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A daily fever curve for the Swiss economy.

ABSTRACT: Because macroeconomic data is published with a substantial delay, assessing the health of the economy during the rapidly evolving COVID-19 crisis is challenging. We develop a fever curve for the Swiss economy using publicly available daily financial market and news data. The indicator can be computed with a delay of 1 day. Moreover, it is highly correlated with macroeconomic data and survey indicators of Swiss economic activity. Therefore, it provides timely and reliable warning signals if the health of the economy takes a turn for the worse.

SUBMITTER: Burri M

PROVIDER: S-EPMC7347051 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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A daily fever curve for the Swiss economy.

Burri Marc M Kaufmann Daniel D

Swiss journal of economics and statistics 20200709 1

Because macroeconomic data is published with a substantial delay, assessing the health of the economy during the rapidly evolving COVID-19 crisis is challenging. We develop a fever curve for the Swiss economy using publicly available daily financial market and news data. The indicator can be computed with a delay of 1 day. Moreover, it is highly correlated with macroeconomic data and survey indicators of Swiss economic activity. Therefore, it provides timely and reliable warning signals if the h ...[more]

PMID: 32835026

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Project description:Defined Daily Doses (DDD) and Defined Course Doses (DCD) have been established in both human and veterinary medicine in order to standardize the measurement of treatments in a population. In 2016 the European Medicines Agency published average defined daily dose (DDDvet) and defined course dose (DCDvet) values for antimicrobial agents used in livestock production. Similarly, national defined doses (DDDch and DCDch) for the pig sector in Switzerland have recently been determined. The aim of this study was to compare the outcome of calculating antimicrobial consumption based on either DDDvet/DCDvet or DDDch/DCDch. Data from 227 Swiss pig farms describing antimicrobial use in 2015 was collected. The numbers of treatment days and treatments were calculated using DDDvet/DCDvet and DDDch/DCDch respectively, for each farm in total and for different antimicrobial classes. Associations between calculated numbers of DDDvet/DCDvet and DDDch/DCDch on farm level were investigated. In addition, differences concerning antimicrobial use were investigated between different production types of farms (piglet-producer, finishing farm or farrow-to-finishing farm). Using DDDch/DCDch values we calculated 1,805,494 treatment days and 433,678 treatments compared to 1,456,771 treatment days (19% ratio) and 303,913 treatments (30% ratio) based on DDDvet/DCDvet. Penicillins (21.4/26.6%), polypeptides (18.6/27.6%) and fluoroquinolones (9.5/8.8%) were the most frequently used classes of antimicrobials based on calculation using both DDDch and DDDvet. Similar findings were observed for complete treatments (DCDch/vet) (penicillins: 52.8/39.6%; polypeptides: 7.8/14.2%; fluoroquinolones: 13.2/12.9%). The number of treatment days or treatments per farm was higher for piglet-producers and farrow-to-finishing farms compared to finisher farms regardless of whether Swiss or European DDD or DCD values were used for the calculation (each P < 0.001). Similar results for antimicrobial use (AMU) obtained at farm level were observed when calculated either by Swiss or European definitions. Nevertheless, marked differences could be observed in the assessment of the use of specific antimicrobial classes in the field based on DDDvet/DCDvet compared to DDDch/DCDch.

Project description:BackgroundVariations in hospitals' care demand relies not only on the patient volume but also on the disease severity. Understanding both daily severity and patient volume in hospitals could help to identify hospital pressure zones to improve hospital-capacity planning and policy-making.ObjectiveThis longitudinal study explored daily care demand dynamics in Swiss general hospitals for 3 measures: (1) capacity utilization, (2) patient turnover, and (3) patient clinical complexity level.MethodsA retrospective population-based analysis was conducted with 1 year of routine data of 1.2 million inpatients from 102 Swiss general hospitals. Capacity utilization was measured as a percentage of the daily maximum number of inpatients. Patient turnover was measured as a percentage of the daily sum of admissions and discharges per hospital. Patient clinical complexity level was measured as the average daily patient disease severity per hospital from the clinical complexity algorithm.ResultsThere was a pronounced variability of care demand in Swiss general hospitals. Among hospitals, the average daily capacity utilization ranged from 57.8% (95% CI 57.3-58.4) to 87.7% (95% CI 87.3-88.0), patient turnover ranged from 22.5% (95% CI 22.1-22.8) to 34.5% (95% CI 34.3-34.7), and the mean patient clinical complexity level ranged from 1.26 (95% CI 1.25-1.27) to 2.06 (95% CI 2.05-2.07). Moreover, both within and between hospitals, all 3 measures varied distinctly between days of the year, between days of the week, between weekdays and weekends, and between seasons.ConclusionsWhile admissions and discharges drive capacity utilization and patient turnover variation, disease severity of each patient drives patient clinical complexity level. Monitoring-and, if possible, anticipating-daily care demand fluctuations is key to managing hospital pressure zones. This study provides a pathway for identifying patients' daily exposure to strained hospital systems for a time-varying causal model.

Project description:BackgroundAs universal health coverage becomes the norm in many countries, it is important to determine public priorities regarding benefits to include in health insurance coverage. We report results of participation in a decision exercise among residents of Switzerland, a high-income country with a long history of universal health insurance and deliberative democracy.MethodsWe adapted the Choosing Healthplans All Together (CHAT) tool, an exercise developed to transform complex healthcare allocation decisions into easily understandable choices, for use in Switzerland. We conducted CHAT exercises in twelve Swiss cities with recruitment from a range of socio-economic backgrounds, taking into account differences in language and culture.ResultsCompared to existing coverage, a majority of 175 participants accepted greater general practice gatekeeping (94%), exclusion of invasive life-sustaining measures in dying patients (80%), longer waiting times for non-urgent episodic care (78%), greater adherence to cost-effectiveness guidelines in chronic care (66%), and lower premium subsidies (51%). Most initially chose greater coverage for dental care (59%), quality of life (57%), and long-term care (90%). During group deliberations, participants increased coverage for out-of-pocket costs (58%) and mental health to current levels (41%) and beyond current levels for rehabilitation (50%), and decreased coverage for quality of life to current levels (74%). Following group deliberation, they tended to change their views back to below current coverage for help with out-of-pocket costs, and back to current levels for rehabilitation. Most participants accepted the plan as appropriate and fair. A significant number would have added nothing.ConclusionSwiss participants who have engaged in a priority setting exercise accept complex resource allocation trade-offs in healthcare coverage. Moreover, in the context of a well-funded healthcare system with universal coverage centered on individual choice, at least some of our participants believed a fully sufficient threshold of health insurance coverage was achieved.

Dataset Information

A daily fever curve for the Swiss economy.

Publications

A daily fever curve for the Swiss economy.

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