Up to ** percent of businesses were completely closed in January 2021, of which only *** percent remained shut down since the outbreak of the coronavirus (COVID-19). Up to ** percent of those also closed for at least *** month between June and December of the previous year, while the rest opened in December but closed again in January.

According to a survey fielded in Mexico in ***********, ** percent of respondents stated having to close their businesses as a result of the COVID-19 pandemic. This represents a noticeable decrease compared to April, when ** percent of participants said they had to shut down their businesses.

During an online survey, *** percent of surveyed small businesses in the United States said they had temporarily closed a location due to the COVID-19 pandemic during the week ending April 17, 2022. Another *** percent of respondents said that they had opened a previously closed location during the same week.

Almost one quarter of all businesses have temporarily closed or paused trading due to the Coronavirus (COVID-19) pandemic in the United Kingdom as of April 2020. The sector with the highest share of business closures were those in the arts, entertainment, and recreation sector, with over ** percent of them currently closed, compared with just *** percent of human health, and social work businesses.

Objectives: Youth with chronic pain often struggle to function in multiple domains due to pain and associated psychosocial distress. In 2020, schools and businesses shut down and people were encouraged to remain at home due to the COVID-19 pandemic, eliminating or reducing stress due to functional difficulties. This study assessed whether pain and associated psychosocial outcomes improved in youth with chronic pain during the shutdown, compared with before the pandemic.Methods: Patients who completed clinical outcome measures during a multidisciplinary evaluation before the pandemic were readministered the same measures (PROMIS Anxiety, Depression, Sleep Disturbance, PCS, PedsQL) during the shutdown. At follow-up, patients also completed measures of adjustment to COVID-19 and their parents completed a measure of pandemic effects.Results: Participants included 47 patients ages 8–18 and a parent/guardian. The pandemic impacted families in both positive (e.g., more quality time with family) and negative ways (e.g., social isolation, disruption in care). Pain intensity and pain catastrophizing significantly decreased during the shutdown (ps <0.01). Change in pain catastrophizing was correlated positively with change in psychological stress (p = 0.004) and anxiety (p = 0.005) and negatively with change in quality of life (p = 0.024).Discussion: Pain and pain catastrophizing decreased initially during the shutdown related to the COVID-19 pandemic. Change in catastrophizing was associated with change in stress and anxiety. It may be that the reduction in functional demands contributed to this change. Functional difficulties should be addressed in treatment, including pain coping and also environmental modification to support optimal functioning in youth with chronic pain.

Research was conducted in summer 2020 to analyze the effect of the shutdown orders due to COVID-19 pandemic on the CO levels across the United States. Since the shutdown orders during the pandemic prevented any public places from operating or conducting any kind of business, the hypothesis was that the CO levels would go down since there was no commute happening or buildings being used. Data was collected from the EPA’s Air Quality public data and analyzed in R: a powerful program used to analyze large datasets. The 15 states analyzed were based on the greatest number of cases on August 20th 2020. Each state had its data, with multiple counties and with multiple sites in each county. In almost every single state, the CO levels went down starting from February, with the lowest CO levels during the shutdown, indicating that the shutdown likely could have led to a decrease in CO levels. As some states opened, the CO level started rising then fluctuating.

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.

According to a survey as of November in 2020, NOGs were the most affected category of business as more than ** percent in India. They had to temporarily shut down due to the coronavirus pandemic. For established companies, the challenges came from increased administrative bottlenecks, and issues with reduced logistics services and infrastructures, i.e., internet among others.

This file shows the closing data of the Covid19 Liquidity line of guarantees according to the type of company that requested them. It provides information on the number of operations, the number of companies, the amount of the guarantee requested and the total amount of financing that these guarantees have made possible. These totals are broken down by type of recipient, with the following categories: Self-employed and SMEs (Self-employed, Micro-SMEs and SMEs) and Non-SMEs.

