Observations of the Turkana jet and the East African dry tropics: The RIFTJet field campaign

The Turkana low-level jet (LLJ) is an intrinsic part of the African climate system. It is the principle conduit for water vapor transport to the African interior from the Indian Ocean, and droughts in East Africa tend to occur when the jet is strong. The only direct observations of the Turkana jet come from manual tracking of pilot balloons in the 1980s. Now, modern reanalysis datasets disagree with one another over the strength of jet winds and underestimate the strength of the jet by 25%–75% compared to the pilot balloon data. This article gives an overview of a field campaign based in northwest Kenya—the Radiosonde Investigation for the Turkana Jet (RIFTJet)—which measured the Turkana jet for the first time in 40 years using modern technologies. Radiosonde data reveal a persistent low-level jet, which formed on every night of the campaign, with an average low-level maximum wind speed of 16.8 m s−1 at 0300 LT. One of the latest reanalysis datasets (ERA5) underestimates low-level wind speeds by an average of 24% (4.1 m s−1) at 0300 LT and by 33% (3.6 m s−1) at 1500 LT. The measurements confirm the role of the Turkana LLJ in water vapor transport: mean water vapor transport at Marsabit is 172 kg m s−1. The dataset provides new opportunities to understand regional dynamics, and to evaluate models in one of the most data-sparse regions in the world

Evaluation of the performance of a multiplex reverse transcription polymerase chain reaction kit as a potential diagnostic and surveillance kit for rotavirus in Kenya

Abstract Background Diarrhea is a serious concern worldwide, especially in developing countries. Rotavirus is implicated in approximately 400,000 infant deaths annually. It is highly contagious elevating the risk of outbreaks especially in enclosed settings such as daycare centers, hospitals, and boarding schools. Reliable testing methods are critical for early detection of infections, better clinical management, pathogen surveillance and evaluation of interventions such as vaccines. Enzyme immunoassays have proved to be reliable and practical in most settings; however, newer multiplex reverse transcription polymerase assays have been introduced in the Kenya market but have not been evaluated locally. Methods Stool samples collected from an ongoing Surveillance of Enteric Pathogens Causing diarrheal illness in Kenya (EPS) study were used to compare an established enzyme immunoassay, Premier™ Rotaclone® (Meridian Bioscience, Cincinnati, Ohio, U.S.A.), that can only detect group A rotavirus against a novel multiplex reverse transcription polymerase chain reaction kit, Seeplex® Diarrhea-V ACE Detection (Seegene, Seoul, Republic of Korea), that can detect rotavirus, astrovirus, adenovirus, and norovirus genogroups I and II. Detection frequency, sensitivity, specificity, turnaround time, and cost were compared to determine the suitability of each assay for clinical work in austere settings versus public health work in well-funded institutes in Kenya. Results The Premier™ Rotaclone® kit had a detection frequency of 11.2%, sensitivity of 77.8%, specificity of 100%, turnaround time of 93 min and an average cost per sample of 13.33 United States dollars (USD). The Seeplex® Diarrhea-V ACE Detection kit had a detection frequency of 16.0%, sensitivity of 100%, specificity of 98.1%, turnaround time of 359 min and an average cost per samples 32.74 United States dollars respectively. The detection frequency sensitivity and specificity of the Seeplex® Diarrhea-V ACE Detection kit mentioned above are for rotavirus only. Conclusions The higher sensitivity and multiplex nature of the Seeplex® Diarrhea-V ACE Detection kit make it suitable for surveillance of enteric viruses circulating in Kenya. However, its higher cost, longer turnaround time and complexity favor well-resourced clinical labs and research applications. The Premier™ Rotaclone®, on the other hand, had a higher specificity, shorter turnaround time, and lower cost making it more attractive for clinical work in low complexity labs in austere regions of the country. It is important to continuously evaluate assay platforms’ performance, operational cost, turnaround time, and usability in different settings so as to ensure quality results that are useful to the patients and public health practitioners.https://deepblue.lib.umich.edu/bitstream/2027.42/152177/1/40794_2019_Article_87.pd

Modeling Infant Mortality Risk Factors using Logistic Regression Model and Spatial Analysis in Kenya

Globally, infant mortality is used as an important indicator for healthcare status hence an important tool for evaluation and planning of public health strategies. Despite of numerous interventions by governments aimed at reducing infant mortality, high rates are still reported in Kenya. A lot of resources are channeled towards its control leading to low productivity hence impacting the household economic welfare and national GD. The specific objective was to establish risk factors and the spatial variation of infantmortality in Kenya by analyzing the 2014 Kenya Demographic Health Survey data. A fully Bayesian paradigm and logistic regression model were used to determine infant mortality risk factors and spatial variation in Kenya.Demographic, socioeconomic and environmental factors were found to have significant effect on infant mortality. Counties from the northern parts of Kenya, Rift Valley, Central, Eastern, Nyanza, Coastal and Western parts of Kenya showed a high level of infant deaths. Infant mortality is highin arid and semi-arid areas and coastal areas due to high prevalence of infectious diseases and inadequate water supply, health facilities and low education levels. Infant mortality varies significantly across regions in Kenya due to cultural activities, and weather patterns hence exists spatial autocorrelation among neighboring regions