276 results on '"Bauni, Evasius"'
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2. A micro-epidemiological analysis of febrile malaria in Coastal Kenya showing hotspots within hotspots.
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Bejon, Philip, Williams, Thomas N, Nyundo, Christopher, Hay, Simon I, Benz, David, Gething, Peter W, Otiende, Mark, Peshu, Judy, Bashraheil, Mahfudh, Greenhouse, Bryan, Bousema, Teun, Bauni, Evasius, Marsh, Kevin, Smith, David L, and Borrmann, Steffen
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Humans ,Malaria ,Falciparum ,Fever ,Risk Factors ,Child ,Kenya ,falciparum ,hotspot ,malaria control ,spatial epidemiology ,Malaria ,Falciparum ,Biochemistry and Cell Biology - Abstract
Malaria transmission is spatially heterogeneous. This reduces the efficacy of control strategies, but focusing control strategies on clusters or 'hotspots' of transmission may be highly effective. Among 1500 homesteads in coastal Kenya we calculated (a) the fraction of febrile children with positive malaria smears per homestead, and (b) the mean age of children with malaria per homestead. These two measures were inversely correlated, indicating that children in homesteads at higher transmission acquire immunity more rapidly. This inverse correlation increased gradually with increasing spatial scale of analysis, and hotspots of febrile malaria were identified at every scale. We found hotspots within hotspots, down to the level of an individual homestead. Febrile malaria hotspots were temporally unstable, but 4 km radius hotspots could be targeted for 1 month following 1 month periods of surveillance.DOI: http://dx.doi.org/10.7554/eLife.02130.001.
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- 2014
3. Human candidate gene polymorphisms and risk of severe malaria in children in Kilifi, Kenya: a case-control association study
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Abathina, Amadou, Abubakar, Ismaela, Achidi, Eric, Agbenyega, Tsiri, Aiyegbo, Mohammed, Akoto, Alex, Allen, Angela, Allen, Stephen, Amenga-Etego, Lucas, Amodu, Folakemi, Amodu, Olukemi, Anchang-Kimbi, Judith, Ansah, Nana, Ansah, Patrick, Ansong, Daniel, Antwi, Sampson, Anyorigiya, Thomas, Apinjoh, Tobias, Asafo-Agyei, Emmanuel, Asoala, Victor, Atuguba, Frank, Auburn, Sarah, Bah, Abdou, Bamba, Kariatou, Bancone, Germana, Band, Gavin, Barnwell, David, Barry, Abdoulaye, Bauni, Evasius, Besingi, Richard, Bojang, Kalifa, Bougouma, Edith, Bull, Susan, Busby, George, Camara, Abdoulie, Camara, Landing, Campino, Susana, Carter, Richard, Carucci, Dan, Casals-Pascual, Climent, Ceesay, Ndey, Ceesay, Pa, Chau, Tran, Chuong, Ly, Clark, Taane, Clarke, Geraldine, Cole-Ceesay, Ramou, Conway, David, Cook, Katharine, Cook, Olivia, Cornelius, Victoria, Corran, Patrick, Correa, Simon, Cox, Sharon, Craik, Rachel, Danso, Bakary, Davis, Timothy, Day, Nicholas, Deloukas, Panos, Dembele, Awa, deVries, Jantina, Dewasurendra, Rajika, Diakite, Mahamadou, Diarra, Elizabeth, Dibba, Yaya, Diss, Andrea, Djimdé, Abdoulaye, Dolo, Amagana, Doumbo, Ogobara, Doyle, Alan, Drakeley, Chris, Drury, Eleanor, Duffy, Patrick, Dunstan, Sarah, Ebonyi, Augustine, Elhassan, Ahmed, Elhassan, Ibrahim, Elzein, Abier, Enimil, Anthony, Esangbedo, Pamela, Evans, Jennifer, Evans, Julie, Farrar, Jeremy, Fernando, Deepika, Fitzpatrick, Kathryn, Fullah, Janet, Garcia, Jacob, Ghansah, Anita, Gottleib, Michael, Green, Angie, Hart, Lee, Hennsman, Meike, Hien, Tran, Hieu, Nguyen, Hilton, Eliza, Hodgson, Abraham, Horstmann, Rolf, Hubbart, Christina, Hughes, Catherine, Hussein, Ayman, Hutton, Robert, Ibrahim, Muntaser, Ishengoma, Deus, Jaiteh, Jula, Jallow, Mariatou, Jallow, Muminatou, Jammeh, Kebba, Jasseh, Momodou, Jeffreys, Anna, Jobarteh, Amie, Johnson, Kimberly, Joseph, Sarah, Jyothi, Dushyanth, Kachala, David, Kamuya, Dorcas, Kanyi, Haddy, Karunajeewa, Harin, Karunaweera, Nadira, Keita, Momodou, Kerasidou, Angeliki, Khan, Aja, Kivinen, Katja, Kokwaro, Gilbert, Konate, Amadou, Konate, Salimata, Koram, Kwadwo, Kwiatkowski, Dominic, Laman, Moses, Le, Si, Leffler, Ellen, Lemnge, Martha, Lin, Enmoore, Ly, Alioune, Macharia, Alexander, MacInnis, Bronwyn, Mai, Nguyen, Makani, Julie, Malangone, Cinzia, Mangano, Valentina, Manjurano, Alphaxard, Manneh, Lamin, Manning, Laurens, Manske, Magnus, Marsh, Kevin, Marsh, Vicki, Maslen, Gareth, Maxwell, Caroline, Mbunwe, Eric, McCreight, Marilyn, Mead, Daniel, Mendy, Alieu, Mendy, Anthony, Mensah, Nathan, Michon, Pascal, Miles, Alistair, Miotto, Olivo, Modiano, David, Mohamed, Hiba, Molloy, Sile, Molyneux, Malcolm, Molyneux, Sassy, Moore, Mike, Moyes, Catherine, Mtei, Frank, Mtove, George, Mueller, Ivo, Mugri, Regina, Munthali, Annie, Mutabingwa, Theonest, Nadjm, Behzad, Ndi, Andre, Ndila, Carolyne, Newton, Charles, Niangaly, Amadou, Njie, Haddy, Njie, Jalimory, Njie, Madi, Njie, Malick, Njie, Sophie, Njiragoma, Labes, Nkrumah, Francis, Ntunthama, Neema, Nyika, Aceme, Nyirongo, Vysaul, O'Brien, John, Obu, Herbert, Oduro, Abraham, Ofori, Alex, Olaniyan, Subulade, Olaosebikan, Rasaq, Oluoch, Tom, Omotade, Olayemi, Oni, Olajumoke, Onykwelu, Emmanuel, Opi, Daniel, Orimadegun, Adebola, O'Riordan, Sean, Ouedraogo, Issa, Oyola, Samuel, Parker, Michael, Pearson, Richard, Pensulo, Paul, Peshu, Norbert, Phiri, Ajib, Phu, Nguyen, Pinder, Margaret, Pirinen, Matti, Plowe, Chris, Potter, Claire, Poudiougou, Belco, Puijalon, Odile, Quyen, Nguyen, Ragoussis, Ioannis, Ragoussis, Jiannis, Rasheed, Oba, Reeder, John, Reyburn, Hugh, Riley, Eleanor, Risley, Paul, Rockett, Kirk, Rodford, Joanne, Rogers, Jane, Rogers, William, Rowlands, Kate, Ruano-Rubio, Valentín, Sabally-Ceesay, Kumba, Sadiq, Abubacar, Saidy-Khan, Momodou, Saine, Horeja, Sakuntabhai, Anavaj, Sall, Abdourahmane, Sambian, David, Sambou, Idrissa, SanJoaquin, Miguel, Sepúlveda, Nuno, Shah, Shivang, Shelton, Jennifer, Siba, Peter, Silva, Nilupa, Simmons, Cameron, Simpore, Jaques, Singhasivanon, Pratap, Sinh, Dinh, Sirima, Sodiomon, Sirugo, Giorgio, Sisay-Joof, Fatoumatta, Sissoko, Sibiry, Small, Kerrin, Somaskantharajah, Elilan, Spencer, Chris, Stalker, Jim, Stevens, Marryat, Suriyaphol, Prapat, Sylverken, Justice, Taal, Bintou, Tall, Adama, Taylor, Terrie, Teo, Yik, Thai, Cao, Thera, Mahamadou, Titanji, Vincent, Toure, Ousmane, Troye-Blomberg, Marita, Usen, Stanley, Uyoga, Sophie, Vanderwal, Aaron, Wangai, Hannah, Watson, Renee, Williams, Thomas, Wilson, Michael, Wrigley, Rebecca, Yafi, Clarisse, Yamoah, Lawrence, Ndila, Carolyne M, Macharia, Alexander W, Nyutu, Gideon, Ojal, John, Shebe, Mohammed, Awuondo, Kennedy O, Mturi, Neema, Tsofa, Benjamin, Clark, Taane G, Kariuki, Silvia, Mackinnon, Margaret, Maitland, Kathryn, Kwiatkowski, Dominic P, Rockett, Kirk A, and Williams, Thomas N
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- 2018
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4. Mortality after inpatient treatment for diarrhea in children: a cohort study
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Talbert, Alison, Ngari, Moses, Bauni, Evasius, Mwangome, Martha, Mturi, Neema, Otiende, Mark, Maitland, Kathryn, Walson, Judd, and Berkley, James A.
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- 2019
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5. Family Planning and Sexual Behavior in the Era of HIV/AIDS: The Case of Nakuru District, Kenya
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Bauni, Evasius K. and Jarabi, Ben Obonyo
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- 2000
6. Prospective Observational Study of Incidence and Preventable Burden of Childhood Tuberculosis, Kenya
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Brent, Andrew J., Nyundo, Christopher, Langat, Joyce, Mulunda, Caroline, Wambua, Joshua, Bauni, Evasius, Sande, Joyce, Park, Kate, Williams, Thomas N., Newton, Charles R.J., Levin, Michael, and Scott, J. Anthony G.
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Medical research ,Tuberculosis -- Risk factors -- Research ,Health ,World Health Organization - Abstract
Sibstantial progress has been made in the fight against uberculosis (TB); however, new approaches are needed to achieve the current target set by the World Health Organization (WHO) to reduce [...]
