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      The effect of COVID-19 on the economy: Evidence from an early adopter of localized lockdowns

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      Journal of Global Health
      International Society of Global Health

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          Abstract

          Background

          Governments worldwide have implemented large-scale non-pharmaceutical interventions, such as social distancing or school closures, to prevent and control the growth of the COVID-19 pandemic. These strategies, implemented with varying stringency, have imposed substantial social and economic costs to society. As some countries begin to reopen and ease mobility restrictions, lockdowns in smaller geographic areas are increasingly considered an attractive policy intervention to mitigate societal costs while controlling epidemic growth. Nevertheless, there is a lack of empirical evidence to support these decisions.

          Methods

          Drawing from a rich data set of localized lockdowns in Chile, we used econometric methods to measure the reduction in local economic activity from lockdowns when applied to smaller or larger geographical areas. We measured economic activity by tax collection at the municipality-level.

          Results

          Our results show that lockdowns were associated with a 10%-15% drop in local economic activity, which is twice the reduction in local economic activity suffered by municipalities that were not under lockdown. A three-to-four-month lockdown had a similar effect on economic activity than a year of the 2009 great recession. We found costs are proportional to the population under lockdown, without differences when lockdowns were measured at the municipality or city-wide levels.

          Conclusions

          Our findings suggest that localized lockdowns have a large effect on local economic activity, but these effects are proportional to the population under lockdown. Our results suggest that epidemiological criteria should guide decisions about the optimal size of lockdown areas since the proportional impact of lockdowns on the economy seems to be unchanged by scale.

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          Most cited references41

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          An interactive web-based dashboard to track COVID-19 in real time

          In December, 2019, a local outbreak of pneumonia of initially unknown cause was detected in Wuhan (Hubei, China), and was quickly determined to be caused by a novel coronavirus, 1 namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The outbreak has since spread to every province of mainland China as well as 27 other countries and regions, with more than 70 000 confirmed cases as of Feb 17, 2020. 2 In response to this ongoing public health emergency, we developed an online interactive dashboard, hosted by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University, Baltimore, MD, USA, to visualise and track reported cases of coronavirus disease 2019 (COVID-19) in real time. The dashboard, first shared publicly on Jan 22, illustrates the location and number of confirmed COVID-19 cases, deaths, and recoveries for all affected countries. It was developed to provide researchers, public health authorities, and the general public with a user-friendly tool to track the outbreak as it unfolds. All data collected and displayed are made freely available, initially through Google Sheets and now through a GitHub repository, along with the feature layers of the dashboard, which are now included in the Esri Living Atlas. The dashboard reports cases at the province level in China; at the city level in the USA, Australia, and Canada; and at the country level otherwise. During Jan 22–31, all data collection and processing were done manually, and updates were typically done twice a day, morning and night (US Eastern Time). As the outbreak evolved, the manual reporting process became unsustainable; therefore, on Feb 1, we adopted a semi-automated living data stream strategy. Our primary data source is DXY, an online platform run by members of the Chinese medical community, which aggregates local media and government reports to provide cumulative totals of COVID-19 cases in near real time at the province level in China and at the country level otherwise. Every 15 min, the cumulative case counts are updated from DXY for all provinces in China and for other affected countries and regions. For countries and regions outside mainland China (including Hong Kong, Macau, and Taiwan), we found DXY cumulative case counts to frequently lag behind other sources; we therefore manually update these case numbers throughout the day when new cases are identified. To identify new cases, we monitor various Twitter feeds, online news services, and direct communication sent through the dashboard. Before manually updating the dashboard, we confirm the case numbers with regional and local health departments, including the respective centres for disease control and prevention (CDC) of China, Taiwan, and Europe, the Hong Kong Department of Health, the Macau Government, and WHO, as well as city-level and state-level health authorities. For city-level case reports in the USA, Australia, and Canada, which we began reporting on Feb 1, we rely on the US CDC, the government of Canada, the Australian Government Department of Health, and various state or territory health authorities. All manual updates (for countries and regions outside mainland China) are coordinated by a team at Johns Hopkins University. The case data reported on the dashboard aligns with the daily Chinese CDC 3 and WHO situation reports 2 for within and outside of mainland China, respectively (figure ). Furthermore, the dashboard is particularly effective at capturing the timing of the first reported case of COVID-19 in new countries or regions (appendix). With the exception of Australia, Hong Kong, and Italy, the CSSE at Johns Hopkins University has reported newly infected countries ahead of WHO, with Hong Kong and Italy reported within hours of the corresponding WHO situation report. Figure Comparison of COVID-19 case reporting from different sources Daily cumulative case numbers (starting Jan 22, 2020) reported by the Johns Hopkins University Center for Systems Science and Engineering (CSSE), WHO situation reports, and the Chinese Center for Disease Control and Prevention (Chinese CDC) for within (A) and outside (B) mainland China. Given the popularity and impact of the dashboard to date, we plan to continue hosting and managing the tool throughout the entirety of the COVID-19 outbreak and to build out its capabilities to establish a standing tool to monitor and report on future outbreaks. We believe our efforts are crucial to help inform modelling efforts and control measures during the earliest stages of the outbreak.
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            Pathophysiology, Transmission, Diagnosis, and Treatment of Coronavirus Disease 2019 (COVID-19): A Review

