Livestock reproductive losses are a major concern for farmers worldwide as they cause significant economic impacts, particularly for those that are heavily dependent on their livestock for food security. On top of this, such losses can also pose a threat to public health if they are caused by infections that can also be transmitted to humans.

Spontaneous abortion (when a pregnancy ends early and a foetus is expelled) can be caused by a number of factors, including infections, nutritional deficiencies and genetic issues. Identifying the cause is easier if high quality samples are collected from the aborting mother and the foetus. However, this can be difficult in some low-and middle-income countries, where such samples are rarely collected and analysed.

Lankester et al. wanted to investigate whether livestock abortion surveillance could be used to understand the causes and effects of livestock abortion in Tanzania. To do this, the researchers asked farmers to report abortion cases to livestock field officers. These officers alerted investigation teams to collect samples and conduct questionnaires which provided information on the livestock breeds, seasonal patterns and potential pathogens involved in 215 abortion cases in cattle, sheep and goats.

Analysis revealed that successfully identifying the cause of abortion depends heavily on the timing and quality of the samples. The chances of diagnosis decreased with each day that passed between the abortion and the samples being collected. Vaginal swabs, which are easier to collect than those from the placenta or aborted foetus, were the most effective at detecting abortion-causing infectious agents.

The analysis also revealed that many of the livestock which had an abortion in the previous 12 months had experienced one or more abortions before. This suggests that an infectious agent may be the cause and that, through surveillance and accurate diagnosis, managing these animals by removing them from the herd might improve productivity. Abortions were also more common in non-local breeds of cattle and goats, suggesting that local breeds may have a degree of resistance to abortion.

The findings of Lankester et al. reveal a method of livestock surveillance that is feasible in areas with limited resources and could be used to increase understanding of the causes of livestock abortion. Such information could help to direct interventions that prevent abortion and improve livestock health, ultimately helping to improve food security while reducing the risk of infection for livestock-owners in lower- and middle-income countries.

Livestock reproductive losses, including spontaneous abortion, are a major concern for the livestock industry worldwide, resulting in significant economic loss and posing a threat to public health (Food and Agriculture Organization, 2011). The impacts of livestock abortion on the world’s poorest livestock-keepers, who are heavily dependent on livestock for food security and livelihoods (Food and Agriculture Organization, 2011), is likely to be substantial. For these families, the loss of a livestock foetus and a subsequent decline in milk production reduces the availability of a high-quality food source (milk) that can be essential for childhood growth and cognitive development (Neumann et al., 2003). In addition, livestock reproductive losses reduce income (from sales of meat and milk), and cause a loss of livestock assets that are a critical source of wealth, collateral or a safety net in times of need (The World Bank, 2021). Recent analyses have shown that because of the need for increased spending on animal management, livestock abortions mayalso have indirect negative impacts on household expenditure and education (Haseeb et al., 2019). Livestock abortion can also pose a direct threat to human health because many abortigenic agents are also zoonotic (Givens and Marley, 2008; Thomas et al., 2022).

Surveillance is defined as the real-time (or near real-time) collection, analysis, interpretation, and dissemination of health-related data to enable the early identification of the impact (or absence of impact) of potential health threats, which require effective action (Hulth, 2014). Effective livestock health surveillance provides critical data for evidence-based approaches to livestock disease control and management but this requires reliable, high-quality, and timely data that can be drawn from multiple sources (George et al., 2021). Over the past decade, increasing attention has been given to animal health syndromic surveillance (Dórea and Vial, 2016), which relies on detection of health indicators, such as livestock abortion, that are discernible before a confirmed diagnosis is made. However, systematic reviews of the literature that collectively cover a period from 2000 to 2016 indicate that syndromic surveillance programmes have mostly been implemented in Europe, North America or Australasia with only a single pilot project identified in Africa (Dórea and Vial, 2016; Dórea et al., 2011).

