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Europe has 'a lot of work to do' to prevent COVID-19, WHO expert warns

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Europe has 'a lot of work to do' to prevent COVID-19, WHO expert warns

Posted | Updated by Insights team:

Publication | Update:

Sep 2020
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Europe has "a lot of work to do right now" to bring down increasing COVID-19 cases, a World Health Organization expert said, stating that deaths in older people would likely increase in the region soon.

"We're starting to see a small uptick in deaths in older people and that will inevitably become more," said Dr Mike Ryan, director of the WHO's health emergencies programme.

"We haven’t even started our flu season yet, so what we are worried about is the possibility that these trends are going in the wrong direction," said Dr Maria Van Kerkhove, the WHO's technical lead on COVID-19.

She said part of this rise in cases was due to "surveillance" as countries get better at detecting cases. But that experts were closely watching rising hospitalisation and intensive care rates.

Dr Ryan and Dr Kerkhove insisted that lockdowns should only be used as a last resort measure.

"Lockdowns and national lockdowns are almost a last resort and to think that we're back in last resort territory in September, at the beginning of the autumn, I think is something that is a pretty sobering thought," Dr Ryan said.

"Have we really exhausted all the tools so we're back to lockdowns as a solution?" he asked, stating that countries need to use testing, tracing and physical distancing to fight COVID-19.

"A good number of countries around the world have never had to resort to lockdowns," Dr Ryan pointed out, adding that contact tracing and quarantine had worked in some countries and not worked well in others.

France recently reduced the number of days in quarantine from 14 to seven to encourage people to follow self-isolation guidelines after experts said people were not doing so.

Lockdowns were only meant to buy countries time, Dr Kerkhove said.

There have recently been record numbers of daily coronavirus cases recorded in multiple European countries including Spain, France, the Netherlands and the United Kingdom.

Spain and France have been recording more than 10,000 daily new cases regularly. France issued new guidelines in multiple cities hard hit by the pandemic while Madrid could soon get much stricter restrictions.

Young people are not at fault, says WHO

Experts at the World Health Organization added on Friday that young people among whom COVID-19 has been circulating more frequently are not at "fault" for increasing transmission.

Dr Ryan said he thought many young people were committed to containing the virus but that multiple factors influence human behaviour.

"The last thing a young person needs is an older person pontificating and wagging the finger," he said, adding that the real question was "how do we work with young people to make their behaviour safer".

But a report released this week from the US Centres for Disease Control and Prevention found that young people contributed to the spread of COVID-19 in more vulnerable populations.

"Across the southern United States in June 2020, the increase in SARS-CoV-2 infection among younger adults preceded the increase among older adults by 4–15 days," the CDC said in the report.

This was because younger adults with little to no symptoms often unknowingly infected older adults, the US agency said.

Another one million people could die before a vaccine is found

As worldwide deaths approach one million, experts at WHO confirmed on Friday that it is possible another one million deaths will occur before a vaccine is found, emphasising that a vaccine is one tool among others that countries should be using.

Seeing another one million deaths in the world is not only "imaginable" but it's also "likely," Dr Ryan said if countries do not employ all the tools they have at their disposal to drive down transmission.

WHO director-general Dr Tedros Adhanom Ghebreyesus added that around 70% of COVID-19 deaths come from just 10 countries, stating that those countries need to drive down cases.

The ten countries with the most deaths due to COVID-19 are the United States, Brazil, India, Mexico, the United Kingdom, Italy, Peru, France, Spain and Iran.

In Europe, Italy has maintained lower numbers of new COVID-19 cases with a slower reopening and stricter policies, experts say. Other countries are just now issuing stricter restrictions, as virus transmission increases significantly.

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The report also studies various growth drivers and restraints impacting the  market, plus a comprehensive market and vendor landscape in addition to a SWOT analysis of the key players.  This analysis also examines the competitive landscape within each market. Market factors are assessed by examining barriers to entry and market opportunities. Strategies adopted by key players including recent developments, new product launches, merger and acquisitions, and other insightful updates are provided.

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We leverage extensive primary research, our contact database, knowledge of companies and industry relationships, patent and academic journal searches, and Institutes and University associate links to frame a strong visibility in the markets and technologies we cover.

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Forecast methodology

The future outlook “forecast” is based on a set of statistical methods such as regression analysis, industry specific drivers as well as analyst evaluations, as well as analysis of the trends that influence economic outcomes and business decision making.
The Global Economic Model is covering the political environment, the macroeconomic environment, market opportunities, policy towards free enterprise and competition, policy towards foreign investment, foreign trade and exchange controls, taxes, financing, the labour market and infrastructure. We aim update our market forecast to include the latest market developments and trends.

Forecasts, Data modelling and indicator normalisation

Review of independent forecasts for the main macroeconomic variables by the following organizations provide a holistic overview of the range of alternative opinions:

  • Cambridge Econometrics (CE)

  • The Centre for Economic and Business Research (CEBR)

  • Experian Economics (EE)

  • Oxford Economics (OE)

As a result, the reported forecasts derive from different forecasters and may not represent the view of any one forecaster over the whole of the forecast period. These projections provide an indication of what is, in our view most likely to happen, not what it will definitely happen.

Short- and medium-term forecasts are based on a “demand-side” forecasting framework, under the assumption that supply adjusts to meet demand either directly through changes in output or through the depletion of inventories.
Long-term projections rely on a supply-side framework, in which output is determined by the availability of labour and capital equipment and the growth in productivity.
Long-term growth prospects, are impacted by factors including the workforce capabilities, the openness of the economy to trade, the legal framework, fiscal policy, the degree of government regulation.

