D5.3 Resilience assessment of current farming systems across the European Union

For improving sustainability and resilience of EU farming system, the current state needs to be assessed, before being able to move on to future scenarios. Assessing sustainability and resilience of farming systems is a multi-faceted research challenge in terms of the scientific domains and scales of integration (farm, household, farming system level) that need to be covered. Hence, in SURE-Farm, multiple approaches are used to evaluate current sustainability and resilience and its underlying structures and drivers. To maintain consistency across the different approaches, all approaches are connected to a resilience framework which was developed for the unique purposes of SURE-Farm. The resilience framework follows five steps: 1) the farming system (resilience of what?), 2) challenges (resilience to what?), 3) functions (resilience for what purpose?), 4) resilience capacities, 5) resilience attributes (what enhances resilience?). The framework was operationalized in 11 case studies across the EU. Applied approaches differ in disciplinary orientation and the farming system process they focus on. Three approaches focus on risk management: 1) a farm survey with a main focus on risk management and risk management strategies, 2) interviews on farmers’ learning capacity and networks of influence, and 3) Focus Groups on risk management. Two approaches address farm demographics: 4) interviews on farm demographics, and 5) AgriPoliS Focus Group workshops on structural change of farming systems from a (farm) demographics perspective. One approach applied so far addresses governance: 6) the Resilience Assessment Tool that evaluates how policies and legislation support resilience of farming systems. Two methods address agricultural production and delivery of public and private goods: 7) the Framework of Participatory Impact Assessment for sustainable and resilient farming systems (FoPIA-SURE-Farm), aiming to integrate multiple perspectives at farming system level, and 8) the Ecosystem Services assessment that evaluates the delivery of public and private goods. In a few case studies, additional methods were applied. Specifically, in the Italian case study, additional statistical approaches were used to increase the support for risk management options (Appendix A and Appendix B). Results of the different methods were compared and synthesized per step of the resilience framework. Synthesized results were used to determine the position of the farming system in the adaptive cycle, i.e. in the exploitation, conservation, release, or reorganization phase. Dependent on the current phase of the farming system, strategies for improving sustainability and resilience were developed. Results were synthesized around the three aspects characterizing the SURE-Farm framework, i.e. (i) it studies resilience at the farming system level, (ii) considers three resilience capacities, and (iii) assesses resilience in the context of the (changing) functions of the system. (i) Many actors are part of the farming system. However, resilience-enhancing strategies are mostly defined at the farm level. In each farming system multiple actors are considered to be part of the system, such as consultants, neighbors, local selling networks and nature organizations. The number of different farming system actors beyond the focal farmers varies between 4 (in French beef and Italian hazelnut systems) and 14 (large-scale arable systems in the UK). These large numbers of actors illustrate the relevance of looking at farming system level rather than at farm level. It also suggests that discussions about resilience and future strategies need to embrace all of these actors. (ii) At system level there is a low perceived capacity to transform. Yet, most systems appear to be at the start of a period in which (incremental) transformation is required. At system level, the capacity to transform is perceived to be relatively low, except in the Romanian mixed farming system. The latter may reflect a combination of ample room to grow and a relatively stable environment (especially when compared to the past 30 to 50 years). The relatively low capacity to transform in the majority of systems is not in line with the suggestion that most systems are at the start of (incremental) transformation, or, at least, reached a situation in which they can no longer grow. Further growth is only deemed possible in the Belgium dairy, Italian hazelnut, Polish fruit and Romanian mixed farming systems. (iii) System functions score well with regard to the delivery of high-quality and safe food but face problems with quality of rural life and protecting biodiversity. Resilience capacities can only be understood in the context of the functions to be delivered by a farming system. We find that across all systems required functions are a mix of private and public goods. With regard to the capacity to deliver private goods, all systems perform well with respect to high-quality and safe food. Viability of farm income is regarded moderate or low in the livestock systems in Belgium (dairy), France (beef) and Sweden (broilers), and the fruit farming system in Poland. Across all functions, attention is especially needed for the delivery of public goods. More specifically the quality of rural life and infrastructure are frequently classified as being important, but currently performing bad. Despite the concerns about the delivery of public goods, many future strategies still focus on improving the delivery of private goods. Suggestions in the area of public goods include among others the implementation of conservation farming in the UK arable system, improved water management in the Italian hazelnut system, and introduction of technologies which reduce the use of herbicides in Polish fruit systems. It is questionable whether these are sufficient to address the need to improve the maintenance of natural resources, biodiversity and attractiveness of rural areas. With regard to the changing of functions over time, we did not find evidence for this in our farming systems

Impact of COVID-19 on farming systems in Europe through the lens of resilience thinking