In public health, event-based surveillance has also been gaining attention for the early detection of unusual events that might signal acute and emerging human health risks (World Health Organization, 2008; Africa Centres for Disease Control and Prevention, 2018). This involves the collection, analysis and interpretation of information through both formal and informal channels to rapidly identify unusual or unexpected health events, such as disease outbreaks, emerging infectious diseases, or other public health threats. Although the WHO guidelines for event-based surveillance (World Health Organization, 2008) make explicit reference to the capture of information around unusual disease events in animals, the development of integrated early-warning systems involving animal disease events is still very limited. Livestock surveillance has a clear potential for identifying and preventing outbreaks of zoonotic and emerging diseases; a substantial proportion (39.4%) of livestock pathogens infect humans (Cleaveland et al., 2001), and ungulates harbour more zoonotic pathogens than any other taxonomic group (Woolhouse and Gowtage-Sequeria, 2005). With several abortigenic agents also causing emerging livestock diseases, for example those caused by Schmallenberg virus, bluetongue virus and porcine reproductive and respiratory syndrome virus, livestock abortion may represent a particularly important syndromic target for zoonotic and emerging disease surveillance. However, there is limited information available on current practices, effectiveness, and challenges/opportunities of livestock abortion surveillance, particularly in low- and middle-income countries.

Livestock abortion has many causes, including infectious, nutritional, physical, and genetic factors. The diversity of causative agents and variation in the relative importance of agents across different livestock management systems and geographies makes abortion diagnosis complex and challenging (Wolf-Jäckel et al., 2020). Challenges relate to timely collection of diagnostic samples, sample availability and deterioration, biases in detectability of agents, as well as complexities around establishment of a causal aetiology, particularly for pathogens such as Coxiella burnetii and Escherichia coli, which can often be present as incidental infections (Thomas et al., 2022; Wolf-Jäckel et al., 2020). As a result, aetiological attribution of livestock abortion rarely exceeds 35%, even in well-resourced industrialised livestock systems (Cabell, 2007; Wolf-Jäckel et al., 2020) and data are particularly sparse in African livestock systems.

A recent prospective study of the aetiologies of livestock abortion, carried out in northern Tanzania (Thomas et al., 2022), investigated 215 cases of livestock abortion of which an attribution was made in 41 cases (19%). The infectious causes of abortion were identified as Rift Valley fever virus (RVFV) in 14 cases (6.6%), followed by Neospora caninum in 10 (4.7%), pestiviruses in 9 (4.2%), Coxiella burnetii in 6 (2.8%), and Brucella sp., and Toxoplasma gondii in one case each (0.5%). Our study draws on the operational data generated from establishment of a livestock abortion study to examine characteristics of reporting and investigation of cases of livestock abortion. While this study was not designed as a systematic or comprehensive evaluation of a surveillance system, we present data on several key attributes (ECDC, 2014) of the platform, including simplicity, data quality, representativeness, timeliness, and usefulness. We discuss our findings in relation to the feasibility, practicality, and value of establishing a livestock abortion surveillance framework to support evidence-based interventions to improve livestock development, livelihoods, and human health in Africa.

This study demonstrated the feasibility of establishing a surveillance platform for reporting and diagnosing cases of livestock abortion and that these investigations, even at small scale, have generated important information on livestock diseases, and their investigation, in Tanzania. This included information that, to our knowledge, has not been captured or reported through existing surveillance systems.

Key findings were that: (i) livestock abortion can be a target for syndromic and/or event-based surveillance, with abortion incidents sufficiently distinctive and noteworthy to be reported by farmers to livestock field officers in a timely manner for investigation; (ii) pragmatic and robust protocols for sample collection and laboratory diagnosis can be established, even in resource-limited settings, to generate important etiological and epidemiological data; (iii) the likelihood of obtaining an etiological diagnosis depended on the timeliness of reporting and quality of sample collection; (iv) there was wide variation in reporting and investigation of cases by different LFOs and this did not appear to be associated with the distance between the ward and the investigation center; (v) in many herds prior livestock abortions were reported to have occurred in the 12 months preceding the investigated abortion event; (vi) abortions and repeat abortions reported disproportionately more frequently in non-indigenous breeds (cross-bred and exotic) than local breeds; and (vii) abortion cases wthere reported and investigated more frequently during drier periods, although there was no evidence of a relationship with monthly rainfall.

