#Serological #Evidence of #Yersiniosis, #TBE, #WNV, #Hepatitis E, #CCHF, Lyme #Borreliosis, and #Brucellosis in Febrile Patients Presenting at Diverse Hospitals in #Kenya (Vector Borne Zoo Dis., abstract)

[Source: Vector-Borne and Zoonotic Diseases, full page: (LINK). Abstract, edited.]

Serological Evidence of Yersiniosis, Tick-Borne Encephalitis, West Nile, Hepatitis E, Crimean-Congo Hemorrhagic Fever, Lyme Borreliosis, and Brucellosis in Febrile Patients Presenting at Diverse Hospitals in Kenya

Josphat Nyataya, Moureen Maraka, Allan Lemtudo, Clement Masakhwe, Beth Mutai, Kariuki Njaanake, Benson B. Estambale, Nancy Nyakoe, Joram Siangla, and John Njenga Waitumbi

Published Online: 13 Jan 2020 / DOI: https://doi.org/10.1089/vbz.2019.2484

 

Abstract

Data on pathogen prevalence is crucial for informing exposure and disease risk. We evaluated serological evidence of tick-borne encephalitis (TBE), West Nile (WN), Hepatitis E virus (HEV), Crimean-Congo Hemorrhagic Fever (CCHF), Yersiniosis, Lyme Disease (LD), and brucellosis in 1033 patients presenting with acute febrile illness at 9 health care facilities from diverse ecological zones of Kenya: arid and semiarid (Garissa District Hospital, Lodwar District Hospital, Marigat District Hospital, Gilgil District Hospital), Lake Victoria basin (Kisumu District Hospital, Alupe District Hospital, Kombewa Sub-County Hospital), Kisii highland (Kisii District Hospital), and coastal (Malindi District Hospital). Epidemiological information of the patients such as geography, age, gender, and keeping animals were analyzed as potential risk factors. Of the 1033 samples, 619 (59.9%) were seropositive to at least one pathogen by IgM (current exposure), IgG/IgM (recent exposure), and IgG (past exposure). Collective seroprevalence for current, recent, and past to the pathogens was 9.4%, 5.1%, and 21.1% for LD; 3.6%, 0.5%, and 12.4% for WN; 0.9%, 0.5%, and 16.9% for HEV; 5.8%, 1.3%, and 3.9% for brucellosis; 5.7%, 0.2%, and 2.3% for yersiniosis; 1.7%, 0%, and 6.2% for TBE; and 0.4%, 0%, and 1.9% for CCHF. Brucellosis risk was higher in patients recruited at Garissa District Hospital (odds ratio [OR] = 3.41), HEV (OR = 2.45) and CCHF (OR = 5.46) in Lodwar District Hospital, LD in Alupe District Hospital (OR = 5.73), Kombewa Sub-district hospital (OR = 8.17), and Malindi District hospital (OR = 3.3). Exposure to LD was highest in the younger age group, whereas yersiniosis did not vary with age. Age was a significant risk for WN, brucellosis, CCHF, TBE, and HEV and in those aged >14 years there was an increased risk to WN (OR = 2.30, p < 0.0001), brucellosis (OR = 1.84, p = 0.005), CCHF (OR = 4.35, p = 0.001), TBE (OR = 2.78, p < 0.0001), and HEV (OR = 1.94, p = 0.0001). We conclude that LD is pervasive and constitutes a significant health burden to the study population, whereas yersiniosis and CCHF are not significant threats. Going forward, community-based studies will be needed to capture the true seroprevalence rates and the associated risk factors.

Keywords: Arbovirus; WNV; CCHF; Borreliosis; TBE; Brucellosis; Seroprevalence; Kenya.

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#Antibiotic #Resistance of #Escherichia coli from #Humans and Black #Rhinoceroses in #Kenya (Ecohealth, abstract)

[Source: US National Library of Medicine, full page: (LINK). Abstract, edited.]

