Kella Douzouné

Geospatial Health 2025; volume 20:1365 Mapping livestock systems, bovine and caprine diseases in Mayo-Kebbi Ouest Province, Chad Kella Douzouné,1 Joseph Oloukoi,1 Ismaila Toko Imorou,2 Toure Gorgui Ba,3 Derrick Chefor Ymele Demeveng3 African Regional Institute for Geospatial Information Science and Technology (AFRIGIST), Obafemi Awolowo University Campus, Ile-Ife, Nigeria; 2University of Abomey-Calavi, Cotonou, Bénin; 3World Health Organization, Brazzaville, Congo 1 Funding: this study did not receive specific funding from any public, private, or non-profit organization. It was entirely self-funded. om ly on m er Ethical considerations: regulatory approvals and participant consent were secured prior to the study, with formal authorisation granted by the Ministry of Livestock and Animal Production in Chad. The procedural steps undertaken were as follows: the African Regional Institute for Geospatial Information Science and Technology (AFRIGIST), based in Ile-Ife, Nigeria, issued an official letter of introduction for the Ph.D. candidate to the Ministry of Livestock and Animal Production in Chad; upon receiving authorisation from the Ministry, the Ph.D. candidate presented it to the Ministry’s provincial representative. This representative subsequently informed and engaged local stakeholders, including the heads of veterinary sectors and livestock farmers’ associations, to facilitate the mobilization of respondents in the study areas. e Conflicts of interest: the authors declare that they have no conflicts of interest, financial or personal, that could have influenced the content of this article. us Field contributions: the data collection was conducted with the assistance of my sister, Fakolné Kella, and my brother, Hainé Kella. This study aimed to compile an inventory of the main diseases affecting these species in Mayo-Kebbi Ouest Province in Chad. A survey was conducted between 6 May and 7 August 2024 using a cascade data collection method identifying 310 farmers and 19 veterinarians with an average of 10 to 12 years of experience in advising and supporting livestock practices The data collected included socio-professional characteristics of participants, livestock practices, and geospatial information. These data were managed in Excel and analysed with R. The analysis involved descriptive and inferential statistical techniques including binary logistic regression resulting in maps illustrating disease hotspots and livestock systems. Thematic maps, tables and charts with a 5% significance threshold visualised risk areas and associated livestock practices. The results show a predominance of male farmers (91.9%) from 20 different ethnic groups. The livestock systems identified include data on farming divided into extensive (14.8%), mixed (0.3%) and semi-intensive farming (84.8%). On average, farms have 41 cattle and 25 goats. Animal diseases were found to cause 29.5% reduction in herd productivity. Transhumance (p=-) and animal disease incidence (p=0.03) were observed as significant risk factors associated with the abandonment of livestock farming. The main diseases recorded in cattle include contagious bovine pleuropneumonia (11.3%), bovine tuberculosis (2.5%), foot-and-mouth disease (45.0%), bluetongue (1.7%) and disease with symptoms reminiscent of rinderpest (2.5%). For goats, notable diseases include brucellosis (3.8%), lumpy skin disease (19.2%), goat plague (7.9%) and Rift Valley fever (6.3%). These findings confirm the importance of a geospatial epidemiological surveillance tool for monitoring animal diseases in this region. al Key words: animal diseases, transhumance, R, Excel, Mayo-Kebbi Ouest, Chad. Abstract ci Correspondence: Douzouné Kella, African Regional Institute for Geospatial Information Science and Technology (AFRIGIST), Obafemi Awolowo University Campus, Ile-Ife, Nigeria. E-mail:- -c Availability of data and materials: all data used or analyzed in this study can be obtained from the corresponding author upon request. N on Acknowledgements: we extend our deepest gratitude to everyone and every institution that contributed to this study. We are particularly grateful to the livestock farmers of Mayo-Kebbi Ouest province for their invaluable collaboration and availability. We also wish to thank the provincial delegate and veterinary officers for their support in accessing data and facilitating field surveys. Our heartfelt thanks also go to our research team members for their dedication and rigour throughout the data collection process. Received: 11 November 2024. Accepted: 18 December 2024. ©Copyright: the Author(s), 2025 Licensee PAGEPress, Italy Geospatial Health 2025; 20:1365 doi:10.4081/gh- This work is licensed under a Creative Commons AttributionNonCommercial 4.0 International License (CC BY-NC 4.0). Publisher's note: all claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher. [page 26] Introduction Sub-Saharan transhumant farming systems pose significant challenges to veterinary health due to the unique nature of seminomadic livestock-rearing practice. The key problem is infectious diseases with high transmission risk related to movement of livestock mixed herds and shared resources. Geospatial analysis is an essential tool for studying livestock systems and animal diseases in rural areas where data access and health monitoring are often limited. The use of Geographic Information Systems (GIS) facilitates the identification of highrisk areas, location of epidemic hotspots and mapping of livestock practices, which enables the development of more targeted health control strategies. For example, integrating GIS in the surveillance of ‘pest of small ruminants’, also called goat plague, and foot-andmouth disease has facilitated early epidemic detection and [Geospatial Health 2025; 20:1365] Article Materials and Methods Study area description The study was carried out in the Mayo-Kebbi West Province of Chad, which shares borders with Cameroon and other Chad provinces and is characterised by geographic diversity, with major rivers supporting agriculture and livestock. The administrative subdivisions of the province are given in Table 1, and the spatial information shown on a map (Figure 1). The socio-cultural diversity, livestock systems and farming practices in this province lead to health challenges for cattle and goat herders. A survey was carried out from 6 May to 7 August 2024 producing a sample consisting of 310 livestock farmers and 19 veterinarians. Lac Léré on Department ly Table 1. Administrative subdivision of the Mayo-Kebbi Ouest Province, the basis for structuring the study’s spatial analyses. e Mayo-Binder us El-Ouaya Mayo-Dallah Canton (District) Guégo, Biparé, Léré Binder Guelo, Lagon, Bissi Pala, Torrock, Gouin, Gagal, Gouingodom, Lamé Based on the administrative structure effective under the 5th Republic of Chad, as of 4 July 2024. N on -c om m er ci al resource allocation optimisation was successfully applied in Algeria (Dahmani et al., 2022). Similarly, a study in China demonstrated the effectiveness of GIS in epidemic surveillance, increasing responsiveness to health threats (Sun et al., 2016). In a study by Palaniyandi et al. (2016), remote sensing and GIS were used to map vector breeding habitats and monitor epidemic transmission. According to research by Belimenko and Gulyukin (2016), GIS enables the creation of interactive and analytical maps, providing valuable tools for estimating epidemiological risks and understanding the spread of diseases such as anthrax and rabies. This spatial and visual approach offers innovative perspectives for developing more effective control and prevention strategies. Evidence from this research demonstrates the effectiveness of these technologies in identifying areas vulnerable to disease transmission and in prioritising control strategies. However, inherent challenges arise when using GIS, including data collection complexity, statistical method limitations and issues related to spatial precision and data interpretation. Mayo-Kebbi Ouest Province in Chad represents a strategic area for livestock farming, a crucial activity for the national economy. However, it is also a region where transhumance, a traditionnel practice of seasonal livestock migration that increases the risk of pathogen spread. Therefore, this region faces major health challenges due to the high prevalence of diseases primarily affecting cattle and goats. GIS was used to map disease hotspots and livestock systems aiming at the compilation of an inventory of the main veterinary diseases in Mayo-Kebbi Ouest to assist efforts to control them. Figure 1. Map of Mayo-Kebbi Ouest Province in Chad showing the geographic boundaries and main landmarks of the study area. Map created using a shapefile from 1 January 2017. [Geospatial Health 2025; 20:1365] [page 27] Article Data analysis us e on ly The inferential statistical tests used in this study included the chi-square and Fisher’s exact tests, which were employed to analyse associations between qualitative variables. This methodology is frequently adopted in epidemiological research on animal health (Ali et al., 2013). Additionally, binary logistic regression was employed to identify risk factors associated with the abandonment of livestock farming, with a significance level of 5%. This approach facilitates risk assessment by integrating various variables, as demonstrated in research concerning the prevalence of animal diseases and health risks in Africa (Noudeke et al., 2017). A description how the collected information was subjected to binary logistic regression including application of chi-square and Fisher’s exact tests need to be given in a