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Review

Review of the Current Status on Ruminant Abortigenic Pathogen Surveillance in Africa and Asia

by
George Peter Semango
* and
Joram Buza
School of Life Sciences and Bioengineering, Nelson Mandela African Institution of Science and Technology, Arusha P.O. Box 447, Tanzania
*
Author to whom correspondence should be addressed.
Vet. Sci. 2024, 11(9), 425; https://doi.org/10.3390/vetsci11090425
Submission received: 4 March 2024 / Revised: 14 May 2024 / Accepted: 17 May 2024 / Published: 12 September 2024
(This article belongs to the Topic Animal Diseases in Agricultural Production Systems, 2nd Edition)
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Abstract

:

Simple Summary

Abortions in ruminants lead to economic losses to livestock-owning communities. The major causes of these abortions are infectious agents. Surveillance of the infectious agents that cause abortions is important to the overall improvement of livestock productivity. Most LMICs have scarce or inadequate surveillance platforms for these pathogens. In this review article, we have summarized the current status of the available surveillance platforms in place for the infectious agents that lead to abortions in ruminants, as well as the sero-epidemiology of these pathogens.

Abstract

Ruminant abortion events cause economic losses. Despite the importance of livestock production for food security and the livelihoods of millions of people in the world’s poorest communities, very little is known about the scale, magnitude, or causes of these abortions in Africa and Asia. The aim of this review was to determine the current status of surveillance measures adopted for ruminant abortigenic pathogens in Africa and Asia and to explore feasible surveillance technologies. A systematic literature search was conducted using PRISMA guidelines for studies published between 1 January 1990 and 1 May 2024 that reported epidemiological surveys of abortigenic pathogens Africa and Asia. A meta-analysis was used to estimate the species-specific sero-prevalence of the abortigenic agents and the regions where they were detected. In the systematic literature search, 39 full-text manuscripts were included. The most prevalent abortigenic pathogens with sero-prevalence greater than 10% were BHV-1, Brucella, Chlamydia abortus, Neospora caninum, RVFV, and Waddlia chondrophila in cattle, BVDV in sheep, and RVFV and Toxoplasma gondii in goats in Africa. In Asia, Anaplasma, BHV-1, Bluetongue virus, Brucella, and BVDV were prevalent in cattle, whereas Mycoplasma was important in goats and sheep.

