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Xiao S, Abade A, Boru W, Kasambara W, Mwaba J, Ongole F, Mmanywa M, Trovão NS, Chilengi R, Kwenda G, Orach CG, Chibwe I, Bwire G, Stine OC, Milstone AM, Lessler J, Azman AS, Luo W, Murt K, Sack DA, Debes AK, Wohl S. New Vibrio cholerae sequences from Eastern and Southern Africa alter our understanding of regional cholera transmission. medRxiv 2024:2024.03.28.24302717. [PMID: 38585829 PMCID: PMC10996759 DOI: 10.1101/2024.03.28.24302717] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
Despite ongoing containment and vaccination efforts, cholera remains prevalent in many countries in sub-Saharan Africa. Part of the difficulty in containing cholera comes from our lack of understanding of how it circulates throughout the region. To better characterize regional transmission, we generated and analyzed 118 Vibrio cholerae genomes collected between 2007-2019 from five different countries in Southern and Eastern Africa. We showed that V. cholerae sequencing can be successful from a variety of sample types and filled in spatial and temporal gaps in our understanding of circulating lineages, including providing some of the first sequences from the 2018-2019 outbreaks in Uganda, Kenya, Tanzania, Zambia, and Malawi. Our results present a complex picture of cholera transmission in the region, with multiple lineages found to be co-circulating within several countries. We also find evidence that previously identified sporadic cases may be from larger, undersampled outbreaks, highlighting the need for careful examination of sampling biases and underscoring the need for continued and expanded cholera surveillance across the African continent.
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Affiliation(s)
- Shaoming Xiao
- Division of Pediatric Infectious Disease, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Ahmed Abade
- Ministry of Health, Dar es Salaam, Tanzania
- Field Epidemiology and Laboratory Training Program, Nairobi, Kenya
| | - Waqo Boru
- Field Epidemiology and Laboratory Training Program, Nairobi, Kenya
| | | | - John Mwaba
- Center for Infectious Disease Research, Zambia
- Department of Pathology and Microbiology, University Teaching Hospital, Lusaka, Zambia
| | | | | | | | - Roma Chilengi
- Zambia National Public Health Institute, Lusaka, Zambia
| | | | | | | | | | - O Colin Stine
- University of Maryland School of Medicine, Baltimore, USA
| | - Aaron M Milstone
- Division of Pediatric Infectious Disease, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Justin Lessler
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Epidemiology, Gillings School of Public Health, University of North Carolina, Chapel Hill, NC, USA
- Carolina Population Center, University of North Carolina, Chapel Hill, NC, USA
| | - Andrew S Azman
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Division of Tropical and Humanitarian Medicine, Geneva University Hospitals, Geneva, Switzerland
- Geneva Centre for Emerging Viral Diseases, Geneva University Hospitals, Geneva, Switzerland
| | - Wensheng Luo
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Kelsey Murt
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Biomedical Sciences, School of Health Sciences, University of Zambia, Lusaka, Zambia
| | - David A Sack
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Amanda K Debes
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Shirlee Wohl
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Division of Infectious Diseases, Brigham and Women's Hospital, Boston, MA, USA
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Boru W, Xiao S, Amoth P, Kareko D, Langat D, Were I, Ali M, Sack DA, Lee EC, Debes AK. Prioritizing interventions for cholera control in Kenya, 2015-2020. PLoS Negl Trop Dis 2023; 17:e0010928. [PMID: 37196011 PMCID: PMC10228803 DOI: 10.1371/journal.pntd.0010928] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 05/30/2023] [Accepted: 04/20/2023] [Indexed: 05/19/2023] Open
Abstract
Kenya has experienced cholera outbreaks since 1971, with the most recent wave beginning in late 2014. Between 2015-2020, 32 of 47 counties reported 30,431 suspected cholera cases. The Global Task Force for Cholera Control (GTFCC) developed a Global Roadmap for Ending Cholera by 2030, which emphasizes the need to target multi-sectoral interventions in priority cholera burden hotspots. This study utilizes the GTFCC's hotspot method to identify hotspots in Kenya at the county and sub-county administrative levels from 2015 through 2020. 32 of 47 (68.1%) counties reported cholera cases during this time while only 149 of 301 (49.5%) sub-counties reported cholera cases. The analysis identifies hotspots based on the mean annual incidence (MAI) over the past five-year period and cholera's persistence in the area. Applying a MAI threshold of 90th percentile and the median persistence at both the county and sub-county levels, we identified 13 high risk sub-counties from 8 counties, including the 3 high risk counties of Garissa, Tana River and Wajir. This demonstrates that several sub-counties are high level hotspots while their counties are not. In addition, when cases reported by county versus sub-county hotspot risk are compared, 1.4 million people overlapped in the areas identified as both high-risk county and high-risk sub-county. However, assuming that finer scale data is more accurate, 1.6 million high risk sub-county people would have been misclassified as medium risk with a county-level analysis. Furthermore, an additional 1.6 million people would have been classified as living in high-risk in a county-level analysis when at the sub-county level, they were medium, low or no-risk sub-counties. This results in 3.2 million people being misclassified when county level analysis is utilized rather than a more-focused sub-county level analysis. This analysis highlights the need for more localized risk analyses to target cholera intervention and prevention efforts towards the populations most vulnerable.
