Bakgrund: Influensa är ett stort folkhälsoproblem på grund av att den är det vanligaste globala smittsamma sjukdomsutbrott som leder till grava mentala och fysiska hälsobelastningar. Syfte: Vi undersökte kliniskt relevanta depressiva och belastade ångestsymptom i kvinnor i samband med förlossningen under två av 1900-talets influensapandemier, N2N2 och/eller H2N3 samt det könsmogna stadiet (mellan ålder vid menarke and ådler vid menopaus) där andra reproduktiva faktorer i den kvinnliga grekiska befolkningen beaktades. Metoder: Tvärsnitts- och historiska data uppkom från 1039 kvinnliga deltagare som deltog i studien Hellenic Longitudinal Investigation of Aging and Diet (HELIAD) där sociodemografiska variabler inkluderade ålder. Resultatet av de depressiva symtomen mättes med hjälp av den Geriatriska depressionsskalan bestående av 15-artiklar (GDS-15). En kliniskt relevant depressiv symptom börda definierades som GDS>5. Ångestsymptom mättes med de 7 ångest artiklarna från sjukhusets ångest och depressionsskala (HADS-A). En kliniskt relevant belastad ångestsymptom definierades som >8 för HADS. H2N2-pandemi perioden inträffades 1956-1958 och H2N3-pandemin, 1967-1969. Självrapporterade reproduktiva steg variabler inkluderade ålder vid menarke, ålder vid menopaus, antal graviditeter, antal barn, barnens födelseår och antal aborter. Resultat: Kliniskt relevanta depressiva och belastade ångestsymptom observerades bland 24,5% respektive 15,8% av HELIAD-deltagarna. Ingen koppling observerades mellan varken GDS >5 (Chi-square, 0,39, p = 0,56) eller HADS >8 (Chi-square, 0,06, p = 0,82) och födelse under H2N2- och / eller H2N3-pandemier. Univariat samband mellan ålder vid menarke, antal graviditeter, det könsmogna stadiet, och antal aborter var dock associerat med GDS >5 (alla p <0,10). Därför, en stegvis logistisk regressionsmodell som utvärderade reproduktiva variabler visade att det fanns högre odds för en kliniskt relevant depressiv symtombörda i samband med en äldre ålder vid menarke (OR 1.09, 95% KI 1.00, 1.18) och högre antal graviditeter (OR 1.07, 95% KI 1,01, 1,14). Inga förbindelser observerades gällande ångest. Slutsats: Vår hypotes att födelse under en influensapandemi skulle påverka förekomsten av kliniskt relevanta senare depressiva och ångestsymptom avvisades i denna analys. Vår sekundära hypotes att reproduktions variabler skulle associeras med psykisk ohälsa senare i livet avvisades dock inte för depressiva symtom. Även om sambandet mellan en kliniskt relevant belastad depressiv symtom och ålder vid menarche och antalet graviditeter inte var övertygande, framhävs den viktiga rollen kvinnors reproduktiva hälsa har under hela livet. Mer forskning behövs för att förstå det tidsmässiga och konsekventa sambandet. / Background: Influenza is a major public health concern due to increasingly frequent global infectious disease outbreaks that result in great mental and physical health burdens. Aim: We investigated clinically relevant later life depressive and anxiety symptom burdens in women in association with giving birth during two 20th century influenza pandemics, H2N2 and/or H2N3, and reproductive stage, the total reproductive years of a woman defined mathematically as the age at menopause minus the age at menarche. We also considered other reproductive factors. Methods: Cross-sectional and historical data originated from 1039 female participants age 54 and older, enrolled in the Hellenic Longitudinal Investigation of Aging and Diet (HELIAD) in Greece. Sociodemographic variables included age. The depressive symptoms outcome was measured using the 15-item Geriatric Depression Scale (GDS-15). A clinically relevant depressive symptom burden was defined as GDS >5, Anxiety symptoms were measured using the 7 anxiety items from the Hospital Anxiety and Depression Scale (HADS-A). A clinically relevant anxiety symptom burden was defined as >8 for HADS. The H2N2 pandemic period occurred from 1956-1958 and the H2N3 pandemic, from 1967-1969. Selfreported reproductive stage variables included age at menarche, age at menopause, number of pregnancies, number of offspring, offspring’ birth year, and number of abortions. Results: Clinically relevant depressive and anxiety symptom burdens were observed among 24.5% and 15.8% of HELIAD participants, respectively. No association was observed between either GDS >5 (2, 0.39, p=0.56) or HADS >8 (2, 0.06, p=0.82) and giving birth during the H2N2 and/or H2N3 pandemics. However, univariate association between age at menarche, number of pregnancies, reproductive stage, and number of abortions were associated with GDS >5 (all p <0.10). Therefore, a stepwise logistic regression model evaluating these reproductive variables showed that higher odds of a clinically relevant depressive symptom burden in association with an older age at menarche (OR 1.09, 95%CI 1.00, 1.18) and higher number of pregnancies (OR 1.07, 95% CI 1.01, 1.14). No associations were observed for anxiety. Conclusion: Our hypothesis that giving birth during an influenza pandemic would influence the occurrence of clinically relevant later life depressive and anxiety symptoms was rejected in this analysis. However, our secondary hypothesis that reproductive variables would be associated with later life mental health was not rejected for depressive symptoms. While the associations between a clinically relevant depressive symptom burden and age at menarche and number of pregnancies were not strong, they point to the important role of women’s reproductive health over the life course. More research is needed to understand the temporality and consistencies of these associations.

