This paper investigates the role of socioeconomic considerations in the formation of official COVID-19 reports. To this end, we employ a dataset that contains 1159 pre-processed indicators from the World Bank Group GovData360 and TCdata360 platforms and an additional 8 COVID-19 variables generated based on reports from 138 countries. During the analysis, a rank-correlation-based complex method is used to identify the time- and space-varying relations between pandemic variables and the main topics of World Bank Group platforms. The results not only draw attention to the importance of factors such as air traffic, tourism, and corruption in report formation but also support further discipline-specific research by mapping and monitoring a wide range of such relationships. To this end, a source code written in R language is attached that allows for the customization of the analysis and provides up-to-date results.

BackgroundNetwork society is creating new opportunities for value generation in all areas of our lives: new collaborative methods and tools are increasingly available for use by closely connected individuals and organizations. The stakeholders of the health ecosystem are potential winners of this networking process as a consequence of the increase in knowledge about health value generation supported by teamwork and collaborative approaches in this field.Case PresentationIn this paper, we focus on the transactional nature of health value generation networks. First, we analyze the transactions in the networks. We then propose a design structure—the Community Health Experience Model—for effective person-centered health value generation networks. In the second phase of the work, we describe how the system design of the complete transaction network was tested in a real-life pilot environment focusing on fall prevention in individuals with osteoporosis.As a result of the network-based collaborative service approach, fall risk decreased by 11.8% and the number of falls decreased by 4.5% within 3 months. Regarding the major health experience outcomes, self-evaluated condition-specific health literacy improved from 7.85 to 8.26 (an improvement of 0.41), while self-evaluated condition-specific self-management capability changed from 7.25 to 8.06 (0.81 improvement).ConclusionsIn conclusion, the proposed Community Health Experience Model is a novel and promising approach to designing the structure of more effective and efficient health services and collaborative networks.Electronic supplementary materialThe online version of this article (10.1186/s40985-018-0105-8) contains supplementary material, which is available to authorized users.

Cross-border areas and cross-border cooperation are one of the priorities of the EU policy. Those areas, often rich in recreational, cultural and natural resources provide a great potential for the development of sustainable tourism. The article analyzes the tourism in the Croatian-Hungarian (HR-HU) cross-border area under the assumption that different interventions can influence the perception of tourists and contribute to the realization of the full potential of the area. The method applied in the analysis is the gravity model. The results obtained by the model were tested with online in-depth interviews with three experts having backgrounds in entrepreneurship, decision making and the non-governmental sector, and focus groups, consisting of 31 experts in the field, show that altogether 72% of the tourists cross the border during a trip to the HR-HU border regions. Almost half of the respondents plan and organize programs during the trip. The main sources of collecting information about a trip are friends, family members and acquaintances, while 80% of the respondents also use at least one online tool for planning of the trip. In order to improve tourism indicators in the Croatian-Hungarian cross-border area, development of a cross-border online platform is being envisaged that would integrate different services and attractions, collect and utilize data, being the most important new raw material, thus opening a completely new space for virtual tourism.

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This paper investigates the role of socioeconomic considerations in the formation of official COVID-19 reports. To this end, we employ a dataset that contains 1,159 preprocessed indicators from the World Bank Group GovData360 and TCdata360 platforms and an additional 8 COVID-19 variables generated based on reports from 138 countries. During the analysis, a rank-correlation-based complex method is used to identify the time- and space-varying relations between pandemic variables and the main topics of World Bank Group platforms. The results not only draw attention to the importance of factors such as air traffic, tourism, and corruption in report formation but also support further discipline-specific research by mapping and monitoring a wide range of such relationships. To this end, an R Notebook is attached that allows for the customization of the analysis and provides up-to-date results.