This study suggests that livestock abortion cases are sufficiently distinctive and observable to be reported by farmers to LFOs, would have widespread acceptability as a target for syndromic or event-based surveillance and would have considerable utility for farmers as well as for the livestock and public health sectors. The platform demonstrated the potential for generating high-quality aetiological data on previously relatively unrecognised livestock disease problems in Tanzania, such as Neospora caninum and novel pestiviruses, as well as data on endemic zoonoses, such as Q fever, brucellosis and toxoplasmosis (Thomas et al., 2022). Reports of unusual livestock abortion cases also provided an early warning of acute human health risks, as shown in this study area by the detection of an outbreak of RVF in livestock in peri-urban smallholder cattle (de Glanville et al., 2022), which was the catalyst for subsequent public health investigations that identified several linked human RVF cases, including one fatality (Madut et al., 2024).

An attempt was made to gauge the sensitivity of the surveillance platform by estimating the percentage of expected abortions that the investigated cases represented. This was carried out using data on ward-level livestock numbers drawn from Ministry of Livestock and Fisheries records. However, given the dynamic nature of livestock populations in the study area and shifts in ward configurations, these estimates should be considered approximate figures only. Overall the sensitivity of this platform was low, with the highest ward level sensitivity (12.4%) below a mean sensitivity of 34% reported for bovine abortion surveillance systems in France (Bronner et al., 2015). Nonetheless, given that this was the first time that an abortion surveillance platform of this kind had been introduced, and the logistic and communication challenges inherent to this type of low-income setting, our study gives confidence of the feasibility and potential utility of this approach. Despite the limitations of the data, our conclusion that there is wide variation in the sensitivity of the surveillance platform across wards is likely to be robust. This finding, together with the ability of the platform to investigate only a very small proportion of expected abortion cases overall, has implications for the representativeness of data generated, which needs to be considered when interpreting the results reported here.

Contrary to expectations, the location and distance of the ward was not associated with the probability of cases being investigated. Association between cases investigated and farming system could not be determined as the number of wards was relatively small and the number representative of each system were not equal. However, relatively few cases were reported and investigated in the three agropastoral system wards, whilst both high and low rates of reporting occurred in individual wards within the smallholder (seven wards) and pastoral (five wards) systems. This suggests that LFOs and farmers in some wards were much more engaged and motivated than in others. To date, much investment in animal and human surveillance has been directed towards strengthening laboratory diagnostic capacity. While this is clearly essential, support also needs to be given to engaging, training, and motivating farmers and front-line animal health workers to effectively report both routine and unusual animal disease events. Understanding why and how animal keepers and LFOs are incentivised to report and investigate livestock health events will be essential for improving the reach and sensitivity of future surveillance platforms. The infrastructure for LFO engagement across Tanzania provides a valuable platform for timely and cost-effective reporting of abortions and other disease events but seems to be underutilised in existing surveillance systems.

The effectiveness of the platform in allowing an aetiological diagnosis to be reached was significantly impacted by the timeliness of investigation. The impact of delays may be explained by degradation of diagnostic samples, which also affected the utility of histopathological diagnosis (Thomas et al., 2022). Delays were caused by several factors, including the time taken by the investigation team to reach households due to remoteness of some areas and multiple cases being reported in different areas on the same day. These findings underscore the importance of being able to respond rapidly to cases and, where access is difficult, of providing locally suitable means of transport.

