply, Young Adult, Blindness, Global Trachoma Mapping Project, sanitation, trachoma, trichiasis, water supply, Clinical Sciences, Opthalmology and Optometry, Public Health and Health Services, Epidemiology, Ophthalmology and optometry, Public health
Abstract

PurposeTo determine prevalence of trachoma after interventions in 15 local government areas (LGAs) of Kebbi, Sokoto and Zamfara States, Nigeria.MethodsA population-based impact survey was conducted in each LGA using Global Trachoma Mapping Project (GTMP) protocols. In each LGA, 25 villages were selected, except in Arewa LGA, where we selected 25 villages from each of four subunits to obtain finer-resolution prevalence information. Villages were selected with probability proportional to size. In each village, 25 households were enrolled and all consenting residents aged ≥1 year were examined by GTMP-certified graders for trachomatous inflammation-follicular (TF) and trachomatous trichiasis (TT). Information on sources of household water and types of sanitation facilities used was collected through questioning and direct observation.ResultsThe number of households enrolled per LGA ranged from 623 (Kware and Tangaza) to 2488 (Arewa). There have been marked reductions in the prevalence of TF and TT since baseline surveys were conducted in all 15 LGAs. Eight of the 15 LGAs have attained TF prevalences

Published
2018

3. Advances in filarial hydrocelectomy reporting in Uganda and Nigeria

Author

D’Souza, Susan F., primary, Awio, John P., additional, Albarka, Jehoshaphat, additional, Bougma, Windtaré Roland, additional, Bartlett, Sarah, additional, Nwosu, Christian, additional, Ngom, Babacar, additional, Wani, Anthony, additional, Gwom, Anita, additional, Okello, Moses, additional, Aba, Abraham, additional, Irema, Sarah, additional, Imhansoloeva, Martins, additional, Nurudeen, Dauda, additional, Wamboga, Charles, additional, Debam, Mark T., additional, Zainab, Haruna, additional, Aleiro, Attahiru, additional, Salah, Malam H., additional, and Downs, Philip, additional

Published
2024
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4. Advances in filarial hydrocelectomy reporting in Uganda and Nigeria.

Author

D'Souza, Susan F., Awio, John P., Albarka, Jehoshaphat, Bougma, Windtaré Roland, Bartlett, Sarah, Nwosu, Christian, Ngom, Babacar, Wani, Anthony, Gwom, Anita, Okello, Moses, Aba, Abraham, Irema, Sarah, Imhansoloeva, Martins, Nurudeen, Dauda, Wamboga, Charles, Debam, Mark T., Zainab, Haruna, Aleiro, Attahiru, Salah, Malam H., and Downs, Philip

Published
2024
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5. Tropical Data: Approach and Methodology as Applied to Trachoma Prevalence Surveys