Ecohealth. 2019 Dec 7. doi: 10.1007/s10393-019-01461-z. [Epub ahead of print]

Antibiotic Resistance of Escherichia coli from Humans and Black Rhinoceroses in Kenya.

Kipkorir KC1, Ang’ienda PO1, Onyango DM1, Onyango PO2.

Author information: 1 Department of Zoology, Maseno University, Private Bag, Maseno, Kenya. 2 Department of Zoology, Maseno University, Private Bag, Maseno, Kenya. patonyango@gmail.com.

 

Abstract

Upsurge of antibiotic resistance in wildlife poses unprecedented threat to wildlife conservation. Surveillance of antibiotic resistance at the human-wildlife interface is therefore needed. We evaluated differences in antibiotic resistance of Escherichia coli isolates from human and the endangered black rhinoceros in Lambwe Valley, Kenya. We used standard microbiological techniques to carry out susceptibility assays using eight antibiotics of clinical and veterinary importance. Standard PCR method was used to characterize antibiotic resistance genes. There was no difference in resistance between E. coli isolates from human and those from rhinoceros (U = 25, p = 0.462). However, higher resistance in isolates from humans was noted for cotrimoxazole (p = 0.000, OR = 0.101), ceftriaxone (p = 0.005, OR = 0.113) and amoxicillin/clavulanic acid (p = 0.017, OR = 0.258), whereas isolates from rhinoceros showed higher gentamicin resistance (p = 0.001, OR = 10.154). Multi-drug resistance phenotype was 69.0% in humans and 43.3% in rhinoceros. Isolates from both species contained blaTEM, tetA, tetB, dfrA1 and sul1 genes. Resistance profiles in the two species suggest potential for cross-transfer of resistance genes or exposure to comparable selective pressure and call for a multi-sectorial action plan on surveillance of antibiotic resistance at the human-wildlife interface. Genome-wide studies are needed to explicate the direction of transfer of genes that confer antibiotic resistance at the human-wildlife interface.

KEYWORDS: Antibacterial resistance; Black rhinoceros; Escherichia coli; Kenya; Multi-drug resistance; Zoonotic

PMID: 31811599 DOI: 10.1007/s10393-019-01461-z

Keywords: Antibiotics; Drugs Resistance; E. Coli; Wildlife; Human; Kenya.

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#Serological evidence of #MERS-CoV and #HKU8-related #Coronavirus #coinfection in #Kenyan #camels (Emerg Microbes Infect., abstract)

[Source: US National Library of Medicine, full page: (LINK). Abstract, edited.]

Emerg Microbes Infect. 2019;8(1):1528-1534. doi: 10.1080/22221751.2019.1679610.

Serological evidence of MERS-CoV and HKU8-related CoV co-infection in Kenyan camels.

Zhang W1, Zheng XS1,2, Agwanda B3, Ommeh S4, Zhao K1,2, Lichoti J5, Wang N1, Chen J1,2, Li B1, Yang XL1, Mani S6, Ngeiywa KJ5,7, Zhu Y1, Hu B1, Onyuok SO1, Yan B1, Anderson DE6, Wang LF6, Zhou P1, Shi ZL1.

Author information: 1 CAS Key Laboratory of Special Pathogens, Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences , Wuhan , People’s Republic of China. 2 University of Chinese Academy of Sciences , Beijing , People’s Republic of China. 3 Department of Zoology, National Museums of Kenya , Nairobi , Kenya. 4 Institute for Biotechnology Research, Jomo Kenyatta University of Agriculture and Technology , Nairobi , Kenya. 5 Directorate of Veterinary Services, State Department of Livestock, Ministry of Agriculture , Livestock and Fisheries , Kenya. 6 Programme in Emerging Infectious Diseases Duke-NUS Medical School , Singapore , Singapore. 7 Kenya Camel Association , Nairobi , Kenya.