This work builds on the use of several Mathematical Modeling tools to develop approaches that address relevant, real and previously unanswered questions related to the improvement of Public Health Systems, in three particular instances. First, this thesis analyzes the variation in state-level vaccination coverage during the emergency response to the 2009 H1N1 pandemic influenza outbreak in the United States. The analysis considers the overall adults population and two priority sub-populations: children and high-risk adults. We focus on quantifying the association between vaccination coverage and the supply chain and distribution system decisions, during the vaccine shortage period, while controlling for other commonly recognized factors such as previous vaccinations, socio-economic characteristics, health seeking behavior and health infrastructure. The variables analyzed are generally correlated, and the problem has a limited sample size with a much larger number of independent variables. The findings of this research have been published in Vaccine and presented to the Centers for Disease Control and Prevention. Second, the research approaches the problem of estimating childhood obesity prevalence in small geographic areas in the U. S. Obesity is recognized as one of the major health problems in the country, and attending this condition in children is of major importance to deal with the sources of the overall problem. The ability to target interventions to the most affected children populations is necessary to achieve cost effective solutions. But local accurate obesity data is hard to obtain and missing for most of the small areas in the country. The research focuses on estimating prevalence of obesity and overweight status in children in small geographical areas in the absence of surveillance and detailed sampling. Our modeling approach is built in two stages. The first one uses a logistic regression model that links individual characteristics to high-BMI status, and generates samples of the empirical distribution of its coefficients though bootstrap re-sampling. The second uses simulation to generate virtual population samples of the small areas, which are then combined with the logistic model samples to estimate prevalence. Confidence intervals are built though re-sampling. A very important feature of our approach is that all of its inputs are from publicly available data, which gives availability for the replication of the methodology to any health stakeholder in the US. The model estimates were validated by using separate models for adults and children in a state with available data. Estimates obtained from our modeling approach were used by a large healthcare provider to geographically target interventions for pediatric obesity. Third, the thesis presents an introductory analysis of the possible effects of partial disruptions to critical supply chains due to absenteeism caused by a generalized flu-like illness in the US. For this analysis, we first construct a plausible national food supply chain for milk and then we simulate its disruption. To build the supply chain we used public information regarding production, consumption, and major milk processors and bottlers, and fitted it into a supply network though optimization. Then, to analyze the effects of flow disruptions of the supply chain, we built a simulation of the operation of the network and virtually generated absenteeism, mildly disrupting the supply chain flows by the proportional absences. We used information on potential absenteeism in work groups from an influenza simulator. Our initial analysis shows that absenteeism may create variations along the supply chain, similar to those described in the bullwhip effect analysis literature, even in the absence of supply shortages and without variations in pricing or demand, for which we find no prior reference in the literature.

