ArticleOne health (Amsterdam, Netherlands)2023
Quantifying the influence of climate, host and change in land-use patterns on occurrence of Crimean Congo Hemorrhagic Fever (CCHF) and development of spatial risk map for India.
Article in One health (Amsterdam, Netherlands), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed.
- Global distribution, pathogen spectrum, and invasion potential ofOne health (Amsterdam, Netherlands) · 2026Article
- [The impact of global change on infectious disease epidemiology].Atencion primaria · 2026Article
- Sero-epidemiology of Crimean-Congo haemorrhagic fever in mixed crop-livestock farming households in Burkina Faso: a one health study.PloS one · 2026Article
- The Effect of Climate Change on Emergence and Evolution of Zoonotic Diseases in Asia.Zoonoses and public health · 2025Review
- Tick-Borne Viruses in a Changing Climate: The Expanding Threat in Africa and Beyond.Microorganisms · 2025Review
- Detecting spatial clusters of Crimean Congo hemorrhagic fever in Iraq in 2023.Global epidemiology · 2025Article
- Spatial analysis and risk mapping of Crimean-Congo hemorrhagic fever (CCHF) in Sub-saharan Africa.Scientific reports · 2025Article
- Hard Ticks as Vectors: The Emerging Threat of Tick-Borne Diseases in India.Pathogens (Basel, Switzerland) · 2024Review
- Building a pathway to One Health surveillance and response in Asian countries.Science in One Health · 2024Review
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Authors and funding
7 authors.
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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.
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