Public health | EPFL Graph Search

Public health is "the science and art of preventing disease, prolonging life and promoting health through the organized efforts and informed choices of society, organizations, public and private, communities and individuals". Analyzing the determinants of health of a population and the threats it faces is the basis for public health. The public can be as small as a handful of people or as large as a village or an entire city; in the case of a pandemic it may encompass several continents. The concept of health takes into account physical, psychological, and social well-being. Public health is an interdisciplinary field. For example, epidemiology, biostatistics, social sciences and management of health services are all relevant. Other important sub-fields include environmental health, community health, behavioral health, health economics, public policy, mental health, health education, health politics, occupational safety, disability, oral health, gender issues i

Evaluation of oxidation-sensitive polymersomes as vaccine nanocarriers to enhance humoral responses against arenavirus envelope glycoproteins

Clara Galan Navarro

Vaccines currently represent one of the most effective means to control and prevent infectious diseases affecting humans and animals and have dramatically improved public health, quality of life, and life expectancy. Over the last years several conceptual and technological advances in the field of bioengineering and immunology have allowed the development of new vaccines designs. Expanding novel domains such as structural biology, human monoclonal antibody isolation, high throughput sequencing, and design of new nanocarrier delivery platforms have changed the landscape of vaccinology. These new vaccine formulations allow the design of tailor-made antigens and particulate vehicles which allow better and fine-tuned protective immune responses against known and newly emerging pathogens. Over the past decades emerging human pathogens with the potential to cause severe epidemics have become a major public health problem. The last Ebola and Zika virus epidemics demonstrated in a dramatic manner that there is an urgent need to develop prophylactic and therapeutic approaches against pathogenic emerging viruses. Most successful vaccines rely on attenuated live microorganisms to induce protective immunity. However, changed demographics and associated safety concerns makes the development of a safer alternative a priority. Subunit vaccines composed of microbial components and proteins have emerged as a suitable alternative, however they are generally less immunogenic. To address this problematic our laboratory works on the development of immunization platforms which allow 1) the development of safe recombinant subunit vaccines and 2) the rapid generation of specific monoclonal antibodies using biosynthetic immunogens without the need for prior isolation and culture of the agent. The approach evaluated in the present studies is based on a novel polymersome (PS) platform serving as nanocarrier for efficient antigen delivery and the induction of humoral immunity. The potential of PS was assessed in the context of two important human emerging pathogens form the arenavirus family that cause severe hemorrhagic fevers and of which there are neither FDA-approved vaccines not prophylactic treatments: Lassa virus (LASV), endemic in Western Africa, and Machupo virus (MACV), the causative agent of Bolivian hemorrhagic fever. In a first part, we evaluated the PS platformâs capacity to enhance humoral immunity against the envelope glycoprotein 1 of LASV, (LASV GP1) that is notorious for its weak immunogenicity and poor antibody response. Immunization of mice with adjuvanted PS (LASV GP1) enhanced the quality of the humoral response to LASV GP1, eliciting antibodies with higher binding affinity to virion GP1, increased levels of polyfunctional anti-viral CD4 T cells, and the frequency of IgG-secreting B cells. PS (LASV GP1) elicited a more diverse epitope repertoire of anti-viral IgG. In a second part, we employed the PS platform in combination with single cell B cell sorting and cloning of recombinant IgG to generate a first set of species-specific mAbs against MACV. These new mAbs show exquisite specificity and negligible cross-reactivity to closely related arenaviruses in relevant techniques making them a unique and powerful tool for research and diagnostics purposes.

