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Ensamhet och social isolering utgör betydande utmaningar för äldre som bor själva och på äldreboende, genom att påverka deras fysiska och psykiska hälsa. På grund av krav på självisolering under Covid-19-pandemin har dessa utmaningar förvärrats ytterligare. Användningen av digital teknik inom äldreomsorgen har potential att motverka social isolering, till exempel genom att öka tillgången till hemtjänst och ge möjligheter att delta i sociala aktiviteter samtidigt är kunskaper om effektiviteten av digitala insatser för att motverka äldre människors ensamhet begränsad.

The incidence and geographical distribution of dengue fever has increased in recent decades. The actual disease burden is unknown owing to frequent underreporting and misclassification of cases. A well-functioning system for diagnosing, treating, and reporting cases is of prime importance as disease statistics is the foundation for decisions aiming to control the disease. This study aimed to explore the hospital-based disease surveillance system in Yogyakarta, a dengue-endemic region on Java, Indonesia. Semi-structured interviews were performed with 16 informants from four hospitals, including five general practitioners, three internists, four pediatricians, and four administrative staff working with administration relating to dengue diagnostics and reporting. Data were analyzed using content analysis. A theme arose from the analysis "Dengue surveillance stands and falls by the rigor of the health system." The theme, and underlying categories and subcategories, describes a surveillance system that in the best-case scenario works well and is likely to produce reliable dengue case data. However, there is a lack of synchronization between regulations and guidelines in different hospitals and some friction between regulatory bodies and the care provider. Knowledge among the staff appears to vary, and many clinical and financial decisions are made rather arbitrarily, which ultimately might lead to unequal health service delivery. In conclusion, the dengue surveillance system under study could improve further, particularly by ensuring that all regulations and recommended procedures are standardized and that all staff are given the best opportunity to stay updated on dengue-related matters, clinical as well as regulatory, on a regular basis.

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Effort to control dengue transmission requires community participation to ensure its sustainability. We carried out a knowledge attitude and practice (KAP) survey of dengue prevention to inform the design of a vector control intervention. A cross-sectional survey was conducted in June⁻August 2014 among 521 households in two villages of Yogyakarta, Indonesia. Demographic characteristics and KAP questions were asked using a self-managed questionnaire. Knowledge, attitudes and practice scores were summarized for the population according to sex, age, occupation and education. The average knowledge score was rather poor-3.7 out of 8-although both attitude and practice scores were good: 25.5 out of 32 and 9.2 out of 11 respectively. The best knowledge within the different groups were found among women, the age group 30⁻44 years, people with a university degree and government employees. Best practice scores were found among retired people and housewives. There were several significant gaps in knowledge with respect to basic dengue symptoms, preventive practices and biting and breeding habits of the Aedes mosquito. In contrast, people's practices were considered good, although many respondents failed to recognize outdoor containers as mosquito breeding sites. Accordingly, we developed a vector control card to support people's container cleaning practices. The card was assessed for eight consecutive weeks in 2015, with pre-post larvae positive houses and containers as primary outcome measures. The use of control cards reached a low engagement of the community. Despite ongoing campaigns aiming to engage the community in dengue prevention, knowledge levels were meagre and adherence to taught routines poor in many societal groups. To increase motivation levels, bottom-up strategies are needed to involve all community members in dengue control, not only those that already comply with best practices.

Background: New strategies are urgently needed to support self-management for people with chronic obstructive pulmonary disease (COPD) in primary care. The use of electronic health (eHealth) solutions is promising. However, there is a lack of knowledge about how such eHealth tools should be designed in order to be perceived as relevant and useful and meet the needs and expectations of the health professionals as well as people with COPD and their relatives. Objective: The objective of this study was to explore the aspects of an eHealth tool design and content that make it relevant and useful for supporting COPD-related self-management strategies from the perspective of health care professionals, people with COPD and their relatives, and external researchers. Methods: Data were collected during the development of an eHealth tool. A cocreation process was carried out with participants from two primary care units in northern Sweden and external researchers. Individual interviews were performed with health care professionals (n=13) as well as people with COPD (n=6) and their relatives (n=2), and focus group discussions (n=9) were held with all groups of participants. Data were analyzed using qualitative content analysis. Results: The overarching theme, reinforcing existing support structures, reflects participant views that the eHealth tool needs to be directly applicable and create a sense of commitment in users. Moreover, participants felt that the tool needs to fit with existing routines and contexts and preferably should not challenge existing hierarchies between health care professionals and people with COPD. Important content for health care professionals and people with COPD included knowledge about self-management strategies. Videos were regarded as the most effective method for communicating such knowledge. Conclusions: The cocreation in the development process enables participant perspectives and priorities to be built into the eHealth tool. This is assumed to

