Background and Aim: Brucellosis is an important zoonotic disease that affects fertility in farm animals. The risk factors of brucellosis have not been well studied. This study aimed to understand the seroprevalence and risk factors of brucellosis among livestock in Bangriposi block of Mayurbhanj district in Odisha, a region that borders Similipal wildlife reserve. Materials and Methods: Rose Bengal plate test (RBPT) was carried out to estimate the seroprevalence of the livestock in this region. Bivariate analysis was carried out to analyze the association between the variables and brucellosis. Binary logistic regression was performed to assess the risk factors associated with brucellosis in the livestock. Results: Based on RBPT, the seroprevalence of brucellosis among cattle and goats was estimated to be 1.1% and 11.2%, respectively. Binary logistic regression analysis indicates that study area, age, goats, animals with a history of abortion, and rearing practices were the major risk factors in this region. Conclusion: This is one of the first studies in India to shed light on risk factors of brucellosis, an important neglected disease that affects the health of animals and humans and nation's economy.

Tick-borne diseases (TBDs) of livestock are endemic across various parts of tropical countries. Theileriosis is one such economically important TBD, caused by the Theileriidae family of organisms, which is transmitted by ticks. Theileria annulata, the causative agent of tropical theileriosis, contributes a significant loss to the dairy sector by causing anorexia, high fever, anemia, inflammatory changes in vital organs and icterus, thus, a loss in milk yield. Though vaccines are available, their protective efficacy is not absolute, and treatment is limited to early diagnosis of the causative agent. Routinely, microscopic identification of piroplasms in the erythrocytes (Giemsa-stained) of infected animals or schizonts in lymph node biopsies are practiced for diagnosis. PCR-based techniques (multiplex, uniplex, nested and real-time) have been reported to perform well in diagnosing active infection. Several attempts have been made using serological assays like Dot blot, ELISA and ICT, but the results were of variable sensitivity and specificity. Recombinant proteins like the Theileria annulata merozoite surface antigen (Tams1) and Theileria annulata surface protein (TaSP) have been explored as antigenic candidates for these assays. In the present study, we predicted an immunogenic peptide, i.e., TaSP-34, from the TaSP using various computational tools. The predicted peptide was custom synthesized. The diagnostic potential of the peptide was assessed by indirect plate ELISA to detect the bovine-IgM against Theileria annulata. Alongside, a recombinant truncated TaSP (rTaSP(tr)) was expressed and purified, which was used to compare the performance of the peptide as a diagnostic candidate. The IgM-based peptide ELISA was 100% sensitive and 92.77% specific as compared to PCR (Tams1 targeting), while 98.04% sensitivity and 97.44% specificity were observed in comparison with rTaSP(tr) ELISA. Almost perfect agreement between peptide ELISA and Tams1 PCR was observed with a Cohen’s kappa coefficient (κ-value) of 0.901 and agreement of 95.31%. Further, the κ-value between the peptide ELISA and rTaSP(tr) ELISA was found to be 0.95, and the agreement was 97.65%, which shows a good correlation between the two tests. The findings suggest that the TaSP-34 peptide can be an efficient and new-generation diagnostic candidate for the diagnosis of T. annulata. Furthermore, the peptide can be synthesized commercially at a larger scale and can be a cost-effective alternative for the protein-based diagnostic candidates for T. annulata.

Over the past decade, dengue incidence has been steadily increasing across the different climatic zones of India. The role of climatic variability in the spatial and temporal distribution of dengue at the district level across India is to be determined. District-level dengue incidence data from 2010 to 2022 were obtained from the National Centre for Vector-Borne Disease Control. Indian districts were categorized into eleven climatic zones based on the Köppen-Geiger climate classification scheme and subsequently grouped into three significant climatic zones (tropical, temperate and arid). Temporal trends were assessed using the Prais-Winsten regression model that accounted for serial autocorrelation, while climate zonal differences in annual incidence were evaluated using Kruskal-Wallis tests and pairwise comparisons. The global Moran’s I test was used to assess overall spatial autocorrelation, followed by Anselin’s local Moran’s I test to identify clustering and hotspots of dengue incidences at the district level. There is significant heterogeneity in dengue distribution across the districts in India. Prais-Winsten regression analysis shows the strongest upward trend in dengue incidence in polar tundra (ET) zone [AIR = 126.9%; p = 0.01], temperate, no dry season, hot summer (Cfa) zone [AIR: 94.8%; p = 0.01], and cold, no dry season, warm summer (Dfb) zone [AIR = 85.1%; p < 0.001], indicating a substantial intensification of dengue transmission even in cooler climatic regions. Kruskal-Wallis tests confirmed persistent and significant disparities between tropical, temperate, and arid regions. Spatial analysis revealed clustering (Global Moran’s I = 0.06, p < 0.001), with 31 high-incidence clusters concentrated primarily in the semi-arid regions of Punjab and Haryana, and humid regions of Tamil Nadu and Kerala. Overall, the identified clustering of high-incidence districts in semi-arid and humid regions, along with the upward trends in multiple climatic zones, highlights an urgent need to embed climate-sensitive planning, early warning systems, and geographically targeted vector-control measures into India’s dengue prevention framework.