Speevr logo

COVID-19 is a developing country pandemic

COVID-19 is a developing country pandemic | Speevr

“Has global health been subverted?” This question was asked exactly a year ago in The Lancet. At the time, the pandemic had already spread across the globe, but mortality remained concentrated in richer economies. Richard Cash and Vikram Patel declared that “for the first time in the post-war history of epidemics, there is a reversal of which countries are most heavily affected by a disease pandemic.”

What a difference a year makes. We know now that this is actually a developing-country pandemic—and has been that for a long time. In this blog, we review the officially published data and contrast them with brand new estimates on excess mortality (kindly provided by the folks at the Economist). We will argue that global health has not been subverted. In fact, compared to rich countries, the developing world appears to be facing very similar—if not higher—mortality rates. Its demographic advantage of a younger population may have been entirely offset by higher infection prevalence and age-specific infection fatality.
Official data: Developing countries account for half of global mortality
The statement that this is a developing-country pandemic is not self-evident when we look at the official statistics (Figures 1 and 2). When it comes to per capita mortality, the official data suggest that the pandemic has been most intense in high-income countries (HICs). Cumulative mortality rates and—with a few exceptions—daily mortality rates have been higher for richer countries. Most people don’t look any further and decide that HICs have suffered more.

But it is necessary to also consider mortality shares. Mortality rates measure intensity, which highlights country performance, but they do a poor job in reflecting the contribution to global mortality. Given that the developing world is both younger and more populous than the HICs, we would expect its mortality rates to be lower and its mortality shares to be higher. Official data indeed show that the developing-country share in cumulative mortality is high: slightly above 50 percent (Figure 3).
This wasn’t always the case: The global mortality distribution has seen big swings since the onset of the pandemic. One upper-middle-income country (UMIC) dominated the global death toll initially: China. Soon after, outbreaks in HICs lifted their share in global mortality to almost 90 percent. A shift to UMICs followed, then quickly to lower-middle-income countries (LMICs). When winter came to the northern hemisphere, a new wave drove up the HIC share. More recently it has again started to recede. Throughout the period, the reported share of low-income countries (LICs) remained negligible.

The daily mortality distribution puts into sharper focus the most recent trends (Figure 4). The good news is that, in part thanks to vaccines, HIC mortality rates have plummeted. The bad news is that rates have spiked in LMICs and remain at high levels in UMICs. As a result, 2021 saw a complete shift in the daily mortality distribution: The LMIC share rose from 7 to 42 percent; the UMIC share from 33 to 42 percent; and the HIC share dropped from 59 percent to 15 percent—a trend that may become more pronounced in coming months.
Excess mortality estimates: The share of developing countries may be as high as 86 percent
The Economist has just published new estimates of excess deaths. Excess deaths measure the difference between observed and expected deaths throughout of the pandemic. Previously confined to mainly the richer countries, excess deaths are thanks to the new estimates available for the entire world. A gradient-boosting machine-learning algorithm helped fill the data gaps on the basis of 121 predictive indicators that are comprehensively available. With this method, global excess deaths are estimated at 7 million to 13 million, with 10 million as the midpoint.
Figure 5 shows the detailed results by World Bank income classification. Two patterns are striking:

Excess mortality rates for the developing world are much higher than what reported COVID-19 mortality data suggest: 2.5 times higher for UMICs, 12 times more for LMICs, and 35 times greater for LICs. For HICs they are practically the same—actually about 3 percent lower. To see this, compare the dashed and solid lines, which represent the population-weighted averages for each income group (see also Figure 6 for the time series).
Non-reported COVID-19 deaths and other excess deaths are much larger than reported COVID-19 deaths especially in poorer countries (compare the darker and lighter shades of each bar). The small gap for HICs may reflect the opposite effects of inadequate testing and “general equilibrium” impacts of the pandemic (such as the vanished flu season).

Perhaps the most striking result is the compression of mortality rates across income groups (Figure 6). Mortality rates in LMICs are the highest (157), then UMICs and HICs (both 118) and then LICs (98). But relative to the dispersion seen in the reported COVID-19 mortality rates (Figure 1), one could say they’re “about the same.” These estimates are subject to uncertainty, but the 95% confidence intervals are considerably above the reported mortality COVID-19 rates, particularly among UMICs and LMICs (which together represent 75 percent of the world’s population).

The midpoint estimates entail a completely different mortality distribution (Figure 7). If the midpoints hold true, the developing world may account for 86 percent of global mortality (as of May 10). This compares to a share of 55 percent using officially reported data. The biggest increases are in the share of LMICs and LICs.
While virtually all developing countries are contributing to the rise (see Figure 5), rising mortality rates in the developing world’s most populous countries will produce the largest absolute impact on global mortality. We can see this very vividly in Figure 8, which shows the cumulative death toll in millions of souls. The tragedy that continues to unfold in India has claimed a very large death toll of close to 3 million. While considerable uncertainty surrounds these estimates, alternative methods suggest they are in the ballpark.

