Poster Presenters

Background: Enteric diseases remain a major cause of morbidity and mortality in sub-Saharan Africa, where safe drinking water access is limited. On 1st March, 2025, Kisii County reported an outbreak of a febrile gastrointestinal illness in Tabaka Ward.

Aim: To determine the outbreak magnitude, aetiology, assess response timeliness, and guide control measures.

Methods: We conducted a descriptive outbreak investigation using a standard case definition. Active case finding and retrospective records review were performed using a structured questionnaire between 3rd  February and 8th March 2025. Clinical and water samples were analyzed using standard microbiological methods, multiplex PCR, and genome sequencing. Response timeliness was evaluated using the WHO 7-1-7 framework. Data were analyzed in Microsoft Excel 2016 and QGIS v3.24.1.

Results: We identified 173 cases (117 from health facilities and 56 community), with a median age of 15 years (IQR 8.8–31.2) and 57% were female. Amarondo village recorded the highest attack rate (21/100 persons). Among 36 interviewed community cases, 76% had consumed untreated water from the community spring. Forty-six clinical and 19 water samples were collected. Stool testing identified: Enteropathogenic Escherichia coli (n=8), Salmonella Typhi (n=5) with Norovirus, Giardia lamblia, Cryptosporidium, and Campylobacter (n=2 each). Five blood samples were positive for S. Typhi. All E. coli isolates were resistant to ampicillin, and 3 of the S. Typhi isolates were multidrug-resistant. Coliforms and E. coli were detected in 17 and 15 of the water samples, respectively. Detection and response benchmarks were achieved with a 16-day notification delay. Interventions included chlorine tablet distribution and community sensitizations. The CFR was 0%.

Conclusion: The outbreak was driven by contaminated water, characterized by multiple pathogens and compounded by antimicrobial resistance. Limited laboratory diagnostic capacity and poor documentation undermined timely notification. Routine water-quality monitoring, consistent WASH practices, stronger surveillance integration, improved diagnostics, and antimicrobial stewardship are essential to prevent future outbreaks.

Background: Tuberculosis (TB) and HIV co-infection is a major global health issue, contributing significantly to deaths among people living with HIV (PLWHIV), especially in Sub-Saharan Africa. In Rwanda, Tuberculosis surveillance system among PLHIV was not evaluated. This study aimed to assess the TB surveillance system, characterize TB cases, and evaluate its performance.

Methods: This five-year cross-sectional study evaluated the performance of the Mycobacterium tuberculosis surveillance system among PLHIV. Primary data was gathered through questionnaires assessing attributes like completeness, timeliness, and flexibility, while secondary data reviewed system functions such as detection and reporting. Performance was scored as good (>80%), average (60-80%), or poor (

Background: Rift Valley Fever (RVF) is a climate-sensitive zoonotic disease associated with periods of above-normal rainfall and flooding. In late 2023, heavy El Niño rains and flooding, coupled with a confirmed outbreak in neighboring Marsabit County in January 2024, heightened the risk of RVF spread to Wajir County.

Objective: To assess the risk of an RVF outbreak in Eldas Sub-County, Wajir County, using a One Health approach integrating human, animal, and environmental data.

Methods: A multidisciplinary team conducted a field risk assessment from January 24 to February 2, 2024. The assessment included review of human and animal health records, active community case searches, focus group discussions, key informant interviews, environmental observations, and laboratory investigations. A risk matrix was used to integrate epidemiological, environmental, and socio-systemic findings.

Results: The assessment identified a high-risk environment for RVF transmission. Laboratory analysis detected RVF virus in 2 of 32 (6.3%) human samples by PCR, confirming active viral circulation. Among 2,751 animals surveyed, 268 exhibited symptoms consistent with RVF (39 camels, 211 goats, 18 sheep), indicating possible ongoing livestock transmission. Entomological risk was elevated, with 96% of respondents reporting increased mosquito density following flooding. High-risk practices were common, with 78% reporting handled sick animal products without protection measures, while only 38% of symptomatic individuals sought formal healthcare. Health system gaps included understaffing, limited vector control, and inadequate laboratory capacity. The convergence of these factors indicates a substantial likelihood of an outbreak.

