Assembling a geospatial database of tsetse-transmitted animal trypanosomosis for Africa by Giuliano Cecchi, Massimo Paone, Udo Feldmann, Marc JB Vreysen, Oumar Diall, Raffaele C Mattioli

“…Results Preliminary results are presented for Ethiopia, Kenya and Uganda in East Africa: 122 papers were identified and analyzed, which contained field data collected from January 1990 to December 2013. …”
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The challenges of changing national malaria drug policy to artemisinin-based combinations in Kenya by Otieno Dorothy N, Greenfield Joanne, Kangwana Beth B, Zurovac Dejan, Amin Abdinasir A, Akhwale Willis S, Snow Robert W

“…AL arrived in Kenya in May 2006, distribution to health facilities began in July 2006 coincidental with cascade in-service training in the revised national guidelines. …”
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The challenges of changing national malaria drug policy to artemisinin-based combinations in Kenya by Amin, A, Zurovac, D, Kangwana, B, Greeenfield, J, Otieno, D, Akhwale, W, Snow, R

“…AL arrived in Kenya in May 2006, distribution to health facilities began in July 2006 coincidental with cascade in-service training in the revised national guidelines. …”

Sub national variation and inequalities in under-five mortality in Kenya since 1965 by Macharia, PM, Giorgi, E, Thuranira, PN, Joseph, NK, Sartorius, B, Snow, RW, Okiro, EA

“…Here the comprehensive compilation and analysis of birth history data was used to understand spatio-temporal variation, inequalities and progress towards achieving the reductions targets of U5M between 1965 and 2013 and projected to 2015 at decentralized health planning units (counties) in Kenya.</p> <p><strong>Methods</strong></p> <p>Ten household surveys and three censuses with data on birth histories undertaken between 1989 and 2014 were assembled. …”

The challenges of changing national malaria drug policy to artemisinin-based combinations in Kenya. by Amin, A, Zurovac, D, Kangwana, B, Greenfield, J, Otieno, D, Akhwale, W, Snow, R

“…AL arrived in Kenya in May 2006, distribution to health facilities began in July 2006 coincidental with cascade in-service training in the revised national guidelines. …”

Sub national variation and inequalities in under-five mortality in Kenya since 1965 by Macharia, P, Giorgi, E, Thuranira, P, Joseph, N, Sartorius, B, Snow, R, Okiro, E

“…Here the comprehensive compilation and analysis of birth history data was used to understand spatio-temporal variation, inequalities and progress towards achieving the reductions targets of U5M between 1965 and 2013 and projected to 2015 at decentralized health planning units (counties) in Kenya. <strong>Methods:</strong> Ten household surveys and three censuses with data on birth histories undertaken between 1989 and 2014 were assembled. …”

Sub national variation and inequalities in under-five mortality in Kenya since 1965 by Peter M. Macharia, Emanuele Giorgi, Pamela N. Thuranira, Noel K. Joseph, Benn Sartorius, Robert W. Snow, Emelda A. Okiro

“…Here the comprehensive compilation and analysis of birth history data was used to understand spatio-temporal variation, inequalities and progress towards achieving the reductions targets of U5M between 1965 and 2013 and projected to 2015 at decentralized health planning units (counties) in Kenya. Methods Ten household surveys and three censuses with data on birth histories undertaken between 1989 and 2014 were assembled. …”
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Understanding Heterogeneity in the Impact of National Neglected Tropical Disease Control Programmes: Evidence from School-Based Deworming in Kenya. by Birgit Nikolay, Charles S Mwandawiro, Jimmy H Kihara, Collins Okoyo, Jorge Cano, Mariam T Mwanje, Hadley Sultani, Dorcas Alusala, Hugo C Turner, Caroline Teti, Josh Garn, Matthew C Freeman, Elizabeth Allen, Roy M Anderson, Rachel L Pullan, Sammy M Njenga, Simon J Brooker

“…To better understand the heterogeneity of programme impact and its underlying reasons, we investigated the influence of contextual factors on reduction in STH infection as part of the national school based deworming (SBD) programme in Kenya. …”
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Earth observation for ecosystem accounting: spatially explicit national seagrass extent and carbon stock in Kenya, Tanzania, Mozambique and Madagascar by Dimosthenis Traganos, Avi Putri Pertiwi, Chengfa Benjamin Lee, Alina Blume, Dimitris Poursanidis, Aurelie Shapiro