Background: Many telehealth (TH) systems have been designed to identify signs of COPD exacerbations, but few previous studies have reported the nature of recorded lung function data and what variations to expect in stable versus unstable patients. Aims: To evaluate the nature of individual diurnal, day-to-day and long-term variation in important prognostic markers of COPD exacerbations in a heterogeneous patient group by employing a newly developed TH system. Methods: Eight women and five men with COPD performed measurements (FEV1, IC, SpO2 and CAT) three times per week during 4-6 months using the TH system. Feasibility was based on the repeatability and quality of the FEV1 and IC measurements, as defined by ERS/ATS guidelines. Short-term and long-term individual variations were assessed using the relative density and mean (SD) respectively. Results: Close to 1100 FEV1 and IC measurements respectively were performed during a total of 240 patient weeks. The 2SD ranges for intra-individual variation were ± 210 mL and ± 350 mL for FEV1 and IC respectively. The values both increased and decreased without corresponding influence on symptoms (CAT) or SpO2 and no exacerbation was reported. However, it was unusual with a decrease of more than 50 mL per measurement in FEV1 between three consecutive measurement days. Conclusions: This study reveals important and, to our knowledge, previously not reported information about short and long-term variability in lung function measurements in stable patients with COPD, of significance when defining criteria for detecting exacerbations with TH systems.

Background: Chronic obstructive pulmonary disease (COPD) is a public health problem. Interprofessional collaboration and health promotion interventions such as exercise training, education, and behaviour change are cost effective, have a good effect on health status, and are recommended in COPD treatment guidelines. There is a gap between the guidelines and the healthcare available to people with COPD. The aim of this study was to increase the understanding of what shapes the provision of primary care services to people with COPD and what healthcare is offered to them from the perspective of healthcare professionals and managers. Methods: The study was conducted in primary care in a Swedish county council during January to June 2015. A qualitatively driven mixed methods design was applied. Qualitative and quantitative findings were merged into a joint analysis. Interviews for the qualitative component were performed with healthcare professionals (n = 14) from two primary care centres and analysed with qualitative content analysis. Two questionnaires were used for the quantitative component; one was answered by senior managers or COPD nurses at primary care centres (n = 26) in the county council and the other was answered by healthcare professionals (n = 18) at two primary care centres. The questionnaire data were analysed with descriptive statistics. Results: The analysis gave rise to the overarching theme building COPD care on shaky ground. This represents professionals driven to build a supportive COPD care on 'shaky' organisational ground in a fragmented and non-compliant healthcare organisation. The shaky ground is further represented by uninformed patients with a complex disease, which is surrounded with shame. The professionals are autonomous and pragmatic, used to taking responsibility for their work, and with limited involvement of the management. They wish to provide high quality COPD care with interprofessional collaboration, but they lack competence and a

In the year of 2016, there were more than 24 million Indonesian twitter users sharing news, events, as well as personal feelings and experiences on Twitter. This study seeks to validate a search protocol of health-related terms using real-time Twitter data which can later be used to understand if, and how, twitter can reveal information on the current health situation in Indonesia. In this validation study of mining protocols, we extracted geo-located conversations related to health and disease postings on Twitter using a set of pre-defined keywords, assessed the prevalence, frequency and timing of such content in these conversations, and validated how this search protocol was able to detect relevant disease tweets. Groups of words and phrases relevant to disease symptoms and health outcomes were used in a protocol developed in the Indonesian language in order to extract relevant content from geo-tagged Twitter feeds. A supervised learning algorithm using Classification and Regression Trees was used to validate search protocols of disease and health hits comparing to those identified by a team of human experts. The experts categorized tweets as positive or negative in respect to health events. The model fit was evaluated based on prediction performance. We observed 390 tweets from historical Twitter feeds and 1,145,649 tweets from Twitter stream feeds during the period July 26th to August 1st, 2016. Only twitter hits with health related keywords in the Indonesian language were obtained. The accuracy of predictions of mined hits versus expert validated hits using the CART algorithm showed good validity with AUC beyond 0.8. Our study shows that monitoring of public sentiment on Twitter, combined with contextual knowledge about the disease, can detect health and disease tweets and potentially be used as a valuable real-time proxy for health events over space and time.