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- 2018
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7. Development and validation of a diagnostic aid for convulsive epilepsy in sub-Saharan Africa: a retrospective case-control study
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Jones, Gabriel Davis, primary, Kariuki, Symon M, additional, Ngugi, Anthony K, additional, Mwesige, Angelina Kakooza, additional, Masanja, Honorati, additional, Owusu-Agyei, Seth, additional, Wagner, Ryan, additional, Cross, J Helen, additional, Sander, Josemir W, additional, Newton, Charles R, additional, Sen, Arjune, additional, Abban, Hanna, additional, Adjei, Patrick, additional, Ae-Ngibise, Ken, additional, Agbokey, Francis, additional, Aissaoui, Lisa, additional, Akpalu, Albert, additional, Akpalu, Bright, additional, Asiamah, Sabina, additional, Asiki, Gershim, additional, Atieno, Mercy, additional, Bauni, Evasius, additional, Bhwana, Dan, additional, Bitta, Mary, additional, Bottomley, Christian, additional, Chabi, Martin, additional, Chengo, Eddie, additional, Chowdhary, Neerja, additional, Connor, Myles, additional, Cross, Helen, additional, Collinson, Mark, additional, Darkwa, Emmanuel, additional, Denison, Timothy, additional, Doku, Victor, additional, Dua, Tarun, additional, Egesa, Isaac, additional, Godi, Tony, additional, Gómez-Olivé, F. Xavier, additional, Grassi, Simone, additional, Iddi, Samuel, additional, Junior, Daniel Nana Yaw Abankwah, additional, Kahn, Kathleen, additional, Kakooza, Angelina, additional, Kariuki, Symon, additional, Kamuyu, Gathoni, additional, Khalayi, Clarah, additional, Kimambo, Henrika, additional, Kleinschmidt, Immo, additional, Kwasa, Thomas, additional, Mahone, Sloan, additional, Manolova, Gergana, additional, Mathew, Alexander, additional, Matuja, William, additional, McDaid, David, additional, Mmbando, Bruno, additional, Mtai Mwanga, Daniel, additional, Muli, Dorcas, additional, Mung'ala Odera, Victor, additional, Murunga Wekesah, Frederick, additional, Mushi, Vivian, additional, Ngugi, Anthony, additional, Odermatt, Peter, additional, Odhiambo, Rachael, additional, O Mageto, James, additional, Otieno, Peter, additional, Pariyo, George, additional, Peterson, Stefan, additional, Sander, Josemir, additional, Sottie, Cynthia, additional, Sylvester, Isolide, additional, Tollman, Stephen, additional, Thoya, Yvonne, additional, Twine, Rhian, additional, Vallentin, Sonia, additional, Walker, Richard, additional, and Waruingi, Stella, additional
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- 2023
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8. Mortality in rural coastal Kenya measured using the Kilifi Health and Demographic Surveillance System: a 16-year descriptive analysis
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Otiende, Mark, primary, Bauni, Evasius, additional, Nyaguara, Amek, additional, Amadi, David, additional, Nyundo, Christopher, additional, Tsory, Emmanuel, additional, Walumbe, David, additional, Kinuthia, Michael, additional, Kihuha, Norbert, additional, Kahindi, Michael, additional, Nyutu, Gideon, additional, Moisi, Jennifer, additional, Deribew, Amare, additional, Agweyu, Ambrose, additional, Marsh, Kevin, additional, Tsofa, Benjamin, additional, Bejon, Philip, additional, Bottomley, Christian, additional, Williams, Thomas N., additional, and Scott, J. Anthony G., additional
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- 2023
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9. Burden of disease in adults admitted to hospital in a rural region of coastal Kenya: an analysis of data from linked clinical and demographic surveillance systems
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Etyang, Anthony O, Munge, Kenneth, Bunyasi, Erick W, Matata, Lena, Ndila, Carolyne, Kapesa, Sailoki, Owiti, Maureen, Khandwalla, Iqbal, Brent, Andrew J, Tsofa, Benjamin, Kabibu, Pamela, Morpeth, Susan, Bauni, Evasius, Otiende, Mark, Ojal, John, Ayieko, Philip, Knoll, Maria D, Smeeth, Liam, Williams, Thomas N, Griffiths, Ulla K, and Scott, J Anthony G
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- 2014
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10. Relation between falciparum malaria and bacteraemia in Kenyan children: a population-based, case-control study and a longitudinal study
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Scott, J Anthony G, Berkley, James A, Mwangi, Isaiah, Ochola, Lucy, Uyoga, Sophie, Macharia, Alexander, Ndila, Carolyne, Lowe, Brett S, Mwarumba, Salim, Bauni, Evasius, Marsh, Kevin, and Williams, Thomas N
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- 2011
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11. Mortality in rural coastal Kenya measured using the Kilifi Health and Demographic Surveillance System: a 16-year descriptive analysis
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Otiende, Mark, primary, Bauni, Evasius, additional, Nyaguara, Amek, additional, Amadi, David, additional, Nyundo, Christopher, additional, Tsory, Emmanuel, additional, Walumbe, David, additional, Kinuthia, Michael, additional, Kihuha, Norbert, additional, Kahindi, Michael, additional, Nyutu, Gideon, additional, Moisi, Jennifer, additional, Deribew, Amare, additional, Agweyu, Ambrose, additional, Marsh, Kevin, additional, Tsofa, Benjamin, additional, Bejon, Philip, additional, Bottomley, Christian, additional, Williams, Thomas N., additional, and Scott, J. Anthony G., additional
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- 2021
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12. Severe lower respiratory tract infection in early infancy and pneumonia hospitalizations among children, Kenya
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Munywoki, Patrick Kiio, Ohuma, Eric O., Ngama, Mwanajuma, Bauni, Evasius, Scott, J. Anthony G., and Nokes, D. James
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Pneumonia in children -- Causes of -- Diagnosis -- Distribution -- Care and treatment -- Research ,Respiratory syncytial virus -- Health aspects -- Genetic aspects -- Distribution -- Research ,Company distribution practices ,Health - Abstract
Pneumonia is a major cause of illness and death among children We report results of a retrospective cohort analysis of children admitted to a rural district hospital in Kenya using [...]
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- 2013
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13. Excess child mortality after discharge from hospital in Kilifi, Kenya: a retrospective cohort analysis/Surmortalite infantile apres la sortie de l'hopital de Kilifi, au Kenya: une analyse de cohorte retrospective/Sobremortalidad infantil tras el alta de un hospital en Kilifi, Kenia: analisis retrospectivo de cohortes
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Moisi, Jennifer C., Gatakaa, Hellen, Berkley, James A., Maitland, Kathryn, Mturi, Neema, Newton, Charles R., Njuguna, Patricia, Nokes, James, Ojal, John, Bauni, Evasius, Tsofa, Benjamin, Peshu, Norbert, Marsh, Kevin, Williams, Thomas N., and Scott, J. Anthony G.
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Mortality -- Research -- Kenya ,Health care industry -- Quality management ,Children -- Health aspects ,Health care industry ,Health - Abstract
Objective To explore excess paediatric mortality after discharge from Kilifi District Hospital, Kenya, and its duration and risk factors. Methods Hospital and demographic data were used to describe post-discharge mortality and survival probability in children aged < 15 years, by age group and clinical syndrome. Cox regression models were developed to identify risk factors. Findings In 2004-2008, approximately 111 000 children were followed for 555 000 person-years. We analysed 14 971 discharges and 535 deaths occurring within 365 days of discharge. Mortality was higher in the post-discharge cohort than in the community cohort (age-adjusted rate ratio, RR: 7.7; 95% confidence interval, Cl: 6.6-8.9) and declined little over time. An increased post-discharge mortality hazard was found in children aged < 5 years with the following: weight-for-age Z score < -4 (hazard ratio, HR: 6.5); weightfor-age Zscore > -4 but < -3 (HR: 3.4); hypoxia (HR: 2.3); bacteraemia (HR: 1.8); hepatomegaly (HR: 2.3); jaundice (HR: 1.8); hospital stay > 13 days (HR: 1.8). Older age was protective (reference < 1 month): 6-23 months, HR: 0.8; 2-4 years, HR: 0.6. Children with at least one risk factor accounted for 545 (33%) of the 1655 annual discharges and for 39 (47%) of the 83 discharge- associated deaths. Conclusion Hospital admission selects vulnerable children with a sustained increased risk of dying. The risk factors identified provide an empiric basis for effective outpatient follow-up. Objectif Explorer la surmortalite infantile apres la sortie de l'Hopital de District de Kilifi, au Kenya, ainsi que sa duree et ses facteurs de risque. Methodes Des donnees medicales et demographiques ont ete utilisees pour decrine la morlalite suite a une sortie de l'hopital et la probabilite de survie parmi les enfants ages de moins de 15 ans, par groupe d'age et par syndrome clinique. Des modeles de regression de Cox ont ete pour identifier les facteurs de risque. Resultats Entre 2004 et 2008, environ 111 000 enfants ont ete suivis, pour 555000 personnes-ans Nous avons analyse 14 971 sorties et 535 deces survenus dans les 365 jours suivant la sortie. La mortalite etait plus elevee dans la cohorte ayant quitte l'hopital que dans la cohorte communautaire (rapport du taux en fonction de l'age, RA: 7,7; intervalle de confiance a 95%, IC: de 6,6 a 8,9) et n'a que peu decline avec le temps. On a constate un risque de mortalite suite a la sortie de l'hopital accru chez les enfants ages de moins de 5 ans, avec les donnees suivantes: z-score poids/age < -4 (rapport de risque, RR: 6,5); z-score poids/age > -4 mais < -3 (RR: 3,4); hypoxie (RR: 2,3); bacteriemie (RR: 1,8); hepatomegalie (RR: 2,3) ; jaunisse (RR: 1,8); hospitalisation > 13 jours (RR: 1,8). Un age plus eleve etait protecteur (reference < 1 mois): de 6 a 23 mois, RR: 0,8; de 2 a 4 ans, RR : 0,6. Les enfants presentant au moins un facteur de risque representaient 545 (33%) des 1655 sorties annuelles de l'hopital et 39 (47%) des 83 deces associes a la sortie de l'hopital. Conclusion L'admission hospitaliere selectionne les enfants fragiles presentant un risque de deces accru. Les facteurs de risques identifies fournissent une base empirique pour un suivi efficace des patients non hospitalises. Objetivo Examinar la sobremortalidad pediatrica tras el alta hospitalaria en el Hospital del Distrito de Kilifi (Kenia), asi como su duracion y factores de riesgo. Metodos Se emplearon datos hospitalarios y demograficos para describir la mortalidad tras el alta hospitalaria y la probabilidad de supervivencia en ninos menores de 15 anos, por franja de edad y sindrome clinico. Se elaboraron modelos de regresion de Cox para identificar los factores de riesgo. Resultados En 2004-2008, se siguieron aproximadamente 111 000 ninos hasta un total de 555 000 anos-persona. Analizamos 14 971 altas hospitalarias y 535 fallecimientos ocurridos en los 365 dias siguientes al alta hospitalaria. La mortalidad fue mayor en la cohorte post-alta que en la cohorte de la comunidad (razon de tasas ajustada segun la edad, RT: 7,7; intervalo de confianza del 95%, IC: 6,6-8,9) y decrecio ligeramente con el tiempo. En ninos menores de 5 anos se encontro un mayor riesgo de mortalidad post-alta, junto con los siguientes estadisticos: puntuacion Z de peso para la edad < -4 (cociente de riesgos instantaneos [hazard ratio, HR]: 6,5); puntuacion Z de peso para la edad >-4 pero 13 dias (HR: 1,8). A mayor edad el riesgo era menor (referencia < 1 mes): 6-23 meses, HR: 0,8; 2-4 anos, HR: 0,6). Los ninos con al menos un factor de riesgo representaban 545 (33%) de las 1655 altas anuales y 39 (47%) de los 83 fallecimientos relacionados con el alta. Conclusion En el ingreso hospitalario se selecciona a los ninos vulnerables con un mayor riesgo de muerte constante. Los factores de riesgo identificados proporcionan una base empirica para un seguimiento ambulatorio eficaz., Introduction The Integrated Management of Childhood Illness (IMCI) programme and inpatient guidelines of the World Health Organization (WHO) aim to standardize and improve the care of critically ill children at [...]
