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1. Tuberculosis and HIV co-infection: its impact on quality of life

Author

Belachew Tefera, Wogi Ajeme, Daba Shallo, Negussu Nebiyu, Hailmichael Yohannes, Tesfaye Markos, Deribew Amare, Apers Ludwig, and Colebunders Robert

Subjects
Computer applications to medicine. Medical informatics, R858-859.7
Abstract

Abstract Background- Very little is known about the quality of life of tuberculosis (TB) and HIV co-infected patients. In this study in Ethiopia, we compared the quality of life HIV positive patients with and without TB. Methods- A cross sectional study was conducted from February to April, 2009 in selected hospitals in Oromiya Regional state, Ethiopia. The study population consisted of 467 HIV patients and 124 TB/HIV co-infected patients. Data on quality of life was collected by trained nurses through face to face interviews using the short Amharic version of the World Health Organization Quality of Life Instrument for HIV clients (WHOQOL HIV). Depression was assessed using a validated version of the Kessler scale. Data was collected by trained nurses and analyzed using SPSS 15.0 statistical software. Results TB/HIV co-infected patients had a lower quality of life in all domains as compared to HIV infected patients without active TB. Depression, having a source of income and family support were strongly associated with most of the Quality of life domains. In co-infected patients, individuals who had depression were 8.8 times more likely to have poor physical health as compared to individuals who had no depression, OR = 8.8(95%CI: 3.2, 23). Self-stigma was associated with a poor quality of life in the psychological domain. Conclusion- The TB control program should design strategies to improve the quality of life of TB/HIV co-infected patients. Depression and self-stigma should be targeted for intervention to improve the quality of life of patients.

Published
2009
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2. 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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5. How well do coverage surveys and programmatically reported mass drug administration coverage match? Results from 214 mass drug administration campaigns in 15 countries, 2008–2017

Author

Zoerhoff, Kathryn L, primary, Mbabazi, Pamela S, additional, Gass, Katherine, additional, Kraemer, John, additional, Fuller, Brian B, additional, Blair, Lynsey, additional, Bougma, Roland, additional, Meite, Aboulaye, additional, Negussu, Nebiyu, additional, Gashaw, Bizuayehu, additional, Nash, Scott D, additional, Biritwum, Nana-Kwadwo, additional, Lemoine, Jean Frantz, additional, Ullyartha Pangaribuan, Helena, additional, Wijayanti, Eksi, additional, Kollie, Karsor, additional, Rasoamanamihaja, Clara Fabienne, additional, Juziwelo, Lazarus, additional, Mkwanda, Square, additional, Rimal, Pradip, additional, Gnandou, Issa, additional, Diop, Bocar, additional, Dorkenoo, Ameyo Monique, additional, Bronzan, Rachel, additional, Tukahebwa, Edridah Muheki, additional, Kabole, Fatima, additional, Yevstigneyeva, Violetta, additional, Bisanzio, Donal, additional, Courtney, Lauren, additional, Koroma, Joseph, additional, Endayishimye, Egide, additional, Reithinger, Richard, additional, Baker, Margaret C, additional, and Fleming, Fiona M, additional

Published
2023
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6. Prevalence of Trachoma after Implementation of Trachoma Elimination Interventions in Oromia Regional State, Ethiopia: Results of Impact Surveys in 131 Evaluation Units Covering 139 Districts.

Author

Miecha, Hirpa, Dejene, Michael, Adugna, Dereje, Kebede, Ageru, Yadeta, Damtew, Alemayehu, Addisu, Abateneh, Aemero, Wondimu, Asfaw, Dayessa, Mihiret, Shafi, Muhammed, Taye, Emawayish, Balcha, Leta, Gadisa, Solomon, Negussu, Nebiyu, Mengistu, Belete, Willis, Rebecca, Jimenez, Cristina, Bakhtiari, Ana, Boyd, Sarah, and Kebede, Biruk

Subjects
TRACHOMA, HOUSEHOLD surveys, ACCESS to information, CONFIDENCE intervals, DRINKING water, HOUSEHOLDS
Abstract

To determine the prevalence of trachomatous inflammation—follicular (TF), trachomatous trichiasis (TT), water, sanitation, and hygiene (WASH) access in 131 evaluation units (EUs) after implementation of trachoma elimination interventions in Oromia Region, Ethiopia. A population-based cross-sectional survey was conducted in each EU using the World Health Organization-recommended two-stage cluster-sampling methodology. Twenty-six clusters, each with a mean of 30 households were enumerated in each EU. All residents aged ≥1 year in selected households were examined for TF and TT. Information on WASH access in surveyed households was also collected through questioning the household head and direct observation. A total of 419,858 individuals were enumerated in 131 EUs, of whom 396,134 (94%) were examined, 54% being female. Age-adjusted EU-level prevalence of TF in children aged 1–9 years ranged from 0.15% (95% confidence interval [CI]: 0.0–0.4) to 37.5% (95% CI: 31.1–43.7). The TF prevalence was <5% in 73/131 (56%) EUs. The EU-level age- and gender-adjusted prevalence of TT unknown to the health system among people aged ≥15 years ranged from 0.001% (95% CI: 0.00–0.02) to 2.2% (95% CI: 1.1–3.1) with 37/131 (28%) EUs having a prevalence <0.2%. Only 48% of all households surveyed had access to improved water sources for drinking. Approximately 96% of households did not have an improved latrine. Oromia is on the path towards elimination of trachoma as a public health problem. [ABSTRACT FROM AUTHOR]

Published
2023
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7. Prevalence of Trachoma in Pre-validation Surveillance Surveys in 11 Evaluation Units (Covering 12 Districts) in Oromia Regional State, Ethiopia: Results from 2018−2020.

