Last data update: Apr 29, 2024. (Total: 46658 publications since 2009)
Records 1-9 (of 9 Records) |
Query Trace: Onyango Clayton O[original query] |
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First cases of SARS-CoV-2 infection and secondary transmission in Kisumu, Kenya
Tippett Barr Beth A , Herman-Roloff Amy , Mburu Margaret , Murnane Pamela M , Sang Norton , Bukusi Elizabeth , Oele Elizabeth , Odhiambo Albert , Lewis-Kulzer Jayne , Onyango Clayton O , Hunsperger Elizabeth , Odhiambo Francesca , Joseph Rachel H , Munyua Peninah , Othieno Kephas , Mulwa Edwin , Akelo Victor , Muok Erick , Bulterys Marc , Nzioka Charles , Cohen Craig R . PLoS Glob Public Health 2022 2 (9) e0000951 We investigated the first 152 laboratory-confirmed SARS-CoV-2 cases (125 primary and 27 secondary) and their 248 close contacts in Kisumu County, Kenya. Conducted June 10–October 8, 2020, this study included interviews and sample collection at enrolment and 14–21 days later. Median age was 35 years (IQR 28–44); 69.0% reported COVID-19 related symptoms, most commonly cough (60.0%), headache (55.2%), fever (53.3%) and loss of taste or smell (43.8%). One in five were hospitalized, 34.4% >25 years of age had at least one comorbidity, and all deaths had comorbidities. Adults ≥25 years with a comorbidity were 3.15 (95% CI 1.37–7.26) times more likely to have been hospitalized or died than participants without a comorbidity. Infectious comorbidities included HIV, tuberculosis, and malaria, but no current cases of influenza, respiratory syncytial virus, dengue fever, leptospirosis or chikungunya were identified. Thirteen (10.4%) of the 125 primary infections transmitted COVID-19 to 27 close contacts, 158 (63.7%) of whom resided or worked within the same household. Thirty-one percent (4 of 13) of those who transmitted COVID-19 to secondary cases were health care workers; no known secondary transmissions occurred between health care workers. This rapid assessment early in the course of the COVID-19 pandemic identified some context-specific characteristics which conflicted with the national line-listing of cases, and which have been substantiated in the year since. These included over two-thirds of cases reporting the development of symptoms during the two weeks after diagnosis, compared to the 7% of cases reported nationally; over half of cases reporting headaches, and nearly half of all cases reporting loss of taste and smell, none of which were reported at the time by the World Health Organization to be common symptoms. This study highlights the importance of rapid in-depth assessments of outbreaks in understanding the local epidemiology and response measures required. |
The epidemiology and estimated etiology of pathogens detected from the upper respiratory tract of adults with severe acute respiratory infections in multiple countries, 2014-2015.
Milucky J , Pondo T , Gregory CJ , Iuliano D , Chaves SS , McCracken J , Mansour A , Zhang Y , Aleem MA , Wolff B , Whitaker B , Whistler T , Onyango C , Lopez MR , Liu N , Rahman MZ , Shang N , Winchell J , Chittaganpitch M , Fields B , Maldonado H , Xie Z , Lindstrom S , Sturm-Ramirez K , Montgomery J , Wu KH , Van Beneden CA . PLoS One 2020 15 (10) e0240309 INTRODUCTION: Etiology studies of severe acute respiratory infections (SARI) in adults are limited. We studied potential etiologies of SARI among adults in six countries using multi-pathogen diagnostics. METHODS: We enrolled both adults with SARI (acute respiratory illness onset with fever and cough requiring hospitalization) and asymptomatic adults (adults hospitalized with non-infectious illnesses, non-household members accompanying SARI patients, adults enrolled from outpatient departments, and community members) in each country. Demographics, clinical data, and nasopharyngeal and oropharyngeal specimens were collected from both SARI patients and asymptomatic adults. Specimens were tested for presence of 29 pathogens utilizing the Taqman® Array Card platform. We applied a non-parametric Bayesian regression extension of a partially latent class model approach to estimate proportions of SARI caused by specific pathogens. RESULTS: We enrolled 2,388 SARI patients and 1,135 asymptomatic adults from October 2013 through October 2015. We detected ≥1 pathogen in 76% of SARI patients and 67% of asymptomatic adults. Haemophilus influenzae and Streptococcus pneumoniae were most commonly detected (≥23% of SARI patients and asymptomatic adults). Through modeling, etiology was attributed to a pathogen in most SARI patients (range among countries: 57.3-93.2%); pathogens commonly attributed to SARI etiology included influenza A (14.4-54.4%), influenza B (1.9-19.1%), rhino/enterovirus (1.8-42.6%), and RSV (3.6-14.6%). CONCLUSIONS: Use of multi-pathogen diagnostics and modeling enabled attribution of etiology in most adult SARI patients, despite frequent detection of multiple pathogens in the upper respiratory tract. Seasonal flu vaccination and development of RSV vaccine would likely reduce the burden of SARI in these populations. |
Rotavirus group A genotype circulation patterns across Kenya before and after nationwide vaccine introduction, 2010-2018.
