Prospective cohort study reveals unexpected aetiologies of livestock abortion in northern Tanzania

Abstract

Livestock abortion is an important cause of productivity losses worldwide and many infectious causes of abortion are zoonotic pathogens that impact on human health. Little is known about the relative importance of infectious causes of livestock abortion in Africa, including in subsistence farming communities that are critically dependent on livestock for food, income, and wellbeing. We conducted a prospective cohort study of livestock abortion, supported by cross-sectional serosurveillance, to determine aetiologies of livestock abortions in livestock in Tanzania. This approach generated several important findings including detection of a Rift Valley fever virus outbreak in cattle; high prevalence of C. burnetii infection in livestock; and the first report of Neospora caninum, Toxoplasma gondii, and pestiviruses associated with livestock abortion in Tanzania. Our approach provides a model for abortion surveillance in resource-limited settings. Our findings add substantially to current knowledge in sub-Saharan Africa, providing important evidence from which to prioritise disease interventions.

Figure 1

Distribution of villages in cross-sectional studies for serologic baseline testing (2013–2016; red dots) and abortion cohort sampling wards (2017–2019; yellow shading) with number of abortion events investigated, Arusha, Kilimanjaro, and Manyara Regions, northern Tanzania. Map created using QGIS version 3.22.1 (https://www.qgis.org/en/site/). Shapefiles were downloaded from GADM (https://gadm.org/) and ICPAC (geoportal.icpac.net).

Figure 2

Seroprevalence of pathogens from cross-sectional studies (2013–2015 and 2016) in cattle, goats, and sheep, northern Tanzania. Where x = not tested and error bars represent Clopper-Pearson 95% confidence intervals.

Figure 3

Results of evolutionary analysis of the N^Pro coding region from pestivirus sequences obtained from cattle and sheep sampled in the abortion cohort study, northern Tanzania. The evolutionary history was inferred using the Maximum Likelihood method and Tamura-Nei model of nucleotide substitution. The tree with the highest log likelihood is shown. The percentage of trees from 500 Bootstrap repeats in which the associated taxa clustered together is shown next to the branches. Evolutionary analyses were conducted in MEGA X. Reference sequences representing nine pestivirus species were also included and are labelled with virus species (A–H,K), genotype and strain name and Genbank accession numbers. Pestivirus species are also shown by bracket labels on the right of the figure. Samples analysed in this study are shown in bold and labelled with unique identifiers (SD/F1-XXX), where SD denotes vaginal swab taken from aborting dam; SF denotes swab taken from aborted foetus. APPV atypical porcine pestivirus, BDV border disease virus, BVDV bovine viral diarrhoea virus, CSFV classical swine fever virus.