A reactive surveillance platform that is managed locally, for example by ward-based LFOs, will require the establishment of effective and safe protocols for collection and transport of samples for laboratory diagnosis that can be carried out without the need for long-distance travel of more highly trained investigators. Protocols for collection of vaginal swabs from aborting dams, which proved effective for both pathogen detection and attribution, may be of value. In this study, the greater accessibility of vaginal swabs, as compared to placental samples and foetal samples, meant more attribution of abortigenic pathogens was attained through these samples (Figure 5). They also require less handling of potentially infectious tissues and are more reliably accessible than placental and foetal tissues, which are often consumed by scavengers or disposed of by the farmer. Indeed, collection of vaginal swabs from the dam was possible in almost all cases investigated in this study. Thus, while logistic, financial, and capacity constraints for comprehensive sampling and investigation of livestock abortions are likely to exist across Africa, these need not preclude the establishment of simple and robust protocols that can yield valuable surveillance data.

All data generated or analysed during this study are included in the manuscript and supporting files.

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Author details

1. Felix Lankester

   1. Paul G. Allen School for Global Health, Washington State University, Pullman, United States
   2. Global Animal Health Tanzania, Arusha, United Republic of Tanzania

   Contribution

   Conceptualization, Data curation, Formal analysis, Supervision, Investigation, Methodology, Writing – original draft, Project administration, Writing – review and editing

   For correspondence

   felix.lankester@wsu.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-0802-0693

2. Tito J Kibona

   Global Animal Health Tanzania, Arusha, United Republic of Tanzania

   Contribution

   Project administration, Writing – review and editing

   Competing interests

   No competing interests declared

3. Kathryn J Allan

   School of Biodiversity, One Health, and Veterinary Medicine, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom

   Contribution

   Conceptualization, Data curation, Formal analysis, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-6612-889X

4. William de Glanville

   School of Biodiversity, One Health, and Veterinary Medicine, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom

   Contribution

   Validation, Writing – review and editing

   Competing interests

   No competing interests declared

5. Joram J Buza

   Nelson Mandela African Institution of Science and Technology, Arusha, United Republic of Tanzania

   Contribution

   Supervision, Project administration, Writing – review and editing

   Competing interests

   No competing interests declared

6. Frank Katzer

   Moredun Research Institute, Pentlands Science Park, Edinburgh, United Kingdom

   Contribution

   Investigation, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-5902-4136

7. Jo E Halliday

   School of Biodiversity, One Health, and Veterinary Medicine, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom

   Contribution

   Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-1329-9035

8. Blandina T Mmbaga

   Kilimanjaro Clinical Research Institute, Moshi, United Republic of Tanzania

   Contribution

   Supervision, Methodology, Project administration, Writing – review and editing

   Competing interests

   No competing interests declared

9. Nick Wheelhouse

   School of Applied Sciences, Edinburgh Napier University, Edinburgh, United Kingdom

   Contribution

   Project administration, Writing – review and editing

   Competing interests

   No competing interests declared

10. Elisabeth A Innes

    Moredun Research Institute, Pentlands Science Park, Edinburgh, United Kingdom

    Contribution

    Data curation, Writing – review and editing

    Competing interests

    No competing interests declared

11. Kate M Thomas

    Centre for International Health, University of Otago, Dunedin, New Zealand

    Contribution

    Data curation, Formal analysis, Investigation, Methodology, Project administration, Writing – review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-1589-8314

12. Obed M Nyasebwa

    Ministry of Livestock and Fisheries, Dodoma, United Republic of Tanzania

    Contribution

    Supervision, Project administration, Writing – review and editing

    Competing interests

    No competing interests declared

13. Emanuel Swai

    Ministry of Livestock and Fisheries, Dodoma, United Republic of Tanzania

    Contribution

    Project administration, Writing – review and editing

    Competing interests

    No competing interests declared

14. John R Claxton

    School of Biodiversity, One Health, and Veterinary Medicine, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom

    Contribution

    Conceptualization, Funding acquisition, Project administration, Writing – review and editing

    Competing interests

    No competing interests declared

15. Sarah Cleaveland

    School of Biodiversity, One Health, and Veterinary Medicine, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom

    Contribution

    Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Writing – original draft, Project administration, Writing – review and editing

    Competing interests

    No competing interests declared

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