Analytics and Statistics for Population Research Panel B (ASPB) study section reviews applications that seek to develop, improve or innovate data integration, study designs, statistical and modeling approaches for human population studies of observational and spatial-temporal data such as clinical, behavioral, environmental, or social data to advance understanding of health-related outcomes. Applications that primarily focus on developing applied analytical methodology and validate their findings with disease, condition or exposure specific data are reviewed in ASPB. Applications that combine the development of applied analytical methodology with the application of the new methodology to drive the epidemiology, behavioral or social science field forward are reviewed in the study sections that cover those exposures, diseases or conditions. Applications that address software development are reviewed in other study sections.
The membership panel is a list of chartered members only.
- Development of causal inference methods for population studies including methods to address confounding, sources of bias, effect heterogeneity, causal mediation, and generalizability, and missing or truncated data
- Studies that develop and/or apply models or simulation approaches to advance the study of population health and well-being
- Studies that propose approaches and methods for population health surveillance.
- Studies developing and testing social network analysis methods and their integration for human population health research
- Development and application of infectious disease modeling methodology, and statistical methods for analyzing infectious disease transmission, outcomes, and intervention effectiveness in human populations
- Studies that advance statistical approaches or tools for the use of survey and observational data, clinical data, electronic health records, text- based social, qualitative, natural or built environmental, and administrative data from population based studies
- Development and adaptation of spatial, spatio-temporal and geospatial analysis methods for human population health studies including improved methodology to comprehensively measure the human exposome
- Development of novel analyses of existing large human population behavioral, social or environmental datasets as well as innovative application of existing statistical and computational methodologies into new areas of application
- Innovative approaches to study design, measurement, and analysis of lifestyle and behavioral factors, and their relationship to biological and biobehavioral health outcomes in human populations
- Adaptation, novel assembly and novel application of existing statistical and computational methodology for clinical, behavioral, infectious disease, environmental or social data analysis in population health studies
Shared Interests and Overlaps
There are shared interests in the development and application of statistical and computational methods to human population health research with Analytics and Statistics for Population Research Panel A (ASPA). Applications focused on observational, environmental, infectious disease, or social/behavioral data and modeling approaches for application to human population health are reviewed in ASPB. Applications focused on biological or biomarker data, particularly those that characterize complex biological/biomedical processes are reviewed in ASPA.
There are shared interests in the geographic and temporal relationship between environmental exposures and human population level health outcomes with Social and Environmental Determinants of Health (SEDH). Applications that emphasize the development and enhancement of spatial, spatio-temporal, and geospatial methodology for environmental exposure modeling and assessment of related human population health outcomes are reviewed in ASPB. Applications that emphasize application of spatial methodology to assess the contribution of social and environmental exposures to population health outcomes are reviewed in SEDH.
There are shared interests in infectious disease transmission modeling with Population-based Research in Infectious Disease (PRID). Applications that emphasize the development of infectious disease dynamic modeling and geospatial analysis methodology to be applied in future human population health studies are reviewed in ASPB. Applications that emphasize the application of infectious disease modeling and geospatial analysis methodology to characterize infectious disease transmission in large human populations are reviewed in PRID.
There are shared interests in infectious disease transmission modeling with Etiology, Diagnostic, Intervention and Treatment of Infectious Diseases (EDIT). Applications that emphasize the development and validation of infectious disease modeling methodology focused on the transmission in human populations are reviewed in ASPB. Applications that emphasize microbial ecology and monitoring pathogens during the transmission of infectious diseases are reviewed in EDIT.
There are shared interests in the measurement of lifestyle and health behaviors like diet, sleep and physical activity with Lifestyle and Health Behaviors (LHB). Applications that primarily develop and adapt methodology to better analyze lifestyle and health behaviors data including data from wearable device and smartphone apps are reviewed in ASPB. Applications that primarily apply this methodology to measure lifestyle and health behaviors and their relationship with population health outcomes including the assessment of the efficacy of technology-based assessments of health behaviors are reviewed in LHB.
There are shared interests in clinical data analysis using behavioral or social data from human populations with the Clinical Data Management and Analysis (CDMA) and Clinical Informatics and Digital Health (CIDH) study sections. Applications that emphasize the development of statistical methodology to support epidemiological studies and public health decision making using clinical behavioral or social data are reviewed in ASPB. Applications that emphasize clinical data analysis and methodology development for eventual translation to clinical use are reviewed in CDMA. Applications that emphasize informatics and computing methodology development using clinical data for clinical decision support and healthcare delivery are reviewed in CIDH.
There are shared interests in infectious disease transmission modeling with Transmission of Vector-Borne and Zoonotic Diseases (TVZ). Applications that emphasize disease ecology and modelling the interactions between pathogens, non-human hosts, and their environment may be reviewed in TVZ. Applications that propose development and validation of infectious disease transmission modeling methodology focused on transmission between human populations may be reviewed in ASPB.