COVID-19 pandemic, Meta Intelligence

Zheng Yongnian (郑永年) on How to Address Western Public Opinion on China: Facts, Science and Reason

[from Pekingology at the Center for China and Globalization (CCG)]

“Be open, open, and more open,” especially to businesses, investors, media, universities, and research institutions. And tit-for-tat doesn’t work, the professor says.

by Zichen Wang, Shuyuan Han, and Li Huiyan

Professor Zheng Yongnian (郑永年), the Founding Director of the Institute for International Affairs at the Chinese University of Hong Kong, Shenzhen, on January 28 published an article on how China should address Western public opinion on China. His advice is in the last part of the article, and below is a translation.

(Emphasis by Pekingnology.)

First, we need to understand how such narratives are formed. Historically, China held a bias due to its self-isolation and limited knowledge of the West. Despite losing the two Opium Wars, Chinese intellectuals at that time still saw Westerners as uncivilized. It was not until China was defeated by Japan, a neighboring country once considered as China’s student, that they realized their ignorance and a need for reform. Before China’s Reform and Opening up, Chinese people barely knew anything about the West. They always assumed Westerners were in deep distress, repeating the same lack of understanding of the West.

Similarly, the West’s uncertainty and fear towards China’s rise stem from a lack of understanding and even fear of the country, and their ingrained ideology would lead to misconceptions.

China is the world’s second-largest economy. The externalities and influence of its economy on the West are obvious. Upon joining the WTO, some Chinese people also felt unsettled by the externalities of the West. Some said, “the wolf is coming.” Now it is the West that is experiencing such worries.

It is crucial to recognize the significant impact of the Western hypocritical narratives against China, even if they are based on ideology rather than facts. We must also acknowledge that ideology-based public opinion from the West can exert a powerful influence on their policies toward China.

Historically, the West tended to demonize others while presenting themselves as morally superior, which enabled them to apply Social Darwinism to international politics easily and thus legitimizing conflicts and even wars with other nations. Given the Soviet Union’s failure in the ideological arena during the Cold War, we should by no means ignore any ideology-based public opinion toward China from the West.

Second, to make rational responses to the Western ideology-based criticisms, we should draw lessons from the history of the world economy, such as the lessons of the Soviet Union, as well as our practices, such as the rhetorical battle with the West in the past few years. Coming up with an externally-facing public opinion based on a different ideology is not the most effective in addressing public opinion attacks based on an ideology. Empirically, tit-for-tat is ineffective and can worsen the situation. Again, the failure of the Soviet Union is a prime example, as its battle with a Western ideology failed. When faced with China-demonizing based on ideology from the West, we need to do the simplest thing, namely resorting to facts, science, and reason.

Third, and most importantly, China needs to prioritize its sustainable development, which ultimately benefits the country itself. It is important to recognize that the foundation of the government’s governance lies in its citizens, not Western praise. The support from its people is crucial for both the nation’s longevity and stability., China’s sustainable development also benefits the world economy by boosting its growth. As mentioned above, China has been the largest contributor to the growth of the world economy since it joined the WTO.

It is crucial to prioritize the building of a knowledge system based on China’s practical experiences. Regarding global soft power, we need a knowledge system based on our experiences rather than a certain ideology. While there has been a proposal for an autonomous knowledge system, continuous effort is still required.

Fourth, given the substantial externalities of our economy, we must further communicate and coordinate with other countries on economic policies, regardless of their respective sizes. Our duty is to fulfill the responsibility as a major player in the international community, which also benefits China.

After the 1997-1998 Asian financial crisis, China promised not to devalue its currency, and that commitment became an international public good in Asia. Similarly, after the global financial crisis from 2007 to 2008, China made similar contributions. As China re-opens its economy after the pandemic, it is important not only to take note of the hypocritical comments from certain quarters in the Western world but also to recognize the positive evaluations and high expectations from many international organizations.

Fifth, we must be open, open, and more open. Despite China’s efforts, there remains a persistent ideological camp in the West that views China through an ideological lens, a situation made worse by the past three years of the pandemic. The pandemic was so severe that it hindered travel across borders; as a result, some Western media and scholars tend to assess China through ideology since they couldn’t come here to see the facts with their own eyes.

The assessment of China through a uniform ideological lens appears to have strengthened the original Western ideological camp. However, the United States and the West have more than one ideology, and not all people believe in the prevailing ideology in the public opinion sphere. China’s openness provides a “seeing is believing” opportunity for different groups in the West. China should increase its openness to Western groups, including businesses, investors, media, universities, and research institutions. The changes in their understanding could render those ideological-based public opinions less effective.

FRBSF Economic Letter: Can Monetary Policy Tame Rent Inflation?

[from the Federal Reserve Bank of San Francisco Economic Letter]

by Zheng Liu and Mollie Pepper

Rent inflation has surged since early 2021. Because the cost of housing is an important component of total U.S. consumer spending, high rent inflation has contributed to elevated levels of overall inflation. Evidence suggests that, as monetary policy tightening cools housing markets, it can also reduce rent inflation, although this tends to adjust relatively slowly. A policy tightening equivalent to a 1 percentage point increase in the federal funds rate could reduce rent inflation as much as 3.2 percentage points over 2½ years.

“We’ve had a time of red-hot housing market all over the country… Shelter inflation is going to remain high for some time. We’re looking for it to come down, but it’s not exactly clear when that will happen. Hope for the best, plan for the worst.”
Federal Reserve Chair Jerome Powell (2022)

The rapid run-up of shelter costs—both house prices and rents—during the recovery from the pandemic has raised questions about how inflation pressures might affect housing affordability. Since March 2022, the Federal Reserve has rapidly lifted its federal funds rate target from near zero to over 4%, and policymakers have signaled that they are open to keeping the monetary policy stance sufficiently restrictive to return inflation to the longer-run goal of 2% on average. The tightened financial conditions following those policy changes, especially the surge in mortgage interest rates, have helped cool house price growth. However, rent inflation remains elevated.

This Economic Letter examines the effectiveness of monetary policy tightening for reducing rent inflation. We estimate that, during the period from 1988 to 2019, a policy tightening equivalent to a 1 percentage point increase in the federal funds rate can reduce rent inflation—measured by 12-month percentage changes in the personal consumption expenditures (PCE) housing price index—by about 3.2 percentage points, but the full impact takes about 2½ years to materialize. Based on housing costs’ share in total PCE, this translates to a reduction in headline PCE inflation of about 0.5 percentage point over the same time horizon.

Rising housing costs

Following the COVID-19 recession, house prices and rents both surged in the United States. For example, the 12-month growth rate of Standard & Poor’s CoreLogic Case-Shiller Home Price Index accelerated from about 10% in December 2020 to over 20% in March 2022. After the Federal Reserve started raising the target for the federal funds rate in March, house price growth has slowed significantly, to about 9% in October 2022.

Rent inflation also accelerated during the pandemic period. Figure 1 shows that rent inflation—measured using 12-month changes in the PCE housing price index and including rents for tenant-occupied housing and imputed rents for owner-occupied housing—rose from a low point of about 2% in early 2021 to 7.7% by December 2022, the highest level since 1986. During the same period, rent inflation measured by 12-month changes in the shelter component of the consumer price index (CPI) experienced a similar increase. Thus, following the tightening of monetary policy, house price growth has slowed but rent inflation continues to rise.

Figure 1: PCE and CPI measures of rent inflation

Source: Bureau of Economic Analysis, Bureau of Labor Statistics, and Haver Analytics.
Note: Twelve-month percentage changes. Gray shading indicates NBER recession dates.