Demographic advantage squandered
It is useful to do a thought experiment (Figure 9). Imagine all countries—rich and poor—faced the same epidemiological odds; that is, suppose that everyone has the same chance of getting infected and everyone faces the same age-specific fatality rates. Under these conditions, we would capture the pure effect of demography on the mortality distribution and obtain an estimate of the demographic advantage of the developing world.
In such a scenario, we expect the developing-world share in global mortality to be around 69 percent (Figure 9, middle bar in red). Applying common epidemiological parameters to the developing world boosts their share in global mortality because of the large absolute numbers of elderly. Though developing countries are younger, they are much more populous. As a result, the 60+ population of the developing world is 2.4 times larger than its counterpart in HICs. India alone, for example, counts 140 million people over 60; this is three times the number in Japan, which has the world’s oldest population after Monaco.
The generally younger age distributions of the developing world were believed to protect against a pandemic that discriminated against older people. The fact that the excess mortality shares (Figure 9, dark blue bar on the right) are significantly higher suggests that developing countries have likely squandered their demographic advantage as mortality is higher than demography alone would indicate. In other words, developing countries likely face worse epidemiological odds in the form of higher infection prevalence and/or more elevated age-specific infection fatality risk.

We can think of many structural reasons why that would be the case. Infection prevalence has likely been fueled by environmental factors such as urban density as well as poverty and informality, which complicate physical distancing. Over 1 billion people, mostly in developing countries, live in slums. Flattening the curve will therefore be more difficult in many developing countries, meaning that preexisting health capacity constraints will become binding more quickly.
Age-specific infection fatality rates are also likely more elevated than in HICs. Comorbidities are highly prevalent in the developing world. Of the 1.1 billion people with hypertension, two-thirds live in developing countries. Over the last decade, the number of cases and prevalence of diabetes has risen most quickly in the developing world. Moreover, limited access to quality health care in developing countries would mean that many ailments would be left untreated or undertreated, heightening vulnerability.
Official data point to a big shift in the mortality distribution to the developing world in recent months. Excess death estimates suggest that developing-country shares have been much higher than previously thought. Regardless of what the precise channels have been, one conclusion is clear: This is now—and has for a long time been—a developing-country pandemic.

Related Content

Partnerships for public purpose: The new PPPs for fighting the biggest crises of our time

Partnerships for public purpose: The new PPPs for fighting the biggest crises of our time | Speevr

We are currently facing some of the biggest crises of our time—climate change, learning loss, global health inequities, and more—and we need new approaches if we are to make meaningful progress toward tackling them. While there is no doubt that government plays an important role in helping to solve these critical issues and support social service programs to combat them, it has long been recognized that the private, or nonstate, sector has the potential to bring a multitude of benefits in either the delivery or financing of those services through public-private partnerships (PPPs). We see great potential for a new type of PPP—partnerships for public purpose* (new PPPs)—which emphasizes not whether the partner is from the public or private sector, but whether these collaborations and their impact have a publicly oriented purpose.