Author

Miecha, Hirpa, Dejene, Michael, Adugna, Dereje, Kebede, Ageru, Yadeta, Damtew, Alemayehu, Addisu, Abateneh, Aemero, Dayessa, Mihiret, Shafi, Muhammed, Taye, Emawayish, Balcha, Leta, Negussu, Nebiyu, Mengistu, Belete, Willis, Rebecca, Jimenez, Cristina, Bakhtiari, Ana, Boyd, Sarah, Kebede, Biruk, Tadesse, Fantahun, and Mamo, Ayele

Subjects
TRACHOMA, CHLAMYDIA trachomatis, INFECTIOUS disease transmission, OPERATIONS research, TOILETS, DRINKING water
Abstract

Interventions to reduce the prevalence of trachoma and transmission of ocular Chlamydia trachomatis have been implemented in Oromia Region, Ethiopia. Following an impact survey in which the trachomatous inflammation—follicular (TF) prevalence in 1–9-year-olds is <5%, a surveillance survey is recommended 2 years later, without additional antibiotic treatment. We report results of surveillance surveys in 11 evaluation units (EUs) covering 12 districts in Oromia Region, to plan whether future interventions are needed. We use a two-stage cluster-sampling cross-sectional survey design. In each EU, 26 clusters (villages) were systematically selected with probability proportional to size; from each cluster, 30 households were selected using compact segment sampling. Water, sanitation and hygiene (WASH) access was assessed in all selected households. All residents of selected households aged ≥1 year were examined for TF and trachomatous trichiasis (TT) by certified graders. Of 31,991 individuals enumerated, 29,230 (91% of) individuals were examined. Eight EUs had an age-adjusted TF prevalence in 1−9-year-olds of ≥5% and seven had a TT prevalence unknown to the health system among adults aged ≥15 years of ≥0.2%. About one-third of visited households had access to an improved water source for drinking, and 5% had access to an improved latrine. Despite TF reductions to <5% at impact survey, prevalence recrudesced to ≥5% in all but three of the 11 EUs. Operational research is needed to understand transmission dynamics and epidemiology, in order to optimise elimination strategies in high-transmission settings like these. [ABSTRACT FROM AUTHOR]

Published
2023
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8. Prevalence of Trachoma from 66 Impact Surveys in 52 Woredas of Southern Nations, Nationalities and Peoples' and Sidama Regions of Ethiopia, 2017–2019.

Author

Seyum, Dawit, Fetene, Nigusie, Kifle, Tezera, Negash, Habtamu, Kabeto, Temesgen, Gebre, Mulatu, Data, Tadesse, Tadele, Tafese, Abayo, Getahun, Wondimu, Asfaw, Butcher, Robert, Bakhtiari, Ana, Willis, Rebecca, Boyd, Sarah, Jimenez, Cristina, Negussu, Nebiyu, Tadesse, Fentahun, Kebede, Fikreab, Dejene, Michael, and Solomon, Anthony W.

Subjects
TRACHOMA, SANITATION, ADMINISTRATIVE & political divisions, COUNTRIES, CLUSTER sampling, DRINKING water
Abstract

Trachoma is endemic in Southern Nations, Nationalities and Peoples' (SNNP) and Sidama regions of Ethiopia. We aimed to measure the prevalence of trachomatous inflammation—follicular (TF) among children aged 1 – 9 years and the prevalence of trachomatous trichiasis (TT) unknown to the health system among people aged ≥15 years following interventions for trachoma in 52 woredas of SNNP and Sidama regions. From 2017 – 2019, 66 two-stage cluster sampling cross-sectional population-based surveys were carried out in 52 woredas (third-level administrative divisions) using a standardized World Health Organization-recommended survey methodology. This included one impact survey in 40 woredas, two consecutive impact surveys in 10 woredas and three consecutive impact surveys in two woredas. Water, sanitation and Hygiene (WASH) access was assessed using a modified version of the United Nations Children's Fund/WHO Joint Monitoring Programme questionnaire. By the end of this survey series, 15 (23%) of the woredas had met the active trachoma elimination threshold (TF prevalence <5%) and 12 (18%) had met the TT threshold (TT ≤ 0.2%). Regarding WASH coverage, 20% of households had access to an improved drinking water source within a 30-min journey and 3% had an improved latrine. There was strong evidence that TF was less common in 4 – 6-year-olds and 7 – 9-year-olds than 1 – 3-year-olds. Based on the findings, further antibiotic mass drug administration is required in 37 woredas and active TT case finding is needed in 40 woredas. In these surveys, access to WASH facilities was very low; WASH improvements are required. [ABSTRACT FROM AUTHOR]

Published
2023
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9. 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

11. Prevalence of Trachoma after Implementation of Trachoma Elimination Interventions in Oromia Regional State, Ethiopia: Results of Impact Surveys in 131 Evaluation Units Covering 139 Districts