1. Introduction

Abortion is defined as fetal death and expulsion before completion of the pregnancy period in livestock, and can be caused by microorganic abortigenic agents. These disease agents infect the reproductive organs of the animal, resulting in the defective attachment of the fetus and thus its premature expulsion. Abortigenic agents in livestock include bacterial, protozoan, and viral agents [1]. Abortions may also be caused by other factors, such as genetic disorders, trauma, environmental factors such as temperature, nutritional factors such as phytotoxins, including mycotoxins, as well as iatrogenic factors such as the administration of abortigenic drugs [1]. However, infectious agents are the leading cause of abortion in livestock [2]. Common infectious agents that lead to abortion include Neospora caninum, Brucella spp., and Rift Valley Fever Virus in cattle, Coxiella burnetii in goats and sheep, and pestiviruses in sheep [3,4,5,6,7,8]. In South Africa, abortigenic agents reported in resource-poor farmers’ cattle included Brucella abortus, Neospora caninum, BVD/MD virus, IBR/IPV, Trichomonas fetus, and Campylobacter fetus [9].
Abortions in livestock are a major cause of economic losses to farmers worldwide, making it an important phenomenon to monitor and control. The magnitude of the economic losses has been quantified in some parts of the world for specific pathogens. For example, in South America, the annual losses due to Neosporosis for the dairy industry were estimated to be USD 43.6 million (range, USD 15.62–194.41 million) in Argentina and USD 51.3 million (range, USD 35.8–111.3 million) in Brazil [10,11]. In Tanzania, gross direct economic losses were recently estimated to be USD 263 million [12].
In addition to economic losses, some livestock abortigenic agents are zoonotic making them relevant to human health as well. Some of those infectious agents, including Brucella abortus, Rift valley fever, Toxoplasma gondii, and Campylobacter, among others, can cause fever and abortion in humans.
Developed countries have been successful in the control of some abortigenic agents by devising and implementing surveillance systems. These surveillance systems capture abortion events as quickly and accurately as possible [13]. The implemented surveillance systems include the use of statutory testing, as well as mandatory reporting by farmers of any abortion event to a veterinary inspector by phone, who would then respond and act accordingly by testing and implementing appropriate interventions [13]. (http://www.gov.scot/Topics/farmingrural/Agriculture/animal-welfare/Diseases/disease/Brucellosis/Surveillance, accessed on 22 May 2022). The surveillance platforms that have been successfully implemented in developed countries include passive, active, targeted, sentinel, syndromic, reportable disease, abattoirs and slaughter slab, and emerging disease surveillance platforms [13]. These surveillance systems are implemented on a regular basis and, for their successful implementation, are coupled with well-trained and equipped response personnel on the ground and state-of-the-art testing facilities [14].
However, it has been noted that one of the major constraints for the control of abortigenic agents in low- and middle-income countries (LMICs) is the absence of qualitative and quantitative information. This is mainly due to the lack of adequate implementation of surveillance systems for livestock diseases in most African and Asian countries. Currently available disease information is dependent on active disease searching by researchers and includes limited or passive participation by the community. This has led to poor control of disease pathogens, including abortigenic agents, in LMICs, leading to unknown economic losses, as well as a lack of guidance for appropriate interventions. In East Africa as a region, there are ongoing research efforts to unravel the epidemiology of disease pathogens, including abortigenic pathogens. As in other LMICs, East African countries have a high burden of abortigenic agents [3,15,16,17,18], but few studies have attempted to estimate the economic losses due to abortions. Currently, the surveillance data collected are not being sufficiently used in rapid response and priority setting in Tanzania [19]. This is mainly because the national surveillance system is not functioning optimally, as in many other LMICs [19,20,21]. This has thus led to massive underreporting of abortion events in Tanzania, whereby approximately less than 10% of all cases are reported (personal communication). The actual causes of the surveillance system not functioning optimally are also undocumented. Typically, the abortion surveillance system requires the abortion events to be reported to the government by the livestock keepers to the Livestock Field Officers (LFOs), stationed at the village level. From there, it is then reported to the District Veterinary Officer (DVO), who reports to the Zonal Veterinary Centre Director (ZVC). The ZVC then informs the Director of Veterinary Services (DVS) at the Ministry Level. Regular reports of the number of abortion events are then provided to the global platforms at the World Organization for Animal Health (OIE). The system is paper-based from the LFO up to the ZVCs.
Despite the availability of established and successfully implemented surveillance systems in place in certain Northern countries, these may not be directly replicable in many African and Asian countries. Indeed, these systems may not be practical due to their financial, infrastructural, and expert requirements. In India, there is an animal disease surveillance program that is limited to a few diseases, such as Brucella and Leptospira.
Using a systematic literature review process, we assessed the available literature on studies that reported livestock abortigenic organisms in Africa and Asia. We appreciate the large heterogeneity between the regions within and between Africa and Asia, but would like to document the distribution of abortigenic pathogens, especially in the wake of the ongoing climate change and its impact on pathogen distribution. Additionally, we determined the surveillance systems that are being used in Africa and Asia in the reporting of livestock abortion events. There is also a wide disparity between the countries within and between Africa and Asia, especially in terms of socio-economic status, but this also shows the importance of the pathogens in these regions. The main objective of this study was to identify the circulating abortigenic pathogens in Africa and Asia through the sero-prevalence surveys conducted in these respective countries and also document on the surveillance platforms in place for their monitoring.

2. Methods

2.1. Study Design and Systematic Review Protocol

References were sought and identified following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [22] (Supplementary Materials, Table S1). Studies were searched in PubMed, Scopus, Embase, and Google Scholar published between 1 January 1990 and 1 May 2024. The search terms are listed in Table 1.

2.2. Search Strategy

Article titles and abstracts were screened for suitability for inclusion by GS. Full-text articles were included once the abstracts passed the initial screening. They were selected for full-text review if the studies investigated any of the abortigenic pathogens of interest, reported on samples collected from cattle, goats, or sheep, involved surveillance of the abortigenic pathogens, and data collection took place in African or Asian regions or countries as defined by the United Nations (UN) statistics division [23]. Full-text articles were reviewed independently by two authors (GS and JB) to determine if each article met the pre-determined inclusion and exclusion criteria (Supplementary Materials, Table S2). Articles were included for full-text review if the full-text article could be retrieved, if it reported primary data, if the article reported surveillance data in sheep, goats, and sheep, regardless of the laboratory methods used, and if the prevalence of abortigenic pathogens could be calculated from the information available in the paper using any sample type.

