Quantitative methods for economics, environment and health - PhD Cycle XLI

Thematic Areas:
The doctoral program focuses on the interconnection between Economics, Environment, and Health, aiming to train researchers capable of analyzing complex phenomena such as climate change, social inequalities, health crises, and the ecological transition through a multidisciplinary approach and the use of quantitative methods and artificial intelligence.
Primary research areas include analyzing the impact of economic policies on the environment and health, as well as identifying new market opportunities. The program also assesses the effects of health conditions on productivity and collective well-being, with a particular emphasis on the search for natural active ingredients for the development of innovative and sustainable therapies. The program also addresses the study of environmental dynamics and the implementation of action research and citizen science projects for social innovation. Finally, a key thematic area concerns the ethical and regulatory aspects related to the use of quantitative tools and artificial intelligence, with particular attention to legal frameworks and the protection of sensitive data. The program combines scientific rigor and strong civic engagement, preparing doctoral students to actively contribute to the transformation of society towards greater economic, environmental, and health justice.

Educational Objectives:
The PhD program in Quantitative Methods for Economics, Environment, and Health aims to train a new generation of researchers capable of addressing the complex problems of our time, such as climate change and social inequalities, through an approach that transcends traditional disciplinary boundaries. The primary goal is to provide doctoral students with advanced and flexible scientific training, enabling them to develop critical thinking skills in the pursuit of sustainable, data-driven solutions.
The program focuses on the interconnection between economics, health, and the environment, providing advanced skills in key areas such as environmental and natural resource economics, health economics, applied statistics, and big data analysis. Doctoral students will learn to use quantitative models, collect data, and evaluate the impact of public policies. Particular attention is paid to the ethical and regulatory aspects related to the use of artificial intelligence, fostering a strong sense of social responsibility. The international dimension is a cornerstone of the program, with the opportunity to undertake research residencies abroad.
The graduates are highly qualified and versatile, ready for careers in the public sector (ministries, environmental and health agencies), the private sector (corporations, startups, consulting firms), particularly in roles related to ESG (Environmental, Social, Governance) objectives and corporate sustainability, and in academic and research careers, with the possibility of pursuing research nationally and internationally.

Educational Activities:

The curriculum includes courses, seminars, and workshops on topics such as:

• Quantitative Methods and Applications: 
  Courses focus on the use of mathematical tools, Data Science (exploratory analysis, visualization, advanced regression), and Artificial Intelligence (machine learning, deep learning) to model, analyze, and predict complex phenomena in the economic, environmental, and healthcare fields. The application of strategic decision-making models to contexts characterized by uncertainty and trade-offs is also addressed;
• Economics, Environment, and Sustainable Development: 
  Green and circular economy paradigms, climate change theories, and territorial sustainability are explored in depth.
  Courses analyze decarbonization policies, sustainable resource management, and circular bioeconomy approaches, providing tools for assessing the economic, social, and ecological impact of various strategies;
• Legal and Ethical Aspects: 
  The program explores the interaction between law and economics in environmental and healthcare regulation. The courses address the criminal protection of collective assets, corporate responsibility, and the ethical implications of the use of quantitative tools and artificial intelligence, incorporating them into national and European regulations;
• Health, Pharmaceuticals, and Pathophysiology: 
  The curriculum includes courses focused on the interaction between the environment, microbiota, and health, the exploration of phytochemicals and microbial derivatives with therapeutic potential, and the study of innovative pharmaceutical formulations. Pathophysiological barriers to the delivery of active ingredients and the integration of sustainable medicine approaches are also examined, with a particular focus on economic and environmental implications;
• Transversal Activities: 
  The doctoral program enhances its curriculum with a series of transversal activities aimed at providing doctoral students with the essential skills for a successful research career. These activities include advanced computer science training, which covers the use of advanced digital tools for data management, scientific communication, and the dissemination of results through open science and public engagement. Another key aspect is research management, which prepares PhD students to address practical aspects such as project planning and organization, participation in competitive calls, and research ethics.

