We implemented a cross-sectional study in Tana River County, Kenya, a Rift Valley fever (RVF)-endemic area, to quantify the strength of association between RVF virus (RVFv) seroprevalences in livestock and humans, and their respective intra-cluster correlation coefficients (ICCs). The study involved 1932 livestock from 152 households and 552 humans from 170 households. Serum samples were collected and screened for anti-RVFv immunoglobulin G (IgG) antibodies using inhibition IgG enzyme-linked immunosorbent assay (ELISA). Data collected were analysed using generalised linear mixed effects models, with herd/household and village being fitted as random variables. The overall RVFv seroprevalences in livestock and humans were 25.41% (95% confidence interval (CI) 23.49–27.42%) and 21.20% (17.86–24.85%), respectively. The presence of at least one seropositive animal in a household was associated with an increased odds of exposure in people of 2.23 (95% CI 1.03–4.84). The ICCs associated with RVF virus seroprevalence in livestock were 0.30 (95% CI 0.19–0.44) and 0.22 (95% CI 0.12–0.38) within and between herds, respectively. These findings suggest that there is a greater variability of RVF virus exposure between than within herds. We discuss ways of using these ICC estimates in observational surveys for RVF in endemic areas and postulate that the design of the sentinel herd surveillance should consider patterns of RVF clustering to enhance its effectiveness as an early warning system for RVF epidemics.

The long-term care sector is generally characterised by low pay and difficult working conditions. Understanding pay structures and differentials within this sector is important in enhancing recruitment, retention, quality of care and productivity. This article uses new national data on the long-term care workforce in England to investigate employer and individual effects on pay levels and differentials, using mixed-effects modelling controlling for region, sector and employer hierarchical factors. We further examine whether gender and ethnic pay gaps exist among different groups of workers. The results indicate a significant relationship between sector and pay across different job roles. The analysis further identifies ethnic and gender pay differences even after controlling for the effects of sector and individual employers. The implications of this are discussed in relation to sustaining the care workforce in the context of an ageing society and the potential for structural employment marginalisation to reflect the marginalisation of older people receiving care.