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Affiliation(s)
- Waqo Boru
- Ministry of Health, Nairobi, Kenya
- Field Epidemiology and Laboratory Training Program, Nairobi, Kenya
| | - Shaoming Xiao
- Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | | | | | | | - Ian Were
- Ministry of Health, Nairobi, Kenya
| | - Mohammad Ali
- Johns Hopkins School of Public Health, Department of International Health, Baltimore, Maryland, United States of America
| | - David A. Sack
- Johns Hopkins School of Public Health, Department of International Health, Baltimore, Maryland, United States of America
| | - Elizabeth C. Lee
- Johns Hopkins School of Public Health, Department of Epidemiology, Baltimore, Maryland, United States of America
| | - Amanda K. Debes
- Johns Hopkins School of Public Health, Department of International Health, Baltimore, Maryland, United States of America
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Ngere P, Onsongo J, Langat D, Nzioka E, Mudachi F, Kadivane S, Chege B, Kirui E, Were I, Mutiso S, Kibisu A, Ihahi J, Mutethya G, Mochache T, Lokamar P, Boru W, Makayotto L, Okunga E, Ganda N, Haji A, Gathenji C, Kariuki W, Osoro E, Kasera K, Kuria F, Aman R, Nabyonga J, Amoth P. Characterization of COVID-19 cases in the early phase (March to July 2020) of the pandemic in Kenya. J Glob Health 2022; 12:15001. [PMID: 36583253 PMCID: PMC9801068 DOI: 10.7189/jogh.12.15001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Background Kenya detected the first case of COVID-19 on March 13, 2020, and as of July 30, 2020, 17 975 cases with 285 deaths (case fatality rate (CFR) = 1.6%) had been reported. This study described the cases during the early phase of the pandemic to provide information for monitoring and response planning in the local context. Methods We reviewed COVID-19 case records from isolation centres while considering national representation and the WHO sampling guideline for clinical characterization of the COVID-19 pandemic within a country. Socio-demographic, clinical, and exposure data were summarized using median and mean for continuous variables and proportions for categorical variables. We assigned exposure variables to socio-demographics, exposure, and contact data, while the clinical spectrum was assigned outcome variables and their associations were assessed. Results A total of 2796 case records were reviewed including 2049 (73.3%) male, 852 (30.5%) aged 30-39 years, 2730 (97.6%) Kenyans, 636 (22.7%) transporters, and 743 (26.6%) residents of Nairobi City County. Up to 609 (21.8%) cases had underlying medical conditions, including hypertension (n = 285 (46.8%)), diabetes (n = 211 (34.6%)), and multiple conditions (n = 129 (21.2%)). Out of 1893 (67.7%) cases with likely sources of exposure, 601 (31.8%) were due to international travel. There were 2340 contacts listed for 577 (20.6%) cases, with 632 contacts (27.0%) being traced. The odds of developing COVID-19 symptoms were higher among case who were aged above 60 years (odds ratio (OR) = 1.99, P = 0.007) or had underlying conditions (OR = 2.73, P < 0.001) and lower among transport sector employees (OR = 0.31, P < 0.001). The odds of developing severe COVID-19 disease were higher among cases who had underlying medical conditions (OR = 1.56, P < 0.001) and lower among cases exposed through community gatherings (OR = 0.27, P < 0.001). The odds of survival of cases from COVID-19 disease were higher among transport sector employees (OR = 3.35, P = 0.004); but lower among cases who were aged ≥60 years (OR = 0.58, P = 0.034) and those with underlying conditions (OR = 0.58, P = 0.025). Conclusion The early phase of the COVID-19 pandemic demonstrated a need to target the elderly and comorbid cases with prevention and control strategies while closely monitoring asymptomatic cases.
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Affiliation(s)
- Philip Ngere
- Department of Disease Surveillance and Epidemic Response, Ministry of Health, Kenya,Washington State University, Global Health, Kenya
| | | | - Daniel Langat
- Department of Disease Surveillance and Epidemic Response, Ministry of Health, Kenya
| | - Elizabeth Nzioka
- Public Health Emergency Operation Centre, Ministry of Health, Kenya
| | - Faith Mudachi
- Department of Promotive and Preventive Health, Ministry of Health, Kenya
| | - Samuel Kadivane
- Department of Disease Surveillance and Epidemic Response, Ministry of Health, Kenya
| | - Bernard Chege
- Public Health Emergency Operation Centre, Ministry of Health, Kenya
| | - Elvis Kirui
- National Public Health Laboratory Services, Ministry of Health, Kenya
| | - Ian Were
- Office of the Director General, Ministry of Health, Kenya
| | - Stephen Mutiso
- Department of Promotive and Preventive Health, Ministry of Health, Kenya
| | - Amos Kibisu
- Public Health Emergency Operation Centre, Ministry of Health, Kenya
| | - Josephine Ihahi
- Public Health Emergency Operation Centre, Ministry of Health, Kenya
| | - Gladys Mutethya
- Public Health Emergency Operation Centre, Ministry of Health, Kenya
| | | | - Peter Lokamar
- National Public Health Laboratory Services, Ministry of Health, Kenya
| | - Waqo Boru
- Field Epidemiology and Laboratory Training Program, Ministry of Health, Kenya
| | - Lyndah Makayotto
- Department of Disease Surveillance and Epidemic Response, Ministry of Health, Kenya
| | - Emmanuel Okunga
- Department of Disease Surveillance and Epidemic Response, Ministry of Health, Kenya
| | | | - Adam Haji
- World Health Organization, Nairobi Kenya
| | | | | | - Eric Osoro
- Washington State University, Global Health, Kenya
| | - Kadondi Kasera
- Public Health Emergency Operation Centre, Ministry of Health, Kenya
| | - Francis Kuria
- Directorate of Public Health, Ministry of Health, Kenya
| | - Rashid Aman
- Cabinet Administrative Secretary, Ministry of Health, Kenya
| | | | - Patrick Amoth
- Office of the Director General, Ministry of Health, Kenya
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Dulacha D, Were V, Oyugi E, Kiptui R, Owiny M, Boru W, Gura Z, Perry RT. Reduction in malaria burden following the introduction of indoor residual spraying in areas protected by long-lasting insecticidal nets in Western Kenya, 2016-2018. PLoS One 2022; 17:e0266736. [PMID: 35442999 PMCID: PMC9020686 DOI: 10.1371/journal.pone.0266736] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2021] [Accepted: 03/25/2022] [Indexed: 11/19/2022] Open
Abstract
Background Long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) are the main malaria vector control measures deployed in Kenya. Widespread pyrethroid resistance among the primary vectors in Western Kenya has necessitated the re-introduction of IRS using an organophosphate insecticide, pirimiphos-methyl (Actellic® 300CS), as a pyrethroid resistance management strategy. Evaluation of the effectiveness of the combined use of non-pyrethroid IRS and LLINs has yielded varied results. We aimed to evaluate the effect of non-pyrethroid IRS and LLINs on malaria indicators in a high malaria transmission area. Methods We reviewed records and tallied monthly aggregate of outpatient department (OPD) attendance, suspected malaria cases, those tested for malaria and those testing positive for malaria at two health facilities, one from Nyatike, an intervention sub-county, and one from Suba, a comparison sub-county, both located in Western Kenya, from February 1, 2016, through March 31, 2018. The first round of IRS was conducted in February–March 2017 in Nyatike sub-county and the second round one year later in both Nyatike and Suba sub-counties. The mass distribution of LLINs has been conducted in both locations. We performed descriptive analysis and estimated the effect of the interventions and temporal changes of malaria indicators using Poisson regression for a period before and after the first round of IRS. Results A higher reduction in the intervention area in total OPD, the proportion of OPD visits due to suspected malaria, testing positivity rate and annual malaria incidences were observed except for the total OPD visits among the under 5 children (59% decrease observed in the comparison area vs 33% decrease in the intervention area, net change -27%, P <0.001). The percentage decline in annual malaria incidence observed in the intervention area was more than twice the observed percentage decline in the comparison area across all the age groups. A marked decline in the monthly testing positivity rate (TPR) was noticed in the intervention area, while no major changes were observed in the comparison area. The monthly TPR reduced from 46% in February 2016 to 11% in February 2018, representing a 76% absolute decrease in TPR among all ages (RR = 0.24, 95% CI 0.12–0.46). In the comparison area, TPR was 16% in both February 2016 and February 2018 (RR = 1.0, 95% CI 0.52–2.09). A month-by-month comparison revealed lower TPR in Year 2 compared to Year 1 in the intervention area for most of the one year after the introduction of the IRS. Conclusions Our findings demonstrated a reduced malaria burden among populations protected by both non-pyrethroid IRS and LLINs implying a possible additional benefit afforded by the combined intervention in the malaria-endemic zone.