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- 2011
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14. Active convulsive epilepsy in a rural district of Kenya: a study of prevalence and possible risk factors
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Edwards, Tansy, Scott, Anthony G, Munyoki, Gilbert, Odera, Victor Mung'ala, Chengo, Edward, Bauni, Evasius, Kwasa, Thomas, Sander, Ley W, Neville, Brian G, and Newton, Charles R
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- 2008
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15. Sensitivity of hospital-based surveillance for severe disease: a geographic information system analysis of access to care in Kilifi district, Kenya/Sensibilite de la surveillance hospitaliere des maladies graves: une analyse du systeme d'information geographique de l'acces aux soins dans le district Kilifi au Kenya/Sensibilidad de la vigilancia hospitalaria de enfermedades graves: analisis
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Moisi, Jennifer C., Nokes, D. James, Gatakaa, Hellen, Williams, Thomas N., Bauni, Evasius, Levine, Orin S., and Scott, J. Anthony G.
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Hospitals -- Management -- Kenya ,Mortality -- Research -- Kenya ,Geographic information systems -- Usage ,Company business management ,Geographic information system ,Health - Abstract
Objective To explore the relationship between homestead distance to hospital and access to care and to estimate the sensitivity of hospital-based surveillance in Kilifi district, Kenya. Methods In 2002-2006, clinical information was obtained from all children admitted to Kilifi District Hospital and linked to demographic surveillance data. Travel times to the hospital were calculated using geographic information systems and regression models were constructed to examine the relationships between travel time, cause-specific hospitalization rates and probability of death in hospital. Access to care ratios relating hospitalization rates to community mortality rates were computed and used to estimate surveillance sensitivity. Findings The analysis included 7200 admissions (64 per 1000 child-years). Median pedestrian and vehicular travel times to hospital were 237 end 61 minutes, respectively. Hospitalization rates decreased by 21% per hour of travel by foot and 28% per half hour of travel by vehicle. Distance decay was steeper for meningitis than for pneumonia, for females than for males, and for areas where mothers had less education on average. Distance was positively associated with the probability of dying in hospital. Overall access to care ratios, which represent the probability that a child in need of hospitalization will have access to care at the hospital, were 51-58% for pneumonia and 66-70% for meningitis. Conclusion In this setting, hospital utilization rates decreased and the severity of cases admitted to hospital increased as distance between homestead and hospital increased. Access to hospital care for children living in remote areas was low, particularly for those with less severe conditions. Distance decay was attenuated by increased levels of maternal education. Hospital-based surveillance underestimated pneumonia and meningitis incidence by more than 45% and 30%, respectively. Objectif Explorer la relation entre la distance du domicile a l'hopital et l'acces aux soins, mais aussi evaluer la sensibilite de la surveillance hospitaliere dans le district de Kilifi au Kenya. Methodes Sur la periode 2002-2006, des informations cliniques ont ete obtenues pour tous les enfants admis au Kilifi District Hospital, puis elles ont ete liees aux donnees relatives a la surveillance demographique. Les temps de trajet vers l'hopital ont ete calcules a l'aide de systemes d'information geographique, et des modeles de regression ont ete crees afin d'examiner les relations entre le temps de trajet, les taux d'hospitalisation par cause et la probabilite de deces a l'hopital. Les taux d'acces aux soins reliant les taux d'hospitalisation aux taux de mortalite de la communaute ont ete calcules et utilises afin d'evaluer la sensibilite de la surveillance. Resultats L'analyse a inclus 7 200 admissions (64 pour 1 000 enfants-annees). Les temps de trajet moyens a pled et en vehicule vers l'hopital etaient respectivement de 237 et de 61 minutes. Les taux d'hospitalisation ont diminue de 21% par heure de trajet a pled et de 28 % par demiheure de trajet en vehicule. L'impact de la distance a ete plus eleve pour la meningite que pour la pneumonie, pour les filles que pour les garcons, mais aussi pour les zones ou l'education des meres etait en moyenne inferieure. La distance etait formellement associee a la probabilite de mourir a l'hopital. Les taux globaux de l'acces aux soins, qui representent la probabilite qu'un enfant necessitant une hospitalisation puisse acceder aux soins hospitaliers, etaient de 51-58 % pour la pneumonie et de 66-70 % pour la meningite. Conclusion Dans ce contexte, les taux d'utilisation de l'hopital ont diminue et la gravite des cas admis a l'hopital a augmente Iorsque la distance entre le domicile et l'hopital augmentait. L'acces aux soins hospitaliers pour les enfants vivant dans les zones eloignees etait faible, en particulier pour ceux dont l'etat de sante etait grave. L'impact de la distance a ete attenue par l'elevation des niveaux d'education maternelle. La surveillance hospitaliere a sous-estime l'incidence de la pneumonie et de la meningite de plus de 45 % et 30 %, respectivement. Objetivo Investigar la relacion existente entre la distancia desde el hogar del paciente al hospital y el acceso a la asistencia. Valorar la sensibilidad de la vigilancia hospitalaria en el distrito de Kilifi, Kenya. Metodos Entre 2002 y 2006 se obtuvo la informacion clinica de todos los ninos ingresados en el Hospital del Distrito de Kilifi y dicha informacion se vinculo a los datos de vigilancia demografica. Se calcularon los trayectos al hospital, empleando los sistemas de informacion geografica, y se disenaron modelos de regresion para analizar las relaciones entre la duracion del trayecto, las tasas de hospitalizacion para cada causa especifica y la probabilidad de muerte hospitalaria. Los porcentajes de acceso a la asistencia, que relacionaban las tasas de hospitalizacion con las tasas de mortalidad en la comunidad, se informatizaron y se emplearon para calcular la sensibilidad de la vigilancia. Resultados EI analisis inciuyo 7 200 ingresos (64 por cada 1000 ninos-anos). La duracion media de los trayectos al hospital fue de 237 minutos caminando y de 61 minutos en coche u otro vehiculo. Las tasas de hospitalizacion descendieron en un 21% por cada hora de trayecto a pie y en un 28% por cada hora de trayecto en coche u otro vehiculo. La influencia de la distancia fue mas pronunciada para la meningitis que para la neumonia, para las mujeres que para los hombres y para las areas en las que las madres contaban con un nivel inferior de educacion. La distancia se asocio categoricamente con la probabilidad de morir en el hospital. Los porcentajes generales de acceso a la asistencia, que representan la probabilidad de que un nino que requiera hospitalizacion tenga acceso a la asistencia hospitalaria, fueron de un 51-58% para la neumonia y de un 66-70% para la meningitis. Conclusion En esta situacion, las tasas de utilizacion del hospital descendieron y la gravedad de los casos de los ingresados en el hospital aumento conforme aumentaba la distancia entre el hogar del paciente y el hospital. EI acceso a la asistencia hospitalaria de los ninos que vivian en las areas alejadas fue baio, especialmente para aquellos que presentaban afecciones de menor gravedad. La influencia de la distancia se atenuo por el aumento del nivel de educacion materna. La vigilancia hospitalaria infravaloro la incidencia de la neumonia y de la meningitis en mas de un 45% y de un 30%, respectivamente., Introduction In addition to a focus on the Millennium Development Goals--specifically Goal 4, which aims for a two-thirds reduction in under-5 mortality between 1990 and 2015--the child survival agenda in [...]
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- 2011
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16. Burden of epilepsy in rural Kenya measured in disability-adjusted life years
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Ibinda, Fredrick, Wagner, Ryan G., Bertram, Melanie Y., Ngugi, Anthony K., Bauni, Evasius, Vos, Theo, Sander, Josemir W., and Newton, Charles R.
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- 2014
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17. Incidence and clinical characteristics of group A rotavirus infections among children admitted to hospital in Kilifi, Kenya
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Nokes, D. James, Abwao, John, Pamba, Allan, Peenze, Ina, Dewar, John, Maghenda, J. Kamino, Gatakaa, Hellen, Bauni, Evasius, Scott, J. Anthony G., Maitland, Kathryn, and Williams, Thomas N.
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Children -- Diseases ,Rotavirus infections -- Distribution -- Development and progression ,Company distribution practices ,Biological sciences - Abstract
Background Rotavirus, predominantly of group A, is a major cause of severe diarrhoea worldwide, with the greatest burden falling on young children living in less-developed countries. Vaccines directed against this virus have shown promise in recent trials, and are undergoing effectiveness evaluation in sub-Saharan Africa. In this region limited childhood data are available on the incidence and clinical characteristics of severe group A rotavirus disease. Advocacy for vaccine intervention and interpretation of effectiveness following implementation will benefit from accurate base-line estimates of the incidence and severity of rotavirus paediatric admissions in relevant populations. The study objective was to accurately define the incidence and severity of group A rotavirus disease in a resource-poor setting necessary to make informed decisions on the need for vaccine prevention. Methods and Findings Between 2002 and 2004 we conducted prospective surveillance for group A rotavirus infection at Kilifi District Hospital in coastal Kenya. Children < 13 y of age were eligible as 'cases' if admitted with diarrhoea, and 'controls' if admitted without diarrhoea. We calculated the incidence of hospital admission with group A rotavirus using data from a demographic surveillance study of 220,000 people in Kilifi District. Of 15,347 childhood admissions 3,296 (22%) had diarrhoea, 2,039 were tested for group A rotavirus antigen and, of these, 588 (29%) were positive. 372 (63%) rotavirus-positive cases were infants. Of 620 controls 19 (3.1%, 95% confidence interval [CI] 1.9-4.7) were rotavirus positive. The annual incidence (per 100,000 children) of rotavirus-positive admissions was 1,431 (95% CI 1,275-1,600) in infants and 478 (437-521) in under-5-y-olds, and highest proximal to the hospital. Compared to children with rotavirus-negative diarrhoea, rotavirus-positive cases were less likely to have coexisting illnesses and more likely to have acidosis (46% versus 17%) and severe electrolyte imbalance except hyponatraemia. In-hospital case fatality was 2% among rotavirus-positive and 9% among rotavirus-negative children. Conclusions In Kilifi > 2% of children are admitted to hospital with group A rotavirus diarrhoea in the first 5 y of life. This translates into over 28,000 vaccine-preventable hospitalisations per year across Kenya, and is likely to be a considerable underestimate. Group A rotavirus diarrhoea is associated with acute life-threatening metabolic derangement in otherwise healthy children. Although mortality is low in this clinical research setting this may not be generally true in African hospitals lacking rapid and appropriate management., The Editors' Summary of this article follows the references. Introduction Rotavirus is a major cause of severe diarrhoea worldwide causing in excess of 2 million hospitalisations per annum in under-5-y-old [...]
