Responses to the COVID-19 pandemic have impeded progress towards the Sustainable Development Goals

The United Nations declared the 2020s the Decade of Action toward the SDGs, encompassing 17 goals and 169 targets across environmental, economic, and social dimensions. Since 2020, the COVID-19 pandemic and associated policy responses have challenged this agenda. Evidence suggests many SDG targets are threatened by pandemic responses that can generate environmental benefits (for example, from reduced mobility and industrial activity) but also substantial social isolation and economic losses. Conversely, fiscal stimuli intended to accelerate recovery may increase emissions. There is an urgent need for a comprehensive, integrated, quantitative assessment of how distinct public health and economic responses to COVID-19 have affected SDG progress globally and nationally, especially in countries already burdened by poverty and conflict. This study aims to fill that gap by quantifying heterogeneous impacts of multiple COVID-19 response measures across multiple SDG targets to inform future pandemic policy that balances public health with sustainable development.

Prior studies assessed COVID-19’s effects on SDG progress via public health and economic pathways and evaluated individual response measures. Research has shown that movement restrictions reduced consumption, income, and employment but also curtailed emissions and air pollution. Trade restrictions threatened food security in developing countries, and fiscal stimuli have mixed implications for climate and sustainability. Some multi-target assessments exist but often focus narrowly on specific contexts or targets, missing interactions and trade-offs that can exacerbate inequalities across countries. This work extends the literature by simultaneously quantifying the differentiated effects of movement restrictions, fiscal stimuli, and trade restrictions on multiple SDG targets across countries, capturing cascading supply-chain effects.

The authors developed a global adaptive multi-regional input–output (AMRIO) model to quantify the impacts of COVID-19 response measures on global supply chains and cascading effects on selected SDG targets. AMRIO captures sector-level supply–demand interactions under short- to medium-term shocks and allows constraints on labor, capital, and transport to simulate movement restrictions, as well as countercyclical fiscal stimuli and trade restrictions. The study considered three response measures: movement restrictions, fiscal stimuli, and trade restrictions. Eight SDG targets (spanning socio-economic and environmental dimensions) were selected based on definitional clarity and data availability, and linked to measurable indicators. Data inputs included the GTAP global input–output table (version 10.3), environmental accounts (greenhouse gas emissions and energy consumption from IEA/GTAP; water and agricultural use from FAO; materials use from UN sources), COVID-19 policy data from the Oxford COVID-19 Government Response Tracker, Google mobility data, and fiscal stimulus information from the IMF and other repositories. National GDP and population projections (2020–2030) were taken from the SSPs database. The baseline followed recent historical trajectories under SSP2. Pandemic response intensities were parameterized using observed policy data up to October 15, 2022. SDG indicators were standardized to a 0–100 scale; target scores were averaged equally across the eight targets and equally across countries to produce national and global SDG scores. Scenario analysis covered 2020–2030 with three post-pandemic narratives: Back to Normal (pandemic ends, restrictions lifted), New Normal (persistent lower-level restrictions), and Pandemic Returns (new waves with re-tightened restrictions). Combinations of response intensities for movement restrictions, fiscal stimuli, and trade restrictions created 27 cases. Uncertainty and sensitivity analyses explored alternative socioeconomic pathways (e.g., SSP1 and SSP3) and policy ranges to test robustness. The model does not aim to precisely forecast SDG achievements but to compare counterfactual ‘what-if’ outcomes of response strategies.