Avec l’entrée d’internet dans notre quotidien, avec les réseaux sociaux, dans un monde de plus en plus numérique et mobile, le recours à la communication par internet est indispensable dans les stratégies de communication, et particulièrement en communication de crise. Une enquête, auprès d’universités françaises, permet d’analyser, à partir de l’exemple de la grippe A, comment internet est devenu un outil majeur dans la communication des universités en situation de crise. La communication par internet est d’abord une aide. Elle permet de diffuser largement les messages d’information et de prévention. A ce titre, elle est une communication interne. Elle aide aussi l’établissement à assurer la continuité du service public d’enseignement, grâce aux outils numériques qu’il développe. Mais la communication par internet présente aussi des risques. Elle peut être brouillée, altérant ainsi les effets attendus, comme il a été constaté lors de la campagne de communication sur la vaccination. Elle peut aussi être victime d’attaques, parce que toute communication empruntant la voie internet est menacée, posant ainsi le problème de la sécurité des systèmes d’information. En cas de crise, les établissements seraient confrontés, d’une part à la nécessité de maîtriser les techniques de communication, d’autre part aux besoins liés à l’utilisation des outils numériques ; mais aussi aux risques pesant sur les systèmes d’information. Prévoir, dans la mesure du possible, la survenance de problèmes qui pourraient se poser en cas de crise, est nécessaire. En se préparant à l’avance à la gestion de crise, grâce notamment à la mutualisation des moyens et à une prise de conscience des risques, les universités pourraient mieux maîtriser ces difficultés. / Internet communication is now generally acknowledged as indispensable in communication strategies, and particularly in crisis communication. A survey of French universities makes it possible to analyze, through the example of the H1N1 flu pandemic, how the Internet became a major tool for the communication of universities in a crisis. At the internal level, Internet communication appears as a reliable resource, allowing the diffusion of informative and preventive messages. It also helps the institution to ensure the continuity of public educational services through digital tools. But Internet communication also involves risks. Messages can be blurred, thus altering their expected effects, as became clear during the communication campaign on immunization. Messages can also be the victim of attacks, because any communication via the Internet channel may be threatened in various ways. This poses the problem of the security of information systems. In sum, institutions in crisis must face not only the necessity to master digital techniques of communication, and to comply with the requirements inherent in the use of digital tools, but also to manage risks that are specific to digital information systems. Anticipating, so far as is possible, the occurrence of problems that might arise in a crisis is essential. By preparing to cope with crises, including through the pooling of resources and the awareness of risks, universities may better control these difficulties. The study of this crisis reveals not only the pertinent issues, but also how such preparation might be most effectively undertaken.

Abstract This study focuses on the process of communication between government agencies and the public during crisis situations, and the development of an effective response strategy when a significant threat to public health and/or safety is believed to exist. My specific research interests are (1) the nature of the decision-making process that influences the communicative choices made during such events, and (2) how decision-makers make sense of an evolving, ambiguous, and unpredictable situation, in order to establish credibility with the public, determine the appropriate response strategy, and gain the public's trust in order to influence its behavior. This is a qualitative research study based on a series of in-depth interviews conducted with key staff members of the Centers for Disease Control and Prevention (CDC) regarding the CDC's organizational response to the 2009-2010 H1N1 influenza pandemic. As global public health threats have the potential to significantly affect critical areas of the U.S. economy, national security policies are evolving to include strategic planning for issues related to global public health threats. However, despite having faced several serious public health threats during the past decade, governments worldwide and the global public health community continue to struggle with developing sufficient contingency plans and effective response strategies to meet the challenges of unexpected, highly unpredictable, and potentially devastating public health crises. My research addresses gaps identified in exploring the experience of crisis response participants in order to understand the process of response development. Additionally, I identify practices, processes, and recommendations that will be useful for future response teams confronted with equally challenging emerging threat and/or crisis scenarios.

