Genotypic characterization of bacterial isolates causing urinary tract infections among adults at Kiambu Level 5 Hospital, Kenya: selected extended-spectrum ß-lactamase genes and biofilm formation.

The menace of antimicrobial resistance affecting public health is rising globally. Many pathogenic bacteria use mechanisms such as mutations and biofilm formation, significantly reducing the efficacy of antimicrobial agents. In this cross-sectional study, we aimed to determine the prevalence of selected extended-spectrum ß-lactamase (ESßL) genes and analyse the biofilm formation abilities of the isolated bacteria causing urinary tract infection among adult patients seeking Medicare at Kiambu Level 5 Hospital, Kenya. The double-disc synergy test was used for phenotypic identification of ESßL-producing isolates, while microtitre plate assays with some modifications were used for the biofilm formation test. Ten isolates were bioassayed for ESßL genes out of 57 bacterial isolates obtained from urine samples. This study found the bla TEM genes to be the most prevalent ESßL type [10/10 (100 %)], followed by blaOXA and blaSHV genes at 4/10 (40 %) and 3/10 (30 %), respectively. In addition, co-carriage of blaTEM and blaSHV was 50 % lower than that of blaTEM+bla OXA genes at 66.7 % among Escherichia coli isolates studied. Biofilm formation was positive in 36/57 (63.2 %) of the isolates tested, with most being Gram-negative [25/36 (69.4 %)]. Escherichia coli [15/36 (41.7 %)], Klebsiella species [7/36 (19.4 %)] and Staphylococcus aureus [7/36 (19.4 %)] were the dominant biofilm formers. However, there was no significant difference in biofilm formation among all tested isolates, with all isolates recording P-values >0.05. In light of these findings, biofilm formation potential coupled with antimicrobial resistance genes in urinary tract infection isolates may lead to difficult-to-treat infections.

Treatment seeking behaviours, antibiotic use and relationships to multi-drug resistance: A study of urinary tract infection patients in Kenya, Tanzania and Uganda.

Antibacterial resistance (ABR) is a major public health threat. An important accelerating factor is treatment-seeking behaviour, including inappropriate antibiotic (AB) use. In many low- and middle-income countries (LMICs) this includes taking ABs with and without prescription sourced from various providers, including health facilities and community drug sellers. However, investigations of complex treatment-seeking, AB use and drug resistance in LMICs are scarce. The Holistic Approach to Unravel Antibacterial Resistance in East Africa (HATUA) Consortium collected questionnaire and microbiological data from adult outpatients with urinary tract infection (UTI)-like symptoms presenting at healthcare facilities in Kenya, Tanzania and Uganda. Using data from 6,388 patients, we analysed patterns of self-reported treatment seeking behaviours ('patient pathways') using process mining and single-channel sequence analysis. Among those with microbiologically confirmed UTI (n = 1,946), we used logistic regression to assess the relationship between treatment seeking behaviour, AB use, and the likelihood of having a multi-drug resistant (MDR) UTI. The most common treatment pathway for UTI-like symptoms in this sample involved attending health facilities, rather than other providers like drug sellers. Patients from sites in Tanzania and Uganda, where over 50% of patients had an MDR UTI, were more likely to report treatment failures, and have repeat visits to providers than those from Kenyan sites, where MDR UTI proportions were lower (33%). There was no strong or consistent relationship between individual AB use and likelihood of MDR UTI, after accounting for country context. The results highlight the hurdles East African patients face in accessing effective UTI care. These challenges are exacerbated by high rates of MDR UTI, suggesting a vicious cycle of failed treatment attempts and sustained selection for drug resistance. Whilst individual AB use may contribute to the risk of MDR UTI, our data show that factors related to context are stronger drivers of variations in ABR.

Predominance of multidrug-resistant bacteria causing urinary tract infections among symptomatic patients in East Africa: a call for action.