Author

Harding-Esch, Emma M, primary, Burgert-Brucker, Clara R, additional, Jimenez, Cristina, additional, Bakhtiari, Ana, additional, Willis, Rebecca, additional, Bejiga, Michael Dejene, additional, Mpyet, Caleb, additional, Ngondi, Jeremiah, additional, Boyd, Sarah, additional, Abdala, Mariamo, additional, Abdou, Amza, additional, Adamu, Yilikal, additional, Alemayehu, Addisu, additional, Alemayehu, Wondu, additional, Al-Khatib, Tawfik, additional, Apadinuwe, Sue-Chen, additional, Awaca, Naomie, additional, Awoussi, Marcel S, additional, Baayendag, Gilbert, additional, Badiane, Mouctar Dieng, additional, Bailey, Robin L, additional, Batcho, Wilfrid, additional, Bay, Zulficar, additional, Bella, Assumpta, additional, Beido, Nassirou, additional, Bol, Yak Yak, additional, Bougouma, Clarisse, additional, Brady, Christopher J, additional, Bucumi, Victor, additional, Butcher, Robert, additional, Cakacaka, Risiate, additional, Cama, Anaseini, additional, Camara, Mamoudou, additional, Cassama, Eunice, additional, Chaora, Shorai Grace, additional, Chebbi, Amel Chenaoui, additional, Chisambi, Alvin Blessings, additional, Chu, Brian, additional, Conteh, Abdulai, additional, Coulibaly, Sidi Mohamed, additional, Courtright, Paul, additional, Dalmar, Abdi, additional, Dat, Tran Minh, additional, Davids, Thully, additional, Djaker, Mohamed El Amine, additional, de Fátima Costa Lopes, Maria, additional, Dézoumbé, Djore, additional, Dodson, Sarity, additional, Downs, Philip, additional, Eckman, Stephanie, additional, Elshafie, Bilghis Elkhair, additional, Elmezoghi, Mourad, additional, Elvis, Ange Aba, additional, Emerson, Paul, additional, Epée, Emilienne EE, additional, Faktaufon, Daniel, additional, Fall, Mawo, additional, Fassinou, Aréty, additional, Fleming, Fiona, additional, Flueckiger, Rebecca, additional, Gamael, Koizan Kadjo, additional, Garae, Mackline, additional, Garap, Jambi, additional, Gass, Katie, additional, Gebru, Genet, additional, Gichangi, Michael M, additional, Giorgi, Emanuele, additional, Goépogui, André, additional, Gómez, Daniela Vaz Ferreira, additional, Gómez Forero, Diana Paola, additional, Gower, Emily W, additional, Harte, Anna, additional, Henry, Rob, additional, Honorio-Morales, Harvy Alberto, additional, Ilako, Dunera R, additional, Issifou, Amadou Alfa Bio, additional, Jones, Ellen, additional, Kabona, George, additional, Kabore, Martin, additional, Kadri, Boubacar, additional, Kalua, Khumbo, additional, Kanyi, Sarjo Kebba, additional, Kebede, Shambel, additional, Kebede, Fikreab, additional, Keenan, Jeremy D, additional, Kello, Amir