Oral Presentations

Background:
Kenya’s mass Insecticide-Treated Net (ITN) campaigns achieve high coverage, which declines after campaigns due to wear, loss, household mobility, and demographic changes. A Continuous Community Net Distribution (CCND) pilot in Kirinyaga County addressed this gap through a community-anchored approach aligned with the national Community Health Strategy (CHS). The pilot assessed feasibility and efficiency in providing targeted ITN replacement, strengthening ITN durability surveillance using the WHO Proportionate Hole Index (PHI), and enhancing stock visibility through digital integration.

Methods:
A digital CCND system was designed by integrating workflows within eCHIS, DHIS2, DigiMal-KE, and the KEMSA LMIS to support household assessment, ITN needs generation, e-voucher allocation and redemption, inventory management, and SMS notifications. Preparatory activities included user acceptance testing, microplanning, quantification, system configuration, stakeholder engagement, and training. A 14-day implementation included community sensitization, a 5-day household ITN assessment by CHPs, and redemption of e-vouchers at link facilities. ITNs were categorized as usable, repairable, or replaceable based on PHI. CHPs referred eligible individuals for routine maternal and child health (MCH) services.

Results:
Training was done for 10 supervisors, 13 CHPs, 3 CHAs, 3 assistant chiefs, and 12 village elders. Of 2,817 households, 1,197 (43.2%) were assessed, generating 1,156 e-vouchers. Eight pregnant women and 22 children under one were referred for ITN access at MCH. Of 1,950 ITNs delivered to three link facilities, 1,816 (93.1%) were allocated through e-vouchers, with a mean of 1.6 ITNs per voucher, and 64.4% of e-vouchers were redeemed, distributing 1,183 ITNs (65.1%). Digital allocation enabled real-time tracking at the facility level.

Conclusion:
The pilot demonstrated feasible digital integration to improve efficiency, accountability, and decision-making. E-vouchers and facility stock management were automated, each ITN linked to verified households, while real-time dashboards enabled timely distribution adjustments. Strengthening eCHIS data completeness is recommended before scaling. CCND should complement mass campaigns.

Introduction
Technological advancements are increasingly recognized as critical enablers of resilient health systems, particularly in low- and middle-income countries.LMICS face workforce shortages, geographical barriers and rising burdens of non-communicable diseases (NCDs). In Kenya, county health systems play a central role in service delivery, yet access disparities persist, especially in rural settings. The Murang’a County Telemedicine Programme, launched in late 2024, represents a pioneering public-sector digital health innovation designed to enhance access, continuity of care and system responsiveness.

Aim
To demonstrate how a county-led telemedicine model can strengthen public health systems, improve healthcare access and contribute to pandemic preparedness through digital transformation.

Methods
The programme adopts a hub-and-spoke model, with a central telemedicine hub at Muriranjas Level 4 Hospital linked to 36 peripheral health facilities across all wards. Consultations are conducted remotely by trained clinicians using the AfyaKe electronic health record system, ensuring real-time data capture and interoperability across facilities. The programme integrates pharmacy, laboratory and referral systems, enabling comprehensive virtual care. Routine programme data, including service utilization, disease patterns and operational metrics, were analyzed to assess performance.

Results

Since implementation, the programme has registered over 21,500 patients and delivered more than 90,000 consultations averaging 7,000 monthly. It has reduced referrals to higher-level facilities by up to 40%, easing congestion and improving system efficiency. Treatment adherence among patients with NCDs increased by approximately 50%, while follow-up attendance exceeded 80%. Patients experienced 70-90% reductions in transport costs. Integrated digital systems enhanced real-time surveillance, data-driven decision-making and continuity of care across facilities.

Conclusion
Murang’a County’s Telemedicine Programme provides a scalable, government-led model for integrating technological innovations into public health systems. Its success highlights the potential of telemedicine to advance universal health coverage, strengthen health security and build resilient health systems capable of responding to current and future health challenges.