United States SBP: KS: Business Didn't Close for 1 Day data was reported at 32.000 % in 20 Sep 2020. This records an increase from the previous number of 30.300 % for 13 Sep 2020. United States SBP: KS: Business Didn't Close for 1 Day data is updated weekly, averaging 67.800 % from Apr 2020 to 20 Sep 2020, with 15 observations. The data reached an all-time high of 92.900 % in 14 Jun 2020 and a record low of 27.100 % in 16 Aug 2020. United States SBP: KS: Business Didn't Close for 1 Day data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s United States – Table US.S025: Small Business Pulse Survey: by State: Midwest Region. [COVID-19-IMPACT]

This file shows the closing data of the Covid19 Investment Guarantee line according to the type of company that requested them. It provides information on the number of operations, the number of companies, the amount of the guarantee requested and the total amount of financing that these guarantees have made possible. These totals are broken down by type of recipient, with the following categories: Self-employed and SMEs (Self-employed, Micro-SMEs and SMEs) and Non-SMEs.

■Purpose and Overview (Summary): Subsidies are provided for 2/3 or 3/4 of the expenses incurred by small businesses taking concrete measures (Response to supply chain damage, shift to non-face-to-face business model, and improvement of telework environment) to overcome the impact of COVID-19 on their business environment by preparing a business plan with the advice of the local chamber of commerce or association of commerce. The maximum subsidy amount is 1 million JPY.

Furthermore, if measures to prevent the spread of infection based on the guidelines for each industry (business resumption quota) are implemented, a flat-rate subsidy of up to 500,000 JPY will be added. In addition, an additional limit of 500,000 JPY can be added for industries where cluster measures are considered particularly necessary.

• Small businesses operating in the Chamber of Commerce and Industry area are invited to apply to the Chamber of Commerce and Industry, which also runs a similar business. ■ Purpose and Overview: Small Businesses and Non-Profit Organizations (hereinafter referred to as "small business operators, etc.".) In order to respond to the system changes (Work style reform, expansion of employee insurance coverage, introduction of Wage Increases and invoice, etc.) that will be faced successively over the next several years, the Government will subsidize part of the costs of efforts by small businesses to develop markets, etc., in order to improve the productivity and achieve sustainable development of small businesses that support local employment and industries. grant Business subsidizes part of the expenses required for small business operators' steady efforts to develop markets based on a management plan for sustainable management (Examples: devising ways of selling to enter new markets, improving and developing products to attract new customer segments, etc.). In addition, in this public offering, we will focus on providing support to businesses that are actively investing to overcome the impact of COVID-19 on the business environment while developing new markets.

At the same time, we will subsidize businesses to take the minimum infection prevention measures necessary to continue their business in light of the industry specific guidelines for business resumption (business resumption framework).

■ Remarks: Please refer to the COVID Special Response Public Offering Guidelines for details, including those eligible for assistance.

Note on the Immediate Payment Scheme: This scheme cannot be used by e-filing J-Grants. If you want to use it, please apply by mail.

■ Contact: Business grant Contact

If you are doing business within the jurisdiction of the Chamber, please contact your local office.

< list of local offices here >

Contact Hours:

9: 30~12:00, 13:00~17:30(Excluding weekends and holidays, year-end and New Year holidays)

■ Reference URL: Click here for the application guidelines

Click here for the grant regulations

Click here to download form sheets

Click here for the jGrants Application Guide

National Federation of Commerce and Industry HP: http://www.shokokai.or.jp/jizokuka_t/ ,

A. SUMMARY This dataset includes COVID-19 tests by resident neighborhood and specimen collection date (the day the test was collected). Specifically, this dataset includes tests of San Francisco residents who listed a San Francisco home address at the time of testing. These resident addresses were then geo-located and mapped to neighborhoods. The resident address associated with each test is hand-entered and susceptible to errors, therefore neighborhood data should be interpreted as an approximation, not a precise nor comprehensive total.

In recent months, about 5% of tests are missing addresses and therefore cannot be included in any neighborhood totals. In earlier months, more tests were missing address data. Because of this high percentage of tests missing resident address data, this neighborhood testing data for March, April, and May should be interpreted with caution (see below)

Percentage of tests missing address information, by month in 2020 Mar - 33.6% Apr - 25.9% May - 11.1% Jun - 7.2% Jul - 5.8% Aug - 5.4% Sep - 5.1% Oct (Oct 1-12) - 5.1%

To protect the privacy of residents, the City does not disclose the number of tests in neighborhoods with resident populations of fewer than 1,000 people. These neighborhoods are omitted from the data (they include Golden Gate Park, John McLaren Park, and Lands End).

