In recent decades, dengue has been expanding rapidly in the tropical cities. Even though environmental factors and landscape features profoundly impact dengue vector abundance and disease epidemiology, significant gaps exist in understanding the role of local environmental heterogeneity on dengue epidemiology in India. In this study, we assessed the role of remotely sensed climatic factors (rainfall, temperature and humidity) and landscape variables (land use pattern, vegetation and built up density) on dengue incidence (2012–2019) in Bhopal city, Central India. Dengue hotspots in the city were assessed through geographical information system based spatial statistics. Dengue incidence increased from 0.59 cases in 2012 to 9.11 cases in 2019 per 10,000 inhabitants, and wards located in Southern Bhopal were found to be dengue hotspots. Distributed lag non-linear model combined with quasi Poisson regression was used to assess the exposure-response association, relative risk (RR), and delayed effects of environmental factors on dengue incidence. The analysis revealed a non-linear relationship between meteorological variables and dengue cases. The model shows that the risk of dengue cases increases with increasing mean temperature, rainfall and absolute humidity. The highest RR of dengue cases (~2.0) was observed for absolute humidity ≥60 g/m3 with a 5–15 week lag. Rapid urbanization assessed by an increase in the built-up area (a 9.1% increase in 2020 compared to 2014) could also be a key factor driving dengue incidence in Bhopal city. The study sheds important insight into the synergistic effects of both the landscape and climatic factors on the transmission dynamics of dengue. Furthermore, the study provides key baseline information on the climatic variables that can be used in the micro-level dengue prediction models in Bhopal and other cities with similar climatic conditions.

Blood feeding is an important behavior of Aedes aegypti, a dominant arboviral disease vector, as it can establish and transmit viruses to humans. Bacteria associated with the mosquito gut can modulate the biological characteristics and behavior of disease vectors. In this study, we characterized the gut microbiota composition of human-blood-fed (HF), non-human-blood-fed (NHF) and non-fed (NF) field-collected Ae. aegypti mosquitoes, using a 16S metagenomic approach, to assess any association of bacterial taxa with the blood-feeding behavior of Ae. aegypti. A significant difference in the microbiota composition between the HF and NF mosquito group was observed. A significant association was observed in the relative abundance of families Rhodobacteraceae, Neisseriaceae and Dermacoccaceae in the HF group in contrast to NF and NHF Ae. aegypti mosquitoes, respectively. At the class level, two classes (Rhodobacterales and Neisseriales) were found to be in higher abundance in the HF mosquitoes compared to a single class of bacteria (Caulobacterales) in the NF mosquitoes. These results show that human-blood feeding may change the gut microbiota in wild Ae. aegypti populations. More research is needed to determine how changes in the midgut bacterial communities in response to human-blood-feeding affect the vectorial capacity of Ae. aegypti.

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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.

Leptospirosis is a spirochaetal infection that possesses a broad host range affecting almost all mammals. In the present study, the microscopic agglutination test (MAT) was compared with recombinant LigA/B antigen-based point-of-care diagnostics such as the in-house IgM dot ELISA dipstick test (IgM- DEDT) and the latex agglutination test (LAT) for the serodiagnosis of human leptospirosis. The comparison of the MAT with these two point–of-care diagnostics was performed using the MAT as the gold standard test and using Bayesian latent class modelling (BLCM), which considers all diagnostic tests as imperfect. The N-terminal conserved region of the LigA/B protein spanning the first to fifth big tandem repeat domains (rLigA/BCon1-5) was employed as a serodiagnostic marker in both of the bedside assays. A total of 340 serum samples collected from humans involved in high risk occupations were screened using the MAT, IgM DEDT and LAT. During the early phase of leptospirosis, BLCM analysis showed that the IgM DEDT and LAT had similar sensitivities (99.6 (96.0–100)) and (99.5 (95.2–100)), respectively, while the single acute phase MAT had the lowest sensitivity (83.3 (72.8–91.3)). Both the IgM DEDT and the LAT may be superior to the single acute phase MAT in terms of sensitivity during the early phase of infection and may be suitable for the early diagnosis of leptospirosis. However, BLCM analysis revealed that the use of both acute and convalescent samples substantially increased the sensitivity of the final MAT (98.2% (93.0–99.8%)) as a test to diagnose human leptospirosis. Both the IgM DEDT and LAT can be employed as bedside spot tests in remote locations where the MAT is not easily accessible.