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. 2025 Jun 30;15(6):2703–2714. doi: 10.5455/OVJ.2025.v15.i6.39

Spatiotemporal analysis of the re-emerging foot and mouth disease outbreak in Central Java, Indonesia

Aldi Salman 1,2,*, Heru Susetya 3, Soedarmanto Indarjulianto 4, Agung Budiyanto 5
PMCID: PMC12451135  PMID: 40989620

Abstract

Background:

Foot-and-mouth disease (FMD) is a highly contagious transboundary animal disease that severely impacts livestock health, productivity, and trade. After FMD was free for over 3 decades, Indonesia experienced a resurgence of the disease in May 2022, with Central Java among the affected regions. The outbreak exposed weaknesses in biosecurity, surveillance, and response mechanisms, necessitating a comprehensive analysis of the spread and control efforts.

Aim:

This study aims to assess the spatiotemporal dynamics of the FMD outbreak in Central Java, evaluating the effectiveness of control measures, including vaccination, movement restrictions, and biosecurity enforcement, to inform future disease management strategies.

Methods:

This study utilized Geographic Information System tools to analyze the spatial patterns of FMD cases using outbreak data from iSIKHNAS. Temporal trends were examined over a 35-week period to identify peak transmission periods. Data analysis was conducted using QGIS 3.34.12 and Microsoft Excel to track the spread and impact of the control interventions.

Results:

The first FMD case in Central Java was reported in Boyolali Regency on May 8, 2022. The outbreak rapidly spread, affecting all regencies within 41 days. By the end of 2022, a total of 8,473 outbreaks involving 65,445 livestock were recorded. Spatial analysis revealed significant clusters of dairy and beef cattle linked to high animal trade activity. Temporal analysis showed rapid case escalation with peaks in weeks 5 and 11, followed by a decline after the intervention measures. Emergency vaccination commenced 7 weeks post-outbreak, contributing to case reduction but facing challenges in distribution and timely execution. The spatial relationship between cattle population density and FMD transmission risk at the subdistrict level, visualized through bivariate mapping.

Conclusion:

The 2022 FMD outbreak in Central Java affected over 65,000 livestock, with cases peaking in week 11 before declining due to emergency vaccination and movement restrictions. Strengthened biosecurity measures and earlier interventions are critical for effective control. Future research should focus on spatial risk factors and evaluate intervention strategies to improve outbreak preparedness and response.

Keywords: Foot-and-mouth-disease, Reemerging, Spatial, Temporal, Central Java

Introduction

Foot-and-mouth disease (FMD) is a highly contagious transboundary animal disease affecting cloven-hoofed livestock, including cattle, buffalo, pigs, sheep, and goats (Admassu et al., 2019; Calkins and Scasta, 2020). Caused by the foot-and-mouth-disease virus, the disease significantly impacts livestock health, productivity, and trade (Knight-Jones et al., 2017).

Indonesia has been historically free from FMD for over 3 decades after successfully eradicating the disease in 1986 (Chen et al., 2022). However, in May 2022, FMD re-emerged in several provinces, including Central Java, posing a major challenge to the country’s animal health system (Dede et al., 2025). The resurgence of FMD has highlighted vulnerabilities in biosecurity measures, surveillance systems, and outbreak response strategies (Lase et al., 2024).

Clinically, FMD manifests as high fever, excessive salivation, lameness, and vesicular lesions on the tongue, lips, gums, hooves, and teats (Mohamad and Shaari, 2022). These symptoms lead to production losses due to reduced weight gain, decreased milk yield, and secondary bacterial infections (Rushton and Knight-Jones, 2012). While adult livestock typically recover, young animals—especially calves, lambs, and piglets—are at higher risk of fatal myocarditis (Admassu et al., 2019).

Following the 2022 outbreak, Indonesia’s Animal Health System implemented several response measures, including movement restrictions, vaccination campaigns, culling of infected animals, and public awareness programs. The government launched a nationwide FMD vaccination program, prioritizing high-risk areas, such as Central Java (Antari et al., 2024). Moreover, veterinary authorities have strengthened biosecurity protocols at farms, markets, and transport hubs (Khairullah et al., 2024). However, challenges remain in ensuring widespread vaccination coverage, enforcing movement restrictions, and maintaining early detection systems (Lase et al., 2024). Given the transboundary nature of FMD and its rapid spread, spatiotemporal analysis is crucial for understanding the dynamics of outbreaks and assessing the effectiveness of control measures (Dede et al., 2025). This study employed geospatial mapping techniques, epidemiological modeling, and outbreak data analysis to evaluate how the Animal Health System in Central Java has responded to recent FMD outbreaks. By identifying spatial clusters, temporal trends, and critical risk factors, this research highlights weaknesses in current surveillance and response mechanisms (Ak et al., 2024). The findings will contribute to developing more effective disease management strategies, supporting evidence-based policymaking, and enhancing regional preparedness for future outbreaks of FMD and other transboundary animal diseases (Ashani et al., 2023).

