ABSTRACTBackgroundEvidence on the distribution of pre-treatment HIV-1 drug resistance (HIVDR) by risk groups is limited in Africa. We assessed prevalence, trends, and transmission dynamics of pre-treatment HIVDR within-and-between men who have sex with men (MSM), people who inject drugs (PWID), female sex workers (FSW), heterosexuals (HET), and children infected perinatally in Kenya.MethodsHIV-1 partialpolsequences from antiretroviral-naïve samples collected between 1986-2020 were used. Pre-treatment RTI, PI and INSTI mutations were assessed using the Stanford HIVDR database. Phylogenetics methods were used to determine and date transmission clusters.ResultsOf 3567 sequences analysed, 550 (15.4%, 95% CI: 14.2-16.6) had at least one pre-treatment HIVDR mutation, which was most prevalent amongst children (41.3%), followed by PWID (31.0%), MSM (19.9%), FSW (15.1%) and HET (13.9%). No INSTI resistance mutations were detected. Among HET, pre-treatment HIVDR increased from 6.6% in 1986-2005 to 20.2% in 2011-2015 but dropped to 6.5% in 2016-2020. Overall, 22 clusters with shared pre-treatment HIVDR mutations were identified. The largest was a K103N mutation cluster involving 16 MSM sequences sampled between 2010-2017, with an estimated tMRCA of 2005 (HPD, 2000-2008). This lineage had a growth rate=0.1/year and R0=1.1, indicating propagation over 12 years among ART-naïve MSM in Kenya.ConclusionsCompared to HET, children and key populations had higher levels of pre-treatment HIVDR. Introduction of INSTIs after 2016 may have reversed the increase in pre-treatment RTI mutations in Kenya. Continued surveillance of HIVDR, with a particular focus on children and key populations, is warranted to inform treatment strategies in Kenya.SummaryCompared to the heterosexual population, key populations had higher levels of pre-treatment HIV-1 drug resistance (HIVDR). Propagation of HIVDR was risk-group exclusive. Introduction of integrase inhibitors abrogated propagation of reverse transcriptase inhibitors mutations among the heterosexual, but not key populations.

We propose a novel modeling framework that efficiently encodes seasonal climate predictions to provide robust and reliable time-series forecasting for supply chain functions. The encoding framework enables effective learning of latent representations-be it uncertain seasonal climate prediction or other time-series data (e.g., buyer patterns)-via a modular neural network architecture. Our extensive experiments indicate that learning such representations to model seasonal climate forecasts results in an error reduction of approximately 13% to 17% across multiple real-world data sets compared to existing demand forecasting methods.

Current time-series forecasting problems use short-term weather attributes as exogenous inputs. However, in specific time-series forecasting solutions (e.g., demand prediction in the supply chain), seasonal climate predictions are crucial to improve its resilience. Representing mid to long-term seasonal climate forecasts is challenging as seasonal climate predictions are uncertain, and encoding spatio-temporal relationship of climate forecasts with demand is complex. We propose a novel modeling framework that efficiently encodes seasonal climate predictions to provide robust and reliable time-series forecasting for supply chain functions. The encoding framework enables effective learning of latent representations -- be it uncertain seasonal climate prediction or other time-series data (e.g., buyer patterns) -- via a modular neural network architecture. Our extensive experiments indicate that learning such representations to model seasonal climate forecast results in an error reduction of approximately 13\% to 17\% across multiple real-world data sets compared to existing demand forecasting methods.

In Kenya, HIV-1 key populations including men having sex with men (MSM), people who inject drugs (PWID) and female sex workers (FSW) are thought to significantly contribute to HIV-1 transmission in the wider, mostly heterosexual (HET) HIV-1 transmission network. However, clear data on HIV-1 transmission dynamics within and between these groups are limited. We aimed to empirically quantify rates of HIV-1 flow between key populations and the HET population, as well as between different geographic regions to determine HIV-1 'hotspots' and their contribution to HIV-1 transmission in Kenya. We used maximum-likelihood phylogenetic and Bayesian inference to analyse 4058 HIV-1 pol sequences (representing 0.3 per cent of the epidemic in Kenya) sampled 1986-2019 from individuals of different risk groups and regions in Kenya. We found 89 per cent within-risk group transmission and 11 per cent mixing between risk groups, cyclic HIV-1 exchange between adjoining geographic provinces and strong evidence of HIV-1 dissemination from (i) West-to-East (i.e. higher-to-lower HIV-1 prevalence regions), and (ii) heterosexual-to-key populations. Low HIV-1 prevalence regions and key populations are sinks rather than major sources of HIV-1 transmission in Kenya. Targeting key populations in Kenya needs to occur concurrently with strengthening interventions in the general epidemic.

