Epidemiology of human and animal leptospirosis in Kenya: A systematic review and meta-analysis of disease occurrence, serogroup diversity and risk factors

Background: Leptospirosis is a priority zoonotic disease in Kenya, but an in-depth review of its presence in humans, animals and the environment is lacking. Therefore, we conducted this systematic review and meta-analysis to understand the epidemiological situation to date.

Methodology: We searched for literature in African journals online, AGRIS, Embase, the Leptospira WOAH reference laboratory library, ProMED-mail, PubMed, Scopus, Web of Science, and the institutional repositories of 33 academic institutions and included 66 publications on leptospirosis in Kenya which spanned from 1951 to 2022. The review was registered on the International Platform of Registered Systematic Review and Meta-analysis Protocols (INPLASY).

Findings: Most investigations were done in rural and urban areas in western, southern, central, and coastal areas in Kenya and the largely pastoral eastern and northern areas were under-represented. A wide host range of domestic animals and wildlife was revealed, and occupational exposure was an important risk factor for humans. The microscopic agglutination test (MAT) was the most frequent test, particularly common in studies conducted during the 1980s and 1990s. However, varying MAT panels and cut-off titres were observed. The overall seroprevalence in cattle was 28.2% (95% confidence intervals [CI]: 12.0–53.0; heterogeneity: I2 = 96.7%, τ2 = 1.4), and 11.0% in goats (95% CI: 5.4–21.2; heterogeneity: I2 = 78.8%, τ2 = 0.4). Molecular tests were seldom used to determine species and illustrate strain diversity. There was a lack of awareness of leptospirosis among farmers and health practitioners.

Conclusion: The widespread presence of leptospires and inadequate diagnostic capacity demonstrate that leptospirosis is a common but underreported disease in Kenya. Raising awareness and boosting the country’s diagnostic capacity is crucial to timely detection and disease control.