Mwanga MJ , Owor BE , Ochieng JB , Ngama MH , Ogwel B , Onyango C , Juma J , Njeru R , Gicheru E , Otieno GP , Khagayi S , Agoti CN , Bigogo GM , Omore R , Addo OY , Mapaseka S , Tate JE , Parashar UD , Hunsperger E , Verani JR , Breiman RF , Nokes DJ . BMC Infect Dis 2020 20 (1) 504 BACKGROUND: Kenya introduced the monovalent G1P [8] Rotarix(R) vaccine into the infant immunization schedule in July 2014. We examined trends in rotavirus group A (RVA) genotype distribution pre- (January 2010-June 2014) and post- (July 2014-December 2018) RVA vaccine introduction. METHODS: Stool samples were collected from children aged < 13 years from four surveillance sites across Kenya: Kilifi County Hospital, Tabitha Clinic Nairobi, Lwak Mission Hospital, and Siaya County Referral Hospital (children aged < 5 years only). Samples were screened for RVA using enzyme linked immunosorbent assay (ELISA) and VP7 and VP4 genes sequenced to infer genotypes. RESULTS: We genotyped 614 samples in pre-vaccine and 261 in post-vaccine introduction periods. During the pre-vaccine introduction period, the most frequent RVA genotypes were G1P [8] (45.8%), G8P [4] (15.8%), G9P [8] (13.2%), G2P [4] (7.0%) and G3P [6] (3.1%). In the post-vaccine introduction period, the most frequent genotypes were G1P [8] (52.1%), G2P [4] (20.7%) and G3P [8] (16.1%). Predominant genotypes varied by year and site in both pre and post-vaccine periods. Temporal genotype patterns showed an increase in prevalence of vaccine heterotypic genotypes, such as the commonly DS-1-like G2P [4] (7.0 to 20.7%, P < .001) and G3P [8] (1.3 to 16.1%, P < .001) genotypes in the post-vaccine introduction period. Additionally, we observed a decline in prevalence of genotypes G8P [4] (15.8 to 0.4%, P < .001) and G9P [8] (13.2 to 5.4%, P < .001) in the post-vaccine introduction period. Phylogenetic analysis of genotype G1P [8], revealed circulation of strains of lineages G1-I, G1-II and P [8]-1, P [8]-III and P [8]-IV. Considerable genetic diversity was observed between the pre and post-vaccine strains, evidenced by distinct clusters. CONCLUSION: Genotype prevalence varied from before to after vaccine introduction. Such observations emphasize the need for long-term surveillance to monitor vaccine impact. These changes may represent natural secular variation or possible immuno-epidemiological changes arising from the introduction of the vaccine. Full genome sequencing could provide insights into post-vaccine evolutionary pressures and antigenic diversity. |
Identification and characterization of influenza A viruses in selected domestic animals in Kenya, 2010-2012.
