Characterization of genital chlamydia amongst female sex workers in Nairobi, Kenya.

Introduction: genital chlamydia, which is caused by diverse Chlamydia trachomatis (C. trachomatis) genotypes, is largely asymptomatic. We aimed to identify C. trachomatis genotypes causing genital chlamydia among female sex workers attending a sex workers outreach program clinic in Nairobi, Kenya. Methods: this cross-sectional study was conducted between 18th April 2017 and 19th March 2021. Genitourinary complaints from eligible female sex workers were documented using a structured questionnaire. Endocervical swabs were collected for laboratory analysis. C. trachomatis plasmid DNA was extracted, PCR-amplified, and sequenced. Consensus sequences were generated and aligned with reference sequences to determine the C. trachomatis genotypes. Bivariate analysis was used to determine the association between genitourinary complaints and genital chlamydia. Results: endocervical swabs were collected from a total of 348 participants. Of these, 46 (13.2%) were positive for C. trachomatis. Most (297, 85.3%) of the participants presented with pelvic discharge with or without other symptoms. Fifteen (15, 4.3%) had abdominal pain and 3 (0.9%) had an itchy vulva. There was no statistically significant relationship between clinical presentation and genital chlamydia. Twenty-three samples were successfully sequenced. Each sequence was at least 90% identical to each of the 13 references C. trachomatis genotypes A, B, C, D, E, F, G, Ia, J, L1, L2, L2b and L3. Conclusion: we found no significant association between individual genitourinary complaints and genital chlamydia infection. The C. trachomatis genotypes circulating amongst female sex workers in Nairobi could be related to genotypes A, B, C, D, E, F, G, Ia, J, L1, L2, L2b, and L3.

Opportunities and challenges on hospital preparedness to handle motorcycle accidents in Busia County, Kenya: an exploratory qualitative study.

Introduction: motorcycles continue to be a popular mode of transport in Kenya. However, the related injuries cause significant morbidity and mortality and remain to be a major and neglected public health issue. This raised the crucial need for hospital preparedness in managing morbidities and in reducing mortalities. This formed the basis of this paper which aims to document the challenges and opportunities in the healthcare system in handling motorcycle accidents in a Kenyan border town in Busia County. Methods: we drew data from an exploratory qualitative study that was carried out in 2021. All six referral hospitals purposively included in the study. The study targeted a total of 25 top level facility managers as key informants on the facility level opportunities and challenges in handling motorcycle accidents. Descriptive data were analyzed using SPSS version 20. Results: the hospitals were not well prepared to handle motorcycle accidents. The major challenges were understaffing in critical care services; inadequate/lack of equipment to handle motorcycle injuries; inadequate/lack of infrastructure i.e. surgical wards, emergency rooms, inadequate space, functional theatre; lack/inadequate supplies; overstretched referral services arising from the hinge burden of motorcycle accidents in the area; inadequate specialized personnel to provide trauma/care services; mishandling of cases at the site of accident; inability of victims to pay related bills; inappropriate identification of victims at the facility; lack/inadequate on-job training. Some opportunities that currently exist include health system interventions which are not limited to employment of more professionals, improvement of infrastructure, provision of equipment and increase of budgetary allocation. Conclusion: the study reveals vast challenges that are faced by hospitals in managing patients. This calls for the government to step in and capitalize on the proposed opportunities by the health managers to be able to manage morbidities and bring down mortalities due to motorcycle accidents.

Correction: Seroprevalence of SARS-CoV-2 antibodies and retrospective mortality in a refugee camp, Dagahaley, Kenya.

[This corrects the article DOI: 10.1371/journal.pone.0260989.].

Monoclonal Antibodies for Rift Valley Fever Virus Nucleocapsid: Application in IgG/IgM ELISA for Sero-Diagnosis.

