{"paper_id":"0eab04ca-aa10-4e75-9ec3-a6097d32231d","body_text":"Seroepidemiology and Serotype Diversity of Foot-and-Mouth Disease Virus Among Domestic Ungulates Across Nigeria | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Seroepidemiology and Serotype Diversity of Foot-and-Mouth Disease Virus Among Domestic Ungulates Across Nigeria Adebayo Emmanuel SOPEJU, Adedayo FANEYE, Andrew Peters, Anyebe Bernard ONOJA This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7437182/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 06 Mar, 2026 Read the published version in BMC Microbiology → Version 1 posted 13 You are reading this latest preprint version Abstract Introduction: Foot-and-mouth disease (FMD) is a highly contagious viral infection of cloven-hoofed animals that causes substantial economic losses and severe disruptions to agricultural systems globally. It affects animal health and productivity in Nigeria but there is paucity of data across regions and among various animal species. This study determined the seroepidemiology and serotype diversity of the FMD virus (FMDV) among domestic ungulates including cattle, sheep, goats, and pigs, across all geopolitical zones in Nigeria. Materials and methods: 1002 sera were collected from domestic ungulate animals (cattle n=511, sheep n=182, goat n=218 and pigs n=91) and were analyzed using commercial ELISA kits (ID Vet®, France and IZLER®, Italy) to antibody and serotype-specific antibodies to FMD. Metadata on individual species were collected through questionnaire uploaded on Kobocollect containing sociodemographic data, and distribution of FMD in Nigeria. Results: The study revealed an overall rate of 45.7% for all the various species and regions in Nigeria with specific host prevalence of 69.7% for cattle, 26.9% for sheep, 20.6% for goats, and 8.8% for pigs. Serotype O was the most predominant (74.9%), followed by A (56.3%), SAT 2 (35.8%), Asia 1 (22.9%) and SAT 1 (16.8%). Kaduna had the highest prevalence (88.9%), while Cross River had the lowest (9.1%). Serotype co-infections were prevalent among cattle, with 32% exhibiting multi-serotype infections. Health status and body condition are major determinants of susceptibility, with unhealthy animals being five times more likely to test positive to FMD (OR = 5.479, p < 0.001). Conclusion: We have systematically determined FMDV seroprevalence and serotype distribution in various domestic ungulate species across all the geopolitical zones in Nigeria. Our findings highlight the importance of improved surveillance networks to address regional patterns and prevalent serotype clusters. It reinforces the need for developing generic multivalent vaccination plans and provides essential data for national policy to improve livestock healthcare strategies and minimize the burden of FMD in Nigeria. Figures Figure 1 Figure 2 Figure 3 Introduction Foot-and-mouth disease (FMD) is a highly contagious viral infection that affects cloven-hoofed livestock and wildlife, causing significant economic losses and severe socioeconomic problems. It is listed as a notifiable disease by the World Organization for Animal Health (WOAH) due to its wide distribution and potential to disrupt animal production systems. Globally, FMD circulate within 77% of the livestock population (OIE, 2021 ). FMD is caused by the Foot-and-Mouth Disease Virus (FMDV), a non-enveloped, single-stranded, positive-sense RNA virus of approximately 8.5kb in size. It belongs to the genus Aphthovirus in the family Picornaviridae and is surrounded by an icosahedral capsid composed of four structural proteins (Rueckert, 1990 ). There are seven immunologically distinct serotypes of FMDV (O, A, C, SAT 1, SAT 2, SAT 3, and Asia 1), with serotype O being the most prevalent globally (FAO, 2021 ). There is no cross-protection across these serotypes, and even among subtypes within a serotype, immune protection is insufficient (Naveed, 2018 ). The disease is endemic and occurs year-round in Nigeria with seasonal outbreaks. Historical records trace the first reported outbreak to 1924 (Libeau, 1960 ), underscoring the long-standing presence and persistent challenge to livestock health and productivity in the country. In Nigeria, serotypes O, A, SAT 1, and SAT 2 have been documented historically, with a study stating the detection of antibodies against SAT3 across multiple states (Ehizibolo et al., 2013 ). The principal domestic hosts of FMDV are cattle, pigs, goats, and sheep (Ferris and Donaldson, 1992 ; Jamal et al., 2013 ). Among these, FMD manifests mildly in sheep and goats, sometimes resembling other vesicular disease like vesicular stomatitis (Blanco et al., 2002 ; FAO, 2024). Pigs, although susceptible, exhibit relatively lower risk for airborne transmission compared to cattle and sheep (Alexandersen and Donaldson, 2002). Transmission of the virus occurs by direct contact via respiratory droplets from infected animals, and indirectly through contaminated fomites such as vehicles, equipment, or personnel (Alexandersen et al., 2003 ). Though FMD typically causes low mortality (except in young calves), it has high morbidity and severely affects productivity. Infected animals show clinical signs including fever, lameness, and vesicle formation in the mouth, on the feet, and on the teats of lactating cows and the snouts of pigs (Grubman and Baxt, 2004 ). These vesicles eventually rupture, leading to painful erosions, excessive salivation, difficulty in eating, and reluctance to move, all of which impair the animal’s performance. Economic losses are compounded by trade restrictions placed on meat and animal products originating from affected regions (FAO, 2025). Routine prophylactic vaccination using inactivated FMD vaccines is recommended in endemic countries, but in Nigeria, it is largely restricted to a few dairy farms where trivalent vaccines targeting serotypes O, A, and SAT 2 are used (Lazarus et al., 2012 ). Despite being endemic, Nigeria has yet to implement a comprehensive FMD vaccination program. Control measures are typically cattle-focused, even though FMD affects all cloven-hoofed species (OIE, 2021 ). The situation is exacerbated by unrestricted transboundary animal movement, particularly at poorly regulated border posts in Africa including Nigeria (Bouslikhane, 2015; Woldemariyam et al., 2022 ) and limited access to vaccines by smallholder farmers in rural areas due to several factors like lack of awareness, lack of access, cost of the vaccine affecting sales by agro-veterinary infrastructures (Sopeju et al., 2025). Oyewusi and Talabi ( 2015 ) stressed the need for broader vaccination programs that include all susceptible species, improved disease surveillance, and the establishment of effective control posts along major livestock entry routes. While numerous studies have been conducted on the epidemiology of FMD in Nigeria, Atuman et al. ( 2020 ) highlighted that seroepidemiological and serotyping investigations are inadequate despite the annual incidence. This gap in research underscores the need for updated and comprehensive surveillance activity. Therefore, we investigated the seroepidemiology FMD and determined the circulating serotypes of FMDV across various domestic ungulate species in all geopolitical zones in the country. Methodology Study Area Border States of Niger Republic (Jigawa, Sokoto and Yobe State), Benin Republic (Niger, Ogun and Oyo States) and Cameroon (Adamawa and Taraba State). Other selected states (Plateau, Kaduna, Lagos, Ebonyi and Cross-River State). Ethical approval was obtained from Ethical Review Board of the National Veterinary Research Institute (NVRI), Vom with reference number AEC/02/148/24. Study Population Domestic ungulate animals (cattle, sheep, goat and pigs) from consenting farmers in our study areas were selected for the study. Samples were collected from 511 cattle, 182 sheep, 218 goats and 91 pigs located in our study areas. Blood samples were collected from individual animals using sterile needle and syringe, with the 5 ml of blood collected from jugular veins of cattle, sheep and goats and from the cranial vena cava in pigs. Study design This is a cross-sectional study, and we aseptically collected 5ml of blood from each of the jugular veins of cattle, sheep and goat and vena cava of pigs in our study. Inclusion and Exclusion Criteria Inclusion Criteria include weaned domestic ungulate animals from markets, farms or communities where there is an on-going or previous history of FMD outbreak. The exclusion Criteria include all domestic ungulate animals that are yet to be weaned and those found on farms or communities where there has not been history of FMD outbreaks were excluded. Border States are states that share boundary with neighbouring countries and with known international livestock trade. Non-border States are states without international cattle trade (with or without boundary with other countries). The sample size was calculated using the following formula with prevalence rate of 50% (Dohoo et al., 2003 ; Thrusfield, 2018 ). 1002 sera were obtained from cattle, sheep, goat and pigs in our study areas. Serological Assay Commercial ELISA kits (NSP and Serotype-specific for serotype A, O, SAT 1, SAT 2 and Asia 1) were used to detect the animals that were seropositive for FMD and the above-mentioned FMD serotypes. The kits were purchased from ID Vet (for NSP, Serotype O and A) and IZLER from Italy for Serotypes SAT 1, SAT 2 and Asia 1. Sera from the samples collected were first tested for positivity using NSP ELISA kits. The positive samples were then anlyzed further for serotyping using serotype-specific ELISA kits for serotype O, A, SAT 1, SAT 2 and Asia 1. Each of the assays were carried out according to each of the manufacturers’ instructions. The results of optical density (O.D.) values were validated, percentage inhibition was calculated, and positivity was determined according to the standard provided by the manufacturer standard provided in the ELISA manuals. Data Analysis Questionnaires uploaded on Kobocollect were used to get information on the animal sampled and other information relevant to this study. Metadata generated from the sampled animals were transferred in an excel sheet with ascribed sample ID for each animal. Descriptive and inferential analysis of data was carried out using EXCEL and IBM SPSS to generate relevant figures. Clinical Trial Number Not applicable Result Seroprevalence of Foot and Mouth Disease (FMD) across Animal Species The overall seroprevalence of Foot and Mouth Disease (FMD) is 45.7% (458/1002), with significant variation across species, Cattle had the highest seropositivity (69.7%), followed by sheep (26.9%), goats (20.6%), and pigs (8.8%) (Table 1 ). Logistic regression analysis further confirmed that cattle had the highest odds of seropositivity compared to pigs (reference category), (Table 2 ). Among cattle, females had a significantly higher seroprevalence (74%) than males (65.5%) (χ² = 4.35, p = 0.037), but age was not a significant determinant. In sheep and goats, sex and age did not significantly influence seropositivity (Table 4). A similar trend was observed in pigs, where seropositivity did not differ significantly by gender or age (Table 2 ). Geographical and Border Proximity Influence on Seroprevalence Seroprevalence varied significantly across states, regions and geopolitical zones, with Kaduna states having the highest prevalence (88.9%),) (Table 1 ). At the geopolitical zonal level, the North-Central (73.8%) and South-East (71.2%) had the highest seropositivity, as shown by the Logistic regression analysis. (Table 2 ). Among cattle, seropositivity was significantly higher in the South-East (95%) and North-Central (87.7%), with the lowest rates in the South-South (12.7%) (χ² = 121.63, p < 0.001) (Table 1 ). For sheep, Ebonyi (100%) showed the highest rates, while Jigawa (9.1%) had the lowest seropositivity (χ² = 72.23, p < 0.001). For goats, the highest prevalence was recorded in Plateau (60%) followed by Niger (50%), while Lagos (3.3%) had the lowest rates (χ² = 41.8, p < 0.001). In pigs, Adamawa