Materials and Methods

Research area

The study area was in Central Java Province, Indonesia. Central Java has 35 administrative units, including 29 regencies and six cities, as the analysis unit (Fig. 1). The topography of Central Java Province is diverse, including mountains, highlands, lowlands, and coasts, with a total area of 32,800.69 km², or about 28.94% of the area of the island of Java. Central Java is a major beef cattle production center in Indonesia, with a population of 1.9 million, ranking second nationally after East Java (Utomo et al., 2023).

Figure 1. Fig. 1. The location of the FMD research is Central Java.

Figure 1.

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Data collection

Geographic Information System data were obtained from the Geospatial Information Agency using the September 2023 edition of the village/subdistrict administrative boundary geodatabase, available on the website geoportal.big.go.id.

FMD outbreak data were obtained from official records downloaded from iSIKHNAS, an integrated national animal health information system application. Outbreak data were obtained from real-time reports from the village fields. The data include the number of cases, animal species (cattle and goats/sheep), outbreak dates, and locations. The data were verified by a veterinary authority officer and summarized and presented in weeks.

Data analysis

The spatial analysis tools available in QGIS software, version 3.34.12-Prizren, available on QGIS.org, licensed under GNU GPLv2+. Spatial-temporal analysis was performed based on weekly outbreak reports using the Kernel Density Estimation (KDE) tool available in QGIS. This method allowed the identification of disease hotspots by generating a continuous surface of outbreak density, which helps assess areas with higher transmission risks.

The outbreak information was compiled and managed using Microsoft Excel 2013 (version 15.0.4420.1017). Both outbreak and case data were organized and presented according to the epidemiological week. An outbreak was defined as the occurrence of disease cases that exceeded the expected number within a specific population, location, or timeframe. The case number is the total count of individual infected animals within a given outbreak or during a defined period (APHIS, 2024).

The FMD transmission risk level was analyzed using a bivariate map based on two key variables: vaccination rate and outbreak rate. The outbreak rate was calculated as the number of cases per 1,000 population, whereas the vaccination rate was expressed as the percentage of the population vaccinated. Each variable is classified into three categories—low, medium, and high—resulting in nine possible combinations. These combinations are then mapped using a categorized symbology with a bivariate color scheme, allowing for a clear visual representation of areas with varying levels of risk based on the interaction between outbreak severity and vaccination coverage.

Ethical approval

Not needed for this study.

Results

Indonesia has been declared a disease-free country since 1986, and the World Organization of Animal Health (WOAH/OIE) recoganized Indonesia as an FMD-free country without vaccination in 1990. After 35 years of freeing from FMD, at the beginning of May 2022, several disease outbreaks with FMD-like symptoms were reported in Aceh and East Java provinces, followed by several FMD cases in other areas, including Central Java (Susila et al., 2023). The first FMD case in Central Java was reported on May 8, 2022, in Boyolali Regency, and involved 15 cows. As time progressed, the infection rapidly expanded to neighboring regions. The transmission pattern indicates a progressive spread, and by the end of the 41-day period, all regencies and cities in Central Java were affected (Fig. 2.

Figure 2. Fig. 2. Progressive spread of FMD in regencies/cities in Central Java.

Figure 2.

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Throughout 2022, 8473 outbreaks involving 65,445 livestock were spread across 2806 out of 8359 villages in Central Java. The series of images (Fig. 3) illustrate the spread of FMD at the village level between and within regencies/cities in Central Java during the first 4 months of the outbreak in 2022. The initial phase shows a limited number of affected villages, which are primarily concentrated in certain regencies. As the outbreak progresses, the number of affected villages increases significantly, with infections spreading both within and across administrative boundaries. A significant cluster of FMD outbreaks emerged in Blora, Rembang, and Grobogan due to their large animal markets and proximity to East Java, the epicenter of FMD in Indonesia. The total number of cases per village accumulated until December 31, 2022, is shown in Figure 4. The spatial patterns indicate that transmission follows major transportation routes and areas with high livestock density. By the fourth month, nearly all regions exhibit widespread cases, indicating rapid and extensive disease dissemination.

Figure 3. Fig. 3. Spatial distribution of the re-emerging FMD outbreak in different villages in Central Java.

Figure 3.

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Figure 4. Fig. 4. The density of FMD cases in Central Java until December 31, 2022.

Figure 4.

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Figure 5 shows the temporal analysis of FMD outbreaks in Central Java over a 35-week period in 2022. The graph shows a sharp increase in reported cases during the initial weeks, with two distinct peaks occurring in weeks 5 and 11. Following these peaks, the number of new cases gradually declined and stabilized. Vaccination was initiated in week eight, as indicated by the blue arrow. This pattern suggests that the outbreak spread rapidly at first, followed by a period of decline. Using the KDE tool for spatiotemporal analysis of FMD in Central Java, three distinct outbreak clusters were identified (Fig. 6). Red dots represent outbreak locations, and light blue circles indicate clusters. The analysis revealed one cluster within a dairy cattle production zone and two clusters within beef cattle regions, all identified during the reemergence phase of the FMD outbreak. A second cluster was detected in the eastern region of the province, occurring between the fourth and eighth weeks after the initial infection, with a radius of 14.79 km. The third cluster appeared in the northeastern part of the province, between the 7th and 11th weeks after the initial outbreak, covering a radius of 43.98 km.

Figure 5. Fig. 5. Temporal distribution of FMD outbreak (column) and Case (line) in Central Java from May to December 2022.

Figure 5.

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Figure 6. Fig. 6. Spatiotemporal clusters of FMD in Central Java using the kernel density estimation tool.

Figure 6.

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The FMD transmission risk level was assessed using a bivariate map that employs a 3 × 3 color grid to represent the risk level classification (Table 1). Figure 8 shows the distribution of cattle population density and risk level of FMD transmission at the subdistrict level. The green shaded areas on the map represent the cattle population density, with light green indicating low population and dark green indicating high population (Salman and Hernawan, 2025). Each colored circle within the subdistrict boundaries indicates the FMD transmission risk level and is categorized as follows: red for very high risk, orange for high risk, yellow for medium-high risk, green for moderate risk, cyan for low risk, and purple for very low risk. Most subdistricts with high cattle populations have high levels of FMD transmission risk.

Table 1. Table 1. Classification of FMD transmission risk according to vaccination and outbreak rates.

Low Vacc Cov Medium Vacc Cov High Vacc Cov
High outbreak rate Very high risk High risk Medium-high risk
Medium outbreak rate High risk Moderate risk Low risk
Low outbreak rate Moderate risk Low risk Very low risk
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Figure 8. Fig. 8. Distribution of cattle population density and risk level of FMD transmission at the subdistrict level.

Figure 8.

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Discussion

The re-emergence of FMD in Indonesia 35 years after being disease-free presents significant challenges for animal health and livestock management. The rapid spread observed in Central Java aligns with patterns seen in previous FMD outbreaks worldwide, where initial localized infections quickly escalate due to livestock movement, trade activities, and biosecurity lapses (Turgenbayev et al., 2023). The early detection of cases in Boyolali Regency and subsequent widespread transmission across all regencies/cities within 41 days (Fig. 2) emphasize the highly contagious nature of the disease and the need for swift containment measures. In the early phase of an outbreak, FMD spreads rapidly. The period before detection, known as the silent phase, is crucial because unnoticed transmission can lead to widespread infections before control measures are implemented. The spread rate varies according to the virus strain, climate, and livestock density. In regions with high livestock concentrations, such as Central Java, FMD is likely to spread more rapidly (Buetre et al., 2013). Efficient surveillance systems are crucial for early detection, enabling timely control measures that prevent widespread transmission and minimize economic losses, with the effectiveness of strategies relying on swift outbreak response (Brito et al., 2017). The spatial analysis of the outbreak at the village level (Fig. 3) highlights the role of transportation routes and high-density livestock areas in accelerating disease transmission. The initial concentration of cases in specific subdistrict, followed by progressive expansion, suggests that direct and indirect animal contact played a crucial role in the spread of the disease. This rapid spread of the disease was likely facilitated by high animal density and extensive livestock trade networks between and within regencies/cities (Hayama, 2016). The main mode of transmission is local spread, supplemented by direct contact with animals, movement through livestock markets, and occasional airborne transmission over distances exceeding 3 km (Firestone et al., 2019). Livestock markets with poor biosecurity significantly contribute to FMD spread by bringing together animals from various sources, facilitating transmission, and influencing the outbreak’s duration, scale, and economic impact (Baluka, 2016). Subdistricts with active livestock trade and economic reliance on animal husbandry are more prone to disease clusters, especially where animal movement is high and biosecurity is weak. In densely populated livestock areas, the risk of FMD spreads rapidly due to frequent interfarm contact and limited controls. These outbreaks often emerge in areas where livestock is a key income source, leading to underreporting driven by fears of trade restrictions (Knight-Jones et al., 2017). Policy efforts should focus on deploying mobile veterinary teams for rapid response and vaccination in high-risk or remote areas. To ensure effective implementation, biosecurity training must be tailored to local economic and social conditions. These targeted actions improve early detection and control while addressing the specific needs of vulnerable communities (Porphyre et al., 2018).

