The term resilience has dominated the discourse among health systems researchers since 2014 and the onset of the Ebola outbreak in West Africa. There is wide consensus that the global community has to help build more resilient health systems. But do we really know what resilience means, and do we all have the same vision of resilience? The present paper presents a new conceptual framework on governance of resilience based on systems thinking and complexity theories. In this paper, we see resilience of a health system as its capacity to absorb, adapt and transform when exposed to a shock such as a pandemic, natural disaster or armed conflict and still retain the same control over its structure and functions.
Objectives To evaluate which non-pharmaceutical interventions (NPIs) have been more and less effective in controlling the COVID-19 pandemic. Methods We performed a systematic review of published and unpublished empirical studies, either observational or interventional, analysing the comparative effectiveness of NPIs against the COVID-19 pandemic. We searched Embase/Medline and medRxiv to identify the relevant literature. Results We identified 34 studies. During the first wave of the COVID-19 pandemic, school closing was the most effective NPI, followed by workplace closing, business and venue closing and public event bans. Public information campaigns and mask wearing requirements were also effective in controlling the pandemic while being less disruptive for the population than other NPIs. There was no evidence on the effectiveness of public transport closure, testing and contact tracing strategies and quarantining or isolation of individuals. Early implementation was associated with a higher effectiveness in reducing COVID-19 cases and deaths, while general stringency of the NPIs was not. Conclusions In this systematic review, we found that school closing, followed by workplace closing, business and venue closing and public event bans were the most effective NPIs in controlling the spread of COVID-19. An early response and a combination of specific social distancing measures are effective at reducing COVID-19 cases and deaths. Continuous monitoring of NPIs effectiveness is needed in order to adapt decision making.
The last months have left no-one in doubt that the COVID-19 pandemic is exerting enormous pressure on health systems around the world, bringing to light the sub-optimal resilience of even those classified as high-performing. This makes us re-think the extent to which we are using the appropriate metrics in evaluating health systems which, in the case of this pandemic, might have masked how unprepared some countries were. It also makes us reflect on the strength of our solidarity as a global community, as we observe that global health protection remains, as this pandemic shows, focused on protecting high income countries from public health threats originating in low and middle income countries. To change this course, and in times like this, all nations should come together under one umbrella to respond to the pandemic by sharing intellectual, human, and material resources. In order to work towards stronger and better prepared health systems, improved and resilience-relevant metrics are needed. Further, a new model of development assistance for health, one that is focused on stronger and more resilient health systems, should be the world’s top priority.
We estimated the impact of a comprehensive set of non-pharmeceutical interventions on the COVID-19 epidemic growth rate across the 37 member states of the Organisation for Economic Co-operation and Development during the early phase of the COVID-19 pandemic and between October and December 2020. For this task, we conducted a data-driven, longitudinal analysis using a multilevel modelling approach with both maximum likelihood and Bayesian estimation. We found that during the early phase of the epidemic: implementing restrictions on gatherings of more than 100 people, between 11 and 100 people, and 10 people or less was associated with a respective average reduction of 2.58%, 2.78% and 2.81% in the daily growth rate in weekly confirmed cases; requiring closing for some sectors or for all but essential workplaces with an average reduction of 1.51% and 1.78%; requiring closing of some school levels or all school levels with an average reduction of 1.12% or 1.65%; recommending mask wearing with an average reduction of 0.45%, requiring mask wearing country-wide in specific public spaces or in specific geographical areas within the country with an average reduction of 0.44%, requiring mask-wearing country-wide in all public places or all public places where social distancing is not possible with an average reduction of 0.96%; and number of tests per thousand population with an average reduction of 0.02% per unit increase. Between October and December 2020 work closing requirements and testing policy were significant predictors of the epidemic growth rate. These findings provide evidence to support policy decision-making regarding which NPIs to implement to control the spread of the COVID-19 pandemic.
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