HIV-1 transmission dynamics involving men who have sex with men (MSM) in Africa are not well understood. We investigated the rates of HIV-1 transmission between MSM across three regions in Kenya: Coast, Nairobi, and Nyanza. We analyzed 372 HIV-1 partial pol sequences sampled during 2006–2019 from MSM in Coast ( N = 178, 47.9%), Nairobi ( N = 137, 36.8%), and Nyanza ( N = 57, 15.3%) provinces in Kenya. Maximum-likelihood (ML) phylogenetics and Bayesian inference were used to determine HIV-1 clusters, evolutionary dynamics, and virus migration rates between geographic regions. HIV-1 sub-subtype A1 (72.0%) was most common followed by subtype D (11.0%), unique recombinant forms (8.9%), subtype C (5.9%), CRF 21A2D (0.8%), subtype G (0.8%), CRF 16A2D (0.3%), and subtype B (0.3%). Forty-six clusters (size range 2–20 sequences) were found—half (50.0%) of which had evidence of extensive HIV-1 mixing among different provinces. Data revealed an exponential increase in infections among MSM during the early-to-mid 2000s and stable or decreasing transmission dynamics in recent years (2017–2019). Phylogeographic inference showed significant (Bayes factor, BF > 3) HIV-1 dissemination from Coast to Nairobi and Nyanza provinces, and from Nairobi to Nyanza province. Strengthening HIV-1 prevention programs to MSM in geographic locations with higher HIV-1 prevalence among MSM (such as Coast and Nairobi) may reduce HIV-1 incidence among MSM in Kenya.

The Coronavirus disease 2019 (COVID-19) global pandemic has transformed almost every facet of human society throughout the world. Against an emerging, highly transmissible disease, governments worldwide have implemented non-pharmaceutical interventions (NPIs) to slow the spread of the virus. Examples of such interventions include community actions, such as school closures or restrictions on mass gatherings, individual actions including mask wearing and self-quarantine, and environmental actions such as cleaning public facilities. We present the Worldwide Non-pharmaceutical Interventions Tracker for COVID-19 (WNTRAC), a comprehensive dataset consisting of over 6,000 NPIs implemented worldwide since the start of the pandemic. WNTRAC covers NPIs implemented across 261 countries and territories, and classifies NPIs into a taxonomy of 16 NPI types. NPIs are automatically extracted daily from Wikipedia articles using natural language processing techniques and then manually validated to ensure accuracy and veracity. We hope that the dataset will prove valuable for policymakers, public health leaders, and researchers in modeling and analysis efforts to control the spread of COVID-19.

Background Developing disease risk maps for priority endemic and episodic diseases is becoming increasingly important for more effective disease management, particularly in resource limited countries. For endemic and easily diagnosed diseases such as anthrax, using historical data to identify hotspots and start to define ecological risk factors of its occurrence is a plausible approach. Using 666 livestock anthrax events reported in Kenya over 60 years (1957–2017), we determined the temporal and spatial patterns of the disease as a step towards identifying and characterizing anthrax hotspots in the region. Methods Data were initially aggregated by administrative unit and later analyzed by agro-ecological zones (AEZ) to reveal anthrax spatio-temporal trends and patterns. Variations in the occurrence of anthrax events were estimated by fitting Poisson generalized linear mixed-effects models to the data with AEZs and calendar months as fixed effects and sub-counties as random effects. Results The country reported approximately 10 anthrax events annually, with the number increasing to as many as 50 annually by the year 2005. Spatial classification of the events in eight counties that reported the highest numbers revealed spatial clustering in certain administrative sub-counties, with 12% of the sub-counties responsible for over 30% of anthrax events, whereas 36% did not report any anthrax disease over the 60-year period. When segregated by AEZs, there was significantly greater risk of anthrax disease occurring in agro-alpine, high, and medium potential AEZs when compared to the agriculturally low potential arid and semi-arid AEZs of the country ( p < 0.05). Interestingly, cattle were > 10 times more likely to be infected by B. anthracis than sheep, goats, or camels. There was lower risk of anthrax events in August ( P = 0.034) and December ( P = 0.061), months that follow long and short rain periods, respectively. Conclusion Taken together, these findings suggest existence of certain geographic, ecological, and demographic risk factors that promote B. anthracis persistence and trasmission in the disease hotspots.

