Q-fever is a zoonotic infectious disease caused by the gram-negative, intracellular, spore-forming bacterium Coxiella burnetii . Infected ruminants (cattle, sheep, and goats) are the reservoirs of the pathogen and thus an important source of infection in humans. This systematic review aims to consolidate the knowledge and awareness of Q-fever in Africa and identify future research opportunities and possible interventions in low-resource settings. We review information on Q-fever epidemiology and the diagnostic challenges in humans and domestic ruminants in Africa from the last 23 years. Six databases including university repositories were searched for relevant articles. A total of 84 studies and 4 theses met the selection criteria and were thus included in the review. They include serological and molecular studies of Q-fever in humans or domestic ruminants in 24/54 African countries. The mean seroprevalence estimates were 16% (95%CI 11–23%) in humans; 14% (95%CI 10–20%) in cattle; 13% (95%CI 9–18%) in sheep; and 21% (95%CI 15–29%) in goats. The mean prevalence for molecular detection of the pathogen were 3% (95%CI 0–16%) in humans; 9% (95%CI 4–19%) in cattle; 16% (95%CI 5–41%) in sheep; and 23% (95%CI 20–80%) in goats. The number of studies that identified risk factors for exposure among domestic ruminants was: sex (n = 6), age (n = 17), contact with other animals (n = 5), lack of quarantine of newly purchased animals (n = 1), extensive grazing system (n = 4), herd size (2), history of abortion (n = 5), absence of vaccination (n = 2), and high temperature (n = 1). The number of studies that reported protective factors was: sanitation (n = 2), burying and/ or burning the aborted foetus (n = 2), and young (age) (n = 2). The studies that identified risk factors for human disease infection included: close contact to animals (n = 7), age (n = 3), and gender (n = 5), while those identifying protective factors included: living in non-irrigated areas (n = 1), awareness/knowledge about zoonosis (n = 1), rodent control (n = 1), sanitation/disinfection of equipment after and before use (n = 1), occasional grazing (n = 1), and do nothing to aborted materials (n = 1). Diagnostic challenges such as poverty, lack of a well-equipped laboratory with biosafety level 3 specific for Q-fever testing, unspecific and self-limiting clinical signs/symptoms, lack of gold standard test, and variation in test specificity and sensitivity were identified. The disease is likely to be widespread in Africa and of public importance and underreported thus ‘One Health’ approaches to future studies are recommended. Further studies should focus on concurrent studies of human and livestock populations. One Health Impact Statement This review applies to One Health stakeholders including, the public, players in the livestock value chain, animal/ human/ environmental health workers, policy makers, and other implementers. This review summarizes the available information regarding Q-fever ( Coxiella burnetii ) in animals and humans in Africa, providing new information on the magnitude of the disease, and risk factors for infection. This information highlights the need for collaboration among One Health stakeholders and multisectoral cooperation towards achieving the One Health goals. The sharing of knowledge generated through research from academic, non-academic, and local/ indigenous knowledge will allow a new foundation for disease control that is applicable and beneficial to all stakeholders under the One Health umbrella rather than academic scientists alone.

Q fever is a zoonotic disease, resulting from infection with Coxiella burnetii. Infection in cattle can cause abortion and infertility, however, there is little epidemiological information regarding the disease in dairy cattle in Tanzania. Between July 2019 and October 2020, a serosurvey was conducted in six high dairy producing regions of Tanzania. Cattle sera were tested for antibodies to C. burnetii using an indirect enzyme-linked immunosorbent assay. A mixed effect logistic regression model identified risk factors associated with C. burnetii seropositivity. A total of 79 out of 2049 dairy cattle tested positive with an overall seroprevalence of 3.9% (95% CI 3.06–4.78) across the six regions with the highest seroprevalence in Tanga region (8.21%, 95% CI 6.0–10.89). Risk factors associated with seropositivity included: extensive feeding management (OR 2.77, 95% CI 1.25–3.77), and low precipitation below 1000 mm (OR 2.76, 95% 1.37–7.21). The disease seroprevalence is relatively low in the high dairy cattle producing regions of Tanzania. Due to the zoonotic potential of the disease, future efforts should employ a “One Health” approach to understand the epidemiology, and for interdisciplinary control to reduce the impacts on animal and human health.

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.

Bovine brucellosis is a bacterial zoonoses caused by Brucella abortus. We conducted a cross-sectional study to determine brucellosis seroprevalence and risk factors among smallholder dairy cattle across six regions in Tanzania. We sampled 2048 dairy cattle on 1374 farms between July 2019 and October 2020. Sera were tested for the presence of anti-Brucella antibodies using a competitive enzyme-linked immunosorbent assay. Seroprevalence was calculated at different administrative scales, and spatial tests were used to detect disease hotspots. A generalized mixed-effects regression model was built to explore the relationships among Brucella serostatus, animals, and farm management factors. Seroprevalence was 2.39% (49/2048 cattle, 95% CI 1.7–3.1) across the study area and the Njombe Region represented the highest percentage with 15.5% (95% CI 11.0–22.0). Moreover, hotspots were detected in the Njombe and Kilimanjaro Regions. Mixed-effects models showed that having goats (OR 3.02, 95% C 1.22–7.46) and abortion history (OR 4.91, 95% CI 1.43–16.9) were significant risk factors for brucellosis. Education of dairy farmers regarding the clinical signs, transmission routes, and control measures for brucellosis is advised. A One Health approach is required to study the role of small ruminants in cattle brucellosis and the status of brucellosis in dairy farmers in the Njombe and Kilimanjaro Regions.