From cause and effect to causes and effects.

It is now-at least loosely-acknowledged that most health and clinical outcomes are influenced by different interacting causes. Surprisingly, medical research studies are nearly universally designed to study-usually in a binary way-the effect of a single cause. Recent experiences during the coronavirus disease 2019 pandemic brought to the forefront that most of our challenges in medicine and healthcare deal with systemic, that is, interdependent and interconnected problems. Understanding these problems defy simplistic dichotomous research methodologies. These insights demand a shift in our thinking from 'cause and effect' to 'causes and effects' since this transcends the classical way of Cartesian reductionist thinking. We require a shift to a 'causes and effects' frame so we can choose the research methodology that reflects the relationships between variables of interest-one-to-one, one-to-many, many-to-one or many-to-many. One-to-one (or cause and effect) relationships are amenable to the traditional randomized control trial design, while all others require systemic designs to understand 'causes and effects'. Researchers urgently need to re-evaluate their science models and embrace research designs that allow an exploration of the clinically obvious multiple 'causes and effects' on health and disease. Clinical examples highlight the application of various systemic research methodologies and demonstrate how 'causes and effects' explain the heterogeneity of clinical outcomes. This shift in scientific thinking will allow us to find the necessary personalized or precise clinical interventions that address the underlying reasons for the variability of clinical outcomes and will contribute to greater health equity.

COVID-19 - An Opportunity to Redesign Health Policy Thinking.

Coronavirus disease 2019 (COVID-19) dramatically unveiled the fragile state of the world's health and social systems - the lack of emergency health crisis preparedness (under-resourced, weak leadership, strategic plans without clear lines of authority), siloed policy frameworks (focus on individual diseases and the lack of integration of health into the whole of societal activity and its impact on individual as well as community well-being and prosperity), and unclear communication (misguided rationale of policies, inconsistent interpretation of data). The net result is fear - about the disease, about risks and survival, and about economic security. We discuss the interdependencies among these domains and their emergent dynamics and emphasise the need for a robust distributed health system and for transparent communication as the basis for trust in the system. We conclude that systems thinking and complexity sciences should inform the redesign of strong health systems urgently to respond to the current health crisis and over time to build healthy, resilient, and productive communities.