B, additional, Khan, Asad Aslam, additional, Khelifi, Houria, additional, Kilangalanga, Janvier, additional, Kim, Sung Hye, additional, Ko, Robert, additional, Lewallen, Susan, additional, Lietman, Thomas, additional, Logora, Makoy Samuel Yibi, additional, Lopez, Yuri A, additional, MacArthur, Chad, additional, Macleod, Colin, additional, Makangila, Felix, additional, Mariko, Brehima, additional, Martin, Diana L, additional, Masika, Michael, additional, Massae, Patrick, additional, Massangaie, Marilia, additional, Matendechero, Hadley S, additional, Mathewos, Tsedeke, additional, McCullagh, Siobhain, additional, Meite, Aboulaye, additional, Mendes, Elsa Palma, additional, Abdi, Hirpa M, additional, Miller, Hollman, additional, Minnih, Abdellahi, additional, Mishra, Sailesh Kumar, additional, Molefi, Tuduetso, additional, Mosher, Aryc, additional, M’Po, Nerkoua, additional, Mugume, Francis, additional, Mukwiza, Robson, additional, Mwale, Consity, additional, Mwatha, Stephen, additional, Mwingira, Upendo, additional, Nash, Scott D, additional, Nassa, Christophe, additional, Negussu, Nebiyu, additional, Nieba, Cece, additional, Noah Noah, Jean Claude, additional, Nwosu, Christian O, additional, Olobio, Nicholas, additional, Opon, Rapheal, additional, Pavluck, Alexandre, additional, Phiri, Isaac, additional, Rainima-Qaniuci, Merelesita, additional, Renneker, Kristen K, additional, Saboyá-Díaz, Martha Idalí, additional, Sakho, Fatoumata, additional, Sanha, Salimato, additional, Sarah, Virginia, additional, Sarr, Boubacar, additional, Szwarcwald, Celia L, additional, Shah Salam, Ahmad, additional, Sharma, Shekhar, additional, Seife, Fikre, additional, Serrano Chavez, Gloria Marina, additional, Sissoko, Mactar, additional, Sitoe, Henis Mior, additional, Sokana, Oliver, additional, Tadesse, Fentahun, additional, Taleo, Fasiah, additional, Talero, Sandra Liliana, additional, Tarfani, Youcef, additional, Tefera, Amsayaw, additional, Tekeraoi, Rabebe, additional, Tesfazion, Andeberhan, additional, Traina, Abubaker, additional, Traoré, Lamine, additional, Trujillo-Trujillo, Julián, additional, Tukahebwa, Edridah M, additional, Vashist, Praveen, additional, Wanyama, Ernest B, additional, Warusavithana, Supriya D.P., additional, Watitu, Titus K, additional, West, Sheila, additional, Win, Ye, additional, Woods, Geordie, additional, Yajima, Aya, additional, Yaya, Georges, additional, Zecarias, Alem, additional, Zewengiel, Solomon, additional, Zoumanigui, Akoi, additional, Hooper, Pamela J, additional, Millar, Tom, additional, Rotondo, Lisa, additional, and Solomon, Anthony W, additional

