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At the present time it is clear that our global healthcare community was not prepared to face the COVID-19 pandemic. Hospitals in the hardest hit areas have been transformed to COVID centres. Surgical societies have recommended postponing non-emergency surgery, and have given recommendations for triaging the ever- growing backlog of patients. However, simply resuming these non-emergency surgeries may lead the healthcare system into a second disaster. If healthcare policymakers around the world do not systematically consider how to resume normal surgical services, hospitals will be quickly overwhelmed, vital resources will be depleted, and patients and providers alike will face an increased exposure risk. This perspective serves to highlight certain aspects of returning to normal that physicians and hospital administrators alike must consider to avoid potential catastrophe.

We examine the net benefits of social distancing to slow the spread of COVID-19 in USA. Social distancing saves lives but imposes large costs on society due to reduced economic activity. We use epidemiological and economic forecasting to perform a rapid benefit–cost analysis of controlling the COVID-19 outbreak. Assuming that social distancing measures can substantially reduce contacts among individuals, we find net benefits of about $5.2 trillion in our benchmark case. We examine the magnitude of the critical parameters that might imply negative net benefits, including the value of statistical life and the discount rate. A key unknown factor is the speed of economic recovery with and without social distancing measures in place. A series of robustness checks also highlight the key role of the value of mortality risk reductions and discounting in the analysis and point to a need for effective economic stimulus when the outbreak has passed.

The COVID-19 pandemic has dramatically impacted lifestyle behaviour as public health initiatives aim to "flatten the curve". This study examined changes in activity patterns (physical activity, sedentary time, sleep), recreational physical activities, diet, weight and wellbeing from before to during COVID-19 restrictions in Adelaide, Australia. This study used data from a prospective cohort of Australian adults (parents of primary school-aged children; n = 61, 66% female, aged 41±6 years). Participants wore a Fitbit Charge 3 activity monitor and weighed themselves daily using Wi-Fi scales. Activity and weight data were extracted for 14 days before (February 2020) and 14 days during (April 2020) COVID-19 restrictions. Participants reported their recreational physical activity, diet and wellbeing during these periods. Linear mixed effects models were used to examine change over time. Participants slept 27 minutes longer (95% CI 9-51), got up 38 minutes later (95% CI 25-50), and did 50 fewer minutes (95% CI -69-29) of light physical activity during COVID-19 restrictions. Additionally, participants engaged in more cycling but less swimming, team sports and boating or sailing. Participants consumed a lower percentage of energy from protein (-0.8, 95% CI-1.5-0.1) and a greater percentage of energy from alcohol (0.9, 95% CI 0.2-1.7). There were no changes in weight or wellbeing. Overall, the effects of COVID-19 restrictions on lifestyle were small; however, their impact on health and wellbeing may accumulate over time. Further research examining the effects of ongoing social distancing restrictions are needed as the pandemic continues Refereed/Peer-reviewed

This paper outlines computer modeling algorithms designed to predict and forecast a COVID-19. In this paper, we consider a deterministic model. Theongoing COVID-19 epidemic quickly spread across the globe. Significant behavioural, social initiatives to limit city transport, case identification and touch tracking, quarantine, advice, and knowledge to the public, creation of detection kits, etc. and state measures were conducted to reduce the epidemic and eliminate coronavirus persistence in humans around theworld from stopping the global coronavirus outbreak. In this paper, we propose a basic SIR epidemic model to show a simulation, the MATLAB algorithm using bouncing dots to depict safe and sick people to simulate infection spread. The graphical model shown here is implemented using MATLAB package version 3.0. In this paper, we discuss the importance of models because they help one explore what could happen. They demonstrate how different possible futures might be shaped by what we are doing now. We can examine the effects of specific interventions in different ways such as quarantine or a lockdown & explore how simulations may predict, how infectious diseases advanced to show the possible result of an outbreak, and better guide initiatives in public health regarding the pandemic response andpandemic past including an overview of the key characteristics of adverse pandemic consequences and epidemic outbreak., CARDIOMETRY, ������������ 20 2021, Pages 126-134

The COVID-19 pandemic has affected 20 million people worldwide with over 732,000 deaths and trillions of dollars of lost economic productivity. It has put many countries into lockdown to contain the virus and save lives. As COVID-19 cases in some countries start to plateau and societies work hard to ‘flatten the curve’, leaders are being asked to formulate plans for safe and staged ‘exit strategies’ to reopen society. Each country will decide on their own exit strategy but many plans are considering similar vital healthcare principles including the maintenance of social distancing to prevent ongoing community transmission, testing capacity, protection of the healthcare systems and the health of their care workers. This review aims to provide an overview of essential factors that plans for exit strategy should consider and their effect on the societies' social and healthcare life., Highlights • Exit strategies following COVID-19 are being formulated with guidelines to ensure society returns to ‘normality’ safely. • Exit strategies are taken a phased approach to end lockdown following COVID-19. • Exit strategies should consider ongoing community transmission, testing capacity and protection of the healthcare systems.