had the highest seroprevalence (100%) while Cross River (4.2%) had the lowest (χ² = 38.37, p < 0.001) (Fig. 3 ). Proximity to international borders did not significantly influence seroprevalence, as border states (48.9% for Niger, 49.4% for Benin, and 45.7% for Cameroon) had similar rates to non-border states (43%) (p = 0.403) (Fig. 1 ). Influence of Health Status and Body Condition on Seroprevalence Health status and body condition significantly influenced FMD seroprevalence. Animals in poor body condition exhibited the highest seroprevalence (66.2%), while those in fair (49.2%) and good condition (39.5%) had lower infection rates (p < 0.001). Logistic regression analysis indicated that animals in poor condition were three times more likely to be seropositive than those in good condition (OR = 3.008, p < 0.001). Animals in fair condition had moderately increased odds of seropositivity (OR = 1.484, p < 0.001). Unhealthy animals demonstrated significantly higher seropositivity (66.9%) compared to apparently healthy ones (26.9%, p < 0.001), with unhealthy animals being over five times more likely to be seropositive (OR = 5.479, p < 0.001) (Table 2 ). Among cattle, animals in poor condition had the highest seroprevalence (80%) compared to those in fair (72.3%) and good condition (64.3%) (p = 0.036). Similarly, unhealthy cattle exhibited higher seroprevalence (76.7%) than apparently healthy cattle (52.1%, p < 0.001). Goats followed a similar pattern, with poor condition animals showing the highest seroprevalence (62.5%) (p = 0.012). Pigs and sheep did not exhibit statistically significant associations between health or body condition and FMD infection. Serotype Distribution and Multi-Serotype Infections The study identified five circulating FMD serotypes in Nigerian livestock, with serotype O being the most prevalent (74.9%), followed by serotype A (56.3%), serotype SAT2 (35.8%), serotype Asia1 (22.9%), and serotype SAT1 (16.8%). The prevalence of FMD serotypes also varied across Nigeria’s six geopolitical zones and serotype O had the highest positivity rate in the North-West at 92.5%. A statistically significant association was found between geopolitical zone and serotype distribution (p < 0.001) (Fig. 3 ). Cattle exhibited the highest diversity serotype infection, while pigs had the least diversity. For cattle, 32% tested positive for two serotypes, 21.2% for three serotypes, 8% for four serotypes, and 8.7% for all five serotypes (Fig. 3 ). Goats and sheep had lower multi-serotype infection rates, while pigs were predominantly infected by single serotypes. Notably, 4.2% of cattle, 8.9% of goats, and 37.5% of pigs tested positive for FMD but not for any of the five major serotypes analyzed. Among multi-serotype combinations, O and A co-infections were most prevalent across all the four animal species, followed by O and SAT2. Chi-square values (p-values) suggested significant variation in serotype distributions across animal species, with p-values below 0.05 for most serotype combinations except specific cases such as SAT 2 and Asia 1 among goats and pigs (Fig. 2 ). Overall, serotype O and A emerged as the most prevalent combination across all animal types, with cattle showing the highest proportional distribution (Fig. 2 ). Lesser frequencies for combinations like SAT 2 and Asia 1, as well as SAT 1 and Asia 1, were consistently observed across species. The prevalence of specific serotype co-infections also differed based on health status. Unhealthy animals demonstrated higher prevalence across most serotype combinations, with significant associations observed for O and A (p = 0.004), O and Asia 1 (p < 0.001), and SAT 2 and Asia 1 (p = 0.001) (Fig. 3 ). Table 1 Seroprevalence of Foot-and-Mouth Disease Across Animal Species and Demographics Category Subcategory Seroprevalence p-value Animal Species Cattle 69.7 < 0.001 Sheep 26.9 Goat 20.6 Pigs 8.8 Sex Male 47.8 0.229 Female 44.0 Age Group Adult 45.4 0.767 Yearling 47.0 Young 38.9 Body Condition Poor 66.2 < 0.001 Fair 49.2 Good 39.5 Health Status Apparently Healthy 26.9 < 0.001 Unhealthy 66.9 Geopolitical Zones North-Central 73.8 < 0.001 North-East 46.3 North-West 51.1 South-East 71.2 South-South 9.1 South-West 45.1 Border Proximity Border States 47.9 0.124 Non-Border States 43.0 Border Region Northern Border States 47.6 0.295 Southern Border States 49.4 Non-Border States 43.0 Table 2 Logistic Regression Analysis of Factors Associated with FMD Seropositivity Variable Category Odds Ratio (Exp(B)) 95% CI (Confidence Interval) p-value Animal Species Pig (Reference) 1.000 (Reference) - - Cattle 23.829 11.259–50.431 < 0.001 Goat 2.699 1.217–5.984 0.015 Sheep 3.822 1.724–8.474 0.001 Geopolitical Zone South-South (Reference) 1.000 (Reference) - - North-Central 28.148 13.706–57.807 < 0.001 North-East 8.616 4.662–15.925 < 0.001 North-West 10.449 5.51–19.816 < 0.001 South-East 24.667 10.781–56.434 < 0.001 South-West 8.226 4.392–15.405 < 0.001 North/South South (Reference) 1.000 (Reference) - - North 1.969 1.523–2.546 < 0.001 Body Condition Good (Reference) 1.000 (Reference) - - Poor 3.008 1.814–4.987 < 0.001 Fair 1.484 1.143–1.927 < 0.001 Health Status Apparently Healthy (Reference) 1.000 (Reference) - - Unhealthy 5.479 4.177–7.186 < 0.001 Discussion The findings of our study carry significant implications for understanding the epidemiology of Foot-and-Mouth Disease (FMD), offering critical insights into the dynamics of its spread across species, geographical locations, and health status of infected animals. Notable patterns in seroprevalence, serotype distribution, and co-infections reveal not only the nature of FMD transmission but also its complex impact. One of the key findings was that the seroprevalence of FMD in Nigeria across various species is 45.7%, with variation in seroprevalence among animal species. Cattle exhibited the highest seropositivity (69.7%), followed by sheep, goats, and pigs, confirming species-specific susceptibility. This aligns with previous observations that cattle are more vulnerable to FMD even in shared ecosystems (Ehizibolo et al., 2019; Ploquin et al., 2025), highlighting the need to prioritise cattle in disease control programs. Differences between species at different locations point to the possible influence of environmental and management factors on infection dynamics, beyond intrinsic host characteristics. Geographical disparities in seroprevalence were prominent in our study, with states in the North-Central and South-East zones recording the highest rates, while the South-South zone had significantly lower prevalence. Our findings mirror previous reports from Nigeria supporting disparities in the seroprevalence by region, with higher prevalence mostly recorded in the northern parts of the country (Begovoeva et al., 2023 ); Wungak et al., 2016 ; Fomenky et al., 2023 ). These patterns suggest that regional factors such as livestock movement, and ecological conditions play a crucial role in shaping FMD epidemiology. Interestingly, proximity to international borders did not significantly affect seroprevalence, challenging reports about cross-border transmission earlier reported by Babangida et al. ( 2017 ), and indicating that localized containment measures may be effective in limiting disease spread. Health status and body condition emerged as strong determinants of seroprevalence. Animals in poor health or with low body condition scores were more likely to test positive for FMD, emphasizing the role of general well-being in disease susceptibility. In previous studies, health status and body condition scores have shown inconsistent associations with FMD seropositivity. While one study in Ethiopia found no significant link (Bahiru & Assefa, 2022 ), another in central Ethiopia established a clear correlation using multivariable logistic regression (Awel et al., 2021 ). However, our findings underline the role of the health status in animal susceptibility to FMD, which indicates the importance of improving livestock nutrition and overall care as part of broader disease prevention efforts, particularly in vulnerable animal populations. Our study also identified distribution of the different serotypes with serotype O being most prevalent in all the species, then followed by serotype A, SAT 2, SAT 1 and Asia 1. Our study also identified some animals that did not test positive to any of the five serotypes analyzed in this study. While SAT 3 have been previously reported in Nigeria (Ehizibolo et al., 2013 ), there is a lack of evidence indicating the circulation of serotype C in Nigeria. Nonetheless, our finding of new serotype, Asia 1, suggests that both serotypes may be circulating within various animal populations in Nigeria and should therefore be considered in future research study. Another view to this finding may be that new topotypes are emerging with similar antigenic variants with those serotypes that are not known to be circulating in this part of the world. Furthermore, serotype Asia 1 has been reported to be geographically restricted to Central Asia (Knowles & Samuel, 2003 ; Roeder & Knowles, 2008 ), however, this study provides evidence of its circulation in Nigeria which may, in the actual sense, be an evolutionary drift of one or more of the commonly circulating serotypes in Nigeria towards serotypes Asia 1. Furthermore, some of the animal species that tested positive for FMD but not for any of the five major serotypes analyzed indicate the potential circulation of overlooked strains such as serotype SAT 3, C or a new one that has not been reported. There are also complex trends of FMD epidemiology, especially with regards to the patterns of multi-serotype co-infections; in which cattle recorded the highest prevalence of co-infections and multiple serotypes. A key finding of this study is the widespread dominance of the O and A serotype combination across all examined animal species. The same pattern is seen with O and SAT 2 in all animal species except sheep. This consistent pairing emerged as the most prevalent co-infection pattern, suggesting a strong epidemiological foothold and possible adaptation of these serotypes within the Nigerian livestock population. The recurring presence of O and A across species underscores their role as a primary driver of multi-serotype FMD infections in the country. These findings have important implications for FMD control strategies. The cross-species dominance of O and A highlights the critical need for vaccines that robustly target both serotypes, ideally through polyvalent formulations. However, cattle showed other serotype combinations with SAT 2 and Asia 1 (15.4%) and SAT 1 and Asia 1 (13.5%) seen in some of the cattle sampled. The broad serotype diversity observed in cattle further reinforces their role as key amplifiers and reservoirs of FMD, a pattern also described by Arzt et al. ( 2021 ). This reservoir potential not only increases the risk of cross-species transmission but may also drive the emergence of novel recombinant strains. Our study supports a couple of other reports on multiple co-infections of various FMD serotypes in clinically and sub clinically infected animals (Fomenky et al., 2023 ; Wungak et al., 2017 ), showing that the multivalent vaccination against different serotypes is indeed needed. The differences in serotype distribution and co-infection patterns seen across species and geographical regions indicate complex transmission patterns that need to be studied in detail. Furthermore, animals in poor body condition scores and those that were unhealthy showed similar trends of serotype co-infection patterns, with unhealthy animals and those with poor body scores showing combination of “O and Asia 1”, and “SAT 2 and Asia 1”. This suggests that compromised immunity, possibly due to malnutrition or other conditions, may increase susceptibility not just to infection, but to specific types of serotype combinations. The extension of the studies to co-infections also contributes to the understanding of the interactions between serotypes, which remains a relatively under-researched subject. In addition, the presence