Infectious Disease Containment Based on a Wireless Sensor System

Related publications (9)

A high-resolution human contact network for infectious disease transmission

Marcel Salathé

The most frequent infectious diseases in humans--and those with the highest potential for rapid pandemic spread--are usually transmitted via droplets during close proximity interactions (CPIs). Despite the importance of this transmission route, very little is known about the dynamic patterns of CPIs. Using wireless sensor network technology, we obtained high-resolution data of CPIs during a typical day at an American high school, permitting the reconstruction of the social network relevant for infectious disease transmission. At 94% coverage, we collected 762,868 CPIs at a maximal distance of 3 m among 788 individuals. The data revealed a high-density network with typical small-world properties and a relatively homogeneous distribution of both interaction time and interaction partners among subjects. Computer simulations of the spread of an influenza-like disease on the weighted contact graph are in good agreement with absentee data during the most recent influenza season. Analysis of targeted immunization strategies suggested that contact network data are required to design strategies that are significantly more effective than random immunization. Immunization strategies based on contact network data were most effective at high vaccination coverage.

2010

Dynamics and control of diseases in networks with community structure

Marcel Salathé

The dynamics of infectious diseases spread via direct person-to-person transmission (such as influenza, smallpox, HIV/AIDS, etc.) depends on the underlying host contact network. Human contact networks exhibit strong community structure. Understanding how such community structure affects epidemics may provide insights for preventing the spread of disease between communities by changing the structure of the contact network through pharmaceutical or non-pharmaceutical interventions. We use empirical and simulated networks to investigate the spread of disease in networks with community structure. We find that community structure has a major impact on disease dynamics, and we show that in networks with strong community structure, immunization interventions targeted at individuals bridging communities are more effective than those simply targeting highly connected individuals. Because the structure of relevant contact networks is generally not known, and vaccine supply is often limited, there is great need for efficient vaccination algorithms that do not require full knowledge of the network. We developed an algorithm that acts only on locally available network information and is able to quickly identify targets for successful immunization intervention. The algorithm generally outperforms existing algorithms when vaccine supply is limited, particularly in networks with strong community structure. Understanding the spread of infectious diseases and designing optimal control strategies is a major goal of public health. Social networks show marked patterns of community structure, and our results, based on empirical and simulated data, demonstrate that community structure strongly affects disease dynamics. These results have implications for the design of control strategies.

Public Library of Science2010

Modeling infectious disease dynamics towards informed public health interventions, with applications on COVID-19 and cholera

Joseph Chadi Benoit Lemaitre

Emerging and existing infectious diseases pose a constant threat to individuals and communities across the world. In many cases, the burden of these diseases is preventable through public health interventions. However, taking the right decisions and designing effective policies is an intricate task: epidemics are complex phenomena resulting from the interaction between the environment, pathogens, individuals, and societies. Modeling offers a principled way to reason about infectious disease dynamics from scarce and biased information and to guide decision-makers towards effective policies. This thesis tackles selected topics in cholera and COVID-19 modeling towards informed public-health decisions. These two contrasting diseases were associated by a twist of fate, but also through the lens of a common modeling approach: compartmental, SIR-based, models are conditioned on the available evidence using computer-age statistical inference frameworks. A set of five models is developed, each tackling a different facet of the spread and control of these two infectious diseases. Each model aims at answering questions related to either the understanding of the mechanisms behind disease transmission, the projection of the future dynamics under different scenarios, or the assessment of the effectiveness of past interventions. Moreover, a novel application of epidemiological models to the formal design of control policies is proposed. Optimal control provides a rigorous framework to identify the most effective control measures under a set of operational constraints, providing a benchmark on what it is possible to achieve with the available resources.The results presented in this thesis range from scientific insight on the relationship between cholera and rainfall in Juba, South Sudan to the COVID Scenario Pipeline which produces reports used to inform the response to the COVID-19 pandemic of different governmental entities. Furthermore, the effectiveness of the non-pharmaceutical interventions against COVID-19 in Switzerland is evaluated; and so is the probability of eliminating cholera from Haiti under different scenarios of mass vaccination campaigns. Finally, the development of an optimal control framework towards the effective spatial allocation of vaccines against SARS-CoV-2 in Italy closes this conversation of models.The present thesis demonstrates how infectious disease modeling enables informed decision-making by projecting the uncertainties under the light of the available evidence. It also highlights the effort needed to tailor the models and inference methods to the specificities of the transmission setting and the research question considered. From insights on transmission pathways to weekly reports aimed at decision-makers, it explores different applications of infectious disease modeling. Methods developed along the way enrich the toolbox available to modelers, to guide policy decisions further towards a reduction of the burden of infectious diseases on communities.

