The SARS-CoV-2 crisis: A crisis of reductionism?

Connections between health research systems and decision-making spaces: lessons from the COVID-19 pandemic in the province of Québec, Canada

The coronavirus 2019 (COVID-19) pandemic allowed for exceptional decision-making power to be placed in the hands of public health departments. Data and information were widely disseminated in the media and on websites. While the improvement of pandemic management is still a learning curve, the ecosystem perspective - that is, the interconnection of academic health research systems and decision-making spaces - has received little attention. In this commentary, we look at the mechanisms in place, or not, in Canada for ensuring decision-making spheres can "speak" to academic research systems. We look at the thick walls that are still in place between health research systems and decision-making spaces. More precisely, we discuss three organizational flaws that we identified in the evidence-informed decision-making ecosystem of Québec and, more broadly, Canada. We introduce some inspiring measures that other countries have implemented to better link evidence and public health decision-making during health crises. The observed flaws and options are related to the vitality of early information sharing relays, the cross-sectional capacity to issue opinions, and the collection and integration of hard and soft data.

SEIR models in the light of Critical Realism - A critique of exaggerated claims about the effectiveness of Covid 19 vaccinations

In a recent modeling study Watson et al. (Lancet Infect Dis 2022;3099:1-10) claim that Covid-19 vaccinations have helped to prevent roughly 14-20 million deaths in 2021. This conclusion is based on an epidemiological susceptible-exposed-infectious-recovered (SEIR) model trained on partially simulated data and yielding a reproduction number distribution which was then applied to a counterfactual scenario in which the efficacy of vaccinations was removed. Drawing on the meta-theory of Critical Realism, we point out several caveats of this model and caution against believing in its predictions. We argue that the absence of vaccinations would have significantly changed the causal tendencies of the system being modelled, yielding a different reproduction number than obtained from training the model on actually observed data. Furthermore, the model omits many important causal factors. Therefore this model, similar to many previous SEIR models, has oversimplified the complex interplay between biomedical, social and cultural dimensions of health and should not be used to guide public health policy. In order to predict the future in epidemic situations more accurately, continuously optimized dynamic causal models which can include the not directly tangible, yet real causal mechanisms affecting public health appear to be a promising alternative to SEIR-type models.

SARS-CoV-2 infection in India bucks the trend: Trained innate immunity?

SARS-CoV-2, the causative agent of COVID-19 pandemic caught the world unawares by its sudden onset in early 2020. Memories of the 1918 Spanish Flu were rekindled raising extreme fear for the virus, but in essence, it was the host and not the virus, which was deciding the outcome of the infection. Age, gender, and preexisting conditions played critical roles in shaping COVID-19 outcome. People of lower socioeconomic strata were disproportionately affected in industrialized countries such as the United States. India, a developing country with more than 1.3 billion population, a large proportion of it being underprivileged and with substandard public health provider infrastructure, feared for the worst outcome given the sheer size and density of its population. Six months into the pandemic, a comparison of COVID-19 morbidity and mortality data between India, the United States, and several European countries, reveal interesting trends. While most developed countries show curves expected for a fast-spreading respiratory virus, India seems to have a slower trajectory. As a consequence, India may have gained on two fronts: the spread of the infection is unusually prolonged, thus leading to a curve that is "naturally flattened"; concomitantly the mortality rate, which is a reflection of the severity of the disease has been relatively low. I hypothesize that trained innate immunity, a new concept in immunology, may be the phenomenon behind this. Biocultural, socioecological, and socioeconomic determinants seem to be influencing the outcome of COVID-19 in different regions/countries of the world.

Public health and expert failure

In a modern democracy, a public health system includes mechanisms for the provision of expert scientific advice to elected officials. The decisions of elected officials generally will be degraded by expert failure, that is, the provision of bad advice. The theory of expert failure suggests that competition among experts generally is the best safeguard against expert failure. Monopoly power of experts increases the chance of expert failure. The risk of expert failure also is greater when scientific advice is provided by only one or a few disciplines. A national government can simulate a competitive market for expert advice by structuring the scientific advice it receives to ensure the production of multiple perspectives from multiple disciplines. I apply these general principles to the United Kingdom's Scientific Advisory Group for Emergencies (SAGE).