paragraph here, with results provided in tables to be placed in the Results section. The collected data were subjected to analysis using descriptive statistics, including means and standard deviations, to characterise livestock practices and the populations studied. Data were systematically organised and cleaned using Excel 2013, while statistical analyses were conducted with the R software (version 4.3.3). This N on -c om m er ci Participants were selected using systematic census and snowball sampling (Djagba et al., 2020), allowing for a representative sample capturing the socio-cultural diversity and livestock practices in the province. Snowball sampling is a non-probability sampling method, where new units are recruited by other units to form part of the sample. It is a commonly used approach to capture the complexity of pastoral systems in animal health studies (Djagba et al., 2020), was employed. Structured interviews were conducted using KoboToolbox (version 2.024.04), covering socio-professional characteristics, farming practices, health perceptions, and geospatial perspectives. Local translators facilitated data collection to enhance reliability. Data were collected through a questionnaire designed using KoboToolbox, ensuring a structured and reliable collection process. The structured interviews addressed various aspects: i) socio-professional characteristics: age, gender, ethnicity and participants’ experience, key elements to understanding the diversity of actors in livestock farming. This diversity’s influence on livestock practices has been highlighted in a study on goat farming in Togo by Djagba et al. (2020); ii) livestock practices: The surveyed practices encompassed a range of systems, including extensive, mixed or semi-intensive farming, as well as average herd size. This classification is crucial for understanding how each system influences animal health and is in line with Missohou et al. (2016), who report that livestock systems in West Africa directly impact animal health management and disease spread; iii) health data: identified disease types, prevention, treatment strategies and associated risk factors were collected. Gathering this data was essential for identifying the main pathogens affecting animal populations, following studies, such as that by Ali et al. (2013) that is focused on brucellosis health risks in professional settings similar to this study. A description of the socio-professional profile of the region’s livestock farmers (Figure 2, Table 2) aid the understanding of livestock practices, while information on the experience and availability of veterinarians in the province (Table 3) is essential for assessing the technical support provided to livestock farmers. al Data collection Figure 2. Map of survey data collection points among farmers and veterinarians in the province illustrating the geographic coverage of the study. [page 28] [Geospatial Health 2025; 20:1365] Article Results ly Veterinary diseases have a significant impact on herd productivity, and we noted an average reduction of 29.5% in production (Figure 5). Transhumance (p=-) and the incidence of animal diseases (p=0.03) were found to be the major risk factors linked to the abandonment of livestock farming (Figure 6). Diseases observed The diseases recorded among cattle and goats in this study include brucellosis, lumpy skin disease and goat plague. Among cows the main diseases include contagious bovine pleuropneumonia (11.3%), bovine tuberculosis (2.5%), foot-and-mouth disease (45%), bluetongue (1.7%). The most frequently observed diseases in goats include brucellosis (3.8%), lumpy skin disease (19.2%), goat plague (PPR) (7.9%), and Rift Valley fever (6.3%). This sum- m er ci al The results of this study highlight several key characteristics of livestock systems and health challenges in the Mayo-Kebbi Ouest province as illustrated in Figures 3 and 4. In addition, Table 4 provides an overview of the disease types that are common in cattle and goats, which assists the identification of species-specific diseases and their biosecurity implications. Impact of diseases on productivity on Geospatial data were analysed using the R programming language along with Excel for data management, with the objective of mapping the distribution of livestock systems and epidemic hotspots. This combination of tools allows for a detailed and accurate visualisation of high-risk areas, as demonstrated in various studies employing similar approaches for rural health surveillance (Dahmani et al., 2022). Thematic maps were designed to visually illustrate high-risk areas and factors contributing to the abandonment of livestock farming. The effectiveness of GIS in identifying and managing epidemic-prone zones has been well documented in comparable contexts, notably in China, where similar geospatial systems