Planned Courses:

1. Mathematics for Complex Systems and Modelling
   Course description: this course provides the mathematical tools needed to model andanalyze complex phenomena related to environmental, economic, and health systems. It explores differential modeling techniques, dynamic systems, complex networks, and stochastic models, with a focus on applications in sustainability, climate change, and environmental epidemiology;
2. Applied Data Science for Economics, Environment, and Health I
   Course description: This course introduces the primary data science tools used in the integrated analysis of economic, environmental, and health phenomena. Participants will learn exploratory analysis techniques, data visualization, clustering, advanced regression, machine learning, and big data management, with a specific focus on territorial analysis and the assessment of public policy impacts;
3. Intelligent Systems and Deep Learning for a Sustainable Future
   Course description: this course explores the theoretical foundations and practical applications of machine learning and deep learning techniques in the context of sustainability and public health. Supervised and unsupervised models, including deep neural networks, convolutional and recurrent networks, and artificial intelligence tools, will be covered for scenario forecasting, risk analysis, and the management of complex systems;
4. Green and Circular Economy: Theories and Applications
   Course description: the course analyzes the main economic paradigms related to the ecological transition, with a particular focus on green and circular economy models. The concepts of decarbonization, sustainable resource management, eco-innovation, industrial symbiosis, and sustainability indicators are explored, with a consistent integration of economic theory, policymaking, and real-world case studies;
5. Sustainable Development and the Economics of Climate Change
   Course description: the course explores the theories and tools of economics applied to sustainable development and the fight against climate change. Macroeconomic and microeconomic models, tools for internalizing externalities, mitigation and adaptation policies, environmental tax instruments, and integrated approaches for assessing the social, ecological, and economic impact of decarbonization strategies will be examined;
6. Law and Economics of Environmental and Health Policies
   Course description: this course examines the interplay between legal principles and economic instruments in environmental regulation and public health. Starting from the analysis of national, European, and international regulations, concepts such as responsibility, precaution, subsidiarity, and environmental justice are examined, relating them to economic incentives, externalities, market instruments, and public policies. The course aims to provide an integrated perspective that is useful for designing and evaluating sustainable, effective, and consistent regulatory and legislative interventions that balance fundamental rights and economic constraints;
7. Criminal Law and the Protection of Collective Goods
   Course description: this course examines the criminal aspects related to environmental protection, public health, and sustainable economic development. Particular attention will be paid to environmental, health, and public administration crimes, with a critical eye on the most recent legislative and case law developments, including at the European level.
   The course also explores the concepts of corporate criminal liability, the precautionary principle, economic crime, and the new frontiers of environmental and health criminal law, including the ethical and political implications for managing common goods;
8. Environment-Microbiota-Health Interactions: Biomedical Potential of Phytochemicals and Microbial Derivatives
   Course description: the course focuses on the analysis and modeling of interactions between the environment, the human gut microbiota, and health, exploring the role of active phytochemicals and microbial derivatives as therapeutic and preventive agents. It will investigate how environmental factors can influence the composition and function of the microbiota, and how compounds derived from edible plants and the microbiota itself can modulate health, with a particular focus on the prevention and treatment of neoplastic diseases. The efficacy of these compounds will be evaluated through in vitro (organoid) and in vivo models;
9. Applied Data Science for Economics, Environment, and Health II
   Course description: advanced course in applied statistics with a focus on multivariate methods, generalized models, time series analysis, and machine learning. Participants will explore the use of open-source statistical software (R, Python) to address complex datasets from economics, health, and environmental fields, developing independent modeling, visualization, and interpretation skills;
10. Strategic Decision-Making in Economics, Environment, and Health
    Course description: this advanced course explores the application of quantitative methods from decision theory to address complex strategic issues at the intersection of economics, environment, and health. Building on the foundations of decision theory, including rational choice models, game theory, and multicriteria methods, the course explores how these tools can be used to support informed and robust decision-making in contexts characterized by uncertainty, conflicts of interest, and multidimensional trade-offs;
11. Innovative Pharmaceutical and Nutraceutical Formulations
    Course description: this course introduces innovative pharmaceutical and nutraceutical forms, providing principles of industrial formulation and characterization for applications in the health field, and analyzes their applications through quantitative models. The course aims to stimulate learning of unconventional processes applied to food and pharmaceutical production, building on prior knowledge typically related to chemistry, health, and nutraceuticals;
12. Territorial Sustainability and Bioeconomy
    Course description: the course addresses the relationship between territorial development and the sustainable use of natural resources from a circular bioeconomy perspective.
    Integrated planning tools, sustainable local development models, the valorization of ecosystem services, and low-impact production chains are studied. The analysis includes participatory approaches, territorial indicators, and climate change adaptation strategies;
13. Advanced Laboratory Methodologies for Sustainable Health: Integration of Anti-Aging and Wellness Approaches
    Course description: this course examines how advanced laboratory methodologies and the application of models to anti-aging and wellness medicine can be integrated into a sustainable health perspective. The use of indicators such as metabolic, genetic, and microbial biomarkers will be analyzed to assess the impact of nutritional and therapeutic interventions not only on individual longevity but also on the environmental sustainability of healthcare practices and lifestyles. The course aims to develop skills and knowledge to analyze the economic and environmental implications of diagnostic and therapeutic choices in promoting health and well-being;
14. Modelling of Organ Pathophysiology: Studying Barriers to the Delivery of Bioactive Compounds
    Course description: this course aims to quantitatively study the organ and tissue barriers that influence the delivery of pharmacologically active ingredients, including both synthetic and natural compounds. Quantitative analysis will include evaluating the effectiveness of delivery in various physiopathological contexts (skin, respiratory system, and central nervous system as models), along with the economic sustainability for the healthcare system and the environmental impact ('green' perspective) of the processes and materials used. Through the application of quantitative models and statistical analyses, we will aim to optimize delivery strategies by considering economic, environmental, and therapeutic efficacy parameters;
15. EU Policies for Integrated Sustainability: Economy, Environment, and Health Nexus
    Course description: this course examines European Union policies that address the interdependencies between the economy, environment, and health. We will analyze how EU strategies for territorial integration and security intersect with the objectives of environmental sustainability, public health promotion, and inclusive economic development, with a particular focus on the challenges and opportunities arising from the European geopolitical context.

