Food and nutrition security under global trade: a relation-driven agent-based global trade model

Impact of the Russian–Ukrainian Conflict on Global Food Crops

The Russian–Ukrainian conflict has been proven to cause significant losses of life and goods on both sides. This may have potentially impacted the agricultural sector. This study examines the impact of the conflict between Russia and Ukraine on the global food situation. We performed a descriptive analysis and literature review to answer this objective. Russia and Ukraine play essential roles in world food production and trade. However, the war has disrupted food production in Ukraine. Estimated Ukrainian wheat, soybean, and maize production in 2022–2023 fell precipitously. On the other hand, Russian production of these three food products shows positive growth during the same period. Furthermore, the global supply chain and food trade are hampered, causing an increase in the world’s food prices. From March to May 2022, the average global price of wheat, soybeans, and maize increased dramatically compared to during and before the COVID-19 pandemic. Finally, this poses a danger to global food security, particularly for low-income countries that depend heavily on food imports from both countries. Therefore, all countries must be prepared for the possibility that the Sustainable Development Goals cannot be achieved.

Agent-based modelling for Urban Analytics: State of the art and challenges

Agent-based modelling (ABM) is a facet of wider Multi-Agent Systems (MAS) research that explores the collective behaviour of individual ‘agents’, and the implications that their behaviour and interactions have for wider systemic behaviour. The method has been shown to hold considerable value in exploring and understanding human societies, but is still largely confined to use in academia. This is particularly evident in the field of Urban Analytics; one that is characterised by the use of new forms of data in combination with computational approaches to gain insight into urban processes. In Urban Analytics, ABM is gaining popularity as a valuable method for understanding the low-level interactions that ultimately drive cities, but as yet is rarely used by stakeholders (planners, governments, etc.) to address real policy problems. This paper presents the state-of-the-art in the application of ABM at the interface of MAS and Urban Analytics by a group of ABM researchers who are affiliated with the Urban Analytics programme of the Alan Turing Institute in London (UK). It addresses issues around modelling behaviour, the use of new forms of data, the calibration of models under high uncertainty, real-time modelling, the use of AI techniques, large-scale models, and the implications for modelling policy. The discussion also contextualises current research in wider debates around Data Science, Artificial Intelligence, and MAS more broadly.

Connected and extracted: Understanding how centrality in the global wheat supply chain affects global hunger using a network approach

While global food trade has allowed countries to buffer against domestic food production shortfalls and gain access to larger markets, engaging in trade has also opened economies up to shocks and increased extraction of food resources. With this research, we analyze how the global grain network influences country-level nourishment, while controlling for per capita land and food production. First, we model the trade network structure of the global wheat supply chain to measure the centrality or positionality of countries. We use spatial regression analysis to assess the impact of trade networks, volume, purchasing power, production capacity and geography on undernourishment. We find that the six countries most central to the global grain trade by betweenness and eigenvector centralities account for more than half of all wheat exports globally by volume. The centrality of these countries as opposed to volume of wheat produced or traded, determines their influence in the wheat supply chain network. The parametric component of our analysis confirms that trade, and centrality have significant implications for national levels of nourishment. Our findings suggest that for countries with low purchasing power, increasing centrality allows improvements in nourishment levels but for countries with very high purchasing power, increasing centrality can increase hunger outcomes. To counteract perturbations and shortfalls such as those being experienced currently in the globalized food system, local and regional governments may consider refocusing on regional and local based food systems.

Effects of Corruption Control on the Number of Undernourished People in Developing Countries

Developing countries will be home to 85% of the world's population by 2030. Hence, it is important to ensure food security for them. This effort is not easy, as the number of undernourished people (NUP) in the world has increased. We investigated the impact of food and non-production factors on the NUP in developing countries. This study employed secondary data from 57 developing countries between 2002 and 2018. These countries come from three regions, namely Africa, Asia, and Latin America and the Caribbean. One-step and two-step generalized method of moments (sys-GMM) models were used to analyze the data. The findings showed that the food production index, cereal import dependency ratio, economic globalization index, and human capital index had different effects on the NUP in each region. The excellent news is that corruption control can help developing countries minimize their NUP. Based on the findings, we propose efforts to improve physical and economical food access and control corruption, and developing country governments and the international community must demonstrate a strong commitment to reducing the prevalence of undernourishment.