Munyua P , Onyango C , Mwasi L , Waiboci LW , Arunga G , Fields B , Mott JA , Cardona CJ , Kitala P , Nyaga PN , Njenga MK . PLoS One 2018 13 (2) e0192721 BACKGROUND: Influenza A virus subtypes in non-human hosts have not been characterized in Kenya. We carried out influenza surveillance in selected domestic animals and compared the virus isolates with isolates obtained in humans during the same period. METHODS: We collected nasal swabs from pigs, dogs and cats; oropharyngeal and cloacal swabs from poultry; and blood samples from all animals between 2010 and 2012. A standardized questionnaire was administered to farmers and traders. Swabs were tested for influenza A by rtRT-PCR, virus isolation and subtyping was done on all positive swabs. All sera were screened for influenza A antibodies by ELISA, and positives were evaluated by hemagglutination inhibition (HI). Full genome sequencing was done on four selected pig virus isolates. RESULTS: Among 3,798 sera tested by ELISA, influenza A seroprevalence was highest in pigs (15.9%; 172/1084), 1.2% (3/258) in ducks, 1.4% (1/72) in cats 0.6% (3/467) in dogs, 0.1% (2/1894) in chicken and 0% in geese and turkeys. HI testing of ELISA-positive pig sera showed that 71.5% had positive titers to A/California/04/2009(H1N1). Among 6,289 swabs tested by rRT-PCR, influenza A prevalence was highest in ducks [1.2%; 5/423] and 0% in cats and turkeys. Eight virus isolates were obtained from pig nasal swabs collected in 2011 and were determined to be A(H1N1)pdm09 on subtyping. On phylogenetic analysis, four hemagglutinin segments from pig isolates clustered together and were closely associated with human influenza viruses that circulated in Kenya in 2011. CONCLUSION: Influenza A(H1N1)pdm09 isolated in pigs was genetically similar to contemporary human pandemic influenza virus isolates. This suggest that the virus was likely transmitted from humans to pigs, became established and circulated in Kenyan pig populations during the study period. Minimal influenza A prevalence was observed in the other animals studied. |
Evaluation of TaqMan Array Card (TAC) for the Detection of Central Nervous System Infections in Kenya.
Onyango CO , Loparev V , Lidechi S , Bhullar V , Schmid DS , Radford K , Lo MK , Rota P , Johnson BW , Munoz J , Oneko M , Burton D , Black CM , Neatherlin J , Montgomery JM , Fields B . J Clin Microbiol 2017 55 (7) 2035-2044 Infections of the central nervous system (CNS) are often acute with significant morbidity and mortality. Routine diagnosis of such infections is limited in developing countries and requires modern equipment in advanced laboratories that may be unavailable to a number of patients in sub-Saharan Africa. We developed a TaqMan Array Card (TAC) that detects multiple pathogens simultaneously from cerebrospinal fluid (CSF). The 21-pathogen TAC assays include two parasites (Balamuthia mandrillaris and Acanthamoeba), six bacterial pathogens (Streptococcus pneumoniae, Haemophilus influenzae, Neisseria meningitidis, Mycoplasma pneumoniae, Mycobacterium tuberculosis, and Bartonella) and 13 viruses (parechovirus, dengue, nipah, varicella zoster, mumps, measles, lyssa, herpes simplex virus 1 and 2, Epstein Barr virus, enterovirus, cytomegalovirus and chikungunya). The card also includes human RNAse P as a nucleic acid extraction control and an internal manufacturer control (glyceraldehyde 3-phosphate dehydrogenase (GAPDH)). This CNS-TAC can test up to eight samples for all 21 agents within 2.5 hours following nucleic acid extraction. The assay was validated for linearity, limit of detection, sensitivity and specificity by either using live viruses (dengue, mumps and measles) or nucleic acid material (nipah and chikungunya). Of the 120 samples tested by individual real-time PCR (IRTP), 35 were positive for eight different targets while CNS-TAC detected 37 positive samples across nine different targets. The TAC assays showed 85.6% sensitivity and 96.7% specificity across the assays. This assay may be useful for outbreak investigation and surveillance of suspected neurological disease. |
Microbiome sharing between children, livestock and household surfaces in western Kenya.