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- 2008
18. Burden, features, and outcome of neurological involvement in acute falciparum malaria in Kenyan children
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Idro, Richard, Ndiritu, Moses, Ogutu, Bernhards, Mithwani, Sadik, Maitland, Kathryn, Berkley, James, Crawley, Jane, Fegan, Gregory, Bauni, Evasius, Peshu, Norbert, Marsh, Kevin, Neville, Brian, and Newton, Charles
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Malaria -- Research ,Malaria -- Complications and side effects ,Neurologic manifestations of general diseases -- Risk factors ,Children -- Diseases ,Children -- Complications and side effects ,Children -- Research - Abstract
A study to determine the incidence and describe the clinical phenotypes and outcomes of neurological involvement with acute falciparum malaria was conducted. The results revealed that neurological involvement was common with acute falciparum malaria.
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- 2007
19. Incidence of convulsive epilepsy in a rural area in Kenya
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Ngugi, Anthony K., Bottomley, Christian, Scott, Anthony J. G., Mungʼala–Odera, Victor, Bauni, Evasius, Sander, Josemir W., Kleinschmidt, Immo, and Newton, Charles R.
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- 2013
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20. Profile: The Kilifi Health and Demographic Surveillance System (KHDSS)
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Scott, J Anthony G, Bauni, Evasius, Moisi, Jennifer C, Ojal, John, Gatakaa, Hellen, Nyundo, Christopher, Molyneux, Catherine S, Kombe, Francis, Tsofa, Benjamin, Marsh, Kevin, Peshu, Norbert, and Williams, Thomas N
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- 2012
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21. Exploring the condom gap: is supply or demand the limiting factor – condom access and use in an urban and a rural setting in Kilifi district, Kenya
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Papo, Jacqueline K, Bauni, Evasius K, Sanders, Eduard J, Brocklehurst, Peter, and Jaffe, Harold W
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- 2011
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22. Clustering of health risk behaviors among adolescents in Kilifi, Kenya, a rural Sub-Saharan African setting
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Ssewanyana, Derrick, primary, Abubakar, Amina, additional, Newton, Charles R. J. C., additional, Otiende, Mark, additional, Mochamah, George, additional, Nyundo, Christopher, additional, Walumbe, David, additional, Nyutu, Gideon, additional, Amadi, David, additional, Doyle, Aoife M., additional, Ross, David A., additional, Nyaguara, Amek, additional, Williams, Thomas N., additional, and Bauni, Evasius, additional
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- 2020
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23. Linking health facility data from young adults aged 18-24 years to longitudinal demographic data: Experience from The Kilifi Health and Demographic Surveillance System
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Nyundo, Christopher, primary, Doyle, Aoife M., additional, Walumbe, David, additional, Otiende, Mark, additional, Kinuthia, Michael, additional, Amadi, David, additional, Jibendi, Boniface, additional, Mochamah, George, additional, Kihuha, Norbert, additional, Williams, Thomas N., additional, Ross, David A., additional, and Bauni, Evasius, additional
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- 2020
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24. Diagnostic criteria for severe acute malnutrition among infants aged under 6 mo123
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Mwangome, Martha, Ngari, Moses, Fegan, Greg, Mturi, Neema, Shebe, Mohammed, Bauni, Evasius, and Berkley, James A
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Male ,Nutritional Status ,Child Nutrition Disorders ,Severity of Illness Index ,infants under 6 months ,Nutritional Epidemiology and Public Health ,Reference Values ,Body Size ,Humans ,Child ,Growth Disorders ,weight-for-length ,Anthropometry ,MUAC ,Body Weight ,Malnutrition ,Age Factors ,Infant, Newborn ,HIV ,Infant ,Kenya ,Body Height ,Patient Discharge ,Hospitalization ,SAM ,ROC Curve ,Acute Disease ,Arm ,Female - Abstract
Background: There is an increasing recognition of malnutrition among infants under 6 mo of age (U6M). Current diagnosis criteria use weight-for-length z scores (WLZs), but the 2006 WHO standards exclude infants shorter than 45 cm. In older children, midupper arm circumference (MUAC) predicts mortality better than does WLZ. Outcomes may also be influenced by exposure to HIV and size or gestational age at birth. Diagnostic thresholds for WLZ, MUAC, and other indexes have not been fully evaluated against mortality risk among U6M infants. Objective: The aim was to determine the association of anthropometric indexes with risks of inpatient and postdischarge mortality among U6M infants recruited at the time of hospitalization. Design: We analyzed data from a cohort of U6M infants admitted to Kilifi County Hospital (2007–2013), Kenya. The primary outcomes were inpatient death and death during follow-up over 1 y after discharge. We calculated adjusted RRs for inpatient mortality and HRs for postdischarge mortality for different anthropometric measures and thresholds. Discriminatory value was assessed by using receiver operating characteristic curves. Results: A total of 2882 infants were admitted: 140 (4.9%) died in the hospital and 1405 infants were followed up after discharge. Of these, 75 (5.3%) died within 1 y during 1318 child-years of observation. MUAC and weight-for-age z score (WAZ) predicted inpatient and postdischarge mortality better than did WLZ (P < 0.0001). A single MUAC threshold of 0.05) and performed better than WLZ
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- 2017
25. Age, Spatial, and Temporal Variations in Hospital Admissions with Malaria in Kilifi County, Kenya: A 25-Year Longitudinal Observational Study
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Mogeni, Polycarp, Williams, Thomas N., Fegan, Gregory, Nyundo, Christopher, Bauni, Evasius, Mwai, Kennedy, Omedo, Irene, Njuguna, Patricia, Newton, Charles R., Osier, Faith, Berkley, James A., Hammitt, Laura L., Lowe, Brett, Mwambingu, Gabriel, Awuondo, Ken, Mturi, Neema, Peshu, Norbert, Snow, Robert W., Noor, Abdisalan, Marsh, Kevin, and Bejon, Philip
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Hospital admission and discharge -- Management ,Plasmodium falciparum -- Research ,Malaria -- Risk factors ,Company business management ,Biological sciences - Abstract
Background Encouraging progress has been seen with reductions in Plasmodium falciparum malaria transmission in some parts of Africa. Reduced transmission might lead to increasing susceptibility to malaria among older children due to lower acquired immunity, and this has implications for ongoing control strategies. Methods and Findings We conducted a longitudinal observational study of children admitted to Kilifi County Hospital in Kenya and linked it to data on residence and insecticide-treated net (ITN) use. This included data from 69,104 children aged from 3 mo to 13 y admitted to Kilifi County Hospital between 1 January 1990 and 31 December 2014. The variation in malaria slide positivity among admissions was examined in logistic regression models using the following predictors: location of the residence, calendar time, the child's age, ITN use, and the enhanced vegetation index (a proxy for soil moisture). The proportion of malaria slide-positive admissions declined from 0.56 (95% confidence interval [CI] 0.54-0.58) in 1998 to 0.07 (95% CI 0.06-0.08) in 2009 but then increased again through to 0.24 (95% CI 0.22-0.25) in 2014. Older children accounted for most of the increase after 2009 (0.035 [95% CI 0.030-0.040] among young children compared to 0.22 [95% CI 0.21-0.23] in older children). There was a nonlinear relationship between malaria risk and prevalence of ITN use within a 2 km radius of an admitted child's residence such that the predicted malaria positive fraction varied from ~0.4 to Conclusion Following a period of reduced transmission, a cohort of older children emerged who have increased susceptibility to malaria. Further reductions in malaria transmission are needed to mitigate the increasing burden among older children, and universal ITN coverage is a promising strategy to achieve this goal., Author(s): Polycarp Mogeni 1,*, Thomas N. Williams 1,2, Gregory Fegan 1,3, Christopher Nyundo 1, Evasius Bauni 1, Kennedy Mwai 1, Irene Omedo 1, Patricia Njuguna 1, Charles R. Newton 1,3, [...]
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- 2016
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26. Bacteremia among Children Admitted to a Rural Hospital in Kenya
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Berkley, James A., Lowe, Brett S., Mwangi, Isaiah, Williams, Thomas, Bauni, Evasius, Mwarumba, Saleem, Ngetsa, Caroline, Slack, Mary P.E., Njenga, Sally, Hart, C. Anthony, Maitland, Kathryn, English, Mike, Marsh, Kevin, and Scott, J. Anthony G.