Background: In low- and middle-income countries, antibiotics are often prescribed for patients with symptoms of urinary tract infections (UTIs) without microbiological confirmation. Inappropriate antibiotic use can contribute to antimicrobial resistance (AMR) and the selection of MDR bacteria. Data on antibiotic susceptibility of cultured bacteria are important in drafting empirical treatment guidelines and monitoring resistance trends, which can prevent the spread of AMR. In East Africa, antibiotic susceptibility data are sparse. To fill the gap, this study reports common microorganisms and their susceptibility patterns isolated from patients with UTI-like symptoms in Kenya, Tanzania and Uganda. Within each country, patients were recruited from three sites that were sociodemographically distinct and representative of different populations. Methods: UTI was defined by the presence of >104 cfu/mL of one or two uropathogens in mid-stream urine samples. Identification of microorganisms was done using biochemical methods. Antimicrobial susceptibility testing was performed by the Kirby-Bauer disc diffusion assay. MDR bacteria were defined as isolates resistant to at least one agent in three or more classes of antimicrobial agents. Results: Microbiologically confirmed UTI was observed in 2653 (35.0%) of the 7583 patients studied. The predominant bacteria were Escherichia coli (37.0%), Staphylococcus spp. (26.3%), Klebsiella spp. (5.8%) and Enterococcus spp. (5.5%). E. coli contributed 982 of the isolates, with an MDR proportion of 52.2%. Staphylococcus spp. contributed 697 of the isolates, with an MDR rate of 60.3%. The overall proportion of MDR bacteria (n = 1153) was 50.9%. Conclusions: MDR bacteria are common causes of UTI in patients attending healthcare centres in East African countries, which emphasizes the need for investment in laboratory culture capacity and diagnostic algorithms to improve accuracy of diagnosis that will lead to appropriate antibiotic use to prevent and control AMR.

Using queueing models as a decision support tool in allocating point-of-care HIV viral load testing machines in Kisumu County, Kenya.

Point-of-care (POC) technologies-including HIV viral load (VL) monitoring-are expanding globally, including in resource-limited settings. Modelling could allow decision-makers to consider the optimal strategy(ies) to maximize coverage and access, minimize turnaround time (TAT) and minimize cost with limited machines. Informed by formative qualitative focus group discussions with stakeholders focused on model inputs, outputs and format, we created an optimization model incorporating queueing theory and solved it using integer programming methods to reflect HIV VL monitoring in Kisumu County, Kenya. We modelled three scenarios for sample processing: (1) centralized laboratories only, (2) centralized labs with 7 existing POC 'hub' facilities and (3) centralized labs with 7 existing and 1-7 new 'hub' facilities. We calculated total TAT using the existing referral network for scenario 1 and solved for the optimal referral network by minimizing TAT for scenarios 2 and 3. We conducted one-way sensitivity analyses, including distributional fairness in each sub-county. Through two focus groups, stakeholders endorsed the provisionally selected model inputs, outputs and format with modifications incorporated during model-building. In all three scenarios, the largest component of TAT was time spent at a facility awaiting sample batching and transport (scenarios 1-3: 78.7%, 89.9%, 91.8%) and waiting time at the testing site (18.7%, 8.7%, 7.5%); transportation time contributed minimally to overall time (2.6%, 1.3%, 0.7%). In scenario 1, the average TAT was 39.8 h (SD: 2.9), with 1077 h that samples spent cumulatively in the VL processing system. In scenario 2, the average TAT decreased to 33.8 h (SD: 4.8), totalling 430 h. In scenario 3, the average TAT decreased nearly monotonically with each new machine to 31.1 h (SD: 8.4) and 346 total hours. Frequency of sample batching and processing rate most impacted TAT, and inclusion of distributional fairness minimally impacted TAT. In conclusion, a stakeholder-informed resource allocation model identified optimal POC VL hub allocations and referral networks. Using existing-and adding new-POC machines could markedly decrease TAT, as could operational changes.

The East African Community mobile laboratory network prepares for monkeypox outbreaks.

In response to the largest recorded monkeypox virus outbreak outside of endemic Central and Western Africa, the East African Community (EAC), in cooperation with the Bernhard-Nocht- Institute for Tropical Medicine, coordinated an emergency monkeypox diagnostic training for the East African Region. As of June 2022, the Democratic Republic of Congo reported a steady increase of suspected monkeypox cases, increasing the risk of spill-over into the remaining six EAC Partner States. Within the existing EAC Mobile Laboratories project, laboratory experts of the National Public Health Laboratories of the remaining six EAC Partner States (Burundi, Rwanda, Tanzania, Kenya, Uganda, and South Sudan) participated in the workshop and were trained in the reception of suspect samples, DNA extraction and diagnosis using real-time polymerase chain reaction (RT-PCR). The EAC region is now equipped with the tools to prepare and rapidly respond to any emerging monkeypox outbreak.

