Environmental drivers of Dengue, Chikungunya and Zika transmission and their mosquito vector, Aedes aegypti, in two coastal hotspots in Ecuador

In the Americas, arbovirus transmission is concentrated within urban settings in tropical zones, where high human population densities and environmental conditions enhance the survival and reproduction of Aedes aegypti. Since its re-emergence in South America in the 70’s, dengue virus has been expanding and increasing in urban settings where it is now endemic. Additionally, the recent arrival of new arboviruses into the region, such as chikungunya (2013) and Zika virus (2015), have triggered major epidemics leading significant public health and economic impacts. These pathogens are linked in sharing a common mosquito vector in Ae. aegypti. Given the absence of effective licenced vaccines, vector control is thus the primary strategy for reducing the transmission of all of these pathogens. Effective vector control and public health preparedness require detailed understanding of vector ecology and human exposure risk within foci of transmission. Both vector populations and viral dynamics are highly dependent on environmental conditions, but the nature of environmental impacts likely depends on local ecological context. Ecuador bears an important burden of arboviral transmission in South America. Most transmission is concentrated in coastal cities where dengue is endemic and rising, and major outbreaks of chikungunya and Zika have recently occurred. However, there has been limited investigation of vector ecology in these rapidly expanding urban settings, and its association with seasonal patterns of arboviral transmission. To address this gap, this study aimed to assess the environmental drivers of Ae. aegypti ecology, infection rates and arboviral transmission within two major urban hotspots in Coastal Ecuador. This was accomplished through a series of field studies of vector ecology, laboratory analyses of arboviruses, and modelling investigations designed to identify environmental determinants of human exposure and infection incidence. The first chapter reviews what is known about the most important Aedes-borne viruses and their vectors in South America, with particular focus on Ecuador, vector control, and the global and regional disease burden. The second chapter presents results from a field study carried out in a urban neighbourhood of Quinindé, Ecuador, that evaluated a novel trapping method, the Mosquito Electrocuting Trap (MET), for direct estimation of human exposure to Ae. aegypti bites. The third chapter describes results of a 6-month field study aimed to characterize the environmental determinants of Ae. aegypti abundance and distribution, behaviour and arboviral infection rates within two cantons in Coastal Ecuador at the tail end of the 2016-17 Zika outbreak. The fourth chapter presents an analysis of seasonal and annual variation in dengue, chikungunya and Zika virus within these 2 cantons, and associations with climatic and entomological variables. The fifth chapter discusses the key results of each of the chapters and the implications of the findings towards an effective vector control in Ecuador and beyond the country. It was found that the MET was effective for measuring Ae. aegypti host-seeking behaviour, and generated representative estimates of their biting rate and activity time relative to the standard BG-sentinel trap (BGS). Analysis of Ae. aegypti ecology indicated that its abundance varied significantly between cantons, neighbourhoods within cantons associated with urbanization gradient, temporal timing of collection and past rainfall. Additionally, there was significant variation in Ae. aegypti resting behaviour (resting in or outside houses) between cantons. This demonstrates the existence of heterogeneity in Ae. aegypti population dynamics and behaviour between and within the study sites, which highlights the importance of localized surveillance to guide vector control. Likewise, arboviral incidence of dengue and chikungunya (as reported to the health system) also differed between the two study sites, being dengue 1.5 and chikungunya 2.5 times higher in Portoviejo than in Quinindé during the peaking week. The seasonal pattern of disease incidence varied among the three arboviruses, with a difference of 5 weeks between each of their peak of incidence. Intra-annual incidence was also found to be linked with climatic and entomological variables, with dengue and chikungunya incidence being positively associated with temperature and rainfall, while Zika incidence negatively associated with such climatic variables. Outdoor Aedes collections with Prokopack aspirators and BGS were positively related to dengue incidence, while indoor Prokopack aspirations were negatively associated with this variable. The interannual incidence of dengue differed between years analysed (2013-2018) with 2015 being the year with highest dengue incidence. Such findings highlight the importance of conducting focalized epidemiological surveillance on each site, but also differentiating between arboviruses, rather than assuming they all will follow dengue trends. Findings from this work have provided new entomological and epidemiological information to the study sites and despite the short period of study, fine spatial scale heterogeneity was detected in arbovirus transmission dynamics

The role of production risks in the conversion to more sustainable arable farming = [De rol van productierisico's in de omschakeling naar een meer duurzame akkerbouw]

The objective of the research described in this thesis was to determine the role of production risks in the conversion to more sustainable production systems of arable farming in The Netherlands. More specifically, the research goals were: (1) to specify the typical production risks that prevent farmers from changing to more sustainable farming, (2) to develop a method to quantify the size of these production risks, (3) to apply that method in order to quantify the risks involved in sustainable arable farming practices as compared to those involved in conventional practices, and (4) to assess farmers' behaviour when choosing from a set of sustainable and conventional farming practices. To achieve these objectives, descriptive research was done on the properties of the innovator (objective (1) ) and normative research was done on the properties of the innovation (objectives (2) and (3) ). Furthermore, an experimental analysis of adoption behaviour in a simulated, uncertain agro-ecological environment was conducted to integrate innovator -specific and innovation -specific properties (objective 4)