This literature-based article found that on 08 June 2020, New Zealand claimed victory over coronavirus disease 2019 (COVID-19) mainly because of effective non-pharmaceutical strategies and interventions that included a hard lockdown. The response was informed by the country’s Influenza Pandemic Plan (although without criticism), which was updated in 2017, and the swift responses from political leadership and other key stakeholders. Strategies instituted included the proclamation of urgent precautionary measures leading to border closures, issuing of a 3-month-long COVID-19 notice under the Epidemic Preparedness Act 2006, the proclamation of the COVID-19 Elimination Strategy and the Initial COVID-19 Māori Response Action Plan, which incorporated COVID-19 Alert Levels that facilitated stepwise easing of the hard lockdown. The non-pharmaceutical strategies seem to have worked again, even as the second wave of COVID-19 infections returned in August 2020 through an Auckland cluster. Hence, the New Zealand case remains one that the world can draw lessons from, although not perfect.

Depuis le début de l’épidémie, nous sommes collectivement pris dans une double avalanche : un flot ininterrompu de chiffres (décompte quotidien des morts, tentatives de mesure de la surmortalité liée au Covid-19, projections et estimations sur l’évolution pandémique par des modèles divers, élaboration d’indicateurs permettant de comprendre la diversité des réactions et réactivités nationales, etc.), mais aussi de tribunes, billets, tweets et autres publications rapides émanant non seulement des éditorialistes rompus à l’exercice du commentaire d’actualité mais aussi de chercheuses et chercheurs en sciences sociales. Ces deux flux se rencontrent parfois autour d’une question dont nous avons fait, depuis quelques années, avec d’autres collègues, un objet de recherches : celle des liens entre nombres et gouvernement. En quoi est-il nécessaire de quantifier pour décrire, comprendre, prévoir et faire face à l’épidémie ? Sous quelles conditions et jusqu’à quel point les opérations de quantification peuvent-elles constituer un danger pour les populations ? Peut-on y voir un simple instrument de manipulation et de coercition aux mains du pouvoir ? Le temps des sciences sociales, et de l’histoire en particulier, n’est pas celui de la médecine d’urgence ou de l’épidémiologie de crise. Il nous semble scientifiquement et déontologiquement prématuré de développer des analyses définitives sur la crise que traverse actuellement la planète, notamment en prétendant porter un regard péremptoire sur la valeur des “chiffres du Covid-19” et le rôle qu’ils jouent dans la mise en place de politiques publiques et la gestion des populations qu’elles engagent. Pourtant, cela n’interdit pas de montrer en quoi certaines assertions qui circulent dans l’espace public paraissent particulièrement problématiques sur les plans intellectuel, politique, voire pratique sur la double question de la construction et de l’usage de données quantitatives. Si nous réservons nos analyses empiriques pour un temps plus apaisé, après avoir pris le recul qui s’impose pour une enquête systématique, nous souhaitons à travers cette contribution rappeler qu’il existe un vaste champ de recherches en histoire sociale et sociologie de la quantification, et qu’il n’est pas possible de s’en tenir à l’indignation, ni de clore la réflexion par des formules catégoriques, des amalgames ou des sophismes. En partant de quelques publications récentes de natures diverses (tribunes, entretiens…), principalement en langues anglaise et française (mais aussi espagnole et italienne), nous défendrons une approche de la quantification par l’histoire et les sciences sociales qui ne saurait se limiter à une association automatique entre des nombres, jugés forcément faux, et la décision publique, dénoncée comme forcément liberticide.