Escherichia coli is a priority pathogen for antimicrobial resistance (AMR) surveillance and one of the most frequently isolated bacterial pathogens in clinical samples. Its primarily transmitted through contaminated water, food, and the fecal–oral route. The World Health Organization (WHO) recommends E. coli as the primary indicator organism for assessing fecal contamination in drinking water. Globally, about 2 billion people consume water contaminated with fecal matter, including over 50% of the population in sub-Saharan Africa and more than half of the population in Kenya. This study aimed to determine the prevalence, pathotype distribution and antimicrobial susceptibility profiles of E. coli isolated from informal water sources in Kibera.

A total of 72 water samples were collected in July 2024 and analyzed using the membrane filtration method. Antimicrobial susceptibility testing was performed using the Kirby–Bauer disk diffusion method, and results were interpreted according to Clinical and Laboratory Standards Institute (2024) guidelines. E. coli pathotypes were identified using real-time multiplex polymerase chain reaction.

Overall, 29.2% (21out of 72) of water samples were contaminated with E. coli. The highest contamination rates were observed in rainwater (100%), water trucks (75.0%), and boreholes (36.0%). Untreated water had significantly higher contamination levels (63.6%) compared to treated sources (14.9%) (p < 0.0001).

The isolates showed high resistance to ampicillin (90.5%) and cefuroxime (76.2%), while remaining largely susceptible to gentamicin (95.2%) and meropenem (93.7%). Multidrug resistance was observed in 52.4% of isolates, with some showing resistance to up to eleven antibiotics. Pathogenic E. coli pathotypes identified included Enteroaggregative (24%), Enterotoxigenic (14%), Enteropathogenic (10%), Enteroinvasive (5%), and mixed-pathotype strains (14%).

Informal water sources in Kibera harbor a substantial burden of multidrug-resistant and pathogenic E. coli, posing a significant public health risk, highlighting an urgent need for targeted water treatment interventions, strengthened sanitation infrastructure and integration of environmental AMR surveillance.

Introduction: Kenya’s counties faced rising public health emergencies driven by infectious disease outbreaks, climate variability, and cross-border population movement. Although surveillance systems such as the Integrated Disease Surveillance and Response (IDSR) framework and the District Health Information System (DHIS2) generated substantial epidemiological data, emergency coordination often remained fragmented. Limited real-time situational awareness and the absence of digital Public Health Emergency Operations Center (PHEOC) coordination tools constrained timely decision-making. Border counties such as Busia experienced heightened vulnerability due to population mobility and trade, underscoring the need for interoperable coordination systems aligned with the International Health Regulations (2005).

Aim: The study aimed to design and pilot PHEOC-Connect, a modular digital platform to strengthen county-level public health emergency preparedness, detection, and response coordination.

Methods: PHEOC-Connect integrated incident reporting, situation reporting (SitRep), and emergency resource coordination within a unified platform. Key functionalities included real-time event monitoring, geo-referenced incident tracking across county and facility levels, and standardized WATCH→ALERT→RESPONSE escalation workflows. Role-based dashboards supported emergency response teams in monitoring events and coordinating actions. The platform interoperated with existing surveillance systems, including IDSR and DHIS2. A 12-month pilot implementation was planned in Busia County through a public–private partnership model.

Results: Evaluation indicators included a ≥30% reduction in incident detection-to-escalation time, ≥80% completeness and timeliness of situation reports, and improved coordination between County Health Management Teams and surveillance units. Expected outputs included a functional county digital PHEOC dashboard, standardized response workflows, and improved real-time situational awareness.

Conclusion: Interoperable digital platforms linking surveillance data with operational coordination strengthened sub-national emergency preparedness. PHEOC-Connect demonstrated potential as a scalable innovation supporting a resilient national PHEOC ecosystem for pandemics, cross-border threats, and climate-sensitive health emergencies across Kenya’s counties.

Background: Globally, approximately 15% of employees experience a mental health disorder. Healthcare workers (HCWs) are particularly vulnerable due to high workload and emotional stress, which may lead to absenteeism, reduced productivity, medical errors, and workforce attrition. In Kenya, limited data exist on the burden of depression and substance use disorder (SUD) among HCWs. This study assessed the prevalence and factors associated with depression and SUD among HCWs.