Systemic lupus erythematosus is a chronic, auto-immune inflammatory syndrome with a diverse clinical phenotype. Lupus nephritis (LN) affects 40-60% of patients. There is significant racial disparity in lupus nephritis with Blacks and Hispanics having more aggressive disease and worse outcomes. Moreover, lupus predominantly affects young females and is associated with significant morbidity and mortality. Notably, the number of lupus patients in Kenya has been on the rise over successive years. There is a paucity of data regarding diagnosis, management and outcome of LN in Africa.

Attacks targeting several millions of non-internet based application users are on the rise. These applications such as SMS and USSD typically do not benefit from existing multi-factor authentication methods due to the nature of their interaction interfaces and mode of operations. To address this problem, we propose an approach that augments blockchain with multi-factor authentication based on evidence from blockchain transactions combined with risk analysis. A profile of how a user performs transactions is built overtime and is used to analyse the risk level of each new transaction. If a transaction is flagged as high risk, we generate n-factor layers of authentication using past endorsed blockchain transactions. A demonstration of how we used the proposed approach to authenticate critical financial transactions in a blockchain-based asset financing platform is also discussed.

While it is clear that in many communities ideas about masculinity and circumcision are connected, it is still unclear how young Kenyan men in the former Nyanza province from the traditionally non-circumcising Luo people perceive voluntary medical male circumcision as connected to masculinity and the role of voluntary medical male circumcision in the transition from boyhood to manhood. The objective of this study was to explore norms of masculinity and the decision-making process among Luo young men to provide a better understanding of how circumcision and masculinity relate to cultural norms within this community. The methodology consisted of eight FGDs with male peer groups and 24 in-depth interviews to elicit young men's perceptions of masculinity and voluntary medical male circumcision. Findings from thematic analysis reveal that young men described several key characteristics of masculinity including responsibility, bravery and sexual attractiveness. For some young men, voluntary medical male circumcision has embedded itself into cultural norms of masculinity by being a step in the transition from boyhood to manhood and by being a marker of some of these masculine characteristics. In the case of voluntary medical male circumcision, there may be opportunities to integrate other programming that helps men transition into healthy adulthood.

Climate change has precipitated tremendous changes in the spatial distribution of multiple infectious diseases, particularly those transmitted by arthropod vectors. In this paper, we investigate the effects of global warming on the distribution of Rift Valley fever (RVF) in East Africa based on the 2050 climate change projections from the global climate model (CCSM4). Two of the four representative concentration pathways (RCPs) - RCP 4.5 and RCP 8.5 - are used to cover alternative projections of the radiative forcing levels. Ecological niche modelling, implemented using the Random Forest algorithm, is used for these scenario analyses. Generally, global warming is predicted to cause local shifts on ecological niches of RVF, with some of the infected areas such as those in the coastal Kenya and northern Tanzania being expected to become more suitable for the disease. This indicates the need for an improvement in the delivery of the existing RVF control measures as well as the development of more effective control technologies to better manage the current and future RVF risks.

The burden of anthrax in wildlife is demonstrated through high numbers of sudden mortalities among herbivore species, including endangered animal species. East Africa is home of multiple species of faunal wildlife numbering in the millions but there are limited disease surveillance programmes, resulting in a paucity of information on the role of anthrax and other infectious diseases on declining wildlife populations in the region. We reviewed historical data on anthrax outbreaks from Kenya Wildlife Service (KWS) spanning from 1999 to 2017 in Kenya to determine the burden, characteristics and spatial distribution of anthrax outbreaks. A total of 51 anthrax outbreaks associated with 1014 animal deaths were reported across 20 of 60 wildlife conservation areas located in six of the seven agro-ecological zones. Overall, 67% of the outbreaks were reported during the dry seasons, affecting 24 different wildlife species. Over 90% (22 of 24) of the affected species were herbivore, including 12 grazers, five browsers and five mixed grazers and browsers. Buffaloes (23.5%), black rhinos (21.6%) and elephants (17.6%) were the most frequently affected species. Our findings demonstrate the extensive geographic distribution of wildlife anthrax in the country, making it one of the important infectious diseases that threaten wildlife conservation.