EPFL2021

Generalized reproduction numbers and the prediction of patterns in waterborne disease

Enrico Bertuzzo, Marino Gatto, Lorenzo Mari, Lorenzo Righetto, Andrea Rinaldo

Understanding, predicting, and controlling outbreaks of waterborne diseases are crucial goals of public health policies, but pose challenging problems because infection patterns are influenced by spatial structure and temporal asynchrony. Although explicit spatial modeling is made possible by widespread data mapping of hydrology, transportation infrastructure, population distribution, and sanitation, the precise condition under which a waterborne disease epidemic can start in a spatially explicit setting is still lacking. Here we show that the requirement that all the local reproduction numbers R-0 be larger than unity is neither necessary nor sufficient for outbreaks to occur when local settlements are connected by networks of primary and secondary infection mechanisms. To determine onset conditions, we derive general analytical expressions for a reproduction matrix G(0), explicitly accounting for spatial distributions of human settlements and pathogen transmission via hydrological and human mobility networks. At disease onset, a generalized reproduction number Lambda(0) (the dominant eigenvalue of G(0)) must be larger than unity. We also show that geographical outbreak patterns in complex environments are linked to the dominant eigenvector and to spectral properties of G(0). Tests against data and computations for the 2010 Haiti and 2000 KwaZulu-Natal cholera outbreaks, as well as against computations for metapopulation networks, demonstrate that eigenvectors of G(0) provide a synthetic and effective tool for predicting the disease course in space and time. Networked connectivity models, describing the interplay between hydrology, epidemiology, and social behavior sustaining human mobility, thus prove to be key tools for emergency management of waterborne infections.

Natl Acad Sciences2012

Vaccination is one of the most effective ways to protect people from being infected by infectious disease. However, it is often impractical to vaccinate all people in a community due to various resource constraints. Therefore, targeted vaccination, which vaccinates a small group of people, is an alternative approach to contain infectious disease spread. To achieve better performance in targeted vaccination, we collect student contact traces in a high school based on wireless sensors carried by students. With our wireless sensor system, we can record student contacts within the disease propagation distance, and then construct a disease propagation graph to model the infectious disease propagation. Based on this graph, we propose a metric called connectivity centrality to measure a node's importance during disease propagation and design centrality based algorithms for targeted vaccination. The proposed algorithms are evaluated and compared with other schemes based on our collected traces. Trace driven simulation results show that our algorithms can help to effectively contain infectious disease

IEEE2015

Infection Dynamics and Immune Response in a Newly Described Drosophila-Trypanosomatid Association

Anna Dostalova, Bruno Lemaitre

Trypanosomatid parasites are significant causes of human disease and are ubiquitous in insects. Despite the importance of Drosophila melanogaster as a model of infection and immunity and a long awareness that trypanosomatid infection is common in the genus, no trypanosomatid parasites naturally infecting Drosophila have been characterized. Here, we establish a new model of trypanosomatid infection in Drosophila-Jaenimonas drosophilae, gen. et sp. nov. As far as we are aware, this is the first Drosophila-parasitic trypanosomatid to be cultured and characterized. Through experimental infections, we find that Drosophila falleni, the natural host, is highly susceptible to infection, leading to a substantial decrease in host fecundity. J. drosophilae has a broad host range, readily infecting a number of Drosophila species, including D. melanogaster, with oral infection of D. melanogaster larvae resulting in the induction of numerous immune genes. When injected into adult hemolymph, J. drosophilae kills D. melanogaster, although interestingly, neither the Imd nor the Toll pathway is induced and Imd mutants do not show increased susceptibility to infection. In contrast, mutants deficient in drosocrystallin, a major component of the peritrophic matrix, are more severely infected during oral infection, suggesting that the peritrophic matrix plays an important role in mediating trypanosomatid infection in Drosophila. This work demonstrates that the J. drosophilae-Drosophila system can be a powerful model to uncover the effects of trypanosomatids in their insect hosts. IMPORTANCE Trypanosomatid parasites are ubiquitous in insects and are significant causes of disease when vectored to humans by blood-feeding insects. In recent decades, Drosophila has emerged as the predominant insect model of infection and immunity and is also known to be infected by trypanosomatids at high rates in the wild. Despite this, there has been almost no work on their trypanosomatid parasites, in part because Drosophila-specific trypanosomatids have been resistant to culturing. Here, we present the first isolation and detailed characterization of a trypanosomatid from Drosophila, finding that it represents a new genus and species, Jaenimonas drosophilae. Using this parasite, we conducted a series of experiments that revealed many of the unknown aspects of trypanosomatid infection in Drosophila, including host range, transmission biology, dynamics of infection, and host immune response. Taken together, this work establishes J. drosophilae as a powerful new opportunity to study trypanosomatid infections in insects.