of serotype co-infections underscores the need for multivalent vaccines to address the dominant strains effectively. Altogether, the observed species-specific, geographic, and health-related variations in co-infection patterns indicate that a uniform, one-size-fits-all vaccination strategy is unlikely to be effective. Instead, tailored interventions that account for the dominant serotype pairings within each region and animal population are essential for efficient control. The practical applications of our study are that it provides evidence that more specific preventive efforts should be designed for particular species and areas. There is thus the need to prioritise the high-risk regions, which include the North-Central and the South-East in terms of surveillance and vaccination. On the same note, it is also necessary to note that better nutrition and health care of livestock can also minimise vulnerability to FMD. Our study went further to highlight specific serotype co-infection dominant in different species, geographical locations and unhealthy animals. These insights also inform policy makers how to develop sound strategies, for instance, improving the coverage of the vaccines to include the circulating serotypes, or reconsidering the measures put in place for border control in light of the actual epidemiology of the region. In a theoretical sense, the study opens up a new approach to the existing models of FMD epidemiology by including species susceptibility, health status and regional variations together in one study. It goes beyond single species or single serotype evaluations and provides a broader perspective on the disease dynamics. Altogether, the outcome of the present study can provide useful information on the current situation, risk factors concerning FMD infection, affected species, geography, health effects, and serotypes. Our results therefore hold important implications for disease management and control measures, highlighting the need for context-specific approaches in the fight against FMD. Through targeting high-risk groups, enhancing animal health, and improving vaccination strategies, policymakers and stakeholders can ensure that the impact of FMD is minimised and communities’ welfare, livestock farmers livelihood and national food security are protected. Although the current study provides useful information regarding the epidemiological aspects of FMD, the following limitations have to be recognised in order to avoid misinterpretation of the results. One limitation concerns the imbalance of sample size across species with cattle having the highest representation in the sample. Also, the body condition scoring was subjective, which could hinder an empirical comparability of health status. However, these limitations do not reduce the usefulness of the study for the advancement of FMD research. In conclusion, we found that the health and nutritional state of animals influenced their susceptibility to infection because animals with poor health conditions showed more seropositivity with severity of viral infections involving multiple serotypes. Improved management practices which focus on nutrition and animal welfare are critical elements in FMD prevention. The polyvalent vaccination is required to protect livestock against the dominant serotypes. Further, improved surveillance systems and regional vaccination strategies for cattle with greater risks of exposure is needed. Since the serological profiles of other animals in this study mirrors what is observed in cattle, this could infer the possibility of transmission across several host species in shared ecosystems hence the need to enforce control measures in other species to fully control the spread of FMD in Nigeria. This study highlights several directions for future research to deepen understanding and improve control of Foot-and-Mouth Disease (FMD). A priority is expanding sample sizes and ensuring balanced species representation, particularly including underrepresented regions, to enhance cross-species and geographical comparisons. Longitudinal studies are also essential for tracking changes in FMD prevalence, serotype distribution, and co-infections over time. Further investigation into molecular and genetic factors could uncover species-specific susceptibility and resistance traits, while research on environmental, trade-related, and management practices, especially in the light of unexpected findings like the limited role of border proximity, can help clarify complex regional dynamics. Additional research should focus on evaluating the impact of targeted health and nutrition interventions on FMD susceptibility, given the strong associations observed between poor condition and infection. Vaccine development also warrants attention, particularly the need for effective multi-serotype formulations to address the widespread presence of serotype O and frequent co-infections. Unanswered questions regarding regional variability in serotype distribution and the ecological and genetic drivers of disease patterns present valuable opportunities for hypothesis-driven studies. Collectively, these research avenues can build on current findings to inform more targeted, effective, and sustainable FMD control strategies. Declarations Ethics Approval and Consent to Participate Ethical approval was obtained from the Ethical Review Committee of the National Veterinary Research Institute (NVRI), Vom, Nigeria with reference number AEC/02/148/24. All participants were provided with detailed information about the study and they gave written informed consent before participation. Consent for Publication All the farmers that participated in this study and allowed their animals to be recruited for this study gave written informed consent for the publication of anonymized data and findings for this study. No personally identifiable information is disclosed in this publication. Availability of Data and Materials The dataset generated during this study are available online in the Harvard Dataverse repository and can be accessed using this link – https://doi.org/10.7910/DVN/NYPX2S Competing Interests The authors of this paper declare that they have no competing interests. Funding There project was supported by Arpexas (Scotland) Limited, United Kingdom. Authors Contribution A.E.S. has made substantial contributions to the conception and design of the work, the acquisition, analysis, and interpretation of data, has drafted the work and approved the submitted version, and has agreed both to be personally accountable for the author's own contributions and to ensure that questions related to the accuracy or integrity of any part of the work. A.F. has substantively revised the work, approved the submitted version and has agreed both to be personally accountable for the author's own contributions and to ensure that questions related to the accuracy or integrity of any part of the work A.P has substantively revised the work and approved the submitted version and has agreed both to be personally accountable for the author's own contributions and to ensure that questions related to the accuracy or integrity of any part of the work. A.B.O has substantively revised the work and approved the submitted version and has agreed both to be personally accountable for the author's own contributions and to ensure that questions related to the accuracy or integrity of any part of the work. Acknowledgment Not applicable References Abdela, N. (2017). Sero-prevalence, risk factors and distribution of foot and mouth disease in Ethiopia. Acta Tropica , 169 , 125–132. https://doi.org/10.1016/j.actatropica.2017.02.017 Alexandersen, S., Donaldson, A.I.2002.Further studies to quantify the dose of natural aerosols of foot-and-mouth disease virus for pigs.Epidem. Infect. 128: 313-323. Alexandersen, S., Kitching, R.P., Mansley, L.M., Donaldson, A.I. 2003.Clinical and laboratory investigations of five outbreaks during the early stages of the 2001 foot-and-mouth disease epidemic in the United Kingdom. Vet. Rec. 152: 489–496 Arzt, J., Fish, I. H., Bertram, M. R., Smoliga, G. R., Hartwig, E. J., Pauszek, S. J., Holinka-Patterson, L., Segundo, D.-S., Sitt, T., Rieder, E., & Stenfeldt, C. (2021). Simultaneous and Staggered Foot-and-Mouth Disease Virus Coinfection of Cattle. Journal of Virology , 95 . https://doi.org/10.1128/jvi.01650-21 Atuman YJ, Kudi CA, Abdu PA, Okubanjo OO, Abubakar A, Wungak Y, Ularamu HG. Seroprevalence of Foot and Mouth Disease Virus Infection in Some Wildlife and Cattle in Bauchi State, Nigeria. Vet Med Int. 2020 Mar 18;2020:3642793. doi: 10.1155/2020/3642793. PMID: 32257095; PMCID: PMC7104331. Awel, S. M., Dilba, G. M., Abraha, B., Zewde, D., Wakjira, B. S., & Aliy, A. (2021). Seroprevalence and Molecular Detection of Foot and Mouth Disease Virus in Dairy Cattle Around Addis Ababa, Central Ethiopia. Veterinary Medicine , Volume 12 , 187–197. https://doi.org/10.2147/vmrr.s317103 Babangida, D., Ibrahim, A. A., Oladayo, F. O., Magaji, A. A., Alkali, B. R., & Jibril, A. H. (2017). Sero Survey of Foot and Mouth Disease Virus Infection in Cattle Crossing Some Major Border States in Northwestern Nigeria. Folia Veterinaria , 61 , 12–18. https://doi.org/10.1515/fv-2017-0022 Bahiru, A., & Assefa, A. (2022). Seroepidemiological investigation of Foot and Mouth Disease (FMD) in Northern Amhara, Ethiopia. Scientific African , 16 , e01267. https://doi.org/10.1016/j.sciaf.2022.e01267 Begovoeva, M., Ehizibolo, D. O., Adedeji, A. J., Oguche, M. O., Oyekan, O., Ijoma, S. I., Atai, R. B., Wungak, Y., Dogonyaro, B. B., Lazarus, D. D., Samson, M., Ularamu, H., Muhammad, M., Rosso, F., Sumption, K. J., Beard, P. M., Ludi, A. B., Stevens, K. B., & Limon, G. (2023). Factors associated with foot-and-mouth disease seroprevalence in small ruminants and identification of hot-spot areas in northern Nigeria. Preventive Veterinary Medicine , 212 , 105842. https://doi.org/10.1016/j.prevetmed.2023.105842 Bouslikhane Mohammed (2015). Cross border movements of animals and animal products and their relevance to the epidemiology of animal diseases in africa. OIE Regional Commission. Retrieved from https://www.woah.org/app/uploads/2021/03/2015-afr2-bouslikhane-a.pdf BLANCO, E., ROMERO, L. J., EL HARRACH, M., and SÁNCHEZ-VIZCAÍNO, J. M. 2002: Serological evidence of FMD subclinical infection in sheep population during the 1999 epidemic in Morocco. Veterinary Microbiology, 85(1), 13–21. Dohoo, I., W. Martin, and H. Stryhn. 2003. Veterinary Epidemiologic Research. Charlottetown, PE, Canada: Atlantic Veterinary College Ehizibolo, D. O., Perez, A., Carrillo, C., Pauszek, S. J., Alkhamis, M. A., Ajogi, I., Umoh, J. U., Kazeem, H. M., Ehizibolo, P. O., Fabian, A., Berninger, M. Lou, Moran, K., Rodriguez, L. L., & Metwally, S. (2013). Epidemiological Analysis, Serological Prevalence and Genotypic Analysis of Foot-and-Mouth Disease in Nigeria 2008-2009. Transboundary and Emerging Diseases , 61 , 500–510. https://doi.org/10.1111/tbed.12054 Ezeokoli, C.D., Abegunde A., Umoh, J.U. and Addo, P.B. (1988). Epidemiology of FMD in Nigeria cattle. Rev. Sci. Off. Int. Epiz., 10(1):485-488. FAO (2021). Foot and mouth disease. Quarterly report, October–December 2021. Rome. Food and Agriculture Organization (2024). FMD: Differential diagnosis in cattle. Retrieved from https://openknowledge.fao.org/server/api/core/bitstreams/a131e390-c9da-4220-8287-ac46c553c381/content Food and Agriculture Organization (2025). Foot-and-mouth disease. Retrieved from https://www.fao.org/animal-health/animal-diseases/foot-and-mouth-disease/en FERRIS, N. P., and DONALDSON, A. I. 1992: The World Reference Laboratory for Foot and Mouth Disease: a review of thirty-three years of activity (1958-1991). Revue Scientifique et Technique (International Office of Epizootics), 11(3), 657–684. Fomenky, B., Wungak, Y. S., Ehizibolo, D. O., Sada, A., Oyekan, O. A., Inuwa, B., Anyika, K. C., Nfon, C., & Ularamu, G. H. (2023). Bovine Sero- surveillance of Foot- and – Mouth Disease in Four States in Nigeria. Journal of Veterinary and Biomedical Sciences , 5 , 24–33. https://doi.org/10.36108/jvbs/3202.50.0140 GRUBMAN, M. J. and BAXT, B. 2004: Foot-and-mouth disease. Clin Microbiol Rev, 17(2), 465– 493. Jamal SM, Shah SI, Ali Q, Mehmood A, Afzal M, Afzal M, Dekker A (2013). Proper Quality Control of Formulated Foot–and–Mouth Disease Vaccines in Countries with Prophylactic Vaccination is Necessary. Transbound Emerg Dis. doi: 10.1111/tbed.12051 Knowles N.J. & Samuel A.R. (2003). – Molecular epidemiology of foot-and-mouth disease virus. Virus Res. , 91 (1), 65–80. doi:10.1016/S0168-1702(02)00260-5. Lazarus, D., Schielen, W. J. G., Wungak, Y. S., Kwange, D., & Fasina, F. O. (2012). Sero-epidemiology of foot-and-mouth disease in some Border States of Nigeria . 