2.3. Exclusion Criteria

(i)
If the numerator (i.e., number positive) and denominator (i.e., number tested) information were not reported at the species and sample type levels;
(ii)
If they were in a language other than English. When required, a third reviewer (TK) served as a tiebreaker, independently reviewing articles to resolve disagreements between the two primary reviewers.

2.4. Article Selection and Data Extraction

From each included article, we extracted information on the species of the affected animal, sample type, the total number of samples tested, and total positive samples. The number of pathogens detected was extracted to determine pathogen prevalence. Sample location data included UN statistics division African and Asian geographic region countries [23]. A formal bias assessment was performed (Supplementary Materials, Table S1), assigning low (L), moderate (M), and high (H) to each potential introduction of bias. The bias elements considered in the formal assessment were related to abortigenic pathogens of interest, studies conducted out of Africa and Asia, and technologies used. An overall assessment of low, moderate, or high risk of bias was assigned to each included article.

2.5. Analysis

Prevalence estimates were calculated from pooled data for each pathogen by livestock species and geographic region. Briefly, all the positive cases were summed up as the numerator and all the tested animals were summed up as the denominator, and a pooled sero-prevalence was calculated as a percentage. Summary statistics were calculated in the R program.

3. Results

The literature search from the two scientific databases resulted in 297 studies, which included abstracts, free full text, full text, books and documents, clinical trials, and randomized controlled clinical trials including citations. After removing duplicate articles from the searches, 277 articles were available for title and abstract screening. Of these, 57 (20.6%) were identified as potentially relevant and 39 (14.1%) were eligible for inclusion after full-text review (Figure 1). The majority of the studies (18 (46.2%)) were on Brucella spp., whereas 9 were on Rift Valley Fever Virus (23.1%), 7 were on Coxiella burnetii (17.9%), and 6 each were on Neospora caninum and BVDV (15.4%), as summarized in Table 2. The number of studies from each country and the animal species investigated are listed in Table 3.
Two studies (5.1%) of the thirty-nine included were embedded in the national surveillance programs of the respective countries in which they were conducted, South Korea and South Africa, whereas the majority (94.9%) were stand-alone cross-sectional studies. Most studies (30 (76.9%)) were reported from Africa and 9 (23.1%) were conducted in Asia.
Table 2 shows a summary of the information extracted from the 39 full-text articles included from the literature search in the two databases. We extracted information on the country where the study was conducted, year of publication, species from which samples were collected, the number of positive samples among the total number of samples tested, the pathogen detected, the type of animal husbandry method of the species tested, the type of study, as well as the diagnostic method used.

Median Sero-Prevalence of Abortigenic Pathogens

The adjusted median prevalence calculations estimated Brucella in Africa at 21.5% in 372,127 cattle, and 0.27% and 0.87% in sheep and goats, respectively. Coxiella was estimated at 13.0%% in cattle, and 2.3% and 4.5% in sheep and goats, respectively. The most prevalent abortigenic pathogens with sero-prevalence greater than 10% were BHV-1, Brucella, Chlamydia abortus, Neospora caninum, RVFV, and Waddlia chondrophila in cattle, BVDV in sheep, and RVFV and Toxoplasma gondii in goats in Africa. In Asia, Anaplasma, BHV-1, Bluetongue virus, Brucella, and BVDV were prevalent in cattle, whereas Mycoplasma was important in goats and sheep. Other pathogens detected with low sero-prevalence were Anaplasma, BVDV, Campylobacter, Listeria, and Salmonella in cattle, Brucella and Coxiella burnetii in goats and sheep, BVDV and Neospora caninum in goats, and Chlamydia pecorum, RVFV, and Toxoplasma gondii in sheep in Africa. In Asia, pestiviruses (BVDV) were prevalent in goats, and Coxiella burnetii and Neospora caninum were prevalent in cattle. These data are summarized in Table 3.