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Affiliation(s)
- Diba Dulacha
- Field Epidemiology and Laboratory Training Program, Ministry of Health, Nairobi, Kenya
- * E-mail:
| | - Vincent Were
- The U.S. Centers for Disease Control and Prevention, Nairobi, Kenya
| | - Elvis Oyugi
- Field Epidemiology and Laboratory Training Program, Ministry of Health, Nairobi, Kenya
| | - Rebecca Kiptui
- National Malaria Control Program, Ministry of Health, Nairobi, Kenya
| | - Maurice Owiny
- Field Epidemiology and Laboratory Training Program, Ministry of Health, Nairobi, Kenya
| | - Waqo Boru
- Field Epidemiology and Laboratory Training Program, Ministry of Health, Nairobi, Kenya
| | - Zeinab Gura
- Field Epidemiology and Laboratory Training Program, Ministry of Health, Nairobi, Kenya
| | - Robert T. Perry
- The U.S. President’s Malaria Initiative-Kenya, Malaria Branch, Division of Parasitic Diseases and Malaria, Centre for Global Health, US Centers for Disease Control and Prevention, Atlanta, GA, United States of America
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Debes AK, Luo W, Waswa E, Boru W, Sack DA. Cholera rapid diagnostic tests recycled for PCR confirmation. Lancet Glob Health 2022; 10:e35-e36. [PMID: 34919850 DOI: 10.1016/s2214-109x(21)00465-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Revised: 09/14/2021] [Accepted: 09/27/2021] [Indexed: 11/18/2022]
Affiliation(s)
- Amanda K Debes
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA.
| | - Wensheng Luo
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | | | - Waqo Boru
- Ministry of Health, Nairobi, Kenya; Field Epidemiology and Laboratory Training Program, Nairobi, Kenya
| | - David A Sack
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
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Sack DA, Debes AK, Ateudjieu J, Bwire G, Ali M, Ngwa MC, Mwaba J, Chilengi R, Orach CC, Boru W, Mohamed AA, Ram M, George CM, Stine OC. Contrasting Epidemiology of Cholera in Bangladesh and Africa. J Infect Dis 2021; 224:S701-S709. [PMID: 34549788 PMCID: PMC8687066 DOI: 10.1093/infdis/jiab440] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
In Bangladesh and West Bengal cholera is seasonal, transmission occurs consistently annually. By contrast, in most African countries, cholera has inconsistent seasonal patterns and long periods without obvious transmission. Transmission patterns in Africa occur during intermittent outbreaks followed by elimination of that genetic lineage. Later another outbreak may occur because of reintroduction of new or evolved lineages from adjacent areas, often by human travelers. These then subsequently undergo subsequent elimination. The frequent elimination and reintroduction has several implications when planning for cholera's elimination including: a) reconsidering concepts of definition of elimination, b) stress on rapid detection and response to outbreaks, c) more effective use of oral cholera vaccine and WASH, d) need to readjust estimates of disease burden for Africa, e) re-examination of water as a reservoir for maintaining endemicity in Africa. This paper reviews major features of cholera's epidemiology in African countries which appear different from the Ganges Delta.
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Affiliation(s)
- David A Sack
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Amanda K Debes
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Jerome Ateudjieu
- Meilleur Acces aux Soins de Sante, and Department of Public Health, Faculty of Medicine and Pharmaceutical Sciences, University of Dschang, and Clinical Research Unit, Division of Health Operations Research, Cameroon Ministry of Public Health, Yaoundé, Cameroon
| | - Godfrey Bwire
- Department of Integrated Epidemiology, Surveillance, and Public Health Emergencies, Ministry of Health, Kampala, Uganda
| | - Mohammad Ali
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Moise Chi Ngwa
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - John Mwaba
- Centre for Infectious Disease Research in Zambia, Lusaka, Zambia
| | - Roma Chilengi
- Centre for Infectious Disease Research in Zambia, Lusaka, Zambia
| | - Christopher C Orach
- Department of Community Health and Behavioural Sciences, Makerere University School of Public Health, Kampala, Uganda
| | - Waqo Boru
- Ministry of Health and Field Epidemiology and Laboratory Training Program, Nairobi, Kenya
| | - Ahmed Abade Mohamed
- Tanzania Field Epidemiology and Laboratory Training Program, Dar-es-Salaam, Tanzania
| | - Malathi Ram
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Christine Marie George
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - O Colin Stine
- Department of Epidemiology and Public Health, School of Medicine, University of Maryland, Baltimore, Maryland, USA
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Debes AK, Murt KN, Waswa E, Githinji G, Umuro M, Mbogori C, Roskosky M, Ram M, Shaffer A, Sack DA, Boru W. Laboratory and Field Evaluation of the Crystal VC-O1 Cholera Rapid Diagnostic Test. Am J Trop Med Hyg 2021; 104:2017-2023. [PMID: 33819171 PMCID: PMC8176501 DOI: 10.4269/ajtmh.20-1280] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Accepted: 01/22/2021] [Indexed: 11/26/2022] Open
Abstract
Cholera is a severe acute, highly transmissible diarrheal disease which affects many low- and middle-income countries. Outbreaks of cholera are confirmed using microbiological culture, and additional cases during the outbreak are generally identified based on clinical case definitions, rather than laboratory confirmation. Many low-resource areas where cholera occurs lack the capacity to perform culture in an expeditious manner. A simple, reliable, and low-cost rapid diagnostic test (RDT) would improve identification of cases allowing rapid response to outbreaks. Several commercial RDTs are available for cholera testing with two lines to detect either serotypes O1 and O139; however, issues with sensitivity and specificity have not been optimal with these bivalent tests. Here, we report an evaluation of a new commercially available cholera dipstick test which detects only serotype O1. In both laboratory and field studies in Kenya, we demonstrate high sensitivity (97.5%), specificity (100%), and positive predictive value (100%) of this new RDT targeting only serogroup O1. This is the first field evaluation for the new Crystal VC-O1 RDT; however, with these high-performance metrics, this RDT could significantly improve cholera outbreak detection and improve surveillance for better understanding of cholera disease burden.