Coordinator: 

• Luca Grilli

Members of the Academic Board:

• Marta Elena Biancardi
• Barbara Cafarelli
• Giulio Mario Cappelletti
• Margherita Ciervo
• Massimo Conese
• Gaetano Corso
• Leonardo, Sergio Di Carlo
• Sante Di Gioia
• Gerarda Fattoruso
• Lucia Maddalena
• Michele Mastroianni
• Giorgio Mori
• Giuseppe Martino Nicoletti
• Andrea Nigri
• Carmela Paolillo
• Domenico Parisi
• Aurelio Portincasa
• Francesca Posa
• Francesco Ruggiero
• Giandomenico Salcuni
• Domenico Santoro
• Daniele Giuseppe Stasi
• Adriana Trapani
• Nicola Varrone

Members from foreign universities and other institutions:

• Ryszard Cierpiszewski
• Giansalvo Cirrincione
• Raffaele Giordano
• Malgorzata Krzywonos
• Tomasz Nitkiewicz
• Mariusz Tichoniuk
• Karolina Wiszumirska
• Vladimir Sashov Zhechev

PhD Student Representative on the Board:
Information currently unavailable

Information currently unavailable

The Doctoral Course's lessons will be delivered in a blended format, ensuring both in-person and remote participation to facilitate doctoral students and promote maximum flexibility.

The Doctoral Program actively promotes the participation of its doctoral students in Third Mission initiatives, which aim to disseminate scientific research beyond the academic sphere and engage with society and the local community.
To this end, doctoral students are invited to present their work at SEME - Multidisciplinary Seminar. This seminar was designed to promote the exchange of knowledge and collaboration among researchers from diverse disciplines. The program includes a series of meetings led by scholars, young researchers, and doctoral students from Italian and international universities and research centers.
In addition to this initiative, various public engagement activities are promoted, including days dedicated to presenting doctoral students' research projects and departmental open days for the public. Participation in scientific dissemination projects in schools and collaborations with local authorities and local businesses are also encouraged. The Doctoral Program boasts collaborations with companies such as Gargano Esco S.R.L. and Gattefossé SAS.
Doctoral students will also have the opportunity to conduct practical and research activities within the Data Analytics and Artificial Intelligence Lab (DAAIL) of the University of Foggia, which fosters interaction with external stakeholders and the implementation of projects with a tangible impact on society and the business world. These opportunities enable doctoral students to engage with the public and institutions, actively contributing to the dissemination of scientific knowledge and culture.

In order to optimize the procedures for authorization and reimbursement of missions for participation in scientific initiatives in Italy and abroad, it is necessary to follow the following steps:

• Send an email, preferably with at least seven days' notice, to the Coordinator and the secretariat requesting authorization for the mission, in accordance with the designated tutor. If available, attach the event flyer or other documentation related to the initiative you intend to participate in.
• Once you have received approval from the Coordinator via email, send the authorization request form reserved for doctoral students to the Administration and Accounting Service for the necessary internal procedures. The form should be completed and signed in each section.
• For the mission, it is possible to request a cash advance, for which the form must be completed and attached to the aforementioned mission assignment.
• At the end of the mission, submit the duly signed reimbursement request form to the Administration and Accounting Service, along with all the original supporting documents for the mission. Travel, meal, and accommodation expenses, receipts, and invoices must be submitted in their original form, accompanied by boarding passes, even if electronic.

Authorization for the mission is always necessary, regardless of any subsequent request for expense reimbursement.

The PhD program requires a mandatory period of training abroad, whose activation procedure should be addressed to the University Doctoral Office.