Research is needed to create early warnings of dengue outbreaks to inform stakeholders and control the disease. This analysis composes of a comparative set of prediction models including only meteorological variables; only lag variables of disease surveillance; as well as combinations of meteorological and lag disease surveillance variables. Generalized linear regression models were used to fit relationships between the predictor variables and the dengue surveillance data as outcome variable on the basis of data from 2001 to 2010. Data from 2011 to 2013 were used for external validation purposed of prediction accuracy of the model. Model fit were evaluated based on prediction performance in terms of detecting epidemics, and for number of predicted cases according to RMSE and SRMSE, as well as AIC. An optimal combination of meteorology and autoregressive lag terms of dengue counts in the past were identified best in predicting dengue incidence and the occurrence of dengue epidemics. Past data on disease surveillance, as predictor alone, visually gave reasonably accurate results for outbreak periods, but not for non-outbreaks periods. A combination of surveillance and meteorological data including lag patterns up to a few years in the past showed most predictive of dengue incidence and occurrence in Yogyakarta, Indonesia. The external validation showed poorer results than the internal validation, but still showed skill in detecting outbreaks up to two months ahead. Prior studies support the fact that past meteorology and surveillance data can be predictive of dengue. However, to a less extent has prior research shown how the longer-term past disease incidence data, up to years, can play a role in predicting outbreaks in the coming years, possibly indicating cross-immunity status of the population.

In the year of 2016, there were more than 24 million Indonesian twitter users sharing news, events, as well as personal feelings and experiences on Twitter. This study seeks to validate a search protocol of health-related terms using real-time Twitter data which can later be used to understand if, and how, twitter can reveal information on the current health situation in Indonesia. In this validation study of mining protocols, we extracted geo-located conversations related to health and disease postings on Twitter using a set of pre-defined keywords, assessed the prevalence, frequency and timing of such content in these conversations, and validated how this search protocol was able to detect relevant disease tweets. Groups of words and phrases relevant to disease symptoms and health outcomes were used in a protocol developed in the Indonesian language in order to extract relevant content from geo-tagged Twitter feeds. A supervised learning algorithm using Classification and Regression Trees was used to validate search protocols of disease and health hits comparing to those identified by a team of human experts. The experts categorized tweets as positive or negative in respect to health events. The model fit was evaluated based on prediction performance. We observed 390 tweets from historical Twitter feeds and 1,145,649 tweets from Twitter stream feeds during the period July 26th to August 1st, 2016. Only twitter hits with health related keywords in the Indonesian language were obtained. The accuracy of predictions of mined hits versus expert validated hits using the CART algorithm showed good validity with AUC beyond 0.8. Our study shows that monitoring of public sentiment on Twitter, combined with contextual knowledge about the disease, can detect health and disease tweets and potentially be used as a valuable real-time proxy for health events over space and time.

BACKGROUND: The healthcare sector is a significant contributor to global carbon emissions, in part due to extensive travelling by patients and health workers. OBJECTIVES: To evaluate the potential of telemedicine services based on videoconferencing technology to reduce travelling and thus carbon emissions in the healthcare sector. METHODS: A life cycle inventory was performed to evaluate the carbon reduction potential of telemedicine activities beyond a reduction in travel related emissions. The study included two rehabilitation units at Umeå University Hospital in Sweden. Carbon emissions generated during telemedicine appointments were compared with care-as-usual scenarios. Upper and lower bound emissions scenarios were created based on different teleconferencing solutions and thresholds for when telemedicine becomes favorable were estimated. Sensitivity analyses were performed to pinpoint the most important contributors to emissions for different set-ups and use cases. RESULTS: Replacing physical visits with telemedicine appointments resulted in a significant 40-70 times decrease in carbon emissions. Factors such as meeting duration, bandwidth and use rates influence emissions to various extents. According to the lower bound scenario, telemedicine becomes a greener choice at a distance of a few kilometers when the alternative is transport by car. CONCLUSIONS: Telemedicine is a potent carbon reduction strategy in the health sector. But to contribute significantly to climate change mitigation, a paradigm shift might be required where telemedicine is regarded as an essential component of ordinary health care activities and not only considered to be a service to the few who lack access to care due to geography, isolation or other constraints.