Economic theory suggests that some common forces such as changes in housing demand can drive both rents and house prices. For example, the expansion of remote work since the COVID-19 pandemic has increased demand for housing, raising both house prices and rents (Kmetz, Mondragon, and Wieland 2022). To the extent that the stream of current and future rents reflects the fundamental value of a house, house prices can be a leading indicator of future rent inflation (Lansing, Oliveira, and Shapiro 2022). Thus, monetary policy can affect both house prices and rents by cooling housing demand.

Housing demand responds to changes in financial conditions, such as increases in mortgage interest rates. However, theory suggests that house prices are more sensitive than rental prices to changes in financial conditions, because home purchases typically require longer-term mortgage financing. In addition, unlike rents, house prices can be partly driven by investor sentiments or beliefs, which explains the observed larger swings in house prices than in rents over business cycles (Dong et al. 2022). Long-term rental contracts can also contribute to slow adjustments in rent inflation.

Rent inflation is an important contributor to overall inflation because housing costs are an important component of total consumption expenditures. On average, housing expenditures represent about 15% of total PCE and 25% of the services component of PCE. In CPI, shelter costs represent an even larger share, accounting for about 30% of total consumption of all urban consumers and about 40% of core consumption expenditures excluding volatile food and energy components.

The contribution of rent inflation to overall PCE inflation has increased since early 2021. As Figure 2 shows, in the first quarter of 2021, rent inflation accounted for about 22% of the four-quarter change in the PCE services price index, excluding energy: 0.5 of the 2.3 percentage points increase in service prices was attributable to rent inflation. By the third quarter of 2022, the contribution of rent inflation had climbed to about one-third, or 1.5 of the 4.7 percentage point increase in service prices.

Figure 2: Rising contribution of rent inflation to services inflation

Source: Bureau of Economic Analysis, Haver Analytics, and authors’ calculations.
Note: Four-quarter changes in PCE services price index excluding energy.

Measuring policy effects

Given the rising contribution of rent inflation to overall inflation, it is important to assess the quantitative effects of monetary policy tightening on rent inflation.

For our analysis, we use a measure of monetary policy surprises constructed by Bauer and Swanson (2022). Their measure focuses on high-frequency changes in financial market indicators within a short period surrounding the Federal Open Market Committee (FOMC) policy announcements. If the public fully anticipates a policy change, then the financial market would not react to new policy announcements. However, if the market does react to an announcement, then the policy change must contain a surprise element. Thus, changes in financial market indicators, such as the price of Eurodollar futures, in a narrow window around an FOMC announcement can capture policy surprises. In practice, however, the data constructed this way are not complete surprises because they can be predicted by some macro and financial variables shortly before FOMC announcements. We follow the approach of Bauer and Swanson (2022) to purge the influences of those macro and financial variables from the measure of policy surprises. We use the resulting quarterly time series to measure monetary policy shocks, with a sample period from 1988 to 2019.

We then use a local projections model—a statistical tool proposed by Jordà (2005)—to project how rent inflation responds over time to a tightening of monetary policy equivalent to a 1 percentage point unanticipated increase in the federal funds rate in a given quarter. The model takes into account how monetary policy shocks interact with other macroeconomic variables, including lags of rent inflation, real GDP growth, and core PCE inflation.

In the final step, we compute the responses of rent inflation relative to its preshock level over a period up to 20 quarters after the initial increase in the federal funds rate.

Gradual impact of policy tightening on rent inflation

Figure 3 shows the response of rent inflation during the first 20 quarters after an unanticipated tightening of monetary policy (solid blue line). The shaded area shows the confidence band, indicating the statistical uncertainty in estimating the responses. Under the assumption that the model is correct, the shaded area contains the actual value of the rent inflation responses to the monetary policy shock roughly two-thirds of the time. The policy shock is normalized such that it is equivalent to a 1 percentage point unanticipated increase in the federal funds rate.

Figure 3: Response of rent inflation to monetary policy tightening

Source: Bureau of Economic Analysis, Bauer and Swanson (2022), and authors’ calculations.
Note: Response of rent inflation to a monetary policy shock equivalent to a 1 percentage point surprise increase in the federal funds rate. Shaded region shows 68% confidence band around the estimate.

The figure shows that monetary policy tightening has significant and gradual effects on rent inflation. On impact, a 1 percentage point increase in the federal funds rate reduces rent inflation about 0.6 percentage point relative to its preshock level. Over time, rent inflation declines gradually, falling about 3.2 percentage points in the 10 quarters following the impact. The slow adjustment in rent inflation partly reflects the stickiness in nominal rents due to long-term rental contracts. Since housing expenditures account for about 15% of total PCE, this estimate translates to a reduction in headline PCE inflation of about 0.5 percentage point, stemming from the decline in rent inflation over a period of 2½ years.

The rent component of PCE is measured based on average rents, including those locked in long-term rental contracts, which are slow to adjust to changes in economic and financial conditions. Rents on new leases, however, are more flexible. For example, the 12-month growth in Zillow’s observed rent index, which measures changes in asking rents on new leases, has slowed significantly since March 2022 (see Figure 4). Asking rents are typically a leading indicator of future average rents. Thus, the slowdown in asking rent growth could portend lower future rent inflation.

Figure 4: Year-over-year observed rent growth starting to slow

Source: Zillow and Haver Analytics.
Note: Twelve-month percentage changes in Zillow’s observed rent index. Gray shading indicates NBER recession dates.

Conclusion

Rents are an important component of consumer expenditures. Recent surges in rent inflation have led to concerns that overall inflation might stay persistently high despite tightening of monetary policy. We present evidence that monetary policy tightening is effective for reducing rent inflation, although the full impact takes time to materialize. A policy tightening equivalent to a 1 percentage point increase in the federal funds rate can reduce rent inflation up to 3.2 percentage points over the course of 2½ years. This translates to a maximum reduction in headline PCE inflation of about 0.5 percentage point over the same time horizon. Although average rents are slow to respond to policy changes, growth of asking rents on new leases has started to slow following recent monetary policy tightening. Our finding suggests that this tightening will gradually bring rent inflation down over time, thereby helping to reduce overall inflation.

Zheng Liu — Vice President and Director of the Center for Pacific Basin Studies, Economic Research Department, Federal Reserve Bank of San Francisco

Mollie Pepper — Research Associate, Economic Research Department, Federal Reserve Bank of San Francisco

[Archived PDF]

Economics-Watching: FedViews for January 2023

[from the Federal Reserve Bank of San Francisco]

Adam Shapiro, vice president at the Federal Reserve Bank of San Francisco, stated his views on the current economy and the outlook as of January 12, 2023.