Evaluation of the diagnostic performance of the urine dipstick test for the detection of urinary tract infections in patients treated in Kenyan hospitals.

Introduction: Culture is the gold-standard diagnosis for urinary tract infections (UTIs). However, most hospitals in low-resource countries lack adequately equipped laboratories and relevant expertise to perform culture and, therefore, rely heavily on dipstick tests for UTI diagnosis. Research gap: In many Kenyan hospitals, routine evaluations are rarely done to assess the accuracy of popular screening tests such as the dipstick test. As such, there is a substantial risk of misdiagnosis emanating from inaccuracy in proxy screening tests. This may result in misuse, under-use or over-use of antimicrobials. Aim: The present study aimed to assess the accuracy of the urine dipstick test as a proxy for the diagnosis of UTIs in selected Kenyan hospitals. Methods: A hospital-based cross-sectional method was used. The utility of dipstick in the diagnosis of UTIs was assessed using midstream urine against culture as the gold standard. Results: The dipstick test predicted 1416 positive UTIs, but only 1027 were confirmed positive by culture, translating to a prevalence of 54.1 %. The sensitivity of the dipstick test was better when leucocytes and nitrite tests were combined (63.1 %) than when the two tests were separate (62.6 and 50.7 %, respectively). Similarly, the two tests combined had a better positive predictive value (87.0 %) than either test alone. The nitrite test had the best specificity (89.8 %) and negative predictive value (97.4 %) than leucocytes esterase (L.E) or both tests combined. In addition, sensitivity in samples from inpatients (69.2 %) was higher than from outpatients (62.7 %). Furthermore, the dipstick test had a better sensitivity and positive predictive value among female (66.0 and 88.6 %) than male patients (44.3 and 73.9 %). Among the various patient age groups, the dipstick test's sensitivity and positive predictive value were exceptionally high in patients ≥75 years old (87.5 and 93.3 %). Conclusion: Discrepancies in prevalence from the urine dipstick test and culture, the gold standard, indicate dipstick test inadequacy for accurate UTI diagnosis. The finding also demonstrates the need for urine culture for accurate UTI diagnosis. However, considering it is not always possible to perform a culture, especially in low-resource settings, future studies are needed to combine specific UTI symptoms and dipstick results to assess possible increases in the test's sensitivity. There is also a need to develop readily available and affordable algorithms that can detect UTIs where culture is not available.

Epidemiological connectivity between humans and animals across an urban landscape.

Urbanization is predicted to be a key driver of disease emergence through human exposure to novel, animal-borne pathogens. However, while we suspect that urban landscapes are primed to expose people to novel animal-borne diseases, evidence for the mechanisms by which this occurs is lacking. To address this, we studied how bacterial genes are shared between wild animals, livestock, and humans (n = 1,428) across Nairobi, Kenya-one of the world's most rapidly developing cities. Applying a multilayer network framework, we show that low biodiversity (of both natural habitat and vertebrate wildlife communities), coupled with livestock management practices and more densely populated urban environments, promotes sharing of Escherichia coli-borne bacterial mobile genetic elements between animals and humans. These results provide empirical support for hypotheses linking resource provision, the biological simplification of urban landscapes, and human and livestock demography to urban dynamics of cross-species pathogen transmission at a landscape scale. Urban areas where high densities of people and livestock live in close association with synanthropes (species such as rodents that are more competent reservoirs for zoonotic pathogens) should be prioritized for disease surveillance and control.

Unravelling patient pathways in the context of antibacterial resistance in East Africa.