6 . https://doi.org/10.5897/ajmr11.1026 Libeau J. Foot-and-mouth disease in Africa south of the Sahara the present situation. Bulletin of Epizootic Diseases in Africa. 1960;8:90–104. https://www.cabidigitallibrary.org/doi/full/10.5555/19612200093 Naveed, A. (2018). Foot-and-Mouth Disease: A Strategic Analysis for the Control of Disease. Vaccines & Vaccination Open Access , 3 . https://doi.org/10.23880/vvoa-16000125 OIE, 2021. FAO and OIE continue to support the control of foot-and-mouth disease in West Africa. Available on https://www.woah.org/en/disease/foot-and-mouth-disease/ (Accessed on 13th January, 2024) Olabode, O.H., Kazeem, H.M., Raji, M.A., Ibrahim, N.D.2014.Participatory appraisal of Foot and Mouth disease outbreaks in Ilesha Baruba, Kwara state Nigeria. Alexandria J. Vet. Sci. 40: 132-138 Oyewusi IK, Talabi AO. Control strategies for foot and mouth disease with particular reference to Nigeria. Afr J Livest Ext 2015; 15(1): 9-17. Roeder P.L. & Knowles N.J. (2008). – Foot-and-mouth disease virus type C situation: the first target for eradication? In Report of the Session of the Research Group of the Standing Technical Committee of EUFMD, Erice, Italy, 14–17 October, Appendix 7. Available at: www.fao.org/ag/againfo/commissions/docs/research_group/erice/APPENDIX_07.pdf RUECKERT, R. R. 1990: Picornaviruses and their replication. In: Fields BN et Al, Eds. Fields Virology. 2nd Edition. Raven Press, New York, 507–548. Thrusfield, M., 2018. Veterinary epidemiology, 4th ed. John Wiley & Sons Ularamu, H., Lefebvre, D., Haegeman, A., Wungak, Y. S., Ehizibolo, D. O., Lazarus, D. D., De, R., & Clercq, K. De. (2020). Complex Circulation of Foot-and-Mouth Disease Virus in Cattle in Nigeria. Frontiers in Veterinary Science , 7 . https://doi.org/10.3389/fvets.2020.00466 Woldemariyam, F.T.; De Vleeschauwer, A.; Hundessa, N.; Muluneh, A. Risk Factor Assessment, Sero-Prevalence, and Genotyping of the Virus that Causes Foot-and-Mouth Disease on Commercial Farms in Ethiopia from October 2018 to February 2020. Agriculture 2022,12, 49 Wungak, Y. S., Ishola, O. O., Olugasa, B. O., Lazarus, D. D., Ehizibolo, D. O., & Ularamu, H. G. (2017). Spatial pattern of foot-and-mouth disease virus serotypes in North Central Nigeria. Veterinary World , 10 , 450–456. https://doi.org/10.14202/vetworld.2017.450-456 Wungak, Y. S., Olugasa, B. O., Ishola, O. O., Lazarus, D. D., & Ularamu, G. H. (2016). Foot-and-mouth disease (FMD) prevalence and exposure factors associated with seropositivity of cattle in north-central, Nigeria. African Journal of Biotechnology , 15 , 1224–1232. https://doi.org/10.5897/ajb2016.15332 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 06 Mar, 2026 Read the published version in BMC Microbiology → Version 1 posted Editorial decision: Revision requested 21 Oct, 2025 Reviews received at journal 16 Oct, 2025 Reviewers agreed at journal 16 Oct, 2025 Reviews received at journal 07 Oct, 2025 Reviews received at journal 18 Sep, 2025 Reviewers agreed at journal 15 Sep, 2025 Reviewers agreed at journal 15 Sep, 2025 Reviewers agreed at journal 14 Sep, 2025 Reviewers invited by journal 12 Sep, 2025 Editor assigned by journal 12 Sep, 2025 Editor invited by journal 12 Sep, 2025 Submission checks completed at journal 11 Sep, 2025 First submitted to journal 11 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-7437182\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":516989147,\"identity\":\"8f729da1-ed0b-4ffb-b73b-72a032086aa5\",\"order_by\":0,\"name\":\"Adebayo Emmanuel SOPEJU\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of Ibadan\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Adebayo\",\"middleName\":\"Emmanuel\",\"lastName\":\"SOPEJU\",\"suffix\":\"\"},{\"id\":516989148,\"identity\":\"093658e6-c69b-49b6-88ae-bce6fc9edfa0\",\"order_by\":1,\"name\":\"Adedayo FANEYE\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of Ibadan\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Adedayo\",\"middleName\":\"\",\"lastName\":\"FANEYE\",\"suffix\":\"\"},{\"id\":516989149,\"identity\":\"7cb03e75-eef2-4401-9484-702e559ed2b8\",\"order_by\":2,\"name\":\"Andrew Peters\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Arpexas (Scotland) Limited\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Andrew\",\"middleName\":\"\",\"lastName\":\"Peters\",\"suffix\":\"\"},{\"id\":516989150,\"identity\":\"ac533322-3e1e-4cf3-9d6b-f6acb097af24\",\"order_by\":3,\"name\":\"Anyebe Bernard ONOJA\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5ElEQVRIiWNgGAWjYBACAwjFDCISGD6ACJK0MM4gVQsDMw8xWszZe589+LnHWs6cveHhZ9s2uzx+9gbGDx9zcGux7DlubtjzLN3YsudAsnRuW3KxZM8BZsmZ2/A47EYamwTPgcOJG24kJAC1MIMYbMy8+LTcf8Ym+QeiJfm3ZVs9EVpusLFJQ21Jk2ZsO0xYi2VPGpu0zIF0Y4MzB9Ise84dT5zZc7AZr1/M2Y+xSb45YC1ncLwn+caPsurEfvbmgx8+4tGCBHgSGBjZQAzGBqLUAwH7AQaGP8QqHgWjYBSMgpEEADKOVVg+uDLCAAAAAElFTkSuQmCC\",\"orcid\":\"\",\"institution\":\"University of Ibadan\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Anyebe\",\"middleName\":\"Bernard\",\"lastName\":\"ONOJA\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2025-08-22 20:08:09\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-7437182/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-7437182/v1\",\"draftVersion\":[],\"editorialEvents\":[{\"content\":\"https://doi.org/10.1186/s12866-026-04774-6\",\"type\":\"published\",\"date\":\"2026-03-06T15:58:23+00:00\"}],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":91702212,\"identity\":\"831018e9-cbbf-4344-9a0e-568cc6615862\",\"added_by\":\"auto\",\"created_at\":\"2025-09-19 10:44:49\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":134143,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cem\\u003eState-wide distribution of FMDV by serotype among infected animals among in Nigeria. The plot is facetted according to serotype, the legend shows a color scale representing prevalence rates of FMD serotypes by proportion where 1 = 100%.\\u003c/em\\u003e\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7437182/v1/6d29e54d9795b0dfb4c808c6.png\"},{\"id\":91704484,\"identity\":\"2ac996ff-fd43-4320-a51f-9daa7e1a2aa9\",\"added_by\":\"auto\",\"created_at\":\"2025-09-19 11:08:55\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":122228,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cem\\u003eState-wide distribution of FMDV by serotype among infected animals among in Nigeria\\u003c/em\\u003e\\u003cem\\u003e\\u003cstrong\\u003e \\u003c/strong\\u003e\\u003c/em\\u003e\\u003cem\\u003ewith a. representing cattle; b. representing goats; c. representing pig; and d. representing sheep\\u003c/em\\u003e\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7437182/v1/58e8501cd1e61267e230a38c.png\"},{\"id\":91702213,\"identity\":\"192d8909-b2f7-447c-9f40-83a15a1c65e2\",\"added_by\":\"auto\",\"created_at\":\"2025-09-19 10:44:50\",\"extension\":\"png\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":164788,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cem\\u003eState-wide distribution of FMDV Serotype co-infection among animals in Nigeria. The plot is facetted according to co-infecting serotypes, the legend shows a color scale representing prevalence rates of FMD serotypes combination by proportion where 1 = 100%.\\u003c/em\\u003e\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"3.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7437182/v1/a1f3898b560ac3c6a4496724.png\"},{\"id\":104251292,\"identity\":\"9b5966ab-37a9-425b-8c7f-a4e9f7a036bb\",\"added_by\":\"auto\",\"created_at\":\"2026-03-09 16:12:40\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":1149708,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7437182/v1/caf0b038-b892-4dcf-98b0-db06b65beb70.pdf\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Seroepidemiology and Serotype Diversity of Foot-and-Mouth Disease Virus Among Domestic Ungulates Across Nigeria\",\"fulltext\":[{\"header\":\"Introduction\",\"content\":\"\\u003cp\\u003eFoot-and-mouth disease (FMD) is a highly contagious viral infection that affects cloven-hoofed livestock and wildlife, causing significant economic losses and severe socioeconomic problems. It is listed as a notifiable disease by the World Organization for Animal Health (WOAH) due to its wide distribution and potential to disrupt animal production systems. Globally, FMD circulate within 77% of the livestock population (OIE, \\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e). FMD is caused by the Foot-and-Mouth Disease Virus (FMDV), a non-enveloped, single-stranded, positive-sense RNA virus of approximately 8.5kb in size. It belongs to the genus Aphthovirus in the family \\u003cem\\u003ePicornaviridae\\u003c/em\\u003e and is surrounded by an icosahedral capsid composed of four structural proteins (Rueckert, \\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e1990\\u003c/span\\u003e). There are seven immunologically distinct serotypes of FMDV (O, A, C, SAT 1, SAT 2, SAT 3, and Asia 1), with serotype O being the most prevalent globally (FAO, \\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e). There is no cross-protection across these serotypes, and even among subtypes within a serotype, immune protection is insufficient (Naveed, \\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e). The disease is endemic and occurs year-round in Nigeria with seasonal outbreaks. Historical records trace the first reported outbreak to 1924 (Libeau, \\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e1960\\u003c/span\\u003e), underscoring the long-standing presence and persistent challenge to livestock health and productivity in the country. In Nigeria, serotypes O, A, SAT 1, and SAT 2 have been documented historically, with a study stating the detection of antibodies against SAT3 across multiple states (Ehizibolo et al., \\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e2013\\u003c/span\\u003e). The principal domestic hosts of FMDV are cattle, pigs, goats, and sheep (Ferris and Donaldson, \\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e1992\\u003c/span\\u003e; Jamal et al., \\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e2013\\u003c/span\\u003e). Among these, FMD manifests mildly in sheep and goats, sometimes resembling other vesicular disease like vesicular stomatitis (Blanco et al., \\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e2002\\u003c/span\\u003e; FAO, 2024). Pigs, although susceptible, exhibit relatively lower risk for airborne transmission compared to cattle and sheep (Alexandersen and Donaldson, 2002). Transmission of the virus occurs by direct contact via respiratory droplets from infected animals, and indirectly through contaminated fomites such as vehicles, equipment, or personnel (Alexandersen et al., \\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e2003\\u003c/span\\u003e). Though FMD typically causes low mortality (except in young calves), it has high morbidity and severely affects productivity. Infected animals show clinical signs including fever, lameness, and vesicle formation in the mouth, on the feet, and on the teats of lactating cows and the snouts of pigs (Grubman and Baxt, \\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e2004\\u003c/span\\u003e). These vesicles eventually rupture, leading to painful erosions, excessive salivation, difficulty in eating, and reluctance to move, all of which impair the animal\\u0026rsquo;s performance. Economic losses are compounded by trade restrictions placed on meat and animal products originating from affected regions (FAO, 2025).