While continuing to cool over the last several months, 12-month inflation remains at historically high levels. The headline personal consumption expenditures (PCE) price index rose 5.5% in November 2022 from a year earlier. This marks a decline in inflation to a level last observed in October 2021, but still well above the Fed’s longer-run goal of 2%. A portion of the inflation moderation is attributable to recent declines in energy prices. Core PCE inflation, which removes food and energy prices, has shown less easing.
Owing to fiscal relief efforts and lower household spending over the course of the pandemic, consumers accumulated over $2 trillion dollars in excess savings, based on pre-pandemic trends. Since then, consumers have drawn down over half of this excess savings which has helped support recent growth in personal consumption expenditures. A considerable amount of accumulated savings remains for some consumers to support spending in 2023.
In the wake of the pandemic, consumer spending patterns shifted away from services towards goods. While there appears to be some normalization of spending behavior, this shift has generally persisted. Real goods spending remains significantly above its pre-pandemic trend, driven by strong demand for durables such as furniture, electronics, and recreational goods. Spending on services has shown a resurgence but remains below its pre-pandemic trend.
Supply chain bottlenecks for materials and labor remain a constraint on production, although there are some recent signs of easing. The fraction of manufacturers who reported operating below capacity due to insufficient materials peaked in late 2021 and has moderately declined over the past year. However, the fraction of manufacturers reporting insufficient labor has persisted at high levels.
The labor market remains tight, despite some signs of cooling. The number of available jobs remains well above the number of available workers, although vacancy postings have been trending down in recent months. The tight labor market has put continued upward pressure on wages and labor market turnover.
A decomposition of headline PCE inflation into supply– and demand-driven components shows that both supply and demand factors are responsible for the recent rise in inflation. The surge in inflation in early 2021 was mainly due to an increase in demand-driven factors. Subsequently, supply factors became more prevalent for the remainder of 2021. Supply-driven inflation has moderated significantly over recent months, while demand-driven inflation remains elevated.
The Federal Open Market Committee (FOMC) raised the federal funds rate by 50 basis points at the December meeting to a range of 4.25 to 4.5%. This cycle of continued rate increases since March of last year represents the fastest pace of monetary policy tightening in 40 years. The increase in the federal funds rate has been accompanied by a gradual reduction in the size of the Federal Reserve’s balance sheet.
Economic activity in sectors such as housing, which is sensitive to rising interest rates, has slowed considerably in recent months. Housing starts have fallen steadily over the past year, as have other housing market indicators, such as existing home sales and house prices.
Although the labor market is currently very strong, financial markets are pointing to some downside risks. Namely, the difference between longer- and shorter-term interest rates has turned negative, which historically tends to occur immediately preceding recessions. It remains unclear whether lower longer-term yields are indicative of anticipated slower growth or lower inflation.
Short-term inflation expectations remain elevated relative to their pre-pandemic levels in December 2019. Consumers are expecting prices to rise 5% this year, while professional forecasters are expecting prices to rise 3.5%. Longer-term inflation expectations remain more subdued, indicating that both consumers and professionals believe inflation pressures will eventually dissipate.
Rent inflation is expected to remain high over the next year. The prices for asking rents have grown quite substantially over the last two years. As new leases begin and existing leases are renewed, these higher asking rents will flow into the stock of rental units, putting upward pressure on rent inflation.
We are expecting inflation to moderate over the next few years as monetary policy continues to restrain demand and supply bottlenecks continue to ease. We anticipate that it will take some time for inflation to reach the Fed’s longer-run goal of 2%.

Inflation is cooling, but remains very high

Supply shortages are prevalent, but easing

Labor market remains tight, but is cooling

Monetary policy tightening is having real effects

Yield curve is inverted, signaling recession risk

Short-term inflation expectations remain elevated

Inflation likely to remain above 2% for some time

[Archived PDF]

Read other issues from FedViews.

From ASEAN and G20 to APEC, as World Leaders Meet in Person Again, 3 Reasons to Root for Multilateralism

By Wang Huiyao | Founder of the Center for China and Globalization (CCG)

Over the past two weeks, Asia has played host to the most intense sequence of multilateral summits since the pandemic began, as national leaders gathered for meetings organized by ASEAN, the G20 and APEC. Although overshadowed by geopolitical tensions, the meetings marked a welcome return to in-person summit diplomacy, and the better-than-expected outcomes show hope yet for multilateralism.

The conclaves began in Phnom Penh with the annual summit of the Association of Southeast Asian Nations. At the first of such in-person events in almost three years, ASEAN leaders took the positive step of agreeing in principle to admit East Timor as the 11th member of the organization.

As leaders moved on to Bali for the Group of 20 summit, expectations were low after ministerial meetings in the run-up had failed to produce consensus. Earlier in the year, given fractures in the wake of Russia’s invasion of Ukraine, there was a question mark over whether the G20 could even go ahead or survive in its existing form.

In the end, the summit surpassed expectations by producing a joint declaration after intense negotiations, with leaders finding the compromises necessary to unite in declaring that “today’s era must not be of war” and pledging to uphold the multilateral system.

The summit also saw a positive face-to-face meeting between China’s President Xi Jinping and U.S. President Joe Biden, their first as leaders, signaling a willingness to halt the downward trajectory of China-U.S. relations.

In Bangkok, the 21 leaders of the Asia-Pacific Economic Cooperation forum also pledged to uphold and strengthen the rules-based multilateral trading system. Importantly, the group agreed on a multi-year work plan for an Asia-Pacific free trade area.

Reflecting on these three summits, three takeaways give reason for cautious optimism that multilateralism can yet be revived and play a major role in solving our challenges.

First, and perhaps most obviously, the return of in-person summit diplomacy is a welcome uplift for global cooperation. Virtual formats played a useful interim role at the height of the pandemic but were never a substitute for getting leaders in the same room. That is especially when it comes to interactions on the sidelines, often as important as the main event.

China’s return to diplomacy at the highest level was a further boost, both for the nation and the rest of the world.

In addition to Xi’s highly anticipated meeting with Biden, the Chinese leader met over a dozen other leaders at the G20 and APEC summits, including a warmer-than-expected first meeting with Japanese Prime Minister Fumio Kishida and his first meeting with an Australian prime minister since 2016.

Leaders got to meet their new counterparts for the first time or build on existing relationships, which can only help global cooperation.

The second takeaway is that as grave as our challenges are, the threat of escalating conflict and severe economic pressures on all nations seem to be focusing minds and increasing the willingness to engage and cooperate—out of necessity if nothing else.

The G20 summit was the second major one this year to surpass expectations after the 12th World Trade Organization Ministerial Conference in June surprised observers by agreeing on a plan to reform the organization and its dispute settlement mechanism. The G20 statement reiterated support for this WTO reform plan, which will be critical to get the free trade agenda back on track and provide a much-needed boost for the global economy.

Third, and perhaps most significantly for the long term, the recent summits marked an acceleration of the trend towards multi-polarization in international diplomacy, and in particular, the rising influence of non-aligned “middle powers” to shape multilateral outcomes.

The middle powers represented at ASEAN, the G20 and APEC have huge stakes in avoiding a bifurcation of the global economy that might result from a new cold war. They don’t want to be forced to pick sides and many show a growing willingness and ability to build bridges and restore positive momentum for multilateralism.

Indonesia is a prime example. The country’s strategic heft and non-aligned credibility make it well-placed to bridge different camps. President Joko Widodo made a big political bet on the success of the G20 and has won praise for the deft diplomacy that kept the organization alive and got it to a joint statement.

The Indian delegation reportedly also played a big role in achieving consensus on language in the statement, with the BRICS group (Brazil, Russia, India, China and South Africa)—as well as Indonesia—turning out to be crucial swing voters in securing the joint statement. One Indian official said it was “the first [G20] summit where developing nations shaped the outcome.”

There is scope for this trend to continue next year as middle powers continue to rise in stature, and India and Indonesia take over the presidency of the G20 and ASEAN, respectively. Brazil will host the G20 the year after.

Over in Sharm el-Sheikh at the COP27 UN climate summit, another middle power—the host Egypt—also won praise for helping to shepherd a historic financing deal for poor countries affected by climate change. But the ultimate failure to reach a commitment to phase down fossil fuels was a sobering reminder of the huge difficulties that remain in forging the global consensus needed to overcome our shared challenges.