Published
2023
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8. Tropical Data: Approach and Methodology as Applied to Trachoma Prevalence Surveys

Author

Harding-Esch, Emma M, Burgert-Brucker, Clara R, Jimenez, Cristina, Bakhtiari, Ana, Willis, Rebecca, Bejiga, Michael Dejene, Mpyet, Caleb, Ngondi, Jeremiah, Boyd, Sarah, Abdala, Mariamo, Abdou, Amza, Adamu, Yilikal, Alemayehu, Addisu, Alemayehu, Wondu, Al-Khatib, Tawfik, Apadinuwe, Sue-Chen, Awaca, Naomie, Awoussi, Marcel S, Baayendag, Gilbert, Badiane, Mouctar Dieng, Bailey, Robin L, Batcho, Wilfrid, Bay, Zulficar, Bella, Assumpta, Beido, Nassirou, Bol, Yak Yak, Bougouma, Clarisse, Brady, Christopher J, Bucumi, Victor, Butcher, Robert, Cakacaka, Risiate, Cama, Anaseini, Camara, Mamoudou, Cassama, Eunice, Chaora, Shorai Grace, Chebbi, Amel Chenaoui, Chisambi, Alvin Blessings, Chu, Brian, Conteh, Abdulai, Coulibaly, Sidi Mohamed, Courtright, Paul, Dalmar, Abdi, Dat, Tran Minh, Davids, Thully, Djaker, Mohamed El Amine, de Fátima Costa Lopes, Maria, Dézoumbé, Djore, Dodson, Sarity, Downs, Philip, Eckman, Stephanie, Elshafie, Bilghis Elkhair, Elmezoghi, Mourad, Elvis, Ange Aba, Emerson, Paul, Epée, Emilienne EE, Faktaufon, Daniel, Fall, Mawo, Fassinou, Aréty, Fleming, Fiona, Flueckiger, Rebecca, Gamael, Koizan Kadjo, Garae, Mackline, Garap, Jambi, Gass, Katie, Gebru, Genet, Gichangi, Michael M, Giorgi, Emanuele, Goépogui, André, Gómez, Daniela Vaz Ferreira, Gómez Forero, Diana Paola, Gower, Emily W, Harte, Anna, Henry, Rob, Honorio-Morales, Harvy Alberto, Ilako, Dunera R, Issifou, Amadou Alfa Bio, Jones, Ellen, Kabona, George, Kabore, Martin, Kadri, Boubacar, Kalua, Khumbo, Kanyi, Sarjo Kebba, Kebede, Shambel, Kebede, Fikreab, Keenan, Jeremy D, Kello, Amir B, Khan, Asad Aslam, Khelifi, Houria, Kilangalanga, Janvier, Kim, Sung Hye, Ko, Robert, Lewallen, Susan, Lietman, Thomas, Logora, Makoy Samuel Yibi, Lopez, Yuri A, MacArthur, Chad, Macleod, Colin, Makangila, Felix, Mariko, Brehima, Martin, Diana L, Masika, Michael, Massae, Patrick, Massangaie, Marilia, Matendechero, Hadley S, Mathewos, Tsedeke, McCullagh, Siobhain, Meite, Aboulaye, Mendes, Elsa Palma, Abdi, Hirpa M, Miller, Hollman, Minnih, Abdellahi, Mishra, Sailesh Kumar, Molefi, Tuduetso, Mosher, Aryc, M’Po, Nerkoua, Mugume, Francis, Mukwiza, Robson, Mwale, Consity, Mwatha, Stephen, Mwingira, Upendo, Nash, Scott D, Nassa, Christophe, Negussu, Nebiyu, Nieba, Cece, Noah Noah, Jean Claude, Nwosu, Christian O, Olobio, Nicholas, Opon, Rapheal, Pavluck, Alexandre, Phiri, Isaac, Rainima-Qaniuci, Merelesita, Renneker, Kristen K, Saboyá-Díaz, Martha Idalí, Sakho, Fatoumata, Sanha, Salimato, Sarah, Virginia, Sarr, Boubacar, Szwarcwald, Celia L, Shah Salam, Ahmad, Sharma, Shekhar, Seife, Fikre, Serrano Chavez, Gloria Marina, Sissoko, Mactar, Sitoe, Henis Mior, Sokana, Oliver, Tadesse, Fentahun, Taleo, Fasiah, Talero, Sandra Liliana, Tarfani, Youcef, Tefera, Amsayaw, Tekeraoi, Rabebe, Tesfazion, Andeberhan, Traina, Abubaker, Traoré, Lamine, Trujillo-Trujillo, Julián, Tukahebwa, Edridah M, Vashist, Praveen, Wanyama, Ernest B, Warusavithana, Supriya D.P., Watitu, Titus K, West, Sheila, Win, Ye, Woods, Geordie, Yajima, Aya, Yaya, Georges, Zecarias, Alem, Zewengiel, Solomon, Zoumanigui, Akoi, Hooper, Pamela