We have been involved in the development of several blockchain-based solutions that largely utilize workflows. Workflows are used to guide users from independent organizations to process and manage transactions, data and documents in a trusted, immutable, and transparent manner for all relevant entities on a given blockchain network. This work discusses our approach to automate the process of creating, updating, and using workflows for blockchain-based solutions. In particular, we present a workflow definition schema using existing templates. We also show how the workflow definition is used to automate the generation of graphical user interfaces and the possibility of generating associated blockchain smart contracts in the future.

Objectives: Voluntary medical male circumcision (VMMC) remains an important component of comprehensive HIV prevention package. Kenya and other key countries are focusing increased attention on achieving large proportions of adolescent circumcisions. Because little is known about the impact of adolescent VMMC counseling, we sought to capture the experiences and opinions of VMMC providers regarding effective adolescent VMMC counseling.Design and Setting: We purposively selected six VMMC sites: three each in Siaya and Kisumu Counties. From each site, we administered key informant interviews to two VMMC providers at a place of their choice for privacy and confidentiality. Outcomes of the study were participant responses to questions regarding their adolescent counseling practices, prior training, and opinions for improvement of counseling practices.Results: Three providers (25%) reported having been trained on adolescent-specific VMMC counseling. Compared to adults, adolescents receive less information during VMMC counseling. There was lack of consistency in counseling procedures, with counselors making subjective judgments as to what content to include, depending on their perception of the sexual experience of the client. Providers recommended greater engagement of parents in the VMMC process, limiting numbers of clients per day to ensure quality of counseling, and allocation of space to facilitate confidentiality.Conclusions: All providers counseling adolescent VMMC clients should receive adolescent-specific counseling training, and adhere to national VMMC guidelines. Measures to assure confidentiality should be taken, and numbers of clients per day limited to ensure quality of counseling services.

Background: Chronic Kidney Disease is a long-term condition caused by damage to both kidneys. It has become a major public health concern worldwide in the past decade and its prevalence is projected to rise in the coming years. Owing to its irreversible nature, renal transplantation has been proven to be the most effective renal replacement therapy. However, it is limited by its high cost and low availability of donor kidneys. Hemodialysis has therefore been adopted widely in Kenya as an alternative therapy for those with End Stage Renal Disease. This has led to an exponential increase in the number of dialysis units in Kenya over the past few years. This therefore raises a concern on the quality of hemodialysis delivered to patients around the country.Objective: To determine dialysis outcomes and practice patterns for Chronic Kidney Disease patients receiving hemodialysis at a private centre in Nairobi, Kenya.Methodology: This was a retrospective study. Records of 43 patients who received dialysis at the centre for more than six months were reviewed and the mid-year results for different parameters obtained.Results: 62.8% were male, 51.2% were Africans with the rest being Asian. The mean age of the patients was 63 years (±16) 79.1% were married. 60.5% had both hypertension and diabetes. Arteriovenous Fistula (81.4%) and Tunneled catheter (18.6%) were the only routes used for vascular access. Majority of the patients (72.1%) received dialysis twice weekly. 93.0% and 97.7% were on iron and erythropoietin supplementation respectively. Most patients (39.53%) had hemoglobin of 10-10.99g/dl. 56.34% of the patients had Parathyroid hormone levels of 150 – 450pg/ml; 73.18% had calcium levels of 2.0 – 2.4mmol/L; 65% had phosphate levels of 1.0 – 1.8mmol/LConclusion: Majority of hemodialysis patients were males, aged above 60 years; Coexistence of diabetes and hypertension was the most common comorbidity among ESRD patients; Majority (67.44%) of the patients had hemoglobin level of 10-12g/dl.; 83% of patients achieved adequate dialysis based on the Urea Reduction Ratio.

Access to electricity is one of the key enablers of socioeconomic development in Sub-Saharan Africa. Microgrid solutions are currently playing an increasing role in providing access to electricity, especially to rural populations whose electricity is not supplied by the national grid. Microgrid developers need to manage their existing sites and expand to new regions. In order for them to manage this expansion effectively and sustainably, they need to make data-driven decisions. Having access to accurate forecasts of electricity demand at the site level is a key input in designing, managing and up-scaling microgrid solutions. Several forecasting mechanisms are proposed for such microgrid developers. Using daily energy consumption data from seven sites operating in Kenya during 2014-2017, it was established that exponential smoothing offers the best out-of-sample forecasting performance with forecast skill exhibited for horizons up to four months ahead.