Statistical Inference for Propagation Processes on Complex Networks

Die Methoden der Netzwerktheorie erfreuen sich wachsender Beliebtheit, da sie die Darstellung von komplexen Systemen durch Netzwerke erlauben. Diese werden nur mit einer Menge von Knoten erfasst, die durch Kanten verbunden werden. Derzeit verfügbare Methoden beschränken sich hauptsächlich auf die deskriptive Analyse der Netzwerkstruktur. In der hier vorliegenden Arbeit werden verschiedene Ansätze für die Inferenz über Prozessen in komplexen Netzwerken vorgestellt. Diese Prozesse beeinflussen messbare Größen in Netzwerkknoten und werden durch eine Menge von Zufallszahlen beschrieben. Alle vorgestellten Methoden sind durch praktische Anwendungen motiviert, wie die Übertragung von Lebensmittelinfektionen, die Verbreitung von Zugverspätungen, oder auch die Regulierung von genetischen Effekten. Zunächst wird ein allgemeines dynamisches Metapopulationsmodell für die Verbreitung von Lebensmittelinfektionen vorgestellt, welches die lokalen Infektionsdynamiken mit den netzwerkbasierten Transportwegen von kontaminierten Lebensmitteln zusammenführt. Dieses Modell ermöglicht die effiziente Simulationen verschiedener realistischer Lebensmittelinfektionsepidemien. Zweitens wird ein explorativer Ansatz zur Ursprungsbestimmung von Verbreitungsprozessen entwickelt. Auf Grundlage einer netzwerkbasierten Redefinition der geodätischen Distanz können komplexe Verbreitungsmuster in ein systematisches, kreisrundes Ausbreitungsschema projiziert werden. Dies gilt genau dann, wenn der Ursprungsnetzwerkknoten als Bezugspunkt gewählt wird. Die Methode wird erfolgreich auf den EHEC/HUS Epidemie 2011 in Deutschland angewandt. Die Ergebnisse legen nahe, dass die Methode die aufwändigen Standarduntersuchungen bei Lebensmittelinfektionsepidemien sinnvoll ergänzen kann. Zudem kann dieser explorative Ansatz zur Identifikation von Ursprungsverspätungen in Transportnetzwerken angewandt werden. Die Ergebnisse von umfangreichen Simulationsstudien mit verschiedenstensten Übertragungsmechanismen lassen auf eine allgemeine Anwendbarkeit des Ansatzes bei der Ursprungsbestimmung von Verbreitungsprozessen in vielfältigen Bereichen hoffen. Schließlich wird gezeigt, dass kernelbasierte Methoden eine Alternative für die statistische Analyse von Prozessen in Netzwerken darstellen können. Es wurde ein netzwerkbasierter Kern für den logistischen Kernel Machine Test entwickelt, welcher die nahtlose Integration von biologischem Wissen in die Analyse von Daten aus genomweiten Assoziationsstudien erlaubt. Die Methode wird erfolgreich bei der Analyse genetischer Ursachen für rheumatische Arthritis und Lungenkrebs getestet. Zusammenfassend machen die Ergebnisse der vorgestellten Methoden deutlich, dass die Netzwerk-theoretische Analyse von Verbreitungsprozessen einen wesentlichen Beitrag zur Beantwortung verschiedenster Fragestellungen in unterschiedlichen Anwendungen liefern kann

Dynamic processes on networks and higher-order structures

Higher-order interactions are increasingly recognized as a critical aspect in the modeling of complex systems. Higher-order networks provide a framework for studying the relationship between the structure of higher-order interactions and the function of the complex system. However, little is known about how higher-order interactions affect dynamic processes. In this thesis, we develop general frameworks of percolation aiming at understanding the interplay between higher-order network structures and the critical properties of dynamics. We reveal that degree correlations strongly affect the percolation threshold on higher-order networks and interestingly, the effect of correlations is different on ordinary percolation and higher-order percolation. We further elucidate the mechanisms responsible for the emergence of discontinuous transitions on higher-order networks. Moreover, we show that triadic regulatory interaction, as a general type of higher-order interaction found widely in nature, can turn percolation into a fully-fledged dynamic process that exhibits period doubling and a route to chaos. As an important example of dynamic processes, we further investigate the role of network topology on epidemic spreading. We show that higher-order interactions can induce a non-linear infection kernel in a pandemic, which results in a discontinuous phase transition, hysteresis, and superexponential spreading. Finally, we propose an epidemic model to evaluate the role of automated contact-and-tracing with mobile apps as a new containment measure to mitigate a pandemic. We reveal the non-linear effect on the reduction of the incidence provided by a certain fraction of app adoption in the population and we propose the optimal strategy to mitigate the pandemic with limited resources. Altogether, the thesis provides new insights into the interplay between the topology of higher-order networks and their dynamics. The results obtained may shed light on the research in other areas of interest such as brain functions and epidemic spreading