The Early Universe and the Future of Humanity/Xi Risks Losing the Middle Class

[from The Institute of Art and Ideas]

The Life and Philosophy of Martin Rees

An Interview with Martin Rees

Astronomer Royal and best-selling science author, Martin Rees pioneering early work led to evidence to contradict the Steady State theory of the universe and confirm the Big Bang. His influence then spread to the wider public—knighted in 1992, elevated to Baron in 2005, then giving the Reith Lectures in 2010. Most recently his attention has turned from the early universe to the future of humanity. In this interview, Lord Rees discusses the ideas and experiences which led to such an illustrious career.

Xi Risks Losing the Middle Class

The zero-COVID strategy has run its course

Kerry Brown | Professor of Chinese Studies and Director of Lau China Institute, King’s College London. He is the co-editor of the Journal of Current Chinese Affairs, and author of Xi: A Study in Power.

China is continuing with its tough zero-COVID policy. But the cracks in the economy and a discontent middle class mean that Xi’s Imperial-like governing style is under challenge, writes Kerry Brown.

China’s zero-COVID strategy operates in Chinese domestic politics a bit like Brexit does in the UK. Despite complaints from business networks and broader society about the negative impact on economic growth and citizens’ freedoms, it’s a policy commitment the government is sticking to no matter what.

Of course, no one voted for the draconian lockdowns implemented across China. And, unlike Brexit, the lockdowns are very much in line with expert advice in the country, rather than running against it. The Chinese Centre for Disease Control and Prevention (CCDC), the main governmental body advising the government over crisis response in this area, said in a weekly update last November that without comprehensive restraints on people’s movement and quarantines on anyone testing positive for the virus, the national health system would soon be overwhelmed with cases, and find itself in the same bind as those in the US or Europe did.

That the words of the experts have been taken so much in earnest is striking for a regime that previously hasn’t been shy to dismiss them. The Xi leadership may be confident in the way it speaks to the outside world, but it seems that it has the same profound wariness in the robustness of the country’s public health as everywhere else. Things have not been helped by clinical trials showing the Chinese vaccines – the only ones accepted in China – are not as effective as foreign ones where the length of protection is in question). On top of this, vaccine take-up by the elderly, the most vulnerable group, has been poor. It is easy to see therefore why the central government might be very cautious. What is harder to understand, however, is why the cautiousness has bordered on obsessiveness.

The Xi way of governing is increasingly almost imperial in style, with broad, high-level policy announcements made in Beijing, sometimes of almost Delphic succinctness.

One scenario is simply about the structures of decision-making in China. This was an issue right from the moment the variant started to appear in late 2019, and local officials in Wuhan stood accused of trying to hush the issue up, delaying reporting to the central authorities till things had already gone on too long. As a result of this, in February 2020 key officials in the city were sacked. But this is unlikely to change the fact that provincial officials are very risk averse under Xi, and that any central direction to manage the pandemic will be interpreted in the purest terms and executed to the letter.

This explains the completeness of the Xian government’s virtual incarceration of its 8 million population after just a few COVID cases at the end of 2021, the first of the more recent lockdowns. It also explains why the traditionally more free-thinking municipal authority of Shanghai and its similarly liberal approach was fiercely knocked back by Beijing last February, to make an example for any other provinces thinking of going their own way. The absolute prohibition on people moving from their homes there, in one of the most dynamic and lively cities of modern China, was perfect proof that if the government could bring about this situation there, it could do it anywhere.

This case study also reveals some important things about the Xi way of governing. It is increasingly almost imperial in style, with broad, high-level policy announcements made in Beijing, sometimes of almost Delphic succinctness, which are then handed down to various levels of government to do as they will. Exactly how and when the discussion amongst Xi and his Politburo colleagues on the best response to COVID happened is unclear. In a world where almost every political system seems to leak incessantly, the Chinese one is unique in maintaining its opacity and secretiveness – no mean achievement in the social media era.

The Communist Party is very aware of how relatively small incidents can mount up and then generate overwhelming force. It itself coined the Chinese phrase ‘a single spark can start a prairie fire.’

Rumors of clashes between Xi and his premier Li Keqiang on the effectiveness of the current response remain just that – rumors, with precious little hard evidence to back them up. Who in the current imperial system might dare to speak from the ranks and say that policy must change is unclear. Scientists should deal in hard facts – but we all know that science is susceptible to politicization. Experts in China have to offer their expertise in a highly political context. A declaration that the current approach is not fit for purpose can easily be reinterpreted as an attempt to launch an indirect attack on the core leader. With an important Congress coming up later this year, at which Xi is expected to be appointed for another five years in power, sensitivities are even more intense than normal. It is little wonder that the COVID strategy status quo settled on last year has not shifted.

Things, however, may well change, and change quickly. China is moving into tricky economic territory. The impact of the pandemic on global supply chains, along with the various stresses domestically on the housing market, and productivity, have shrunk expectations for growth. A predicted 6% in the earlier part of the year now looks overly ambitious. There is a real possibility China might experience a recession. At a moment like this, the government, which after all operates as a constant crisis and risk management entity, might do what it does best and prompt rapid, and dramatic, changes.

The handling of COVID-19 might look like further proof that Chinese politics under Xi is repressive and zero-sum. But even in an autocratic state like the current People’s Republic, the pandemic will not leave politics unchanged.

This doesn’t mean that China’s COVID-19 bind gets any easier. Like the country’s serious demographic challenges, with a rapidly aging population, the only thing the government will be picking an argument with is reality as it proceeds into the future. As with Europe and the US, being more liberal about facing COVID-19 will involve accepting some of the harsh consequences – rising fatalities, particularly for the elderly and vulnerable, and health systems put under enormous stress. In such a huge, complex country, and of enormous geopolitically importance, a misstep could easily lead to huge and unwanted consequences, generating discontent and triggering mass protests in a way reminiscent of 1989. The Communist Party is very aware of how relatively small incidents can mount up and then generate overwhelming force. It itself coined the Chinese phrase ‘a single spark can start a prairie fire.’ One such spark – the introduction of Marxism into China in the 1910s – led to its gaining of power three decades later.

The handling of COVID-19 might look like further proof that Chinese politics under Xi is repressive and zero-sum. But I suspect that even in an autocratic state like the current People’s Republic, the pandemic will not leave politics unchanged. In particular, the middle classes in cities like Shanghai have had their patience tested in recent months. This is the key group for Xi, the heart of his new innovative, more self-dependent, higher-quality service sector workers in an urbanized economy. Their support remains crucial if Xi is able to steer China towards the moment when it hopes it will become the world’s largest economy. Policies to try to placate them by addressing imbalances, critical environmental issues and improving public health are likely to only increase. Delivery however will be key.

Faced with a potentially life-threatening infectious disease, the Party can throw out injunctions and claim it has been the victim of bad luck. But an ailing economy and no clear signs of the government knowing how to manage this will prove a toxic mixture for it. Xi and his third term in office will be all about delivery. The question is whether, even with the formidable suite of powers he has, he can do this. Governing China has always been the ultimate political challenge. COVID-19 has made that even harder.

“2022 Monkeypox Outbreak: Situational Awareness” with Syra Madad [Zoom]

[from Harvard Kennedy School’s Belfer Center, part of Harvard University]

Thursday, July 21, 2:30-4:00 PM EDT

RSVP (Required)

The 2022 Monkeypox outbreak continues to expand with case counts mounting in many countries. This seminar will cover where we are in the global fight against monkeypox, where we may be headed as a nation, and what we need to do right now to mitigate the growing threat of monkeypox. Join Belfer Fellow Dr. Syra Madad in conversation with Kai Kupferschmidt, Dr. Krutika Kuppalli, Dr. Anne Rimoin, Dr. Boghuma Kabisen Titanji, and Dr. Jay K. Varma.