Author

Miecha, Hirpa, primary, Dejene, Michael, additional, Adugna, Dereje, additional, Kebede, Ageru, additional, Yadeta, Damtew, additional, Alemayehu, Addisu, additional, Abateneh, Aemero, additional, Wondimu, Asfaw, additional, Dayessa, Mihiret, additional, Shafi, Muhammed, additional, Taye, Emawayish, additional, Balcha, Leta, additional, Gadisa, Solomon, additional, Negussu, Nebiyu, additional, Mengistu, Belete, additional, Willis, Rebecca, additional, Jimenez, Cristina, additional, Bakhtiari, Ana, additional, Boyd, Sarah, additional, Kebede, Biruk, additional, Tadesse, Fantahun, additional, Mamo, Ayele, additional, Bekele, Mengistu, additional, Sinke, Zelalem, additional, Solomon, Anthony W., additional, and Harding-Esch, Emma M., additional

Published
2022
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12. Prevalence of Trachoma in Pre-validation Surveillance Surveys in 11 Evaluation Units (Covering 12 Districts) in Oromia Regional State, Ethiopia: Results from 2018−2020

Author

Miecha, Hirpa, primary, Dejene, Michael, additional, Adugna, Dereje, additional, Kebede, Ageru, additional, Yadeta, Damtew, additional, Alemayehu, Addisu, additional, Abateneh, Aemero, additional, Dayessa, Mihiret, additional, Shafi, Muhammed, additional, Taye, Emawayish, additional, Balcha, Leta, additional, Negussu, Nebiyu, additional, Mengistu, Belete, additional, Willis, Rebecca, additional, Jimenez, Cristina, additional, Bakhtiari, Ana, additional, Boyd, Sarah, additional, Kebede, Biruk, additional, Tadesse, Fantahun, additional, Mamo, Ayele, additional, Bekele, Mengistu, additional, Sinke, Zelalem, additional, Solomon, Anthony W., additional, and Harding-Esch, Emma M., additional

Published
2022
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13. Prevalence of Trachoma in Benishangul Gumuz Region, Ethiopia, after Implementation of the SAFE Strategy: Results of Four Population-Based Surveys

Author

Mengistu, Belete, primary, Wirtu, Fikru, additional, Alemayehu, Addisu, additional, Alene, Shigute, additional, Asmare, Aemiro, additional, Backers, Sharone, additional, Bakhtiari, Ana, additional, Brady, Molly, additional, Butcher, Robert M. R., additional, Dayessa, Mihiret, additional, Frawley, Hannah, additional, Gebru, Genet, additional, Jimenez, Cristina, additional, Kebede, Fikreab, additional, Kejela, Asfaw, additional, McPherson, Scott, additional, Mihret, Addisalem, additional, Negussu, Nebiyu, additional, Ngondi, Jeremiah M., additional, Taddese, Fentahun, additional, Willis, Rebecca, additional, Wondimu, Asfaw, additional, Dejene, Michael, additional, Solomon, Anthony W., additional, and Harding-Esch, Emma M., additional

Published
2022
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14. Correction to: Model-based geostatistics enables more precise estimates of neglected tropical-disease prevalence in elimination settings: mapping trachoma prevalence in Ethiopia

Author

Amoah, Benjamin, primary, Fronterre, Claudio, additional, Johnson, Olatunji, additional, Dejene, Michael, additional, Seife, Fikre, additional, Negussu, Nebiyu, additional, Bakhtiari, Ana, additional, Harding-Esch, Emma M, additional, Giorgi, Emanuele, additional, Solomon, Anthony W, additional, and Diggle, Peter J, additional

Published
2022
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15. Correction to: Model-based geostatistics enables more precise estimates of neglected tropical-disease prevalence in elimination settings: mapping trachoma prevalence in Ethiopia

Author

Amoah, Benjamin, Fronterre, Claudio, Johnson, Olatunji, Dejene, Michael, Seife, Fikre, Negussu, Nebiyu, Bakhtiari, Ana, Harding-Esch, Emma M, Giorgi, Emanuele, Solomon, Anthony W, Diggle, Peter J, Amoah, Benjamin, Fronterre, Claudio, Johnson, Olatunji, Dejene, Michael, Seife, Fikre, Negussu, Nebiyu, Bakhtiari, Ana, Harding-Esch, Emma M, Giorgi, Emanuele, Solomon, Anthony W, and Diggle, Peter J

Abstract

In the originally published version of this manuscript, a funding statement and disclaimer were omitted in error. The following passages have been added to the Funding section: a note reading “AWS is a staff member of the World Health Organization.” a disclaimer reading, “The authors alone are responsible for the views expressed in this article and they do not necessarily represent the views, decisions or policies of the institutions with which they are affiliated. The boundaries and names shown and the designations used on the maps in this article do not imply the expression of any opinion whatsoever on the part of the authors, or the institutions with which they are affiliated, concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries.” These errors have been corrected online.