 

Abstract

Dromedary camels are important reservoir hosts of various coronaviruses, including Middle East respiratory syndrome coronavirus (MERS-CoV) that cause human infections. CoV genomes regularly undergo recombination during infection as observed in bat SARS-related CoVs. Here we report for the first time that only a small proportion of MERS-CoV receptor-binding domain positive (RBD) of spike protein positive camel sera in Kenya were also seropositive to MERS-CoV nucleocapsid (NP). In contrast, many of them contain antibodies against bat HKU8-related (HKU8r)-CoVs. Among 584 camel samples that were positive against MERS-CoV RBD, we found only 0.48 (8.22%) samples were also positive for NP. Furthermore, we found bat HKU8r-CoV NP antibody in 73 (12.5%) of the MERS-CoV RBD positive and NP negative samples, yet found only 3 (0.43%) of the HKU8r-CoV S1 antibody in the same samples. These findings may indicate co-infection with MERS-CoV and a HKU8r-CoV in camels. It may also raise the possibility of the circulation of a recombinant coronavirus virus with the spike of MERS-CoV and the NP of a HKU8r-CoV in Kenya. We failed to find molecular evidence of an HKU8r-CoV or a putative recombinant virus. Our findings should alert other investigators to look for molecular evidence of HKU8r-CoV or recombinants.

KEYWORDS: HKU8; MERS; bat; camel; coronavirus

PMID: 31645223 DOI: 10.1080/22221751.2019.1679610

Keywords: MERS-CoV; Coronavirus; Bats; Camels; Recombination; Kenya.

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#Genetic characterization and #pathogenesis of the first #H9N2 low pathogenic #avian #influenza viruses isolated from #chickens in #Kenyan live bird markets (Infect Genet Evol., abstract)

[Source: US National Library of Medicine, full page: (LINK). Abstract, edited.]

Infect Genet Evol. 2019 Oct 18:104074. doi: 10.1016/j.meegid.2019.104074. [Epub ahead of print]

Genetic characterization and pathogenesis of the first H9N2 low pathogenic avian influenza viruses isolated from chickens in Kenyan live bird markets.

Kariithi HM1, Welch CN2, Ferreira HL3, Pusch EA2, Ateya LO4, Binepal YS5, Apopo AA6, Dulu TD6, Afonso CL7, Suarez DL8.

Author information: 1 Biotechnology Research Institute, Kenya Agricultural and Livestock Research Organization, P.O Box 57811, 00200, Kaptagat Road, Loresho, Nairobi, Kenya; Southeast Poultry Research Laboratory, US National Poultry Research Center, Agricultural Research Service, U.S. Department of Agriculture, 934 College Station Road, Athens, GA 30605, USA. Electronic address: henry.kariithi@kalro.org. 2 Southeast Poultry Research Laboratory, US National Poultry Research Center, Agricultural Research Service, U.S. Department of Agriculture, 934 College Station Road, Athens, GA 30605, USA. 3 Southeast Poultry Research Laboratory, US National Poultry Research Center, Agricultural Research Service, U.S. Department of Agriculture, 934 College Station Road, Athens, GA 30605, USA; University of Sao Paulo, ZMV- FZEA, Pirassununga 13635900, Brazil. Electronic address: hlage@usp.br. 4 Biotechnology Research Institute, Kenya Agricultural and Livestock Research Organization, P.O Box 57811, 00200, Kaptagat Road, Loresho, Nairobi, Kenya. Electronic address: leonard.ateya@kalro.org. 5 Biotechnology Research Institute, Kenya Agricultural and Livestock Research Organization, P.O Box 57811, 00200, Kaptagat Road, Loresho, Nairobi, Kenya. Electronic address: yatinder.binepal@kalro.org. 6 Directorate of Veterinary Services, State Department of Livestock, Ministry of Agriculture, Livestock, Fisheries and Irrigation, Private Bag-00625, Nairobi, Kenya. 7 Southeast Poultry Research Laboratory, US National Poultry Research Center, Agricultural Research Service, U.S. Department of Agriculture, 934 College Station Road, Athens, GA 30605, USA. Electronic address: cafonso@uga.edu. 8 Southeast Poultry Research Laboratory, US National Poultry Research Center, Agricultural Research Service, U.S. Department of Agriculture, 934 College Station Road, Athens, GA 30605, USA. Electronic address: david.suarez@usda.gov.