4. Discussion

In this systematic literature search, we found that livestock abortigenic pathogens are still are burden in the livestock sector in African and Asian countries. The most important abortigenic pathogens identified included Brucella spp., BHV-1, Chlamydia spp., Neospora caninum, and Waddlia chondrophila in African cattle. RVFV was found to be important in both African cattle and goats. Toxoplasma gondii and pestiviruses (BVDV) were important in African goats and sheep, respectively. As for Asia, Anaplasma, BHV-1, Bluetongue virus, Brucella spp., and BVDV were important in cattle, and Mycoplasma was important in sheep. Brucella, BHV-1, and pestiviruses were important in both Asia and Africa, while Anaplasma, Bluetongue, and Mycoplasma were important in Asia only. Brucella research in goats and sheep in Asia seems to be minimally conducted, probably because of the ongoing surveillance activities aimed at the pathogen, for instance, in India [20]. Similarly, for Leptospira, we could not find a study that detected the pathogen in both Africa and Asia, but it is also under constant surveillance in India [20]. The presence of this surveillance program in India and other parts of Asia may also explain the lack of studies on pathogens such as Brucella spp. in goats and sheep. Brucella spp. have been reported to be prevalent in India, and our finding of 14.4% sero-prevalence is similar to a recent meta-analysis that reported a pooled sero-prevalence of 16.6% in cattle (O’Donovan & Bersin, 2015) [60]. Anaplasmosis is prevalent in Asia, with different countries reporting different rates of occurrence, such as Iran (37.3%) [61], which is similar to our pooled sero-prevalence. As for Bluetongue virus, which is endemic to Asia and Africa, there is a lack of published data on it in Africa, as also stated elsewhere [62], with very few African countries reporting its occurrence. However, in Asia, BTV has been documented to occur as it is endemic to the region. There are also consortia conducting research on the pathogen, such as the research efforts in Indonesia and Malaysia in collaboration with Australia [63].
It is worth noting that certain pathogens have not been reported at all in Asia in sheep and goats while being present in Africa, such as Brucella spp., BVDV, Chlamydia, Coxiella, Neospora, and RVFV. This is unexpected, as the Asia Pacific region hosts over 49% of goats and 22% of sheep in the world [64]. For RVFV, this virus has not yet been spread to most parts of Asia, which explains the lack of published data from Asia [65]. On the other hand, Mycoplasma, Trypanosoma, and Trichomonas are not as well documented as other pathogens. This may be due to their low sero-prevalence or due to them being neglected as there are other more prevalent pathogens.
Furthermore, surveillance systems for livestock abortigenic pathogens in many African and Asian are so far not optimal, with the exception of a few countries, such as South Africa, India, South Korea, India, and Saudi Arabia which have been reported to have National surveillance programs. The African and Asian regions have the highest rate of growth in surveillance systems using mHealth technology in human medicine. Additionally, most studies employed the serological surveillance approach at single timepoints using a cross-sectional study design. These studies demonstrated the burden of abortigenic pathogens, but were not embedded in the national surveillance systems which would provide continuous real-time information, except for a few Asian countries; namely India, South Korea, Saudi Arabia, and South Africa, which have national Brucella surveillance programs.
In the included articles, most studies used serological tests for pathogen detection. These are cheaper and form a good basis for pathogen monitoring programs compared with molecular diagnostic methods and pathogen culture and isolation. For near-real-time surveillance, serological methods are very useful tools [66].
The establishment of effective surveillance systems for zoonotic diseases has been on the research agenda for some time. This is because it is estimated that 75% of human epidemics and 60% of human pathogens are of animal origin. These facts demonstrate the importance of the surveillance of zoonotic pathogens, among which abortigenic agents belong. These abortigenic agents also cause economic losses in instances where they may not have caused disease to a human.
Several different modes of surveillance have been proposed for zoonotic pathogens in different settings of the world, with varying successes. For instance, in France, it is mandatory for livestock keepers to report abortion events to the veterinary department by calling, and failure incurs a fine of EUR 1500 [67]. However, even with advanced response systems in place in France, there are still many keepers who do not report abortions [67].
Participatory systems using mobile phones have been implemented for veterinary surveillance systems in several countries and across a range of diseases. For example, in Cambodia and Madagascar, participatory surveillance systems using mobile phone technologies have been successfully implemented for the surveillance of animal diseases in remote environments [68].
In Tanzania, as in most other African countries, mobile-based technologies have been trialed in both human and veterinary medicine. Mobile phone technology has been applied successfully in zoonotic diseases, like rabies, in some parts of Tanzania [69]. Other veterinary programs whereby mhealth has been used include the innovative Smartphone App (AfyaData) for Innovative One Health Disease Surveillance from Community to National Levels in Africa [70]. This program has highlighted that rural areas have the potential to utilize mobile phones to link livestock keepers with veterinary professionals and provide timely access to information to assist in the diagnosis and treatment of livestock diseases. Furthermore, the availability of mobile phones in rural areas, in combination with supporting infrastructure and facilities in urban areas, has the potential to stimulate local development and improve the delivery of animal health and extension services [71].
In human medicine, mhealth has been applied more extensively and has been more acceptable among health workers than in veterinary disease surveillance [72]. A number of programs are currently ongoing at the national level. These mhealth programs include maternal health and nutrition programs [73] for HIV/ AIDS [72], Malaria [74], and other diseases. Tanzania is reportedly setting the stage at the global level in integrating eHealth as a component of the national health system. Tanzania has established a community of practice working group since 2009 and in 2011 also developed a National mhealth strategy.
The documented major drawbacks of mobile-based technologies include unclear benefits, uncertain long-term results [73,75,76,77,78,79], and unknown cost-effectiveness [73,80]. Furthermore, there are still issues of under-reporting [77,78]. However, even with the drawbacks, mhealth is by far the most promising surveillance method, especially for zoonotic diseases, and especially in Tanzania with the increasing mobile network coverage and mobile phone ownership in both rural and urban areas. Most developing countries where feasibility studies for the application of mhealth and ehealth have been conducted have reported that most mhealth programs are implemented in silos without the involvement of key stakeholders and hence unsustainability of the mhealth programs [81,82]
We believe that our review has some major strengths in terms of outlining the abortigenic pathogens in ruminants that are found in Africa and Asia; however, our manuscript has limitations in that we were limited to a few databases and also may have not explored all factors and variables that may influence pathogen distribution. However, these were not the immediate objectives of this review.

