Brucellosis is an infectious disease in lower to moderate-income countries. It primarily affects small ruminant (sheep and goat) populations and can also be transmitted to mammals (humans). Brucella melitensis (B. melitensis) is the primary cause, posing a zoonotic threat. Controlling the spread of B. melitensis, especially in regions with high risk to humans and small ruminants, remains challenging. Current research explores the prevalence, genetic diversity, and prediction of brucellosis transmission in ruminants and humans. In this study, we developed an integrated database providing information on B. melitensis incidence in livestock from 2003 to 2024 and a systematic review and meta-analysis to assess the prevalence by following the Cochran collaborators' Preferred Reporting Items for Systematic Reviews and Meta-analysis guidelines. A comprehensive literature search was conducted using reputable sources. These included reputable sources of electronic databases such as PubMed, ScienceDirect, Scopus, Biomed Central, CeRA, Krishikosh, ProQuest Dissertations & Theses Global, and Web of Science, complemented by the Google Scholar search engine. We also utilized Zotero 5.0 and Rayyan QCR, two web-based tools. Time series model to predict incidence trends and pan-genomic analysis to determine genetic diversity across Asia and Africa. Meta-analysis revealed an overall prevalence of 12 % of which the African continent rose at 7 % (95 % CI: 5-8 %, I² = 99 %, τ² = 0.03, P = 0), while the corresponding prevalence in the Asian continent constituted 12 % (95 % CI: 11-14 %, I² = 99 %, τ² = 0.02, P = 0). The Time series model predicts a rising trend in brucellosis incidence from 2023 to 2030. The pan-genome analysis identified Rev 1 (0.000712) strain from China and the CIIMS-PH-3 (0.000209) strains from India showed the highest branch length, considered to have more genetic diversity. These findings underscore the critical need for ongoing surveillance models and research to monitor the evolving B. melitensis landscape. High-prevalence regions exhibit significant genetic diversity. Effective prevention & control and response & preparedness strategies, including precise detection through advanced diagnostics, robust surveillance models to track trends, and targeted vaccination of susceptible animals, are vital. Stringent quarantine protocols, biosecurity measures, and exploring herbal remedies as a complementary approach to conventional treatment are crucial to mitigate the brucellosis burden as a public health concern and its socioeconomic impact on livelihood.

Anthrax, a zoonotic disease affecting both livestock and humans globally, is caused by Bacillus anthracis. The objectives of this study were the following: (1) to identify environmental risk factors for anthrax and use this information to develop an improved predictive risk map, and (2) to estimate spatial variation in basic reproduction number (Ro) and herd immunity threshold at the village level, which can be used to optimize vaccination policies within high-risk regions. Based on the anthrax incidences from 2000–2023 and vaccine administration figures between 2008 and 2022 in Karnataka, this study depicted spatiotemporal pattern analysis to derive a risk map employing machine learning algorithms and estimate Ro and herd immunity threshold for better vaccination coverage. Risk factors considered were key meteorological, remote sensing, soil, and geographical parameters. Spatial autocorrelation and SaTScan analysis revealed the presence of hotspots and clusters predominantly in the southern, central, and uppermost northern districts of Karnataka and temporal cluster distribution between June and September. Factors significantly associated with anthrax were air temperature, surface pressure, land surface temperature (LST), enhanced vegetation index (EVI), potential evapotranspiration (PET), soil temperature, soil moisture, pH, available potassium, sulphur, and boron, elevation, and proximity to waterbodies and waterways. Ensemble technique with random forest and classification tree models were used to improve the prediction accuracy of anthrax. High-risk areas are expected in villages in the southern, central, and extreme northern districts of Karnataka. The estimated Ro revealed 11 high-risk districts with Ro > 1.50 and respective herd immunity thresholds ranging from 11.24% to 55.47%, and the assessment of vaccination coverage at the 70%, 80%, and 90% vaccine efficacy levels, all serving for need-based strategic vaccine allocation. A comparison analysis of vaccinations administered and vaccination coverage estimated in this study is used to illustrate difference in the supply and vaccine force. The findings from the present study may support in planning preventive interventions, resource allocation, especially of vaccines, and other control strategies against anthrax across Karnataka, specifically focusing on predicted high-risk regions.

Escherichia coli (E. coli), a common gut commensal, includes pathogenic strains responsible for gastrointestinal infections and hemolytic uremic syndrome (HUS). It spreads mainly through contaminated water and food, as well as direct human contact, with the risk being particularly high in densely populated regions. The growing emergence of antimicrobial-resistant (AMR) strains, particularly in Asia, poses serious public health challenges. This study employed a multi-tiered computational framework comprising systematic review, quantitative evidence synthesis (meta-analysis), the Markov cluster algorithm with random walks on pan-genomics, and positive selection through evolutionary analysis, shedding light on the prevalence, geographical distribution, genomic diversity, and evolutionary dynamics of E. coli across Asia. Quantitative evidence synthesis (meta-analysis) technique included 66 articles (total sample n = 1,20,207) and revealed an E. coli prevalence of 18 % (95 % CI:14 %-21 %, I²=100, τ ²=0.0, P = 0) in Asia. The E. coli incidences identified the Indian strain Ec40 collected in 2013 showed the highest genetic diversity, and the sequences collected between 2012 and 2019 displayed the most variation. The emrY gene, recurrently identified within the E. coli genomes, was subjected to evolutionary analysis. Codon-based selection models indicated adaptive evolution, with five codon sites under pervasive selection and twelve under episode selection (ω > 1), suggesting antimicrobial pressure as the main driver of regional adaptation. These findings underscore the urgent need for integrated prevention and control strategies, including robust surveillance systems to monitor infection trends, targeted interventions to curb transmission, and strengthened biosecurity measures aimed at reducing environmental contamination. Furthermore, the emergence of AMR variants calls for alternative treatment, e.g., bacteriophage therapy, to reduce the clinical and socioeconomic burden of E. coli infections in humans and animal populations.