Published
2022

16. Model-based geostatistics enables more precise estimates of neglected tropical-disease prevalence in elimination settings:mapping trachoma prevalence in Ethiopia

Author

Amoah, Benjamin, Fronterre, Claudio, Johnson, Olatunji, Dejene, Michael, Seife, Fikre, Negussu, Nebiyu, Bakhtiari, Ana, Harding-Esch, Emma M., Giorgi, Emanuele, Solomon, Anthony W., Diggle, Peter, Amoah, Benjamin, Fronterre, Claudio, Johnson, Olatunji, Dejene, Michael, Seife, Fikre, Negussu, Nebiyu, Bakhtiari, Ana, Harding-Esch, Emma M., Giorgi, Emanuele, Solomon, Anthony W., and Diggle, Peter

Abstract

Background As the prevalences of neglected tropical diseases reduce to low levels in some countries, policymakers require precise disease estimates to decide whether the set public health targets have been met. At low prevalence levels, traditional statistical methods produce imprecise estimates. More modern geospatial statistical methods can deliver the required level of precision for accurate decision-making. Methods Using spatially referenced data from 3567 cluster locations in Ethiopia in the years 2017, 2018 and 2019, we developed a geostatistical model to estimate the prevalence of trachomatous trichiasis and to calculate the probability that the trachomatous trichiasis component of the elimination of trachoma as a public health problem has already been achieved for each of 482 evaluation units. We also compared the precision of traditional and geostatistical approaches by the ratios of the lengths of their 95% predictive intervals. Results The elimination threshold of trachomatous trichiasis (prevalence ≤ 0.2% in individuals aged ≥15 years) is met with a probability of 0.9 or more in 8 out of the 482 evaluation units assessed, and with a probability of ≤0.1 in 469 evaluation units. For the remaining five evaluation units, the probability of elimination is between 0.45 and 0.65. Prevalence estimates were, on average, 10 times more precise than estimates obtained using the traditional approach. Conclusions By accounting for and exploiting spatial correlation in the prevalence data, we achieved remarkably improved precision of prevalence estimates compared with the traditional approach. The geostatistical approach also delivers predictions for unsampled evaluation units that are geographically close to sampled evaluation units.

Published
2022

17. Prevalence of Trachoma from 66 Impact Surveys in 52 Woredas of Southern Nations, Nationalities and Peoples’ and Sidama Regions of Ethiopia, 2017–2019

Author

Seyum, Dawit, primary, Fetene, N, additional, Kifle, Tezera, additional, Negash, Habtamu, additional, Kabeto, Temesgen, additional, Gebre, Mulatu, additional, Data, Tadesse, additional, Tadele, Tafese, additional, Abayo, Getahun, additional, Wondimu, Asfaw, additional, Butcher, Robert, additional, Bakhtiari, Ana, additional, Willis, Rebecca, additional, Boyd, Sarah, additional, Jimenez, Cristina, additional, Negussu, Nebiyu, additional, Tadesse, Fentahun, additional, Kebede, Fikreab, additional, Dejene, Michael, additional, Solomon, Anthony W., additional, Harding-Esch, Emma M., additional, and Sisay, Alemayehu, additional

Published
2022
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18. Model-based geostatistics enables more precise estimates of neglected tropical-disease prevalence in elimination settings: mapping trachoma prevalence in Ethiopia

Author

Amoah, Benjamin, primary, Fronterre, Claudio, additional, Johnson, Olatunji, additional, Dejene, Michael, additional, Seife, Fikre, additional, Negussu, Nebiyu, additional, Bakhtiari, Ana, additional, Harding-Esch, Emma M, additional, Giorgi, Emanuele, additional, Solomon, Anthony W, additional, and Diggle, Peter J, additional

Published
2021
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21. Additional file 1 of Soil-transmitted helminths and schistosome infections in Ethiopia: a systematic review of progress in their control over the past 20 years

Author

Maddren, Rosie, Phillips, Anna, Ower, Alison, Landeryou, Toby, Mengistu, Birhan, Anjulo, Ufaysa, Firdawek, Ewnetu, Negussu, Nebiyu, and Anderson, Roy

Subjects
parasitic diseases
Abstract

Additional file 1: Figure S1. Intensity and prevalence age profiles for soil-transmitted helminths (STH).

Published
2021
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24. Comparison of Face Washing and Face Wiping Methods for Trachoma Control: A Pilot Study

Author

Czerniewska, Alexandra, Versteeg, Aalbertus, Shafi, Oumer, Dumessa, Gebeyehu, Aga, Muluadam Abraham, Last, Anna, MacLeod, David, Sarah, Virginia, Dodson, Sarity, Negussu, Nebiyu, Sori, Birhanu Kenate, Kirumba, Michael, Biran, Adam, Cairncross, Sandy, Burton, Matthew J, and Greenland, Katie

Subjects
eye diseases
Abstract

Eye-to-eye transmission of Chlamydia trachomatis, the causative agent of trachoma, may be plausibly interrupted if faces are kept free of ocular and nasal discharge. Between April and June 2018, 83 children aged 1-9 years with active trachoma were recruited from 62 households and allocated to a face cleaning protocol: face washing with water, face washing with water and soap, or face wiping. Faces were examined for the presence of ocular and nasal discharge, and swabs were taken from faces and hands to test for C. trachomatis at baseline, immediately post protocol, and after 1, 2, and 4 hours (washing protocols). Washing with soap was more effective at removing ocular discharge than either washing with water (89% and 27% of discharge removed, respectively, P = 0.003) or wiping with a hand (42%, P = 0.013). The reduction in prevalence of ocular discharge was sustained for at least four hours. The prevalence of C. trachomatis on face swabs was reduced by all washing protocols. The importance of soap should not be overlooked during facial cleanliness promotion.

