1.     Background

Epidemiology studies the causes and consequences of morbidity and mortality across geographical boundaries, with emphasis on equitable disease control and health promotion in low-income and middle-income countries [1]. During the past decade, research integrity and research fairness have gained considerable momentum as they have direct implications for global health epidemiology [1].

Research integrity has emerged as a response to the ‘reproducibility crisis’ (the inability to reproduce research findings), which has shaken the foundations of most scientific disciplines [2]. Within epidemiological research findings obtained from ill-designed, badly implemented, inappropriately analyzed or selectively reported studies will also lead to irreproducible results [3, 4].

In clinical or interventional research, having a clear set of standards, like Good Clinical Practice (GCP) [5], has made a big difference. These guidelines help ensure that studies involving people are not only scientifically solid but also ethically sound and legally compliant [5]. They basically give researchers clear instructions, through the entire study development process, from designing the study to collecting data and sharing results, offering a reliable framework to follow at every step.

In epidemiology, especially in public and global health, there is no equivalent set of guidelines that are widely used in a similar way [6]. The good thing is that several groups have proposed standards for Good Epidemiological Practice (GEP) [1, 7-11], but these are applied inconsistently and often interpreted differently depending on the context. This lack of cohesion becomes even more noticeable in international and multidisciplinary research, where issues like ethical review, data sharing, and engaging local stakeholders are of particular importance as well as challenging .

Now, this idea of having standardized GEP guidelines is not new and there have been some efforts lately about the need for clearer, more practical guidelines for epidemiological research, especially focusing on global health. While (as stated above), clinical studies have long adhered to standards, epidemiological research has lacked a comparable framework that reflects the unique challenges of working across countries, disciplines, and communities. This gap is especially evident in global health settings, where the ethical and scientific stakes are particularly high.

Two important papers by Alba and colleagues [1, 6] have helped move this conversation forward. The first, published in 2020, introduced the BRIDGE statement. This is a detailed set of guidelines built through consultation with researchers around the world. What makes BRIDGE stand out is how it combines rigor with fairness. It does not just tell researchers what good science looks like, but it also considers how to do epidemiological research ethically in places where resources, power dynamics, and local contexts vary a lot [1]. The guidance offered on partnerships, ethics, and data sharing is especially relevant for work in low- and middle-income countries.

An earlier piece by Alba and Mergenthaler (2018) [6] makes a similar point: existing GEP frameworks are useful, but they do not go far enough for global health. The authors mention some all-too-familiar issues such as ethics reviews that do not align across countries, local researchers being left out of key decisions, and study practices that, often unintentionally, sideline the people closest to the work. They make a strong case for clearer, more relevant guidelines that reflect the real-world challenges of doing research that crosses borders and puts equity at the center.

Taken together, these two contributions lay the groundwork for a stronger, more responsive approach to GEP. They show that it is possible, and necessary, to combine scientific integrity with fairness and inclusiveness. The recommendations that we offer in this review are built on that foundation. Our aim is to review the already existing GEP guidelines and contribute to making them clearer, more consistent, and better aligned with the principles of global health. Out of scope is the review of complementary guidelines, as these will be discussed in another installment of our review.

2.     Overview of current GEP guidelines

The following overview categorizes the available GEP guidelines by how comprehensive these are, a summary overview can be found in Table 1. To determine which GEP guidelines are the most comprehensive, we need to evaluate them across several dimensions:

The evaluation criteria used were the following:

• Coverage across study phases: design, conduct, analysis, reporting.
• Ethics and governance: informed consent, ethics committees, data protection.
• Robust scientific standards: Validity, reproducibility, quality assurance
• Operational guidance: standard operating procedures (SOPs), project management, stakeholder roles
• Flexibility across settings: applicability in global/multicultural settings
• Integration with existing regulatory frameworks: alignment with available national/international laws and regulations.
• Resources for learning and professional growth.
• Ease of use/implementation.