have improved responsiveness to animal disease outbreaks (Sun et al., 2016). Please describe briefly how your data were calculated in the GIS environment here. The majority of farmers, accounting for 91.9%, are men from 20 different ethnic groups. Veterinarians participating in the survey reported an average of 10 to 12 years of professional experience, which is considered crucial for managing rural health risks. In this province, livestock systems are primarily characterised by a semiintensive approach, and were found to amount to 84.8% of the observed practices, while extensive farming constituted 14.8% and the mixed system accounts only 0.3%. The farms in the study area were calculated to hold an average of 41 cattle and 25 goats, although these figures varied depending on the farming system and local constraints. e Spatial analysis tools Characteristics of farmers and livestock systems us approach aligns with methodological recommendations for data analysis in animal health contexts, where statistical rigor is essential to obtain reliable results (Mazzucato et al., 2023). Table 2. Socio-professional characteristics of livestock farmers (n = 310). Parameter Gender Female Male -c on N Ethnicity Arabe Bororo Caro Foulbé Haoussa Kera Lame Lélé Mbaïnawa Mbaye moisala Mboum Moundang Nabouzi Ngambaye Niellim de Sarah Peuhl Sime PV Tikalga Toupouri Zimé 2 98 Department Lac Léré (%) Mayo-Binder (%) om El-Ouaya (%) Experience in farming (years) SD, standard deviation; mean± SD. 100 2 2 2 8 33 100 100 11 82 2 2 20.72±9.23* - - - 9 0.5 17 1 6 35.14±16.69* [Geospatial Health 2025; 20:1365] Mean±SD 10 90 0.5 0.5 52 28 6 26.83±17.35* Mayo-Dallah (%) 3 8 23.26±16.90* 23.32±16* [page 29] us e on ly Article N on -c om m er ci al Figure 3. Map showing the spatial distribution of livestock systems in Mayo-Kebbi Ouest Province enabling a geographical view of livestock practices. Figure 4. Map of the geographic distribution of cattle and goats in Mayo-Kebbi Ouest Province identifying areas of high concentration for each species. [page 30] [Geospatial Health 2025; 20:1365] us e on ly Article m er ci al Figure 5. Map of geographical areas where herders have ceased livestock activities allowing for an analysis of causes linked to health and economic risks. Table 3. Veterinarian characteristics. Parameter om -c on Ethnicity Foulbé Gourane Moundang Zimé N Gender Female Male El-Ouaya (%) Experience in support of livestock farmers (2024) Availability of veterinary clinics (%) Yes No Departement Lac Léré (%) Mayo-Binder (%) 25 75 75 25 Viral 50 100 - 14 57 29 - 100 10.25±9* 12±10* 11±0* 9±8.93* 10.12±7.92* 100 67 33 100 100 94 6 Table 4. Types of bovine and caprine diseases. Bacterial 100 100 Table based on 19 veterinarians; SD= standard deviation; *mean± SD. Type of disease 33 67 Mean Mayo-Dallah (%) Cattle disease Contagious bovine pleuropneumonia (11.3%) Bovine tuberculosis (2.5%) Foot-and-mouth disease (45.0%) Bluetongue (1.7%) Suspected rinderpest (2.5%)* Goat disease Brucellosis (3.8%) Lumpy skin disease (19.2%) Goat plague (7.9%) Rift Valley fever (6.3%) *Although rinderpest has been eradicated worldwide, respondents reported clinical signs consistent with the disease. Due to logistical constraints, laboratory confirmation was not conducted. [Geospatial Health 2025; 20:1365] [page 31] Article Discussion These findings align with observations in comparable regions of West Africa, where transhumance practices, combined with a lack of biosecurity measures, heighten the health risks faced by herds (Missohou et al., 2016; Meybeck et al., 2017). Integrating GIS and appropriate biosecurity measures could significantly enhance the management of animal diseases and reduce associated economic losses. For example, similar initiatives implemented in Algeria have shown that GIS can facilitate a more efficient alloca- on -c om m er ci al us e on ly mary of transmission modes and symptoms for each animal disease is summarized in Table 5, which should aid identifying health risks. Figure 7 highlights high-risk areas for health interventions and the epidemic risk map (Figure 8) illustrates areas of high disease prevalence in Mayo-Kebbi Ouest province, derived from geospatial data. This map highlights epidemic hotspots particularly concentrated in the Pala and Torrock areas, where risk densities reach peak levels. N Figure 6. Epidemic risk map indicating high-density disease areas in the region. Table 5. Modes of transmission and symptoms of recorded animal diseases. Veterinary disease Brucellosis Lumpy Skin disease Foot-and-Mouth disease Rift Valley fever Bluetongue Transmission mode Contaminated water or feed ingestion, animal cohabitation, uncontrolled animal movement High prevalence of vector arthropods (flies and ticks), high animal population density Transmission between infected and healthy animals via