Published
2020

26. Model-based geostatistics enables more precise estimates of neglected tropical-disease prevalence in elimination settings: mapping trachoma prevalence in Ethiopia.

Author

Amoah, Benjamin, Fronterre, Claudio, Johnson, Olatunji, Dejene, Michael, Seife, Fikre, Negussu, Nebiyu, Bakhtiari, Ana, Harding-Esch, Emma M, Giorgi, Emanuele, Solomon, Anthony W, and Diggle, Peter J

Subjects
TRACHOMA prevention, PUBLIC health, DISEASE prevalence, RESEARCH funding, TRACHOMA, STYE
Abstract

Background: As the prevalences of neglected tropical diseases reduce to low levels in some countries, policymakers require precise disease estimates to decide whether the set public health targets have been met. At low prevalence levels, traditional statistical methods produce imprecise estimates. More modern geospatial statistical methods can deliver the required level of precision for accurate decision-making.Methods: Using spatially referenced data from 3567 cluster locations in Ethiopia in the years 2017, 2018 and 2019, we developed a geostatistical model to estimate the prevalence of trachomatous trichiasis and to calculate the probability that the trachomatous trichiasis component of the elimination of trachoma as a public health problem has already been achieved for each of 482 evaluation units. We also compared the precision of traditional and geostatistical approaches by the ratios of the lengths of their 95% predictive intervals.Results: The elimination threshold of trachomatous trichiasis (prevalence ≤ 0.2% in individuals aged ≥15 years) is met with a probability of 0.9 or more in 8 out of the 482 evaluation units assessed, and with a probability of ≤0.1 in 469 evaluation units. For the remaining five evaluation units, the probability of elimination is between 0.45 and 0.65. Prevalence estimates were, on average, 10 times more precise than estimates obtained using the traditional approach.Conclusions: By accounting for and exploiting spatial correlation in the prevalence data, we achieved remarkably improved precision of prevalence estimates compared with the traditional approach. The geostatistical approach also delivers predictions for unsampled evaluation units that are geographically close to sampled evaluation units. [ABSTRACT FROM AUTHOR]

Published
2022
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27. EnDPoINT: protocol for an implementation research study to integrate a holistic package of physical health, mental health and psychosocial care for podoconiosis, lymphatic filariasis and leprosy into routine health services in Ethiopia

Author

Semrau, Maya, primary, Ali, Oumer, additional, Deribe, Kebede, additional, Mengiste, Asrat, additional, Tesfaye, Abraham, additional, Kinfe, Mersha, additional, Bremner, Stephen A, additional, Hounsome, Natalia, additional, Kelly-Hope, Louise A, additional, MacGregor, Hayley, additional, Taddese, Henock B, additional, Banteyerga, Hailom, additional, HaileMariam, Damen, additional, Negussu, Nebiyu, additional, Fekadu, Abebaw, additional, and Davey, Gail, additional

Published
2020
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29. Preventive chemotherapy coverage against Soil-transmitted helminthiases among school age children in vertical versus integrated treatment approaches: Implications from coverage validation survey in Ethiopia

Author

Asfaw, Mekuria, primary, Zerdo, Zerihun, additional, Churko, Chuchu, additional, Seife, Fikre, additional, Yihune, Manaye, additional, Chisha, Yilma, additional, Teshome, Abinet, additional, Getachew, Birhanu, additional, and Negussu, Nebiyu, additional

Published
2020
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30. Detecting extra-ocular Chlamydia trachomatis in a trachoma-endemic community in Ethiopia: Identifying potential routes of transmission

Author

Last, Anna, primary, Versteeg, Bart, additional, Shafi Abdurahman, Oumer, additional, Robinson, Ailie, additional, Dumessa, Gebeyehu, additional, Abraham Aga, Muluadam, additional, Shumi Bejiga, Gemechu, additional, Negussu, Nebiyu, additional, Greenland, Katie, additional, Czerniewska, Alexandra, additional, Thomson, Nicholas, additional, Cairncross, Sandy, additional, Sarah, Virginia, additional, Macleod, David, additional, Solomon, Anthony W., additional, Logan, James, additional, and Burton, Matthew J., additional

Published
2020
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33. The Galabat-Metema cross-border onchocerciasis focus: The first coordinated interruption of onchocerciasis transmission in Africa

Author

Katabarwa, Moses N., primary, Zarroug, Isam M. A., additional, Negussu, Nebiyu, additional, Aziz, Nabil M., additional, Tadesse, Zerihun, additional, Elmubark, Wigdan A., additional, Shumo, Zainab, additional, Meribo, Kadu, additional, Kamal, Hashim, additional, Mohammed, Aderajew, additional, Bitew, Yewondwossen, additional, Seid, Tewodros, additional, Bekele, Firdaweke, additional, Yilak, Abebual, additional, Endeshaw, Tekola, additional, Hassen, Mohammed, additional, Tillahun, Abate, additional, Samuel, Fikresilasie, additional, Birhanu, Henok, additional, Asmare, Tadesse, additional, Boakye, Daniel, additional, Feleke, Sindew M., additional, Unnasch, Thomas, additional, Post, Rory, additional, Higazi, Tarig, additional, Griswold, Emily, additional, Mackenzie, Charles, additional, and Richards, Frank, additional