COVID-19 Induced Economic Slowdown and Mental Health Issues

The COVID-19 pandemic has pressed a pause button on global economic development, and induced significant mental health problems. In order to demonstrate the progressed relationship between the pandemic, economic slowdown, and mental health burden, we overviewed the global-level gross domestic product changes and mental problems variation since the outbreak of COVID-19, and reviewed comprehensively the specific sectors influenced by the pandemic, including international trade, worldwide travel, education system, healthcare system, and individual employment. We hope to provide timely evidence to help with the promotion of policymakers’ effective strategies in mitigating economic losses induced by the pandemic; we suggest different governments or policy makers in different countries to share information and experience in dealing with COVID-19-induced economic slowdown and promote COVID-19 vaccine popularization plan to protect every individual worldwide against the coronavirus essentially; and we appeal international information share and collaboration to minimize stigmatization related to adverse mental consequences of COVID-19 and to increase mental health wellbeings of people all over the world.

Use of the DELTA Model to Understand the Food System and Global Nutrition

BACKGROUND

Increasing attention is being directed at the environmental, social, and economic sustainability of the global food system. However, a key aspect of a sustainable food system should be its ability to deliver nutrition to the global population. Quantifying nutrient adequacy with current tools is challenging.

OBJECTIVE

To produce a computational model illustrating the nutrient adequacy of current and proposed global food systems.

METHODS

The DELTA Model was constructed using global food commodity balance sheet data, alongside demographic and nutrient requirement data from UN and European Food Safety Authority sources. It also includes nutrient bioavailability considerations for protein, the indispensable amino acids, iron, and zinc, sourced from scientific literature.

RESULTS

The DELTA Model calculates global per capita nutrient availability under conditions of equal distribution and identifies areas of nutrient deficiency for various food system scenarios. Modeling the 2018 global food system showed that it supplied insufficient calcium (64% of demographically weighted target intake) and vitamin E (69%), despite supplying sufficient macronutrients. Several future scenarios were modeled, including variations in waste; scaling up current food production for the 2030 global population; plant-based food production systems; and removing sugar crops from the global food system. Each of these scenarios fell short of meeting requirements for multiple nutrients. These results emphasize the need for a balanced approach in the design of future food systems.

CONCLUSIONS

Nutrient adequacy must be at the forefront of the sustainable food system debate. The DELTA Model was designed for both experts and nonexperts to inform this debate as to what may be possible, practical, and optimal for our food system. The model results strongly suggest that both plant and animal foods are necessary to achieve global nutrition. The model is freely available for public use so that anyone can explore current and simulated global food systems.

Has the COVID-19 Pandemic Affected Maritime Connectivity? An Estimation for China and the Polar Silk Road Countries

In light of about 80% of international freight traffic carried by sea, maritime supply chains’ stability is pivotal to global connectivity. For over a year now, the transboundary mobility of vessels and cargoes has been restricted by diverse forms of the COVID-19 containment measures applied by national governments, while the lockdowns of people, businesses, and economic activities have significantly affected the growth prospects of various maritime connectivity initiatives. This study investigates how the pandemic-related public health, trade, and market factors have shifted the connectivity patterns in the Polar Silk Road (PSR) transport corridor between China, South Korea, Japan, Russia, and four economies of Northern Europe. The causality links between the Shipping Connectivity Index (SCI) and the number of COVID-19 cases and deaths, trade volumes with China and the rest of the world, and price indexes of minerals, fuels, food, and agricultural products are revealed separately for eight countries and thirty-five ports. The study algorithm is built on the consecutive application of the Augmented Dickey-Fuller (ADF) and the Phillips-Perron (PP) stationarity tests, the Autoregressive Distributed Lag (ARDL) method, the Fully-Modified Ordinary Least Squares (FMOLS) and the Dynamic Ordinary Least Squares (DOLS) robustness checks, and the Toda-Yamamoto causality test. Tight trade-connectivity links are recorded in all locations along the China-PSR transport corridor in 2015–2019, but in 2020, the relationships weakened. Bidirectional influences between the number of COVID-19 cases and connectivity parameters demonstrate the maritime sector’s sensitivity to safety regulations and bring into focus the role of cargo shipping in the transboundary spread of the virus. The authors’ four-stage approach contributes to the establishment of a methodology framework that may equip stakeholders with insights about potential risks to maritime connectivity in the China-PSR maritime trade in the course of the pandemic.