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Coming dissertations at Uppsala university

  • Cracks in the Ivory Tower : Antibiotics Research and the Changes in Academia 1980-2015 Author: Carl Björvang Link: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-474261 Publication date: 2022-06-09 14:15

    At the same time as resistance to antibiotics became an increasingly problematic health care concern around the world, major changes occurred in the condition scientists faced when conducting university-based research. This thesis aims to study these changes as they applied to antibacterial and bacteriological research, and how they influenced the researchers’ ability to make new scientific discoveries. Especially such discoveries that could be of critical importance for addressing the resistance problems of the era.

    Using interviews with researchers, funding data and political documents, this thesis has been able to confirm that findings regarding the global trend of changes in academic research from previous research also applied to the bacteriological research in Sweden in the late 20th and early 21st century. These changes included increased performance pressure, administrative burden, and concentration of funding to a few large research groups as well as decreased employment security and less time for senior researchers to be directly active in the scientific work. While there were many intertwined underlying factors for these developments, most of them could be traced back to the changes in funding model for academic science. Most crucially, research funding turned from being based on employment to being based on recurring applications to funding agencies.

    In conclusion, the changes in academic research conditions had major impacts on the ability of researchers to make new scientific discoveries. They incentivised doing safe, low-risk research with predictable outcomes, and producing many small, insubstantial publications. There were also some positive effects, such as a decrease in the impunity of senior researchers and a limitation on their ability to rest on their laurels. However, overall, this move away from taking chances and daring to research the truly unknown is likely to have decreased the ability of researchers to utilise their talents and follow-up on chance findings, decreasing their potential for discovery-making. Instead, it is likely that these changes within academia indirectly contributed to the antibacterial resistance problem by slowing down the rate of major breakthroughs in antibacterial treatments.

  • Lifestyle counselling in primary health care for patients with high cardiovascular risk : Aspects of a 1-year structured lifestyle programme promoting healthier lifestyle habits to reduce future risk of cardiovascular disease Author: Lena Lönnberg Link: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-474166 Publication date: 2022-06-09 09:31

    While the effects of lifestyle habits on hypertension or type 2 diabetes mellitus (T2DM) are well established, few lifestyle programmes in primary care directed towards patients with high cardiovascular risk have been evaluated.

    Aims To describe and elaborate on how participation in a 1-year lifestyle programme supported changes in lifestyle habits and altered the risk of cardiovascular disease (CVD) as well as explore patients’ and community health nurses’ (CHNs’) experiences of lifestyle change and counselling.

    Methods The 1-year lifestyle programme consisted of five appointments with a CHN for patients diagnosed with hypertension, T2DM or impaired glucose tolerance (n = 448). Focuse was on lifestyle habits that were related to patients’ diagnosis. Different behaviour change techniques were used to support lifestyle changes. Blood sampling and anthropometrical measurements were obtained at baseline and 1-year follow-up. The design of Studies I and II was observational and based on data that were consecutively collected between 2009 and 2014, whereas Studies III and IV had a qualitative design. Qualitative content analyses were performed based on data from individual interviews with patients (n = 16) and a focus group interview of CHNs (n = 3).

    Results Study I: Favourable changes in physical activity, dietary habits and smoking were detected after participation in the programme. Study II: Significant improvements were demonstrated for all cardiovascular risk factors and the estimated 10-year CVD risk after participation in the programme. Study III: Patients’ experiences of lifestyle changes indicated that increased knowledge of lifestyle habits, gaining trust in oneself and support from others were important elements in the adoption of lifestyle changes. Study IV: The informants expressed that counselling should be based on a partnership, include goal setting and repeated measurements, and incorporate long-term support after the completion of the lifestyle programme.

    Conclusion This thesis adds to the knowledge on how lifestyle counselling can be designed and implemented in primary care. The findings show that patients with a new diagnosis of hypertension or T2DM are at high risk for future CVD and a structured lifestyle programme can contribute to improved lifestyle habits and a reduced 10-year CVD risk.

  • Computational Modeling, Parameterization, and Evaluation of the Spread of Diseases Author: Robin Marin Link: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-473445 Publication date: 2022-05-24 11:48

    Computer simulations play a vital role in the modeling of infectious diseases. Different modeling regimes fit specific purposes, from ordinary differential equations to probabilistic formulations. Throughout the COVID-19 pandemic, we have seen how the results from these computational models can come to dictate our daily lives and the importance of reliable results. This thesis aims to address the challenge of exploiting the increase in available computational power to build accurate models with well-understood uncertainties. The latter is essential when basing decisions on any model predictions.

    Data collection relevant to epidemiology is expanding, and methods to incorporate models in data fitting need to follow suit. This thesis applies the Bayesian framework connecting data with models in a probabilistic setting. We propose simulation-based inference methods that allow for the use of complex models otherwise excluded due to their intractable likelihoods. Our computational set-up exemplifies how modelers can deploy Bayesian inference in large-scale, real-world data environments.

    The thesis includes four papers relevant for modelers considering dynamic systems, approximate Bayesian inference, or epidemics. Paper I finds the approximate posterior of a complex chemical reaction network and estimates the prior and posterior uncertainties using the pathwise Fisher information matrix, thus framing our methodology in a fully synthetic setting. Paper II constructs a disease spread model for the spread of a verotoxigenic E. coli prevalent in the Swedish cattle population. The data includes a high-resolution transport network and actual bacterial-swab observations from selected farms. The results show that even if the data is sparse in space and time, it is still possible to recover a posterior that replicates the data and is viable for mitigation evaluations. Paper III studies a form of meta-models, the Ornstein-Uhlenbeck process, and how they approximate epidemiological models and enable broad analysis. We state an analytical limit of what is possible to learn from data subject to binary filters with confirming numerical examples. Finally, Paper IV finds a posterior model of the COVID-19 pandemic in Sweden and the 21 regions using a Kalman filter approximation. The findings result in a probabilistic regional surveillance tool for an epidemic at a national scale with considerable cost-cutting potential independent of large-scale testing of individuals.

    In conclusion, the thesis examines how reasonably realistic and computationally expensive epidemic models can be adapted to data using a Bayesian framework without compromising model complexity and estimating uncertainties that further support decision-making.

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