Tests for residents that listed a Skilled Nursing Facility as their home address are not included in this neighborhood-level testing data. Skilled Nursing Facilities have required and repeated testing of residents, which would change neighborhood trends and not reflect the broader neighborhood's testing data.

This data was de-duplicated by individual and date, so if a person gets tested multiple times on different dates, all tests will be included in this dataset (on the day each test was collected).

The total number of positive test results is not equal to the total number of COVID-19 cases in San Francisco. During this investigation, some test results are found to be for persons living outside of San Francisco and some people in San Francisco may be tested multiple times (which is common). To see the number of new confirmed cases by neighborhood, reference this map: https://sf.gov/data/covid-19-case-maps#new-cases-maps

B. HOW THE DATASET IS CREATED COVID-19 laboratory test data is based on electronic laboratory test reports. Deduplication, quality assurance measures and other data verification processes maximize accuracy of laboratory test information. All testing data is then geo-coded by resident address. Then data is aggregated by analysis neighborhood and specimen collection date.

Data are prepared by close of business Monday through Saturday for public display.

C. UPDATE PROCESS Updates automatically at 05:00 Pacific Time each day. Redundant runs are scheduled at 07:00 and 09:00 in case of pipeline failure.

D. HOW TO USE THIS DATASET San Francisco population estimates for geographic regions can be found in a view based on the San Francisco Population and Demographic Census dataset. These population estimates are from the 2016-2020 5-year American Community Survey (ACS).

Due to the high degree of variation in the time needed to complete tests by different labs there is a delay in this reporting. On March 24 the Health Officer ordered all labs in the City to report complete COVID-19 testing information to the local and state health departments.

In order to track trends over time, a data user can analyze this data by "specimen_collection_date".

Calculating Percent Positivity: The positivity rate is the percentage of tests that return a positive result for COVID-19 (positive tests divided by the sum of positive and negative tests). Indeterminate results, which could not conclusively determine whether COVID-19 virus was present, are not included in the calculation of pe

Companies in the arts, entertainment and recreation sector have had to shut down their activity the most, since the beginning of the coronavirus crisis (COVID-19). Companies in this sector have been closed for an average of almost 100 days. The hotel industry was the second sector most affected by closures. The pharmaceutical industry was the least affected by closures. On average, French companies were closed for ** days in France.

The effects of government interventions on COVID-19 infection rate.

The global effort to slow the spread of the coronavirus disease 2019 (COVID-19) largely depends on the support of every citizen to comply with societal regulations (e.g., school closure) and personal precautions (e.g., wearing a facemask). In an online study with participants from three societies (United States, China, and Japan; Ns = 122, 215, 191, respectively), we examined people’s acceptance of societal and personal preventive measures and their reasons. Drawing on social domain theory, we distinguished among moral, societal, personal, and prudential considerations as potential reasons. In the present study, participants indicated their acceptance of different societal and personal preventive measures and then endorsed the reasons (considerations) they believed to be most important to their acceptance of these measures. Also, they completed scales measuring perceived vulnerability to disease and sense of control. They were also asked to identify societal regulations already implemented by the government of their home country. Finally, using two items, we assessed participants’ subjective evaluation of the controllability of the pandemic (through societal regulations) and the preventability of COVID-19 (through personal precautions). Please see the "measures" document for the full list of items used in this study, and the "data" file for the original data of the study. We found that participants from the United States indicated the highest acceptance of personal preventive measures (e.g., handwashing, wearing facemasks), whereas participants from China indicated the highest acceptance of societal preventive measures (e.g., closing borders, shutting down non-essential businesses). Moral considerations predicted higher acceptance of societal preventive measures, whereas personal considerations predicted lower acceptance of both societal and personal preventive measures. Chinese participants, compared with American and Japanese participants, exhibited a stronger link between societal considerations and higher acceptance of societal preventive measures.

According to a survey conducted in February 2022, around *** percent of small to medium-sized companies in Japan foresaw a likelihood of discontinuation of their business activities due to the impact of the coronavirus (COVID-19) outbreak. By comparison, about *** percent of large business enterprises reported the potential closing down.

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The personal finance software market is expected to grow at a CAGR of 4% during the forecast period. Growing dependency on the internet, drivers.2, and drivers.3 are some of the significant factors fueling personal finance software market growth.