Temporal analysis (Fig. 5) further supported the aggressive nature of the outbreak, with two major peaks in weeks 5 and 11 before the number of new cases gradually declined and stabilized. Despite the establishment of a national FMD task force and the issuance of a circular letter and ministerial decree, the response to FMD re-emergence in Central Java was delayed, with the region only being officially declared an outbreak area on June 25, 2022, through Ministerial Decree No. 500.1/KPTS/PK.300/M.06/2022. To enhance the Ministry of Agriculture’s directive on controlling and eradicating FMD in livestock, the Governor of Central Java issued Decree No. 443/38 of 2022 on July 25, 2022, establishing a provincial task force for FMD management.

The application of KDE for the spatiotemporal analysis of FMD in Central Java yielded three distinct outbreak clusters delineated (Fig. 6). KDE is a nonparametric method used to estimate the probability density function of a sample set, and it has been widely applied in various fields, including animal disease mapping (Ruckthongsook et al., 2018). The most likely cluster occurred in a dairy cattle region spanning the Boyolali, Klaten, and Magelang Regencies, extending into the Special Region of Yogyakarta. This cluster emerged during the third to fifth week following the initial infection and covered a radius of 35.15 km. The second cluster was detected in the eastern region of the province, spanning from the fourth to the eighth week after the initial infection. This cluster has a radius of 14.79 km and includes areas within Sragen and Grobogan Regencies. The third and largest cluster was located in the northeastern part of the province, emerging between the seventh and eleventh weeks post-infection, with a radius of 43.98 km covering Jepara, Pati, Rembang, and Blora Regencies. All identified clusters occurred between May and July, suggesting that FMD outbreaks were most prevalent during this period, which coincides with the dry season in Central Java.

The FMD outbreak in Central Java is strongly associated with the delayed implementation of animal movement control measures, particularly in East Java, where the outbreak occurred earlier. Inadequate supervision and restrictions on livestock movement between regions facilitated the spread of the virus into Central Java. Additionally, the forced sale of livestock by traditional farmers, driven by concerns over economic losses, further contributed to transmission. In an attempt to minimize financial damage, farmers sold potentially infected animals before clinical symptoms appeared or before official movement bans were enacted, inadvertently accelerating the spread of the disease across the region (Chen et al., 2022; Antari et al., 2024).

Emergency vaccination was initiated 7 weeks after the initial outbreak was detected, following the Minister of Agriculture’s Decree No. 500.1/KPTS/ PK.300/M/06/2022, to curb disease transmission. Its effectiveness in controlling FMD outbreaks relies heavily on sufficient vaccine supply and swift execution because any delays in distribution or decision-making can exacerbate the spread and amplify economic consequences (Porphyre et al., 2018). Emergency vaccination is a critical tool in controlling FMD outbreaks across various countries. In Switzerland (1965–1966), mass emergency vaccination helped suppress a severe outbreak, significantly reducing its duration and the number of animals culled (Zingg et al., 2015). Japan’s 2010 outbreak in Miyazaki was brought under control within 3 months following targeted vaccination after initial containment measures proved insufficient (Muroga et al., 2012). Similarly, Pakistan in 2019 implemented emergency vaccination in high-risk dairy colonies, resulting in zero clinical cases post-booster doses and improved veterinary infrastructure (Ali et al., 2022). Vietnam’s 2020 response focused on deploying multivalent vaccines against circulating strains, effectively minimizing further spread (Chanchaidechachai, 2023). These examples underscore the effectiveness of emergency vaccination when aligned with rapid response, surveillance, and tailored biosecurity measures.