5. Conclusions

In conclusion, livestock abortigenic pathogens are prevalent in many African and Asian countries. Adequate near-real-time surveillance systems for livestock abortigenic pathogens in many African and Asian countries are not present, except for a few countries, such as India, South Africa, South Korea, and Saudi Arabia, which have surveillance programs.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/vetsci11090425/s1, Table S1: Criteria list fulltext; Table S2: Criteria list title/abstract.

Author Contributions

Conception: G.P.S. and J.B.; Design of the work: G.P.S. and J.B.; Data acquisition: G.P.S. and J.B. Data interpretation: G.P.S. and J.B.; Manuscript draft: G.P.S.; Manuscript review: J.B.; Final approval: G.P.S. and J.B. All authors have read and agreed to the published version of the manuscript.

Funding

This study was funded in whole by Science for Africa Foundation to the Developing Excellence in Leadership, Training and Science in Africa (DELTAS Africa) programme [Afrique One-ASPIRE, Del-15-008 and Afrique One-REACH, Del-22-011] with support from Wellcome Trust and the UK Foreign, Commonwealth & Development Office and is part of the EDCPT2 programme supported by the European Union. For purposes of open access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Dataset available on request from the authors.

Acknowledgments

We would like to acknowledge Tito Kibona (TK) for serving as a tiebreaker, independently reviewing articles to resolve disagreement between the two primary reviewers.

Conflicts of Interest

The authors declare no conflicts of interest.