BACKGROUND: A key factor driving the development and maintenance of antibacterial resistance (ABR) is individuals' use of antibiotics (ABs) to treat illness. To better understand motivations and context for antibiotic use we use the concept of a patient treatment-seeking pathway: a treatment journey encompassing where patients go when they are unwell, what motivates their choices, and how they obtain antibiotics. This paper investigates patterns and determinants of patient treatment-seeking pathways, and how they intersect with AB use in East Africa, a region where ABR-attributable deaths are exceptionally high. METHODS: The Holistic Approach to Unravelling Antibacterial Resistance (HATUA) Consortium collected quantitative data from 6,827 adult outpatients presenting with urinary tract infection (UTI) symptoms in Kenya, Tanzania, and Uganda between February 2019- September 2020, and conducted qualitative in-depth patient interviews with a subset (n = 116). We described patterns of treatment-seeking visually using Sankey plots and explored explanations and motivations using mixed-methods. Using Bayesian hierarchical regression modelling, we investigated the associations between socio-demographic, economic, healthcare, and attitudinal factors and three factors related to ABR: self-treatment as a first step, having a multi-step treatment pathway, and consuming ABs. RESULTS: Although most patients (86%) sought help from medical facilities in the first instance, many (56%) described multi-step, repetitive treatment-seeking pathways, which further increased the likelihood of consuming ABs. Higher socio-economic status patients were more likely to consume ABs and have multi-step pathways. Reasons for choosing providers (e.g., cost, location, time) were conditioned by wider structural factors such as hybrid healthcare systems and AB availability. CONCLUSION: There is likely to be a reinforcing cycle between complex, repetitive treatment pathways, AB consumption and ABR. A focus on individual antibiotic use as the key intervention point in this cycle ignores the contextual challenges patients face when treatment seeking, which include inadequate access to diagnostics, perceived inefficient public healthcare and ease of purchasing antibiotics without prescription. Pluralistic healthcare landscapes may promote more complex treatment seeking and therefore inappropriate AB use. We recommend further attention to healthcare system factors, focussing on medical facilities (e.g., accessible diagnostics, patient-doctor interactions, information flows), and community AB access points (e.g., drug sellers).

Bacterial etiology of urinary tract infections in patients treated at Kenyan health facilities and their resistance towards commonly used antibiotics.

BACKGROUND: Evidence-based empirical antibiotic prescribing requires knowledge of local antimicrobial resistance patterns. The spectrum of pathogens and their susceptibility strongly influences guidelines for empirical therapies for urinary tract infections (UTI) management. OBJECTIVE: This study aimed to determine the prevalence of UTI causative bacteria and their corresponding antibiotic resistance profiles in three counties of Kenya. Such data could be used to determine the optimal empirical therapy. METHODS: In this cross-sectional study, urine samples were collected from patients who presented with symptoms suggestive of UTI in the following healthcare facilities; Kenyatta National Hospital, Kiambu Hospital, Mbagathi, Makueni, Nanyuki, Centre for Microbiology Research, and Mukuru Health Centres. Urine cultures were done on Cystine Lactose Electrolyte Deficient (CLED) to isolate UTI bacterial etiologies, while antibiotic sensitivity testing was done using the Kirby-Bauer disk diffusion using CLSI guidelines and interpretive criteria. RESULTS: A total of 1,027(54%) uropathogens were isolated from the urine samples of 1898 participants. Staphylococcus spp. and Escherichia coli were the main uropathogens at 37.6% and 30.9%, respectively. The percentage resistance to commonly used drugs for the treatment of UTI were as follows: trimethoprim (64%), sulfamethoxazole (57%), nalidixic acid(57%), ciprofloxacin (27%), amoxicillin-clavulanic acid (5%), and nitrofurantoin (9%) and cefixime (9%). Resistance rates to broad-spectrum antimicrobials, such as ceftazidime, gentamicin, and ceftriaxone, were 15%, 14%, and 11%, respectively. Additionally, the proportion of Multidrug-resistant (MDR) bacteria was 66%. CONCLUSION: High resistance rates toward fluoroquinolones, sulfamethoxazole, and trimethoprim were reported. These antibiotics are commonly used drugs as they are inexpensive and readily available. Based on these findings, more robust standardised surveillance is needed to confirm the patterns observed while recognising the potential impact of sampling biases on observed resistance rates.

Treatment seeking behaviours, antibiotic use and relationships to multi-drug resistance: A study of urinary tract infection patients in Kenya, Tanzania and Uganda.