American Society for Microbiology2015

Effective vaccine design and public vaccination programs have led to the eradication of several diseases and protected millions of people from deadly infections. However, intracellular infections remain a challenge and their eradication requires the activation of cytolytic mechanisms. CD8+ T cells promote effector mechanisms for infected cell killing subsequent to their priming by antigen-presenting cells. Their activation occurs upon detection of intracellular antigen in a pathway that many current subunit vaccine technologies are trying to approach by cross-presentation. Advances in CD8+ T cell-inducing subunit vaccines include direct targeting of antigens to cross-presenting cells and are studied in this thesis. Antigen delivery to the appropriate cell type for cross-presentation to CD8+ T cells can occur with fusion antibodies. Our laboratory has previously demonstrated that antigens bearing an erythrocyte-binding antibody domain (TER119) target the liver. We used this technology to fuse TER119 and ovalbumin (OVA) antigen with the BBOX domain of the high mobility group box 1 (HMGB1) danger signal and co-administer it with CpG-B adjuvant in a hepatic vaccine context. In liver vaccines, activation of local cytotoxic responses represents an important challenge. Erythrocyte-mediated OVA delivery with adjuvants resulted in cytotoxic CD8+ T lymphocyte (CTL) activation with memory formation in the liver and protection was provided after infection with Listeria monocytogenes. Another method for antigen targeting is through a cross-presenting dendritic cell (DC) subset, called CD8+ DCs. Recent studies in mice showed successful vaccination against OVA fused to XCL1 ligand, which binds CD8+ DCs. To attract CD8+ DCs to the site of injection for increased antigen uptake, we co-injected XCL1-OVA with a fusion protein consisting of XCL1 and the extracellular matrix (ECM) binding domain of placenta growth factor-2 (PlGF-2123-144), called XCL1-PlGF. XCL1-PlGF binds extracellular matrix at the injection site and attracts CD8+ DCs locally. In the context of prophylactic and therapeutic vaccination, the combination of two fusion proteins (XCL1-OVA and XCL1-PlGF) enhanced cytotoxicity and prolonged survival against B16-OVA melanoma. Finally, antigen transport via biomaterial delivery platforms was evaluated as an alternative method to deliver antigens to immunologically relevant sites. Our laboratory and others have shown that nanoscale carriers promote CTL responses in vaccination. Here we present a cationic micelle vaccination platform in which OVA and adjuvant (CpG-B and/or MPLA) loading is mediated by non-covalent molecular encapsulation and adsorption. Following a prime and double boost vaccination, CTL responses were raised in the spleen and lymph nodes of vaccinated mice, along with antigen-specific antibody production. These findings highlight the advantages of the micelle carrier platform in vaccine applications. Overall, this thesis presents novel techniques to target antigens to the appropriate cell compartments, facilitating CTL activation in vaccination either by direct targeting of antigen fused to antibodies and chemokines, or antigen delivery with polymeric vehicles. These platforms for optimized delivery seek to improve current approaches and impact the design of new strategies in CD8+ T cell inductive vaccination.

EPFL2016

An ecological and digital epidemiology analysis on the role of human behavior on the 2014 Chikungunya outbreak in Martinique

Marcel Salathé

Understanding the spatio-temporal dynamics of endemic infections is of critical importance for a deeper understanding of pathogen transmission, and for the design of more efficient public health strategies. However, very few studies in this domain have focused on emerging infections, generating a gap of knowledge that hampers epidemiological response planning. Here, we analyze the case of a Chikungunya outbreak that occurred in Martinique in 2014. Using time series estimates from a network of sentinel practitioners covering the entire island, we first analyze the spatio-temporal dynamics and show that the largest city has served as the epicenter of this epidemic. We further show that the epidemic spread from there through two different propagation waves moving northwards and southwards, probably by individuals moving along the road network. We then develop a mathematical model to explore the drivers of the temporal dynamics of this mosquito-borne virus. Finally, we show that human behavior, inferred by a textual analysis of messages published on the social network Twitter, is required to explain the epidemiological dynamics over time. Overall, our results suggest that human behavior has been a key component of the outbreak propagation, and we argue that such results can lead to more efficient public health strategies specifically targeting the propagation process.

2017

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

Infection Dynamics and Immune Response in a Newly Described Drosophila-Trypanosomatid Association

Anna Dostalova, Bruno Lemaitre

American Society for Microbiology2015

EPFL2016

Modeling infectious disease dynamics towards informed public health interventions, with applications on COVID-19 and cholera

Joseph Chadi Benoit Lemaitre

EPFL2021

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

Clara Galan Navarro

EPFL2017