2.1  Most comprehensive guidelines:

• DGEpi GEP (Germany)

Germany’s epidemiological community, through the Deutsche Gesellschaft für Epidemiologie (DGEpi), developed their own set of GEP guidelines [8] to help researchers stay on track throughout the entire research process, not only during data collection, but from the initial planning stages through to the reporting of results. These guidelines are meant to help researchers keep things transparent while making sure that privacy and data quality are not overlooked. They offer practical steps that can make studies more trustworthy and ethically sound, without being overly complicated. These are best suited to provide comprehensive guidance throughout all stages of epidemiological research, especially within Germany offering practical recommendations for both academia and applied settings, and most importantly, aligning with international regulations (e.g., ICH-GCP). The guidelines are by far the most complete set of guidelines: they are methodologically robust, ethically grounded and operationally useful. The only limitation is that these have a strong national focus and thus, some principles may need adaptation for non-German regulatory environments.

• Dutch GEP guidelines

The Dutch Society for Epidemiology developed its Good Epidemiological Practice (GEP) guidelines to support high-quality research across all stages of epidemiological studies [7]. These guidelines cover all study related steps from planning and study design to how data should be handled, and findings reported; giving strong emphasis on transparency, ethical responsibility, and proper data management, helping researchers stay focused on both scientific rigor and accountability. They also offer templates and structured implementation guidance. One major limitation is that they are less detailed in community engagement and global health contexts.

• Swiss Essentials of GEP

The Swiss Society for Public Health created a set of guidelines, known as the Essentials of GEP [10], to help make sure research in Switzerland meets basic quality and ethical standards. The aim of these guidelines is to support good science that is also transparent and ethically sound. They provide researchers with a clear way to think about how they plan, carry out, and share their studies. The guidelines also make it easier for those working in different areas of public health/epidemiology to collaborate by aligning international rules and regulations and creating a shared foundation for evaluating research.

The strengths of these guidelines are based on the balanced approach to scientific integrity, data ethics, and collaboration, and the fact that they harmonize well with international and European research standards. They also shed light on how to set clear communication standards and stakeholder roles. Their limitation lies in that they provide fewer operational tools for large-scale project management or digital data use.

2.2  Intermediate completeness

• KIT GEP

The Royal Tropical Institute (Koninklijk Instituut voor de Tropen or KIT) in the Netherlands put together its own GEP guidelines with the clear focus of making epidemiological research work properly in low-resource settings [1]. These guidelines grew out of the reality that doing research in low- and middle-income countries comes with a specific set of challenges, whether it's limited infrastructure, complex ethical questions, or the need to build trust and engage communities meaningfully. KIT’s approach is very hands-on. It’s not just about theory; it’s about helping researchers deal with the real-world issues that come up in global health fieldwork. These guidelines are excellent for global health research and LMICs with a strong focus on contextualization, pragmatic ethics, and community integration. These, however, have less technical detail on statistical design and less applicable for regulatory studies in high-income countries.

• ADELF GEP

The French-speaking epidemiology community, through the Association des épidémiologistes de langue française (ADELF) and partner organizations, created their own GEP guidelines [11] to help bring consistency and quality to research across Francophone regions. At their heart, these guidelines are about making sure research is done properly and responsibly. The guidelines outline practical steps for designing, running, and reporting epidemiological studies, focusing on both solid methods and ethical integrity in observational research. They also help researchers align with international expectations, so the work holds up both scientifically and ethically, regardless of the setting. The guidelines are methodologically rigorous and ethical, especially in French speaking settings, although these are more narrative than operational and are limited on actionable tools or templates.

2.3  Limited completeness

• IEA GEP

The International Epidemiological Association (IEA) authored their GEP guidelines to ensure that ethical standards are consistently applied in epidemiological research [9]. These guidelines are rooted in key ethical principles like respecting individuals’ autonomy, doing good, avoiding harm, and promoting fairness. They highlight the importance of informed consent and the critical role of ethics committees in reviewing studies. These GEP guidelines are about making sure that research benefits public health while also protecting the rights and well-being of participants, however they provide a very narrow scope for epidemiological research as they focus mainly on ethical principles and not operational processes. Having said this, they are very useful for universal ethical framing but lacks applied research tools.

