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. 2024 Dec 16:13:RP95296.
doi: 10.7554/eLife.95296.

Livestock abortion surveillance in Tanzania reveals disease priorities and importance of timely collection of vaginal swab samples for attribution

Felix Lankester  1   2 , Tito J Kibona  2 , Kathryn J Allan  3 , William de Glanville  3 , Joram J Buza  4 , Frank Katzer  5 , Jo E Halliday  3 , Blandina T Mmbaga  6 , Nick Wheelhouse  7 , Elisabeth A Innes  5 , Kate M Thomas  8 , Obed M Nyasebwa  9 , Emanuel Swai  9 , John R Claxton  3 , Sarah Cleaveland  3
Affiliations

Livestock abortion surveillance in Tanzania reveals disease priorities and importance of timely collection of vaginal swab samples for attribution

Felix Lankester et al. Elife. .

Abstract

Lack of data on the aetiology of livestock diseases constrains effective interventions to improve livelihoods, food security and public health. Livestock abortion is an important disease syndrome affecting productivity and public health. Several pathogens are associated with livestock abortions but across Africa surveillance data rarely include information from abortions, little is known about aetiology and impacts, and data are not available to inform interventions. This paper describes outcomes from a surveillance platform established in Tanzania spanning pastoral, agropastoral and smallholder systems to investigate causes and impacts of livestock abortion. Abortion events were reported by farmers to livestock field officers (LFO) and on to investigation teams. Events were included if the research team or LFO could attend within 72 hr. If so, samples and questionnaire data were collected to investigate (a) determinants of attribution; (b) patterns of events, including species and breed, previous abortion history, and seasonality; (c) determinants of reporting, investigation and attribution; (d) cases involving zoonotic pathogens. Between 2017-2019, 215 events in cattle (n=71), sheep (n=44), and goats (n=100) were investigated. Attribution, achieved for 19.5% of cases, was significantly affected by delays in obtaining samples. Histopathology proved less useful than PCR due to rapid deterioration of samples. Vaginal swabs provided practical and sensitive material for pathogen detection. Livestock abortion surveillance, even at a small scale, can generate valuable information on causes of disease outbreaks, reproductive losses and can identify pathogens not easily captured through other forms of livestock disease surveillance. This study demonstrated the feasibility of establishing a surveillance system, achieved through engagement of community-based field officers, establishment of practical sample collection and application of molecular diagnostic platforms.

Keywords: PCR; Tanzania; community-based; epidemiology; global health; infectious disease; livestock abortion; microbiology; syndromic surveillance; zoonoses.

Plain language summary

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.

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Conflict of interest statement

FL, TK, KA, Wd, JB, FK, JH, BM, NW, EI, KT, ON, ES, JC, SC No competing interests declared

Figures

Figure 1.
Figure 1.. LIvestock field officer reports.
(a) The number and percentage of abortion cases reported by each LFO (95% error bars, n = 215) (b) The relationship between the number of reports per LFO and the distance to the research laboratories based in the town of Moshi.
Figure 2.
Figure 2.. The number of days between abortion and the investigation (95% error bars, n = 213).
No cases were investigated more than after 4 days after the abortion.
Figure 3.
Figure 3.. The difference between the expected and actual proportion of abortion cases in each species and breed (95% error bars, n = 215, exact binomial test, level of significance 0.05).
Value of 0 = the expected number of cases occurred,>0 more than expected,<0 less than expected (LOC = indigenous (local), XB = non-indigenous cross-bred, EX = non-indigenous exotic breed).
Figure 4.
Figure 4.. The number of abortion cases investigated per month (blue columns) shown against mean rainfall recorded in the Arusha region over each month of the study period (red line).
Figure 5.
Figure 5.. The type of samples in which pathogens were detected in the 41 abortion cases for which an attribution was made using PCR are shown.
Each row represents one abortion event. Red - sample type returned a positive result; blue - sample type returned a negative result; grey - sample type was not collected.
Figure 6.
Figure 6.. Predicted probability of attribution being made as a function of increasing delay between abortion and case investigation, as determined by the regression model output.
The blue line indicates the regression line with the 95% confidence interval shaded blue.
Figure 7.
Figure 7.. A logic model illustrating the conceptual links between the inputs, activities, outputs, and short to long-term impacts expected from effective livestock health surveillance with a particular focus on abortion.
Figure 8.
Figure 8.. Map of the study area in northern Tanzania showing selected pastoral, agropastoral and smallholder wards in Kilimanjaro, Arusha, and Manyara Regions.
The number of investigated cases per ward and the study base (Moshi) are shown.
See this image and copyright information in PMC

Update of

  • doi: 10.1101/2024.01.07.574517
  • doi: 10.7554/eLife.95296.1
  • doi: 10.7554/eLife.95296.2

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References

    1. Africa Centres for Disease Control and Prevention Africa CDC - Event Based Surveillance Framework. 2018. [June 21, 2023]. http://www.africacdc.org/resources/strategic-framework/Strategic%0AFrame...
    1. Alemayehu G, Mamo G, Alemu B, Desta H, Tadesse B, Benti T, Bahiru A, Yimana M, Wieland B. Causes and flock level risk factors of sheep and goat abortion in three agroecology zones in Ethiopia. Frontiers in Veterinary Science. 2021;8:615310. doi: 10.3389/fvets.2021.615310. - DOI - PMC - PubMed
    1. Amouei A, Sharif M, Sarvi S, Bagheri Nejad R, Aghayan SA, Hashemi-Soteh MB, Mizani A, Hosseini SA, Gholami S, Sadeghi A, Sarafrazi M, Daryani A. Aetiology of livestock fetal mortality in Mazandaran province, Iran. PeerJ. 2019;6:e5920. doi: 10.7717/peerj.5920. - DOI - PMC - PubMed
    1. Anderson ML, Blanchard PC, Barr BC, Hoffman RL. A survey of causes of bovine abortion occurring in the San Joaquin Valley, California. Journal of Veterinary Diagnostic Investigation. 1990;2:283–287. doi: 10.1177/104063879000200405. - DOI - PubMed
    1. Ashouri H, Hsu KL, Sorooshian S, Braithwaite DK, Knapp KR, Cecil LD, Nelson BR, Prat OP. PERSIANN-CDR: Daily precipitation climate data record from multisatellite observations for hydrological and climate studies. Bulletin of the American Meteorological Society. 2015;96:69–83. doi: 10.1175/BAMS-D-13-00068.1. - DOI

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