Depuis le début de l’épidémie, nous sommes collectivement pris dans une double avalanche : un flot ininterrompu de chiffres (décompte quotidien des morts, tentatives de mesure de la surmortalité liée au Covid-19, projections et estimations sur l’évolution pandémique par des modèles divers, élaboration d’indicateurs permettant de comprendre la diversité des réactions et réactivités nationales, etc.), mais aussi de tribunes, billets, tweets et autres publications rapides émanant non seulement des éditorialistes rompus à l’exercice du commentaire d’actualité mais aussi de chercheuses et chercheurs en sciences sociales. Ces deux flux se rencontrent parfois autour d’une question dont nous avons fait, depuis quelques années, avec d’autres collègues, un objet de recherches : celle des liens entre nombres et gouvernement. En quoi est-il nécessaire de quantifier pour décrire, comprendre, prévoir et faire face à l’épidémie ? Sous quelles conditions et jusqu’à quel point les opérations de quantification peuvent-elles constituer un danger pour les populations ? Peut-on y voir un simple instrument de manipulation et de coercition aux mains du pouvoir ? Le temps des sciences sociales, et de l’histoire en particulier, n’est pas celui de la médecine d’urgence ou de l’épidémiologie de crise. Il nous semble scientifiquement et déontologiquement prématuré de développer des analyses définitives sur la crise que traverse actuellement la planète, notamment en prétendant porter un regard péremptoire sur la valeur des “chiffres du Covid-19” et le rôle qu’ils jouent dans la mise en place de politiques publiques et la gestion des populations qu’elles engagent. Pourtant, cela n’interdit pas de montrer en quoi certaines assertions qui circulent dans l’espace public paraissent particulièrement problématiques sur les plans intellectuel, politique, voire pratique sur la double question de la construction et de l’usage de données quantitatives. Si nous réservons nos analyses empiriques pour un temps plus apaisé, après avoir pris le recul qui s’impose pour une enquête systématique, nous souhaitons à travers cette contribution rappeler qu’il existe un vaste champ de recherches en histoire sociale et sociologie de la quantification, et qu’il n’est pas possible de s’en tenir à l’indignation, ni de clore la réflexion par des formules catégoriques, des amalgames ou des sophismes. En partant de quelques publications récentes de natures diverses (tribunes, entretiens…), principalement en langues anglaise et française (mais aussi espagnole et italienne), nous défendrons une approche de la quantification par l’histoire et les sciences sociales qui ne saurait se limiter à une association automatique entre des nombres, jugés forcément faux, et la décision publique, dénoncée comme forcément liberticide.

Author(s): Villas-Boas, Sofia B; Sears, James; Villas-Boas, Miguel; Villas-Boas, Vasco | Abstract: The recent spread of COVID-19 across the U.S. led to concerted efforts by states to ``flatten the curve" through the adoption of stay-at-home mandates that encourage individuals to reduce travel and maintain social distance. Combining data on changes in travel activity with COVID-19 health outcomes and state policy adoption timing, we characterize nationwide changes in mobility patterns and isolate the portion attributable to statewide mandates. We find evidence of dramatic nationwide declines in mobility prior to adoption of any statewide mandates. Once states adopt a mandate, we estimate further mandate-induced declines between 2.1 and 7.0 percentage points across methods that account for states' differences in travel behavior prior to policy adoption. In addition, we investigate the effects of stay-at-home mandates on changes in COVID-19 health outcomes while controlling for pre-trends and observed pre-treatment mobility patterns. We estimate mandate-induced declines between 0.13 and 0.17 in deaths (5.6 to 6.0 in hospitalizations) per 100 thousand across methods. Across 43 adopting states, this represents 23,366-30,144 fewer deaths (and roughly one million averted hospitalizations) for the months of March and April - which indicates that death rates could have been 42-54% higher had states not adopted statewide policies. We further find evidence that changes in mobility patterns prior to adoption of statewide policies also played a role in reducing COVID-19 mortality and morbidity. Adding in averted deaths due to pre-mandate social distancing behavior, we estimate a total of 48-71,000 averted deaths from COVID-19 for the two-month period. Given that the actual COVID-19 death toll for March and April was 55,922, our estimates suggest that deaths would have been 1.86-2.27 times what they were absent any stay-at-home mandates during this period. These estimates represent a lower bound on the health impacts of stay-at-home policies, as they do not account for spillovers or undercounting of COVID-19 mortality. Our findings indicate that early behavior changes and later statewide policies reduced death rates and helped attenuate the negative consequences of COVID-19. Further, our findings of substantial reductions in mobility prior to state-level policies convey important policy implications for re-opening.Take Away Linknhttps://are.berkeley.edu/sites/are.berkeley.edu/files/PolicyTakeAway_Web.pdf

COVID-19 is a matter of common European interest since its very first detection on the continent. Yet this pandemic outbreak has largely been handled as an essentially national matter.This article makes a first attempt at unpacking how such fragmented, uncoordinated national responses to COVID19 came into being under the EU legal order. To do so, it systematizes the European response into separate stages. Phase 1 – the emergency – has been characterized by the adoption of national emergency risk management measures that, albeit country specific, were inspired by a common objective of pandemic suppression, i.e. to reduce disease transmission and thereby diminishing pressure on health services, under the by now well-known ‘flatten the curve’ imperative. Phase 2 – the lifting – is about the attempt at relaxing some of the national risk responses in a coordinated fashion to avoid creating negative spillovers or distortions – be they sanitary and/or financial – across the Union.The article argues that contrary to conventional wisdom the resulting uncoordinated EU response to Covid-19 shouldn’t be seen as the inevitable consequence of the EU’s limited competence in public health. Against this backdrop, it strives to define the regulatory policy framework that might be governing the next phases of the European risk management response to this pandemic as they will emerge from a widely undefined yet unescapable dialectic between the Union and its member states. Ultimately, it predicts that by testing the outer limits of the EU public health competence COVID-19 is set to go down in history as a major catalyst in the advancement of EU health emergency action.