ABSTRACT
Crimean Congo Hemorrhagic Fever (CCHF), is an emerging zoonosis globally and in India. The present study focused on identifying the risk factors for occurrence of CCHF in the Indian state of Gujarat and development of risk map for India. The past CCHF outbreaks in India were collated for the analyses. Influence of land use change and climatic factors in determining the occurrence of CCHF in Gujarat was assessed using Bayesian spatial models. Change in maximum temperature in affected districts was analysed to identify the significant change points over 110 years. Risk map was developed for Gujarat using Bayesian Additive Regression Trees (BART) model with remotely sensed environmental variables and host (livestock and human) factors. We found the change in land use patterns and maximum temperature in affected districts to be contributing to the occurrence of CCHF in Gujarat. Spatial risk map developed using CCHF occurrence data for Gujarat identified density of buffalo, minimum land surface temperature and elevation as risk determinants. Further, spatial risk map for the occurrence of CCHF in India was developed using selected variables. Overall, we found that combination of factors such as change in land-use patterns, maximum temperature, buffalo density, day time minimum land surface temperature and elevation led to the emergence and further spread of the disease in India. Mitigation measures for CCHF in India could be designed considering disease epidemiology and initiation of surveillance strategies based on the risk map developed in this study.
ABSTRACT
Rabies is one of the most important zoonoses resulting in a high case fatality rate in humans. Most of the human Rabies cases are due to dog bites which can be prevented by effective vaccination in dogs. Globally, epidemiological studies on understanding the seasonality and risk factors for occurrence in canines are limited. The present study aimed to understand the temporal pattern of Rabies occurrence in Chennai city of Tamil Nadu, India, and address the suggestive clinical signs for better clinical ante-mortem rabies diagnosis. Data of 598 suspected canine hippocampus brain smear samples with Seller's staining and/or FAT percent positivity of 71.57% (428/598) from March 2010 to February 2019 were included in this study. Cross-correlation between rabies cases and meteorological factors showed that maximum temperature (lag 15), morning relative humidity (lag 0 and lag 5) and evening relative humidity (lag 4) were significantly associated with rabies cases. Auto-Regressive Integrated Moving Average (ARIMA) model with exogenous variables (significant lags of meteorological variables) was used to fit the time series of canine Rabies in Chennai. In logistic regression analysis, the following risk factors were found to be playing a significant role in Rabies positivity viz., behavioural changes in dogs (P < 0.001), free-roaming, unprovoked biting, hyper salivation (P < 0.05), dog bite history and drop jaw (P < 0.01). Hence, the study results highlight the need for continuous surveillance of canine Rabies for devising and implementing future preventive strategies and is helpful to establish the above-identified risk factors as a criterion to help in clinical rabies diagnosis.