Methods: We conducted a cross-sectional study between April and August 2025 in 30 health facilities across 10 counties in Kenya. Participants were selected using stratified random sampling. Standardized tools were used to assess depression (Patient Health Questionnaire-9), burnout (Maslach Burnout Inventory), and SUD (Drug Abuse Screening Test-10). Information on workplace mental health policies, socio-demographic, and occupational factors was collected. Descriptive statistics were summarized using means and proportions. Associations between covariates and outcomes were assessed using chi-square tests. Variables with a p-value < 0.2 were included in logistic regression to identify independent associations. Data were analysed using Epi Info version 7.0 and Microsoft Excel 2016.

Results: We enrolled 604 respondents; 54.1% (327) were male, and 50.3% (304) were aged 30–39 years. The prevalence of depression was 6.1% (95% CI: 4.5%–8.3%), and SUD was 8.8% (95% CI: 6.8%–11.3%). Burnout affected 29.1% (176) of HCWs and was independently associated with both depression (AOR 2.4, 95% CI: 1.1–5.50) and SUD (AOR 14.4, 95% CI: 5.2–39.7). Being male (AOR 3.4, 95% CI: 1.6–7.2) and having a poor personal wellness score (AOR 5.2, 95% CI: 1.2–22.8) were independently associated with SUD.

Conclusion: We report a modest prevalence of depression and SUD among HCWs in Kenya, with burnout as an independent predictor. We recommend workplace mental health interventions to reduce burnout and improve HCW well-being.

Background: Soil-transmitted helminth (STH) infections are a neglected tropical disease (NTD) that significantly impacts children's growth and development. Affecting 613 million children worldwide and 117 million in Africa. In Kenya, 5 million children are at risk with prevalence in Narok being 39.9%; despite mass drug administration, understanding prevalence, intensity, and identifying factors will guide targeted intervention.

Objectives: To estimate the prevalence, intensity, and factors associated with soil-transmitted helminth among children below 14 years of age in Transmara East and Transmara West Sub-Counties in Narok County, Kenya.

Methods:  Community-based cross-sectional study carried out  multistage sampling used to enroll households.  structured questionnaire used for data collection from children under 14, with stool samples collected in leakproof containers for laboratory analysis, and fingernail status observed. Caregivers responded for children under five. Social demographics, education status, and nail status were collected, Descriptive and analytical statistics were conducted and factors associated with soil-transmitted helminths were identified through bivariate analysis and logistic regression. Ethical approval was granted by the institutional review board, informed consent obtained from household head, assent from child participants, unique identifiers used for confidentiality.

Results: A total of 438 children were included in the study, median age, six years, STH prevalence 19.41% (85 /438). The most common species, Ascaris lumbricoides, accounting for 13.01% (57/438). Higher prevalence rates noted in Transmara West Sub County (22.67%) and Keiya ward (37.5%). Most infections were of light intensity (57%). independent factors associated with STH infection: residing in Kapsasian ward (aOR=6.99), non-attendance at school (aOR=3.90), care by unwashed hands (aOR=2.69), not washing hands before meals (aOR=5.12), and untrimmed nails (aOR=4.80).

Conclusion: STH prevalence in the study area was high, above the WHO-recommended prevalence of below 10%. The identified factors highlight areas for targeted interventions. Integrating preventive chemotherapy, community engagement through awareness of behavior change, and personal hygiene to complement chemotherapy in STH control

Background: A significant gap often persists between the clinical information provided during visits and a patient’s ability to understand and act upon it, which contributes to poor treatment adherence and adverse outcomes. Traditional one-size-fits-all education methods frequently fail due to medical jargon and limited consultation time. This project addressed these barriers by utilising advanced AI to create personalised, empathetic, and actionable health information tailored to the unique situation of each patient.

