By Ahmed Mushfiq Mobarak, Professor of Economics at Yale University, and Faculty director of the Yale Research Initiative on Innovation and Scale (Y-RISE), and Jaya Wen, Postdoctoral Fellow, Northwestern University

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This blog is part of a series on tackling COVID-19 in developing countries. Visit the OECD dedicated page to access the OECD’s data, analysis and recommendations on the health, economic, financial and societal impacts of COVID-19 worldwide.

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The new coronavirus has already exacted a profound toll all over the world. A notable feature of COVID-19’s course is that early outbreaks occurred primarily in middle- and high-income countries, so evidence and policy guidance have been tailored for these contexts. Policymakers will need to reevaluate these approaches as the disease progresses to poor countries. Even if the ultimate objective remains protecting the quality and extent of human life everywhere, effective intermediate goals and policy approaches are context-dependent, modulated by factors like health care capacity, poverty levels, government capacity, economic informality, and the prevalence of high-density, low-infrastructure living conditions.

For example, the plea to “flatten the curve” is motivated by the desire to not overwhelm health care systems – in particular, intensive care capacity.  While this goal is laudable in wealthy countries like the United States, where there is roughly one hospital bed per 350 people, it is likely infeasible in countries like Bangladesh, which has just one hospital bed for every 1,600 people and one ICU bed for every 230,000 people. While delaying the speed of the outbreak may offer other benefits, for example, by delaying infections until treatment strategies improve, the motivation of keeping cases below hospital capacity is likely irrelevant. Flattening the curve is unlikely to reduce pressure on overburdened health systems or offer enough time to build medical capacity. Under such circumstances, it may be better to forgo a full economic shutdown in favour of disease prevention strategies, like enforcing spacing in public areas and encouraging hygiene practices.

The costs and benefits of public health measures also differ in developing countries due to an interaction of poverty and lower government capacity. For example, widespread social distancing measures may be unworkable in places like Bangladesh. For many day-wage labourers, remote work is not possible and no work could mean starvation. If the government orders social distancing but does not provide sufficient economic support to compensate, these workers will likely choose to violate distancing guidelines to feed their families. However, many developing countries will find it economically and logistically difficult to (1) provide large social protection schemes that encourage people to stay at home, and (2) comprehensively enforce lockdowns. To complicate matters further, people in developing countries may live in crowded conditions up to 30 times as dense as New York City, often without regular access to running water.

Another key characteristic of developing countries is the extent of the informal economy. In Bangladesh, informal firms employ over 40% of the workforce. Over 60% of informally employed workers are concentrated in services and retail, which are high-contact sectors hit hard by social distancing policies. At the same time, the unregistered status of informal firms means the government lacks a channel through which to disburse cash transfers, wage subsidies, or emergency loans, meaning that the hardest-hit firms may also be the hardest to help.

Developing countries face a uniquely painful tradeoff between two risks: mortality and morbidity due to COVID-19 and mortality and morbidity brought on by the potential economic and health consequences of mitigation policies. A coordinated, international response among epidemiologists, medical practitioners, policymakers, and economists is essential to combat this unprecedented crisis. In particular, the economics community can contribute in several key ways to the short-term response. These include: (1) collecting data on COVID-19 prevalence and attitudes, as well as on economic conditions, (2) developing models that combine epidemiological and economic insights, (3) guiding implementation with pre-existing data and evidence, and (4) deploying, evaluating, and adapting disease-prevention interventions.

First, measurement is of direct value in alleviating some uncertainty facing policymakers. Economists can implement phone surveys on statistically representative samples to understand the prevalence and location of disease symptoms, adherence to public health directives, attitudes and beliefs about the disease, economic situations, and other key measures. Our team at the Yale Research Initiative on Innovation and Scale (Y-RISE) is leveraging existing research infrastructure in Bangladesh to collect this information from key populations, including urban labourers, seasonal migrant workers, Rohingya refugees and host communities, beneficiaries of social transfer programmes, and international migrants. We also plan to analyse observational data descriptively to shed light on where disease-vulnerable demographics live, which industries are most important to peoples’ livelihood, and more.

Secondly, such data can be used to add economic and behavioural elements to epidemiological models designed to track and predict the spread of the virus. The effectiveness of policy responses in in low- and middle-income countries is dependent on the details of behavioural responses to policy, including variation guideline adherence, variation in the authorities’ enforcement capacity across rural and urban areas, mobility of workers in the informal sector, the economic pressures imposed on society through distancing, and people’s religious sensibilities. Moreover, combined economic-epidemiological models can provide a quantitative framework for balancing the direct health benefits of public health interventions with their economic side effects, highlighting what tradeoffs are feasible. Our team is spearheading multiple efforts to gather insights from past economics research and create analytical frameworks that will allow policymakers to better assess the direct and unintended consequences of policies like social distancing.

A third key activity is to inform policy implementation. Past research in economics has documented the types of social programmes most likely to help households most in times of crisis, what segments of society and economy are likely to be hit hardest, and what policies might best protect citizens’ livelihoods. Tailored literature reviews can help decision-makers choose among policies and determine how best to implement them. For example, when implementing a transfer programme, should transfers be given to a particular member of the household? Should resources be disbursed digitally, or in-kind? After identifying firms that need cash grants, should they be encouraged to formalize? Experimentation is not always feasible, so previous evidence can be of great value.

Finally, another comparative advantage of economists is to dynamically evaluate the effectiveness of mitigation strategies using randomized-controlled trials. For example, our team is testing whether public health text messages that encourage social distancing are more effective when trusted religious and community leaders, as opposed to automated systems, send them.  As soon as an answer becomes clear, we plan to inform the government and encourage them to adopt the better strategy at full scale.

Although both developed and developing countries have the same goal of containing the devastation of COVID-19, they face vastly different contexts and trade-offs. In the coming months, our network of researchers and practitioners will continue to assist developing countries in designing, implementing, evaluating, and adjusting locally suitable policies, so that they can weather this storm and set the stage for recovery.