M Riddle
Biographic Data
| ID | 5484653 |
|---|---|
| NAME | M Riddle |
| GIVEN NAMES | M |
| FAMILY NAME | Riddle |
| SIGNATURE | RIDDLE M |
| VERIFIED | No |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2010 |
| LATEST PUBLICATION YEAR | 2011 |
| H-INDEX | 0 |
O4-2.4 Complexity, epidemiology and the understanding of “what if”
Einstein is reputed to have said that “everything should be as simple as possible, but not simpler.” These words ring ever more true to epidemiologists as we struggle to gain knowledge about complex disease processes that involve dynamic interactions between biological, behavioural, social, spatial, socioeconomic, and global determinants. Understanding the etiologic and policy implications of such a rich stew of factors challenges the “independen…
Causal thinking and complex system approaches in epidemiology
Identifying biological and behavioural causes of diseases has been one of the central concerns of epidemiology for the past half century. This has led to the development of increasingly sophisticated conceptual and analytical approaches focused on the isolation of single causes of disease states. However, the growing recognition that (i) factors at multiple levels, including biological, behavioural and group levels may influence health and diseas…
No prominent works on this page.
Causal thinking and complex system approaches in epidemiology
Identifying biological and behavioural causes of diseases has been one of the central concerns of epidemiology for the past half century. This has led to the development of increasingly sophisticated conceptual and analytical approaches focused on the isolation of single causes of disease states. However, the growing recognition that (i) factors at multiple levels, including biological, behavioural and group levels may influence health and diseas…
O4-2.4 Complexity, epidemiology and the understanding of “what if”
Einstein is reputed to have said that “everything should be as simple as possible, but not simpler.” These words ring ever more true to epidemiologists as we struggle to gain knowledge about complex disease processes that involve dynamic interactions between biological, behavioural, social, spatial, socioeconomic, and global determinants. Understanding the etiologic and policy implications of such a rich stew of factors challenges the “independen…
Computer Science (2 works) · Data science (2 works) · Disease (2 works) · Health disparities and outcomes (2 works) · Medicine (2 works) · Bioinformatics (1 work) · Biology (1 work) · Causation (1 work) · Cognitive psychology (1 work) · COVID-19 epidemiological studies (1 work)