About the Speakers

Dr. Anne Rimoin is a Professor of Epidemiology at the UCLA Fielding School of Public Health. She is the Gordon-Levin Endowed Chair in Infectious Diseases and Public Health. Dr. Rimoin is the director of the Center for Global and Immigrant Health and is an internationally recognized expert on emerging infections, global health, surveillance systems, and vaccination.

Rimoin has been working in the DRC since 2002, where she founded the UCLA-DRC Health Research and Training Program to train U.S. and Congolese epidemiologists to conduct high-impact infectious disease research in low-resource, logistically-complex settings.

Dr. Rimoin’s research focuses on emerging and vaccine-preventable diseases. It has led to fundamental understandings of the epidemiology of human monkeypox in post-eradication of smallpox, long-term immunity to Ebola virus in survivors and durability of immune response to Ebola virus vaccine in health workers in DRC. Her current research portfolio includes studies of COVID-19, Ebola, Marburg, Monkeypox and vaccine-preventable diseases of childhood.

Boghuma Kabisen Titanji (MD, MSc., DTM&H, PhD) is a Cameroonian born physician-scientist and Assistant Professor of Medicine at Emory University in Atlanta. She obtained her MD from the University of Yaoundé I in Cameroon and worked for two years after graduation as a medical officer, before pursuing post-graduate research training in London, United Kingdom. As an awardee of the prestigious Commonwealth Scholarship program, she obtained a Masters Degree in Tropical Medicine and International Health from the London School of Hygiene and Tropical Medicine, a diploma in Tropical Medicine and Hygiene from the Royal College of Physicians and a Ph.D. in Virology from University College London. Dr. Titanji joined Emory University School of Medicine in 2016 where she completed a residency in Internal Medicine, on the ABIM research pathway and a fellowship Infectious Diseases. She has three parallel career interests: translational and clinical research in HIV and emerging virus infections, science communication, and global health. Her clinical focus is general infectious diseases and people with HIV. Her current research focuses on chronic inflammation as a mediator of cardiovascular disease in people with HIV. She is passionate about leveraging translational research to improve the care of people with HIV, global health equity and using science to influence health policy through science communication and advocacy.

Jay K. Varma, MD is a Professor of Population Health Sciences and Director of the Cornell Center for Pandemic Prevention and Response at Weill Cornell Medicine. Dr. Varma is an expert on the prevention and control of diseases, having led epidemic responses, developed global and national policies, and led large-scale programs that have saved hundreds of thousands of lives in China, Southeast Asia, Africa, and the United States. After graduating magna cum laude with highest honors from Harvard, Dr. Varma completed medical school, internal medicine residency, and chief residency at the University of California, San Diego School of Medicine. From 2001-2021, he worked for the U.S. Centers for Disease Control and Prevention with postings in Atlanta, Thailand, China, Ethiopia, and New York City. From April 2020 – May 2021, he served as the principal scientific spokesperson and lead for New York City’s COVID-19 response. Dr. Varma has authored 143 scientific manuscripts, 13 essays, and one book.

Kai Kupferschmidt is a science journalist based in Berlin, Germany. He is a contributing correspondent for Science where he often covers infectious diseases. Kai received a diploma in molecular biomedicine from the University of Bonn, Germany and later visited the Berlin Journalism School. He has won several awards for his work, including the Journalism Prize of the German AIDS Foundation. Together with two colleagues he runs a podcast on global health called Pandemia [German]. He has also written two books, one about infectious diseases and one about the science of the color blue.

Krutika Kuppalli, MD, FIDSA is a Medical Officer for Emerging Zoonotic Diseases and Clinical Management in the Health Emergencies Program at the World Health Organization where she currently supports activities for the Monkeypox outbreak and COVID-19 pandemic. She completed her Internal Medicine residency and Infectious Diseases fellowship at Emory University, a Post-Doctoral Fellowship in Global Public Health at the University of California, San Diego and the Emerging Leader in Biosecurity Fellowship at the Johns Hopkins Center for Health Security. Dr. Kuppalli currently serves on the American Society of Tropical Medicine and Hygiene (ASTMH) Trainee Committee and is the Chair of the Infectious Diseases Society of America (IDSA) Global Health Committee.

Dr. Kuppalli was previously awarded the NIH Fogarty International Clinical Research Fellowship and conducted research in Southern India to understand barriers to care and how emerging infections impacted persons living with HIV/AIDS. She was the medical director of a large Ebola Treatment Unit in Sierra Leone during the 2014 West Africa Ebola outbreak, helped lead the development and implementation of pandemic response preparedness activities in resource limited settings, and has consulted on the development of therapeutics for emerging pathogens. Her clinical and research interests focus on health systems strengthening in resource limited settings, research and clinical care for emerging infections, outbreak preparedness and response, and policy. She has worked in numerous countries including Ethiopia, India, Sierra Leone, Uganda, and Haiti.

During the COVID-19 pandemic Dr. Kuppalli served as a consultant for the San Francisco Department of Health and helped develop and operationalize a field hospital. She served as an expert witness to the U.S. Congress, Financial Services Committee Task Force on Artificial Intelligence (AI) about how digital technologies may be leveraged for exposure notification and contact tracing to improve the pandemic response. She also collaborated with the Brennan Center for Justice to develop guidelines to inform “Healthy in-person Voting” in advance of the 2020 U.S. election and testified before the U.S. House Select Subcommittee regarding these recommendations. Prior to her position at WHO, she was the medical lead for COVID-19 vaccine rollout at the Medical University of South Carolina (MUSC) and helped coordinate vaccine education events for the staff and community and oversaw the reporting of adverse vaccine events.

Since joining WHO in August 2021, Dr. Kuppalli has been part of the WHO headquarters incident management team (IMST) for COVID-19, the clinical characterization and management working group for COVID-19, the COVID-19 therapeutics steering committee, and is the technical focal point for the post COVID-19 condition (Long COVID) steering committee. She is a member of the secretariat on the scientific advisory group on the origins of emerging and re-emerging infectious diseases (SAGO) which was convened by the Director General to understand and investigate the origins of SARS-CoV-2 and other novel pathogens. More recently since the development of the multi-country monkeypox outbreak she has been part of the IMST at WHO as one of the clinical management focal points. In this capacity she was part of the WHO core group that helped write the recently published Clinical Management and Infection Prevention and Control guidelines for Monkeypox and advising on the clinical endpoints for the global CORE therapeutics protocol.

Dr. Kuppalli is recognized as a scientific expert in global health, biosecurity and outbreak response. She was recognized by NPR Source of The Week early in the pandemic as an expert to follow and named to Elemental’s 50 Experts to Trust in a Pandemic. She has been a frequent contributor to numerous domestic and international media outlets including The New York Times, NPR, Reuters, The Washington Post, Vox, Stat News, San Francisco Chronicle, Forbes, NBC Bay Area, BBC News.