Conclusion: The risk of an RVF outbreak in Eldas Sub-County is high, driven by confirmed viral circulation, favourable vector conditions, community exposure, and health system gaps. Urgent, integrated One Health interventions—including vector control, livestock vaccination, community risk communication, and strengthened surveillance and laboratory capacity—are needed to mitigate this imminent threat.

Introduction: Timely tuberculosis (TB) diagnosis remains a challenge in resource-limited settings, where fragmented specimen referral systems delay case detection and treatment. In Nyandarua County, Kenya, irregular and donor-dependent specimen transport contributed to diagnostic gaps and delayed result delivery. This abstract reports a programmatic evaluation of the ISRS pilot implemented from July to December 2025.

Aim: To evaluate whether a county-owned, integrated hub-and-spoke specimen referral model could improve early TB diagnosis by reducing turnaround time, lowering specimen rejection rates, and strengthening diagnostic system integration.

Methods: A before-and-after programmatic evaluation was conducted using routine operational data collected during the six-month ISRS pilot. Baseline indicators were compared with pilot-period indicators to assess changes in turnaround time, specimen rejection rate, result return, and cold chain integrity. The system operated across 37 health facilities, including 5 hubs and 32 spokes, and integrated TB, HIV, and other specimen referrals into one county-managed network. Data were drawn from specimen referral logs, laboratory registers, transport records, temperature monitoring tools, and result-return records. Key indicators assessed included specimen volume, facility coverage, mean turnaround time, rejection rate, result return rate, and cold chain performance.

Results: During the pilot, 6,105 specimens were referred, achieving 100% ISRS supported facilities coverage. The mean TB specimen turnaround time improved from 72 hours to 24 hours. Specimen rejection rates declined from 24% to 12%, representing a 50% reduction. Result return reached 100%, and cold chain integrity was maintained, with five temperature alarms resolved without sample compromise. The integrated model improved coordination, reduced operational inefficiencies, and strengthened system ownership.

Conclusion: The Nyandarua County ISRS pilot demonstrates that a county-owned, integrated specimen referral system can significantly improve TB diagnostic timeliness, quality, and access. The observed improvements support scale-up as a practical contribution toward Universal Health Coverage and the End TB Strategy.

Background:
Advancing health security requires the strategic integration of science, innovation, and equity. The COVID-19 pandemic exposed critical gaps in health systems while simultaneously accelerating the adoption of digital technologies. In Kenya, Nyeri County implemented the Chanjo digital platform to support the national vaccination program, aiming to strengthen real-time data management, improve service delivery, and promote equitable access to vaccination services.

Objective:

To assess how the optimized use of digital health systems and real-time  data-informed strategies improved Covid-19 vaccination strategies and program performance among eligible populations in Nyeri County.  

Methods:

We conducted a cross-sectional analytical study using routinely collected program data from 2020 to 2023.Data were extracted from the Chanjo platform and triangulated with county health records.Key indicators included vaccination uptake,system utilization and performance of critical modules such as inventory management and Adverse Events Following Immunization(AEFI)reporting.Descriptive statistical analysis was used to evaluate  coverage trends and system performance.Additionally,programmatic review assessed how real-time data dashboards were applied to guide micro-planning,resource allocation,and targetted outreach interventions.

Key Findings:
The integration of digital technology significantly enhanced vaccination program performance and health system responsiveness. By June 2023, 71% of the eligible population had received at least one vaccine dose, while 57% were fully vaccinated. Real-time data capture facilitated timely decision-making, efficient resource allocation, and improved coordination of vaccination activities. Despite these gains, gaps were identified in specific system components, with inventory commodity management and Adverse Events Following Immunization (AEFI) reporting modules performing below optimal levels (less than 50%), highlighting areas for system strengthening.

Conclusion:
Beyond technology adoption,the deliberate use of digital data for decision-making  is a key driver of improved vaccination outcomes and health system resilience.Scaling such data-driven approaches can enhance preparedness and response to future public health emergencies,particularly in resource-limited settings.