 

Abstract

Poultry production plays an important role in the economy and livelihoods of rural households in Kenya. As part of a surveillance program, avian influenza virus (AIV)-specific real-time RT-PCR (RRT-PCR) was used to screen 282 oropharyngeal swabs collected from chickens at six live bird markets (LBMs) and 33 backyard poultry farms in Kenya and 8 positive samples were detected. Virus was isolated in eggs from five samples, sequenced, and identified as H9N2 low pathogenic AIV (LPAIV) G1 lineage, with highest nucleotide sequence identity (98.6-99.9%) to a 2017 Ugandan H9N2 isolate. The H9N2 contained molecular markers for mammalian receptor specificity, implying their zoonotic potential. Virus pathogenesis and transmissibility was assessed by inoculating low and medium virus doses of a representative Kenyan H9N2 LPAIV isolate into experimental chickens and exposing them to naïve uninfected chickens at 2 -days post inoculation (dpi). Virus shedding was determined at 2/4/7 dpi and 2/5 days post placement (dpp), and seroconversion determined at 14 dpi/12 dpp. None of the directly-inoculated or contact birds exhibited any mortality or clinical disease signs. All directly-inoculated birds in the low dose group shed virus during the experiment, while only one contact bird shed virus at 2 dpp. Only two directly-inoculated birds that shed high virus titers seroconverted in that group. All birds in the medium dose group shed virus at 4/7 dpi and at 5 dpp, and they all seroconverted at 12/14 dpp. This is the first reported detection of H9N2 LPAIV from Kenya and it was shown to be infectious and transmissible in chickens by direct contact and represents a new disease threat to poultry and potentially to people.

Copyright © 2018. Published by Elsevier B.V.

KEYWORDS: Backyard poultry farms; G1 lineage; H9N2 LPAIV; Live-bird markets; Oropharyngeal; Zoonotic

PMID: 31634645 DOI: 10.1016/j.meegid.2019.104074

Keywords: Avian Influenza; H9N2; Poultry; Kenya.

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#Force of #infection of #MERS in dromedary #camels in #Kenya (Epidemiol Infect., abstract)

[Source: US National Library of Medicine, full page: (LINK). Abstract, edited.]

Epidemiol Infect. 2019 Sep 24;147:e275. doi: 10.1017/S0950268819001663.

Force of infection of Middle East respiratory syndrome in dromedary camels in Kenya.

Gardner EG1, Kiambi S2, Sitawa R3, Kelton D1, Kimutai J2, Poljak Z1, Tadesse Z2, Von Dobschuetz S4, Wiersma L4, Greer AL1.

Author information: 1 University of Guelph, Guelph, Ontario, Canada. 2 Food and Agriculture Organization of the United Nations, Nairobi, Kenya. 3 Directorate of Veterinary Services, Nairobi, Kenya. 4 Food and Agriculture Organization of the United Nations, Nairobi, Italy.