INTRODUCTION: Rift Valley fever virus (RVFV) belonging to the Phenuiviridae family is responsible for a zoonotic disease called Rift Valley fever (RVF). Currently, RVFV has spread from Africa to Asia, and due to its ability to cause high mortality rates, it has significantly impacted human health and economic development in many societies. Highly specific and sensitive systems for sero-diagnosis of RVFV infection are needed for clinical use. METHOD: BALB/c mice were immunized with recombinant RVFV nucleocapsid (rRVFV-N) protein and the spleen cells fused with SP2/0 myeloma cells to create hybridoma cell lines. The secreted monoclonal antibodies (MAbs) were purified and characterized. Enzyme-linked immunosorbent assay (ELISA) systems for the detection of IgG and IgM using the new MAbs were established and evaluated. Serum samples from 96 volunteers and 93 patients of suspected RVF from Kenya were tested compared with the ELISA systems based on inactivated viruses and the rabbit polyclonal antibody. RESULT: Three monoclonal antibodies against rRVFV-N protein were established. The performance of the MAb-based sandwich IgG ELISA and the IgM capture ELISA perfectly matched the ELISA systems using the inactivated virus or the polyclonal antibody. CONCLUSIONS: Recombinant RVFV-N protein-specific MAbs were developed and they offer useful tools for RVFV studies. The MAb-based ELISA systems for detecting IgG and IgM offer safe and useful options for diagnosing RVFV infections in humans.

Factors associated with viral load non-suppression among treatment-experienced pre-teenage children living with HIV in Kenya: a nationwide population-based cohort study, 2015-2021.

Background: Viral load non-suppression (VLNS) in children is a major public health concern because of attendant HIV disease progression and risk of morbidity and mortality. Based on a nationally representative database we present estimates of the prevalence, trends and factors associated with VLNS in Kenyan pre-teenage children between 2015 and 2021. Methods: Kenya National AIDS & STI Control Program's (NASCOP) maintains an early infant diagnosis and viral load (EID/VL) database for all persons living with HIV who are enrolled in the country's primary care clinics for purposes of monitoring progress towards achievement of the 95% viral suppression goals. Participants were eligible if they were children living with HIV (CLHIV), on combination ART (cART) treatment, and ≤12 years old. The modified Mann-Kendall trend test for serially correlated data was used to identify VLNS trends. Generalized estimating equations (GEE) with a logit link was used to assess the effects of covariates on the odds of VLNS (VL ≥1,000 copies/mL) over repeated points in time, allowing for the correlation among the repeated measures. Findings: Between January 2015 and December 2021, 508,743 viral load tests were performed on samples collected from 109,682 pre-teenage children. The prevalence of VLNS decreased from 22.9% (95% CI 22.4-23.3) to 12.5% (95% CI 12.1-12.9), p < 0.0001, and mean age increased from 3.1 (4.2) to 8.0 (3.2) years in 2015 and 2021 respectively. A modified Mann-Kendall trend test for serially correlated data denotes a statistically significant decreasing trend (τ = -0.300, p < 0.0001) over the study period. In the multivariable GEE analysis adjusted for covariates, the odds of VLNS decreased by 11% per year during the study period, (GEE-aOR 0.89, 95% CI 0.88-0.90; p < 0.0001). Factors positively associated with VLNS were EFV/NVP-based first-line cART regimen (GEE-aOR 1.74, 95% CI 1.65-1.84, p < 0.0001), PI-based cART regimen (GEE-aOR 1.82, 95% CI 1.72-1.92, p < 0.0001), and children aged 1-3 years (toddlers) (GEE-aOR: 1.84, 95% CI 1.79-1.90, p < 0.0001). On the contrary, DTG-based cART regimen, were negatively associated with VLNS (GEE-aOR 0.70, 95% CI 0.65-0.75, p < 0.0001). Interpretation: There is a strong evidence of decreasing viremia between 2015 and 2021. To sustain the decreasing trend, accelerating the switch from the suboptimal EVP/NVP first-line regimen to optimised DTG regimen is warranted. Funding: U.S. President's Emergency Plan for AIDS Relief (PEPFAR) and Clinton Health Access Initiative (CHAI).

In-hospital mortality during the wild-type, alpha, delta, and omicron SARS-CoV-2 waves: a multinational cohort study in the EuCARE project.