Background: Mobilization of skilled public health responders is essential for the containment of outbreaks, within the recommended 7-1-7 target. Kenya has adopted the Global Health Emergency Artificial Intelligence (GHEC AI) platform to enable data driven coordination of public health responders. As an initial step in adopting the platform we assessed Kenya’s public health responder databases.

Method: A mapping of available responder databases was conducted covering the period 2022- 2026. Workforce data on variables such as professional qualifications, International Health Regulations core capacity expertise, geographical location, contact details and previous experience in outbreak response were consolidated from the accessible databases, specifically the national rapid responders list and the National African Volunteers Health Corp (AVOHC) Surge list and subsequently uploaded onto the GHEC AI platform. Simultaneously, historical outbreak data was uploaded to enable scenario-based simulations.

Results: Integration of the GHEC AI platform with responders’ information improved interoperability across databases, supported scenario-based preparedness planning and enhanced the visibility of available rapid response expertise. However, Only 2 (40%) of the available 5 databases were accessible, with 23% of the responder details being incomplete. Of the 164 responders identified through the databases, (42%) were Female and (58%) were Male, national responders were a majority at (71%) and County responders at (29%). The workforce directories remain largely centralized at the national level, with limited integration of county and sub-county teams. Additionally, gaps in competency coverage, including insufficient psychosocial expertise (2%) logistics expertise (3%) and risk communication expertise( 8%), was noted.

Conclusion: The GHEC AI platform presents a promising approach to strengthening rapid response capacity by enabling faster, coordinated and targeted deployment of health personnel during disease outbreaks. To optimize the use of the GHEC AI platform, more financial and technical resources are required to facilitate the collection of workforce data at county and sub county level.

Introduction: Malaria remains a major vector-borne disease and public health threat in Kenya’s highland epidemic-prone areas, where unstable transmission increases the risk of outbreaks and require strong surveillance systems for early detection and response.

Aim: This study aimed to evaluate the performance of the Malaria Epidemic Preparedness and Response (EPR) surveillance system in detecting and informing response to malaria upsurges.

Methods: A cross-sectional mixed-methods evaluation was conducted at Kaptumo Sub-County Hospital, Nandi County, from January to December 2024. The evaluation was guided by the CDC Updated Guidelines for Evaluating Public Health Surveillance Systems. Quantitative data on malaria cases, reporting completeness, and timeliness were extracted from the Kenya Health Information System (KHIS). Qualitative data were collected through structured questionnaires and key informant interviews with 14 healthcare workers involved in surveillance.

Results: A total of 406 confirmed malaria cases were reported, with 48% occurring between January and March, demonstrating marked seasonal transmission. Individuals under 20 years accounted for 60% of cases, highlighting increased vulnerability among younger populations. Spatial clustering was observed in Koyo-Ndurio ward (60%), suggesting localized transmission hotspots. The surveillance system was highly useful and acceptable, with all respondents reporting that surveillance data informed targeted malaria control interventions. However, key system limitations undermined its effectiveness as an early warning tool. Weekly reporting completeness was 76.9%, below the recommended threshold, limiting timely outbreak detection. Significant data quality gaps were identified, with a congruence of 0.58 between weekly and monthly reports, indicating poor data consistency. System stability was further constrained by internet connectivity challenges and limited trained personnel.

Conclusion: The malaria EPR surveillance system was useful but constrained by data quality and reporting gaps. Strengthening data quality assurance, workforce capacity, and digital infrastructure are critical to improving early detection and response to malaria outbreaks.

Background

Rapid and reliable transmission of laboratory results is critical for timely clinical decision-making. Labware’s Remote Logging system—a web-based platform that allows facilities to enter patient and specimen information at the point of collection and track samples through referral and testing—was introduced in Homa Bay County to improve TB specimen management. This evaluation assessed its implementation and effect on specimen referral and turnaround time (TAT).

Methods:

A cross-sectional assessment was conducted from January to June 2025 across 11 purposively selected GeneXpert sites. The sites were trained in October 2024 and  equipped with the Remote Logging application to strengthen the hub-and-spoke sample referral system. An additional 46 laboratory officers were trained. Prior to implementation, assessments confirmed the availability of functional computers, stable internet connectivity, and printers. Using an Excel abstraction tool and with approval from the County Department of Health, we reviewed the number of sputum samples logged remotely, referral completion, and TAT for culture and Line Probe Assay (LPA). Data from the Remote Logging system and TB registers were compared with the January–June 2024 period. Data were summarized using descriptive statistics.

