Bernard C. K. Choi

This article points out deficiencies in present-day definitions of public health surveillance, which include data collection, analysis, interpretation and dissemination, but not public health action. Controlling a public health problem of concern requires a public health response that goes beyond information dissemination. It is undesirable to have public health divided into data generation processes (public health surveillance) and data use processes (public health response), managed by two separate groups (surveillance experts and policy-makers). It is time to rethink the need to modernize the definition of public health surveillance, inspired by the authors’ enhanced Data, Information, Knowledge, Intelligence and Wisdom model. Our recommendations include expanding the scope of public health surveillance beyond information dissemination to comprise actionable knowledge (intelligence); mandating surveillance experts to assist policy-makers in making evidence-informed decisions; encouraging surveillance experts to become policy-makers; and incorporating public health literacy training – from data to knowledge to wisdom – into the curricula for all public health professionals. Work on modernizing the scope and definition of public health surveillance will be a good starting point.

Réponse des auteurs aux lettres à la rédaction à propos du commentaire « Santé publique clinique : exploiter le meilleur des deux mondes pour la santé comme pour le traitement des maladies », PSPMC 2023;43(4). https://doi.org/10.24095/hpcdp.43.4.07f

Authors’ response to Letters to the Editor re: Clinical public health: harnessing the best of both worlds in sickness and in health, HPCDPJ 2023;43(4). https://doi.org/10.24095/hpcdp.43.4.07

Purpose: To solve complex health issues, an innovative and multidisciplinary framework is necessary. The Clinical Public Health (CPH) Division was established at the University of Toronto (UofT), Canada to foster inte-gration of primary care, preventive medicine and public health in education, practice and research. To better understand how the construct of CPH might be applied, we surveyed clinicians, researchers and public health professionals affiliated with the CPH Division to assess their understanding of the CPH concept and its utility in fostering broad collaboration. Methods: A two-wave anonymous survey of the active faculty of the CPH Division, UofT was conducted across Canada. Wave 1 participants (n = 187; 2016) were asked to define CPH, while Wave 2 participants (n = 192; 2017) were provided a synthesis of Wave 1 results and asked to rank each definition. Both waves were asked about the need for a common definition, and to comment on CPH. Results: Response rates for the first and second waves were 25% and 22%, respectively. Of the six definitions of CPH from Wave 1, “the intersection of clinical practice and public health,” was most highly ranked by Wave 2 participants. Positive perceptions of CPH included multidisciplinary collaboration, new fields and insights, forward thinking and innovation. Negative perceptions included CPH being a confusing term, too narrow in scope or too clinical. Conclusion: The concept of Clinical Public Health can foster multidisciplinary collaboration to address com-plex health issues because it provides a useful framework for bringing together key disciplines and diverse professional specialties.

In modern society, a huge volume of data (big data) are being collected and accumulated, and growing exponentially.^{1 2} Data come from the internet, social media, medical records, customer databases, massive open data and other data sources. Big data are huge in quantity (volume), fast in production sometimes in real time (velocity), structured and unstructured in data types (variety), inconsistent and changing (variability), uncertain in data quality (veracity) and potentially useful (value).^{3 4}

Setting: This paper documents a participatory process of Health Portfolio staff in the design of a clock, and announces the 2020 Canadian Health Clock, with links to numerous online health calculators. The clock is part of the Health Portfolio’s celebration activities in 2019 of “100 Years of Health”, as the Department of Health was established in Canada in 1919. Intervention: The intervention was the development of a clock on the Government of Canada website with linkage to calculators as a health promotion tool. The clock was built on the concept of the 2004 Chronic Disease Clock, which shows the number of deaths so far today, and so far this year. The clock was developed using a consultative approach, following a review of the original clock. Outcomes: The 2020 clock incorporates new data visualization concepts. New features, facilitated by improved technology, include: expansion to all causes of death; blinking red dots to enhance visual impact; and three clock versions (analogue, featuring a moving circle; digital, table format; and graphical, bar chart format). The clock also provides links to a number of health calculators, to allow people to seek personalized information to improve their health. Implications: The online health clock and health calculators are good examples of innovation in health risk communication tools for effective knowledge translation and dissemination. They inform people about health statistics (clock) and their health (calculators). The clock engages people in the context of the Canadian population, whereas the calculators provide personalized information about improving an individual’s future health.

Objectives. To document the underlying science of how the Pan American Health Organization (PAHO) adapted the Hanlon method, which prioritizes disease control programs, to its wider range of program areas and used it to implement the PAHO Strategic Plan 2014 – 2019. Methods. In 2014, PAHO established a Strategic Plan Advisory Group (SPAG) with representatives from 12 Member States to work closely with the PAHO Technical Team to adapt the Hanlon method to disease and non-disease control programs. Three meetings were held in 2015 – 2016 during which SPAG reviewed existing priority-setting methods, assessed the original Hanlon method and subsequent revisions, and developed the adapted method. This project was initiated by Member States, facilitated by PAHO, and conducted jointly in transparent and horizontal technical cooperation. Results. From the original Hanlon equation, the PAHO-adapted method maintains components A (size of problem), B (seriousness of problem), and C (effectiveness of intervention), drops component D (PEARL – Propriety, Economics, Acceptability, Resources, and Legality), and adds component E (inequity) and F (institutional positioning). The PEARL score was dropped because it serves a purpose for pre-screening process, but not in the priority-setting process for PAHO. Conclusions. The PAHO-adapted Hanlon method provides a refined approach for prioritizing public health programs that include disease and non-disease control areas. The method may be useful for the World Health Organization and country governments with similar needs.

The article titled “The Past, Present, and Future of Public Health Surveillance” [1] was found to contain material from the following published articles. Although they were all cited and some text was quoted, there was inadvertently insufficient use of quotation in the use of these sources, for which the author sincerely apologizes.

American Journal of Public Health (AJPH) from the American Public Health Association (APHA) Period Life Tables for Calculating Life Expectancy: Options to Assess and Minimize the Potential for Bias, an article from American Journal of Public Health, Vol 108 Issue 3

The objective of this concept paper is to describe non-traditional data sources for public health surveillance to enable early identification of health issues, track positive health, and improve responsiveness. This paper brings attention to the use of non-traditional data sources that could supplement traditional public health surveillance and render it useful at local levels, overcoming the challenges of traditional data sources which are often cost prohibitive and have significant time lags.