Antibacterial resistance (ABR) is a major public health threat. An important accelerating factor is treatment-seeking behaviours, including inappropriate antibiotic (AB) use. In many low- and middle-income countries (LMICs) this includes taking ABs with and without prescription sourced from various providers, including health facilities and community drug sellers. However, investigations of complex treatment-seeking, AB use and drug resistance in LMICs are scarce. The Holistic Approach to Unravel Antibacterial Resistance in East Africa (HATUA) Consortium collected questionnaire and microbiological data from 6,827 adult outpatients with urinary tract infection (UTI)-like symptoms presenting at healthcare facilities in Kenya, Tanzania and Uganda. Among 6,388 patients we analysed patterns of self-reported treatment seeking behaviours ('patient pathways') using process mining and single-channel sequence analysis. Of those with microbiologically confirmed UTI (n=1,946), we used logistic regression to assessed the relationship between treatment seeking behaviour, AB use, and likelihood of having a multi-drug resistant (MDR) UTI. The most common treatment pathways for UTI-like symptoms included attending health facilities, rather than other providers (e.g. drug sellers). Patients from the sites sampled in Tanzania and Uganda, where prevalence of MDR UTI was over 50%, were more likely to report treatment failures, and have repeated visits to clinics/other providers, than those from Kenyan sites, where MDR UTI rates were lower (33%). There was no strong or consistent relationship between individual AB use and risk of MDR UTI, after accounting for country context. The results highlight challenges East African patients face in accessing effective UTI treatment. These challenges increase where rates of MDR UTI are higher, suggesting a reinforcing circle of failed treatment attempts and sustained selection for drug resistance. Whilst individual behaviours may contribute to the risk of MDR UTI, our data show that factors related to context are stronger drivers of ABR.

Antimicrobial Resistant Pathogens Detected in Raw Pork and Poultry Meat in Retailing Outlets in Kenya.

There is increasing proof of bacterial resistance to antibiotics all over the world, and this puts the effectiveness of antimicrobials that have been essential in decreasing disease mortality and morbidity at stake. The WHO has labeled some classes of antimicrobials as vitally important to human health. Bacteria from animals are thought to be reservoirs of resistance genes that can be transferred to humans through the food chain. This study aimed to identify the resistance patterns of bacteria from pork and poultry meat samples purchased from leading retail outlets in Kenya. Of the 393 samples collected, 98.4% of pork and 96.6% of poultry were contaminated with high levels of bacteria. Among the 611 bacterial isolates recovered, 38.5% were multi-drug resistant. This resistance was noted for critically essential antimicrobials (according to the WHO) such as rifampicin (96%), ampicillin (35%), cefotaxime (9%), cefepime (6%), and ciprofloxacin (6%). Moreover, there was high resistance to key antimicrobials for veterinary medicine such as tetracycline (39%), sulfamethoxazole (33%), and trimethoprim (30%). It is essential to spread awareness about the judicious use of antibiotics and take preventive measures to reduce disease burden.

Diagnostic accuracy of the Panbio COVID-19 antigen rapid test device for SARS-CoV-2 detection in Kenya, 2021: A field evaluation.