 

Abstract

Middle East respiratory syndrome coronavirus (MERS-CoV) is a zoonotic disease transmitted from dromedary camels to people, which can result in outbreaks with human-to-human transmission. Because it is a subclinical infection in camels, epidemiological measures other than prevalence are challenging to assess. This study estimated the force of infection (FOI) of MERS-CoV in camel populations from age-stratified serological data. A cross-sectional study of MERS-CoV was conducted in Kenya from July 2016 to July 2017. Seroprevalence was stratified into four age groups: <1, 1-2, 2-3 and >3 years old. Age-independent and age-dependent linear and quadratic generalised linear models were used to estimate FOI in pastoral and ranching camel herds. Models were compared based on computed AIC values. Among pastoral herds, the age-dependent quadratic FOI was the best fit model, while the age-independent FOI was the best fit for the ranching herd data. FOI provides an indirect estimate of infection risk, which is especially valuable where direct estimates of incidence and other measures of infection are challenging to obtain. The FOIs estimated in this study provide important insight about MERS-CoV dynamics in the reservoir species, and contribute to our understanding of the zoonotic risks of this important public health threat.

KEYWORDS: Dromedary camels; MERS-CoV; emerging infections; force of infection; reservoir

PMID: 31547888 DOI: 10.1017/S0950268819001663

Keywords: MERS-CoV; Camels; Kenya.

—–

Impact of the 1918 #Influenza #Pandemic in Coastal #Kenya (Trop Med Infect Dis., abstract)

[Source: US National Library of Medicine, full page: (LINK). Abstract, edited.]

Trop Med Infect Dis. 2019 Jun 8;4(2). pii: E91. doi: 10.3390/tropicalmed4020091.

Impact of the 1918 Influenza Pandemic in Coastal Kenya.

Andayi F1, Chaves SS2,3, Widdowson MA4,5.

Author information: 1 Influenza Program, Centers for Disease Control and Prevention-Kenya, Nairobi 00621, Kenya. Fredandayi@gmail.com. 2 Influenza Program, Centers for Disease Control and Prevention-Kenya, Nairobi 00621, Kenya. bev8@cdc.gov. 3 Influenza Division, National Center for Immunization and Respiratory Diseases, US Centers for Disease Control and Prevention, Atlanta, GA 30333, USA. bev8@cdc.gov. 4 Division of Global Health Protection, Centers for Disease Control and Prevention-Kenya, Nairobi 00621, Kenya. zux5@cdc.gov. 5 Division of Global Health Protection, Centers for Disease Control and Prevention, Atlanta, GA 30333, USA. zux5@cdc.gov.

 

Abstract

The 1918 influenza pandemic was the most significant pandemic recorded in human history. Worldwide, an estimated half billion persons were infected and 20 to 100 million people died in three waves during 1918 to 1919. Yet the impact of this pandemic has been poorly documented in many countries especially those in Africa. We used colonial-era records to describe the impact of 1918 influenza pandemic in the Coast Province of Kenya. We gathered quantitative data on facility use and all-cause mortality from 1912 to 1925, and pandemic-specific data from active reporting from September 1918 to March 1919. We also extracted quotes from correspondence to complement the quantitative data and describe the societal impact of the pandemic. We found that crude mortality rates and healthcare utilization increased six- and three-fold, respectively, in 1918, and estimated a pandemic mortality rate of 25.3 deaths/1000 people/year. Impact to society and the health care system was dramatic as evidenced by correspondence. In conclusion, the 1918 pandemic profoundly affected Coastal Kenya. Preparation for the next pandemic requires continued improvement in surveillance, education about influenza vaccines, and efforts to prevent, detect and respond to novel influenza outbreaks.

KEYWORDS: 1918 pandemic; Africa; Kenya; Spanish flu; influenza pandemic

PMID: 31181715 DOI: 10.3390/tropicalmed4020091

Keywords: Influenza A; Pandemic Influenza; Spanish Flu; Society; Kenya.

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#Serological #evidence of #Flavivirus #circulation in #human populations in Northern #Kenya: an assessment of disease risk 2016-2017 (Virol J., abstract)

[Source: US National Library of Medicine, full page: (LINK). Abstract, edited.]

Virol J. 2019 May 17;16(1):65. doi: 10.1186/s12985-019-1176-y.

Serological evidence of Flavivirus circulation in human populations in Northern Kenya: an assessment of disease risk 2016-2017.

