In an increasingly globalized world, the intricate web of diseases and macroeconomic factors forms a complex tableau. Recent global health crises have underscored the profound influence that macroeconomic variables can exert on the occurrence, spread, and control of diseases. From economic growth, labor markets, international trade, public spending, to policy responses, the potential impact on disease dynamics is vast yet challenging to get accurately quantified. Crucially, temporal and spatial factors play pivotal roles in these processes, but their precise mechanisms and degree of influence remain unclear. To better understand this complex phenomenon and provide robust policy recommendations, it is imperative to employ refined temporal and spatial analysis methods, integrating multidisciplinary knowledge from economics, epidemiology, public health, and geography.
The goal of this Research Topic is to delve into the intricate relationships between diseases and macroeconomic factors within the realm of spatial and temporal dimensions. We aim to unravel the patterns of disease dynamics, employ advanced technological and statistical methods, and scrutinize the influences of socioeconomic factors on disease occurrences and transmissions. By integrating sophisticated spatio-temporal data mining for risk prediction, and tailoring strategies to disease characteristics for optimized spatial planning and policy interventions. We aspire to mitigate the societal and economic impact of diseases. Through this exploration, we hope to stimulate multidisciplinary dialogue and contribute to a more comprehensive understanding of the interplay between public health and macroeconomic resilience.
We welcome submissions of Original Research, Review and Mini-review, in the following subtopics, but not limited to:
? Apply spatial statistical methods to investigate disease-macroeconomic factor correlations.
? Analyze the influence of socioeconomic factors on spatial and temporal disease distribution.
? Examine the temporal and spatial evolution of diseases, revealing patterns of disease dynamics.
? Utilize Geographic Information Systems (GIS), Remote Sensing (RS), and Global Positioning Systems (GPS) for disease study.
? Explore transmission mechanisms influencing disease dynamics across regions and periods.
? Use spatio-temporal data mining for disease risk prediction and assessment.
? Propose strategies tailored to spatio-temporal disease characteristics for optimizing spatial planning and policy interventions.
In an increasingly globalized world, the intricate web of diseases and macroeconomic factors forms a complex tableau. Recent global health crises have underscored the profound influence that macroeconomic variables can exert on the occurrence, spread, and control of diseases. From economic growth, labor markets, international trade, public spending, to policy responses, the potential impact on disease dynamics is vast yet challenging to get accurately quantified. Crucially, temporal and spatial factors play pivotal roles in these processes, but their precise mechanisms and degree of influence remain unclear. To better understand this complex phenomenon and provide robust policy recommendations, it is imperative to employ refined temporal and spatial analysis methods, integrating multidisciplinary knowledge from economics, epidemiology, public health, and geography.
The goal of this Research Topic is to delve into the intricate relationships between diseases and macroeconomic factors within the realm of spatial and temporal dimensions. We aim to unravel the patterns of disease dynamics, employ advanced technological and statistical methods, and scrutinize the influences of socioeconomic factors on disease occurrences and transmissions. By integrating sophisticated spatio-temporal data mining for risk prediction, and tailoring strategies to disease characteristics for optimized spatial planning and policy interventions. We aspire to mitigate the societal and economic impact of diseases. Through this exploration, we hope to stimulate multidisciplinary dialogue and contribute to a more comprehensive understanding of the interplay between public health and macroeconomic resilience.
We welcome submissions of Original Research, Review and Mini-review, in the following subtopics, but not limited to:
? Apply spatial statistical methods to investigate disease-macroeconomic factor correlations.
? Analyze the influence of socioeconomic factors on spatial and temporal disease distribution.
? Examine the temporal and spatial evolution of diseases, revealing patterns of disease dynamics.
? Utilize Geographic Information Systems (GIS), Remote Sensing (RS), and Global Positioning Systems (GPS) for disease study.
? Explore transmission mechanisms influencing disease dynamics across regions and periods.
? Use spatio-temporal data mining for disease risk prediction and assessment.
? Propose strategies tailored to spatio-temporal disease characteristics for optimizing spatial planning and policy interventions.