J, Millar, Tom, Rotondo, Lisa, Solomon, Anthony W, Harding-Esch, Emma M, Burgert-Brucker, Clara R, Jimenez, Cristina, Bakhtiari, Ana, Willis, Rebecca, Bejiga, Michael Dejene, Mpyet, Caleb, Ngondi, Jeremiah, Boyd, Sarah, Abdala, Mariamo, Abdou, Amza, Adamu, Yilikal, Alemayehu, Addisu, Alemayehu, Wondu, Al-Khatib, Tawfik, Apadinuwe, Sue-Chen, Awaca, Naomie, Awoussi, Marcel S, Baayendag, Gilbert, Badiane, Mouctar Dieng, Bailey, Robin L, Batcho, Wilfrid, Bay, Zulficar, Bella, Assumpta, Beido, Nassirou, Bol, Yak Yak, Bougouma, Clarisse, Brady, Christopher J, Bucumi, Victor, Butcher, Robert, Cakacaka, Risiate, Cama, Anaseini, Camara, Mamoudou, Cassama, Eunice, Chaora, Shorai Grace, Chebbi, Amel Chenaoui, Chisambi, Alvin Blessings, Chu, Brian, Conteh, Abdulai, Coulibaly, Sidi Mohamed, Courtright, Paul, Dalmar, Abdi, Dat, Tran Minh, Davids, Thully, Djaker, Mohamed El Amine, de Fátima Costa Lopes, Maria, Dézoumbé, Djore, Dodson, Sarity, Downs, Philip, Eckman, Stephanie, Elshafie, Bilghis Elkhair, Elmezoghi, Mourad, Elvis, Ange Aba, Emerson, Paul, Epée, Emilienne EE, Faktaufon, Daniel, Fall, Mawo, Fassinou, Aréty, Fleming, Fiona, Flueckiger, Rebecca, Gamael, Koizan Kadjo, Garae, Mackline, Garap, Jambi, Gass, Katie, Gebru, Genet, Gichangi, Michael M, Giorgi, Emanuele, Goépogui, André, Gómez, Daniela Vaz Ferreira, Gómez Forero, Diana Paola, Gower, Emily W, Harte, Anna, Henry, Rob, Honorio-Morales, Harvy Alberto, Ilako, Dunera R, Issifou, Amadou Alfa Bio, Jones, Ellen, Kabona, George, Kabore, Martin, Kadri, Boubacar, Kalua, Khumbo, Kanyi, Sarjo Kebba, Kebede, Shambel, Kebede, Fikreab, Keenan, Jeremy D, Kello, Amir B, Khan, Asad Aslam, Khelifi, Houria, Kilangalanga, Janvier, Kim, Sung Hye, Ko, Robert, Lewallen, Susan, Lietman, Thomas, Logora, Makoy Samuel Yibi, Lopez, Yuri A, MacArthur, Chad, Macleod, Colin, Makangila, Felix, Mariko, Brehima, Martin, Diana L, Masika, Michael, Massae, Patrick, Massangaie, Marilia, Matendechero, Hadley S, Mathewos, Tsedeke, McCullagh, Siobhain, Meite, Aboulaye, Mendes, Elsa Palma, Abdi, Hirpa M, Miller, Hollman, Minnih, Abdellahi, Mishra, Sailesh Kumar, Molefi, Tuduetso, Mosher, Aryc, M’Po, Nerkoua, Mugume, Francis, Mukwiza, Robson, Mwale, Consity, Mwatha, Stephen, Mwingira, Upendo, Nash, Scott D, Nassa, Christophe, Negussu, Nebiyu, Nieba, Cece, Noah Noah, Jean Claude, Nwosu, Christian O, Olobio, Nicholas, Opon, Rapheal, Pavluck, Alexandre, Phiri, Isaac, Rainima-Qaniuci, Merelesita, Renneker, Kristen K, Saboyá-Díaz, Martha Idalí, Sakho, Fatoumata, Sanha, Salimato, Sarah, Virginia, Sarr, Boubacar, Szwarcwald, Celia L, Shah Salam, Ahmad, Sharma, Shekhar, Seife, Fikre, Serrano Chavez, Gloria Marina, Sissoko, Mactar, Sitoe, Henis Mior, Sokana, Oliver, Tadesse, Fentahun, Taleo, Fasiah, Talero, Sandra Liliana, Tarfani, Youcef, Tefera, Amsayaw, Tekeraoi, Rabebe, Tesfazion, Andeberhan, Traina, Abubaker, Traoré, Lamine, Trujillo-Trujillo, Julián, Tukahebwa, Edridah M, Vashist, Praveen, Wanyama, Ernest B, Warusavithana, Supriya D.P., Watitu, Titus K, West, Sheila, Win, Ye, Woods, Geordie, Yajima, Aya, Yaya, Georges, Zecarias, Alem, Zewengiel, Solomon, Zoumanigui, Akoi, Hooper, Pamela J, Millar, Tom, Rotondo, Lisa, and Solomon, Anthony W

