With a low 0.05% recovery rate, the United Kingdom has no immediate plans to reopen. Last but not least, people in these countries are cautiously remaining indoors as their governments continue to work on crisis response. As a result, it has opted to keep its activity to a minimum to try and boost the 65% recovery rate, even as it slowly emerges from over 10 weeks of lockdown. Italy, the once-epicenter for the crisis in Europe is understandably wary of cases rising back up to critical levels. Low Mobility, High RecoveryĬountries in this quadrant are playing it safe, and holding off on reopening their economies until the population has fully recovered. On May 28th, for example, the country had 24,151 new cases and 1,067 new deaths. After deferring lockdown decisions to state and local levels, the country is now averaging the highest number of daily cases out of any country. Some countries have loosened lockdown measures, while others did not have strict measures in place to begin with.īrazil is an interesting case study to consider here. High Mobility, Low Recoveryĭespite low COVID-19 related recoveries, mobility rates of countries in this quadrant remain higher than average. After almost 50 days of lockdown, the government is recommending a flexible four-day work week to boost the economy back up. This has resulted in a 98% recovery rate, the highest of all countries. New Zealand has earned praise for its early and effective pandemic response, allowing it to curtail the total number of cases. High recovery rates are resulting in lifted restrictions for countries in this quadrant, and people are steadily returning to work. In the main scatterplot visualization, we’ve taken things a step further, assigning these countries into four distinct quadrants: 1. Here’s how these countries fare based on the above metrics. In most cases, mobility rate also correlates with a higher rate of recovered people in the population. In general, the higher the mobility rate, the more economic activity this signifies. Note that China does not show up in the graphic as the government bans Google services.ĬOVID-19 recovery rates rely on values from CoronaTracker, using aggregated information from multiple global and governmental databases such as WHO and CDC. The number of recovered cases in a country is measured as the percentage of total cases.ĭata for the first measure comes from Google’s COVID-19 Community Mobility Reports, which relies on aggregated, anonymous location history data from individuals. This refers to the change in activity around workplaces, subtracting activity around residences, measured as a percentage deviation from the baseline. Today’s chart measures the extent to which 41 major economies are reopening, by plotting two metrics for each country: the mobility rate and the COVID-19 recovery rate: The Road to Recovery: Which Economies are Reopening?ĬOVID-19 has brought the world to a halt-but after months of uncertainty, it seems that the situation is slowly taking a turn for the better. With the effects of automation expected to be felt in OECD countries by the mid-2020s, it’s likely we won’t have to wait long to see how things shake out this time around. Many jobs were lost in key sectors like manufacturing and farming, but they’ve been replaced (so far) with new jobs in other sectors. In the timeframe of 1850 to 2015, it’s clear that new technologies came in and disrupted the prevailing industries. job picture remains unclear, this above data series does provide some comfort – after all, history doesn’t always repeat, but it often rhymes. While the eventual impact of AI and automation on the U.S. That’s because today, they add up to fewer than 13% of the total jobs that exist in the country, and it’s likely these shares will continue to decline as time passes. Of course, for any prospective job seeker in the modern era, it’s rare to see jobs advertised in either of these sectors. By the year 1960, the high-flying manufacturing sector eventually peaked at a share of 26% of all American jobs. Much later on, in the mid-20th century, factories took the country by storm. The agricultural sector was king in 1850, providing a whopping 60% of all U.S. Here is a recap of the data, by sector: SectorĮmployment share change, 1850-2015 (Percentage points) employment by sector between the years of 18. Today’s chart uses data from the McKinsey Global Institute that shows U.S. While no one knows the outcome for sure, what is clear is how the job distribution has changed over time: as jobs in agriculture and manufacturing have disappeared, new jobs have materialized in other sectors. It’s a fair question, and it’s certainly one that is a hot topic of debate among experts trying to figure out the ultimate impact of AI and automation on the global economy.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |