Livestock abortion surveillance in Tanzania reveals disease priorities and importance of timely collection of vaginal swab samples for attribution
- Paul G. Allen School for Global Health, Washington State University, United States
- Global Animal Health Tanzania, United Republic of Tanzania
- School of Biodiversity, One Health, and Veterinary Medicine, College of Medical, Veterinary and Life Sciences, University of Glasgow, United Kingdom
- Nelson Mandela African Institution of Science and Technology, United Republic of Tanzania
- Moredun Research Institute, Pentlands Science Park, United Kingdom
- Kilimanjaro Clinical Research Institute, United Republic of Tanzania
- School of Applied Sciences, Edinburgh Napier University, United Kingdom
- Centre for International Health, University of Otago, New Zealand
- Ministry of Livestock and Fisheries, United Republic of Tanzania
Figures
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
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
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
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
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
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
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
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.
Tables
Table 1
The number (and percentage) of abortion cases by species and agro-ecological zone and the composition of the livestock herds (and percentage) in investigated households.
| Event | Category | Number (%) |
|---|---|---|
| Number of abortion cases | All species | 215 |
| Cattle | 71 (33%) | |
| Goats | 100 (46.5%) | |
| Sheep | 44 (20.5%) | |
| Number of abortion cases in each agricultural ecological zone | Pastoral | 144 (67.0%) |
| Agro-pastoral | 1 (0.5%) | |
| Peri-urban | 70 (32.5%) | |
| Number of households that had an abortion event | Households | 150 |
| Number of households in each agricultural ecological zone | Pastoral | 84 (56.0%) |
| Agro-pastoral | 1 (0.7%) | |
| Peri-urban | 65 (43.3%) | |
| Composition of the 150 herds | Cattle, goats and sheep | 77 (51.3%) |
| Cattle and goats | 17 (11.3%) | |
| Goats and sheep | 7 (4.7%) | |
| Cattle and sheep | 1 (0.7%) | |
| Cattle only | 40 (26.6%) | |
| Goats only | 8 (5.3%) |
Table 2
Output of final regression model investigating determinants of attribution.
| Odds Ratio | 2.5% | 97.5% | z value | p | |
|---|---|---|---|---|---|
| (Intercept) | 0.353 | 0.053 | 2.361 | –1.074 | 0.283 |
| Delay | 0.539 | 0.306 | 0.95 | –2.139 | 0.032 |
| Goat | 0.195 | 0.058 | 0.653 | –2.651 | 0.008 |
| Sheep | 0.615 | 0.142 | 2.664 | –0.65 | 0.516 |
| Foetus present | 0.936 | 0.345 | 2.544 | –0.129 | 0.897 |
| Placental present | 1.779 | 0.621 | 5.094 | 1.074 | 0.283 |
| Milk collected | 2.405 | 0.639 | 9.055 | 1.297 | 0.195 |
Additional files
-
Supplementary file 1
Herd level summary statistics are provided.
- https://cdn.elifesciences.org/articles/95296/elife-95296-supp1-v1.docx
-
Supplementary file 2
The actual number of abortions reported for each species and breed and, based on the proportion of each breed in all the herds that reported cases, the expected number of abortions.
- https://cdn.elifesciences.org/articles/95296/elife-95296-supp2-v1.docx
-
Supplementary file 3
A copy of the household questionnaire (comprised of mixed open and closed questions) conducted to collect information on livestock demographics, livestock abortion history, the aborting dam (age, breed), household livestock parturition practices and household socio-economic data.
- https://cdn.elifesciences.org/articles/95296/elife-95296-supp3-v1.docx
-
Supplementary file 4
Instructions to provide farmers with advice as to locally appropriate preventive measures that could be taken to reduce transmission or contamination risks associated with abortion cases, which included safe removal of abortion tissues from livestock-occupied areas (e.g. burning, burying or covering the tissues in thorny branches).
- https://cdn.elifesciences.org/articles/95296/elife-95296-supp4-v1.docx
-
Supplementary file 5
The number of abortion cases per head of livestock reported over a 12 month period obtained through a previous randomized cross-sectional study (described in de Glanville et al., 2022).
- https://cdn.elifesciences.org/articles/95296/elife-95296-supp5-v1.xlsx
-
Supplementary file 6
The number of livestock in the ward reported by surveys conducted by Livestock Field Officers from the Tanzania Ministry of Livestock and Fisheries covering a period from 2011–2016 (E. Swai, unpublished data).
- https://cdn.elifesciences.org/articles/95296/elife-95296-supp6-v1.xlsx
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MDAR checklist
- https://cdn.elifesciences.org/articles/95296/elife-95296-mdarchecklist1-v1.pdf
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Livestock abortion surveillance in Tanzania reveals disease priorities and importance of timely collection of vaginal swab samples for attribution
eLife 13:RP95296.
https://doi.org/10.7554/eLife.95296.3