Reimagining public-private partnerships
PPPs have existed since at least the Roman Empire—in the form of concessions —for the construction of public baths and roads and the management of public markets. In fact, when most people think of PPPs, this Roman model is often what they picture—an antiquated model of government infrastructure outsourcing that pits public interest against private financial interest, rather than fostering collaboration, as the term partnership would imply. Furthermore, in this old model, the “private” sector implies for-profit industries, and thus nonprofit, third-sector, social-enterprise, and other stakeholders are often excluded. PPPs must evolve beyond this traditional definition in order to meet this moment.
Partnerships for public purpose, on the other hand, put the emphasis on multilateral relationships that support sustainable, long-term, and systemic impact. Instead of being constrained by private finance contracts or by cost-reduction strategies, these new PPPs encourage true partnerships with a diversity of stakeholders. By harnessing the technical expertise, approaches, and networks possessed by governments, private-sector organizations, nongovernmental actors, and donor agencies, these new PPPs can provide innovative mechanisms and promote collaboration to address challenges that traditional government resources and competing priorities struggle to negotiate. In doing so, they can increase capacity, improve quality, enhance equity, and target poor or marginalized populations for the delivery or financing of services.
An increasing number of these new PPPs are being put into practice and delivering results for citizens around the world. Over the past decade, outcome-based financing mechanisms such as social, development, and environmental impact bonds (SIBs, DIBs, and EIBs), as well as outcomes funds, have arisen as key forms of these new PPPs. These mechanisms bring together multiple stakeholders, which could include governments, NGOs, social enterprises, donors, and investors, to collaborate and deliver a set of outcomes—paying only when results are achieved. In an impact bond, investors (often impact investors) provide risk funding for social services programs, and this investment is repaid—oftentimes with a return—based on the program’s achievement of predetermined social and/or environmental outcomes. Outcomes funds pool funding to pay for outcomes in a particular issue or geographic area, potentially for distribution across many impact bonds. For more on how these mechanisms work, see “Impact bonds in developing countries: Early learnings from the field.”
What makes impact bonds and outcomes funds partnerships for public purpose?
Impact bonds and outcomes funds foster deep partnerships through various mechanisms inherent to the model. First of all, they bring together a multitude of actors that often don’t sit together at the table and—since they require the expertise and contributions of all stakeholders involved—each is dependent on the others for the initiative to function. Furthermore, while these mechanisms often face criticism for being costly and labor intensive to design, the time and resources dedicated upfront and throughout impact bond and outcome funds projects creates both collective accountability and ownership of the results. Finally, the model has the potential to create true partnerships with the beneficiaries themselves, who best understand their own needs, by including them in the design of the initiatives.
These models are also designed with public purpose at the fore, since the focus is on successful achievement of outcomes, such as improved learning levels or gainful and sustained employment. Moreover, since impact bonds and outcomes funds allow for the tailoring of services to disadvantaged populations, they can provide more comprehensive support across multiple sectors or issue areas, which can benefit all of society. In addition, these models ensure that public spending is effective: Tax dollars are not wasted on social services that don’t work, and they can reduce costly remedial services and increase benefits further down the road.
Impact bonds, outcomes funds, and other partnerships for public purpose (new PPPs) have the potential to support COVID-19 recovery while strengthening social service delivery and, in essence, changing its DNA.
Impact bonds have already demonstrated their potential to help address a range of social issues in high-, middle-, and low-income countries, with over 200 implemented across 35 countries, including 19 in developing countries. Some examples of impact bonds achieving public good include a program to improve learning outcomes of over 200,000 disadvantaged children across four states in India, an initiative aimed at improving livelihoods by supporting first-time entrepreneurs in Kenya and Uganda, and a program in Israel focused on the prevention of Type 2 diabetes. Another impact bond, the Impact Bond Innovation Fund, brought together a multitude of actors including a local government agency, several philanthropic entities, a university, and both a local and an international NGO to support an early childhood development program for marginalized children in the Western Cape in South Africa.
Several outcomes funds have also been established, and additional ones are being designed. One example is the Education Outcomes Fund (EOF), an effort to significantly improve learning and employment outcomes by tying funding to measurable results. EOF partners with governments, donors, implementing partners, and investors to achieve concrete targets for learning, skill development, and employment. With initial projects in Ghana and Sierra Leone, this approach is being scaled up with the aim of transforming the lives of 10 million children and youth around the world. EOF has recently joined the United Nations as a hosted partnership—showing the growing institutionalization of this model.
Conclusion: Where do we go from here?
While the past decade has seen significant growth in new ways for private, public, and third-sector actors to work together in partnership, thus far many of these initiatives have been on a small scale. What will it take to expand this model? Seeding and institutionalizing an outcomes-focused mindset at all levels of government, among international agencies, and within nonprofit service providers is the first step. This will require risk-taking, the willingness to rethink traditional models, and the agility to go big. It will also necessitate capacity building of all stakeholders to engage in this new way of working. Models like EOF and other outcomes funds are laying the path for large-scale partnerships that place beneficiaries at the forefront. Now more than ever, as the world is building back after the COVID-19 crisis, we will need strong partnerships that support public purpose in a cost-effective and impactful way. Impact bonds, outcomes funds, and other partnerships for public purpose (new PPPs) have the potential to support this recovery while strengthening social service delivery and, in essence, changing its DNA.
*Note: The authors borrowed the term “partnerships for public purpose” from K. Srinath Reddy in “The Convergence of Infectious Diseases and Noncommunicable Diseases: Proceedings of a Workshop (2019).”

Related Content

EMERGING MARKETS: Covid-19 Vaccination Strategies and Challenges

EMERGING MARKETS: Covid-19 Vaccination Strategies and Challenges | Speevr

Our Covid-19 vaccination table includes updated information on the immunization strategies selected EMs are pursuing and the challenges they face. Below are some of this week’s key developments. Please do not hesitate to contact us if you want to discuss any of the countries m…   Become a member to read the rest of this […]

MALAYSIA: Important weeks ahead for Prime Minister Muhyiddin Yassin

MALAYSIA: Important weeks ahead for Prime Minister Muhyiddin Yassin | Speevr

Earlier this week, Prime Minister Muhyiddin Yassin defended his government’s decision not to reimpose the strictest version of business and movement restrictions, called movement control orders (MCO) 1.0, despite the rising Covid-19 case numbers and some pressure from the healthc…   Become a member to read the rest of this article

Whom do consumers trust with their data? US survey evidence

Whom do consumers trust with their data? US survey evidence | Speevr

* In a recent survey, US households say they are more likely to trust traditional financial institutions than government agencies or fintechs to safeguard their personal data. They have far less trust in big techs. * This pattern differs across demographic groups: respondents from racial minorities have less trust in financial institutions, while younger respondents trust fintechs relatively more. Female, minority and younger respondents are more concerned about implications of data-sharing for their personal safety. * A quarter of respondents say Covid-19 made them less willing to share data. In this group, nearly half became less willing to share with big techs. Concerns centred on identity theft and abuse of data. * As the economy becomes increasingly digital, and new players expand further into financial services, strong data protection policies will become more important to shield consumers from these harms.