Direct contribution to GDP
The method for calculating the direct contribution of an industry to GDP, is to measure its ‘gross value added’ (GVA); that is, to calculate the difference between the industry’s total pre­tax revenue and its total bought­in costs (costs excluding wages and salaries).

Forecasts of GDP growth: GDP = CN+IN+GS+NEX

GDP growth estimates take into account:

  • Consumption, expressed as a function of income, wealth, prices and interest rates;

  • Investment as a function of the return on capital and changes in capacity utilization; Government spending as a function of intervention initiatives and state of the economy;

  • Net exports as a function of global economic conditions.

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Market Quantification
All relevant markets are quantified utilizing revenue figures for the forecast period. The Compound Annual Growth Rate (CAGR) within each segment is used to measure growth and to extrapolate data when figures are not publicly available.

Revenues

Our market segments reflect major categories and subcategories of the global market, followed by an analysis of statistical data covering national spending and international trade relations and patterns. Market values reflect revenues paid by the final customer / end user to vendors and service providers either directly or through distribution channels, excluding VAT. Local currencies are converted to USD using the yearly average exchange rates of local currencies to the USD for the respective year as provided by the IMF World Economic Outlook Database.

Industry Life Cycle Market Phase

Market phase is determined using factors in the Industry Life Cycle model. The adapted market phase definitions are as follows:

  • Nascent: New market need not yet determined; growth begins increasing toward end of cycle

  • Growth: Growth trajectory picks up; high growth rates

  • Mature: Typically fewer firms than growth phase, as dominant solutions continue to capture the majority of market share and market consolidation occurs, displaying lower growth rates that are typically on par with the general economy

  • Decline: Further market consolidation, rapidly declining growth rates

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The Global Economic Model
The Global Economic Model brings together macroeconomic and sectoral forecasts for quantifying the key relationships.

The model is a hybrid statistical model that uses macroeconomic variables and inter-industry linkages to forecast sectoral output. The model is used to forecast not just output, but prices, wages, employment and investment. The principal variables driving the industry model are the components of final demand, which directly or indirectly determine the demand facing each industry. However, other macroeconomic assumptions — in particular exchange rates, as well as world commodity prices — also enter into the equation, as well as other industry specific factors that have been or are expected to impact.

  • Vector Auto Regression (VAR) statistical models capturing the linear interdependencies among multiple time series, are best used for short-term forecasting, whereby shocks to demand will generate economic cycles that can be influenced by fiscal and monetary policy.

  • Dynamic-Stochastic Equilibrium (DSE) models replicate the behaviour of the economy by analyzing the interaction of economic variables, whereby output is determined by supply side factors, such as investment, demographics, labour participation and productivity.

  • Dynamic Econometric Error Correction (DEEC) modelling combines VAR and DSE models by estimating the speed at which a dependent variable returns to its equilibrium after a shock, as well as assessing the impact of a company, industry, new technology, regulation, or market change. DEEC modelling is best suited for forecasting.

Forecasts of GDP growth per capita based on these factors can then be combined with demographic projections to give forecasts for overall GDP growth.
Wherever possible, publicly available data from official sources are used for the latest available year. Qualitative indicators are normalised (on the basis of: Normalised x = (x - Min(x)) / (Max(x) - Min(x)) where Min(x) and Max(x) are, the lowest and highest values for any given indicator respectively) and then aggregated across categories to enable an overall comparison. The normalised value is then transformed into a positive number on a scale of 0 to 100. The weighting assigned to each indicator can be changed to reflect different assumptions about their relative importance.

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The principal explanatory variable in each industry’s output equation is the Total Demand variable, encompassing exogenous macroeconomic assumptions, consumer spending and investment, and intermediate demand for goods and services by sectors of the economy for use as inputs in the production of their own goods and services.

Elasticities
Elasticity measures the response of one economic variable to a change in another economic variable, whether the good or service is demanded as an input into a final product or whether it is the final product, and provides insight into the proportional impact of different economic actions and policy decisions.
Demand elasticities measure the change in the quantity demanded of a particular good or service as a result of changes to other economic variables, such as its own price, the price of competing or complementary goods and services, income levels, taxes.
Demand elasticities can be influenced by several factors. Each of these factors, along with the specific characteristics of the product, will interact to determine its overall responsiveness of demand to changes in prices and incomes.
The individual characteristics of a good or service will have an impact, but there are also a number of general factors that will typically affect the sensitivity of demand, such as the availability of substitutes, whereby the elasticity is typically higher the greater the number of available substitutes, as consumers can easily switch between different products.
The degree of necessity. Luxury products and habit forming ones, typically have a higher elasticity.
Proportion of the budget consumed by the item. Products that consume a large portion of the consumer’s budget tend to have greater elasticity.
Elasticities tend to be greater over the long run because consumers have more time to adjust their behaviour.
Finally, if the product or service is an input into a final product then the price elasticity will depend on the price elasticity of the final product, its cost share in the production costs, and the availability of substitutes for that good or service.

Prices
Prices are also forecast using an input-output framework. Input costs have two components; labour costs are driven by wages, while intermediate costs are computed as an input-output weighted aggregate of input sectors’ prices. Employment is a function of output and real sectoral wages, that are forecast as a function of whole economy growth in wages. Investment is forecast as a function of output and aggregate level business investment.

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