How many people is the COVID-19 pandemic pushing into poverty? A long-term forecast to 2050 with alternative scenarios.

The COVID-19 pandemic has changed the course of human development. In this manuscript we analyze the long-term effect of COVID-19 on poverty at the country-level across various income thresholds to 2050. We do this by introducing eight quantitative scenarios that model the future of Sustainable Development Goal 1 (SDG1) achievement using alternative assumptions about COVID-19 effects on both economic growth and inequality in the International Futures model. Relative to a scenario without the pandemic (the No COVID scenario), the COVID Base scenario increases global extreme poverty by 73.9 million in 2020 (the range across all scenarios: 43.5 to 155.0 million), 63.6 million in 2030 (range: 9.8 to 167.2 million) and 57.1 million in 2050 (range: 3.1 to 163.0 million). The COVID Base results in seven more countries not meeting the SDG1 target by 2030 that would have achieved the target in a No COVID scenario. The most pessimistic scenario results in 17 more countries not achieving SDG1 compared with a No COVID scenario. The greatest pandemic driven increases in poverty occur in South Asia and sub-Saharan Africa.

Enhancing integrated analysis of national and global goal pursuit by endogenizing economic productivity.

Analysis with integrated assessment models (IAMs) and multisector dynamics models (MSDs) of global and national challenges and opportunities, including pursuit of Sustainable Development Goals (SDGs), requires projections of economic growth. In turn, the pursuit of multiple interacting goals affects economic productivity and growth, generating complex feedback loops among actions and objectives. Yet, most analysis uses either exogenous projections of productivity and growth or specifications endogenously enriched with a very small set of drivers. Extending endogenous treatment of productivity to represent two-way interactions with a significant set of goal-related variables can considerably enhance analysis. Among such variables incorporated in this project are aspects of human development (e.g., education, health, poverty reduction), socio-political change (e.g., governance capacity and quality), and infrastructure (e.g. water and sanitation and modern energy access), all in conditional interaction with underlying technological advance and economic convergence among countries. Using extensive datasets across countries and time, this project broadly endogenizes total factor productivity (TFP) within a large-scale, multi-issue IAM, the International Futures (IFs) model system. We demonstrate the utility of the resultant open system via comparison of new TFP projections with those produced for Shared Socioeconomic Pathways (SSP) scenarios, via integrated analysis of economic growth potential, and via multi-scenario analysis of progress toward the SDGs. We find that the integrated system can reproduce existing SSP projections, help anticipate differential economic progress across countries, and facilitate extended, integrated analysis of trade-offs and synergies in pursuit of the SDGs.

Projections of global health outcomes from 2005 to 2060 using the International Futures integrated forecasting model.

OBJECTIVE: To develop an integrated health forecasting model as part of the International Futures (IFs) modelling system. METHODS: The IFs model begins with the historical relationships between economic and social development and cause-specific mortality used by the Global Burden of Disease project but builds forecasts from endogenous projections of these drivers by incorporating forward linkages from health outcomes back to inputs like population and economic growth. The hybrid IFs system adds alternative structural formulations for causes not well served by regression models and accounts for changes in proximate health risk factors. Forecasts are made to 2100 but findings are reported to 2060. FINDINGS: The base model projects that deaths from communicable diseases (CDs) will decline by 50%, whereas deaths from both non-communicable diseases (NCDs) and injuries will more than double. Considerable cross-national convergence in life expectancy will occur. Climate-induced fluctuations in agricultural yield will cause little excess childhood mortality from CDs, although other climate-health pathways were not explored. An optimistic scenario will produce 39 million fewer deaths in 2060 than a pessimistic one. Our forward linkage model suggests that an optimistic scenario would result in a 20% per cent increase in gross domestic product (GDP) per capita, despite one billion additional people. Southern Asia would experience the greatest relative mortality reduction and the largest resulting benefit in per capita GDP. CONCLUSION: Long-term, integrated health forecasting helps us understand the links between health and other markers of human progress and offers powerful insight into key points of leverage for future improvements.