Science-Watching: Forecasting New Diseases in Low-Data Settings Using Transfer Learning

[from London Mathematical Laboratory]

by Kirstin Roster, Colm Connaughton & Francisco A. Rodrigues

Abstract

Recent infectious disease outbreaks, such as the COVID-19 pandemic and the Zika epidemic in Brazil, have demonstrated both the importance and difficulty of accurately forecasting novel infectious diseases. When new diseases first emerge, we have little knowledge of the transmission process, the level and duration of immunity to reinfection, or other parameters required to build realistic epidemiological models. Time series forecasts and machine learning, while less reliant on assumptions about the disease, require large amounts of data that are also not available in early stages of an outbreak. In this study, we examine how knowledge of related diseases can help make predictions of new diseases in data-scarce environments using transfer learning. We implement both an empirical and a synthetic approach. Using data from Brazil, we compare how well different machine learning models transfer knowledge between two different dataset pairs: case counts of (i) dengue and Zika, and (ii) influenza and COVID-19. In the synthetic analysis, we generate data with an SIR model using different transmission and recovery rates, and then compare the effectiveness of different transfer learning methods. We find that transfer learning offers the potential to improve predictions, even beyond a model based on data from the target disease, though the appropriate source disease must be chosen carefully. While imperfect, these models offer an additional input for decision makers for pandemic response.

Introduction

Epidemic models can be divided into two broad categories: data-driven models aim to fit an epidemic curve to past data in order to make predictions about the future; mechanistic models simulate scenarios based on different underlying assumptions, such as varying contact rates or vaccine effectiveness. Both model types aid in the public health response: forecasts serve as an early warning system of an outbreak in the near future, while mechanistic models help us better understand the causes of spread and potential remedial interventions to prevent further infections. Many different data-driven and mechanistic models were proposed during the early stages of the COVID-19 pandemic and informed decision-making with varying levels of success. This range of predictive performance underscores both the difficulty and importance of epidemic forecasting, especially early in an outbreak. Yet the COVID-19 pandemic also led to unprecedented levels of data-sharing and collaboration across disciplines, so that several novel approaches to epidemic forecasting continue to be explored, including models that incorporate machine learning and real-time big data data streams. In addition to the COVID-19 pandemic, recent infectious disease outbreaks include Zika virus in Brazil in 2015, Ebola virus in West Africa in 2014–16, Middle East respiratory syndrome (MERS) in 2012, and coronavirus associated with severe acute respiratory syndrome (SARS-CoV) in 2003. This trajectory suggests that further improvements to epidemic forecasting will be important for global public health. Exploring the value of new methodologies can help broaden the modeler’s toolkit to prepare for the next outbreak. In this study, we consider the role of transfer learning for pandemic response.

Transfer learning refers to a collection of techniques that apply knowledge from one prediction problem to solve another, often using machine learning and with many recent applications in domains such as computer vision and natural language processing. Transfer learning leverages a model trained to execute a particular task in a particular domain, in order to perform a different task or extrapolate to a different domain. This allows the model to learn the new task with less data than would normally be required, and is therefore well-suited to data-scarce prediction problems. The underlying idea is that skills developed in one task, for example the features that are relevant to recognize human faces in images, may be useful in other situations, such as classification of emotions from facial expressions. Similarly, there may be shared features in the patterns of observed cases among similar diseases.

The value of transfer learning for the study of infectious diseases is relatively under-explored. The majority of existing studies on diseases remain in the domain of computer vision and leverage pre-trained neural networks to make diagnoses from medical images, such as retinal diseases, dental diseases, or COVID-19. Coelho and colleagues (2020) explore the potential of transfer learning for disease forecasts. They train a Long Short-Term Memory (LSTM) neural network on dengue fever time series and make forecasts directly for two other mosquito-borne diseases, Zika and Chikungunya, in two Brazilian cities. Even without any data on the two target diseases, their model achieves high prediction accuracy four weeks ahead. Gautam (2021) uses COVID-19 data from Italy and the USA to build an LSTM transfer model that predicts COVID-19 cases in countries that experienced a later pandemic onset.

These studies provide empirical evidence that transfer learning may be a valuable tool for epidemic forecasting in low-data situations, though research is still limited. In this study, we aim to contribute to this empirical literature not only by comparing different types of knowledge transfer and forecasting algorithms, but also by considering two different pairs of endemic and novel diseases observed in Brazilian cities, specifically (i) dengue and Zika, and (ii) influenza and COVID-19. With an additional analysis on simulated time series, we hope to provide theoretical guidance on the selection of appropriate disease pairs, by better understanding how different characteristics of the source and target diseases affect the viability of transfer learning.

Zika and COVID-19 are two recent examples of novel emerging diseases. Brazil experienced a Zika epidemic in 2015–16 and the WHO declared a public health emergency of global concern in February 2016. Zika is caused by an arbovirus spread primarily by mosquitoes, though other transmission methods, including congenital and sexual have also been observed. Zika belongs to the family of viral hemorrhagic fevers and symptoms of infection share some commonalities with other mosquito-borne arboviruses, such as yellow fever, dengue fever, or chikungunya. Illness tends to be asymptomatic or mild but can lead to complications, including microcephaly and other brain defects in the case of congenital transmission.

Given the similarity of the pathogen and primary transmission route, dengue fever is an appropriate choice of source disease for Zika forecasting. Not only does the shared mosquito vector result in similar seasonal patterns of annual outbreaks, but consistent, geographically and temporally granular data on dengue cases is available publicly via the open data initiative of the Brazilian government.

COVID-19 is an acute respiratory infection caused by the novel coronavirus SARS-CoV-2, which was first detected in Wuhan, China, in 2019. It is transmitted directly between humans via airborne respiratory droplets and particles. Symptoms range from mild to severe and may affect the respiratory tract and central nervous system. Several variants of the virus have emerged, which differ in their severity, transmissibility, and level of immune evasion.

Influenza is also a contagious respiratory disease that is spread primarily via respiratory droplets. Infection with the influenza virus also follows patterns of human contact and seasonality. There are two types of influenza (A and B) and new strains of each type emerge regularly. Given the similarity in transmission routes and to a lesser extent in clinical manifestations, influenza is chosen as the source disease for knowledge transfer to model COVID-19.

For each of these disease pairs, we collect time series data from Brazilian cities. Data on the target disease from half the cities is retained for testing. To ensure comparability, the test set is the same for all models. Using this empirical data, as well as the simulated time series, we implement the following transfer models to make predictions.

Random forest: First, we implement a random forest model which was recently found to capture well the time series characteristics of dengue in Brazil. We use this model to make predictions for Zika without re-training. We also train a random forest model on influenza data to make predictions for COVID-19. This is a direct transfer method, where models are trained only on data from the source disease.
Random forest with TrAdaBoost: We then incorporate data from the target disease (i.e., Zika and COVID-19) using the TrAdaBoost algorithm together with the random forest model. This is an instance-based transfer learning method, which selects relevant examples from the source disease to improve predictions on the target disease.
Neural network: The second machine learning algorithm we deploy is a feed-forward neural network, which is first trained on data of the endemic disease (dengue/influenza) and applied directly to forecast the new disease.
Neural network with re-training and fine-tuning: We then retrain only the last layer of the neural network using data from the new disease and make predictions on the test set. Finally, we fine-tune all the layers’ parameters using a small learning rate and low number of epochs. These models are examples of parameter-based transfer methods, since they leverage the weights generated by the source disease model to accelerate and improve learning in the target disease model.
Aspirational baseline: We compare these transfer methods to a model trained only on the target disease (Zika/COVID-19) without any data on the source disease. Specifically, we use half the cities in the target dataset for training and the other half for testing. This gives a benchmark of the performance in a large-data scenario, which would occur after a longer period of disease surveillance.