Methods: An AI-powered platform was implemented as a custom Extendable Service Module (ESM) within the OpenMRS 3.x platform. The system utilised a modern, decoupled architecture where a Java backend aggregated patient data, including vitals, diagnoses, and medications, via the HL7 FHIR API. To ensure data privacy, the system stripped personally identifiable information (PII) before a containerised Python service processed the data using GPT-3.5 prompt engineering. The generated content explained complex diagnoses and medication purposes in simple language.

Results: The system achieved a 90-95% accuracy rate in the generation of educational materials with minimal hallucinations. The module successfully personalised content based on specific patient factors like age and BMI, while the workflow ensured clinicians remained the final validators of all information. Initial implementation prioritised SMS delivery to reach patients with basic feature phones, ensuring equity. Pilot testing indicated that the automated generation of tailored materials saved significant time, reducing the repetitive burden of education for healthcare providers.

Conclusion: Leveraging large language models within existing electronic medical record workflows provides a scalable method to improve health literacy. By transforming patients into active partners in their care, this tool enhances safety and strengthens the healthcare ecosystem. Future phases aim to expand delivery via WhatsApp and integrate closed-loop feedback mechanisms.

Background: The COVID-19 pandemic necessitated a radical shift in surveillance, moving from traditional aggregated weekly reports to granular, real-time laboratory diagnostic data. This transition integrated data from both private and public sectors into a centralized database at the National Public Health Laboratories (NPHL). This study evaluates the progress in health system interoperability for multi-disease surveillance and assesses its direct impact on data quality and systemic readiness.

Methods : To bridge primary data entry and Laboratory Information Systems (LIS), two international interoperability standards (HL7 FHIR and LOINC) were adopted across 12 priority diseases. Data quality was measured by analysing the completeness of submitted paper Integrated Case Reporting Forms (ICRF) against digital entries at the Influenza and Virology reference laboratories. A stratified random sample of 48 forms (4 per month from 2025) was audited to determine the accuracy of transcribed data.

Results: The median data completeness for all mandatory variables reached 91%, indicating a high level of fidelity in the transcription and transmission process. However, the technical implementation of interoperability between the Outbreak Disease Data collection system(ADAM) and the LIS remained a significant bottleneck, requiring 8 to 11 weeks for successful pilot testing. Furthermore, the prerequisite training and development of Implementation Guides (published at fhir.nphl.go.ke) required a one-year lead time.

Conclusion: While standardization significantly enhances data quality, the timeline for deployment remains a barrier. To close the cost-benefit gap, the health sector must prioritize demand creation for high-fidelity data and develop simplified adoption pathways for system developers and vendors. Streamlining these implementation frameworks is essential for transitioning from reactive pandemic response to proactive national health defence.

Background: In Kenya, limited rapid diagnostic capabilities and inadequate understanding of respiratory pathogen diversity have led to empirical antibiotic prescriptions, contributing to antimicrobial resistance (AMR). Strengthening sentinel surveillance for severe acute respiratory illness (SARI) and influenza-like illness (ILI), as defined by the World Health Organization (WHO), is critical. This study aimed to estimate the prevalence of respiratory viral pathogens among symptomatic patients, determine their molecular characterization, and identify associated risk factors.

Methods: A cross-sectional analysis was conducted on data from nine strategically located sentinel surveillance sites across Kenya from 2019 to 2024. The study included records collected from symptomatic patients presenting with SARI or ILI. A suspected case was a record classified as either SARI or ILI, and a confirmed case had a positive test. Data analysis included descriptive statistics and logistic regression to identify risk factors.

Results: Of the 27,025 records, the majority of suspected cases were SARI (79.4%; n=21,467), with males comprising 54.9% and children

Background

Tuberculosis (TB) remains the leading cause of mortality globally. In underserved counties such as Marsabit, TB is complicated by HIV co-infection, undernutrition, comorbidities and limited access to healthcare services. We assessed trends and determinants of poor treatment outcomes (PTO) among drug-susceptible TB (DSTB) patients in Marsabit County.

