Climate change, along with various natural and human-induced stressors, has multifaceted impacts on human health and disease. It significantly influences infectious agents, vector organisms, non-human reservoir species, and pathogen replication rates, all of which are highly sensitive to climatic conditions.
Over recent years, several theories have emerged to elucidate the nexus between climate change and infectious diseases. These theories encompass concepts such as heightened disease proliferation at elevated temperatures, longer transmission seasons, alterations in ecological balances, and climate-driven movements of disease vectors, reservoir hosts, or human populations.
Climate change is the greatest health threat of the 21st century. Many infectious agents, vector organisms, non-human reservoir species, and pathogen replication rates are particularly sensitive to climatic conditions. In recent years, numerous theories have been developed to explain the relationship between climate change and infectious diseases. These include higher proliferation rates at higher temperatures, longer transmission seasons, changes in ecological balances, and climate-related migrations of vectors, reservoir hosts, or human populations. Health effects include increases in respiratory and cardiovascular diseases, injuries and premature deaths related to extreme weather events, changes in the prevalence and geographical distribution of food- and water-borne and other infectious diseases, and threats to mental health. Preventive and adaptive actions, such as the establishment of early warning systems for extreme weather events, represent a considerable public health challenge and will be key for reducing the severity of these impacts.
The scope of this Research Topic includes, but is not limited to, the following topics:
• Climate data processing and analytics
• Climate data models, algorithms, and architectures for public health
• Real-time surveillance and early detection of emerging disease
• Machine learning and its applications for climate change
• Application of cognitive computing in climate change monitoring.
Keywords:
sustainability; extreme events; predictive modelling; public health; climate change; data analytics
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
Climate change, along with various natural and human-induced stressors, has multifaceted impacts on human health and disease. It significantly influences infectious agents, vector organisms, non-human reservoir species, and pathogen replication rates, all of which are highly sensitive to climatic conditions.
Over recent years, several theories have emerged to elucidate the nexus between climate change and infectious diseases. These theories encompass concepts such as heightened disease proliferation at elevated temperatures, longer transmission seasons, alterations in ecological balances, and climate-driven movements of disease vectors, reservoir hosts, or human populations.
Climate change is the greatest health threat of the 21st century. Many infectious agents, vector organisms, non-human reservoir species, and pathogen replication rates are particularly sensitive to climatic conditions. In recent years, numerous theories have been developed to explain the relationship between climate change and infectious diseases. These include higher proliferation rates at higher temperatures, longer transmission seasons, changes in ecological balances, and climate-related migrations of vectors, reservoir hosts, or human populations. Health effects include increases in respiratory and cardiovascular diseases, injuries and premature deaths related to extreme weather events, changes in the prevalence and geographical distribution of food- and water-borne and other infectious diseases, and threats to mental health. Preventive and adaptive actions, such as the establishment of early warning systems for extreme weather events, represent a considerable public health challenge and will be key for reducing the severity of these impacts.
The scope of this Research Topic includes, but is not limited to, the following topics:
• Climate data processing and analytics
• Climate data models, algorithms, and architectures for public health
• Real-time surveillance and early detection of emerging disease
• Machine learning and its applications for climate change
• Application of cognitive computing in climate change monitoring.
Keywords:
sustainability; extreme events; predictive modelling; public health; climate change; data analytics
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.