BACKGROUND: Accurate and timely diagnosis is essential in limiting the spread of SARS-CoV-2 infection. The reference standard, rRT-PCR, requires specialized laboratories, costly reagents, and a long turnaround time. Antigen RDTs provide a feasible alternative to rRT-PCR since they are quick, relatively inexpensive, and do not require a laboratory. The WHO requires that Ag RDTs have a sensitivity ≥80% and specificity ≥97%. METHODS: This evaluation was conducted at 11 health facilities in Kenya between March and July 2021. We enrolled persons of any age with respiratory symptoms and asymptomatic contacts of confirmed COVID-19 cases. We collected demographic and clinical information and two nasopharyngeal specimens from each participant for Ag RDT testing and rRT-PCR. We calculated the diagnostic performance of the Panbio™ Ag RDT against the US Centers for Disease Control and Prevention's (CDC) rRT-PCR test. RESULTS: We evaluated the Ag RDT in 2,245 individuals where 551 (24.5%, 95% CI: 22.8-26.3%) tested positive by rRT-PCR. Overall sensitivity of the Ag RDT was 46.6% (95% CI: 42.4-50.9%), specificity 98.5% (95% CI: 97.8-99.0%), PPV 90.8% (95% CI: 86.8-93.9%) and NPV 85.0% (95% CI: 83.4-86.6%). Among symptomatic individuals, sensitivity was 60.6% (95% CI: 54.3-66.7%) and specificity was 98.1% (95% CI: 96.7-99.0%). Among asymptomatic individuals, sensitivity was 34.7% (95% CI 29.3-40.4%) and specificity was 98.7% (95% CI: 97.8-99.3%). In persons with onset of symptoms <5 days (594/876, 67.8%), sensitivity was 67.1% (95% CI: 59.2-74.3%), and 53.3% (95% CI: 40.0-66.3%) among those with onset of symptoms >7 days (157/876, 17.9%). The highest sensitivity was 87.0% (95% CI: 80.9-91.8%) in symptomatic individuals with cycle threshold (Ct) values ≤30. CONCLUSION: The overall sensitivity and NPV of the Panbio™ Ag RDT were much lower than expected. The specificity of the Ag RDT was high and satisfactory; therefore, a positive result may not require confirmation by rRT-PCR. The kit may be useful as a rapid screening tool only for symptomatic patients in high-risk settings with limited access to rRT-PCR. A negative result should be interpreted based on clinical and epidemiological information and may require retesting by rRT-PCR.

The role of multidimensional poverty in antibiotic misuse: a mixed-methods study of self-medication and non-adherence in Kenya, Tanzania, and Uganda.

BACKGROUND: Poverty is a proposed driver of antimicrobial resistance, influencing inappropriate antibiotic use in low-income and middle-income countries (LMICs). However, at subnational levels, studies investigating multidimensional poverty and antibiotic misuse are sparse, and the results are inconsistent. We aimed to investigate the relationship between multidimensional poverty and antibiotic use in patient populations in Kenya, Tanzania, and Uganda. METHODS: In this mixed-methods study, the Holistic Approach to Unravelling Antimicrobial Resistance (HATUA) Consortium collected data from 6827 outpatients (aged 18 years and older, or aged 14-18 years and pregnant) with urinary tract infection (UTI) symptoms in health-care facilities in Kenya, Tanzania, and Uganda. We used Bayesian hierarchical modelling to investigate the association between multidimensional poverty and self-reported antibiotic self-medication and non-adherence (ie, skipping a dose and not completing the course). We analysed linked qualitative in-depth patient interviews and unlinked focus-group discussions with community members. FINDINGS: Between Feb 10, 2019, and Sept 10, 2020, we collected data on 6827 outpatients, of whom 6345 patients had complete data; most individuals were female (5034 [79·2%]), younger than 35 years (3840 [60·5%]), worked in informal employment (2621 [41·3%]), and had primary-level education (2488 [39·2%]). Antibiotic misuse was more common among those least deprived, and lowest among those living in severe multidimensional poverty. Regardless of poverty status, difficulties in affording health care, and more familiarity with antibiotics, were related to more antibiotic misuse. Qualitative data from linked qualitative in-depth patient interviews (n=82) and unlinked focus-group discussions with community members (n=44 groups) suggested that self-medication and treatment non-adherence were driven by perceived inconvenience of the health-care system, financial barriers, and ease of unregulated antibiotic access. INTERPRETATION: We should not assume that higher deprivation drives antibiotic misuse. Structural barriers such as inefficiencies in public health care, combined with time and financial constraints, fuel alternative antibiotic access points and treatment non-adherence across all levels of deprivation. In designing interventions to reduce antibiotic misuse and address antimicrobial resistance, greater attention is required to these structural barriers that discourage optimal antibiotic use at all levels of the socioeconomic hierarchy in LMICs. FUNDING: UK National Institute for Health Research, UK Medical Research Council, and the Department of Health and Social Care.

Genomic epidemiology of Escherichia coli: antimicrobial resistance through a One Health lens in sympatric humans, livestock and peri-domestic wildlife in Nairobi, Kenya.