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- 2005
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27. Electroencephalographic features of convulsive epilepsy in Africa: A multicentre study of prevalence, pattern and associated factors
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Kariuki, Symon M., White, Steven, Chengo, Eddie, Wagner, Ryan G., Ae-Ngibise, Kenneth A., Kakooza-Mwesige, Angelina, Ngugi, Anthony K., Sander, Josemir W., Neville, Brian G., Newton, Charles R., Wagner, Ryan, Twine, Rhian, Connor, Myles, Olivé, F. Xavier Gómez, Collinson, Mark, Kahn, Kathleen, Tollman, Stephen, Masanja, Honratio, Mathew, Alexander, Kakooza, Angelina, Pariyo, George, Peterson, Stefan, Ndyomughenyi, Donald, Odhiambo, Rachael, Chabi, Martin, Bauni, Evasius, Kamuyu, Gathoni, Odera, Victor Mung ala, Mageto, James O., Ae-Ngibise, Ken, Akpalu, Bright, Akpalu, Albert, Agbokey, Francis, Adjei, Patrick, Owusu-Agyei, Seth, Bottomley, Christian, Kleinschmidt, Immo, Doku, Victor C K, Odermatt, Peter, Neville, Brian, Nutman, Thomas, Wilkins, Patricia, and Noh, John
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Adult ,Male ,Pediatrics ,medicine.medical_specialty ,Adolescent ,Clinical Neurology ,Electroencephalography ,Article ,Temporal lobe ,Young Adult ,03 medical and health sciences ,symbols.namesake ,Epilepsy ,0302 clinical medicine ,Physiology (medical) ,Prevalence ,medicine ,Humans ,Active convulsive epilepsy ,030212 general & internal medicine ,Poisson regression ,Young adult ,Child ,Seizure frequency ,medicine.diagnostic_test ,business.industry ,Electroencephalographic features ,Middle Aged ,medicine.disease ,Sensory Systems ,Confidence interval ,3. Good health ,Risk factors ,Neurology ,Relative risk ,Africa ,symbols ,Female ,Neurology (clinical) ,business ,030217 neurology & neurosurgery - Abstract
Highlights • Electroencephalographic abnormalities are common in Africans with epilepsy, with an adjusted prevalence of 2.7 (95% confidence interval, 2.5–2.9) per 1000 population. • Electroencephalographic abnormalities are associated with preventable factors such as adverse perinatal events and frequent seizures. • Electroencephalography is helpful in identifying focal epilepsy in Africa, where timing of focal aetiologies is problematic and there is a lack of neuroimaging services., Objective We investigated the prevalence and pattern of electroencephalographic (EEG) features of epilepsy and the associated factors in Africans with active convulsive epilepsy (ACE). Methods We characterized electroencephalographic features and determined associated factors in a sample of people with ACE in five African sites. Mixed-effects modified Poisson regression model was used to determine factors associated with abnormal EEGs. Results Recordings were performed on 1426 people of whom 751 (53%) had abnormal EEGs, being an adjusted prevalence of 2.7 (95% confidence interval (95% CI), 2.5–2.9) per 1000. 52% of the abnormal EEG had focal features (75% with temporal lobe involvement). The frequency and pattern of changes differed with site. Abnormal EEGs were associated with adverse perinatal events (risk ratio (RR) = 1.19 (95% CI, 1.07–1.33)), cognitive impairments (RR = 1.50 (95% CI, 1.30–1.73)), use of anti-epileptic drugs (RR = 1.25 (95% CI, 1.05–1.49)), focal seizures (RR = 1.09 (95% CI, 1.00–1.19)) and seizure frequency (RR = 1.18 (95% CI, 1.10–1.26) for daily seizures; RR = 1.22 (95% CI, 1.10–1.35) for weekly seizures and RR = 1.15 (95% CI, 1.03–1.28) for monthly seizures)). Conclusions EEG abnormalities are common in Africans with epilepsy and are associated with preventable risk factors. Significance EEG is helpful in identifying focal epilepsy in Africa, where timing of focal aetiologies is problematic and there is a lack of neuroimaging services.
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- 2016
28. The validation of a three-stage screening methodology for detecting active convulsive epilepsy in population-based studies in health and demographic surveillance systems
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Ngugi Anthony K, Bottomley Christian, Chengo Eddie, Kombe Martha Z, Kazungu Michael, Bauni Evasius, Mbuba Caroline K, Kleinschmidt Immo, and Newton Charles R
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Epilepsy ,Three-stage methodology ,Screening ,Validation ,Sensitivity ,LMIC ,Infectious and parasitic diseases ,RC109-216 - Abstract
Abstract Background There are few studies on the epidemiology of epilepsy in large populations in Low and Middle Income Countries (LMIC). Most studies in these regions use two-stage population-based screening surveys, which are time-consuming and costly to implement in large populations required to generate accurate estimates. We examined the sensitivity and specificity of a three-stage cross-sectional screening methodology in detecting active convulsive epilepsy (ACE), which can be embedded within on-going census of demographic surveillance systems. We validated a three-stage cross-sectional screening methodology on a randomly selected sample of participants of a three-stage prevalence survey of epilepsy. Diagnosis of ACE by an experienced clinician was used as ‘gold standard’. We further compared the expenditure of this method with the standard two-stage methodology. Results We screened 4442 subjects in the validation and identified 35 cases of ACE. Of these, 18 were identified as false negatives, most of whom (15/18) were missed in the first stage and a few (3/18) in the second stage of the three-stage screening. Overall, this methodology had a sensitivity of 48.6% and a specificity of 100%. It was 37% cheaper than a two-stage survey. Conclusion This was the first study to evaluate the performance of a multi-stage screening methodology used to detect epilepsy in demographic surveillance sites. This method had poor sensitivity attributed mainly to stigma-related non-response in the first stage. This method needs to take into consideration the poor sensitivity and the savings in expenditure and time as well as validation in target populations. Our findings suggest the need for continued efforts to develop and improve case-ascertainment methods in population-based epidemiological studies of epilepsy in LMIC.
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- 2012
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29. Human candidate gene polymorphisms and risk of severe malaria in children in Kilifi, Kenya: a case-control association study
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Ndila, Carolyne M, Uyoga, Sophie, Macharia, Alexander W, Nyutu, Gideon, Peshu, Norbert, Ojal, John, Shebe, Mohammed, Awuondo, Kennedy O, Mturi, Neema, Tsofa, Benjamin, Sepúlveda, Nuno, Clark, Taane G, Band, Gavin, Clarke, Geraldine, Rowlands, Kate, Hubbart, Christina, Jeffreys, Anna, Kariuki, Silvia, Marsh, Kevin, Mackinnon, Margaret, Maitland, Kathryn, Kwiatkowski, Dominic P, Rockett, Kirk A, Williams, Thomas N, Abathina, Amadou, Abubakar, Ismaela, Achidi, Eric, Agbenyega, Tsiri, Aiyegbo, Mohammed, Akoto, Alex, Allen, Angela, Allen, Stephen, Amenga-Etego, Lucas, Amodu, Folakemi, Amodu, Olukemi, Anchang-Kimbi, Judith, Ansah, Nana, Ansah, Patrick, Ansong, Daniel, Antwi, Sampson, Anyorigiya, Thomas, Apinjoh, Tobias, Asafo-Agyei, Emmanuel, Asoala, Victor, Atuguba, Frank, Auburn, Sarah, Bah, Abdou, Bamba, Kariatou, Bancone, Germana, Barnwell, David, Barry, Abdoulaye, Bauni, Evasius, Besingi, Richard, Bojang, Kalifa, Bougouma, Edith, Bull, Susan, Busby, George, Camara, Abdoulie, Camara, Landing, Campino, Susana, Carter, Richard, Carucci, Dan, Casals-Pascual, Climent, Ceesay, Ndey, Ceesay, Pa, Chau, Tran, Chuong, Ly, Clark, Taane, Cole-Ceesay, Ramou, Conway, David, Cook, Katharine, Cook, Olivia, Cornelius, Victoria, Corran, Patrick, Correa, Simon, Cox, Sharon, Craik, Rachel, Danso, Bakary, Davis, Timothy, Day, Nicholas, Deloukas, Panos, Dembele, Awa, Devries, Jantina, Dewasurendra, Rajika, Diakite, Mahamadou, Diarra, Elizabeth, Dibba, Yaya, Diss, Andrea, Djimdé, Abdoulaye, Dolo, Amagana, Doumbo, Ogobara, Doyle, Alan, Drakeley, Chris, Drury, Eleanor, Duffy, Patrick, Dunstan, Sarah, Ebonyi, Augustine, Elhassan, Ahmed, Elhassan, Ibrahim, Elzein, Abier, Enimil, Anthony, Esangbedo, Pamela, Evans, Jennifer, Evans, Julie, Farrar, Jeremy, Fernando, Deepika, Fitzpatrick, Kathryn, Fullah, Janet, Garcia, Jacob, Ghansah, Anita, Gottleib, Michael, Green, Angie, Hart, Lee, Hennsman, Meike, Hien, Tran, Hieu, Nguyen, Hilton, Eliza, Hodgson, Abraham, Horstmann, Rolf, Hughes, Catherine, Hussein, Ayman, Hutton, Robert, Ibrahim, Muntaser, Ishengoma, Deus, Jaiteh, Jula, Jallow, Mariatou, Jallow, Muminatou, Jammeh, Kebba, Jasseh, Momodou, Jobarteh, Amie, Johnson, Kimberly, Joseph, Sarah, Jyothi, Dushyanth, Kachala, David, Kamuya, Dorcas, Kanyi, Haddy, Karunajeewa, Harin, Karunaweera, Nadira, Keita, Momodou, Kerasidou, Angeliki, Khan, Aja, Kivinen, Katja, Kokwaro, Gilbert, Konate, Amadou, Konate, Salimata, Koram, Kwadwo, Kwiatkowski, Dominic, Laman, Moses, Si, Le, Leffler, Ellen, Lemnge, Martha, Lin, Enmoore, Alioune, Ly, Macharia, Alexander, Macinnis, Bronwyn, Mai, Nguyen, Makani, Julie, Malangone, Cinzia, Mangano, Valentina, Manjurano, Alphaxard, Manneh, Lamin, Manning, Laurens, Manske, Magnus, Marsh, Vicki, Maslen, Gareth, Maxwell, Caroline, Mbunwe, Eric, Mccreight, Marilyn, Mead, Daniel, Mendy, Alieu, Mendy, Anthony, Mensah, Nathan, Michon, Pascal, Miles, Alistair, Miotto, Olivo, Modiano, David, Mohamed, Hiba, Molloy, Sile, Molyneux, Malcolm, Molyneux, Sassy, Moore, Mike, Moyes, Catherine, Mtei, Frank, Mtove, George, Mueller, Ivo, Mugri, Regina, Munthali, Annie, Mutabingwa, Theonest, Nadjm, Behzad, Ndi, Andre, Ndila, Carolyne, Newton, Charles, Niangaly, Amadou, Njie, Haddy, Njie, Jalimory, Njie, Madi, Njie, Malick, Njie, Sophie, Njiragoma, Labes, Nkrumah, Francis, Ntunthama, Neema, Nyika, Aceme, Nyirongo, Vysaul, O'Brien, John, Obu, Herbert, Oduro, Abraham, Ofori, Alex, Olaniyan, Subulade, Olaosebikan, Rasaq, Oluoch, Tom, Omotade, Olayemi, Oni, Olajumoke, Onykwelu, Emmanuel, Opi, Daniel, Orimadegun, Adebola, O'Riordan, Sean, Ouedraogo, Issa, Oyola, Samuel, Parker, Michael, Pearson, Richard, Pensulo, Paul, Phiri, Ajib, Phu, Nguyen, Pinder, Margaret, Pirinen, Matti, Plowe, Chris, Potter, Claire, Poudiougou, Belco, Puijalon, Odile, Quyen, Nguyen, Ragoussis, Ioannis, Ragoussis, Jiannis, Rasheed, Oba, Reeder, John, Reyburn, Hugh, Riley, Eleanor, Risley, Paul, Rockett, Kirk, Rodford, Joanne, Rogers, Jane, Rogers, William, Ruano-Rubio, Valentín, Sabally-Ceesay, Kumba, Sadiq, Abubacar, Saidy-Khan, Momodou, Saine, Horeja, Sakuntabhai, Anavaj, Sall, Abdourahmane, Sambian, David, Sambou, Idrissa, Sanjoaquin, Miguel, Shah, Shivang, Shelton, Jennifer, Siba, Peter, Silva, Nilupa, Simmons, Cameron, Simpore, Jaques, Singhasivanon, Pratap, Sinh, Dinh, Sirima, Sodiomon, Sirugo, Giorgio, Sisay-Joof, Fatoumatta, Sissoko, Sibiry, Small, Kerrin, Somaskantharajah, Elilan, Spencer, Chris, Stalker, Jim, Stevens, Marryat, Suriyaphol, Prapat, Sylverken, Justice, Taal, Bintou, Tall, Adama, Taylor, Terrie, Teo, Yik, Thai, Cao, Thera, Mahamadou, Titanji, Vincent, Toure, Ousmane, Troye-Blomberg, Marita, Usen, Stanley, Vanderwal, Aaron, Wangai, Hannah, Watson, Renee, Williams, Thomas, Wilson, Michael, Wrigley, Rebecca, Yafi, Clarisse, Yamoah, Lawrence, The