Quantifying the economic response to COVID‐19 mitigations and death rates via forecasting purchasing managers' indices using generalised network autoregressive models with exogenous variables

Knowledge of the current state of economies, how they respond to COVID-19 mitigations and indicators, and what the future might hold for them is important. We use recently developed generalised network autoregressive (GNAR) models, using trade-determined networks, to model and forecast the Purchasing Managers' Indices for a number of countries. We use networks that link countries where the links themselves, or their weights, are determined by the degree of export trade between the countries. We extend these models to include node-specific time series exogenous variables (GNARX models), using this to incorporate COVID-19 mitigation stringency indices and COVID-19 death rates into our analysis. The highly parsimonious GNAR models considerably outperform vector autoregressive models in terms of mean-squared forecasting error and our GNARX models themselves outperform GNAR ones. Further mixed frequency modelling predicts the extent to which that the UK economy will be affected by harsher, weaker or no interventions.

Xiaoping Shi, Yue Zhang and Yucheng Dong's contribution to the ‘First Discussion Meeting on Statistical Aspects of the Covid‐19 Pandemic’

Knowledge of the current state of economies, how theyrespond to COVID-19 mitigations and indicators, andwhat the future might hold for them is important.We use recently developed generalised network autoregres-sive (GNAR) models, using trade-determined networks, tomodel and forecast the Purchasing Managers' Indices for anumber of countries. We use networks that link countrieswhere the links themselves, or their weights, are deter-mined by the degree of export trade between the coun-tries. We extend these models to include node-specific timeseries exogenous variables (GNARX models), using this toincorporate COVID-19 mitigation stringency indices andCOVID-19 death rates into our analysis. The highly par-simonious GNAR models considerably outperform vectorautoregressive models in terms of mean-squared forecast-ing error and our GNARX models themselves outperform GNAR ones. Further mixed frequency modelling predictsthe extent to which that the UK economy will be affectedby harsher, weaker or no interventions.

The interplay among COVID-19 economic recovery, behavioural changes, and the European Green Deal: An energy-economic modelling perspective.

In the EU, COVID-19 and associated policy responses led to economy-wide disruptions and shifts in services demand, with considerable energy-system implications. The European Commission's response paved the way towards enhancing climate ambition through the European Green Deal. Understanding the interactions among environmental, social, and economic dimensions in climate action post-COVID thus emerged as a key challenge. This study disaggregates the implications of climate ambition, speed of economic recovery from COVID-19, and behavioural changes due to pandemic-related measures and/or environmental concerns for EU transition dynamics, over the next decade. It soft-links two large-scale energy-economy models, EU-TIMES and NEMESIS, to shed light on opportunities and challenges related to delivering on the EU's 2030 climate targets. Results indicate that half the effort required to reach the updated 55% emissions reduction target should come from electricity decarbonisation, followed by transport. Alongside a post-COVID return to normal, the European Green Deal may lead to increased carbon prices and fossil-fuel rebounds, but these risks may be mitigated by certain behavioural changes, gains from which in transport energy use would outweigh associated consumption increases in the residential sector. Finally, the EU recovery mechanism could deliver about half the required investments needed to deliver on the 2030 ambition.

Five years after Treat All implementation: Botswana's HIV response and future directions in the era of COVID-19.

BACKGROUND: As the relentless coronavirus disease-2019 (COVID-19) pandemic continues to spread across Africa, Botswana could face challenges maintaining the pathway towards control of its HIV epidemic. OBJECTIVE: Utilising the Spectrum GOALS module (GOALS-2021), the 5-year outcomes from the implementation of the Treat All strategy were analysed and compared with the original 2016 Investment Case (2016-IC) projections. Future impact of adopting the new Joint United Nations Programme on HIV/AIDS (UNAIDS) Global AIDS Strategy (2021-2026) targets and macroeconomic analysis estimating how the financial constraints from the COVID-19 pandemic could impact the available resources for Botswana's National HIV Response through 2030 were also considered. METHOD: Programmatic costs, population demographics, prevention and treatment outputs were determined. Previous 2016-IC data were uploaded for comparison, and inputs for the GOALS, AIM, DemProj, Resource Needs and Family Planning modules were derived from published reports, strategic plans, programmatic data and expert opinion. The economic projections were recalibrated with consideration of the impact of the COVID-19 pandemic. RESULTS: Decreases in HIV infections, incidence and mortality rates were achieved. Increases in laboratory costs were offset by estimated decreases in the population of people living with HIV (PLWH). Moving forward, young women and others at high risk must be targeted in HIV prevention efforts, as Botswana transitions from a generalised to a more concentrated epidemic. CONCLUSION: The Treat All strategy contributed positively to decreases in new HIV infections, mortality and costs. If significant improvements in differentiated service delivery, increases in human resources and HIV prevention can be realised, Botswana could become one of the first countries with a previously high-burdened generalised HIV epidemic to gain epidemic control, despite the demands of the COVID-19 pandemic.

Energy-socio-economic-environmental modelling for the EU energy and post-COVID-19 transitions.

Relevant energy questions have arisen because of the COVID-19 pandemic. The pandemic shock leads to emissions' reductions consistent with the rates of decrease required to achieve the Paris Agreement goals. Those unforeseen drastic reductions in emissions are temporary as long as they do not involve structural changes. However, the COVID-19 consequences and the subsequent policy response will affect the economy for decades. Focusing on the EU, this discussion article argues how recovery plans are an opportunity to deepen the way towards a low-carbon economy, improving at the same time employment, health, and equity and the role of modelling tools. Long-term alignment with the low-carbon path and the development of a resilient transition towards renewable sources should guide instruments and policies, conditioning aid to energy-intensive sectors such as transport, tourism, and the automotive industry. However, the potential dangers of short-termism and carbon leakage persist. The current energy-socio-economic-environmental modelling tools are precious to widen the scope and deal with these complex problems. The scientific community has to assess disparate, non-equilibrium, and non-ordinary scenarios, such as sectors and countries lockdowns, drastic changes in consumption patterns, significant investments in renewable energies, and disruptive technologies and incorporate uncertainty analysis. All these instruments will evaluate the cost-effectiveness of decarbonization options and potential consequences on employment, income distribution, and vulnerability.

Effects of social-distancing on infectious disease dynamics: an evolutionary game theory and economic perspective.

We propose two models inspired by the COVID-19 pandemic: a coupled disease-human behaviour (or disease-game theoretic), and a coupled disease-human behaviour-economic model, both of which account for the impact of social-distancing on disease control and economic growth. The models exhibit rich dynamical behaviour including multistable equilibria, a backward bifurcation, and sustained bounded periodic oscillations. Analyses of the first model suggests that the disease can be eliminated if everybody practices full social-distancing, but the most likely outcome is some level of disease coupled with some level of social-distancing. The same outcome is observed with the second model when the economy is weaker than the social norms to follow health directives. However, if the economy is stronger, it can support some level of social-distancing that can lead to disease elimination.

Modelling the economic impact of COVID19 under different policy choices: Mitigation versus suppression when time is a scarce resource.

Keogh-Brown et al.(2020) illustrate the application of economic modelling to inform and guide policy making during the COVID-19 pandemic in the UK. The methodology is based on linking a general equilibrium economic model to a simple epidemiological model of the infection. In this commentary a number of issues are discussed relating to the construction and application of the model, and the implications of the findings for government policies.