BACKGROUND: Livestock systems have been proposed as a reservoir for antimicrobial-resistant (AMR) bacteria and AMR genetic determinants that may infect or colonise humans, yet quantitative evidence regarding their epidemiological role remains lacking. Here, we used a combination of genomics, epidemiology and ecology to investigate patterns of AMR gene carriage in Escherichia coli, regarded as a sentinel organism. METHODS: We conducted a structured epidemiological survey of 99 households across Nairobi, Kenya, and whole genome sequenced E. coli isolates from 311 human, 606 livestock and 399 wildlife faecal samples. We used statistical models to investigate the prevalence of AMR carriage and characterise AMR gene diversity and structure of AMR genes in different host populations across the city. We also investigated household-level risk factors for the exchange of AMR genes between sympatric humans and livestock. RESULTS: We detected 56 unique acquired genes along with 13 point mutations present in variable proportions in human and animal isolates, known to confer resistance to nine antibiotic classes. We find that AMR gene community composition is not associated with host species, but AMR genes were frequently co-located, potentially enabling the acquisition and dispersal of multi-drug resistance in a single step. We find that whilst keeping livestock had no influence on human AMR gene carriage, the potential for AMR transmission across human-livestock interfaces is greatest when manure is poorly disposed of and in larger households. CONCLUSIONS: Findings of widespread carriage of AMR bacteria in human and animal populations, including in long-distance wildlife species, in community settings highlight the value of evidence-based surveillance to address antimicrobial resistance on a global scale. Our genomic analysis provided an in-depth understanding of AMR determinants at the interfaces of One Health sectors that will inform AMR prevention and control.

Draft Genome Sequence of an Enterotoxigenic Escherichia coli Strain Carrying Genes for Colonization Surface Antigen 13 and a Heat-Labile Toxin.

Here, we report the draft genome of ESEI_597, an enterotoxigenic Escherichia coli (ETEC) strain harboring genes encoding colonization surface antigen 13 (CS13) and a heat-labile toxin. The ESEI_597 strain was isolated from an 8-month-old child living in Korogocho, Kenya, in 2013.

Transmission networks of SARS-CoV-2 in Coastal Kenya during the first two waves: A retrospective genomic study.

Background: Detailed understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) regional transmission networks within sub-Saharan Africa is key for guiding local public health interventions against the pandemic. Methods: Here, we analysed 1139 SARS-CoV-2 genomes from positive samples collected between March 2020 and February 2021 across six counties of Coastal Kenya (Mombasa, Kilifi, Taita Taveta, Kwale, Tana River, and Lamu) to infer virus introductions and local transmission patterns during the first two waves of infections. Virus importations were inferred using ancestral state reconstruction, and virus dispersal between counties was estimated using discrete phylogeographic analysis. Results: During Wave 1, 23 distinct Pango lineages were detected across the six counties, while during Wave 2, 29 lineages were detected; 9 of which occurred in both waves and 4 seemed to be Kenya specific (B.1.530, B.1.549, B.1.596.1, and N.8). Most of the sequenced infections belonged to lineage B.1 (n = 723, 63%), which predominated in both Wave 1 (73%, followed by lineages N.8 [6%] and B.1.1 [6%]) and Wave 2 (56%, followed by lineages B.1.549 [21%] and B.1.530 [5%]). Over the study period, we estimated 280 SARS-CoV-2 virus importations into Coastal Kenya. Mombasa City, a vital tourist and commercial centre for the region, was a major route for virus imports, most of which occurred during Wave 1, when many Coronavirus Disease 2019 (COVID-19) government restrictions were still in force. In Wave 2, inter-county transmission predominated, resulting in the emergence of local transmission chains and diversity. Conclusions: Our analysis supports moving COVID-19 control strategies in the region from a focus on international travel to strategies that will reduce local transmission. Funding: This work was funded by The Wellcome (grant numbers: 220985, 203077/Z/16/Z, 220977/Z/20/Z, and 222574/Z/21/Z) and the National Institute for Health and Care Research (NIHR), project references: 17/63/and 16/136/33 using UK Aid from the UK government to support global health research, The UK Foreign, Commonwealth and Development Office. The views expressed in this publication are those of the author(s) and not necessarily those of the funding agencies.