Chepkorir E1,2, Tchouassi DP3, Konongoi SL4, Lutomiah J4, Tigoi C3, Irura Z5, Eyase F6, Venter M7, Sang R3.

Author information: 1 International Centre of Insect Physiology and Ecology, P. O. Box 30772-00100, Nairobi, Kenya. echepkorir@icipe.org. 2 Center for Viral Zoonoses, Department of Medical Virology, University of Pretoria, P. O. Box 323, Arcadia, 0007, South Africa. echepkorir@icipe.org. 3 International Centre of Insect Physiology and Ecology, P. O. Box 30772-00100, Nairobi, Kenya. 4 Center for Virus Research, Kenya Medical Research Institute, P. O. Box 54628-00200, Nairobi, Kenya. 5 Division of Disease Surveillance and Response, Ministry of Health, P. O. Box 20781-00202, Nairobi, Kenya. 6 Jomo Kenyatta University of Agriculture and Technology, P.O. Box 606, Village Market, Nairobi, Kenya. 7 Center for Viral Zoonoses, Department of Medical Virology, University of Pretoria, P. O. Box 323, Arcadia, 0007, South Africa.

 

Abstract

BACKGROUND:

Yellow fever, Dengue, West Nile and Zika viruses are re-emerging mosquito-borne Flaviviruses of public health concern. However, the extent of human exposure to these viruses and associated disease burden in Kenya and Africa at large remains unknown. We assessed the seroprevalence of Yellow fever and other Flaviviruses in human populations in West Pokot and Turkana Counties of Kenya. These areas border Uganda, South Sudan and Ethiopia where recent outbreaks of Yellow fever and Dengue have been reported, with possibility of spillover to Kenya.

METHODOLOGY:

Human serum samples collected through a cross-sectional survey in West Pokot and Turkana Counties were screened for neutralizing antibodies to Yellow fever, Dengue-2, West Nile and Zika virus using the Plaque Reduction Neutralization Test (PRNT). Seroprevalence was compared by county, site and important human demographic characteristics. Adjusted odds ratios (aOR) were estimated using Firth logistic regression model.

RESULTS:

Of 877 samples tested, 127 neutralized with at least one of the four flaviviruses (14.5, 95% CI 12.3-17.0%), with a higher proportion in Turkana (21.1%, n = 87/413) than in West Pokot (8.6%, n = 40/464). Zika virus seroprevalence was significantly higher in West Pokot (7.11%) than in Turkana County (0.24%; χ2 P < 0.0001). A significantly higher Yellow fever virus seroprevalence was also observed in Turkana (10.7%) compared to West Pokot (1.29%; χ2 P < 0.0001). A high prevalence of West Nile virus was detected in Turkana County only (10.2%) while Dengue was only detected in one sample, from West Pokot. The odds of infection with West Nile virus was significantly higher in males than in females (aOR = 2.55, 95% CI 1.22-5.34). Similarly, the risk of Zika virus infection in West Pokot was twice higher in males than females (aOR = 2.01, 95% CI 0.91-4.41).

CONCLUSION:

Evidence of neutralizing antibodies to West Nile and Zika viruses indicates that they have been circulating undetected in human populations in these areas. While the observed Yellow Fever prevalence in Turkana and West Pokot Counties may imply virus activity, we speculate that this could also be as a result of vaccination following the Yellow Fever outbreak in the Omo river valley, South Sudan and Uganda across the border.

KEYWORDS: Dengue virus; Flaviviruses risk assessment; Northern Kenya; Plaque reduction neutralization test; Seroprevalence; West Nile virus; Yellow fever virus; Zika virus

PMID: 31101058 DOI: 10.1186/s12985-019-1176-y

Keywords: Flavivirus; WNV; Zika Virus; Dengue Fever; Yellow Fever; Serology; Seroprevalence; Kenya.

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