CONTEXT Resilience is the ability to deal with shocks and stresses, including the unknown and previously unimaginable, such as the Covid-19 crisis. OBJECTIVE This paper assesses (i) how different farming systems were exposed to the crisis, (ii) which resilience capacities were revealed and (iii) how resilience was enabled or constrained by the farming systems’ social and institutional environment. METHODS The 11 farming systems included have been analysed since 2017. This allows a comparison of pre-Covid-19 findings and the Covid-19 crisis. Pre-Covid findings are from the SURE-Farm systematic sustainability and resilience assessment. For Covid-19 a special data collection was carried out during the early stage of lockdowns. RESULTS AND CONCLUSIONS Our case studies found limited impact of Covid-19 on the production and delivery of food and other agricultural products. This was due to either little exposure or the agile activation of robustness capacities of the farming systems in combination with an enabling institutional environment. Revealed capacities were mainly based on already existing connectedness among farmers and more broadly in value chains. Across cases, the experience of the crisis triggered reflexivity about the operation of the farming systems. Recurring topics were the need for shorter chains, more fairness towards farmers, and less dependence on migrant workers. However, actors in the farming systems and the enabling environment generally focused on the immediate issues and gave little real consideration to long-term implications and challenges. Hence, adaptive or transformative capacities were much less on display than coping capacities. The comparison with pre-Covid findings mostly showed similarities. If challenges, such as shortage of labour, already played before the crisis, they persisted during the crisis. Also, the eminent role of resilience attributes was confirmed. In cases with high connectedness and diversity we found that these system characteristics importantly contributed to dealing with the crisis. Also the focus on coping capacities was already visible before the crisis. We are not sure yet whether the focus on short-term robustness just reflects the higher visibility and urgency of shocks compared to slow processes that undermine or threaten important system functions, or whether they betray an imbalance in resilience capacities at the expense of adaptability and transformability. SIGNIFICANCE Our analysis indicates that if transformations are required, e.g. to respond to concerns about transnational value chains and future pandemics from zoonosis, the transformative capacity of many farming systems needs to be actively enhanced through an enabling environment

Global variation in postoperative mortality and complications after cancer surgery: a multicentre, prospective cohort study in 82 countries

© 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 licenseBackground: 80% of individuals with cancer will require a surgical procedure, yet little comparative data exist on early outcomes in low-income and middle-income countries (LMICs). We compared postoperative outcomes in breast, colorectal, and gastric cancer surgery in hospitals worldwide, focusing on the effect of disease stage and complications on postoperative mortality. Methods: This was a multicentre, international prospective cohort study of consecutive adult patients undergoing surgery for primary breast, colorectal, or gastric cancer requiring a skin incision done under general or neuraxial anaesthesia. The primary outcome was death or major complication within 30 days of surgery. Multilevel logistic regression determined relationships within three-level nested models of patients within hospitals and countries. Hospital-level infrastructure effects were explored with three-way mediation analyses. This study was registered with ClinicalTrials.gov, NCT03471494. Findings: Between April 1, 2018, and Jan 31, 2019, we enrolled 15 958 patients from 428 hospitals in 82 countries (high income 9106 patients, 31 countries; upper-middle income 2721 patients, 23 countries; or lower-middle income 4131 patients, 28 countries). Patients in LMICs presented with more advanced disease compared with patients in high-income countries. 30-day mortality was higher for gastric cancer in low-income or lower-middle-income countries (adjusted odds ratio 3·72, 95% CI 1·70–8·16) and for colorectal cancer in low-income or lower-middle-income countries (4·59, 2·39–8·80) and upper-middle-income countries (2·06, 1·11–3·83). No difference in 30-day mortality was seen in breast cancer. The proportion of patients who died after a major complication was greatest in low-income or lower-middle-income countries (6·15, 3·26–11·59) and upper-middle-income countries (3·89, 2·08–7·29). Postoperative death after complications was partly explained by patient factors (60%) and partly by hospital or country (40%). The absence of consistently available postoperative care facilities was associated with seven to 10 more deaths per 100 major complications in LMICs. Cancer stage alone explained little of the early variation in mortality or postoperative complications. Interpretation: Higher levels of mortality after cancer surgery in LMICs was not fully explained by later presentation of disease. The capacity to rescue patients from surgical complications is a tangible opportunity for meaningful intervention. Early death after cancer surgery might be reduced by policies focusing on strengthening perioperative care systems to detect and intervene in common complications. Funding: National Institute for Health Research Global Health Research Unit

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

© 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licenseBackground: Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide. Methods: A multimethods analysis was performed as part of the GlobalSurg 3 study—a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital. Findings: Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3·85 [95% CI 2·58–5·75]; p<0·0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63·0% vs 82·7%; OR 0·35 [0·23–0·53]; p<0·0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer. Interpretation: Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised. Funding: National Institute for Health and Care Research