Population genomics of Escherichia coli in livestock-keeping households across a rapidly developing urban landscape.

Quantitative evidence for the risk of zoonoses and the spread of antimicrobial resistance remains lacking. Here, as part of the UrbanZoo project, we sampled Escherichia coli from humans, livestock and peri-domestic wildlife in 99 households across Nairobi, Kenya, to investigate its distribution among host species in this rapidly developing urban landscape. We performed whole-genome sequencing of 1,338 E. coli isolates and found that the diversity and sharing patterns of E. coli were heavily structured by household and strongly shaped by host type. We also found evidence for inter-household and inter-host sharing and, importantly, between humans and animals, although this occurs much less frequently. Resistome similarity was differently distributed across host and household, consistent with being driven by shared exposure to antimicrobials. Our results indicate that a large, epidemiologically structured sampling framework combined with WGS is needed to uncover strain-sharing events among different host populations in complex environments and the major contributing pathways that could ultimately drive the emergence of zoonoses and the spread of antimicrobial resistance.

An Android-Based Mobile App (ARVPredictor) for the Detection of HIV Drug-Resistance Mutations and Treatment at the Point of Care: Development Study.

BACKGROUND: HIV/AIDS remains one of the major global human health challenges, especially in resource-limited environments. By 2017, over 77.3 million people were infected with the disease, and approximately 35.4 million individuals had already died from AIDS-related illnesses. Approximately 21.7 million people were accessing ART with significant clinical outcomes. However, numerous challenges are experienced in the delivery and accurate interpretation of data on patients with HIV data by various health care providers at different care levels. Mobile health (mHealth) technology is progressively making inroads into the health sector as well as medical research. Different mobile devices have become common in health care settings, leading to rapid growth in the development of downloadable software specifically designed to fulfill particular health-related purposes. OBJECTIVE: We developed a mobile-based app called ARVPredictor and demonstrated that it can accurately define HIV-1 drug-resistance mutations in the HIV pol gene for use at the point of care. METHODS: ARVPredictor was designed using Android Studio with Java as the programming language and is compatible with both Android and iOS. The app system is hosted on Nginx Server, and network calls are built on PHP's Laravel framework handled by the Retrofit Library. The DigitalOcean offers a high-performance and stable cloud computing platform for ARVPredictor. This mobile app is enlisted in the Google Play Store as an "ARVPredictor" and the source code is available under MIT permissive license at a GitHub repository. To test for agreement between the ARVPredictor and Stanford HIV Database in detecting HIV subtype and NNRT and NRTI mutations, a total of 100 known HIV sequences were evaluated. RESULTS: The mobile-based app (ARVPredictor) takes in a set of sequences or known mutations (protease, reverse transcriptase and integrase). It then returns inferred levels of resistance to selected nucleoside, nonnucleoside protease, and integrase inhibitors for accurate HIV/AIDS management at the point of care. The ARVPredictor identified similar HIV subtypes in 98/100 sequences compared with the Stanford HIV Database (κ=0.98, indicating near perfect agreement). There were 89/100 major NNRTI and NRTI mutations identified by ARVPredictor, similar to the Stanford HIV Database (κ=0.89, indicating near perfect agreement). Eight mutations classified as major by the Stanford HIV Database were classified as others by ARVPredictor. CONCLUSIONS: The ARVPredictor largely agrees with the Stanford HIV Database in identifying both major and minor proteases, reverse transcriptase, and integrase mutations. The app can be conveniently used robustly at the point of care by HIV/AIDS care providers to improve the management of HIV infection.

Impact of nucleos(t)ide reverse transcriptase inhibitor resistance on dolutegravir and protease-inhibitor-based regimens in children and adolescents in Kenya.

We assessed the impact of using dolutegravir or a protease inhibitor with an inactive nucleoside-reverse transcriptase inhibitor (NRTI) in children and adolescents. We observed high-levels of viral suppression among those on tenofovir-lamivudine-dolutegravir even in presence of an inactive NRTI backbone but lower levels among those on protease inhibitors, especially those retained on an inactive abacavir. Although tenofovir may be recycled with dolutegravir, more studies are needed to determine if abacavir can be reused with dolutegravir or protease inhibitors.