\\u003c/p\\u003e\\u003cp\\u003eRoutine prophylactic vaccination using inactivated FMD vaccines is recommended in endemic countries, but in Nigeria, it is largely restricted to a few dairy farms where trivalent vaccines targeting serotypes O, A, and SAT 2 are used (Lazarus et al., \\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e2012\\u003c/span\\u003e). Despite being endemic, Nigeria has yet to implement a comprehensive FMD vaccination program. Control measures are typically cattle-focused, even though FMD affects all cloven-hoofed species (OIE, \\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e). The situation is exacerbated by unrestricted transboundary animal movement, particularly at poorly regulated border posts in Africa including Nigeria (Bouslikhane, 2015; Woldemariyam et al., \\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e) and limited access to vaccines by smallholder farmers in rural areas due to several factors like lack of awareness, lack of access, cost of the vaccine affecting sales by agro-veterinary infrastructures (Sopeju et al., 2025). Oyewusi and Talabi (\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e2015\\u003c/span\\u003e) stressed the need for broader vaccination programs that include all susceptible species, improved disease surveillance, and the establishment of effective control posts along major livestock entry routes.\\u003c/p\\u003e\\u003cp\\u003eWhile numerous studies have been conducted on the epidemiology of FMD in Nigeria, Atuman et al. (\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e) highlighted that seroepidemiological and serotyping investigations are inadequate despite the annual incidence. This gap in research underscores the need for updated and comprehensive surveillance activity. Therefore, we investigated the seroepidemiology FMD and determined the circulating serotypes of FMDV across various domestic ungulate species in all geopolitical zones in the country.\\u003c/p\\u003e\"},{\"header\":\"Methodology\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eStudy Area\\u003c/h2\\u003e\\u003cp\\u003eBorder States of Niger Republic (Jigawa, Sokoto and Yobe State), Benin Republic (Niger, Ogun and Oyo States) and Cameroon (Adamawa and Taraba State). Other selected states (Plateau, Kaduna, Lagos, Ebonyi and Cross-River State). Ethical approval was obtained from Ethical Review Board of the National Veterinary Research Institute (NVRI), Vom with reference number AEC/02/148/24.\\u003c/p\\u003e\\u003c/div\\u003e\\n\\u003ch3\\u003eStudy Population\\u003c/h3\\u003e\\n\\u003cp\\u003eDomestic ungulate animals (cattle, sheep, goat and pigs) from consenting farmers in our study areas were selected for the study. Samples were collected from 511 cattle, 182 sheep, 218 goats and 91 pigs located in our study areas. Blood samples were collected from individual animals using sterile needle and syringe, with the 5 ml of blood collected from jugular veins of cattle, sheep and goats and from the cranial vena cava in pigs.\\u003c/p\\u003e\\n\\u003ch3\\u003eStudy design\\u003c/h3\\u003e\\n\\u003cp\\u003eThis is a cross-sectional study, and we aseptically collected 5ml of blood from each of the jugular veins of cattle, sheep and goat and vena cava of pigs in our study.\\u003c/p\\u003e\\n\\u003ch3\\u003eInclusion and Exclusion Criteria\\u003c/h3\\u003e\\n\\u003cp\\u003eInclusion Criteria include weaned domestic ungulate animals from markets, farms or communities where there is an on-going or previous history of FMD outbreak. The exclusion Criteria include all domestic ungulate animals that are yet to be weaned and those found on farms or communities where there has not been history of FMD outbreaks were excluded. Border States are states that share boundary with neighbouring countries and with known international livestock trade. Non-border States are states without international cattle trade (with or without boundary with other countries). The sample size was calculated using the following formula with prevalence rate of 50% (Dohoo et al., \\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e2003\\u003c/span\\u003e; Thrusfield, \\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e). 1002 sera were obtained from cattle, sheep, goat and pigs in our study areas.\\u003c/p\\u003e\\n\\u003ch3\\u003eSerological Assay\\u003c/h3\\u003e\\n\\u003cp\\u003eCommercial ELISA kits (NSP and Serotype-specific for serotype A, O, SAT 1, SAT 2 and Asia 1) were used to detect the animals that were seropositive for FMD and the above-mentioned FMD serotypes. The kits were purchased from ID Vet (for NSP, Serotype O and A) and IZLER from Italy for Serotypes SAT 1, SAT 2 and Asia 1. Sera from the samples collected were first tested for positivity using NSP ELISA kits. The positive samples were then anlyzed further for serotyping using serotype-specific ELISA kits for serotype O, A, SAT 1, SAT 2 and Asia 1. Each of the assays were carried out according to each of the manufacturers\\u0026rsquo; instructions. The results of optical density (O.D.) values were validated, percentage inhibition was calculated, and positivity was determined according to the standard provided by the manufacturer standard provided in the ELISA manuals.\\u003c/p\\u003e\\u003cdiv id=\\\"Sec8\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eData Analysis\\u003c/h2\\u003e\\u003cp\\u003eQuestionnaires uploaded on Kobocollect were used to get information on the animal sampled and other information relevant to this study. Metadata generated from the sampled animals were transferred in an excel sheet with ascribed sample ID for each animal. Descriptive and inferential analysis of data was carried out using EXCEL and IBM SPSS to generate relevant figures.\\u003c/p\\u003e\\u003cp\\u003e\\u003cstrong\\u003eClinical Trial Number\\u003c/strong\\u003e\\u003cp\\u003eNot applicable\\u003c/p\\u003e\\u003c/p\\u003e\\u003c/div\\u003e\"},{\"header\":\"Result\",\"content\":\"\\u003cdiv id=\\\"Sec10\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eSeroprevalence of Foot and Mouth Disease (FMD) across Animal Species\\u003c/h2\\u003e\\u003cp\\u003eThe overall seroprevalence of Foot and Mouth Disease (FMD) is 45.7% (458/1002), with significant variation across species, Cattle had the highest seropositivity (69.7%), followed by sheep (26.9%), goats (20.6%), and pigs (8.8%) (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). Logistic regression analysis further confirmed that cattle had the highest odds of seropositivity compared to pigs (reference category), (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). Among cattle, females had a significantly higher seroprevalence (74%) than males (65.5%) (χ\\u0026sup2; = 4.35, p\\u0026thinsp;=\\u0026thinsp;0.037), but age was not a significant determinant. In sheep and goats, sex and age did not significantly influence seropositivity (Table\\u0026nbsp;4). A similar trend was observed in pigs, where seropositivity did not differ significantly by gender or age (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e).\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec11\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eGeographical and Border Proximity Influence on Seroprevalence\\u003c/h2\\u003e\\u003cp\\u003eSeroprevalence varied significantly across states, regions and geopolitical zones, with Kaduna states having the highest prevalence (88.9%),) (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). At the geopolitical zonal level, the North-Central (73.8%) and South-East (71.2%) had the highest seropositivity, as shown by the Logistic regression analysis. (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). Among cattle, seropositivity was significantly higher in the South-East (95%) and North-Central (87.7%), with the lowest rates in the South-South (12.7%) (χ\\u0026sup2; = 121.63, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001) (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). For sheep, Ebonyi (100%) showed the highest rates, while Jigawa (9.1%) had the lowest seropositivity (χ\\u0026sup2; = 72.23, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001). For goats, the highest prevalence was recorded in Plateau (60%) followed by Niger (50%), while Lagos (3.3%) had the lowest rates (χ\\u0026sup2; = 41.8, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001). In pigs, Adamawa had the highest seroprevalence (100%) while Cross River (4.2%) had the lowest (χ\\u0026sup2; = 38.37, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e). Proximity to international borders did not significantly influence seroprevalence, as border states (48.9% for Niger, 49.4% for Benin, and 45.7% for Cameroon) had similar rates to non-border states (43%) (p\\u0026thinsp;=\\u0026thinsp;0.403) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e).\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec12\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eInfluence of Health Status and Body Condition on Seroprevalence\\u003c/h2\\u003e\\u003cp\\u003eHealth status and body condition significantly influenced FMD seroprevalence. Animals in poor body condition exhibited the highest seroprevalence (66.2%), while those in fair (49.2%) and good condition (39.5%) had lower infection rates (p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001). Logistic regression analysis indicated that animals in poor condition were three times more likely to be seropositive than those in good condition (OR\\u0026thinsp;=\\u0026thinsp;3.008, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001). Animals in fair condition had moderately increased odds of seropositivity (OR\\u0026thinsp;=\\u0026thinsp;1.484, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001). Unhealthy animals demonstrated significantly higher seropositivity (66.9%) compared to apparently healthy ones (26.9%, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001), with unhealthy animals being over five times more likely to be seropositive (OR\\u0026thinsp;=\\u0026thinsp;5.479, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001) (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). Among cattle, animals in poor condition had the highest seroprevalence (80%) compared to those in fair (72.3%) and good condition (64.3%) (p\\u0026thinsp;=\\u0026thinsp;0.036). Similarly, unhealthy cattle exhibited higher seroprevalence (76.7%) than apparently healthy cattle (52.1%, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001). Goats followed a similar pattern, with poor condition animals showing the highest seroprevalence (62.5%) (p\\u0026thinsp;=\\u0026thinsp;0.012). Pigs and sheep did not exhibit statistically significant associations between health or body condition and FMD infection.