“…Leveraging a biennial percentile composite, assembled from 16 453 Sentinel‐2 surface reflectance image tiles at 10‐m spatial resolution, and 20 820 reference data points, we applied the cloud‐native framework to produce the first national inventories of seagrass extent and total seagrass carbon stocks in Kenya, Tanzania, Mozambique and Madagascar. …”
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The risks of malariainfection in Kenya in 2009 by Hay Simon I, Patil Anand P, Alegana Victor A, Gething Peter W, Noor Abdisalan M, Muchiri Eric, Juma Elizabeth, Snow Robert W

“…Advances in model based geo-statistics and malaria parasite prevalence data assemblies provide unique opportunities to redefine national <it>Plasmodium falciparum </it>risk distributions. …”
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Distribution of the main malaria vectors in Kenya. by Okara, R, Sinka, M, Minakawa, N, Mbogo, C, Hay, S, Snow, R

“… BACKGROUND: A detailed knowledge of the distribution of the main Anopheles malaria vectors in Kenya should guide national vector control strategies. …”

The risks of malaria infection in Kenya in 2009. by Noor, A, Gething, P, Alegana, V, Patil, A, Hay, S, Muchiri, E, Juma, E, Snow, R

“…Advances in model based geo-statistics and malaria parasite prevalence data assemblies provide unique opportunities to redefine national Plasmodium falciparum risk distributions. …”

The risks of malaria infection in Kenya in 2009 by Noor, A, Gething, P, Alegana, V, Patil, A, Hay, S, Muchiri, E, Juma, E, Snow, R

“…Advances in model based geo-statistics and malaria parasite prevalence data assemblies provide unique opportunities to redefine national <em>Plasmodium falciparum</em> risk distributions. …”

The risks of malaria infection in Kenya in 2009 by Noor, A, Gething, P, Alegana, V, Patil, A, Hay, S, Muchiri, E, Juma, E, Snow, R

“…Advances in model based geo-statistics and malaria parasite prevalence data assemblies provide unique opportunities to redefine national Plasmodium falciparum risk distributions. …”

Distribution of the main malaria vectors in Kenya by Okara, R, Sinka, M, Minakawa, N, Mbogo, C, Hay, S, Snow, R

“…Background: A detailed knowledge of the distribution of the main <em>Anopheles</em> malaria vectors in Kenya should guide national vector control strategies. …”

Draft genome of a clinical Pseudomonas qingdaonensis isolate from a hospitalized patient at Kenyatta National Hospital, Kenya [version 1; peer review: 2 approved] by Racheal Gachogo, Brian Ogoti, Frank Onyambu

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Malaria micro-stratification using routine surveillance data in Western Kenya by Alegana, VA, Suiyanka, L, Macharia, PM, Ikahu-Muchangi, G, Snow, RW

“…Background<br> There is an increasing need for finer spatial resolution data on malaria risk to provide micro-stratification to guide sub-national strategic plans. Here, spatial-statistical techniques are used to exploit routine data to depict sub-national heterogeneities in test positivity rate (TPR) for malaria among patients attending health facilities in Kenya. …”

A vulnerability index for COVID-19: spatial analysis at the subnational level in Kenya by Macharia, PM, Joseph, NK, Okiro, EA

“…We created three vulnerability indices to identify areas and people who require greater support while elucidating health inequities to inform emergency response in Kenya. Methods Geospatial indicators were assembled to create three vulnerability indices; Social VulnerabilityIndex (SVI), Epidemiological Vulnerability Index (EVI) and a composite of the two, that is, Social Epidemiological Vulnerability Index (SEVI) resolved at 295 subcounties in Kenya. …”

Modelling and Validation of Typical PV Mini-Grids in Kenya: Experience from RESILIENT Project by Khalid Hanbashi, Zafar Iqbal, Dimitri Mignard, Colin Pritchard, Sasa Z. Djokic

“…PV-based mini-grids are identified as a feasible and, often, only economically viable option for the electrification of Kenyan remote and scattered rural areas, where connection to the national grid is challenging, and the related costs are high, if not prohibitive. …”
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Spatio‐temporal analysis of Plasmodium falciparum prevalence to understand the past and chart the future of malaria control in Kenya by Macharia, P, Giorgi, E, Noor, A, Waqo, E, Kiptui, R, Okiro, E, Snow, R

“…<strong>Results</strong> 5020 surveys at 3701 communities were assembled. Nationally, there was an 88% reduction in the mean modelled PfPR2–10 from 21.2% (ICR: 13.8–32.1%) in 1990 to 2.6% (ICR: 1.8–3.9%) in 2015. …”