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Affiliation(s)
- Amanda K. Debes
- Department of International Health, Johns Hopkins School of Public Health, Baltimore, Maryland
| | - Kelsey N. Murt
- Department of International Health, Johns Hopkins School of Public Health, Baltimore, Maryland
| | | | | | | | | | - Mellisa Roskosky
- Department of International Health, Johns Hopkins School of Public Health, Baltimore, Maryland
| | - Malathi Ram
- Department of International Health, Johns Hopkins School of Public Health, Baltimore, Maryland
| | - Allison Shaffer
- Department of International Health, Johns Hopkins School of Public Health, Baltimore, Maryland
| | - David A. Sack
- Department of International Health, Johns Hopkins School of Public Health, Baltimore, Maryland
| | - Waqo Boru
- Ministry of Health, Nairobi, Kenya
- Field Epidemiology and Laboratory Training Program, Nairobi, Kenya
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Kigen HT, Boru W, Gura Z, Githuka G, Mulembani R, Rotich J, Abdi I, Galgalo T, Githuku J, Obonyo M, Muli R, Njeru I, Langat D, Nsubuga P, Kioko J, Lowther S. A protracted cholera outbreak among residents in an urban setting, Nairobi county, Kenya, 2015. Pan Afr Med J 2020; 36:127. [PMID: 32849982 PMCID: PMC7422748 DOI: 10.11604/pamj.2020.36.127.19786] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2019] [Accepted: 06/03/2020] [Indexed: 11/11/2022] Open
Abstract
Introduction in 2015, a cholera outbreak was confirmed in Nairobi county, Kenya, which we investigated to identify risk factors for infection and recommend control measures. Methods we analyzed national cholera surveillance data to describe epidemiological patterns and carried out a case-control study to find reasons for the Nairobi county outbreak. Suspected cholera cases were Nairobi residents aged >2 years with acute watery diarrhea (>4 stools/≤12 hours) and illness onset 1-14 May 2015. Confirmed cases had Vibrio cholerae isolated from stool. Case-patients were frequency-matched to persons without diarrhea (1:2 by age group, residence), interviewed using standardized questionaires. Logistic regression identified factors associated with case status. Household water was analyzed for fecal coliforms and Escherichia coli. Results during December 2014-June 2015, 4,218 cholera cases including 282 (6.7%) confirmed cases and 79 deaths (case-fatality rate [CFR] 1.9%) were reported from 14 of 47 Kenyan counties. Nairobi county reported 781 (19.0 %) cases (attack rate, 18/100,000 persons), including 607 (78%) hospitalisations, 20 deaths (CFR 2.6%) and 55 laboratory-confirmed cases (7.0%). Seven (70%) of 10 water samples from communal water points had coliforms; one had Escherichia coli. Factors associated with cholera in Nairobi were drinking untreated water (adjusted odds ratio [aOR] 6.5, 95% confidence interval [CI] 2.3-18.8), lacking health education (aOR 2.4, CI 1.1-7.9) and eating food outside home (aOR 2.4, 95% CI 1.2-5.7). Conclusion we recommend safe water, health education, avoiding eating foods prepared outside home and improved sanitation in Nairobi county. Adherence to these practices could have prevented this protacted cholera outbreak.
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Affiliation(s)
- Hudson Taabukk Kigen
- Ministry of Health, Nairobi, Kenya.,Field Epidemiology and Laboratory Training Program, Nairobi, Kenya
| | - Waqo Boru
- Ministry of Health, Nairobi, Kenya.,Field Epidemiology and Laboratory Training Program, Nairobi, Kenya
| | - Zeinab Gura
- Ministry of Health, Nairobi, Kenya.,Field Epidemiology and Laboratory Training Program, Nairobi, Kenya
| | - George Githuka
- Ministry of Health, Nairobi, Kenya.,Field Epidemiology and Laboratory Training Program, Nairobi, Kenya
| | - Robert Mulembani
- Field Epidemiology and Laboratory Training Program, Nairobi, Kenya.,Ministry of Agriculture, Livestock and Fisheries, Nairobi, Kenya
| | - Jacob Rotich
- Ministry of Health, Nairobi, Kenya.,Field Epidemiology and Laboratory Training Program, Nairobi, Kenya
| | - Isack Abdi
- Ministry of Health, Nairobi, Kenya.,Field Epidemiology and Laboratory Training Program, Nairobi, Kenya
| | - Tura Galgalo
- Field Epidemiology and Laboratory Training Program, Nairobi, Kenya.,African Field Epidemiology Network, Nairobi, Kenya
| | - Jane Githuku
- Ministry of Health, Nairobi, Kenya.,Field Epidemiology and Laboratory Training Program, Nairobi, Kenya
| | - Mark Obonyo
- Field Epidemiology and Laboratory Training Program, Nairobi, Kenya.,Ministry of Agriculture, Livestock and Fisheries, Nairobi, Kenya
| | - Raphael Muli
- Department of Health, County Government of Nairobi, Nairobi, Kenya
| | - Ian Njeru
- Ministry of Health, Nairobi, Kenya.,Division of Disease Surveillance and Response, Ministry of Health, Nairobi, Kenya
| | - Daniel Langat
- Ministry of Health, Nairobi, Kenya.,Division of Disease Surveillance and Response, Ministry of Health, Nairobi, Kenya
| | | | | | - Sara Lowther
- US Centers for Disease Control and Prevention, Atlanta, Georgia, USA
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9
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Oyugi EO, Boru W, Obonyo M, Githuku J, Onyango D, Wandeba A, Omesa E, Mwangi T, Kigen H, Muiruri J, Gura Z. An outbreak of cholera in western Kenya, 2015: a case control study. Pan Afr Med J 2018; 28:12. [PMID: 30167037 PMCID: PMC6113693 DOI: 10.11604/pamj.supp.2017.28.1.9477] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2016] [Accepted: 04/03/2016] [Indexed: 11/11/2022] Open
Abstract
Introduction in February 2015, an outbreak of acute watery diarrhea was reported in two sub counties in western Kenya. Vibrio cholerae 01 serotype Ogawa was isolated from 26 cases and from water samples collected from a river mainly used by residents of the two sub-counties for domestic purposes. We carried out an investigation to determine factors associated with the outbreak. Methods we conducted a frequency matched case control study in the community. We defined cases as episodes of watery diarrhea (at least three motions in 24 hours) in persons ≥ 2 years who were residents of Rongo or Ndhiwa sub-counties from January 23-February 25, 2015. Cases were systematically recruited from a cholera line list and matched to two controls (persons without diarrhea since January 23, 2015) by age category and residence. A structured questionnaire was administered to evaluate exposures in cases and controls and multivariable logistic regression done to determine independent factors associated with the outbreak. Results we recruited 52 cases and 104 controls. Females constituted 61% (95/156) of all participants. Overall latrine coverage was 58% (90/156). Latrine coverage was 44% (23/52) for cases and 64% (67/104) for controls. Having no latrine at home (aOR = 10.9; 95% CI: 3.02-39.21), practicing communal hand washing in a basin (aOR = 6.5; 95% CI: 2.30-18.11) and vending of food as an occupation (aOR = 3.4; 95% CI: 1.06-10.74) were independently associated with the outbreak. Conclusion poor latrine coverage and personal hygiene practices were identified as the main drivers of the outbreak. We recommended improved public health education on latrine usage and promotion of hand washing with soap and water in the community.