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec13\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eSerotype Distribution and Multi-Serotype Infections\\u003c/h2\\u003e\\u003cp\\u003e The study identified five circulating FMD serotypes in Nigerian livestock, with serotype O being the most prevalent (74.9%), followed by serotype A (56.3%), serotype SAT2 (35.8%), serotype Asia1 (22.9%), and serotype SAT1 (16.8%). The prevalence of FMD serotypes also varied across Nigeria\\u0026rsquo;s six geopolitical zones and serotype O had the highest positivity rate in the North-West at 92.5%. A statistically significant association was found between geopolitical zone and serotype distribution (p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e). Cattle exhibited the highest diversity serotype infection, while pigs had the least diversity. For cattle, 32% tested positive for two serotypes, 21.2% for three serotypes, 8% for four serotypes, and 8.7% for all five serotypes (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e). Goats and sheep had lower multi-serotype infection rates, while pigs were predominantly infected by single serotypes. Notably, 4.2% of cattle, 8.9% of goats, and 37.5% of pigs tested positive for FMD but not for any of the five major serotypes analyzed. Among multi-serotype combinations, O and A co-infections were most prevalent across all the four animal species, followed by O and SAT2. Chi-square values (p-values) suggested significant variation in serotype distributions across animal species, with p-values below 0.05 for most serotype combinations except specific cases such as SAT 2 and Asia 1 among goats and pigs (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). Overall, serotype O and A emerged as the most prevalent combination across all animal types, with cattle showing the highest proportional distribution (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). Lesser frequencies for combinations like SAT 2 and Asia 1, as well as SAT 1 and Asia 1, were consistently observed across species. The prevalence of specific serotype co-infections also differed based on health status. Unhealthy animals demonstrated higher prevalence across most serotype combinations, with significant associations observed for O and A (p\\u0026thinsp;=\\u0026thinsp;0.004), O and Asia 1 (p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001), and SAT 2 and Asia 1 (p\\u0026thinsp;=\\u0026thinsp;0.001) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003e\\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e\\u003ccaption language=\\\"En\\\"\\u003e\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\u003cp\\u003eSeroprevalence of Foot-and-Mouth Disease Across Animal Species and Demographics\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/caption\\u003e\\u003ccolgroup cols=\\\"4\\\"\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e\\u003cthead\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eCategory\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eSubcategory\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eSeroprevalence\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003ep-value\\u003c/p\\u003e\\u003c/th\\u003e\\u003c/tr\\u003e\\u003c/thead\\u003e\\u003ctbody\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eAnimal Species\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eCattle\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e69.7\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eSheep\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e26.9\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eGoat\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e20.6\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003ePigs\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e8.8\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eSex\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eMale\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e47.8\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003e0.229\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eFemale\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e44.0\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eAge Group\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eAdult\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e45.4\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003e0.767\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eYearling\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e47.0\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eYoung\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e38.9\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eBody Condition\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003ePoor\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e66.2\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eFair\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e49.2\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eGood\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e39.5\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eHealth Status\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eApparently Healthy\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e26.9\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eUnhealthy\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e66.9\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eGeopolitical Zones\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eNorth-Central\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e73.8\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eNorth-East\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e46.3\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eNorth-West\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e51.1\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eSouth-East\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e71.2\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eSouth-South\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e9.1\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" 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colname=\\\"c2\\\"\\u003e\\u003cp\\u003eNorth\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e1.969\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e1.523\\u0026ndash;2.546\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eBody Condition\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eGood (Reference)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e1.000 (Reference)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e-\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e-\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003ePoor\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e3.008\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e1.814\\u0026ndash;4.987\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eFair\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e1.484\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e1.143\\u0026ndash;1.927\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eHealth Status\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eApparently Healthy (Reference)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e1.000 (Reference)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e-\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e-\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eUnhealthy\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e5.479\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e4.177\\u0026ndash;7.186\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tbody\\u003e\\u003c/colgroup\\u003e\\u003c/table\\u003e\\u003c/div\\u003e\\u003c/p\\u003e\\u003cp\\u003e\\u003c/p\\u003e\\u003cp\\u003e\\u003c/p\\u003e\\u003cp\\u003e\\u003c/p\\u003e\\u003c/div\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eThe findings of our study carry significant implications for understanding the epidemiology of Foot-and-Mouth Disease (FMD), offering critical insights into the dynamics of its spread across species, geographical locations, and health status of infected animals. Notable patterns in seroprevalence, serotype distribution, and co-infections reveal not only the nature of FMD transmission but also its complex impact.\\u003c/p\\u003e\\u003cp\\u003eOne of the key findings was that the seroprevalence of FMD in Nigeria across various species is 45.7%, with variation in seroprevalence among animal species. Cattle exhibited the highest seropositivity (69.7%), followed by sheep, goats, and pigs, confirming species-specific susceptibility. This aligns with previous observations that cattle are more vulnerable to FMD even in shared ecosystems (Ehizibolo et al., 2019; Ploquin et al., 2025), highlighting the need to prioritise cattle in disease control programs. Differences between species at different locations point to the possible influence of environmental and management factors on infection dynamics, beyond intrinsic host characteristics.\\u003c/p\\u003e\\u003cp\\u003eGeographical disparities in seroprevalence were prominent in our study, with states in the North-Central and South-East zones recording the highest rates, while the South-South zone had significantly lower prevalence. Our findings mirror previous reports from Nigeria supporting disparities in the seroprevalence by region, with higher prevalence mostly recorded in the northern parts of the country (Begovoeva et al., \\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e); Wungak et al., \\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e2016\\u003c/span\\u003e; Fomenky et al., \\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e). These patterns suggest that regional factors such as livestock movement, and ecological conditions play a crucial role in shaping FMD epidemiology. Interestingly, proximity to international borders did not significantly affect seroprevalence, challenging reports about cross-border transmission earlier reported by Babangida et al. (\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e2017\\u003c/span\\u003e), and indicating that localized containment measures may be effective in limiting disease spread.\\u003c/p\\u003e\\u003cp\\u003eHealth status and body condition emerged as strong determinants of seroprevalence. Animals in poor health or with low body condition scores were more likely to test positive for FMD, emphasizing the role of general well-being in disease susceptibility. In previous studies, health status and body condition scores have shown inconsistent associations with FMD seropositivity. While one study in Ethiopia found no significant link (Bahiru \\u0026amp; Assefa, \\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e), another in central Ethiopia established a clear correlation using multivariable logistic regression (Awel et al., \\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e). However, our findings underline the role of the health status in animal susceptibility to FMD, which indicates the importance of improving livestock nutrition and overall care as part of broader disease prevention efforts, particularly in vulnerable animal populations.\\u003c/p\\u003e\\u003cp\\u003eOur study also identified distribution of the different serotypes with serotype O being most prevalent in all the species, then followed by serotype A, SAT 2, SAT 1 and Asia 1. Our study also identified some animals that did not test positive to any of the five serotypes analyzed in this study. While SAT 3 have been previously reported in Nigeria (Ehizibolo et al., \\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e2013\\u003c/span\\u003e), there is a lack of evidence indicating the circulation of serotype C in Nigeria. Nonetheless, our finding of new serotype, Asia 1, suggests that both serotypes may be circulating within various animal populations in Nigeria and should therefore be considered in future research study. Another view to this finding may be that new topotypes are emerging with similar antigenic variants with those serotypes that are not known to be circulating in this part of the world. Furthermore, serotype Asia 1 has been reported to be geographically restricted to Central Asia (Knowles \\u0026amp; Samuel, \\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e2003\\u003c/span\\u003e; Roeder \\u0026amp; Knowles, \\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e2008\\u003c/span\\u003e), however, this study provides evidence of its circulation in Nigeria which may, in the actual sense, be an evolutionary drift of one or more of the commonly circulating serotypes in Nigeria towards serotypes Asia 1. Furthermore, some of the animal species that tested positive for FMD but not for any of the five major serotypes analyzed indicate the potential circulation of overlooked strains such as serotype SAT 3, C or a new one that has not been reported.