Dengue fever is a major problem in many developing countries, including Indonesia. Laboratory examination is used to diagnose dengue infection and to monitor disease progression. Hematology tests, such as platelet count, are also used for timely recognition of the development of severe dengue. In primary health care centers platelet counting is typically performed manually, which is labor intensive and requires an experienced laboratory technician. To address this challenge, we have developed an automatic platelet counter for primary health care and resource-poor settings. The technology is based on a conventional microscope equipped with a digital camera linked to a personal computer, which can capture and analyze microscope images of blood samples. To evaluate the accuracy of the technology, it was compared to platelet counts performed manual by an experienced laboratory technician. Statistical analysis shows no difference between the techniques with a kappa coefficient of 0.6. This method is judged to have great potential as a tool to help primary health centers and other facilities with limited resources to deal with the burden of dengue.

Climate change is one of today's most pressing global issues. Policies to guide mitigation and adaptation are needed to avoid the devastating impacts of climate change. The health sector is a significant contributor to greenhouse gas emissions in developed countries, and its climate impact in low-income countries is growing steadily. This paper reviews and discusses the literature regarding health sector mitigation potential, known and hypothetical co-benefits, and the potential of health information technology, such as eHealth, in climate change mitigation and adaptation. The promising role of eHealth as an adaptation strategy to reduce societal vulnerability to climate change, and the link's between mitigation and adaptation, are also discussed. The topic of environmental eHealth has gained little attention to date, despite its potential to contribute to more sustainable and green health care. A growing number of local and global initiatives on 'green information and communication technology (ICT)' are now mentioning eHealth as a promising technology with the potential to reduce emission rates from ICT use. However, the embracing of eHealth is slow because of limitations in technological infrastructure, capacity and political will. Further research on potential emissions reductions and co-benefits with green ICT, in terms of health outcomes and economic effectiveness, would be valuable to guide development and implementation of eHealth in health sector mitigation and adaptation policies.

Cholera is a disease which shows a clear blood group profile, with blood group 0 individuals experiencing the most severe symptoms. For a long time, the cholera toxin has been suspected to be the main culprit of this blood group dependence. Here, we show that both El Tor and classical cholera toxin B-pentamers do indeed bind blood group determinants (with equal affinities), using Surface Plasmon Resonance and NMR spectroscopy. Together with previous structural data, this confirms our earlier hypothesis as to the molecular basis of cholera blood group dependence, with an interesting twist: the shorter blood group H-determinant characteristic of blood group 0 individuals binds with similar binding affinity compared to the A-determinant, however, with different kinetics. (C) 2012 Elsevier Inc. All rights reserved.

In a number of bacterial infections, such as Helicobacter pylori, Campylobacter jejuni and Vibrio cholerae infections, a correlation between the severity of disease and blood group phenotype of infected individuals has been observed. In the present investigation, we have studied the molecular basis of this effect for enterotoxigenic Escherichia coli (ETEC) infections. ETEC are non-invasive bacteria, which act through second messenger pathways to cause diarrhea. It has been suggested that the major virulence factor of ETEC from human isolates, i.e. the human heat-labile enterotoxin (hLT), recognizes certain blood group epitopes, although the molecular basis of blood group antigen recognition is unknown. The 2.5 angstrom crystal structure of the receptor-binding B-subunit of hLT in complex with the blood group A antigen analog GalNAc alpha 3(Fuc alpha-2)Gal beta 4(Fuc alpha-3)Glc beta provides evidence of a previously unknown binding site in the native toxin. The structure reveals the molecular interactions underlying blood group antigen recognition and suggests how this protein can discriminate between different blood group epitopes. These results support the previously debated role of hLT in the blood group dependence of ETEC infections. Similar observations regarding the closely related cholera toxin in V. cholera infections are also discussed.