Abstract

Population-based prevalence surveys are essential for decision-making on interventions to achieve trachoma elimination as a public health problem. This paper outlines the methodologies of Tropical Data, which supports work to undertake those surveys. Tropical Data is a consortium of partners that supports health ministries worldwide to conduct globally standardised prevalence surveys that conform to World Health Organization recommendations. Founding principles are health ministry ownership, partnership and collaboration, and quality assurance and quality control at every step of the survey process. Support covers survey planning, survey design, training, electronic data collection and fieldwork, and data management, analysis and dissemination. Methods are adapted to meet local context and needs. Customisations, operational research and integration of other diseases into routine trachoma surveys have also been supported. Between 29 February 2016 and 24 April 2023, 3373 trachoma surveys across 50 countries have been supported, resulting in 10,818,502 people being examined for trachoma. This health ministry-led, standardised approach, with support from the start to the end of the survey process, has helped all trachoma elimination stakeholders to know where interventions are needed, where interventions can be stopped, and when elimination as a public health problem has been achieved. Flexibility to meet specific country contexts, adaptation to changes in global guidance and adjustments in response to user feedback have facilitated innovation in evidence-based methodologies, and supported health ministries to strive for global disease control targets.

Published
2023

9. Improving data use in trachomatous trichiasis programmes: operationalisation of the TT Tracker.

Author

Bartlett, Sarah, Ngom, Babacar, Olobio, Nicholas, Badiane, Mouctar Dieng, Tarboh, Godwin, Diagne, Aliou, and Nwosu, Christian

Subjects
EYE diseases, CELL phones, MOBILE apps, TELEPHONE calls, TRACHOMA
Abstract

Trachoma is a disease of the eye and the leading infectious cause of blindness worldwide. Years of repeated infections can cause in-turning of the lashes so that they rub against the eyeball, causing pain, discomfort and, if left untreated, blindness. This is known as trachomatous trichiasis (TT) and can be remedied by surgery. To improve oversight and reporting of TT outreach, Sightsavers developed a mobile phone application called the TT Tracker so that TT surgeons, assistants and supervisors can collect and analyse information about surgical outcomes and performance and determine when and where follow-up appointments are required. The TT Tracker is being used by seven national programmes. Examples of use and programme improvements from Nigeria, Benin and Senegal are discussed here. [ABSTRACT FROM AUTHOR]

Published
2023
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10. Groundwater exploration using vertical electrical sounding techniques in parts of Etche Local Government Area of Rivers State, Nigeria

Author

Nwankwoala, Hycienth Ogunka, Osayande Ayo Desmond, Nwosu, Christian Hemetu, and Ugwu Sylvester Amunabo

Subjects
Geophysical investigation, Resistivity, Groundwater, aquifer, Etche, Rivers State
Abstract

Vertical Electrical Sounding (VES) was carried out in parts of Etche Local Government Area, Rivers State, Nigeria to investigate availability of groundwater. An ABEM SAS 1000 terrameter was used. Schlumberger configuration was adopted for the sounding to acquire a 4 point data, with the use of ID Interpex software in order to know the subsurface variations in resistivity with respect to depth. The investigation revealed the subsurface, thickness of lithology, prolific aquiferous zones, the resistivity curve portrays an overall increase in resistivity trend ranging from 228.7Ωm - 5872Ωm. The resistivity trend in the form of ρ1< ρ2< ρ3< ρ4< ρ5, indicates the presence of conductive materials present at a shallow depth of the point of survey. The highest resistivity value is observed in the fifth layer and it is believed to have gravely sized particles. A stratigraphic layer with gravely sized particles in this area revealed a good aquifer quality with reasonable quantity of aquifer fluid contained within the interconnected pore spaces. This zone of the studied area contains rock units from the geoelectric section such as silt, medium sand, coarse sand and gravel. The fifth layer is the prospect zone for aquifer delineation. A geoelectric section drawn from the resistivity data shows that the first layer is silt, the second layer is fine sand, the third layer is medium sand, the fourth layer is silty sand, the fifth layer is fine sand and the sixth layer is medium sand. The sixth layer is believed to be the prospect zone for aquifer characterization. A suitable data from drilled boreholes should be introduced to this study so as to have a profound knowledge and views about the grain size, sphericity, roundness and parking. These characteristics will be useful to determine the dominant grain size existing in these aquifers and characterize them appropriately.

Published
2022
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14. Process Analysis and Optimization of Crude Glycerol Autothermal Reforming Using Response Surface Methodology and Artificial Neural Network

Author

Nwosu, Christian Ekejiuba, Ibrahim, Hussameldin, Henni, Amr, Muthu, Jacob, and El-Darieby, Mohamed