\\u003c/p\\u003e\\u003cp\\u003eThere are also complex trends of FMD epidemiology, especially with regards to the patterns of multi-serotype co-infections; in which cattle recorded the highest prevalence of co-infections and multiple serotypes. A key finding of this study is the widespread dominance of the O and A serotype combination across all examined animal species. The same pattern is seen with O and SAT 2 in all animal species except sheep. This consistent pairing emerged as the most prevalent co-infection pattern, suggesting a strong epidemiological foothold and possible adaptation of these serotypes within the Nigerian livestock population. The recurring presence of O and A across species underscores their role as a primary driver of multi-serotype FMD infections in the country. These findings have important implications for FMD control strategies. The cross-species dominance of O and A highlights the critical need for vaccines that robustly target both serotypes, ideally through polyvalent formulations. However, cattle showed other serotype combinations with SAT 2 and Asia 1 (15.4%) and SAT 1 and Asia 1 (13.5%) seen in some of the cattle sampled. The broad serotype diversity observed in cattle further reinforces their role as key amplifiers and reservoirs of FMD, a pattern also described by Arzt et al. (\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e). This reservoir potential not only increases the risk of cross-species transmission but may also drive the emergence of novel recombinant strains. Our study supports a couple of other reports on multiple co-infections of various FMD serotypes in clinically and sub clinically infected animals (Fomenky et al., \\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e; Wungak et al., \\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e2017\\u003c/span\\u003e), showing that the multivalent vaccination against different serotypes is indeed needed. The differences in serotype distribution and co-infection patterns seen across species and geographical regions indicate complex transmission patterns that need to be studied in detail. Furthermore, animals in poor body condition scores and those that were unhealthy showed similar trends of serotype co-infection patterns, with unhealthy animals and those with poor body scores showing combination of \\u0026ldquo;O and Asia 1\\u0026rdquo;, and \\u0026ldquo;SAT 2 and Asia 1\\u0026rdquo;. This suggests that compromised immunity, possibly due to malnutrition or other conditions, may increase susceptibility not just to infection, but to specific types of serotype combinations. The extension of the studies to co-infections also contributes to the understanding of the interactions between serotypes, which remains a relatively under-researched subject. In addition, the presence of serotype co-infections underscores the need for multivalent vaccines to address the dominant strains effectively. Altogether, the observed species-specific, geographic, and health-related variations in co-infection patterns indicate that a uniform, one-size-fits-all vaccination strategy is unlikely to be effective. Instead, tailored interventions that account for the dominant serotype pairings within each region and animal population are essential for efficient control.\\u003c/p\\u003e\\u003cp\\u003eThe practical applications of our study are that it provides evidence that more specific preventive efforts should be designed for particular species and areas. There is thus the need to prioritise the high-risk regions, which include the North-Central and the South-East in terms of surveillance and vaccination. On the same note, it is also necessary to note that better nutrition and health care of livestock can also minimise vulnerability to FMD. Our study went further to highlight specific serotype co-infection dominant in different species, geographical locations and unhealthy animals. These insights also inform policy makers how to develop sound strategies, for instance, improving the coverage of the vaccines to include the circulating serotypes, or reconsidering the measures put in place for border control in light of the actual epidemiology of the region. In a theoretical sense, the study opens up a new approach to the existing models of FMD epidemiology by including species susceptibility, health status and regional variations together in one study. It goes beyond single species or single serotype evaluations and provides a broader perspective on the disease dynamics. Altogether, the outcome of the present study can provide useful information on the current situation, risk factors concerning FMD infection, affected species, geography, health effects, and serotypes. Our results therefore hold important implications for disease management and control measures, highlighting the need for context-specific approaches in the fight against FMD. Through targeting high-risk groups, enhancing animal health, and improving vaccination strategies, policymakers and stakeholders can ensure that the impact of FMD is minimised and communities\\u0026rsquo; welfare, livestock farmers livelihood and national food security are protected. Although the current study provides useful information regarding the epidemiological aspects of FMD, the following limitations have to be recognised in order to avoid misinterpretation of the results. One limitation concerns the imbalance of sample size across species with cattle having the highest representation in the sample. Also, the body condition scoring was subjective, which could hinder an empirical comparability of health status. However, these limitations do not reduce the usefulness of the study for the advancement of FMD research.\\u003c/p\\u003e\\u003cp\\u003eIn conclusion, we found that the health and nutritional state of animals influenced their susceptibility to infection because animals with poor health conditions showed more seropositivity with severity of viral infections involving multiple serotypes. Improved management practices which focus on nutrition and animal welfare are critical elements in FMD prevention. The polyvalent vaccination is required to protect livestock against the dominant serotypes. Further, improved surveillance systems and regional vaccination strategies for cattle with greater risks of exposure is needed. Since the serological profiles of other animals in this study mirrors what is observed in cattle, this could infer the possibility of transmission across several host species in shared ecosystems hence the need to enforce control measures in other species to fully control the spread of FMD in Nigeria. This study highlights several directions for future research to deepen understanding and improve control of Foot-and-Mouth Disease (FMD). A priority is expanding sample sizes and ensuring balanced species representation, particularly including underrepresented regions, to enhance cross-species and geographical comparisons. Longitudinal studies are also essential for tracking changes in FMD prevalence, serotype distribution, and co-infections over time. Further investigation into molecular and genetic factors could uncover species-specific susceptibility and resistance traits, while research on environmental, trade-related, and management practices, especially in the light of unexpected findings like the limited role of border proximity, can help clarify complex regional dynamics. Additional research should focus on evaluating the impact of targeted health and nutrition interventions on FMD susceptibility, given the strong associations observed between poor condition and infection. Vaccine development also warrants attention, particularly the need for effective multi-serotype formulations to address the widespread presence of serotype O and frequent co-infections. Unanswered questions regarding regional variability in serotype distribution and the ecological and genetic drivers of disease patterns present valuable opportunities for hypothesis-driven studies. Collectively, these research avenues can build on current findings to inform more targeted, effective, and sustainable FMD control strategies.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eEthics Approval and Consent to Participate\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eEthical approval was obtained from the Ethical Review Committee of the National Veterinary Research Institute (NVRI), Vom, Nigeria with reference number AEC/02/148/24. All participants were provided with detailed information about the study and they gave written informed consent before participation.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConsent for Publication\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eAll the farmers that participated in this study and allowed their animals to be recruited for this study gave written informed consent for the publication of anonymized data and findings for this study. No personally identifiable information is disclosed in this publication.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAvailability of Data and Materials\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe dataset generated during this study are available online in the Harvard Dataverse repository and can be accessed using this link \\u0026ndash; https://doi.org/10.7910/DVN/NYPX2S\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCompeting Interests\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors of this paper declare that they have no competing interests.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFunding\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThere project was supported by Arpexas (Scotland) Limited, United Kingdom.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAuthors Contribution\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eA.E.S. has made substantial contributions to the conception and design of the work, the acquisition, analysis, and interpretation of data, has drafted the work and approved the submitted version, and has agreed both to be personally accountable for the author\\u0026apos;s own contributions and to ensure that questions related to the accuracy or integrity of any part of the work.\\u003c/p\\u003e\\n\\u003cp\\u003eA.F. has substantively revised the work, approved the submitted version and has agreed both to be personally accountable for the author\\u0026apos;s own contributions and to ensure that questions related to the accuracy or integrity of any part of the work\\u003c/p\\u003e\\n\\u003cp\\u003eA.P has substantively revised the work and approved the submitted version and has agreed both to be personally accountable for the author\\u0026apos;s own contributions and to ensure that questions related to the accuracy or integrity of any part of the work.\\u003c/p\\u003e\\n\\u003cp\\u003eA.B.O has substantively revised the work and approved the submitted version and has agreed both to be personally accountable for the author\\u0026apos;s own contributions and to ensure that questions related to the accuracy or integrity of any part of the work.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAcknowledgment\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eNot applicable\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n\\u003cli\\u003eAbdela, N. 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Cross border movements of animals and animal products and their relevance to the epidemiology of animal diseases in africa. OIE Regional Commission. Retrieved from https://www.woah.org/app/uploads/2021/03/2015-afr2-bouslikhane-a.pdf\\u003c/li\\u003e\\n\\u003cli\\u003eBLANCO, E., ROMERO, L. J., EL HARRACH, M., and S\\u0026Aacute;NCHEZ-VIZCA\\u0026Iacute;NO, J. M. 2002: Serological evidence of FMD subclinical infection in sheep population during the 1999 epidemic in Morocco. Veterinary Microbiology, 85(1), 13\\u0026ndash;21.\\u003c/li\\u003e\\n\\u003cli\\u003eDohoo, I., W. Martin, and H. Stryhn. 2003. Veterinary Epidemiologic Research. Charlottetown, PE, Canada: Atlantic Veterinary College\\u003c/li\\u003e\\n\\u003cli\\u003eEhizibolo, D. O., Perez, A., Carrillo, C., Pauszek, S. J., Alkhamis, M. A., Ajogi, I., Umoh, J. U., Kazeem, H. M., Ehizibolo, P. O., Fabian, A., Berninger, M. Lou, Moran, K., Rodriguez, L. L., \\u0026amp; Metwally, S. (2013). Epidemiological Analysis, Serological Prevalence and Genotypic Analysis of Foot-and-Mouth Disease in Nigeria 2008-2009. \\u003cem\\u003eTransboundary and Emerging Diseases\\u003c/em\\u003e, \\u003cem\\u003e61\\u003c/em\\u003e, 500\\u0026ndash;510. https://doi.org/10.1111/tbed.12054\\u003c/li\\u003e\\n\\u003cli\\u003eEzeokoli, C.D., Abegunde A., Umoh, J.U. and Addo, P.B. (1988). Epidemiology of FMD in Nigeria cattle. Rev. Sci. Off. Int. Epiz., 10(1):485-488.