Published
2020
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35. Estimating the Intracluster Correlation Coefficient for the Clinical Sign “Trachomatous Inflammation—Follicular” in Population-Based Trachoma Prevalence Surveys: Results From a Meta-Regression Analysis of 261 Standardized Preintervention Surveys Carried Out in Ethiopia, Mozambique, and Nigeria

Author

Macleod, Colin K, primary, Bailey, Robin L, primary, Dejene, Michael, primary, Shafi, Oumer, primary, Kebede, Biruck, primary, Negussu, Nebiyu, primary, Mpyet, Caleb, primary, Olobio, Nicholas, primary, Alada, Joel, primary, Abdala, Mariamo, primary, Willis, Rebecca, primary, Hayes, Richard, primary, and Solomon, Anthony W, primary

Published
2019
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36. The public health control of scabies: priorities for research and action

Author

Engelman, Daniel, primary, Cantey, Paul T, additional, Marks, Michael, additional, Solomon, Anthony W, additional, Chang, Aileen Y, additional, Chosidow, Olivier, additional, Enbiale, Wendemagegn, additional, Engels, Dirk, additional, Hay, Roderick J, additional, Hendrickx, David, additional, Hotez, Peter J, additional, Kaldor, John M, additional, Kama, Mike, additional, Mackenzie, Charles D, additional, McCarthy, James S, additional, Martin, Diana L, additional, Mengistu, Birhan, additional, Maurer, Toby, additional, Negussu, Nebiyu, additional, Romani, Lucia, additional, Sokana, Oliver, additional, Whitfeld, Margot J, additional, Fuller, L Claire, additional, and Steer, Andrew C, additional

Published
2019
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37. Gender equity in mass drug administration for neglected tropical diseases: data from 16 countries

Author

Cohn, Daniel A, primary, Kelly, Maureen P, additional, Bhandari, Kalpana, additional, Zoerhoff, Kathryn L, additional, Batcho, Wilfrid E, additional, Drabo, François, additional, Negussu, Nebiyu, additional, Marfo, Benjamin, additional, Goepogui, André, additional, Lemoine, Jean-Frantz, additional, Ganefa, Sitti, additional, Massangaie, Marilia, additional, Rimal, Pradip, additional, Gnandou, Issa, additional, Anagbogu, Ifeoma N, additional, Ndiaye, Mamadou, additional, Bah, Yakuba Madina, additional, Mwingira, Upendo J, additional, Awoussi, Marcel S, additional, Tukahebwa, Edridah M, additional, Stelmach, Rachel D, additional, Mingkwan, Pia C, additional, Pou, Bolivar, additional, Koroma, Joseph B, additional, Rotondo, Lisa A, additional, Kraemer, John D, additional, and Baker, Margaret C, additional

Published
2019
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38. Integrated delivery of school health interventions through the school platform: Investing for the future

Author

Appleby, Laura J., primary, Tadesse, Gemechu, additional, Wuletawu, Yonas, additional, Dejene, Nigussie G., additional, Grimes, Jack E. T., additional, French, Michael D., additional, Teklu, Askale, additional, Moreda, Berhanu, additional, Negussu, Nebiyu, additional, Kebede, Biruck, additional, Yard, Elodie, additional, Gardiner, Iain, additional, and Drake, Lesley J., additional

Published
2019
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39. Optimising age adjustment of trichiasis prevalence estimates using data from 162 standardised surveys from seven regions of Ethiopia

Author

Macleod, Colin K., primary, Porco, Travis C., additional, Dejene, Michael, additional, Shafi, Oumer, additional, Kebede, Biruck, additional, Negussu, Nebiyu, additional, Bero, Berhanu, additional, Taju, Sadik, additional, Adamu, Yilikal, additional, Negash, Kassahun, additional, Haileselassie, Tesfaye, additional, Riang, John, additional, Badei, Ahmed, additional, Bakhtiari, Ana, additional, Willis, Rebecca, additional, Bailey, Robin L., additional, and Solomon, Anthony W., additional

Published
2018
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40. Estimating the Intracluster Correlation Coefficient for the Clinical Sign "Trachomatous Inflammation—Follicular" in Population-Based Trachoma Prevalence Surveys: Results From a Meta-Regression Analysis of 261 Standardized Preintervention Surveys Carried Out in Ethiopia, Mozambique, and Nigeria

Author

Macleod, Colin K, Bailey, Robin L, Dejene, Michael, Shafi, Oumer, Kebede, Biruck, Negussu, Nebiyu, Mpyet, Caleb, Olobio, Nicholas, Alada, Joel, Abdala, Mariamo, Willis, Rebecca, Hayes, Richard, and Solomon, Anthony W

Subjects
CLUSTER analysis (Statistics), INFLAMMATION, META-analysis, PUBLIC health surveillance, SURVEYS, TRACHOMA, DISEASE prevalence, FOLLICULITIS, STATISTICAL models
Abstract