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Affiliation(s)
- Elvis O Oyugi
- Field Epidemiology and Laboratory Training Program, Ministry of Health, Kenya
| | - Waqo Boru
- Field Epidemiology and Laboratory Training Program, Ministry of Health, Kenya
| | - Mark Obonyo
- Field Epidemiology and Laboratory Training Program, Ministry of Health, Kenya.,Ministry of Agriculture, Livestock and Fisheries, Kenya
| | - Jane Githuku
- Field Epidemiology and Laboratory Training Program, Ministry of Health, Kenya
| | - Dickens Onyango
- Kisumu County Department of Health, Ministry of Health, Kenya
| | - Alfred Wandeba
- Field Epidemiology and Laboratory Training Program, Ministry of Health, Kenya.,Ministry of Agriculture, Livestock and Fisheries, Kenya
| | - Eunice Omesa
- Field Epidemiology and Laboratory Training Program, Ministry of Health, Kenya.,Ministry of Agriculture, Livestock and Fisheries, Kenya
| | - Tabitha Mwangi
- Field Epidemiology and Laboratory Training Program, Ministry of Health, Kenya.,Ministry of Agriculture, Livestock and Fisheries, Kenya
| | - Hudson Kigen
- Field Epidemiology and Laboratory Training Program, Ministry of Health, Kenya.,Ministry of Agriculture, Livestock and Fisheries, Kenya
| | - Joshua Muiruri
- Field Epidemiology and Laboratory Training Program, Ministry of Health, Kenya.,Ministry of Agriculture, Livestock and Fisheries, Kenya
| | - Zeinab Gura
- Field Epidemiology and Laboratory Training Program, Ministry of Health, Kenya.,Ministry of Agriculture, Livestock and Fisheries, Kenya
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10
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Golicha Q, Shetty S, Nasiblov O, Hussein A, Wainaina E, Obonyo M, Macharia D, Musyoka RN, Abdille H, Ope M, Joseph R, Kabugi W, Kiogora J, Said M, Boru W, Galgalo T, Lowther SA, Juma B, Mugoh R, Wamola N, Onyango C, Gura Z, Widdowson MA, DeCock KM, Burton JW. Cholera Outbreak in Dadaab Refugee Camp, Kenya - November 2015-June 2016. MMWR Morb Mortal Wkly Rep 2018; 67:958-961. [PMID: 30161101 PMCID: PMC6124821 DOI: 10.15585/mmwr.mm6734a4] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Dadaab Refugee camp in Garissa County, Kenya, hosts nearly 340,000 refugees in five subcamps (Dagahaley, Hagadera, Ifo, Ifo2, and Kambioos) (1). On November 18 and 19, 2015, during an ongoing national cholera outbreak (2), two camp residents were evaluated for acute watery diarrhea (three or more stools in ≤24 hours); Vibrio cholerae serogroup O1 serotype Ogawa was isolated from stool specimens collected from both patients. Within 1 week of the report of index cases, an additional 45 cases of acute watery diarrhea were reported. The United Nations High Commissioner for Refugees and their health-sector partners coordinated the cholera response, community outreach and water, sanitation, and hygiene (WASH) activities; Médecins Sans Frontiéres and the International Rescue Committee were involved in management of cholera treatment centers; CDC performed laboratory confirmation of cases and undertook GIS mapping and postoutbreak response assessment; and the Garissa County Government and the Kenya Ministry of Health conducted a case-control study. To prevent future cholera outbreaks, improvements to WASH and enhanced disease surveillance systems in Dadaab camp and the surrounding area are needed.
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Curran KG, Wells E, Crowe SJ, Narra R, Oremo J, Boru W, Githuku J, Obonyo M, De Cock KM, Montgomery JM, Makayotto L, Langat D, Lowther SA, O'Reilly C, Gura Z, Kioko J. Systems, supplies, and staff: a mixed-methods study of health care workers' experiences and health facility preparedness during a large national cholera outbreak, Kenya 2015. BMC Public Health 2018; 18:723. [PMID: 29890963 PMCID: PMC5996545 DOI: 10.1186/s12889-018-5584-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2017] [Accepted: 05/22/2018] [Indexed: 11/26/2022] Open
Abstract
Background From December 2014 to September 2016, a cholera outbreak in Kenya, the largest since 2010, caused 16,840 reported cases and 256 deaths. The outbreak affected 30 of Kenya’s 47 counties and occurred shortly after the decentralization of many healthcare services to the county level. This mixed-methods study, conducted June–July 2015, assessed cholera preparedness in Homa Bay, Nairobi, and Mombasa counties and explored clinic- and community-based health care workers’ (HCW) experiences during outbreak response. Methods Counties were selected based on cumulative cholera burden and geographic characteristics. We conducted 44 health facility cholera preparedness checklists (according to national guidelines) and 8 focus group discussions (FGDs). Frequencies from preparedness checklists were generated. To determine key themes from FGDs, inductive and deductive codes were applied; MAX software for qualitative data analysis (MAXQDA) was used to identify patterns. Results Some facilities lacked key materials for treating cholera patients, diagnosing cases, and maintaining infection control. Overall, 82% (36/44) of health facilities had oral rehydration salts, 65% (28/43) had IV fluids, 27% (12/44) had rectal swabs, 11% (5/44) had Cary-Blair transport media, and 86% (38/44) had gloves. A considerable number of facilities lacked disease reporting forms (34%, 14/41) and cholera treatment guidelines (37%, 16/43). In FDGs, HCWs described confusion regarding roles and reporting during the outbreak, which highlighted issues in coordination and management structures within the health system. Similar to checklist findings, FGD participants described supply challenges affecting laboratory preparedness and infection prevention and control. Perceived successes included community engagement, health education, strong collaboration between clinic and community HCWs, and HCWs’ personal passion to help others. Conclusions The confusion over roles, reporting, and management found in this evaluation highlights a need to adapt, implement, and communicate health strategies at the county level, in order to inform and train HCWs during health system transformations. International, national, and county stakeholders could strengthen preparedness and response for cholera and other public health emergencies in Kenya, and thereby strengthen global health security, through further investment in the existing Integrated Disease Surveillance and Response structure and national cholera prevention and control plan, and the adoption of county-specific cholera control plans.
