In his thought-provoking and concise commentary ‘Making epidemiology matter’,1 Galea has correctly described epidemiology as the ‘quantitative heart of public health’. He has justly put emphasis on the process of causal thinking that is a unique strength of epidemiology in comparison with other population-oriented scientific disciplines. Observing the noticeable gaps in the achievements of public health between the developed and the developing countries, he has identified our focusing on ill health and ignoring ‘big data’ as two of its major reasons. He has identified the ever-changing parameters of public health issues as a challenge, and use of the ‘increasingly available data characterizing populations’ as an opportunity for epidemiologists to attempt to reduce such a gap. The fact is that in the context of public health, achievements of epidemiologists are actually a kind of ‘blueprint’ for possible actions by the relevant agencies, generally governments, in various parts of the world. Yes, it was the epidemiologist who successfully nailed the causal association between smoking and lung cancer, but the real achievement in reducing the incidence of and mortality from lung cancer came through such actions as creating smoke-free zones and tax increases, both of which were purely administrative. The gap between the communities in their public health achievements is not due to their lack of epidemiological knowledge and expertise, but because of the difference in the political will and enthusiasm of local governments and administrations in using the available knowledge. The point I am trying to make is that to achieve lasting public health results, epidemiologists must remember and accept that on top of being a scientist, they are a significant member of the political and administrative structure in their communities and should actively engage in and be a driving force behind public health decision making. This outlook and concept is unfortunately not included, and mostly not even discussed, as part of the professional training of epidemiologists. This brings up another significant point, which is the expansion of epidemiological methods and thinking to issues outside the common boundaries of ‘public health’. Many individuals and organizations repeatedly use the ‘increasingly available data characterizing populations’ to support their own agenda in various ways. However, a large proportion of such uses remains at the very elementary level of simple tabulations of selected data that will end up as a sound bite at best. Epidemiology, with its in-depth teachings of descriptive data handling, causal thinking and analytical research, can provide an important service to the organizations that collect and use such massive data repositories. With input from a well-trained epidemiologist, the nature and quality of the data collection will be more focused and significantly better utilized. It is time for epidemiology to break the mould of public health and expand to cover other areas of population-based fields of sciences. A properly designed version of ‘Epi 101’, with a mix of examples from general mass phenomena along with those related to public health, can provide the basic understanding of appropriate methods of data handling, analysis and causal inferences for all who begin their education in other population-centred fields of studies, such as sociology, demography, marketing and information technology. Reference 1 Galea S. Making epidemiology matter. Int J Epidemiol 2017; 46: 1083– 85. Google Scholar CrossRef Search ADS PubMed © The Author 2017; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association
International Journal of Epidemiology – Oxford University Press
Published: Feb 1, 2018
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