Table 1.- Comparative overview of current GEP guidelines

3.     Identified gaps in GEP guidelines

From the summaries above, we can see that there are quite a few guidelines already existing out there, however, there are some important pieces still missing. A major gap is how to handle digital health tools and big data (as that coming from RWD), most guidelines barely touch on this, even though it’s now a major part of research. There’s also the issue of global consistency and harmonization. Without shared standards, it is evidently difficult to run meaningful cross-country studies or compare results. Additionally, community involvement is another weak spot; few guidelines give clear advice on how to bring local voices into the planning and execution of studies. Finally, many frameworks are not built to pivot quickly when things shift, like during a public health emergency or the appearance of a new disease.

4.     Discussion and conclusions

In this review we aimed at highlighting the strengths and limitations of available GEP guidelines to improve their relevance in today’s complex research environments. Among the existing frameworks, the DGEpi GEP [8] stands out as the most comprehensive overall as it combines methodological rigor, ethical principles, and clear operational guidance. The Dutch GEP [7] is particularly strong in implementation, offering structured templates and a clear focus on reproducibility. Meanwhile, the KIT GEP [1] brings a high degree of adaptability, making it especially useful for global health research and low-resource settings.

While these strengths are encouraging, there are still some important gaps that need attention. With more studies now using digital health tools and RWD [12], researchers are looking for clear, hands-on guidance especially when it comes to working with electronic health records, mobile health apps, and the large datasets that are routinely collected [13]. At the same time, as artificial intelligence (AI) and machine learning (ML) become more common in public health research, there is a pressing need for standards that ensure transparency, fairness, and the ability to reproduce results [14].

Community engagement is another crucial area that requires additional attention under GEP guidelines [15]. Though this is particularly important when studies involve groups that are considered vulnerable, the majority of guidelines currently do not provide much practical guidance on how to meaningfully involve communities in shaping research. The fact that many GEPs are primarily adapted to national contexts is another shortcoming of these guidelines, as for cross-border research, we require adaptable instruments that can function in various infrastructures, cultural norms, and regulatory contexts.

Regardless of how structured and available GEP guidelines become in the future, the responsibility for the implementation of these does not rest solely in single researchers but also in governments and research organizations. We mention this as throughout our years in observational research, we have observed the lack of understanding of what observational studies entail and the different needs between GEP and GCP. The most drastic example of this is when Institutional Review Boards or Ethics Committees do not have epidemiologists and/or researchers with experience in observational studies enlisted as part of their roster. This lack of relevant knowledge could result in slow reviews or decisions based on unsuitable criteria, occasionally using guidelines designed for clinical trials on studies with quite a different rationale. Institutions must therefore proactively develop that capacity by providing training and creating room for many points of view. Without such kind of support, even the best policies run the danger of sitting on the shelf rather than guiding research in the intended manner.

Finally, there are still some areas that do not get covered enough such as: One Health [16], environmental epidemiology [16], emergency preparedness [17], and open science [18]. As public health issues become more intertwined and reliant on data, it is important that GEPs grow with them. That means being open to more flexible study designs, encouraging collaboration across fields, and finding practical, transparent ways to share data responsibly.

5.     Recommendations

GEP guidelines need to evolve to stay relevant in a fast-changing research environment. There is a clear opportunity to widen their scope in several important areas. For example, we need stronger guidance on how to work with digital health tools and RWD, which are now central to many studies [13]. As AI and ML become more routine in public health, there is a real need for straightforward, practical guidance on how to use these tools responsibly [19]. That includes making sure the models are understandable and that others can check and replicate the results [19].

There is also the need to do improve the way communities are involved, especially those who are most affected by health disparities [15]. And with more studies now crossing borders, we also need tools that can help bring different countries in sync when it comes to ethics, data practices, and how research is actually done on the ground [20].

Emerging areas like One Health [16], which looks at the links between human, animal, and environmental health, also need more space in the current frameworks. Similarly, we need flexible guidance for doing research in emergencies such as a pandemic, natural disaster, or a conflict [17]. Finally, open science is not just a trend; it is a responsibility. We need stronger standards for data sharing, transparency, and making research results accessible and reusable [21]. Bringing these areas into GEP frameworks would help ensure they reflect how research is actually being done today and where it’s heading.

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