saliva, milk, or blood; lack of biosecurity measures Favourable climatic conditions for mosquitoes, movements of infected animals Symptom Abortions, genital infections, joint problems Skin nodules, ulcers, respiratory issues Vesicular lesions in mouth and on feet, lameness, reduced production Fever, abortions, neonatal infections Presence of competent vectors (Culicoides midges) Mouth ulcers, swelling, respiratory issues Goat plague (PPR) Contact with contaminated objects like feeders or waterers Bovine tuberculosis Transmission through respiratory and oral routes Respiratory issues, gastrointestinal disorders, mouth ulcers Contagious bovine pleuropneumonia [page 32] Inhalation of respiratory droplets from infected animals [Geospatial Health 2025; 20:1365] Fever, laboured breathing, cough, nasal discharge Lung infections, potential transmission to humans Article sive and semi-intensive livestock systems (Missohou et al., 2016). The results regarding farmer and veterinarian profiling show that both have long professional experience, which is crucial for the successful management of rural health risks. It emphasises the crucial role of knowledge transfer in livestock practices and animal health. Integrating educational and training programmes could improve the implementation of health practices and risk management, as recommended in other livestock contexts in West Africa om m er ci al us e on ly tion of resources in epidemic management (Dahmani et al., 2022). Moreover, the use of GIS for real-time epidemic hotspot mapping in China has increased responsiveness to health crises, illustrating its potential to enhance the resilience of livestock systems in analogous contexts (Sun et al., 2016). This underscores the importance of reinforcing biosecurity practices, especially in high-risk areas. Comparable research has shown that proximity and lack of biosecurity measures increase disease transmission risks within inten- N on -c Figure 7. Geographic distribution of veterinary diseases identified in Mayo-Kebbi Ouest Province. Figure 8. Parameter distribution of diagnostic criteria. [Geospatial Health 2025; 20:1365] [page 33] Article The importance of a geospatial surveillance system Implementing a Geographic Information System (GIS) for animal disease monitoring could provide an effective response to the health challenges identified in this study. Mapping epidemic hotspots and livestock systems facilitates a more strategic allocation of resources and interventions, enabling the identification of priority areas. Comparative research shows that integrating GIS in livestock practices significantly improves resilience to health crises and promotes the sustainability of livestock systems (Dahmani et al., 2022). For instance, in Algeria, GIS use has facilitated more rigorous monitoring of diseases such as foot-andmouth disease and Peste des Petits Ruminants (PPR), thereby reducing epidemic spread in rural areas (Dahmani et al., 2022). Similarly, in China, real-time mapping of epidemic hotspots using GIS has enhanced responsiveness to health crises, illustrating its potential to strengthen livestock system resilience in similar contexts (Sun et al., 2016). ly Analysis and interpretation of epidemic risk results al us e on The epidemic risk map highlights a significant concentration of animal diseases around the areas of Pala and Torrock. This high density is attributed to the proximity of semi-intensive farming systems and transhumance movements, which facilitate disease transmission between herds. Implementing a geospatial monitoring system would therefore be essential to enhance the responsiveness of health authorities to epidemics in these high-risk areas. Similar studies have shown that integrating geospatial monitoring systems improves epidemic response in regions where extensive farming and transhumance are common, thereby reducing economic and health losses (Missohou et al., 2016). These findings indicate priority areas for health interventions and the application of enhanced biosecurity measures. Integrating GIS and molecular diagnostics is critical for enhancing disease monitoring and biosecurity in high-risk areas -c om m er ci (Djagba et al., 2020). With regard to the livestock systems, found to be primarily characterised by a semi-intensive approach is representative of many sub-Saharan African regions, where herders choose this model to balance productivity with sustainable resource management (Missohou et al., 2016). Although an average of the farms held around 65 animals, there was a great variation as it is in other Sahel regions, due to socio-economic and environmental factors, as noted in the study by Gnanda et al. (2016) in Burkina Faso. With respect to the impact of diseases on productivity, our observation of 29.5% reduction in production reflects figures widely documented in livestock