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Affiliation(s)
- Kathryn G Curran
- US Centers for Disease Control and Prevention, 1600 Clifton Road NE, Mailstop E-04, Atlanta, GA, 30329, USA.
| | - Emma Wells
- US Centers for Disease Control and Prevention, 1600 Clifton Road NE, Mailstop E-04, Atlanta, GA, 30329, USA
| | - Samuel J Crowe
- US Centers for Disease Control and Prevention, 1600 Clifton Road NE, Mailstop E-04, Atlanta, GA, 30329, USA
| | - Rupa Narra
- US Centers for Disease Control and Prevention, 1600 Clifton Road NE, Mailstop E-04, Atlanta, GA, 30329, USA
| | | | - Waqo Boru
- Ministry of Health, Kenya Field Epidemiology and Laboratory Training Program, Nairobi, Kenya
| | - Jane Githuku
- Ministry of Health, Kenya Field Epidemiology and Laboratory Training Program, Nairobi, Kenya
| | - Mark Obonyo
- Ministry of Health, Kenya Field Epidemiology and Laboratory Training Program, Nairobi, Kenya
| | - Kevin M De Cock
- US Centers for Disease Control and Prevention, 1600 Clifton Road NE, Mailstop E-04, Atlanta, GA, 30329, USA.,US Centers for Disease Control and Prevention , Nairobi, Kenya
| | - Joel M Montgomery
- US Centers for Disease Control and Prevention, 1600 Clifton Road NE, Mailstop E-04, Atlanta, GA, 30329, USA.,US Centers for Disease Control and Prevention , Nairobi, Kenya
| | - Lyndah Makayotto
- Ministry of Health, Disease Surveillance and Response Unit, Nairobi, Kenya
| | - Daniel Langat
- Ministry of Health, Disease Surveillance and Response Unit, Nairobi, Kenya
| | - Sara A Lowther
- US Centers for Disease Control and Prevention, 1600 Clifton Road NE, Mailstop E-04, Atlanta, GA, 30329, USA.,US Centers for Disease Control and Prevention , Nairobi, Kenya
| | - Ciara O'Reilly
- US Centers for Disease Control and Prevention, 1600 Clifton Road NE, Mailstop E-04, Atlanta, GA, 30329, USA
| | - Zeinab Gura
- Ministry of Health, Kenya Field Epidemiology and Laboratory Training Program, Nairobi, Kenya
| | - Jackson Kioko
- Ministry of Health, Department of Preventive and Promotive Health, Nairobi, Kenya
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12
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Johnson M, Lemi BL, Tonny HL, David AD, Boru W, Ransom J. Late entry to HIV and AIDS care and treatment, Juba Teaching Hospital, Juba, South Sudan, 2013-2016. Afr J AIDS Res 2018; 17:213-216. [PMID: 29745288 DOI: 10.2989/16085906.2018.1467473] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Late diagnosis of HIV and enrolment to care are global public health challenges. This study aimed to characterise late HIV diagnoses and initiation of treatment among patients at Juba Teaching Hospital (JTH) in South Sudan. We conducted a retrospective review of lab-confirmed HIV patients at JTH, 2013-2016. Demographic, clinical, and laboratory data were entered into and descriptive statistics were calculated using Microsoft Excel. We identified 401 patients, with mean age 33.71±4.54 years, 235 (59%) were female, 307 (77%) were late entry, 64 (16%) were lost to follow-up, and 57 (14%) died within 12 months of diagnosis. Among patients who presented late, 122 (57%) were female, and 112 (53%) were <34 years old. Among patients who died, 33 (58%) were male, and 52 (91%) had CD4 counts <350 cells/mm3 and World Health Organization (WHO) stage >2 at diagnosis. Late diagnosis of HIV infection is a significant public health problem in South Sudan, particularly for younger and female patients.
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Affiliation(s)
- Muki Johnson
- a Immunization and Field Epidemiology Training Project , Juba , South Sudan.,b Field Epidemiology and Laboratory Training Program , Nairobi , Kenya
| | | | | | | | - Waqo Boru
- b Field Epidemiology and Laboratory Training Program , Nairobi , Kenya
| | - James Ransom
- b Field Epidemiology and Laboratory Training Program , Nairobi , Kenya.,d Piret Partners Consulting , Washington, DC , USA
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13
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Gituro CN, Nyerere A, Ngayo MO, Maina E, Githuku J, Boru W. Etiology of bacterial meningitis: a cross-sectional study among patients admitted in a semi-urban hospital in Nairobi, Kenya. Pan Afr Med J 2017; 28:10. [PMID: 30167035 PMCID: PMC6113691 DOI: 10.11604/pamj.supp.2017.28.1.9383] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2016] [Accepted: 10/24/2016] [Indexed: 11/17/2022] Open
Abstract
Introduction bacterial meningitis, responsible for childhood morbidity and mortality, can also lead to permanent neurological disability among survivors. This study conducted from January to December, 2015 used standard bacteriological and molecular methods to investigate the etiology of three common causes of bacterial meningitis among hospitalized patients admitted at a semi-urban hospital in Nairobi, Kenya. Methods a total of 196 patients admitted at Mama Lucy Kibaki with clinically diagnosed meningitis were recruited into this cross-sectional study. Participants’ information was collected through patient interviews and abstraction of health records. Bacterial culture, gram stains and multiplex polymerase chain reaction (PCR) were used to investigate causes of bacterial meningitis from cerebrospinal fluid (CSF) samples. Characteristics such as age, gender, occupation, underlying conditions of patients with laboratory confirmed bacterial meningitis infection are described. Results among the 196 patients diagnosed with bacterial meningitis, the median age was 1 year (range 1 to 36 years) with 87.2% aged 1 to 4 years; 54.6% were males. Using PCR, 22 out of 196 (11.2%) samples had evidence suggesting a bacterial infection. These included 12/22 (54.5%) S. pneumonia, 7/22 (31.8%) N. meningitides and 3/22 (13.6%) H. influenza. From bacterial culture, four of 196 (2.1%) samples grew S. pneumonia. All three samples found positive for H. influenza were from male patients aged between 1 to 4 years. Conclusion of the three common causes evaluated, S. pneumonia was the most common cause of bacterial meningitis among patients from this region, particularly among infants. One older patient was diabetic, thereby highlighting the importance of pre-existing conditions. Although serotyping of bacteria was not done, under-vaccination might have played a role in the cases identified and ensuring complete and timely vaccination may prevent further cases of bacterial meningitis.