Growing dependency on the internet

A major driver for this segment is the user-friendliness of personal finance software. It helps in easy management of monetary funds and budget. It eases the revenue inflow and outflow for home businesses in a secure way. It assures data privacy as the vendors offer advanced security features in their personal finance software products. Further, the availability of cost-effective solutions is driving the market for home business users. The shutdown of countless businesses and the subsequent effects of COVID-19 have negatively affected the global economy. Several months into the COVID-19 crisis, some countries have managed to control new cases, while in others, the spread remains extensive. Many countries have reopened their economies, allowing a cautious return to work and economic life. Similarly, home business users are also dealing with financial crises due to the disruption of supply chain and transportation. Such factors have increased the demand for personal finance software. The halt of various business activities has negatively impacted many individuals' income, which, in turn, has put pressure on monthly budgets, EMI outflow, insurance premiums, and investments. In such situations, personal finance software has emerged as a key solution in managing business and other personal financial crisis. This software functions as a dashboard; it tracks the user's transactions and gives an early warning when problems arise. Such factors are expected to drive market growth during the forecast period.

The COVID-19 outbreak led governmental officials to close many businesses and schools, including colleges and universities. Thus, the ability to resume normal campus operation required adoption of safety measures to monitor and respond to COVID-19. The objective of this study was to determine the efficacy of wastewater-based epidemiology as a surveillance method in monitoring COVID-19 on a college campus. The use of wastewater monitoring as part of a surveillance program to control COVID-19 outbreaks at East Carolina University was evaluated. During the Spring and Fall 2021 semesters, wastewater samples (N = 830) were collected every Monday, Wednesday, and Friday from the sewer pipes exiting the dormitories on campus. Samples were analyzed for SARS-CoV-2 and viral quantification was determined using qRT-PCR. During the Spring 2021 semester, there was a significant difference in SARS-CoV-2 virus copies in wastewater when comparing dorms with the highest number student cases of COVID-19 and those with the lowest number of student cases, (p = 0.002). Additionally, during the Fall 2021 semester it was observed that when weekly virus concentrations exceeded 20 copies per ml, there were new confirmed COVID-19 cases 85% of the time during the following week. Increases in wastewater viral concentration spurred COVID-19 swab testing for students residing in dormitories, aiding university officials in effectively applying COVID testing policies. This study showed wastewater-based epidemiology can be a cost-effective surveillance tool to guide other surveilling methods (e.g., contact tracing, nasal/salvia testing, etc.) to identify and isolate afflicted individuals to reduce the spread of pathogens and potential outbreaks within a community.

The size of the Micro Lending Market was valued at USD 213.58 Million in 2023 and is projected to reach USD 431.81 Million by 2032, with an expected CAGR of 10.58% during the forecast period. Recent developments include: November 2023: Funding Circle and Atom Bank unveiled a lending collaboration to extend GBP 150 million (USD 180.87 million) in fresh funding to small businesses. Combined with the previous lending of GBP 350 million (USD 422.03 million) facilitated through the Funding Circle platform, this new commitment boosts Atom's total lending via Funding Circle to GBP 800 million (USD 964.65 million)., July 2023: Funding Circle, the biggest lending platform in the United Kingdom for small businesses, unveiled a fresh collaboration with Rainbow Energy. This partnership aimed to empower small businesses to utilize a Funding Circle loan to install top-tier solar panels and battery storage systems offered by Rainbow. Small businesses can reduce their ongoing energy expenses by transitioning to renewable energy while achieving societal net zero goals., April 2023: Wise, the renowned global technology company specializing in optimizing money transfers worldwide, joined forces with Bluevine, a leading provider of comprehensive small business banking solutions. This partnership harnesses the capabilities of the Wise Platform to enhance the convenience, simplicity, and transparency of international payments for Bluevine's customers within its all-in-one digital banking account.. Key drivers for this market are: Increasing Interest in Socially Responsible Investment Driving Market Growth, Advancement in Mobile Banking and Digital Platform Driving Market Growth. Potential restraints include: Shutdown of Small and Medium Businesses During COVID-19 Pandemic. Notable trends are: The Micro lending Industry is Being Dominated by Banks.