farming contexts in West Africa, where diseases limit animal growth and productivity, directly affecting farmers’ incomes (Missohou et al., 2016). In addition, our finding that transhumance and the incidence of veterinary diseases as the main risk factors correspond to other African reports as observed in similar studies on pastoral practices in the Sahel (Meybeck et al., 2017). These factors increase losses and discourage herders, contributing to a reduction in the sustainability of livestock farming (Noudeke et al., 2017). The disease panorama observed in this study shares notable similarities with observations in other West African countries, where high prevalence rates of brucellosis in cattle are well-documented (Noudeke et al., 2017). Furthermore, the high PPR rates observed here align with those reported in the semi-intensive livestock systems of the region (Ali et al., 2013). It is of interest that the same diseases observed in this study have also been reported in other regional studies, particularly in extensive farming contexts where health control is limited (Hunter et al., 2006). Of great importance is the fact that experienced veterinarians have reported symptoms reminiscent of rinderpest in 2.5% of the cases. When this disease was erradicated in 2011, it was the first time for a veterinary disease. Rinderpest, also known as cattle plague, was a highly contagious viral disease affecting cattle with devastating impacts on livestock and agricultural economies. For this reason, this finding will be reported and the cases further investigated. The high prevalence rates of goat plague and brucellosis in goats correspond to regional trends in sub-Saharan Africa, where these diseases are a significant obstacle to goat productivity (Missohou et al., 2016). on Factors influencing abandonment of livestock farming N Transhumance practices in the region are identified as a major risk factor for animal disease transmission due to frequent contacts between herds from different geographical areas. This phenomenon has been observed in other West African regions, where cross-border herd movements play a significant role in pathogen spread (Meybeck et al., 2017). Additionally, the lack of biosecurity measures in transhumance zones exacerbates these risks, underscoring the need for targeted interventions to enhance biosecurity. Studies indicate that biosecurity strategies are essential to limit disease transmission in high-transhumance contexts (Missohou et al., 2016). While essential for managing natural resources, transhumance exposes animals to infected areas, increasing the risk of cross-infections. Our results indicate that herders practising transhumance are more likely to abandon livestock farming due to the economic losses associated with epidemics. To address this issue, integrating mobile surveillance strategies appears crucial for limiting pathogen spread in transhumance areas. Similar surveillance systems have proven effective in enhancing responsiveness and preventing epidemics in rural areas of China, as demonstrated by Sun et al. (2016) [page 34] Conclusion This research has shed light on the structural and health challenges faced by the livestock sector in Mayo-Kebbi Ouest province, Chad. The analyses reveal that transhumance practices, the concentration of semi-intensive livestock systems, and the absence of appropriate epidemiological surveillance contribute to the increased vulnerability of livestock systems in this region. To address the identified challenges, it is recommended to strengthen farmers’ biosecurity skills and promote sustainable livestock practices through training and awareness programmes. Cooperation between health authorities and farmers is essential to establish an effective epidemiological surveillance system, which could have a significant impact on the sustainability of the livestock sector in the province. Recommandations Biosecurity training for farmers should be intensified and promote the adoption of sustainable livestock practices in line with strategies implemented in comparable contexts in sub-Saharan Africa, where training initiatives have proven effective in reducing animal epidemics (Missohou et al., 2016; Djagba et al., 2020; Dahmani et al., 2022). The results of this study highlight the fundamental importance [Geospatial Health 2025; 20:1365] Article ly on om m er ci al Ali S, Ali Q, Melzer F, Khan I, Akhter S, Neubauer H, Jamal SM, 2014. 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Herd mobility exposes animals to cross-infection risks; therefore, it is essential to integrate suitable biosecurity strategies in transhumance zones, in line with recommendations from studies on rural areas in sub-Saharan Africa (Meybeck et al., 2017). on N Résumé -c Online supplementary materials: [Geospatial Health 2025; 20:1365] [page 35]