- Global impact (2020–2023): COVID-19 responses reduced overall SDG progress by 8.2% (global SDG score fell from 55.5 to 51.1 in 2020), followed by a V-shaped recovery to ~55.5 by 2023 as restrictions eased. - Dimension-specific effects: Socio-economic sustainability declined by 18.1%, while environmental sustainability improved by 5.1% relative to business-as-usual (BAU). - Inequality across countries: Developing countries experienced larger overall declines (−9.7%) than developed countries (−7.1%). Socio-economic setbacks were especially pronounced in developing countries (notably SDG2.1, SDG8.1, and SDG9.3), linked to cascading global supply-chain effects and reliance on labor-intensive agriculture. - Environmental outcomes: Environmental targets improved in 2020 due to reduced industrial activity and transport; countries reliant on polluting, resource-intensive industries (e.g., Indonesia) saw larger gains. - Role of specific responses: • Movement restrictions: Largest contributor to socio-economic declines; simultaneously improved environmental targets. On average, environmental scores rose by about 3.1% under movement restrictions, with increases reported for SDG8.4 (+6.0%), SDG7.2 (+3.2%), SDG13.2 (+1.8%), and SDG6.4 (+1.8%). Stronger restrictions deepened socio-economic losses but enhanced environmental gains. • Fiscal stimuli: Partly offset socio-economic losses (e.g., SDG2.1 +3.0%, SDG8.1 +6.7%, SDG9.2 +0.1%), but slightly worsened environmental targets (SDG6.4, SDG7.2, SDG8.4, SDG13.2 each decreasing by ~0.2%). Effects were insufficient to fully counteract movement-restriction impacts and were often domestically focused, yielding little improvement in exports (SDG17.11). • Trade restrictions: Lowest overall impact. Temporary, small-scale measures primarily affected agriculture. However, export bans impeded trade globalization, contributing to a global SDG17.11 decrease of 9.3%. - Post-pandemic scenarios (2024–2030): • Back to Normal: Highest global SDG score (~55.7). Even without renewed pandemics, SDG scores decline slightly (~1.0%) from 2024–2030 under no additional responses, implying traditional development trajectories are insufficient to meet the SDGs. • New Normal: With continued moderate restrictions, the global SDG score lags Back to Normal (~54.5) and remains roughly flat (~55.4) from 2024–2030; additional fiscal or trade measures cannot fully offset movement restriction impacts. • Pandemic Returns: V-shaped SDG trend with a low point around 2027; scores recover as restrictions ease (reported increase from ~55.5 to ~55.6 by 2030). Fiscal stimuli modestly improve selected socio-economic targets (e.g., SDG2.1 +0.2%, SDG1.1 +1.7%) while reducing others; trade restrictions negatively affect SDG2.1 and SDG11.1 and reduce the global SDG score (~−0.4%). - Inequality trends: Gaps between developed and developing countries widen in most cases, escalating with stricter or longer movement restrictions. Under Pandemic Returns, relative declines in 2024 were ~0.7% for developed countries versus ~1.0% for developing countries.

Findings indicate that pandemic responses created strong trade-offs: movement restrictions benefited environmental targets but sharply curtailed socio-economic progress, while fiscal stimuli aided socio-economic recovery at environmental cost. Trade restrictions had comparatively minor but negative implications for trade globalization (SDG17.11). These dynamics collectively impeded progress toward the 2030 Agenda and exacerbated inequalities, especially affecting developing countries with limited fiscal capacity, incomplete industrial systems, and higher exposure to supply-chain shocks. The analysis clarifies how distinct response measures differentially shape SDG trajectories, offering evidence to design pandemic policies that minimize cross-target trade-offs and cross-country inequities. The widening gap underscores the need for tailored support to developing countries, considering both direct and cascading effects across global supply chains.

The study contributes a quantitative, multi-dimensional assessment of how COVID-19 response measures affected SDG progress using a global AMRIO model. It shows substantial overall setbacks, pronounced socio-economic losses alongside modest environmental gains, and rising inequality—with movement restrictions driving socio-economic declines and fiscal stimuli offering partial relief but imposing environmental trade-offs. Policy implications include designing sustainable pandemic responses that: (1) carefully calibrate movement restrictions (prioritize targeted, adaptive measures, increase vaccination, and protect vulnerable groups) to limit socio-economic harm; (2) align fiscal stimuli with green recovery—boosting low-carbon and cleaner industries to convert trade-offs into synergies, particularly in developed economies; (3) in developing countries, prioritize fundamental socio-economic needs (e.g., food security and livelihoods) given limited fiscal space; (4) strengthen international cooperation for health, finance, and technology transfer consistent with the SDG ‘leave no one behind’ principle; and (5) avoid broad trade restrictions, especially by major agricultural exporters, due to adverse effects on SDG1 and SDG17. Future work should expand SDG coverage, incorporate adaptive productivity and technological change, and better resolve temporal, regional, and sectoral policy details.

- Scope: Only eight SDG targets were analyzed due to data and methodological constraints; key areas such as unemployment and health security were not fully covered. - Model assumptions: The approach assumes limited adaptation in economic productivity, resource efficiency, and technology, potentially biasing cross-country comparisons. - Policy representation: Simplified policy effects and limited granularity (temporal, regional, sectoral) due to constraints of GTAP-MRIO data and available policy datasets. Despite these limitations, the authors argue the results are robust for assessing relative impacts of response measures rather than precise forecasts.