            The coronavirus disease 2019 (COVID-19) pandemic, due to the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused a worldwide sudden and substantial increase in hospitalizations for pneumonia with multiorgan disease. This review discusses current evidence regarding the pathophysiology, transmission, diagnosis, and management of COVID-19.
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              Using social and behavioural science to support COVID-19 pandemic response

              The COVID-19 pandemic represents a massive global health crisis. Because the crisis requires large-scale behaviour change and places significant psychological burdens on individuals, insights from the social and behavioural sciences can be used to help align human behaviour with the recommendations of epidemiologists and public health experts. Here we discuss evidence from a selection of research topics relevant to pandemics, including work on navigating threats, social and cultural influences on behaviour, science communication, moral decision-making, leadership, and stress and coping. In each section, we note the nature and quality of prior research, including uncertainty and unsettled issues. We identify several insights for effective response to the COVID-19 pandemic and highlight important gaps researchers should move quickly to fill in the coming weeks and months.
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                Author and article information

                Journal
                J Glob Health
                J Glob Health
                JGH
                Journal of Global Health
                International Society of Global Health
                2047-2978
                2047-2986
                16 January 2021
                2021
                : 11
                : 05002
                Affiliations
                [1 ]Escuela de Gobierno, Pontificia Universidad Católica de Chile, Santiago, Región Metropolitana, Chile
                [2 ]Centre for Sustainable Urban Development (CEDEUS), Chile
                [3 ]Millennium Nucleus for the Study of the Life Course and Vulnerability (MLIV), Santiago, Chile
                [4 ]Millennium Initiative for Collaborative Research in Bacterial Resistance (MICROB-R), Santiago, Chile
                [5 ]Research Center for Integrated Disaster Risk Management (CIGIDEN), Santiago, Chile
                [6 ]Business School, Universidad Adolfo Ibáñez, Santiago, Chile
                [7 ]Growth Lab, Center for International Development, Harvard, Cambridge, Massachusetts, USA
                Author notes
                Correspondence to:
Eduardo A. Undurraga
Escuela de Gobierno
Pontificia Universidad Católica de Chile
Vicuña Mackenna 4860
Macul CP 7820436
Región Metropolitana
Chile
 eundurra@ 123456uc.cl
                Article
                jogh-11-05002
                10.7189/jogh.10.05002
                7897430
                e06bd373-b305-4f85-aa6a-12a8b8a5f112
                Copyright © 2021 by the Journal of Global Health. All rights reserved.

                This work is licensed under a Creative Commons Attribution 4.0 International License.

                History
                Page count
                Figures: 4, Tables: 3, Equations: 2, References: 62, Pages: 11
                Categories
                Research Theme 1: COVID-19 Pandemic

                Public health
                Public health

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