Results

All 11 GeneXpert sites (100%) adopted the system, linking 207 sputum-referring facilities. During the review period, 214 sputum samples were referred to for culture and 100 for LPA; 184 (86%) culture samples and all LPA samples were logged remotely. All 214 culture and 100 LPA results were returned, compared with 73 culture and 51 LPA samples sent and 51 (70%) culture and 51 (100%) LPA results received before implementation. Among processed samples, 103 showed MTB growth, one was rifampicin-resistant, and 11 yielded non-tuberculous mycobacteria. TAT improved markedly: LPA decreased from 65 to 32 days, and culture from 64 to 14 days.

Conclusion: Remote Logging improved TB result reporting and significantly reduced diagnostic turnaround times.

Background: Chikungunya is a vector-borne viral infection caused by the Chikungunya virus (CHIKV). The disease presents with non-specific symptoms such as fever and joint pain. Mombasa County is vulnerable due to its tropical climate and seasonal rains, creating breeding grounds for mosquitoes. We conducted an outbreak investigation to determine the magnitude of the disease and control its spread.

Methods: We used a mixed-method approach, including review of hospital records, vector surveillance, and sensitization of healthcare workers. Chikungunya disease was suspected in patients with an acute onset of fever >38.5°C and severe joint pain not explained by other medical conditions. We conducted vector surveys in areas with documented cases using a systematic random sampling. We conducted descriptive analysis of Chikungunya cases from March to July 2025.

Results: The index case was detected on 14th March 2025. Cumulatively, 612 Chikungunya cases were reported between March and July 2025, with 101 confirmed by PCR. Tudor Sub-county Hospital in Mvita constituency actively tested for CHIKV IgM and IgG antibodies. The attack rate ranged from 11.77/100,000 in Nyali to 80.86/100,000 in Likoni, with an average of 43.35/100,000. Those aged 16-35 years contributed 248/612 (40.5%), with 271/536 (50.6%) being female. Fever and joint pain were present in 523/612 (85.5%) of the cases. A total of 347/612 (56.7%) cases were managed as outpatients. Vector breeding sites were identified as stagnant water inside homesteads and the surrounding environment. We collected adult mosquitoes and larvae, and sent the samples to KEMRI for analysis.

Conclusion: The outbreak appeared to be closely associated with the rainy season and poor WaSH infrastructure. Almost equal gender distribution suggested equal exposure risk. Fever and joint pains were the most common presentation of the disease. The epidemiology and transmission patterns of Chikungunya are poorly understood. We recommended enhanced surveillance for early detection and case management, personal protective measures, vector control, and increasing community awareness of the disease.

Background: Visceral Leishmaniasis (VL), or Kala Azar, is a protozoal disease endemic within 11 counties in Kenya. It causes severe morbidity and, if left untreated, is fatal in 95% of cases. Samburu County reported suspected cases of VL in Samburu East Subcounty in March 2025. We conducted an outbreak investigation to confirm the outbreak, estimate the magnitude, and institute prevention and control measures for VL.

Methods: A multidisciplinary team from national and county levels conducted the investigation from 9th to 14th March 2025. VL was suspected in any person presenting with fever lasting more than two weeks, and either splenomegaly, weight loss, or lymphadenopathy. We conducted active case search to estimate the prevalence of VL cases, healthcare worker and community sensitization on case detection, reporting and management.

Results: The index case presented at Westgate Dispensary on 15th January 2025, with the national level notified on 7th March 2025. Eight (8) cases were detected in the Westgate area, with two (2) deaths. The age range was 10 months to 22 years. Three (3) samples collected from suspected cases tested positive for VL. Verbal autopsies revealed suspected cases for over a decade before the index case. Mud houses and anthills are present throughout the area. Patients presented with persistent fever, abdominal distension, weight loss and symptoms of anaemia. Case management was at Isiolo County Referral Hospital.