Mosites E , Sammons M , Otiang E , Eng A , Noecker C , Manor O , Hilton S , Thumbi SM , Onyango C , Garland-Lewis G , Call DR , Njenga MK , Wasserheit JN , Zambriski JA , Walson JL , Palmer GH , Montgomery J , Borenstein E , Omore R , Rabinowitz PM . PLoS One 2017 12 (2) e0171017 The gut microbiome community structure and development are associated with several health outcomes in young children. To determine the household influences of gut microbiome structure, we assessed microbial sharing within households in western Kenya by sequencing 16S rRNA libraries of fecal samples from children and cattle, cloacal swabs from chickens, and swabs of household surfaces. Among the 156 households studied, children within the same household significantly shared their gut microbiome with each other, although we did not find significant sharing of gut microbiome across host species or household surfaces. Higher gut microbiome diversity among children was associated with lower wealth status and involvement in livestock feeding chores. Although more research is necessary to identify further drivers of microbiota development, these results suggest that the household should be considered as a unit. Livestock activities, health and microbiome perturbations among an individual child may have implications for other children in the household. |
Use of quantitative molecular diagnostic methods to identify causes of diarrhoea in children: a reanalysis of the GEMS case-control study.
Liu J , Platts-Mills JA , Juma J , Kabir F , Nkeze J , Okoi C , Operario DJ , Uddin J , Ahmed S , Alonso PL , Antonio M , Becker SM , Blackwelder WC , Breiman RF , Faruque AS , Fields B , Gratz J , Haque R , Hossain A , Hossain MJ , Jarju S , Qamar F , Iqbal NT , Kwambana B , Mandomando I , McMurry TL , Ochieng C , Ochieng JB , Ochieng M , Onyango C , Panchalingam S , Kalam A , Aziz F , Qureshi S , Ramamurthy T , Roberts JH , Saha D , Sow SO , Stroup SE , Sur D , Tamboura B , Taniuchi M , Tennant SM , Toema D , Wu Y , Zaidi A , Nataro JP , Kotloff KL , Levine MM , Houpt ER . Lancet 2016 388 (10051) 1291-301 BACKGROUND: Diarrhoea is the second leading cause of mortality in children worldwide, but establishing the cause can be complicated by diverse diagnostic approaches and varying test characteristics. We used quantitative molecular diagnostic methods to reassess causes of diarrhoea in the Global Enteric Multicenter Study (GEMS). METHODS: GEMS was a study of moderate to severe diarrhoea in children younger than 5 years in Africa and Asia. We used quantitative real-time PCR (qPCR) to test for 32 enteropathogens in stool samples from cases and matched asymptomatic controls from GEMS, and compared pathogen-specific attributable incidences with those found with the original GEMS microbiological methods, including culture, EIA, and reverse-transcriptase PCR. We calculated revised pathogen-specific burdens of disease and assessed causes in individual children. FINDINGS: We analysed 5304 sample pairs. For most pathogens, incidence was greater with qPCR than with the original methods, particularly for adenovirus 40/41 (around five times), Shigella spp or enteroinvasive Escherichia coli (EIEC) and Campylobactor jejuni o C coli (around two times), and heat-stable enterotoxin-producing E coli ([ST-ETEC] around 1.5 times). The six most attributable pathogens became, in descending order, Shigella spp, rotavirus, adenovirus 40/41, ST-ETEC, Cryptosporidium spp, and Campylobacter spp. Pathogen-attributable diarrhoeal burden was 89.3% (95% CI 83.2-96.0) at the population level, compared with 51.5% (48.0-55.0) in the original GEMS analysis. The top six pathogens accounted for 77.8% (74.6-80.9) of all attributable diarrhoea. With use of model-derived quantitative cutoffs to assess individual diarrhoeal cases, 2254 (42.5%) of 5304 cases had one diarrhoea-associated pathogen detected and 2063 (38.9%) had two or more, with Shigella spp and rotavirus being the pathogens most strongly associated with diarrhoea in children with mixed infections. INTERPRETATION: A quantitative molecular diagnostic approach improved population-level and case-level characterisation of the causes of diarrhoea and indicated a high burden of disease associated with six pathogens, for which targeted treatment should be prioritised. FUNDING: Bill & Melinda Gates Foundation. |
Plasmodium Parasitemia Associated With Increased Survival in Ebola Virus-Infected Patients.