Because of limited resources, some vaccination sites were prioritized, leading to uneven vaccine distribution (Fig. 7) and continued spread of outbreaks into new areas until the end of 2022. When vaccine supplies are scarce, the most effective approach involves the swift implementation of ring vaccination during outbreaks while strategically administering prophylactic vaccination over an extended period to maximize resource efficiency (Ringa and Bauch, 2014).

Figure 7. Fig. 7. distribution of FMD vaccination until December 31 2022.

Figure 7.

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Figure 8 illustrates the spatial distribution of cattle population density alongside FMD transmission risk at the subdistrict level. Bivariate maps are a powerful tool for visualizing the spatial relationship between two variables simultaneously (Biesecker et al., 2020), allowing for more nuanced interpretation than univariate maps. In this case, the combined visualization of cattle density and FMD risk highlights spatial patterns that may not be apparent when analyzing each variable in isolation. Most subdistricts with a high cattle population exhibit a high level of FMD transmission risk, primarily due to low vaccination coverage and the continued presence of the disease. The clustering of high-risk areas in regions with dense cattle populations underscores the epidemiological principle that larger animal populations can facilitate more rapid and extensive disease transmission when protective measures are inadequate (Vaziry et al., 2022). The continued presence of very high-risk zones demands immediate and focused attention because these areas may serve as persistent reservoirs for the virus and facilitate its spread to adjacent, lower-risk regions. Without effective intervention strategies, high-risk areas pose a significant challenge to broader disease containment efforts (Hayama et al., 2016).

The insights provided by this bivariate choropleth map are of practical value for animal health planning. By identifying high-priority zones for intervention, stakeholders can more effectively allocate limited resources to areas with the greatest need. Targeted strategies, such as ring vaccination around high-risk areas and intensified monitoring in neighboring regions, may enhance the efficacy of disease control programs (Madden et al., 2021).

Stricter oversight of the live animal trade is reinforced by Circular Letter No. 3 of 2022 from the Chairman of the Task Force for Foot-and-Mouth-Disease Management, addressing the regulation of animal movement and products susceptible to the disease based on regional classifications. The closure of live animal markets and movement restrictions can serve as supplementary control measures in conjunction with mass vaccination efforts (Pomeroy et al., 2017).

Control measures such as emergency vaccination and restrictions on livestock movement contributed to the overall decline in FMD cases in Central Java. After the 11th week, the number of cases continued to decrease until it stabilized in the 19th week, averaging 45 cases per week. The continuous rise in cumulative cases throughout the 35-week period suggests that eradication efforts require sustained vigilance. The implementation of a comprehensive emergency vaccination program combined with a large vaccination zone can significantly reduce outbreaks (Schroeder et al., 2015).

These findings not only underscore the urgent need for enhanced biosecurity measures, early detection systems, and coordinated response strategies but also highlight key directions for future research. Strengthening disease surveillance and implementing contingency plans are essential for mitigating the risk of future outbreaks and preventing FMD recurrence in Indonesia. Moreover, incorporating additional spatial data layers—such as transportation routes, livestock market locations, and relevant environmental factors— could deepen our understanding of transmission dynamics and risk distribution. Longitudinal analyses would further enhance this by monitoring temporal shifts in risk and assessing the effectiveness of implemented control measures over time. Together, these strategies provide a foundation for the development of informed policy and more resilient animal health systems.

Conclusion

The 2022 FMD outbreak in Central Java resulted in 8,473 reported outbreaks and affected 65,445 livestock, with a major concentration in the eastern region. Spatial and temporal analyses indicated a rapid rise in cases, peaking in week 11, followed by a decline after the implementation of emergency vaccination and movement restrictions. Although effective, these measures would have been more impactful if applied earlier.

To enhance preparedness, there is a critical need to improve biosecurity through standardized farm protocols, controlled animal movement, better disinfection practices, and increased stakeholder awareness. Future research should explore the integration of spatial risk factors, such as transport and market networks, alongside longitudinal and economic analyses to assess the efficiency of various intervention strategies and guide policy development.

Acknowledgments

The authors thank the head of the Central Java Department of Livestock and Animal Health for permission to use official data.

Conflict of interest

The authors declare no conflict of interest.

Funding

This research received no specific grant, but self-funded support.

Authors’ contributions

AS: Conception, Data curation, Formal analysis, Writing original draft; HS: Supervision, Conception, Validation; SI: Supervision, Conception, Validation; AB: Supervision, Conception, Validation. All authors have reviewed and approved the final version of the manuscript.

Data availability

All data were provided in the manuscript.

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Data Availability Statement

All data were provided in the manuscript.

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