Big data analysis descriptively of Brucella abortus cases in Indonesia during 2006-2020

Citra Sari 1, *, Ajeng Erika Prihastuti Haskito 1, Dinda Rahma Kurniasari 2 and Fajar Shodiq Permata 3

1 Laboratory of Veterinary Public Health, Faculty of Veterinary Medicine, Universitas Brawijaya, Puncak Dieng Eksklusif, Kalisongo, Dau, Malang, East Java Indonesia, 65151.
2 Faculty of Veterinary Medicine, Universitas Brawijaya, Puncak Dieng Eksklusif, Kalisongo, Dau, Malang, East Java Indonesia, 65151
3 Laboratory of Veterinary Anatomy, Histology and Embriology, Faculty of Veterinary Medicine, Universitas Brawijaya, Puncak Dieng Eksklusif, Kalisongo, Dau, Malang, East Java Indonesia, 65151.
 
Review
International Journal of Science and Research Archive, 2023, 10(02), 1048–1061.
Article DOI: 10.30574/ijsra.2023.10.2.1077
Publication history: 
Received on 13 November 2023; revised on 19 December 2023; accepted on 22 December 2023
 
Abstract: 
Brucellosis represents a formidable zoonotic challenge, primarily impacting animal breeders and raising substantial health and economic concerns. This study delves into the epidemiological analysis of Brucella abortus infections in Indonesia, leveraging the extensive quantitative big data from the World Animal Health Information System (WAHIS) database managed by the World Organisation for Animal Health (WOAH). Covering the period from 2006 to 2020, the research utilizes advanced clustering techniques to dissect the incidence and distribution of this zoonotic disease across various Indonesian provinces and animal species, including cattle, buffaloes, sheep, goats, and swine. The findings reveal a prominent prevalence of the infection in Sulawesi Selatan Province, accounting for 26.71% of cases, with a fluctuating trend observed nationwide and the peak incidence in 2019, notably in Sulawesi Tenggara Province. The study highlights cattle as the species most susceptible to Brucella abortus. The comprehensive analysis underscores the criticality of targeted interventions and sustained surveillance in particular regions, especially focusing on cattle. This research not only enhances understanding of Brucellosis's spread and impact in Indonesia but also aids in formulating effective disease management strategies, thereby addressing both health and economic concerns associated with this zoonotic challenge.
 
Keywords: 
Animal species; Big data; Brucella abortus; Indonesia province; WAHIS
 
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