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Vetsci 11 00425 g001
Figure 1. PRISMA flow diagram showing identification, screening, and selection of eligible articles for inclusion in the systematic review, 1990–2002.
Figure 1. PRISMA flow diagram showing identification, screening, and selection of eligible articles for inclusion in the systematic review, 1990–2002.
Vetsci 11 00425 g001
Table 1. Literature search strategies.
Table 1. Literature search strategies.
Search StringDatabase or Further SourcesResultsDateComments
((((ASIA[Text Word]) OR (AFRICA[Text Word]) AND (1990/1/1:2024/5/1[pdat])) AND (((GOATS[Title/Abstract]) OR (SHEEP[Title/Abstract])) OR (CATTLE[Title/Abstract]) AND (1990/1/1:2024/5/1[pdat]))) AND (ABORT*[Title/Abstract] AND (1990/1/1:2024/5/1[pdat]))) AND (surve*[Title/Abstract])PubMed371 May 2024PubMed search
abortion surveillance cattle OR sheep OR goats * * * * “Asia OR Africa” -human -people -persons -man -woman -Europe -americas -australia -pacific -“south america”1990–2024Google Scholar2401 May 2024Google Scholar search through NM-AIST
Table 2. Summary of the information extracted from the full-text articles that were included in the meta-analysis.
Table 2. Summary of the information extracted from the full-text articles that were included in the meta-analysis.
s/noCountryRegionYearSpeciesNumber of Species (Positive)Pathogen(s) DetectedStudy TypeHusbandry Method (Climatic Zone)Detection MethodRef
1TanzaniaEast Africa1996Cross-bred bulls; Taurine breeds [24] (Friesian, Ayrshire, and Simmental crossed with Tanzanian short-horn zebu, boran, and Sahiwal)Campylobacter fetus 3/58, Trichomonas foetus 0/58Campylobacter fetus subsp. Venerealis, Trichomonas foetusSero-surveySmallholder dairy farms (zero-grazing)
Tropical climate		Culture and biochemical tests[24]
2UgandaEast Africa2000Cattle (Ankole, crosses—Fresian and Boran)Brucella—41/143
Anaplasma 3/454		Brucella, AnaplasmaCross-sectionalPastoral communities Tropical climateRBPT, ELISA[25]
3IndiaAsia2002–2004Cattle35/427 (9.6%)Neospora caninumCross-sectional surveyDairy farms Tropical climateELISA, IFAT[26]
4SenegalWest Africa2003Sheep7/260 (2.7%)RVFVSerological surveyNomadic Tropical climateSero neutralization test[27]
5ZimbabweSouthern Africa2004–2005Cattle71/1291 (5.5%)BrucellaCross-sectionalSmallholder Subtropical climateRBT, ELISA[28]
6Sudan Central Africa2005Sheep and goatsSheep 3/270 (1.1%)RVFVSero-surveillanceNomadic pastoralist Tropical savannahELISA, Hemagglutination[29]
7South AfricaSouthern Africa2006–2016193 cattle, 39 goats, and 57 sheep63/288; Brucella 21/288 (7.3%) Cattle, Trueperella pyogenes 5/288 Cattle, 1/288 sheep Brucella, Trueperella pyogenes, E. coli, Salmonella, L. monocytogenes, C. burnetii, B. licheniformus, Rhizopus, B. abortus, Leptospira, C. pecorum, CampylobacterObservational retrospective studyArchived samples Subtropical and temperateMicrobiology, necropsy, histopathology, PCR[30]
8EthiopiaEast Africa2008–2009Sheep and goats0/270 sheep, 2/230 goatsBrucellaCross-sectionalMixed farming TropicalRose Bengal Plate Test, Complement Fixation Test[31]
9EthiopiaEast Africa2009–2010Cattle2/370 (0.05%)BrucellaCross-sectional surveyMixed farming Equatorial rainforest, Afro-alpineRose Bengal, Complement Fixation Test[32]
10TunisiaNorth Africa2010–2012Cattle214 blood, vaginal swabs, milk. Brucella 47/150 (31.3%) RBPT, DANA PCR 46/150 (30.6%). Chlamydia 27/150 (18%), L. monocytogenes 7/150 (4.6%), Salmonella 5/150 (3.3%). Vaginal swabs; Brucella 46/150 (30.6%), Chlamydiales 27/150 (2.65%), L. monocytogenes 4/150 (2.6%)Brucella, Chamydiales (C. abortus, C. pecorum), Listeria, Salmonella, Coxiella burnetii, CampylobacterCross-sectional surveyLimited pasture or tethered Mediterranean climatePCR, Rose Bengal[33]