Background: Investigating outcomes of hospitalised COVID-19 patients throughout the pandemic is crucial to understand the impact of different SARS-CoV-2 variants. We compared 28-day in-hospital mortality of Wild-type, Alpha, Delta, and Omicron variant infections. Whether the difference in risk by variant varied by age was also evaluated. Methods: We conducted a cohort study including patients ≥18 years, hospitalised between 2020 and 02-01 and 2022-10-15 with a SARS-CoV-2 positive test, from nine countries. Variant was classified based on sequenced viruses or from national public metadata. Mortality was compared using the cumulative incidence function and subdistribution hazard ratios (SHR) adjusted for age, sex, calendar time, and comorbidities. Results were shown age-stratified due to effect measure modification (P < 0.0001 for interaction between age and variant). Findings: We included 38,585 participants: 19,763 Wild-type, 6387 Alpha, 3640 Delta, and 8795 Omicron. The cumulative incidence of mortality decreased throughout the study period. Among participants ≥70 years, the adjusted SHR (95% confidence interval) for Delta vs. Omicron was 1.66 (1.29-2.13). This estimate was 1.66 (1.17-2.36) for Alpha vs. Omicron, and 1.34 (0.92-1.95) for Wild-type vs. Omicron. These were 1.21 (0.81-1.82), 1.21 (0.68-2.17), and 0.98 (0.53-1.82) among unvaccinated participants. When comparing Omicron sublineages, the aSHR for BA.1 was 1.92 (1.43-2.58) compared to BA.2 and 1.52 (1.11-2.08) compared to BA.5. Interpretation: The herein observed decrease in in-hospital mortality seems to reflect a combined effect of immunity from vaccinations and previous infections, although differences in virulence between SARS-CoV-2 variants may also have contributed. Funding: European Union's Horizon Europe Research and Innovation Programme.

A Machine Learning Approach to Predict HIV Viral Load Hotspots in Kenya Using Real-World Data.

Background: Machine learning models are not in routine use for predicting HIV status. Our objective is to describe the development of a machine learning model to predict HIV viral load (VL) hotspots as an early warning system in Kenya, based on routinely collected data by affiliate entities of the Ministry of Health. Based on World Health Organization's recommendations, hotspots are health facilities with ≥20% people living with HIV whose VL is not suppressed. Prediction of VL hotspots provides an early warning system to health administrators to optimize treatment and resources distribution. Methods: A random forest model was built to predict the hotspot status of a health facility in the upcoming month, starting from 2016. Prior to model building, the datasets were cleaned and checked for outliers and multicollinearity at the patient level. The patient-level data were aggregated up to the facility level before model building. We analyzed data from 4 million tests and 4,265 facilities. The dataset at the health facility level was divided into train (75%) and test (25%) datasets. Results: The model discriminates hotspots from non-hotspots with an accuracy of 78%. The F1 score of the model is 69% and the Brier score is 0.139. In December 2019, our model correctly predicted 434 VL hotspots in addition to the observed 446 VL hotspots. Conclusion: The hotspot mapping model can be essential to antiretroviral therapy programs. This model can provide support to decision-makers to identify VL hotspots ahead in time using cost-efficient routinely collected data.

Accreditation of a molecular HIV diagnostic laboratory following the Strengthening Laboratory Management Towards Accreditation (SLMTA)-Stepwise Laboratory Quality Improvement Process Towards Accreditation (SLIPTA) approach in Kenya: an implementation science study.

Introduction: accreditation is the most effective approach to ensure the quality of services. Laboratory performance can be evaluated using the World Health Organization (WHO)-SLIPTA checklist, which checks a laboratory´s compliance with ISO 15189 on a five-star score scale and improved using the SLMTA approach. Compliance is assessed by an external body and can result in accreditation. In this paper, we describe the steps taken by the Kenya Medical Research Institute (KEMRI) HIV Laboratory, Alupe, a resource-limited public entity, towards accreditation, and discuss the lessons learned. Methods: the laboratory adopted a SLMTA-SLIPTA approach that included targeted mentorship, on-site workshops, and training. Mentorship-based interventions were used to establish a robust quality management system. Targeted mentorship, on-site workshops, and training were conducted between September 2015 and July 2016. Audits used the SLIPTA checklist to detect gaps in 12 quality system essentials. Performance indicators including turnaround time, external quality assurance, sample rejection rates, and corrective actions were tracked. An external assessment by the national accreditation body was conducted between September 2016 and November 2016. Results: training and mentorship-based interventions were successfully conducted. Quality management systems aligned with ISO 15189 were established. Baseline, midterm, and exit audits yielded scores of 47%, 75%, and 94% respectively. Early infant diagnosis external quality assurance scores were 100% in 2014-2016, while average viral load scores were at 60%, 70% and 90% during the same period. Turnaround time from September 2015 surpassed the 80% target. Accreditation was awarded in March 2017. Conclusion: the SLMTA-SLIPTA approach is suitable for quality improvement in resource-limited laboratories.