EPFL2017

A field-based modelling framework of the ecohydrology of schistosomiasis

Francisco Javier Perez Saez

Successful control of schistosomiasis, a water-borne parasitic disease, is challenged by the intricacy of the wormâs lifecycle, which depends on aquatic snail intermediate hosts, and involves environmental, ecologic, and socio-economic factors. Current strategies rely on deworming through mass drug administration which however do not protect against reinfection and the persistence of hotspots. It is recognized that multifaceted approaches will be necessary to reach elimination, whose development will require a renewed focus on the diseaseâs social-ecological drivers. Taking cue from the hydrological underpinning of these drivers, this Thesis aims at developing an ecohydrological approach to schistosomiasis with a view to identifying and exploiting the points in which its cycle can be broken. Schistosomiasis is a poverty-reinforcing disease affecting more than 150 million people in sub-Saharan Africa, being the parasitic disease causing the largest health burden after malaria. However, the impairing morbidity it causes has been undervalued in the past, qualifying it as a neglected tropical disease. Moreover, water resources development often exacerbate transmission, posing scientific and ethical challenges in addressing the ensuing trade-off between economic development and public health. The relevance of this Thesisâ work lies in furthering tools to offset this trade-off by unlocking the predictive appraisal of the social-ecological drivers of transmission. An integration of fieldwork applied in Burkina Faso (West Africa) and theoretical methods are employed to address this aim. This Thesis establishes the use of spatially explicit mathematical models of schistosomiasis at the national-scale, allowing to study the effect of human mobility and spatial heterogeneity of transmission parameters. Weekly ecological samplings of snail abundance and continuous environmental monitoring were preformed at three sites along the countryâs climatic gradient, leveraged through ecological modelling. A novel methodology for the large-scale prediction of river network ephemerality allowed for refined snail species distribution models, and the analysis of the diseaseâs geography in link with socio-economic covariates. Finally, surveys and participatory workshops shed light on local-scale water contact patterns. The obtained results substantiate the stance that hydrology is a first-order control of disease transmission. Stability analysis of the spatially explicit model generated additional insight into the impact of the expansion of suitable snail habitat due to water resources development, highlighting the interplay between local and country-wide effects driven by human mobility. Models of snail ecology revealed key hydrological drivers, and disputed density feedbacks. Uncovered phase shifts between permanent and ephemeral habitats were adequately reproduced at the national scale through model regionalization. Characterization and predictions of hydrological ephemerality improved the estimation of the snailsâ ecological range, mirroring the diseaseâs geography. Finally a national-scale association between ephemerality and disease risk was observed, possibly due to human-water contacts aggregation, as supported by preliminary results at village-level. The future incorporation of these ecohydrological findings into spatially explicit models of schistosomiasis is considered promising for optimizing control strategies and attaining disease elimination.

EPFL2018

Adaptive Mitigation: Identification of the Dynamic Drivers of Effective Policy during the COVID-19 Pandemic

Thierry Bossy

Introduction: The unprecedented speed and scale of the COVID-19 pandemic necessitated the rapid implementation of untested public health measures to mitigate the consequences of viral spread. In the 8 months that have passed since the first recognized case, an enormous amount of research has been published evaluating the efficacy of the various policies implemented by different countries, however the majority of these studies focus on a specific region or time, over-representing high-income countries during periods of extreme transmission or “peak events”. The aim of this study is to provide a more general analysis that considers a global scope of the pandemic and the dynamic drivers that build effective policies to mitigate human interactions and slow the spread of disease. Methods: We collected a range of information regarding epidemic trends, weather, demographics, government response and mobility reports across the globe. We then built an hybrid Neural Network that combined an LSTM layer with a multilayer perceptron to infer the reproduction number from various non-epidemiological factors. The model was designed to predict the reproduction number (R-value) on 93 countries with available data and compare it to our ground truth estimate obtained from officially reported epidemiological data. Finally, we used an alternative model to assess the impact of public health measures on the epidemic. Findings: From the available features, we obtained the best performances using demographics combined with mobility features. The sanitary indices (beds/thousand, diabetes prevalence, ...) did not help the prediction and, more interestingly, the pressure indicator of historical weather forecast improved the prediction of the reproduction number by about 4.5%. This optimized model predicted the reproduction number with a mean absolute error of 0.254 across the 93 countries over the time of the epidemic. For many countries (Switzerland, United Kingdom, South Africa, ...) this error passed below 0.17. An alternative version of the model allowed us to estimate the impact of policies in terms of average reduction in reproduction number, and more importantly, allowed us to compare these trends between countries. For instance, we observe that the model showed that no policy had a positive impact in India as opposed to Switzerland, where most of them are associated to improved epidemic control. Conclusion: Understanding these complex interactions may allow individuals and policy makers to better adapt mitigation strategies to optimize the efficacy of the implemented policies.

2020