Abstract

A Thesis Submitted to the Faculty of Graduate Studies and Research In Partial Fulfillment of the Requirements for the Degree of Master of Applied Science in Process Systems Engineering , University of Regina. xv, 167 p. There is an urgent need to curtail the effects of global warming through the development of efficient, cheap and accessible alternative source of energy since the combustion of carbon containing compounds has become a problem. The combustion of hydrogen gas for example for either heat generation or use as fuel cells in automobiles produces only water vapour as by-product. Though, water vapour is also greenhouse gas, it does not last long in the atmosphere when released since hydrologic cycle ensures the excess water vapour is sent down via precipitation. Based on this and in addition to its high heat capacity, the use of hydrogen as an alternative to fossil fuel has become highly beneficial. Hydrogen gas can be cheaply produced from glycerol; a major waste product in bio-diesel gas production which contains very high impurities and requires a lot of money for purifications. This research work therefore focused on the in-situ production of hydrogen gas as well as optimization from crude glycerol using a very stable catalyst without having to undergo some purification steps thereby saving cost. The methodology deployed in this research work in their respective order involves; (1) the preparation of 5%Ni/CeZrCa catalyst with great performance and activity (2) characterization of the prepared catalyst via: TGA, N2 physisorption, XRD, TPR and XRF, (3) design of experiment using central composite design (CCD), (4) preparation of crude glycerol which mirrors waste glycerol from a typical bio-diesel production station, (5) laboratory experiment for hydrogen gas production through autothermal reforming of crude glycerol method which involves two important parts; partial oxidation and steam reforming processes. The experiments were carried out following the design of experiment with CCD which involves catalytic and non-catalytic runs to evaluate the performance of the catalyst. (6) optimization of hydrogen gas using response surface methodology (RSM) and artificial neural network (ANN). The design of experiment was executed with the following range of input variables; temperature: 500 - 650oC, crude glycerol flow rate: 0.0019 - 0.0033 mols C/min, Steam to carbon ratio: 1.6 - 3.6, Oxygen to carbon ratio: 0.05 – 0.2, Catalyst weight: 0.05 - 0.25g. The highest feed conversion and yield were 92 mol% and 0.995 mols respectively at temp: 575oC, feed flow rate: 0.0026 mols C/min, S/C center point of: 0.78, O/C: 0.13 and catalyst weight of 0.15g. The fitted quadratic model using RSM gave a coefficient of determination R2 of 0.951, an RMSE of 1.51% and AAD of 3.14%. and also established best operating conditions for hydrogen productions as temp: 650oC, feed flow rate: 0.0033 mols C/min, S/C: 2.34, O/C: 0.052 and catalyst weight of 0.15g with catalyst size constantly maintained at 0.05mm. Furthermore, the results of the variable ranking of the ANN using the connection weight approach showed that temperature has the highest influence with a ranking weight of 53% while O/C has the least influence with a ranking weight of 3%. The regression analysis of the ANN using the Levenberg-Marquardt Model and TANSIG as transfer function gave better results with an R2 of 0.999, MSE: 10-8, AAD: 0.34% and RMSE: 3.5x10-4%. A standard quadratic polynomial equation has been established for hydrogen gas production and optimization in the autothermal reforming process. Also, optimum conditions required for hydrogen gas production has been established. From the results of RSM and ANN predictions and those of R2, AAD, RMSE and MSE obtained, it is evidently clear that the ANN model was superior to RSM in predicting hydrogen gas. Student yes

Published
2020

17. future of data management for pediatric cataract.

Author

Bartlett, Sarah, Hassan, Amina, Ibrahim, Nazaradden, Isiyaku, Sunday, Muhammad, Nasiru, Ngom, Babacar, and Nwosu, Christian

Subjects
CATARACT, DATA management, BLINDNESS in children, EXECUTIVE departments, EYE care
Abstract

Cataract is a leading cause of blindness in children worldwide. Blindness can be treated with effective surgery, but in low-resource settings this treatment can be difficult to access. In addition, positive outcomes of the surgery are heavily dependent on comprehensive postoperative care. To date in Nigeria and many other low-resource countries, robust electronic data-management systems that help facility teams to manage their patient data, especially when it comes to tracking children for follow-up visits after surgery, have either yet to be put into place or are in place but have yet to be refined to respond to the specific needs of eye care programs. Sightsavers has worked with multiple state ministries in Nigeria to set up and test a system that responds to those needs. [ABSTRACT FROM AUTHOR]

Published
2022
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18. Prevalence of Trachoma in 47 Administrative Districts of Zambia: Results of 32 Population-Based Prevalence Surveys