11MozambiqueSouthern Africa2010–2016Cattle, goats, and sheepCattle 149/404
Goats 45/223
Sheep		RVFVSero-surveyMixed farming Tropical to sub-tropicalELISA, PRNT[34]
12ZimbabweSouthern Africa2011Cattle (mixed breeds)81/1440 (5.6%)BrucellaCross-sectional surveySmallholder, mixed farming (strictly separate pastures) SubtropicalELISA[35]
13IranAsia2011–2012Sheep and goatsPCR: Sheep 101/274. Goats 10/25, Culture Sheep 76/274. Goats’ 9/25Mycoplasma spp.Cross-sectionalMixed farming Arid and semi-arid climatePCR, bacterial culture[36]
14IndiaAsia2012–2014Cattle11/61 (18.03%)Trypanosoma evansiSero-surveyMixed farming. Tropical climateELISA[37]
15South KoreaAsia2012–2013Cattle (Holstein breed)37/171 and 85/466Blue Tongue VirusSerological survey from National Surveillance ProgramMixed farming Temperate climateELISA, BTV neutralization test, RT-PCR[38]
16CameroonWest Africa2013Cattle117/1498RVFVCross-sectional surveyPastoralists
Humid and Equatorial climate		ELISA[39]
17TanzaniaEast Africa2013–2016Cattle, goats, and sheepBrucella Cattle 1/71, Coxiella Goats 5/100, Sheep 1/44, Neospora Cattle 9/71, Goats 1/100, Toxoplasma Sheep 1/44, BHV-1 Cattle 2/49, BVDV Cattle 2/71, Goats 1/100, Sheep 6/44, RVFV Cattle 14/71Brucella, Chlamydia abortus, Coxiella burnetii, Leptospira hardjo, Neospora caninum, Toxoplasma gondii, Bluetongue Virus, Bovine Herpes Virus 1, Pestiviruses (BVDV/BDV), RVFVCross-sectional surveyPastoral, agro-pastoral, and smallholder Tropical climateELISA, PCR[40]
18South AfricaSouthern Africa2013–2018Cattle359,026 (22.1%)BrucellaCross-sectional survey, Provincial surveillance programMixed farming Subtropical and temperateCFT, Rose Bengal Plate Test[41]
19MozambiqueSouthern Africa2014GoatsSerology: 31/127 (24.4%)RVFVOutbreak investigationMixed farming Tropical to sub-tropicalELISA, PCR[42]
20IndiaAsia2014Cattle160 RBPT 3/160 (1.8%), Standard Tube Agglutination Test (STAT) 5/160 (3.13%)BrucellaSero-epidemiological surveyMixed farming Tropical climateRBPT, STAT, Bacterial culture, Milk Ring Test[43]
21NigeriaWest Africa2015Cattle11/97 (11.3%)RVFVCross-sectional surveyNomadic pastoral
Tropical monsoon climate, tropical savannah, and Sahelian hot and semi-arid		ELISA[18]
22KenyaEast Africa2016Cattle100/955, 10.5%Coxiella burnetiiCross-sectional surveyMixed crop-livestock Tropical climateELISA[4]
23EgyptNorth Africa2016–2018Cattle165/176 (93.86%)BHV-1Transboundary, Import from SudanNomadic Subtropical desert climateELISA[44]
24TajikistanCentral Asia2016Cattle570 (58 PCR, 12 ELISA)BrucellaSero-prevalenceSmallholder Continental, subtropical, desertELISA, qPCR, DNA sequencing[45]
25TunisiaNorth Africa2017Cattle and sheepCattle Waddlia 12/27, Parachlamydiaceae 8/27, Chlamydiaceae 7/27, Sheep P. acanthamoebae 9/164, C. pecorum 6/164 Waddlia chondrophila, C. abortus, C. pecorumCross-sectional surveySmallholder MediterraneanPCR[46]
26AlgeriaNorth Africa2017–2019Atlas brown cows650 pregnant (235(36.2%))Neospora caninumSero-prevalenceSmallholder MediterraneanELISA[47]
27TanzaniaEast Africa2017–2019Cattle14/63 (23%)RVFVProspective cohortPastoral, agropastoral, and smallholder Tropical climateELISA, RT-qPCR[48]
28Benin West Africa2017Sheep and goatsGoats 83/153, Sheep 3/215Toxoplasma gondiiSero-epidemiological surveyPastoral.
Steppe climate and topical humid climate		ELISA[15]
29GuineaWest Africa2017–2019Cattle, goats, and sheepBrucella; Cattle 52/463, Sheep 2/486. Coxiella; Cattle 95/463, Goats 18/408, Sheep 11/486. RVF; Cattle 76/463, Goats 4/408, Sheep 5/486Brucella, Coxiella burnetii, RVFVSero-survey from archived samplesIntensive farms Samples from different prefectures
Hot and humid 		ELISA, Virus Neutralizing Ab[49]
30AlgeriaNorth Africa2018–2019Cattle201/460 (43.7%)Bovine Herpes Virus 1Abortion investigationMixed farming Mediterranean climateELISA[50]