Wellcome Trust Centre for Human Genetics [Oxford], University of Oxford, London School of Hygiene and Tropical Medicine (LSHTM), The Wellcome Trust Sanger Institute [Cambridge], St Mary's Hospital, Imperial College, TNW and MM are funded through awards from the Wellcome Trust (grants 091758 and 202800 [to TNW] and grant 088634 [to MM]) and DPK and TGC receive support from the Medical Research Council (grant G19/9 [to DPK] and grants MR/K000551/1, MR/M01360X/1, MR/N010469/1, and MC_PC_15103 [to TGC]). The research leading to these results received funding from the European Community's Seventh Framework Programme (FP7/2007-2013, under grant agreement 242095) and from the Medical Research Council (grant G0600718). MalariaGEN is supported by the Wellcome Trust (WT077383/Z/05/Z) and by the Foundation for the National Institutes of Health (grant 566) as part of the Bill & Melinda Gates' Grand Challenges in Global Health Initiative. The Resource Centre for Genomic Epidemiology of Malaria is supported by the Wellcome Trust (grant 090770/Z/09/Z). Support was also provided by the Medical Research Council (grant G0600718). The Wellcome Trust also provides core awards to the Wellcome Trust Centre for Human Genetics (grant 090532/Z/09/Z) and to the Wellcome Trust Sanger Institute (grant 098051). This work forms part of a larger collaboration with the MalariaGEN Consortium, whose members are listed at http://www.malariagen.net/projects/host/consortium-members. This paper is published with permission from the Director of the Kenya Medical Research Institute (KEMRI)., MalariaGEN Consortium (Anavaj Sakuntabhai), and European Project: 242095,EC:FP7:HEALTH,FP7-HEALTH-2009-single-stage,EVIMALAR(2009)
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Case-Control Studies ,Child ,Child, Preschool ,Female ,Gene Frequency ,Genetic Predisposition to Disease ,Humans ,Kenya ,Malaria ,Male ,Polymorphism, Genetic ,Hematology ,macromolecular substances ,[SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM] ,Article ,Genetic ,[SDV.GEN.GH]Life Sciences [q-bio]/Genetics/Human genetics ,parasitic diseases ,[SDV.MP.PAR]Life Sciences [q-bio]/Microbiology and Parasitology/Parasitology ,[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie ,Polymorphism ,Preschool - Abstract
Summary Background Human genetic factors are important determinants of malaria risk. We investigated associations between multiple candidate polymorphisms—many related to the structure or function of red blood cells—and risk for severe Plasmodium falciparum malaria and its specific phenotypes, including cerebral malaria, severe malaria anaemia, and respiratory distress. Methods We did a case-control study in Kilifi County, Kenya. We recruited as cases children presenting with severe malaria to the high-dependency ward of Kilifi County Hospital. We included as controls infants born in the local community between Aug 1, 2006, and Sept 30, 2010, who were part of a genetics study. We tested for associations between a range of candidate malaria-protective genes and risk for severe malaria and its specific phenotypes. We used a permutation approach to account for multiple comparisons between polymorphisms and severe malaria. We judged p values less than 0·005 significant for the primary analysis of the association between candidate genes and severe malaria. Findings Between June 11, 1995, and June 12, 2008, 2244 children with severe malaria were recruited to the study, and 3949 infants were included as controls. Overall, 263 (12%) of 2244 children with severe malaria died in hospital, including 196 (16%) of 1233 with cerebral malaria. We investigated 121 polymorphisms in 70 candidate severe malaria-associated genes. We found significant associations between risk for severe malaria overall and polymorphisms in 15 genes or locations, of which most were related to red blood cells: ABO, ATP2B4, ARL14, CD40LG, FREM3, INPP4B, G6PD, HBA (both HBA1 and HBA2), HBB, IL10, LPHN2 (also known as ADGRL2), LOC727982, RPS6KL1, CAND1, and GNAS. Combined, these genetic associations accounted for 5·2% of the variance in risk for developing severe malaria among individuals in the general population. We confirmed established associations between severe malaria and sickle-cell trait (odds ratio [OR] 0·15, 95% CI 0·11–0·20; p=2·61 × 10−58), blood group O (0·74, 0·66–0·82; p=6·26 × 10−8), and –α3·7-thalassaemia (0·83, 0·76–0·90; p=2·06 × 10−6). We also found strong associations between overall risk of severe malaria and polymorphisms in both ATP2B4 (OR 0·76, 95% CI 0·63–0·92; p=0·001) and FREM3 (0·64, 0·53–0·79; p=3·18 × 10−14). The association with FREM3 could be accounted for by linkage disequilibrium with a complex structural mutation within the glycophorin gene region (comprising GYPA, GYPB, and GYPE) that encodes for the rare Dantu blood group antigen. Heterozygosity for Dantu was associated with risk for severe malaria (OR 0·57, 95% CI 0·49–0·68; p=3·22 × 10−11), as was homozygosity (0·26, 0·11–0·62; p=0·002). Interpretation Both ATP2B4 and the Dantu blood group antigen are associated with the structure and function of red blood cells. ATP2B4 codes for plasma membrane calcium-transporting ATPase 4 (the major calcium pump on red blood cells) and the glycophorins are ligands for parasites to invade red blood cells. Future work should aim at uncovering the mechanisms by which these polymorphisms can result in severe malaria protection and investigate the implications of these associations for wider health. Funding Wellcome Trust, UK Medical Research Council, European Union, and Foundation for the National Institutes of Health as part of the Bill & Melinda Gates Grand Challenges in Global Health Initiative.
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- 2018
30. Effect of ten-valent pneumococcal conjugate vaccine on invasive pneumococcal disease and nasopharyngeal carriage in Kenya: a longitudinal surveillance study
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Hammitt, Laura L, primary, Etyang, Anthony O, additional, Morpeth, Susan C, additional, Ojal, John, additional, Mutuku, Alex, additional, Mturi, Neema, additional, Moisi, Jennifer C, additional, Adetifa, Ifedayo M, additional, Karani, Angela, additional, Akech, Donald O, additional, Otiende, Mark, additional, Bwanaali, Tahreni, additional, Wafula, Jackline, additional, Mataza, Christine, additional, Mumbo, Edward, additional, Tabu, Collins, additional, Knoll, Maria Deloria, additional, Bauni, Evasius, additional, Marsh, Kevin, additional, Williams, Thomas N, additional, Kamau, Tatu, additional, Sharif, Shahnaaz K, additional, Levine, Orin S, additional, and Scott, J Anthony G, additional
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- 2019
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31. Effect of Previous Exposure to Malaria on Blood Pressure in Kilifi, Kenya: A Mendelian Randomization Study
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Etyang, Anthony O., primary, Kapesa, Sailoki, additional, Odipo, Emily, additional, Bauni, Evasius, additional, Kyobutungi, Catherine, additional, Abdalla, Marwah, additional, Muntner, Paul, additional, Musani, Solomon K., additional, Macharia, Alex, additional, Williams, Thomas N., additional, Cruickshank, J. Kennedy, additional, Smeeth, Liam, additional, and Scott, J. Anthony G., additional
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- 2019
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32. Validating physician-certified verbal autopsy and probabilistic modeling (InterVA) approaches to verbal autopsy interpretation using hospital causes of adult deaths
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Tsofa Benjamin, Mutinda Maureen, Mambo Barbara, Ondieki Charles, Matata Lena, Nyutu Gideon, Mochamah George, Ndila Carolyne, Bauni Evasius, Maitha Eric, Etyang Anthony, and Williams Thomas N
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verbal autopsy ,InterVA ,validation ,cause-specific mortality fraction ,kappa ,ROC ,Computer applications to medicine. Medical informatics ,R858-859.7 ,Public aspects of medicine ,RA1-1270 - Abstract
Abstract Background The most common method for determining cause of death is certification by physicians based either on available medical records, or where such data are not available, through verbal autopsy (VA). The physician-certification approach is costly and inconvenient; however, recent work shows the potential of a computer-based probabilistic model (InterVA) to interpret verbal autopsy data in a more convenient, consistent, and rapid way. In this study we validate separately both physician-certified verbal autopsy (PCVA) and the InterVA probabilistic model against hospital cause of death (HCOD) in adults dying in a district hospital on the coast of Kenya. Methods Between March 2007 and June 2010, VA interviews were conducted for 145 adult deaths that occurred at Kilifi District Hospital. The VA data were reviewed by a physician and the cause of death established. A range of indicators (including age, gender, physical signs and symptoms, pregnancy status, medical history, and the circumstances of death) from the VA forms were included in the InterVA for interpretation. Cause-specific mortality fractions (CSMF), Cohen's kappa (κ) statistic, receiver operating characteristic (ROC) curves, sensitivity, specificity, and positive predictive values were applied to compare agreement between PCVA, InterVA, and HCOD. Results HCOD, InterVA, and PCVA yielded the same top five underlying causes of adult deaths. The InterVA overestimated tuberculosis as a cause of death compared to the HCOD. On the other hand, PCVA overestimated diabetes. Overall, CSMF for the five major cause groups by the InterVA, PCVA, and HCOD were 70%, 65%, and 60%, respectively. PCVA versus HCOD yielded a higher kappa value (κ = 0.52, 95% confidence interval [CI]: 0.48, 0.54) than the InterVA versus HCOD which yielded a kappa (κ) value of 0.32 (95% CI: 0.30, 0.38). Overall, (κ) agreement across the three methods was 0.41 (95% CI: 0.37, 0.48). The areas under the ROC curves were 0.82 for InterVA and 0.88 for PCVA. The observed sensitivities and specificities across the five major causes of death varied from 43% to 100% and 87% to 99%, respectively, for the InterVA/PCVA against the HCOD. Conclusion Both the InterVA and PCVA compared well with the HCOD at a population level and determined the top five underlying causes of death in the rural community of Kilifi. We hope that our study, albeit small, provides new and useful data that will stimulate further definitive work on methods of interpreting VA data.