Conclusion: The delayed notification of the outbreak was due to an inadequate capacity to detect the cases. Feedback from the community suggests that VL is endemic in Samburu East Subcounty. The subcounty lies between Isiolo and Marsabit counties, both of which are endemic. Capacity building of healthcare workers has been conducted, with Archer’s Post Subcounty Hospital identified as a VL treatment centre in Samburu County. Community awareness was recommended to raise awareness and enhance health-seeking behaviour.

Introduction
Poor-quality medicines in resource-limited settings are well documented, yet limited evidence exists on the quality of medical devices (MDs) and in-vitro diagnostics (IVDs). Field observations suggest similar quality concerns, but scientific reporting remains scarce.

Aim

This study assessed laboratory officers’ knowledge of pharmacovigilance and the quality of routine in-vitro diagnostic test kits in Kenya.

Methods
A cross-sectional  study was conducted among laboratory professionals working in public, private, and faith-based facilities. Data was collected using a structured, self-administered online questionnaire disseminated via WhatsApp between April 23 and May 19, 2025. Quantitative responses were analysed using SPSS version 20.0 for descriptive statistics  whereas qualitative data using NVivo version 15 for thematic analysis.

Results
A total of 99 laboratory officers from 30 counties participated: 69.7% from public facilities, 24.2% from private, and 6.1% from faith-based institutions. Most participants (69.7%) had encountered problems with rapid diagnostic kits; however, only 17.2% were aware of the Pharmacovigilance Electronic Reporting System (PvERs). While 63.3% acknowledged that poor-quality devices should be reported, only 55.6% had ever reported such incidents, with just 6.1% using the PvERs platform. The H. pylori kit was most frequently reported for quality concerns (50%), and false-positive results were the most common issue (46.4%). Participants emphasized the need for improved regulation, validation, and approval processes for diagnostic kits in Kenya.

Conclusion
Poor-quality diagnostic test kits are present in Kenya, yet underreporting persists largely due to limited awareness of formal reporting systems such as PvERs. Unreliable diagnostic kits threaten patient safety, contribute to mismanagement of infectious diseases, promote antimicrobial resistance, and undermine disease surveillance and overall national health security.

Training laboratory officers on pharmacovigilance, enforcing regulatory oversight to ensure use of approved diagnostic kits, and establishing a national diagnostic policy with clear implementation mechanisms are critical steps towards improving diagnostic quality.

Background: Long-lasting insecticidal nets (LLINs) are a primary malaria prevention strategy; however, their effectiveness declines over time due to reduced insecticidal activity and physical deterioration, often leading to repurposing or disposal. This study examined the drivers of premature LLIN attrition at the 36th month post-distribution in Kirinyaga County, a low-risk malaria area with high vector presence. 

Methods: A mixed-methods design was employed to assess LLIN physical integrity, attrition, socio-demographic and economic predictors, and community knowledge, attitudes, and practices related to net use and malaria risk perception influencing net use. Quantitative data were collected from 270 households using structured questionnaires administered and physical integrity was assessed in a subsample of 150 LLINs. Qualitative data were obtained from eight focus group discussions segregated by age, gender and level of education.

Results: Overall LLIN attrition was 33.1% (95% CI: 29.7–36.8%), primarily due to repurposing (11.7%) and discarding due to physical damage (9.9%). Over half of assessed nets remained in good condition (56%), while 18% were severely torn, with damage predominantly on the lower panels. Attrition was significantly associated with household wealth (poor: AOR = 1.46, 95% CI: 1.03–2.07; p value = 0.038; richest: AOR = 1.59, 95% CI: 1.08–2.34; p value = 0.019) and large household size (AOR = 1.68, 95% CI: 1.09–2.59; p value = 0.018). Household size, wealth quartile and net care behaviors were key drivers of attrition. Malaria risk perceptions, influenced by cultural beliefs, treatment costs and proximity to rice fields, strongly influenced net use.

Conclusion: Premature attrition key drivers were socio-economic status, household size, behavioral practices, environmental conditions, and misconceptions undermining LLIN longevity. These findings highlight need for targeted behavior change communication, integration of household demographic composition and socio-cultural norms into distribution strategies and continuous monitoring of net durability to sustain effective community-level malaria protection.