\\u003c/li\\u003e\\n\\u003cli\\u003eFAO (2021). Foot and mouth disease. Quarterly report, October\\u0026ndash;December 2021. Rome. \\u003c/li\\u003e\\n\\u003cli\\u003eFood and Agriculture Organization (2024). FMD: Differential diagnosis in cattle. Retrieved from https://openknowledge.fao.org/server/api/core/bitstreams/a131e390-c9da-4220-8287-ac46c553c381/content\\u003c/li\\u003e\\n\\u003cli\\u003eFood and Agriculture Organization (2025). Foot-and-mouth disease. Retrieved from https://www.fao.org/animal-health/animal-diseases/foot-and-mouth-disease/en\\u003c/li\\u003e\\n\\u003cli\\u003eFERRIS, N. P., and DONALDSON, A. I. 1992: The World Reference Laboratory for Foot and Mouth Disease: a review of thirty-three years of activity (1958-1991). Revue Scientifique et Technique (International Office of Epizootics), 11(3), 657\\u0026ndash;684.\\u003c/li\\u003e\\n\\u003cli\\u003eFomenky, B., Wungak, Y. S., Ehizibolo, D. O., Sada, A., Oyekan, O. A., Inuwa, B., Anyika, K. C., Nfon, C., \\u0026amp; Ularamu, G. H. (2023). Bovine Sero- surveillance of Foot- and \\u0026ndash; Mouth Disease in Four States in Nigeria. \\u003cem\\u003eJournal of Veterinary and Biomedical Sciences\\u003c/em\\u003e, \\u003cem\\u003e5\\u003c/em\\u003e, 24\\u0026ndash;33. https://doi.org/10.36108/jvbs/3202.50.0140\\u003c/li\\u003e\\n\\u003cli\\u003eGRUBMAN, M. J. and BAXT, B. 2004: Foot-and-mouth disease. Clin Microbiol Rev, 17(2), 465\\u0026ndash; 493.\\u003c/li\\u003e\\n\\u003cli\\u003eJamal SM, Shah SI, Ali Q, Mehmood A, Afzal M, Afzal M, Dekker A (2013). Proper Quality Control of Formulated Foot\\u0026ndash;and\\u0026ndash;Mouth Disease Vaccines in Countries with Prophylactic Vaccination is Necessary. Transbound Emerg Dis. doi: 10.1111/tbed.12051\\u003c/li\\u003e\\n\\u003cli\\u003eKnowles N.J. \\u0026amp; Samuel A.R. (2003). \\u0026ndash; Molecular epidemiology of foot-and-mouth disease virus. \\u003cem\\u003eVirus Res.\\u003c/em\\u003e, \\u003cstrong\\u003e91 \\u003c/strong\\u003e(1), 65\\u0026ndash;80. doi:10.1016/S0168-1702(02)00260-5.\\u003c/li\\u003e\\n\\u003cli\\u003eLazarus, D., Schielen, W. J. G., Wungak, Y. S., Kwange, D., \\u0026amp; Fasina, F. O. (2012). \\u003cem\\u003eSero-epidemiology of foot-and-mouth disease in some Border States of Nigeria\\u003c/em\\u003e. \\u003cem\\u003e6\\u003c/em\\u003e. https://doi.org/10.5897/ajmr11.1026\\u003c/li\\u003e\\n\\u003cli\\u003eLibeau J. Foot-and-mouth disease in Africa south of the Sahara the present situation. Bulletin of Epizootic Diseases in Africa. 1960;8:90\\u0026ndash;104. https://www.cabidigitallibrary.org/doi/full/10.5555/19612200093\\u003c/li\\u003e\\n\\u003cli\\u003eNaveed, A. (2018). Foot-and-Mouth Disease: A Strategic Analysis for the Control of Disease. \\u003cem\\u003eVaccines \\u0026amp; Vaccination Open Access\\u003c/em\\u003e, \\u003cem\\u003e3\\u003c/em\\u003e. https://doi.org/10.23880/vvoa-16000125\\u003c/li\\u003e\\n\\u003cli\\u003eOIE, 2021. FAO and OIE continue to support the control of foot-and-mouth disease in West Africa. Available on https://www.woah.org/en/disease/foot-and-mouth-disease/ (Accessed on 13th January, 2024)\\u003c/li\\u003e\\n\\u003cli\\u003eOlabode, O.H., Kazeem, H.M., Raji, M.A., Ibrahim, N.D.2014.Participatory appraisal of Foot and Mouth disease outbreaks in Ilesha Baruba, Kwara state Nigeria. Alexandria J. Vet. Sci. 40: 132-138\\u003c/li\\u003e\\n\\u003cli\\u003eOyewusi IK, Talabi AO. Control strategies for foot and mouth disease with particular reference to Nigeria. Afr J Livest Ext 2015; 15(1): 9-17.\\u003c/li\\u003e\\n\\u003cli\\u003eRoeder P.L. \\u0026amp; Knowles N.J. (2008). \\u0026ndash; Foot-and-mouth disease virus type C situation: the first target for eradication? \\u003cem\\u003eIn\\u003c/em\\u003e Report of the Session of the Research Group of the Standing Technical Committee of EUFMD, Erice, Italy, 14\\u0026ndash;17 October, Appendix 7. Available at: www.fao.org/ag/againfo/commissions/docs/research_group/erice/APPENDIX_07.pdf\\u003c/li\\u003e\\n\\u003cli\\u003eRUECKERT, R. R. 1990: Picornaviruses and their replication. In: Fields BN et Al, Eds. Fields Virology. 2nd Edition. Raven Press, New York, 507\\u0026ndash;548.\\u003c/li\\u003e\\n\\u003cli\\u003eThrusfield, M., 2018. Veterinary epidemiology, 4th ed. John Wiley \\u0026amp; Sons\\u003c/li\\u003e\\n\\u003cli\\u003eUlaramu, H., Lefebvre, D., Haegeman, A., Wungak, Y. S., Ehizibolo, D. O., Lazarus, D. D., De, R., \\u0026amp; Clercq, K. De. (2020). Complex Circulation of Foot-and-Mouth Disease Virus in Cattle in Nigeria. \\u003cem\\u003eFrontiers in Veterinary Science\\u003c/em\\u003e, \\u003cem\\u003e7\\u003c/em\\u003e. https://doi.org/10.3389/fvets.2020.00466\\u003c/li\\u003e\\n\\u003cli\\u003eWoldemariyam, F.T.; De Vleeschauwer, A.; Hundessa, N.; Muluneh, A. Risk Factor Assessment, Sero-Prevalence, and Genotyping of the Virus that Causes Foot-and-Mouth Disease on Commercial Farms in Ethiopia from October 2018 to February 2020. Agriculture 2022,12, 49\\u003c/li\\u003e\\n\\u003cli\\u003eWungak, Y. S., Ishola, O. O., Olugasa, B. O., Lazarus, D. D., Ehizibolo, D. O., \\u0026amp; Ularamu, H. G. (2017). Spatial pattern of foot-and-mouth disease virus serotypes in North Central Nigeria. \\u003cem\\u003eVeterinary World\\u003c/em\\u003e, \\u003cem\\u003e10\\u003c/em\\u003e, 450\\u0026ndash;456. https://doi.org/10.14202/vetworld.2017.450-456\\u003c/li\\u003e\\n\\u003cli\\u003eWungak, Y. S., Olugasa, B. O., Ishola, O. O., Lazarus, D. D., \\u0026amp; Ularamu, G. H. (2016). Foot-and-mouth disease (FMD) prevalence and exposure factors associated with seropositivity of cattle in north-central, Nigeria. \\u003cem\\u003eAfrican Journal of Biotechnology\\u003c/em\\u003e, \\u003cem\\u003e15\\u003c/em\\u003e, 1224\\u0026ndash;1232. https://doi.org/10.5897/ajb2016.15332\\u003c/li\\u003e\\n\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":true,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"bmc-microbiology\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"mcro\",\"sideBox\":\"Learn more about [BMC Microbiology](http://bmcmicrobiol.biomedcentral.com/)\",\"snPcode\":\"\",\"submissionUrl\":\"https://www.editorialmanager.com/mcro\",\"title\":\"BMC Microbiology\",\"twitterHandle\":\"#bmcmicrobiology\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true},\"keywords\":\"\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-7437182/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-7437182/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003e\\u003cstrong\\u003eIntroduction: \\u003c/strong\\u003eFoot-and-mouth disease (FMD) is a highly contagious viral infection of cloven-hoofed animals that causes substantial economic losses and severe disruptions to agricultural systems globally. It affects animal health and productivity in Nigeria but there is paucity of data across regions and among various animal species. This study determined the seroepidemiology and serotype diversity of the FMD virus (FMDV) among domestic ungulates including cattle, sheep, goats, and pigs, across all geopolitical zones in Nigeria.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eMaterials and methods: \\u003c/strong\\u003e1002 sera were collected from domestic ungulate animals (cattle n=511, sheep n=182, goat n=218 and pigs n=91) and were analyzed using commercial ELISA kits (ID Vet®, France and IZLER®, Italy) to antibody and serotype-specific antibodies to FMD. Metadata on individual species were collected through questionnaire uploaded on Kobocollect containing sociodemographic data, and distribution of FMD in Nigeria.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eResults: \\u003c/strong\\u003eThe study revealed an overall rate of 45.7% for all the various species and regions in Nigeria with specific host prevalence of 69.7% for cattle, 26.9% for sheep, 20.6% for goats, and 8.8% for pigs. Serotype O was the most predominant (74.9%), followed by A (56.3%), SAT 2 (35.8%), Asia 1 (22.9%) and SAT 1 (16.8%). Kaduna had the highest prevalence (88.9%), while Cross River had the lowest (9.1%). Serotype co-infections were prevalent among cattle, with 32% exhibiting multi-serotype infections. Health status and body condition are major determinants of susceptibility, with unhealthy animals being five times more likely to test positive to FMD (OR = 5.479, p \\u0026lt; 0.001).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConclusion: \\u003c/strong\\u003eWe have\\u003cstrong\\u003e \\u003c/strong\\u003esystematically determined FMDV seroprevalence and serotype distribution in various domestic ungulate species across all the geopolitical zones in Nigeria. Our findings highlight the importance of improved surveillance networks to address regional patterns and prevalent serotype clusters. It reinforces the need for developing generic multivalent vaccination plans and provides essential data for national policy to improve livestock healthcare strategies and minimize the burden of FMD in Nigeria.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Seroepidemiology and Serotype Diversity of Foot-and-Mouth Disease Virus Among Domestic Ungulates Across Nigeria\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2025-09-19 10:44:45\",\"doi\":\"10.21203/rs.3.rs-7437182/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"decision\",\"content\":\"Revision requested\",\"date\":\"2025-10-21T11:28:14+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2025-10-16T19:39:58+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"226274287898908410954604391674912526015\",\"date\":\"2025-10-16T18:06:29+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2025-10-07T15:59:13+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2025-09-18T09:36:54+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"302331613389617139300443813813889624668\",\"date\":\"2025-09-15T09:13:11+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"332490696285351315475014500268155748982\",\"date\":\"2025-09-15T04:19:59+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"72266728944530481794352861768551600941\",\"date\":\"2025-09-14T13:02:05+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewersInvited\",\"content\":\"\",\"date\":\"2025-09-12T08:13:57+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorAssigned\",\"content\":\"\",\"date\":\"2025-09-12T07:25:21+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvited\",\"content\":\"\",\"date\":\"2025-09-12T06:22:28+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"checksComplete\",\"content\":\"\",\"date\":\"2025-09-11T10:57:24+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"submitted\",\"content\":\"BMC Microbiology\",\"date\":\"2025-09-11T10:28:33+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"bmc-microbiology\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"mcro\",\"sideBox\":\"Learn more about [BMC Microbiology](http://bmcmicrobiol.biomedcentral.com/)\",\"snPcode\":\"\",\"submissionUrl\":\"https://www.editorialmanager.com/mcro\",\"title\":\"BMC Microbiology\",\"twitterHandle\":\"#bmcmicrobiology\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"ae8373a7-fd6a-4f20-be35-c0ebdc5f44a2\",\"owner\":[],\"postedDate\":\"September 19th, 2025\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"published-in-journal\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2026-03-09T16:08:16+00:00\",\"versionOfRecord\":{\"articleIdentity\":\"rs-7437182\",\"link\":\"https://doi.org/10.1186/s12866-026-04774-6\",\"journal\":{\"identity\":\"bmc-microbiology\",\"isVorOnly\":false,\"title\":\"BMC Microbiology\"},\"publishedOn\":\"2026-03-06 15:58:23\",\"publishedOnDateReadable\":\"March 6th, 2026\"},\"versionCreatedAt\":\"2025-09-19 10:44:45\",\"video\":\"\",\"vorDoi\":\"10.1186/s12866-026-04774-6\",\"vorDoiUrl\":\"https://doi.org/10.1186/s12866-026-04774-6\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-7437182\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-7437182\",\"identity\":\"rs-7437182\",\"version\":[\"v1\"]},\"buildId\":\"8U1c8b4HqxoKbykW_rLl7\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}