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Affiliation(s)
- Charles Njonjo Gituro
- National Public Health Laboratory Services (NPHLS), Ministry of Health, Nairobi Kenya.,Institute of Tropical Medicine and Infectious Diseases, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya.,Field Epidemiology and Laboratory Training Program, Nairobi, Ministry of Health, Kenya
| | - Andrew Nyerere
- Institute of Tropical Medicine and Infectious Diseases, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya
| | - Musa Otieno Ngayo
- Centre of Microbiology and Research Kenya Medical Research Institute, Nairobi, Kenya
| | - Edward Maina
- Centre of Microbiology and Research Kenya Medical Research Institute, Nairobi, Kenya
| | - Jane Githuku
- Field Epidemiology and Laboratory Training Program, Nairobi, Ministry of Health, Kenya
| | - Waqo Boru
- Field Epidemiology and Laboratory Training Program, Nairobi, Ministry of Health, Kenya
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14
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Oyugi E, Gura Z, Boru W, Githuku J, Onyango D, Otieno W, Nyambati V. Male partner involvement in efforts to eliminate mother-to-child transmission of HIV in Kisumu County, Western Kenya, 2015. Pan Afr Med J 2017; 28:6. [PMID: 30167032 PMCID: PMC6113695 DOI: 10.11604/pamj.supp.2017.28.1.9283] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2016] [Accepted: 07/27/2016] [Indexed: 11/21/2022] Open
Abstract
INTRODUCTION male partner involvement in elimination of mother-to-child transmission (eMTCT) of HIV activities remains low in Western Kenya, despite its importance in reducing rates of child HIV transmission. We sought to identify factors associated with male partner involvement in eMTCT in Kisumu East sub-County, Western Kenya. METHODS we conducted a cross-sectional study among women aged ≥ 18 years who had children aged ≤ 12 months and were attending a child health clinic for immunization services in one of four Western Kenya health centers between February and April, 2015. We assessed male involvement using an "involvement index" of five factors of equal weight: partner antenatal care (ANC) attendance, partner HIV testing, partner financial support to the woman during ANC, partner awareness of ANC services and partner participation in decision making on contraception including condom use. Male involvement was classified as high or low based on their index score. We calculated odds ratios (OR) and 95% confidence intervals (CI) to identify factors associated with high male partner involvement. RESULTS we recruited 216 female participants. Mean age was 26.1 years (± 5.5 years), 189 (87.5%) were married. The majority (94.4%) had attended ANC in public health facilities. Nineteen percent of women had high male involvement. Having > 8 years of formal education (AOR 3.9, CI = 1.51-10.08), having male partner who was employed, history of previous couple testing (AOR = 3.2, CI = 1.42-7.22) and reports of partner having read the mother-child booklet during ANC (AOR = 2.9, CI = 1.30-6.49), were associated with high male involvement. CONCLUSION based on our findings, we recommend targeted strategies to actively sensitize men and encourage their involvement in eMTCT, particularly among partners of women with fewer years of education and among partners who are not employed.
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Affiliation(s)
- Elvis Oyugi
- Jomo Kenyatta University of Agriculture and Technology, Kenya
- Field Epidemiology and Laboratory Training Program, Ministry of Health, Kenya
| | - Zeinab Gura
- Field Epidemiology and Laboratory Training Program, Ministry of Health, Kenya
| | - Waqo Boru
- Field Epidemiology and Laboratory Training Program, Ministry of Health, Kenya
| | - Jane Githuku
- Field Epidemiology and Laboratory Training Program, Ministry of Health, Kenya
| | | | | | - Venny Nyambati
- Jomo Kenyatta University of Agriculture and Technology, Kenya
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15
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Roka ZG, Githuku J, Obonyo M, Boru W, Galgalo T, Amwayi S, Kioko J, Njoroge D, Ransom JA. Strengthening health systems in Africa: a case study of the Kenya field epidemiology training program for local frontline health workers. Public Health Rev 2017; 38:23. [PMID: 29450095 PMCID: PMC5809989 DOI: 10.1186/s40985-017-0070-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2017] [Accepted: 09/12/2017] [Indexed: 11/10/2022] Open
Abstract
The logistical and operational challenges to improve public health practice capacity across Africa are well documented. This report describes Kenya's Field Epidemiology and Laboratory Training Program's (KFELTP) experience in implementing frontline public health worker training to transfer knowledge and practical skills that help strengthen their abilities to detect, document, respond to, and report unusual health events. Between May 2014 and May 2015, KFELTP hosted five training courses across the country to address practice gaps among local public health workers. Participants completed a 10-week process: two 1-week didactic courses, a 7-week field project, and a final 1-week course to present and defend the findings of their field project. The first year was a pilot period to determine whether the program could fit into the existing 2-year KFELTP model and whether this frontline-level training would have an impact on local practice. At the end of the first year, KFELTP certified 167 frontline health workers in field epidemiology and data management. This paper concludes that local, national, and international partnerships are critical for improving local public health response capacity and workforce development training in an African setting.
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Affiliation(s)
- Zeinab Gura Roka
- Field Epidemiology and Laboratory Training Program, Nairobi, Kenya
| | - Jane Githuku
- Field Epidemiology and Laboratory Training Program, Nairobi, Kenya
| | - Mark Obonyo
- Field Epidemiology and Laboratory Training Program, Nairobi, Kenya
| | - Waqo Boru
- Field Epidemiology and Laboratory Training Program, Nairobi, Kenya
| | - Tura Galgalo
- African Field Epidemiology Network, Nairobi, Kenya
| | - Samuel Amwayi
- 3Disease Surveillance and Response Unit, Ministry of Health, Nairobi, Kenya
| | - Jackson Kioko
- 4Division of Preventive and Promotive Health, Ministry of Health, Nairobi, Kenya
| | - David Njoroge
- 5Human Resources Department, Ministry of Health, Nairobi, Kenya
| | - James Anthony Ransom
- Piret Partners Consulting, 611 Pennsylvania Avenue SE, Unit 358, Washington, DC 20003-4303 USA
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Odhiambo F, Buff AM, Moranga C, Moseti CM, Wesongah JO, Lowther SA, Arvelo W, Galgalo T, Achia TO, Roka ZG, Boru W, Chepkurui L, Ogutu B, Wanja E. Factors associated with malaria microscopy diagnostic performance following a pilot quality-assurance programme in health facilities in malaria low-transmission areas of Kenya, 2014. Malar J 2017; 16:371. [PMID: 28903758 PMCID: PMC5598012 DOI: 10.1186/s12936-017-2018-2] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2017] [Accepted: 09/06/2017] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Malaria accounts for ~21% of outpatient visits annually in Kenya; prompt and accurate malaria diagnosis is critical to ensure proper treatment. In 2013, formal malaria microscopy refresher training for microscopists and a pilot quality-assurance (QA) programme for malaria diagnostics were independently implemented to improve malaria microscopy diagnosis in malaria low-transmission areas of Kenya. A study was conducted to identify factors associated with malaria microscopy performance in the same areas. METHODS From March to April 2014, a cross-sectional survey was conducted in 42 public health facilities; 21 were QA-pilot facilities. In each facility, 18 malaria thick blood slides archived during January-February 2014 were selected by simple random sampling. Each malaria slide was re-examined by two expert microscopists masked to health-facility results. Expert results were used as the reference for microscopy performance measures. Logistic regression with specific random effects modelling was performed to identify factors associated with accurate malaria microscopy diagnosis. RESULTS Of 756 malaria slides collected, 204 (27%) were read as positive by health-facility microscopists and 103 (14%) as positive by experts. Overall, 93% of slide results from QA-pilot facilities were concordant with expert reference compared to 77% in non-QA pilot facilities (p < 0.001). Recently trained microscopists in QA-pilot facilities performed better on microscopy performance measures with 97% sensitivity and 100% specificity compared to those in non-QA pilot facilities (69% sensitivity; 93% specificity; p < 0.01). The overall inter-reader agreement between QA-pilot facilities and experts was κ = 0.80 (95% CI 0.74-0.88) compared to κ = 0.35 (95% CI 0.24-0.46) between non-QA pilot facilities and experts (p < 0.001). In adjusted multivariable logistic regression analysis, recent microscopy refresher training (prevalence ratio [PR] = 13.8; 95% CI 4.6-41.4), ≥5 years of work experience (PR = 3.8; 95% CI 1.5-9.9), and pilot QA programme participation (PR = 4.3; 95% CI 1.0-11.0) were significantly associated with accurate malaria diagnosis. CONCLUSIONS Microscopists who had recently completed refresher training and worked in a QA-pilot facility performed the best overall. The QA programme and formal microscopy refresher training should be systematically implemented together to improve parasitological diagnosis of malaria by microscopy in Kenya.