Methods

We conducted a cross-sectional analytic study using individual-level routine surveillance data from Treatment Information from Basic Unit (TIBU), Kenya’s national electronic TB surveillance system. All DSTB patients registered between January 2019 and December 2024 were included. PTO was defined as death, treatment failure, lost to follow-up (LTFU), or transfer out. Variables with p

Introduction:
Mpox (monkeypox) has emerged as a growing public health concern globally and across Africa, with sporadic and imported cases increasingly being reported in Kenya. Rapid laboratory confirmation and genomic characterization are critical for outbreak investigation, case management, and public health response. In addition to confirming infection, genomic approaches enable identification of circulating viral clades and the detection of co-infections that may complicate clinical outcomes.

Aim:
This investigation aimed to determine the etiological agent of suspected Mpox cases using molecular and metagenomic sequencing analysis, while identifying viral clades and potential co-infections of clinical and public health significance.

Methods:
Three clinical samples from suspected Mpox cases received on 17 July 2025 were analyzed at the Genomics and Molecular Surveillance Laboratory. Total nucleic acids were extracted using the QIAGEN RNA/DNA kit, followed by cDNA synthesis and library preparation using Illumina Viral Surveillance Panel V2. Sequencing was performed on the Illumina platform, and metagenomic data were analyzed using Illumina BaseSpace DRAGEN viral surveillance workflow and the CZ ID pipeline. Viral consensus sequences were further analyzed using Nextclade to determine Mpox lineage and clade classification. Additional sequence interrogation was conducted to assess possible co-infections and relevant mutations.

Results:
One of the three samples was confirmed as Mpox with high genomic sequence coverage and was classified as Clade 1b, indicating circulation of a lineage of significant public health concern. The remaining two samples were Mpox PCR-negative but demonstrated evidence of HIV infection with possible co-infections, including human papillomavirus. One HIV-positive sample showed mutations within the reverse transcriptase region suggestive of resistance to nucleoside reverse transcriptase inhibitors, while remaining susceptible to non-nucleoside reverse transcriptase inhibitors.

Conclusion:
Metagenomic sequencing confirmed Mpox Clade 1b infection and identified HIV-related co-infections and drug resistance markers in other suspected cases, highlighting the importance of integrated genomic surveillance for outbreak response.

Introduction:
Mpox (monkeypox) has emerged as a growing public health concern globally and across Africa, with sporadic and imported cases increasingly being reported in Kenya. Rapid laboratory confirmation and genomic characterization are critical for outbreak investigation, case management, and public health response. In addition to confirming infection, genomic approaches enable identification of circulating viral clades and the detection of co-infections that may complicate clinical outcomes.

Aim:
This investigation aimed to determine the etiological agent of suspected Mpox cases using molecular and metagenomic sequencing analysis, while identifying viral clades and potential co-infections of clinical and public health significance.

Methods:
Three clinical samples from suspected Mpox cases received on 17 July 2025 were analyzed at the Genomics and Molecular Surveillance Laboratory. Total nucleic acids were extracted using the QIAGEN RNA/DNA kit, followed by cDNA synthesis and library preparation using Illumina Viral Surveillance Panel V2. Sequencing was performed on the Illumina platform, and metagenomic data were analyzed using Illumina BaseSpace DRAGEN viral surveillance workflow and the CZ ID pipeline. Viral consensus sequences were further analyzed using Nextclade to determine Mpox lineage and clade classification. Additional sequence interrogation was conducted to assess possible co-infections and relevant mutations.

Results:
One of the three samples was confirmed as Mpox with high genomic sequence coverage and was classified as Clade 1b, indicating circulation of a lineage of significant public health concern. The remaining two samples were Mpox PCR-negative but demonstrated evidence of HIV infection with possible co-infections, including human papillomavirus. One HIV-positive sample showed mutations within the reverse transcriptase region suggestive of resistance to nucleoside reverse transcriptase inhibitors, while remaining susceptible to non-nucleoside reverse transcriptase inhibitors.

Conclusion:
Metagenomic sequencing confirmed Mpox Clade 1b infection and identified HIV-related co-infections and drug resistance markers in other suspected cases, highlighting the importance of integrated genomic surveillance for outbreak response.