The remainder of this paper is organized as follows. The models are described in more technical detail in Section 2. Section 3 shows the results of the synthetic and empirical predictions. Finally, Section 4 discusses practical implications of the analyses.

Access the full paper [via institutional access or paid download].

Russia-Watching: Economic Dysfunctionalities

[from the Russian Analytical Digest]

This issue deals with dysfunctionalities in the Russian economy. The first three contributions look at the direct impact of sanctions. Ilya Matveev provides an overview, while Andrei Yakovlev compares the government’s anti-sanctions measures to its reaction to the economic impact of the COVID-19 pandemic. Janis Kluge offers a more detailed picture of the short- and long-term effects of the unfolding sanction regime. Michael Rochlitz then goes on to explain the lack of strategic planning in the country’s economic policy. Finally, Olga Masyutina and Ekaterina Paustyan provide a case study of inefficient governance mechanisms looking at waste management.

Read the full issue [archived PDF].

Analyses

Sanctions against Russia: No Blitzkrieg, but a Devastating Effect Nonetheless

by Ilya Matveev

In response to the Russian invasion of Ukraine, over 40 countries have introduced sanctions against Russia. The new restrictions concern finance, trade, logistics, and personal sanctions against businessmen and officials. In addition, more than 1,000 companies have ceased or limited their activities in Russia. In this article, Ilya Matveev argues that the sanctions, despite their unprecedented scale, have not led to the collapse of the Russian economy, yet their effect is dramatic, multi-faceted, and will increase over time.

Read the full issue [archived PDF].

Fighting the Pandemic and Fighting Sanctions: Can the Russian Economy Now Benefit from Its Experience with Anti-Crisis Measures?

by Andrei Yakovlev

Faced with tough international sanctions in reaction to its war against Ukraine, the Russian government has resorted to measures developed during the COVID-19 pandemic in order to stabilize the economy. This short analysis discusses the rationale behind this approach and demonstrates its limits.

Read the full issue [archived PDF].

Russia’s Economy under Sanctions: Early Impact and Long-Term Outlook

by Janis Kluge

Four months after a coalition of Western states imposed unprecedented sanctions on Russia, the Russian economy seems to be holding up better than expected. The Central Bank has managed to stabilize the country’s financial system and Russian officials are trying to project optimism about the future. However, this optimism is likely to be short-lived. The sanctions’ effects are only just beginning to unfold: supply-chain problems are intensifying and demand is falling quickly. In the longer run, Russia’s economy will become more primitive as it partially decouples from international trade. To avoid social tensions, the government will intervene to support Russian businesses, leading to more protectionism and a larger state footprint in the economy.

Read the full issue [archived PDF].

Why Russia Is Lacking an Economic Strategy for the Future

by Michael Rochlitz

Even before the economic crisis caused by Russia’s full-scale attack against Ukraine and the ensuing sanctions, the Russian economy was plagued by a number of growing problems. As a result, Russia’s economy has hardly grown for almost a decade, with an average annual growth rate of just 0.5% between 2013 and 2021. However, the Russian government does not have a strategy for addressing the fundamental economic challenges that are looming just over the horizon. There also seem to be no public debates about these challenges, whether in the policy circles around the government or among the wider public.

Read the full issue [archived PDF].

The Political Economy of Waste Management in Russia

by Olga Masyutina and Ekaterina Paustyan

The problem of household waste is one of the numerous environmental challenges facing Russia today. The 2019 nation-wide waste management reform was designed to tackle this problem by promoting recycling. However, the reform is stalling, due in large part to the nature of state-business relations in Russia. The lack of transparency in the public procurement process and the importance of personal connections between businesses and the federal and regional authorities undermine the implementation of the reform and produce suboptimal outcomes in the fight against waste.

Read the full issue [archived PDF].

Coronavirus Update: Fall Boosters Could Have Bits of Omicron

[from ScienceNews Coronavirus Update, by Erin Garcia de Jesús]

For all the coronavirus variants that have thrown pandemic curve balls—including alpha, beta, gamma, delta—COVID-19 vaccines have stayed the same. That could change this fall.

Yesterday, an advisory committee to the U.S. Food and Drug Administration met to discuss whether vaccine developers should update their jabs to include a portion of the omicron variant—the version of the coronavirus that currently dominates the globe. The verdict: The omicron variant is different enough that it’s time to change the vaccines. Exactly how is up in the air; the FDA still has to weigh in and decide what versions of the coronavirus will be in the shot.

“This doesn’t mean that we are saying that there will be boosters recommended for everyone in the fall,” Amanda Cohn, chief medical officer for vaccine policy at the U.S. Centers for Disease Control and Prevention said at the June 28 advisory meeting. “But my belief is that this gives us the right vaccine for preparation for boosters in the fall.”

The decision to update COVID-19 vaccines didn’t come out of nowhere. In the two-plus years that the coronavirus has been spreading around the world, it has had a few “updates” of its own—mutating some of its proteins that allow the virus to more effectively infect our cells or hide from our immune systems.

Vaccine developers had previously crafted vaccines to tackle the beta variant that was first identified in South Africa in late 2020. Those were scrapped after studies showed that current vaccines remained effective.

The current vaccines gave our immune systems the tools to recognize variants such as beta and alpha, which each had a handful of changes from the original SARS-CoV-2 virus that sparked the pandemic. But the omicron variant is a slipperier foe. Lots more viral mutations combined with our own waning immunity mean that omicron can gain a foothold in the body. And vaccine protection isn’t as good as it once was at fending off COVID-19 symptoms.

The shots still largely protect people from developing severe symptoms, but there has been an uptick in hospitalizations and deaths among older age groups, Heather Scobie, deputy team lead of the CDC’s Surveillance and Analytics Epidemiology Task Force said at the meeting. And while it’s impossible to predict the future, we could be in for a tough fall and winter, epidemiologist Justin Lessler of the University of North Carolina at Chapel Hill said at the meeting. From March 2022 to March 2023, simulations project that deaths from COVID-19 in the United States might number in the tens to hundreds of thousands.

A switch to omicron-containing jabs may give people an extra layer of protection for the upcoming winter. Pfizer–BioNTech presented data at the meeting showing that updated versions of its mRNA shot gave clinical trial participants a boost of antibodies that recognize omicron. One version included omicron alone, while the other is a twofer, or bivalent, jab that mixes the original formulation with omicron. Moderna’s bivalent shot boosted antibodies too. Novavax, which developed a protein-based vaccine that the FDA is still mulling whether to authorize for emergency use, doesn’t have an omicron-based vaccine yet, though the company said its original shot gives people broad protection, generating antibodies that probably will recognize omicron.

Pfizer and Moderna both updated their vaccines using a version of omicron called BA.1, which was the dominant variant in the United States in December and January. But BA.1 has siblings and has already been outcompeted by some of them.

Since omicron first appeared late last year, “we’ve seen a relatively troubling, rapid evolution of SARS-CoV-2,” Peter Marks, director of the FDA’s Center for Biologics Evaluation and Research in Silver Spring, Maryland, said at the advisory meeting.

Now, omicron subvariants BA.2, BA.2.12.1, BA.4 and BA.5 are the dominant versions in the United States and other countries. The CDC estimates that roughly half of new U.S. infections the week ending June 25 were caused by either BA.4 or BA.5. By the time the fall rolls around, yet another new version of omicron—or a different variant entirely—may join their ranks. The big question is which of these subvariants to include in the vaccines to give people the best protection possible.