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- 2011
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33. Coverage and timeliness of vaccination and the validity of routine estimates: Insights from a vaccine registry in Kenya
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Adetifa, Ifedayo M.O., primary, Karia, Boniface, additional, Mutuku, Alex, additional, Bwanaali, Tahreni, additional, Makumi, Anne, additional, Wafula, Jackline, additional, Chome, Martina, additional, Mwatsuma, Pauline, additional, Bauni, Evasius, additional, Hammitt, Laura L., additional, Mataza, Christine, additional, Tabu, Collins, additional, Kamau, Tatu, additional, Williams, Thomas N., additional, and Scott, J. Anthony G., additional
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- 2018
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34. Neonatal seizures in a rural Kenyan District Hospital: aetiology, Incidence and outcome of hospitalization
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Newton Charles RJC, Bauni Evasius, Mturi Neema, Gwer Samson, Mathenge Ali, Mwaniki Michael, Berkley James, and Idro Richard
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Medicine - Abstract
Abstract Background Acute seizures are common among children admitted to hospitals in resource poor countries. However, there is little data on the burden, causes and outcome of neonatal seizures in sub-Saharan Africa. We determined the minimum incidence, aetiology and immediate outcome of seizures among neonates admitted to a rural district hospital in Kenya. Methods From 1st January 2003 to 31st December 2007, we assessed for seizures all neonates (age 0-28 days) admitted to the Kilifi District Hospital, who were resident in a defined, regularly enumerated study area. The population denominator, the number of live births in the community on 1 July 2005 (the study midpoint) was modelled from the census data. Results Seizures were reported in 142/1572 (9.0%) of neonatal admissions. The incidence was 39.5 [95% confidence interval (CI) 26.4-56.7] per 1000 live-births and incidence increased with birth weight. The main diagnoses in neonates with seizures were sepsis in 85 (60%), neonatal encephalopathy in 30 (21%) and meningitis in 21 (15%), but only neonatal encephalopathy and bacterial meningitis were independently associated with seizures. Neonates with seizures had a longer hospitalization [median period 7 days - interquartile range (IQR) 4 to10] -compared to 5 days [IQR 3 to 8] for those without seizures, P = 0.02). Overall, there was no difference in inpatient case fatality between neonates with and without seizures but, when this outcome was stratified by birth weight, it was significantly higher in neonates ≥ 2.5 kg compared to low birth weight neonates [odds ratio 1.59 (95%CI 1.02 to 2.46), P = 0.037]. Up to 13% of the surviving newborn with seizures had neurological abnormalities at discharge. Conclusion There is a high incidence of neonatal seizures in this area of Kenya and the most important causes are neonatal encephalopathy and meningitis. The high incidence of neonatal seizures may be a reflection of the quality of the perinatal and postnatal care available to the neonates.
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- 2010
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35. Geographic access to care is not a determinant of child mortality in a rural Kenyan setting with high health facility density
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Williams Thomas N, Noor Abdisalan M, Gatakaa Hellen, Moïsi Jennifer C, Bauni Evasius, Tsofa Benjamin, Levine Orin S, and Scott J Anthony G
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Public aspects of medicine ,RA1-1270 - Abstract
Abstract Background Policy-makers evaluating country progress towards the Millennium Development Goals also examine trends in health inequities. Distance to health facilities is a known determinant of health care utilization and may drive inequalities in health outcomes; we aimed to investigate its effects on childhood mortality. Methods The Epidemiological and Demographic Surveillance System in Kilifi District, Kenya, collects data on vital events and migrations in a population of 220,000 people. We used Geographic Information Systems to estimate pedestrian and vehicular travel times to hospitals and vaccine clinics and developed proportional-hazards models to evaluate the effects of travel time on mortality hazard in children less than 5 years of age, accounting for sex, ethnic group, maternal education, migrant status, rainfall and calendar time. Results In 2004-6, under-5 and under-1 mortality ratios were 65 and 46 per 1,000 live-births, respectively. Median pedestrian and vehicular travel times to hospital were 193 min (inter-quartile range: 125-267) and 49 min (32-72); analogous values for vaccine clinics were 47 (25-73) and 26 min (13-40). Infant and under-5 mortality varied two-fold across geographic locations, ranging from 34.5 to 61.9 per 1000 child-years and 8.8 to 18.1 per 1000, respectively. However, distance to health facilities was not associated with mortality. Hazard Ratios (HR) were 0.99 (95% CI 0.95-1.04) per hour and 1.01 (95% CI 0.95-1.08) per half-hour of pedestrian and vehicular travel to hospital, respectively, and 1.00 (95% CI 0.99-1.04) and 0.97 (95% CI 0.92-1.05) per quarter-hour of pedestrian and vehicular travel to vaccine clinics in children Conclusions Significant spatial variations in mortality were observed across the area, but were not correlated with distance to health facilities. We conclude that given the present density of health facilities in Kenya, geographic access to curative services does not influence population-level mortality.
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- 2010
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36. Impact of 10-valent pneumococcal conjugate vaccine on invasive pneumococcal disease and nasopharyngeal carriage in Kenya
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Hammitt, Laura L., primary, Etyang, Anthony O., additional, Morpeth, Susan C., additional, Ojal, John, additional, Mutuku, Alex, additional, Mturi, Neema, additional, Moisi, Jennifer C., additional, Adetifa, Ifedayo M., additional, Karani, Angela, additional, Akech, Donald O., additional, Otiende, Mark, additional, Bwanaali, Tahreni, additional, Wafula, Jackline, additional, Mataza, Christine, additional, Mumbo, Edward, additional, Tabu, Collins, additional, Knoll, Maria Deloria, additional, Bauni, Evasius, additional, Marsh, Kevin, additional, Williams, Thomas N., additional, Kamau, Tatu, additional, Sharif, Shahnaaz K., additional, Levine, Orin S., additional, and Scott, J. Anthony G., additional
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- 2018
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37. The impact of 10-valent Pneumococcal Conjugate Vaccine on the incidence of radiologically-confirmed pneumonia and clinically-defined pneumonia in Kenyan children
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Silaba, Micah, primary, Ooko, Michael, additional, Bottomley, Christian, additional, Sande, Joyce, additional, Benamore, Rachel, additional, Park, Kate, additional, Ignas, James, additional, Maitland, Kathryn, additional, Mturi, Neema, additional, Makumi, Anne, additional, Otiende, Mark, additional, Kagwanja, Stanley, additional, Safari, Sylvester, additional, Ochola, Victor, additional, Bwanaali, Tahreni, additional, Bauni, Evasius, additional, Gleeson, Fergus, additional, Knoll, Maria Deloria, additional, Adetifa, Ifedayo, additional, Marsh, Kevin, additional, Williams, Thomas N, additional, Kamau, Tatu, additional, Sharif, Shahnaaz, additional, Levine, Orin S, additional, Hammitt, Laura L, additional, and Scott, J Anthony G, additional
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- 2018
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38. A growth reference for mid upper arm circumference for age among school age children and adolescents, and validation or mortality: growth curve construction and longitudinal cohortstudy
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Mramba, Lazarus, Ngari, Moses, Mwangome, Martha, Muchai, Lilian, Bauni, Evasius, Walker, A Sarah, Gibb, Diana, Fegan, Gregory, Berkley, James, Mramba, Lazarus, Ngari, Moses, Mwangome, Martha, Muchai, Lilian, Bauni, Evasius, Walker, A Sarah, Gibb, Diana, Fegan, Gregory, and Berkley, James
- Abstract
OBJECTIVES To construct growth curves for mid-upper-arm circumference (MUAC)-for-age z score for 5-19 year olds that accord with the World Health Organization growth standards, and to evaluate their discriminatory performance for subsequent mortality. DESIGN Growth curve construction and longitudinal cohort study. SETTING United States and international growth data, and cohorts in Kenya, Uganda, and Zimbabwe. PARTICIPANTS The Health Examination Survey (HES)/National Health and Nutrition Examination Survey (NHANES) US population datasets (age 5-25 years), which were used to construct the 2007 WHO growth reference for body mass index in this age group, were merged with an imputed dataset matching the distribution of the WHO 2006 growth standards age 2-6 years. Validation data were from 685 HIV infected children aged 5-17 years participating in the Antiretroviral Research for Watoto (ARROW) trial in Uganda and Zimbabwe; and 1741 children aged 5-13 years discharged from a rural Kenyan hospital (3.8% HIV infected). Both cohorts were followed-up for survival during one year. MAIN OUTCOME MEASURES Concordance with WHO 2006 growth standards at age 60 months and survival during one year according to MUAC-for-age and body mass index-for-age z scores.
