Decisions to shutdown economic activities to control the spread of COVID-19 early in the pandemic remain controversial, with negative impacts including high rates of unemployment. Here we present a counterfactual scenario for the state of California in which the economy remained open and active during the pandemic’s first year. The exercise provides a baseline against which to compare actual levels of job losses. We developed an economic-epidemiological mathematical model to simulate outbreaks of COVID-19 in ten large Californian socio-economic areas. Results show that job losses are an unavoidable consequence of the pandemic, because even in an open economy, debilitating illness and death among workers drive economic downturns. Although job losses in the counterfactual scenario were predicted to be less than those actually experienced, the cost would have been the additional death or disablement of tens of thousands of workers. Furthermore, whereas an open economy would have favoured populous, services-oriented coastal areas in terms of employment, the opposite would have been true of smaller inland areas and those with relatively larger agricultural sectors. Thus, in addition to the greater cost in lives, the benefits of maintaining economic activity would have been unequally distributed, exacerbating other realized social inequities of the disease’s impact.

The number of small and medium-sized enterprises in the United States was forecast to continuously decrease between 2024 and 2029 by in total 6.7 thousand enterprises (-2.24 percent). After the fourteenth consecutive decreasing year, the number is estimated to reach 291.94 thousand enterprises and therefore a new minimum in 2029. According to the OECD an enterprise is defined as the smallest combination of legal units, which is an organisational unit producing services or goods, that benefits from a degree of autonomy with regards to the allocation of resources and decision making. Shown here are small and medium-sized enterprises, which are defined as companies with 1-249 employees.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in more than 150 countries and regions worldwide. All input data are sourced from international institutions, national statistical offices, and trade associations. All data has been are processed to generate comparable datasets (see supplementary notes under details for more information).

Decisions to shutdown economic activities to control the spread of COVID-19 early in the pandemic remain controversial, with negative impacts including high rates of unemployment. Here we present a counterfactual scenario for the state of California in which the economy remained open and active during the pandemic’s first year. The exercise provides a baseline against which to compare actual levels of job losses. We developed an economic-epidemiological mathematical model to simulate outbreaks of COVID-19 in ten large Californian socio-economic areas. Results show that job losses are an unavoidable consequence of the pandemic, because even in an open economy, debilitating illness and death among workers drive economic downturns. Although job losses in the counterfactual scenario were predicted to be less than those actually experienced, the cost would have been the additional death or disablement of tens of thousands of workers. Furthermore, whereas an open economy would have favoured populous, services-oriented coastal areas in terms of employment, the opposite would have been true of smaller inland areas and those with relatively larger agricultural sectors. Thus, in addition to the greater cost in lives, the benefits of maintaining economic activity would have been unequally distributed, exacerbating other realized social inequities of the disease’s impact.

The total amount of data created, captured, copied, and consumed globally is forecast to increase rapidly, reaching 149 zettabytes in 2024. Over the next five years up to 2028, global data creation is projected to grow to more than 394 zettabytes. In 2020, the amount of data created and replicated reached a new high. The growth was higher than previously expected, caused by the increased demand due to the COVID-19 pandemic, as more people worked and learned from home and used home entertainment options more often. Storage capacity also growing Only a small percentage of this newly created data is kept though, as just two percent of the data produced and consumed in 2020 was saved and retained into 2021. In line with the strong growth of the data volume, the installed base of storage capacity is forecast to increase, growing at a compound annual growth rate of 19.2 percent over the forecast period from 2020 to 2025. In 2020, the installed base of storage capacity reached 6.7 zettabytes.