Sample sizes in cluster surveys must be greater than those in surveys using simple random sampling in order to obtain similarly precise prevalence estimates, because results from subjects examined in the same cluster cannot be assumed to be independent. Therefore, a crucial aspect of cluster sampling is estimation of the intracluster correlation coefficient (ρ): the degree of relatedness of outcomes in a given cluster, defined as the proportion of total variance accounted for by between-cluster variation. In infectious disease epidemiology, this coefficient is related to transmission patterns and the natural history of infection; its value also depends on particulars of survey design. Estimation of ρ is often difficult due to the lack of comparable survey data with which to calculate summary estimates. Here we use a parametric bootstrap model to estimate ρ for the ocular clinical sign "trachomatous inflammation—follicular" (TF) among children aged 1–9 years within population-based trachoma prevalence surveys. We present results from a meta-regression analysis of data from 261 such surveys completed using standardized methods in Ethiopia, Mozambique, and Nigeria in 2012–2015. Consistent with the underlying theory, we found that ρ increased with increasing overall TF prevalence and smaller numbers of children examined per cluster. Estimates of ρ for TF were independently higher in Ethiopia than in the other countries. [ABSTRACT FROM AUTHOR]

Published
2020
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42. Incidence, prevalence and mortality rates of malaria in Ethiopia from 1990 to 2015: analysis of the global burden of diseases 2015

Author

Deribew, Amare, primary, Dejene, Tariku, additional, Kebede, Biruck, additional, Tessema, Gizachew Assefa, additional, Melaku, Yohannes Adama, additional, Misganaw, Awoke, additional, Gebre, Teshome, additional, Hailu, Asrat, additional, Biadgilign, Sibhatu, additional, Amberbir, Alemayehu, additional, Yirsaw, Biruck Desalegn, additional, Abajobir, Amanuel Alemu, additional, Shafi, Oumer, additional, Abera, Semaw F., additional, Negussu, Nebiyu, additional, Mengistu, Belete, additional, Amare, Azmeraw T., additional, Mulugeta, Abate, additional, Mengistu, Birhan, additional, Tadesse, Zerihun, additional, Sileshi, Mesfin, additional, Cromwell, Elizabeth, additional, Glenn, Scott D., additional, Deribe, Kebede, additional, and Stanaway, Jeffrey D., additional

Published
2017
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43. Optimising age adjustment of trichiasis prevalence estimates using data from 162 standardised surveys from seven regions of Ethiopia.

Author

Macleod, Colin K., Bailey, Robin L., Solomon, Anthony W., Riang, John, Badei, Ahmed, Bakhtiari, Ana, Willis, Rebecca, Porco, Travis C., Dejene, Michael, Shafi, Oumer, Kebede, Biruck, Negussu, Nebiyu, Bero, Berhanu, Taju, Sadik, Adamu, Yilikal, Negash, Kassahun, and Haileselassie, Tesfaye

Subjects
TRACHOMA, CONJUNCTIVA diseases, CHLAMYDIA infections, POPULATION, ECONOMICS
Abstract

Purpose: The prevalence of trichiasis is higher in females and increases markedly with age. Surveys carried out in the daytime, particularly in developing countries, are prone to find older individuals and females at home at the time of the survey. Population-level trichiasis estimates should adjust sample proportions to reflect the demographic breakdown of the population, although the most accurate method of doing this is unclear. Methods: Having obtained data from 162 surveys carried out in Ethiopia as part of the Global Trachoma Mapping Project from 2012 to 2015, we used internal validation with both Brier and Logarithmic forecast scoring to test stratification models to identify those models with the highest predictive accuracy. Selection of partitions was undertaken by both simple random sampling (SRS) and cluster sampling (CS) over 8192 selections. Results: A total of 4529 (1.9%) cases of trichiasis were identified from 241,139 individuals aged ≥15 years from a total of 4210 kebeles and 122,090 households visited. Overall, the binning method using 5-year bands from age 15 to 69 years, with coarser binning in 20-year age-bands above this age, provided the best predictive accuracy, in both SRS and CS methodologies and for both the Brier and Logarithmic scoring rules. Conclusion: The greatest predictive accuracy for trichiasis estimates was found by adjusting for sex and in 5-year age-bands from the age of 15 to 69 years and in 20-year age-bands in those aged 70 years and greater. Trichiasis surveys attempting to make population-level inferences should use this method to optimise surgery backlog estimates. [ABSTRACT FROM AUTHOR]

Published
2019
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47. Safe mass drug administration and trachoma elimination.

Author

Addiss, David, Sarah, Virginia, Negussu, Nebiyu, and Emerson, Paul

Subjects
TRACHOMA prevention, FATIGUE risk factors, DRUG side effects, DRUG administration, MEDICAL errors, MEDICAL protocols, ORAL drug administration, PATIENT safety, PEDIATRICS, PROBLEM solving, PUBLIC health, SUSPENSIONS (Chemistry), WORLD health, AZITHROMYCIN
Published
2019

48. Ethiopia schistosomiasis and soil-transmitted helminthes control programme: Progress and prospects

Author

Negussu, Nebiyu, Mengistu, Birhan, Kebede, Biruck, Deribe, Kebede, Ejigu, Ephrem, Tadesse, Gemechu, Mekete, Kalkidan, and Sileshi, Mesfin