This dissertation, studies two specific topics related to the research of computer-aided drug design(CADD) by employing the molecular simulations approach, that of protein drugs and that of small agents. These results can help drug designers to improve their products for treating special diseases. This work is divided into two parts: Protein drugs: Potential of mean force of the hepatitis C virus core protein¡Vmonoclonal 19D9D6 antibody interaction: Antigen-antibody interactions are critical for understanding antigen-antibody associations in immunology. To shed further light on this question, we studied a dissociation of the 19D9D6-HCV core protein antibody complex structure. However, forced separations in single molecule experiments are difficult, and therefore molecular simulation techniques were applied in our study. The stretching, that is, the distance between the centre of mass of the HCV core protein and the 19D9D6 antibody, has been studied using the potential of mean force calculations based on molecular dynamics and the explicit water model. Our simulations indicate that the 7 residues Gly70, Gly72, Gly134, Gly158, Glu219, Gln221 and Tyr314, the interaction region (antibody), and the 14 interprotein molecular hydrogen bonds might play important roles in the antigen-antibody interaction, and this finding may be useful for protein engineering of this antigen-antibody structure. In addition, the 3 residues Gly134, Gly158 and Tyr314 might be more important in the development of bioactive antibody analogues. Potential of mean force for syrian hamster prion epitope protein - monoclonal fab 3f4 antibody interaction studies: Simulating antigen-antibody interactions is crucial for understanding antigen-antibody associations in immunology. To shed further light into this question, we study a dissociation of syrian hamster prion epitope protein-fab3f4 antibody complex structure. The stretching (the distance between the center of mass of the prion epitope protein and the fab3f4 antibody) have been studied using potential of mean force (PMF) calculations based on molecular dynamics (MD) and implicit water model. For the complex structure, there are four important intermediates and two inter protein molecular hydrogen bonds in the stretching process. Inclusion of our simulations may help to understand the binding mechanics of the complex structure and will be an important consideration in design of antibodies against the prion disease. Potential of mean force for human lysozyme - camelid vhh hl6 antibody interaction studies: Calculating antigen-antibody interaction energies is crucial for understanding antigen-antibody associations in immunology. To shed further light into this equation, we study a separation of human lysozyme-camelid vhh hl6 antibody (cAb-HuL6) complex. The c-terminal end-to-end stretching of the lysozyme-antibody complex structures have been studied using potential of mean force (PMF) calculations based on molecular dynamics (MD) and explicit water model. For the lysozyme-antibody complex, there are six important intermediates in the c-terminal extensions process. Inclusion of our simulations may help to understand the binding mechanics of lysozym- cAb-HuL6 antibody complex. Small agents: Predictions of binding for dopamine D2 receptor antagonists by the SIE method: The control of tetralindiol derivative antagonists released through the inhibition of dopamine D2 receptors has been identified as a potential target for the treatment of schizophrenia. We employed molecular dynamics simulation techniques to identify the predicted D2 receptor structure. Homology models of the protein were developed on the basis of crystal structures of four receptor crystals. Compound docking revealed the possible binding mode. In addition, the docking analyses results indicate that five residues (Asp72, Val73, Cys76, Leu183, and Phe187) were responsible for the selectivity of the tetralindiol derivatives. Our molecular dynamics simulations were applied in combination with the solvated interaction energies (SIE) technique to predict the compounds' docking modes in the binding pocket of the D2 receptor. The simulations revealed satisfactory correlations between the calculated and experimental binding affinities of all seven tetralindiol derivative antagonists, as indicated by the obtained R2 value of 0.815. Combining homology modeling, docking, and molecular dynamics to predict the binding modes of oseltamivir, zanamivir, and Chinese natural herb products with the neuramindase of the H1N1 influenza A virus: The neuraminidase of the influenza virus is the target of the anti-flu drugs oseltamivir and zanamivir. Clinical practices show that zanamivir and oseltamivir are effective to treat the 2009 H1N1 influenza virus. Herein, we report the findings of molecular simulations for zanamivir, oseltamivir, and Chinese natural herb products with the neuramindase of the 2009 H1N1 influenza. Our approach theoretically suggests that the Glu278 residue is responsible for the neuramindase of the 2009 influenza drug selectivity.

A global outbreak of a new strain of H1N1 influenza virus caused the 2009 flu pandemic. Taiwan was one of the 12 countries in the world capable of producing H1N1 vaccine domestically. The domestic vaccine manufactured by Adimmune Corporation proved to be safe and effective. However, the public opinion generally criticized negatively toward this H1N1 prevention work. This study explored the various entities and relations surrounding the prevention. The first experiment looked into people¡¦s recall toward government¡¦s promotion. This experiment used EyeLink to track subjects¡¦ eye movements on the promotional posters. The data showed the correlation between eye movement and recall, as well as the amount of information received by the subjects. The second experiment looked into people¡¦s decision toward H1N1 prevention. This experiment constructed an AHP model to study the problem. The subjects from various fields answered their view toward H1N1 prevention alternatives, and reported the actual inoculation rate of H1N1 vaccine. The goal aimed to choose a prevention method. The criteria included convenience, confidence, safety, and comfort. The alternatives included vaccination, medication, and sanitation. The experiment outcome summarized the inoculation statistics, attention distribution, involvement correlations, and decision priorities. The experiment result shows the subjects do not receive government¡¦s promotion well. The result also shows the subjects prefer sanitation for prevention. In addition, this study investigates Taiwan¡¦s vaccine and disease prevention development status. The analysis examines Adimmune Corporation and the vaccine market from different aspects. Finally, the conclusion provides recommendations for the people, the vaccine factory, and the government.