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Affiliation(s)
- Fredrick Odhiambo
- Field Epidemiology and Laboratory Training Programme, P.O. Box 225-00202, Nairobi, Kenya. .,Jomo Kenyatta University of Agriculture and Technology, P.O. Box 62000-00200, Nairobi, Kenya.
| | - Ann M Buff
- Division of Parasitic Diseases and Malaria, Center for Global Health, U.S. Centers for Disease Control and Prevention, 1600 Clifton Rd NE, Atlanta, GA, 30333, USA.,U.S. President's Malaria Initiative, United Nations Avenue, P.O. Box 606, Village Market, Nairobi, 00621, Kenya
| | - Collins Moranga
- United States Army Medical Research Unit-Kenya, Malaria Diagnostics Center, P.O. Box 54, Kisumu, 40100, Kenya
| | - Caroline M Moseti
- United States Army Medical Research Unit-Kenya, Malaria Diagnostics Center, P.O. Box 54, Kisumu, 40100, Kenya
| | - Jesca Okwara Wesongah
- Jomo Kenyatta University of Agriculture and Technology, P.O. Box 62000-00200, Nairobi, Kenya
| | - Sara A Lowther
- Division of Parasitic Diseases and Malaria, Center for Global Health, U.S. Centers for Disease Control and Prevention, 1600 Clifton Rd NE, Atlanta, GA, 30333, USA
| | - Wences Arvelo
- Division of Parasitic Diseases and Malaria, Center for Global Health, U.S. Centers for Disease Control and Prevention, 1600 Clifton Rd NE, Atlanta, GA, 30333, USA
| | - Tura Galgalo
- Field Epidemiology and Laboratory Training Programme, P.O. Box 225-00202, Nairobi, Kenya.,Division of Parasitic Diseases and Malaria, Center for Global Health, U.S. Centers for Disease Control and Prevention, 1600 Clifton Rd NE, Atlanta, GA, 30333, USA
| | - Thomas O Achia
- Division of Parasitic Diseases and Malaria, Center for Global Health, U.S. Centers for Disease Control and Prevention, 1600 Clifton Rd NE, Atlanta, GA, 30333, USA
| | - Zeinab G Roka
- Field Epidemiology and Laboratory Training Programme, P.O. Box 225-00202, Nairobi, Kenya
| | - Waqo Boru
- Field Epidemiology and Laboratory Training Programme, P.O. Box 225-00202, Nairobi, Kenya
| | - Lily Chepkurui
- Field Epidemiology and Laboratory Training Programme, P.O. Box 225-00202, Nairobi, Kenya
| | - Bernhards Ogutu
- United States Army Medical Research Unit-Kenya, Malaria Diagnostics Center, P.O. Box 54, Kisumu, 40100, Kenya.,Kenya Medical Research Institute, Centre for Clinical Research, P.O. Box 1578, Kisumu, 40100, Kenya
| | - Elizabeth Wanja
- United States Army Medical Research Unit-Kenya, Malaria Diagnostics Center, P.O. Box 54, Kisumu, 40100, Kenya
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George G, Rotich J, Kigen H, Catherine K, Waweru B, Boru W, Galgalo T, Githuku J, Obonyo M, Curran K, Narra R, Crowe SJ, O’Reilly CE, Macharia D, Montgomery J, Neatherlin J, De Cock KM, Lowther S, Gura Z, Langat D, Njeru I, Kioko J, Muraguri N. Notes from the Field: Ongoing Cholera Outbreak — Kenya, 2014–2016. MMWR Morb Mortal Wkly Rep 2016; 65:68-9. [DOI: 10.15585/mmwr.mm6503a7] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
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18
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Odhiambo F, Galgalo T, Wences A, Muchemi OM, Kanyina EW, Tonui JC, Amwayi S, Boru W. Antimicrobial resistance: capacity and practices among clinical laboratories in Kenya, 2013. Pan Afr Med J 2014; 19:332. [PMID: 25918572 PMCID: PMC4405071 DOI: 10.11604/pamj.2014.19.332.5159] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2014] [Accepted: 09/01/2014] [Indexed: 11/11/2022] Open
Abstract
Introduction Antimicrobial resistance is neglected in developing countries; associated with limited surveillance and unregulated use of antimicrobials. Consequently, delayed patient recoveries, deaths and further antimicrobial resistance occur. Recent gastroenteritis outbreak at a children's home associated with multidrug resistant non-typhoidal Salmonella spp, raised concerns about the magnitude of the problem in Kenya, prompting antimicrobial resistance assessment preceding surveillance system establishment. Methods Eight public medical laboratories were conveniently selected. Questionnaires were administered to key informants to evaluate capacity, practice and utilization of antimicrobial susceptibility tests. Retrospective review of laboratory records determined antimicrobial resistance to isolates. Antimicrobial resistance was defined as resistance of a microorganism to an antimicrobial agent to which it was previously sensitive and multidrug resistance as non-susceptibility to at least one agent in three or more antimicrobial categories. Results The laboratories comprised; 2(25%) national, 4(50%) sub-national and 2(25%) district. Overall, antimicrobial susceptibility testing capacity was inadequate in all. Seven (88%) had basic capacity for stool cultures, 3(38%) had capacity for blood culture. Resistance to enteric organisms was observed with the following and other commonly prescribed antimicrobials, ampicillin: 40(91%) Salmonella spp isolates; Tetracycline: 16(84%) Shigella flexineri isolates; cotrimoxazole: 20(100%) Shigella spp isolates, 24(91%) Salmonella spp isolates. Comparable patterns of multidrug resistance were evident with Shigella flexineri and Salmonella typhimurium. Ten (100%) clinicians reported not using laboratory results for patient management, for various reasons.
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Affiliation(s)
| | - Tura Galgalo
- Field Epidemiology and Laboratory Training Program, Kenya
| | - Arvelo Wences
- Field Epidemiology and Laboratory Training Program, Kenya
| | | | | | | | - Samwel Amwayi
- Field Epidemiology and Laboratory Training Program, Kenya
| | - Waqo Boru
- Field Epidemiology and Laboratory Training Program, Kenya
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