Author

Mwale, Consity, primary, Mumbi, Willard, additional, Funjika, Misa, additional, Sokesi, Teddy, additional, Silumesii, Andrew, additional, Mulenga, Muma, additional, Mutati, Grace, additional, Kwendakwema, Davison, additional, Chelu, Chisanga, additional, Adamu, Yilikal, additional, Alemayehu, Wondu, additional, Al-Khatib, Tawfik, additional, Bakhtiari, Ana, additional, Dejene, Michael, additional, Massae, Patrick A., additional, Mpyet, Caleb, additional, Nwosu, Christian, additional, Willis, Rebecca, additional, Courtright, Paul, additional, and Solomon, Anthony W., additional

Published
2018
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19. Impact Survey Results after SAFE Strategy Implementation in 15 Local Government Areas of Kebbi, Sokoto and Zamfara States, Nigeria.

Author

for the Global Trachoma Mapping Project, Alada, Joel, Mpyet, Caleb, Labbo, Abdullahi A, Boisson, Sophie, Gordon, Bruce A., Rabiu, Mansur M., Solomon, Anthony W., Nwosu, Christian, Damina, Marthe, Gwom, Anita, Isiyaku, Sunday, William, Adamani, Muhammad, Nasiru, Adamu, Mohammed Dantani, Ladan, Mohammad, Willis, Rebecca, Bakhtiari, Ana, Flueckiger, Rebecca Mann, and Pavluck, Alexandre L.

Subjects
BLINDNESS, TRACHOMA, SANITATION, WATER supply, LOCAL government
Abstract

Purpose: To determine prevalence of trachoma after interventions in 15 local government areas (LGAs) of Kebbi, Sokoto and Zamfara States, Nigeria. Methods: A population-based impact survey was conducted in each LGA using Global Trachoma Mapping Project (GTMP) protocols. In each LGA, 25 villages were selected, except in Arewa LGA, where we selected 25 villages from each of four subunits to obtain finer-resolution prevalence information. Villages were selected with probability proportional to size. In each village, 25 households were enrolled and all consenting residents aged ≥1 year were examined by GTMP-certified graders for trachomatous inflammation—follicular (TF) and trachomatous trichiasis (TT). Information on sources of household water and types of sanitation facilities used was collected through questioning and direct observation. Results: The number of households enrolled per LGA ranged from 623 (Kware and Tangaza) to 2488 (Arewa). There have been marked reductions in the prevalence of TF and TT since baseline surveys were conducted in all 15 LGAs. Eight of the 15 LGAs have attained TF prevalences <5% in children, while 10 LGAs have attained TT prevalences <0.2% in persons aged ≥15 years. Between 49% and 96% of households had access to water for hygiene purposes within 1 km of the household, while only 10-59% had access to improved sanitation facilities. Conclusion: Progress towards elimination of trachoma has been made in these 15 LGAs. Collaboration with water and sanitation agencies and community-based trichiasis surgery are still needed in order to eliminate trachoma by the year 2020. [ABSTRACT FROM AUTHOR]

Published
2018
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20. The future of data management for pediatric cataract.

Author

Bartlett S, Hassan A, Ibrahim N, Isiyaku S, Muhammad N, Ngom B, and Nwosu C

Subjects
Blindness etiology, Child, Data Management, Humans, Nigeria, Cataract complications, Cataract therapy, Cataract Extraction adverse effects
Abstract

Cataract is a leading cause of blindness in children worldwide. Blindness can be treated with effective surgery, but in low-resource settings this treatment can be difficult to access. In addition, positive outcomes of the surgery are heavily dependent on comprehensive postoperative care. To date in Nigeria and many other low-resource countries, robust electronic data-management systems that help facility teams to manage their patient data, especially when it comes to tracking children for follow-up visits after surgery, have either yet to be put into place or are in place but have yet to be refined to respond to the specific needs of eye care programs. Sightsavers has worked with multiple state ministries in Nigeria to set up and test a system that responds to those needs., (© The Author(s) 2022. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene.)

Published
2022
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