Rosenke K , Adjemian J , Munster VJ , Marzi A , Falzarano D , Onyango CO , Ochieng M , Juma B , Fischer RJ , Prescott JB , Safronetz D , Omballa V , Owuor C , Hoenen T , Groseth A , Martellaro C , van Doremalen N , Zemtsova G , Self J , Bushmaker T , McNally K , Rowe T , Emery SL , Feldmann F , Williamson BN , Best SM , Nyenswah TG , Grolla A , Strong JE , Kobinger G , Bolay FK , Zoon KC , Stassijns J , Giuliani R , de Smet M , Nichol ST , Fields B , Sprecher A , Massaquoi M , Feldmann H , de Wit E . Clin Infect Dis 2016 63 (8) 1026-33 BACKGROUND: The ongoing Ebola outbreak in West Africa has resulted in 28 646 suspected, probable, and confirmed Ebola virus infections. Nevertheless, malaria remains a large public health burden in the region affected by the outbreak. A joint Centers for Disease Control and Prevention/National Institutes of Health diagnostic laboratory was established in Monrovia, Liberia, in August 2014, to provide laboratory diagnostics for Ebola virus. METHODS: All blood samples from suspected Ebola virus-infected patients admitted to the Medecins Sans Frontieres ELWA3 Ebola treatment unit in Monrovia were tested by quantitative real-time polymerase chain reaction for the presence of Ebola virus and Plasmodium species RNA. Clinical outcome in laboratory-confirmed Ebola virus-infected patients was analyzed as a function of age, sex, Ebola viremia, and Plasmodium species parasitemia. RESULTS: The case fatality rate of 1182 patients with laboratory-confirmed Ebola virus infections was 52%. The probability of surviving decreased with increasing age and decreased with increasing Ebola viral load. Ebola virus-infected patients were 20% more likely to survive when Plasmodium species parasitemia was detected, even after controlling for Ebola viral load and age; those with the highest levels of parasitemia had a survival rate of 83%. This effect was independent of treatment with antimalarials, as this was provided to all patients. Moreover, treatment with antimalarials did not affect survival in the Ebola virus mouse model. CONCLUSIONS: Plasmodium species parasitemia is associated with an increase in the probability of surviving Ebola virus infection. More research is needed to understand the molecular mechanism underlying this remarkable phenomenon and translate it into treatment options for Ebola virus infection. |
Development of a TaqMan Array Card for Acute Febrile Illness Outbreak Investigation and Surveillance of Emerging Pathogens including Ebola Virus.
Liu J , Ochieng C , Wiersma S , Stroher U , Towner JS , Whitmer S , Nichol ST , Moore CC , Kersh GJ , Kato C , Sexton C , Petersen J , Massung R , Hercik C , Crump JA , Kibiki G , Maro A , Mujaga B , Gratz J , Jacob ST , Banura P , Scheld WM , Juma B , Onyango CO , Montgomery JM , Houpt E , Fields B . J Clin Microbiol 2015 54 (1) 49-58 Acute febrile illness (AFI) is associated with substantial morbidity and mortality worldwide yet an etiologic agent is often not identified. Convalescent serology is impractical, blood culture is slow, and many pathogens are fastidious or impossible to cultivate. We developed a real-time PCR based TaqMan Array Card (TAC) that can test six to eight samples within 2.5 hours from sample to results and simultaneously detect 26 AFI associated organisms, including 15 viruses (Chikungunya, Crimean-Congo hemorrhagic fever virus, Dengue, Ebola virus, Bundibugyo virus, Sudan virus, Hantaviruses (HTN and SEO), Hepatitis E, Marburg, Nipah virus, O'nyong-nyong virus, Rift Valley fever virus, West Nile virus, Yellow fever virus), eight bacteria (Bartonella spp., Brucella spp., Coxiella burnetii, Leptospira spp., Rickettsia spp., Salmonella enterica and Salmonella enterica serovar Typhi, Yersinia pestis), and three protozoa (Leishmania spp., Plasmodium spp., Trypanosoma brucei). Two extrinsic controls (Phocine Herpesvirus 1 and bacteriophage MS2) were included to assure extraction and amplification efficiency. Analytical validation was performed on spiked specimens for linearity, intra-assay precision, inter-assay precision, limit of detection, and specificity. The performance of the card on clinical specimens was evaluated with 1,050 blood samples by comparison to the individual real-time PCR assays, and TAC exhibited overall 88% (278/315, 95% confidence interval 84% to 92%) sensitivity and 99% (5261/5326, 98% to 99%) specificity. This TaqMan Array Card can be used in field settings as a rapid screen for outbreak investigation or pathogen surveillance, including Ebola virus. |
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