International European border regions, known as Euregions, presents special challenges. While people working and carrying out daily activities outside of the border, the regulatory regime on health is divided by national borders. These populations were confronted with tremendous challenges as illustrated by the COVID pandemic. Therefore, we need to promote cooperation on the health-related issues cross-borderly to overcome the hurdles of national regime and to the direction of a structured Euregional decision-making. Our Public Health Service, GGD South Limburg and euPrevent have been working together for years on joint collaboration in the border region. Here we present you some work we have done during the last two years. Just to give you some idea how cross-border collaboration can contribute to better understanding of health, the health crisis, and how this can be used for better policy-making beyond the national border. One of our joint research projects is the euPrevent COVID-19 Project. This project aims to analyze the impact of COVID-19 on the border region between the Netherlands, Belgium, and Germany, which constitutes the Meuse-Rhine Euregion, also known as EMR. This project studied the prevalence of COVID-19 antibodies in the targeted population in relation to compliance with infection prevention and response measures. In 2021, a total of 30,000 test kits and surveys were sent out in two separate rounds and more than half of the recipients responded. The measures examined mainly include wearing a face mask, keeping social distance, limiting group size, limiting travels, cross border mobility, and reasons for vaccination. The participants were asked whether they judged the measures easy to comply with and to what extent they thought it important to keep certain measures. Some important findings of this study where the measures taken to limit the spread of the virus have disrupted normal life and the support from people for these measures decreased as the crisis continued. Also this restrictive measures concerning cross-border traffic did have very obvious effects in reducing cross-border traffic, but also had other undesired social and economic consequences while the impact on COVID control was minimal. Also the mass vaccination campaign is without a doubt a great success. An overwhelming majority of elders population is now fully vaccinated and only a small but significant minority has not yet been vaccinated. The fact that the Dutch population could and did cross the border to go to Aachen, a neighboring city in Germany, to get their booster vaccine showed the benefit of cross-border collaboration. The project resulted in a vast data and it could be a pity not to do anything with this data. Therefore we have integrated this data into Euregional Health Atlas and the COVID dashboard. Another example of our successful Euregional collaboration in research. It's an easy accessible platform that provides digital and comparable health data of the Euregions. This Atlas is accessible for everyone, health professionals and policymakers, as well as the general public. The data included in the Atlas mainly cover four topics: Health care, demography, lifestyle data, and quality of life. Most data presented in the Atlas comes from registered data and health surveys from the respective countries. In addition, data from the Euregional collaboration projects are also included in this Atlas. Lessons learned from the research perspective. Why doing cross-border research and what should we keep in mind? Citizens cross the border for many reasons, leisure, family visits, grocery shopping, going to work. Even in times of a pandemic, they still find it normal to do so. But authorities in charge of a pandemic often stop at the border. If you want to know how an infection is spreading and if you get it from your neighboring country, you need comparable data. However, compatible regional data are still largely lacking. Different national standards lead to data collection with different methods and these incompatible data do not have so much meaning for, for example, infectious disease control in a particular region that covers different sides of the border. It is also important from a research perspective that cross-border cooperation and data collection results in transparency and compatibility of data. It makes monitoring of real-time data in the region possible. This could and should be used as evidence and is the baseline for policy and decision-making. Sit together with your neighbors and see what kind of data they regularly collect, meaning existing data. See if there is a match and try to find a way to share these data with each other. The borders region is the best place for mutual learning. Create a data working group, cross-borderly. Now, at a time where there is maybe not a pandemic. Invest in this network. As soon as the pandemic rises, this will help you to get access quickly to data that you need.