published_or_final_version / Community Medicine / Doctoral / Doctor of Philosophy

published_or_final_version / Public Health / Master / Master of Public Health

In the United States and other developed countries, despite great efforts in time and funding for the prevention of foodborne and airborne diseases, there is still an unacceptable level of common pathogens spread via food, water, and air. To this end, lab-on-a-chip (LOC) technologies were developed for field-deployable assays and point of care diagnostics. These devices have potential applications in hospitals, agricultural farms, processing plants, and even on fields of battle. Two successful types of assays in the recent years towards point of care diagnostics are immunoassays and nucleic acid detection assays. In the Appendix A, we demonstrated a complete, field-deployable particle immunoassay encased within a microfluidic chip that detects small quantities of Salmonella Typhimurium in poultry fluid samples. Because the necessary reagents are pre-loaded and the test and negative control channels are fed by a single sample inlet, single pipetting of sample is possible. This assay demonstrated a 10 CFU/mL limit of detection, which is considerably lower than PCR and enzyme-linked immunosorbent assay (ELISA). Total assay time, including sample reading in an integrated handheld device, was 10 minutes, which was much lower than conventional methods. Because of the simplified protocol and assay time, this biosensor has potential in clinical and field diagnostic applications. In Appendix B, we fit the particle immunoassay to test for Influenza A H1N1/2009 virus and included aerosol sampling from a scaled-down mock classroom. To make the assay field deployable, we used an iPhone for signal detection. The detection limit of the assay was 1 pg/mL (10 pg/mL using the iPhone), which is well below the limit of detection for RT-PCR. This protocol demonstrated that immunoassays can be effective in the presence of interfering dust particles and that viruses can be collected from aerosol with minimal sample preparation. In Appendix C, we demonstrated that paper microfluidics, a newer vision of microfluidics, is a cheap and easy method to extract nucleic acid from S. Typhimurium in a variety of samples, including poultry packaging liquid, whole blood, and feces. Fluorescent detection with an iPhone allows for field and clinical testing. This protocol interfaces with rapid PCR and is a true diagnostic tool.

Influenza is a contagious respiratory disease that has caused at least four pandemics and countless epidemics since the 20th century, impacted millions of people worldwide and the global economy. To date, the predominant influenza species circulating in humans are influenza A and B. Influenza may cause serious illness in all age groups but individuals such as the newborns and senior population whose immune systems are compromised are at higher risk for severe disease. Interestingly, during the outbreak of pandemic 2009 H1N1 (H1N1pdm), it was found that the elderly had the lowest hospitalization rate and an increased proportion of healthy adults developed severe disease. Furthermore, several clinical studies have demonstrated that most H1N1pdm infected children experienced mild to moderate illness and led to the least mortality. The difference of disease outcome in age groups between different influenza infections may be due to several factors, which include differing pathogenicity between the viruses, differential immune status and composition among the age groups, and pre-existing immunity from previous encounter(s) with a similar virus. Since the human clinical data are often complicated by secondary factors such as co-morbidities, I used the ferret model to address these questions. I first compared the clinical and pathological patterns among the pandemic and seasonal influenza strains and found H1N1pdm caused the most severe illness to healthy ferrets. Importantly, the disease severity did not correlate with viral burden but immunopathology. To study the age effect, I found that H1N1pdm infected young ferrets with mild clinical symptoms developed specialized ectopic lymphoid structures and a distinct cytokine expression profile in the lungs, which were absent in adult ferrets with severe illness. I also examined antigenic change in historical H1N1s and anti-H1 responses to explain the pre-existing immunity of H1N1pdm found in the elderly. However, low similarity was found between historical H1N1s and H1N1pdm. Lastly, I conducted a detailed influenza B comparative study. I observed the pathogenic B strain was capable to cause lower respiratory tract infection and pathology like the influenza A viruses. Overall, this thesis provides novel insights for developing therapeutic and prophylactic strategies against influenza infection.