Abstract

Schistosomiasis and soil-transmitted helminthes are among seventeen WHO prioritized neglected tropical diseases that infect humans. These parasitic infections can be treated using single-dose and safe drugs. Ethiopia successfully mapped the distribution of these infections nationwide. According to the mapping there are an estimated 37.3 million people living in schistosomiasis endemic areas, and 79 million in schistosomiasis and soil-transmitted helminthes endemic areas. The Federal Ministry of Health successfully scaled up Schistosomiasis and schistosomiasis and soil-transmitted helminthes intervention in endemic areas and treated over 19 million individuals in 2015. The Ministry of Health has made a huge effort to establish neglected tropical diseases, including schistosomiasis and soil-transmitted helminthes program in the health system which helped to map majority of the woredas and initiate nationwide intervention. The National control programme is designed to achieve elimination for those diseases as a major public health problem by 2020 and aim to attain transmission break by 2025. The programme focuses on reaching those school-aged children who are not attending school, integration between neglected tropical diseases programme, and further collaboration with the WASH actors.

49. Towards the trachoma elimination target in the Southern region of Ethiopia: How well is the SAFE strategy being implemented?

Author

Asfaw, Mekuria Asnakew, Zolfo, Maria, Negussu, Nebiyu, Tadesse, Fantahun, Tadele, Tafese, Sisay, Alemayehu, Seyum, Dawit, Gezmu, Tigist, Senkoro, Mbazi, Owiti, Philip, and Adriaensen, Wim

Subjects
*TRACHOMA, *WELL-being, *TROPICAL medicine, *OPERATIONS research, *DATA analysis
Abstract

Introduction: Trachoma is one of the 20 neglected tropical diseases and a serious public health problem in Ethiopia. To reach the WHO elimination target by 2020, SAFE (Surgery, Antibiotics, Facial cleanliness, Environmental improvement) strategy has been implemented in the Southern Nations, Nationalities, and Peoples' Region (SNNPRs), Ethiopia. Scarce evidence exists regarding recent progress in achieving elimination of active trachoma (< 5%) and how well the SAFE strategy implemented. Methodology: A retrospective analysis of programmatic data in the period 2013-2018 was used. All trachoma endemic districts in SNNPR were included. Data collected from the Federal Ministry of Health on trachoma prevalence and SAFE strategy were analyzed. Results: Out of 134 endemic districts, only 35 had their planned impact survey, of which only 11 districts achieved the elimination target. Six districts reverted backwards from eliminated status to low (1) or moderate (5) level. The median prevalence of active trachoma in these 35 districts was 10% in 2017/18. In 2017, the mean antibiotic treatment coverage was 90%, but only 56% and 68% of districts implemented and reported on "F" and "E" components, respectively. In the high prevalence districts, only 10% delivered their planned five rounds of Zithromax® mass distribution. Conclusions: These data showed a lack in planned impact surveys with only a limited number of districts reached the WHO elimination threshold by 2018. Lack of attention on high prevalent districts, and recent reversal of trachoma eliminated districts to moderate or low prevalence levels argue for urgent and prioritized implementation of the SAFE strategy. [ABSTRACT FROM AUTHOR]

Published
2020
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50. Prevalence of Trachoma After Three Rounds of Antibiotic Mass Drug Administration in 13 Woredas of Gambella Region, Ethiopia.

Author

Alemayehu, Addisu, Mekonen, Ademe, Mengistu, Belete, Mihret, Addisalem, Asmare, Aemiro, Bakhtiari, Ana, Mengistu, Bekele, Jimenez, Cristina, Kebede, Demis, Bol, Doul, Tadesse, Fentahun, Kebede, Fikreab, Gebru, Genet, Frawley, Hannah, Ngondi, Jeremiah, Jemal, Mohammed, Brady, Molly, Negussu, Nebiyu, Butcher, Robert, and McPherson, Scott

Abstract

Background Methods Results Conclusion Following baseline surveys in 2013 and 2014, trachoma elimination interventions, including three rounds of azithromycin mass drug administration (MDA), were implemented in 13 woredas (administrative districts) of Gambella Regional State, Ethiopia. We conducted impact surveys to determine if elimination thresholds have been met or if additional interventions are required.Cross-sectional population-based surveys were conducted in 13 woredas of Gambella Regional State, combined into five evaluation units (EUs), 6─12 months after their last MDA round. A two-stage systematic (first stage) and random (second stage) sampling technique was used. WHO-recommended protocols were implemented with the support of Tropical Data. Household water, sanitation and hygiene (WASH) access was assessed.The age-adjusted prevalence of trachomatous inflammation – follicular (TF) in 1–9-year-olds in the five EUs ranged from 0.3–19.2%, representing a general decline in TF prevalence compared to baseline estimates. The age- and gender-adjusted prevalence of trachomatous trichiasis (TT) unknown to the health system in those aged ≥ 15 years ranged from 0.47–3.08%. Of households surveyed, 44% had access to an improved drinking water source within a 30-minute return journey of the house, but only 3% had access to an improved latrine.In two EUs, no further MDA should be delivered, and a surveillance survey should be conducted after two years without MDA. In one EU, one further round of MDA should be conducted followed by another impact survey. In two EUs, three further MDA rounds are required. Surgery, facial cleanliness and environmental improvement interventions are needed throughout the region. [ABSTRACT FROM AUTHOR]

Published
2023
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