COVID-19 mass testing and sequencing: Experiences from a laboratory in Western Kenya.

Background: The Basic Science Laboratory (BSL) of the Kenya Medical Research Institute/Walter Reed Project in Kisumu, Kenya addressed mass testing challenges posed by the emergent coronavirus disease 2019 (COVID-19) in an environment of global supply shortages. Before COVID-19, the BSL had adequate resources for disease surveillance and was therefore designated as one of the testing centres for COVID-19. Intervention: By April 2020, the BSL had developed stringent safety procedures for receiving and mass testing potentially infectious nasal specimens. To accommodate increased demand, BSL personnel worked in units: nucleic acid extraction, polymerase chain reaction, and data and quality assurance checks. The BSL adopted procedures for tracking sample integrity and minimising cross-contamination. Lessons learnt: Between May 2020 and January 2022, the BSL tested 63 542 samples, of which 5375 (8.59%) were positive for COVID-19; 1034 genomes were generated by whole genome sequencing and deposited in the Global Initiative on Sharing All Influenza Data database to aid global tracking of viral lineages. At the height of the pandemic (August and November 2020, April and August 2021 and January 2022), the BSL was testing more than 500 samples daily, compared to 150 per month prior to COVID-19. An important lesson from the COVID-19 pandemic was the discovery of untapped resilience within BSL personnel that allowed adaptability when the situation demanded. Strict safety procedures and quality management that are often difficult to maintain became routine. Recommendations: A fundamental lesson to embrace is that there is no 'one-size-fits-all' approach and adaptability is the key to success.

Seroprevalence of Coxiella burnetii in patients presenting with acute febrile illness at Marigat District Hospital, Baringo County, Kenya.

Q fever is not routinely diagnosed in Kenyan hospitals. This study reports on Q fever in patients presenting at Marigat District Hospital, Kenya, with febrile illness. ELISA was used to detect Coxiella burnetii phase antigens. Of 406 patients, 45 (11.1%) were judged to have acute disease (phase II IgM or IgG > phase I IgG), 2 (0.5%) were chronic (phase I IgG titer >800 or phase I IgG > phase II IgG), while 26 (6.4%) had previous exposure (phase I IgG titer <800). Age (6-10 years, p = 0.002) and contact with goats (p = 0.014) were significant risk factors. Compared to immunofluorescence antibody test, the sensitivity and specificity for phase I IgG were 84% and 98%, respectfully, 46% and 100% for phase II IgG and 35% and 89% for phase II IgM. It is concluded that the low sensitivity of phase II ELISA underestimated the true burden of acute Q fever in the study population.

Serological Evidence of Yersiniosis, Tick-Borne Encephalitis, West Nile, Hepatitis E, Crimean-Congo Hemorrhagic Fever, Lyme Borreliosis, and Brucellosis in Febrile Patients Presenting at Diverse Hospitals in Kenya.

Data on pathogen prevalence is crucial for informing exposure and disease risk. We evaluated serological evidence of tick-borne encephalitis (TBE), West Nile (WN), Hepatitis E virus (HEV), Crimean-Congo Hemorrhagic Fever (CCHF), Yersiniosis, Lyme Disease (LD), and brucellosis in 1033 patients presenting with acute febrile illness at 9 health care facilities from diverse ecological zones of Kenya: arid and semiarid (Garissa District Hospital, Lodwar District Hospital, Marigat District Hospital, Gilgil District Hospital), Lake Victoria basin (Kisumu District Hospital, Alupe District Hospital, Kombewa Sub-County Hospital), Kisii highland (Kisii District Hospital), and coastal (Malindi District Hospital). Epidemiological information of the patients such as geography, age, gender, and keeping animals were analyzed as potential risk factors. Of the 1033 samples, 619 (59.9%) were seropositive to at least one pathogen by IgM (current exposure), IgG/IgM (recent exposure), and IgG (past exposure). Collective seroprevalence for current, recent, and past to the pathogens was 9.4%, 5.1%, and 21.1% for LD; 3.6%, 0.5%, and 12.4% for WN; 0.9%, 0.5%, and 16.9% for HEV; 5.8%, 1.3%, and 3.9% for brucellosis; 5.7%, 0.2%, and 2.3% for yersiniosis; 1.7%, 0%, and 6.2% for TBE; and 0.4%, 0%, and 1.9% for CCHF. Brucellosis risk was higher in patients recruited at Garissa District Hospital (odds ratio [OR] = 3.41), HEV (OR = 2.45) and CCHF (OR = 5.46) in Lodwar District Hospital, LD in Alupe District Hospital (OR = 5.73), Kombewa Sub-district hospital (OR = 8.17), and Malindi District hospital (OR = 3.3). Exposure to LD was highest in the younger age group, whereas yersiniosis did not vary with age. Age was a significant risk for WN, brucellosis, CCHF, TBE, and HEV and in those aged >14 years there was an increased risk to WN (OR = 2.30, p < 0.0001), brucellosis (OR = 1.84, p = 0.005), CCHF (OR = 4.35, p = 0.001), TBE (OR = 2.78, p < 0.0001), and HEV (OR = 1.94, p = 0.0001). We conclude that LD is pervasive and constitutes a significant health burden to the study population, whereas yersiniosis and CCHF are not significant threats. Going forward, community-based studies will be needed to capture the true seroprevalence rates and the associated risk factors.