Seroepidemiology of Leptospira serovar Hardjo and associated risk factors in smallholder dairy cattle in Tanzania

Abstract

Background: Smallholder dairy farming is crucial for the Tanzanian dairy sector which generates income and employment for thousands of families. This is more evident in the northern and southern highland zones where dairy cattle and milk production are core economic activities. Here we estimated the seroprevalence of Leptospira serovar Hardjo and quantified potential risk factors associated with its exposure in smallholder dairy cattle in Tanzania.

Methods: From July 2019 to October 2020, a cross-sectional survey was carried out in a subset of 2071 smallholder dairy cattle. Information about animal husbandry and health management was collected from farmers, and blood was taken from this subset of cattle. Seroprevalence was estimated and mapped to visualize potential spatial hotspots. The association between a set of animal husbandry, health management and climate variables and ELISA binary results was explored using a mixed effects logistic regression model.

Results: An overall seroprevalence of 13.0% (95% CI 11.6-14.5%) for Leptospira serovar Hardjo was found in the study animals. There was marked regional variations with the highest seroprevalence in Iringa 30.2% (95% CI 25.1-35.7%) and Tanga 18.9% (95% CI 15.7-22.6) with odds ratios of OR = 8.13 (95% CI 4.23-15.63) and OR = 4.39 (95% CI 2.31-8.37), respectively. Multivariate analysis revealed the individual animal factors that were a significant risk for Leptospira seropositivity in smallholder dairy cattle were: animals over 5 years of age (OR = 1.41, 95% CI 1.05-1.9); and indigenous breed (OR = 2.78, 95% CI 1.47-5.26) compared to crossbred animals SHZ-X-Friesian (OR = 1.48, 95% CI 0.99-2.21) and SHZ-X-Jersey (OR = 0.85, 95% CI 0.43-1.63). Farm management factors significantly associated with Leptospira seropositivity included: hiring or keeping a bull for raising purposes (OR = 1.91, 95% CI 1.34-2.71); distance between farms of more than 100 meters (OR = 1.75, 95% CI 1.16-2.64); cattle kept extensively (OR = 2.31, 95% CI 1.36-3.91); farms without cat for rodent control (OR = 1.87, 95% CI 1.16-3.02); farmers with livestock training (OR = 1.62, 95% CI 1.15-2.27). Temperature (OR = 1.63, 95% CI 1.18-2.26), and the interaction of higher temperature and precipitation (OR = 1.5, 95%CI 1.12-2.01) were also significant risk factors.

Conclusion: This study indicated seroprevalence of Leptospira serovar Hardjo, as well as the risk factors driving dairy cattle leptospirosis exposure in Tanzania. The study showed an overall high leptospirosis seroprevalence with regional variations, where Iringa and Tanga represented the highest seroprevalence and risk. The study highlighted the urgent need to understand the human exposures and risks from this important zoonosis to develop control measures and awareness of the problem and quantify the economic and production impacts through abortion and milk loss. In addition, given that the available data was limited to Leptospira serovar Hardjo, the study recommends more studies to identify serologically the most common serovars in cattle for targeted vaccination and risk reduction.

Fig 1. Geographic location of farms, regions, and dairy zones in Tanzania.

a), geographic location across six regions from two economically important dairy zones over an elevation map of Tanzania. Red squares indicate the important dairy zones. b), a close-up of the northern zone integrated by the regions of Arusha, Kilimanjaro and Tanga in which a total of 12 districts were sampled. c), a close-up of the southern highland zone of Tanzania integrating the Iringa, Njombe, and Mbeya regions in which 11 districts were sampled. In all panels, farm location (dots) is colour-coded to indicate their administrative region. Map source: https://www.usgs.gov/centers/eros/science/usgs-eros-archive-digital-elevation-global-multi-resolution-terrain-elevation.

Fig 2. Geographic mapping of leptospirosis distributions and hotspots in 24 districts of study across six regions from two economically important dairy zones of Tanzania.

The northern zone (a, b, and c) and southern zone (d, e, and f). a) Arusha region consisting of Arusha City Council (ACC), Meru District Council (MeDC), Arusha District Council (ADC), b) Kilimanjaro region consisting of Rombo District Council (RoDC), Moshi District Council (MoRDC), Hai District Council (HDC), Siha District Council (SDC), c) Tanga region consisting of Tanga City Council (TCC), Muheza District (MuDC), Korogwe District (KRDC), Korogwe Town Council (KTC), Lushoto District (LDC), d) Mbeya region consisting of Mbeya District Council (MDC), Mbeya City Council (MCC), Mbozi District Council (MbDC), e) Njombe region consisting of Njombe District Council (NDC), Makambako Town Council (MaTC), Rungwe District Council (RuDC), Njombe Town Council (NTC) and f) Iringa region consisting of Iringa District Council (IDC), Iringa Municipal Council (IMC), Mafinga Town Council (MTC), Mufindi District Council (MuDC). Map source: data shape file for Tanzania map at all levels downloaded from https://gadm.org/.

Fig 3. A forest plot summarizing the final multivariable model of significant predictive variables for leptospirosis association to seropositive occurrence in smallholder Tanzanian dairy cattle.

Fig 4. Three-dimensional graph shows the predicted probability of Leptospira serovar Hardjo seropositivity, Pr(seropositive), as a result of the interaction of increased temperature (°C) and precipitation (mm), and accounting for all other fixed effects in final generalised linear mixed effects model.