BA.1, the version already in the updated vaccines, may be the right choice, virologist Kanta Subbarao said at the FDA meeting. An advisory committee to the World Health Organization, which Subbarao chairs, recommended on June 17 that vaccines may need to be tweaked to include omicron, likely BA.1. “We’re not trying to match [what variants] may circulate,” Subbarao said. Instead, the goal is to make sure that the immune system is as prepared as possible to recognize a wide variety of variants, not just specific ones. The hope is that the broader the immune response, the better our bodies will be at fighting the virus off even as it evolves.

The variant that is farthest removed from the original virus is probably the best candidate to accomplish that goal, said Subbarao, who is director of the WHO’s Collaborating Center for Reference and Research on Influenza at the Doherty Institute in Melbourne, Australia. Computational analyses of how antibodies recognize different versions of the coronavirus suggest that BA.1 is probably the original coronavirus variant’s most distant sibling, she said.

Some members of the FDA advisory committee disagreed with choosing BA.1, instead saying that they’d prefer vaccines that include a portion of BA.4 or BA.5. With BA.1 largely gone, it may be better to follow the proverbial hockey puck where it’s going rather than where it’s been, said Bruce Gellin, chief of Global Public Health Strategy with the Rockefeller Foundation in Washington, D.C. Plus, BA.4 and BA.5 are also vastly different from the original variant. Both BA.4 and BA.5 have identical spike proteins, which the virus uses to break into cells and the vaccines use to teach our bodies to recognize an infection. So when it comes to making vaccines, the two are somewhat interchangeable.

There are some real-world data suggesting that current vaccines offer the least amount of protection from BA.4 and BA.5 compared with other omicron subvariants, Marks said. Pfizer also presented data showing results from a test in mice of a bivalent jab with the original coronavirus strain plus BA.4/BA.5. The shot sparked a broad immune response that boosted antibodies against four omicron subvariants. It’s unclear what that means for people.

Not everyone on the FDA advisory committee agreed that an update now is necessary—two members voted against it. Pediatrician Henry Bernstein of Zucker School of Medicine at Hofstra/Northwell in Uniondale, N.Y., noted that the current vaccines are still effective against severe disease and that there aren’t enough data to show that any changes would boost vaccine effectiveness. Pediatric infectious disease specialist Paul Offit of Children’s Hospital of Philadelphia said that he agrees that vaccines should help people broaden their immune responses, but he’s not yet convinced omicron is the right variant for it.

Plenty of other open questions remain too. The FDA could authorize either a vaccine that contains omicron alone or a bivalent shot, although some data hinted that a bivalent dose might spark immunity that could be more durable. Pfizer and Moderna tested their updated shots in adults. It’s unclear what the results mean for kids. Also unknown is whether people who have never been vaccinated against COVID-19 could eventually start with such an omicron-based vaccine instead of the original two doses.

Maybe researchers will get some answers before boosters start in the fall. But health agencies need to make decisions now so vaccine developers have a chance to make the shots in the first place. Unfortunately, we’re always lagging behind the virus, said pediatrician Hayley Gans of Stanford University. “We can’t always wait for the data to catch up.”

OFR Working Paper Finds Cash Biases Measurement of the Stock Return Correlations

[from the U.S. Office of Financial Research]

Today, the U.S. Office of Financial Research published a working paper, “Cash-Hedged Stock Returns” [archived PDF], and an accompanying blog (below), regarding firms’ cash holdings and the implications for asset prices and financial stability.

Cash holdings are important for financial stability because of their value in crises. Corporate cash piles vary across companies and over time. Firms’ cash holdings typically earn low returns, and their cash returns are correlated across firms. Thus, the asset pricing results are important for investors managing a portfolio’s risk and policymakers concerned about sources of vulnerability.

The working paper [archived PDF] shows how investors can hedge cash on firms’ balance sheets when making portfolio choices. Cash generates variation in beta estimates, and the working paper decomposes stock betas into components that depend on the firm’s cash holding, return on cash, and cash-hedged return. Common asset pricing premia have large implicit cash positions, and portfolios of cash-hedged premia often have higher Sharpe ratios, used by investors to understand a return on investment, because of the correlation between firms’ cash returns. The paper shows the value of a dollar increased in 2020, and firms hold cash because they are riskier.

Read the working paper [archived PDF].

OFR Finds Large Cash Holdings Can Lead to Mismeasuring Risk

[from the OFR blog, by Sharon Ross]

Cash is necessary for companies’ operations. Firms use cash to make payments, finance investments, and manage risk. But holding cash comes at a cost: its low pecuniary return. Published today by the OFR, the working paper, “Cash-Hedged Stock Returns” [archived PDF], shows that the cash returns of publicly traded, non-financial firms are correlated. Since cash returns are a part of equity returns, investors that are using equity return correlations to measure risk can mismeasure risk.

We show the importance of cash for systemic risk by documenting the value of cash in crises, showing that firms hold cash in part due to risk management and studying how cash biases the measurement of the interconnectedness of stock returns. The consequences of cash are important for policymakers monitoring aggregate risks, and sources of market vulnerability and for investors making portfolio choices.

Cash holdings are important for financial stability because of their value in crises. Several papers document a “dash for cash” during the initial panicked stages of the coronavirus 2019 (COVID-19) pandemic when firms rushed to hold cash in their coffers. The dash for cash was driven by firms drawing down on lines of credit from banks, which in turn affected bank lending. The dash for cash highlighted the critical role of firms’ cash holdings and returns in understanding risk in the financial system.

We show the value of a dollar increased in 2020. Moreover, our results show that firms may hold cash because they are riskier, as opposed to firms with high cash shares being less risky due to their cash holdings. Our results are consistent with a precautionary savings motive for holding cash. In other words, firms hold cash for risk management, in part to weather bad times.

Cash is a growing share of public firms’ assets. The value-weighted U.S. stock market held 22% of its assets in cash in December 2020 compared to 8% in the 1980s. An investor buying the market in 2020 ends up with an implicit cash position three times larger than in 1980. Individual firms vary in how much cash they hold. As cash holdings increase, it is important to understand how cash holdings affect returns, which in turn impacts who chooses to invest in the firms.

Cash returns are correlated across firms, and cash biases measurement of the interconnectedness of stock returns, making it a risk for financial stability. As a result, the asset pricing results are important both for investors managing portfolio risk and for policymakers concerned about interconnected returns.

We argue that the value of corporate cash is distinct, and we can separate the value of cash and the value of the firm’s primary business. We show how investors can explicitly account for the effect of corporate cash holdings when forming a portfolio. When an investor owns stock in a company with substantial cash, the investor has an implicit cash position managed by the company—something the investor might not intend. We argue that investors should account for the effect of corporate cash holdings in the portfolio decision to measure a portfolio’s risk. Firms’ cash management is not consistent across firms, and investors may want to manage their cash positions themselves. Policymakers should be aware of investors’ choices in cash because of investors’ portfolio risk and the implications for aggregate risk.

We separate a company’s stock return into its cash and non-cash components, and we show that using the non-cash return gives a more informative correlation structure across stocks. In other words, if investors take out the correlated cash returns, the remaining return is less correlated, yielding portfolios that provide better diversification. We show how cash holdings and returns affect the returns of standard asset pricing strategies and asset pricing models like the capital asset pricing model (CAPM).

As cash holdings of public firms increase, it is important that policymakers understand how these increases impact stock returns for both individual firms and the aggregate market. Cash returns are correlated across firms, and cash biases the measurement of the interconnectedness of stock returns. This correlation is important both for investors who are managing a portfolio’s risk and policymakers concerned about sources of vulnerability stemming from interconnected returns.