31Saudi ArabiaAsia2018–2020Sheep and goatsGoat 3/84 (3.5%) SerumBVDVSero-prevalence-Abattoir surveillanceAbattoir, semi-closed management Desert climateELISA[51]
32EthiopiaEast Africa2018–2019Cattle cross and pure breeds; Boran–Fresian cross, Boran–Jersey, Pure Jersey, and BoranBHV-1 68/86(79.1%), BVD 33/86 (38.4%), Neospora 3/86 (3.5%), Coxiella 1/86 (1.2%)Brucella spp., Neospora caninum, BVD, BHV-1, Coxiella burnetiiReproductive problem investigationSemi-intensive farming system (grazing and indoor feeding) Equatorial rainforest, Afro-alpineELISA[52]
33Ethiopia East Africa2018–2019Cattle (Zebu, Holstein, Fresian, and crossbreed)0/882 (ear notch samplesBVDVCross-sectional surveyPeri-urban dairy farms, mixed crop–livestock farms (small holder extensive management system), pastoral herds (seasonal mobility)
Equatorial rainforest, Afro-alpine		ELISA[53]
34IndiaAsia2019Cattle crossbreeds, exotic, and indigenousBHV-1 425/1004, BVDV 604/1004, Brucella 176/1004, Coxiella 57/1004, Anaplasma 363/1004, Neospora 9/1004BHV-1, BVDV, Brucella, Coxiella burnetii, Neospora caninum, Anaplasma marginaleCros-sectionalIntensive dairy farms
Tropical		ELISA[54]
35NigeriaWest Africa2020Cattle61/1810 (3.37%)BrucellaCross-sectionalMixed farming Tropical monsoon climate, tropical savannah, and Sahelian hot and semi-aridSAT[55]
36EgyptNorth Africa2020CattleNeospora 35/116 (30.17%), BVDV 31/116(26.72%)Neospora caninum, BVDVCross-sectionalMedium-sized farms
Subtropical desert climate		ELISA[56]
37KenyaEast Africa2020–2021Cattle6593(449)BrucellaSero-prevalenceAgro-alpine, high and medium potential, semi-arid, arid, and very arid Tropical climateELISA[57]
38BangladeshAsia2023Cattle (local, cross)66/386 (17.09%)BrucellaCross-sectionalTransboundary area, mixed farming
Humid, warm climate		RBPT, Plate agglutination test, serum agglutination[58]
39South Africa Southern Africa2023Cattle2% 770BrucellaCross-sectional survey, abattoir surveyCommunal, commercial, and non-commercial farms Subtropical and temperateRNT, CFT, Milk Ring Test[59]
Table 3. Seroprevalence of abortigenic pathogens by species.
Table 3. Seroprevalence of abortigenic pathogens by species.
Abortigenic PathogenSpeciesCases (n)Total Tested (N)Median Sero-Prevalence
AfricaAsiaAfrica AsiaAfricaAsia
AnaplasmaCattle336345410040.736.2
BHV-1Cattle436245771100456.524.4
Bluetongue virusCattle01220637019.2
Brucella spp.Goats2023000.870
Sheep2075400.270
Cattle80,165305372,127212021.514.4
BVDVGoats131008413.6
Sheep6044013.60
Cattle66604115510045.760.2
CampylobacterCattle305805.20
Chlamydia abortusCattle340177019.20
Chlamydia pecorumSheep6016403.70
Coxiella burnetiiGoats23050804.50
Sheep12053002.30
Cattle1965415041004135.4
ListeriaCattle7015004.70
MycoplasmaGoats010025040
Sheep01010274036.9
Neospora caninumGoats10100010
Cattle28244923143130.63.1
RVFVGoats800758010.60
Sheep150101601.50
Cattle38102596014.70
SalmonellaCattle5015003.30
Toxoplasma gondiiGoats830153054.20
Sheep4025901.50
Trichomonas foetusCattle0058000
Trypanosoma evansiCattle011061018
Waddlia chondrophilaCattle12027044.40
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Semango, G.P.; Buza, J. Review of the Current Status on Ruminant Abortigenic Pathogen Surveillance in Africa and Asia. Vet. Sci. 2024, 11, 425. https://doi.org/10.3390/vetsci11090425

AMA Style

Semango GP, Buza J. Review of the Current Status on Ruminant Abortigenic Pathogen Surveillance in Africa and Asia. Veterinary Sciences. 2024; 11(9):425. https://doi.org/10.3390/vetsci11090425

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Semango, George Peter, and Joram Buza. 2024. "Review of the Current Status on Ruminant Abortigenic Pathogen Surveillance in Africa and Asia" Veterinary Sciences 11, no. 9: 425. https://doi.org/10.3390/vetsci11090425

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