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- 2017
39. Psychometric evaluation of the Major Depression Inventory among young people living in Coastal Kenya
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Otiende, Mark, primary, Abubakar, Amina, additional, Mochamah, George, additional, Walumbe, David, additional, Nyundo, Christopher, additional, Doyle, Aoife M, additional, Ross, David A, additional, Newton, Charles R, additional, and Bauni, Evasius, additional
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- 2017
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40. Trends in bednet ownership and usage, and the effect of bednets on malaria hospitalization in the Kilifi Health and Demographic Surveillance System (KHDSS): 2008–2015
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Kamau, Alice, primary, Nyaga, Victoria, additional, Bauni, Evasius, additional, Tsofa, Benjamin, additional, Noor, Abdisalan M., additional, Bejon, Philip, additional, Scott, J. Anthony G., additional, and Hammitt, Laura L., additional
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- 2017
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41. A growth reference for mid upper arm circumference for age among school age children and adolescents, and validation for mortality: growth curve construction and longitudinal cohort study
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Mramba, Lazarus, primary, Ngari, Moses, additional, Mwangome, Martha, additional, Muchai, Lilian, additional, Bauni, Evasius, additional, Walker, A Sarah, additional, Gibb, Diana M, additional, Fegan, Gregory, additional, and Berkley, James A, additional
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- 2017
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42. Linking health facility data from young adults aged 18-24 years to longitudinal demographic data: Experience from The Kilifi Health and Demographic Surveillance System
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Nyundo, Christopher, primary, Doyle, Aoife M., additional, Walumbe, David, additional, Otiende, Mark, additional, Kinuthia, Michael, additional, Amadi, David, additional, Jibendi, Boniface, additional, Mochamah, George, additional, Kihuha, Norbert, additional, Williams, Thomas N., additional, Ross, David A., additional, and Bauni, Evasius, additional
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- 2017
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43. Mortality after Inpatient Treatment for Severe Pneumonia in Children: a Cohort Study
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Ngari, Moses M., primary, Fegan, Greg, additional, Mwangome, Martha K., additional, Ngama, Mwanajuma J., additional, Mturi, Neema, additional, Scott, John Anthony Gerard, additional, Bauni, Evasius, additional, Nokes, David James, additional, and Berkley, James A., additional
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- 2017
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44. Clinical and Epidemiological Implications of 24‐Hour Ambulatory Blood Pressure Monitoring for the Diagnosis of Hypertension in Kenyan Adults: A Population‐Based Study
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Etyang, Anthony O., primary, Warne, Ben, additional, Kapesa, Sailoki, additional, Munge, Kenneth, additional, Bauni, Evasius, additional, Cruickshank, J. Kennedy, additional, Smeeth, Liam, additional, and Scott, J. Anthony G., additional
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- 2016
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45. Incidence, Remission and Mortality of Convulsive Epilepsy in Rural Northeast South Africa
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Wagner, Ryan G, Bottomley, Christian, Ngugi, Anthony K, Ibinda, Fredrick, Gómez-Olivé, F Xavier, Kahn, Kathleen, Tollman, Stephen, Newton, Charles R, SEEDS Writing Group, Wagner, Ryan, Twine, Rhian, Connor, Myles, Collinson, Mark, Masanja, Honratio, Mathew, Alexander, Kakooza, Angelina, Pariyo, George, Peterson, Stefan, Ndyo-mughenyi, Donald, Odhiambo, Rachael, Chengo, Eddie, Chabi, Martin, Bauni, Evasius, Kamuyu, Gathoni, Odera, Victor Mung'ala, Mageto, James O, Ae-Ngibise, Ken, Akpalu, Bright, Akpalu, Albert, Agbokey, Francis, Adjei, Patrick, Owusu-Agyei, Seth, Kleinschmidt, Immo, Doku, Victor CK, Odermatt, Peter, Neville, Brian, Sander, Josemir W, White, Steve, Nutman, Thomas, Wilkins, Patricia, and Noh, John
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Adult ,Male ,Rural Population ,medicine.medical_specialty ,Pediatrics ,Adolescent ,Science ,Population ,Context (language use) ,Disease ,South Africa ,Young Adult ,03 medical and health sciences ,Epilepsy ,0302 clinical medicine ,Risk Factors ,Cause of Death ,Environmental health ,Epidemiology ,Humans ,Medicine ,030212 general & internal medicine ,Mortality ,Child ,education ,education.field_of_study ,Multidisciplinary ,business.industry ,Incidence ,Incidence (epidemiology) ,Mortality rate ,1. No poverty ,Public Health, Global Health, Social Medicine and Epidemiology ,medicine.disease ,3. Good health ,Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi ,Cross-Sectional Studies ,Population Surveillance ,Life expectancy ,Female ,business ,030217 neurology & neurosurgery ,Research Article - Abstract
BackgroundEpilepsy is one of the most common neurological conditions globally, estimated to constitute 0.75% of the global burden of disease, with the majority of this burden found in low- and middle- income countries (LMICs). Few studies from LMICs, including much of sub-Saharan Africa, have described the incidence, remission or mortality rates due to epilepsy, which are needed to quantify the burden and inform policy. This study investigates the epidemiological parameters of convulsive epilepsy within a context of high HIV prevalence and an emerging burden of cardiovascular disease.MethodsA cross-sectional population survey of 82,818 individuals, in the Agincourt Health and Socio-demographic Surveillance Site (HDSS) in rural northeast South Africa was conducted in 2008, from which 296 people were identified with active convulsive epilepsy. A follow-up survey was conducted in 2012. Incidence and mortality rates were estimated, with duration and remission rates calculated using the DISMOD II software package.ResultsThe crude incidence for convulsive epilepsy was 17.4/100,000 per year (95%CI: 13.1-23.0). Remission was 4.6% and 3.9% per year for males and females, respectively. The standardized mortality ratio was 2.6 (95%CI: 1.7-3.5), with 33.3% of deaths directly related to epilepsy. Mortality was higher in men than women (adjusted rate ratio (aRR) 2.6 (95%CI: 1.2-5.4)), and was significantly associated with older ages (50+ years versus those 0-5 years old (RR 4.8 (95%CI: 0.6-36.4)).ConclusionsThe crude incidence was lower whilst mortality rates were similar to other African studies; however, this study found higher mortality amongst older males. Efforts aimed at further understanding what causes epilepsy in older people and developing interventions to reduce prolonged seizures are likely to reduce the overall burden of ACE in rural South Africa.
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- 2015
46. Cohort Profile: The Kilifi Vaccine Monitoring Study
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Adetifa, Ifedayo M.O., primary, Bwanaali, Tahreni, additional, Wafula, Jackline, additional, Mutuku, Alex, additional, Karia, Boniface, additional, Makumi, Anne, additional, Mwatsuma, Pauline, additional, Bauni, Evasius, additional, Hammitt, Laura L., additional, Nokes, D. James, additional, Maree, Ephantus, additional, Tabu, Collins, additional, Kamau, Tatu, additional, Mataza, Christine, additional, Williams, Thomas N., additional, and Scott, J. Anthony G., additional
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- 2016
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47. Under-five mortality rate variation between the Health and Demographic Surveillance System (HDSS) and Demographic and Health Survey (DHS) approaches
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Deribew, Amare, primary, Ojal, John, additional, Karia, Boniface, additional, Bauni, Evasius, additional, and Oteinde, Mark, additional
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- 2016
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48. Clinical features, proximate causes, and consequences of active convulsive epilepsy in Africa
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Kariuki, Symon M, Matuja, William, Akpalu, Albert, Kakooza-Mwesige, Angelina, Chabi, Martin, Wagner, Ryan G, Connor, Myles, Chengo, Eddie, Ngugi, Anthony K, Odhiambo, Rachael, Bottomley, Christian, White, Steven, Sander, Josemir W, Neville, Brian GR, Newton, Charles RJC, SEEDS writing group, Twine, Rhian, Gómez Olivé, F Xavier, Collinson, Mark, Kahn, Kathleen, Tollman, Stephen, Masanja, Honratio, Mathew, Alexander, Pariyo, George, Peterson, Stefan, Ndyomughenyi, Donald, Bauni, Evasius, Kamuyu, Gathoni, Odera, Victor Mung'ala, Mageto, James O, Ae-Ngibise, Ken, Akpalu, Bright, Agbokey, Francis, Adjei, Patrick, Owusu-Agyei, Seth, Kleinschmidt, Immo, Doku, Victor CK, Odermatt, Peter, Nutman, Thomas, Wilkins, Patricia, and Noh, John
- Abstract
PURPOSE: Epilepsy is common in sub-Saharan Africa (SSA), but the clinical features and consequences are poorly characterized. Most studies are hospital-based, and few studies have compared different ecological sites in SSA. We described active convulsive epilepsy (ACE) identified in cross-sectional community-based surveys in SSA, to understand the proximate causes, features, and consequences. METHODS: We performed a detailed clinical and neurophysiologic description of ACE cases identified from a community survey of 584,586 people using medical history, neurologic examination, and electroencephalography (EEG) data from five sites in Africa: South Africa; Tanzania; Uganda; Kenya; and Ghana. The cases were examined by clinicians to discover risk factors, clinical features, and consequences of epilepsy. We used logistic regression to determine the epilepsy factors associated with medical comorbidities. KEY FINDINGS: Half (51%) of the 2,170 people with ACE were children and 69% of seizures began in childhood. Focal features (EEG, seizure types, and neurologic deficits) were present in 58% of ACE cases, and these varied significantly with site. Status epilepticus occurred in 25% of people with ACE. Only 36% received antiepileptic drugs (phenobarbital was the most common drug [95%]), and the proportion varied significantly with the site. Proximate causes of ACE were adverse perinatal events (11%) for onset of seizures before 18 years; and acute encephalopathy (10%) and head injury prior to seizure onset (3%). Important comorbidities were malnutrition (15%), cognitive impairment (23%), and neurologic deficits (15%). The consequences of ACE were burns (16%), head injuries (postseizure) (1%), lack of education (43%), and being unmarried (67%) or unemployed (57%) in adults, all significantly more common than in those without epilepsy. SIGNIFICANCE: There were significant differences in the comorbidities across sites. Focal features are common in ACE, suggesting identifiable and preventable causes. Malnutrition and cognitive and neurologic deficits are common in people with ACE and should be integrated into the management of epilepsy in this region. Consequences of epilepsy such as burns, lack of education, poor marriage prospects, and unemployment need to be addressed.
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- 2013
49. Risk of Injection-Site Abscess among Infants Receiving a Preservative-Free, Two-Dose Vial Formulation of Pneumococcal Conjugate Vaccine in Kenya
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Burton, Deron C., primary, Bigogo, Godfrey M., additional, Audi, Allan O., additional, Williamson, John, additional, Munge, Kenneth, additional, Wafula, Jackline, additional, Ouma, Dominic, additional, Khagayi, Sammy, additional, Mugoya, Isaac, additional, Mburu, James, additional, Muema, Shadrack, additional, Bauni, Evasius, additional, Bwanaali, Tahreni, additional, Feikin, Daniel R., additional, Ochieng, Peter M., additional, Mogeni, Ondari D., additional, Otieno, George A., additional, Olack, Beatrice, additional, Kamau, Tatu, additional, Van Dyke, Melissa K., additional, Chen, Robert, additional, Farrington, Paddy, additional, Montgomery, Joel M., additional, Breiman, Robert F., additional, Scott, J. Anthony G., additional, and Laserson, Kayla F., additional
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- 2015
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50. Incidence and Risk Factors for Neonatal Tetanus in Admissions to Kilifi County Hospital, Kenya
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Ibinda, Fredrick, primary, Bauni, Evasius, additional, Kariuki, Symon M., additional, Fegan, Greg, additional, Lewa, Joy, additional, Mwikamba, Monica, additional, Boga, Mwanamvua, additional, Odhiambo, Rachael, additional, Mwagandi, Kiponda, additional, Seale, Anna C., additional, Berkley, James A., additional, Dorfman, Jeffrey R., additional, and Newton, Charles R. J. C., additional
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- 2015
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