Inside UMaine, vol. 2, no. 4

Inside UMaine was the employee newsletter issued starting in 2005. The newsletter was published once each month during the academic year. The intent was to complement the university\u27s other communication vehicles, including the UMaine Today magazine, UMaine Today Online and various other online Information Services, such as the university\u27s Web-based calendar. The newsletter took over where the Maine Perspective left off to promote professional achievement and stories about campus events and advancements

Mathematical modelling of Mosquito Dispersal for Malaria\ud Vector Control.

In malaria endemic regions, dispersal of mosquitoes from one location to another searching for resources for their survival and reproduction is a fundamental biological process that operates at multiple temporal and spatial scales. This dispersal behaviour is an important factor that causes uneven distribution of malaria vectors causing heterogeneous transmission. Although mosquito dependence in a heterogeneous environment has several implications for malaria vector control and in public health in general, its inclusion in mathematical models of malaria transmission and control has received limited attention. Most models of malaria transmission and control explain relationships between the number of mosquitoes and malaria transmission in humans while assuming enclosed systems of mosquitoes in which spatial dynamics and movements are not taken into account. These models have limited ability to assess and quantify the distribution of risks and interventions at local scales. Therefore, in order to overcome this limitation, mathematical models that consider the interaction between dispersal behaviour, population dynamics, environmental heterogeneity, and age structures of the mosquito are needed for designing, planning, and management of the control strategies at local scales. Advances in malaria modelling have recently begun to incorporate spatial heterogeneity and highlight the need for more spatial explicit models that include all the vital components of ecological interactions. In response to this need, this thesis develops a spatial mathematical model that captures mosquito dispersal and includes all of the above characteristics to achieve a broader and deeper understanding of mosquito foraging behaviour, population dynamics, and its interactions with environmental heterogeneity, distribution of malaria risk, and vector control interventions. The model is applied to assess the impact of dispersal and heterogeneous distribution of mosquito resources on the spatial distribution, dynamics, and persistence of mosquito populations, to estimate the distance travelled by mosquitoes, and to evaluate and assess the impact of spatial distribution of vector control interventions on effectiveness of interventions under mosquitoes' natural dispersal behaviour. Chapter 2 develops a spatial mathematical model of mosquito dispersal in heterogeneous environments with a framework that is simple to allow investigation of aspects that affects malaria transmission. The model incorporates age distribution in form of the aquatic and adult stages of the mosquito life cycle and further divides the adult mosquito population into three stages of the mosquitoes searching for hosts, those resting, and those searching for oviposition sites. These three adult stages provide an opportunity to study the life style of the adult mosquito, and also offer a direct opportunity to assess the impact of interventions targeting different adult states such as insecticide treated bednets (ITNs), indoor residual spraying (IRS), and spatial repellents that reduce contacts between host seeking mosquitoes and human hosts. The spatial characteristics of the model are based on discretization of space into discrete patches. Host and oviposition site searching mosquitoes disperse to the nearest neighbours across the spatial platform where hosts and breeding sites are distributed. In the same Chapter, the model is applied to investigate the effect of heterogeneous distribution of resources used by mosquitoes, estimate the dispersal distance, and to assess the impact of spatial repellents on the dispersal distance. Results revealed that due to dispersal, the distribution of mosquitoes highly depend on the distribution of hosts and breeding sites and the random distribution of spatial repellents reduces the distance travelled by mosquitoes; offering a promising vector control strategy for malaria. In addition, analysis indicated that when only a single patch is considered, and movement ignored, the recruitment parameter and parameters related to the larval and host seeking stages of the mosquito strongly determine mosquito population persistence and extinction. Chapter 3 extends the model developed in Chapter 2 to include vector control interventions. As vector control intervention deployment plans need to consider the spatial distribution of intervention packages, the model extension developed in this chapter is used to examine the effect of spatial arrangement of vector control interventions on their effectiveness. Application of the model to IRS, larvicide, and ITNs showed that randomly distributing these interventions will in general be more effective than clustering them on side of an area. Mosquito dispersal and the different patterns of heterogeneity have different effects on population distribution and dynamics of mosquitoes, and thus, that of malaria. Models that incorporate dispersal when integrated with environmental heterogeneity allow predictions to capture ecological behaviour of mosquitoes, the main source of variations in malaria risk at local spatial scales, providing information needed for determining risk areas for malaria vector control purposes

Current Perspectives on Viral Disease Outbreaks

The COVID-19 pandemic has reminded the world that infectious diseases are still important. The last 40 years have experienced the emergence of new or resurging viral diseases such as AIDS, ebola, MERS, SARS, Zika, and others. These diseases display diverse epidemiologies ranging from sexual transmission to vector-borne transmission (or both, in the case of Zika). This book provides an overview of recent developments in the detection, monitoring, treatment, and control of several viral diseases that have caused recent epidemics or pandemics

An Initial Framework Assessing the Safety of Complex Systems

Trabajo presentado en la Conference on Complex Systems, celebrada online del 7 al 11 de diciembre de 2020.Atmospheric blocking events, that is large-scale nearly stationary atmospheric pressure patterns, are often associated with extreme weather in the mid-latitudes, such as heat waves and cold spells which have significant consequences on ecosystems, human health and economy. The high impact of blocking events has motivated numerous studies. However, there is not yet a comprehensive theory explaining their onset, maintenance and decay and their numerical prediction remains a challenge. In recent years, a number of studies have successfully employed complex network descriptions of fluid transport to characterize dynamical patterns in geophysical flows. The aim of the current work is to investigate the potential of so called Lagrangian flow networks for the detection and perhaps forecasting of atmospheric blocking events. The network is constructed by associating nodes to regions of the atmosphere and establishing links based on the flux of material between these nodes during a given time interval. One can then use effective tools and metrics developed in the context of graph theory to explore the atmospheric flow properties. In particular, Ser-Giacomi et al. [1] showed how optimal paths in a Lagrangian flow network highlight distinctive circulation patterns associated with atmospheric blocking events. We extend these results by studying the behavior of selected network measures (such as degree, entropy and harmonic closeness centrality)at the onset of and during blocking situations, demonstrating their ability to trace the spatio-temporal characteristics of these events.This research was conducted as part of the CAFE (Climate Advanced Forecasting of sub-seasonal Extremes) Innovative Training Network which has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 813844

Topology Reconstruction of Dynamical Networks via Constrained Lyapunov Equations

The network structure (or topology) of a dynamical network is often unavailable or uncertain. Hence, we consider the problem of network reconstruction. Network reconstruction aims at inferring the topology of a dynamical network using measurements obtained from the network. In this technical note we define the notion of solvability of the network reconstruction problem. Subsequently, we provide necessary and sufficient conditions under which the network reconstruction problem is solvable. Finally, using constrained Lyapunov equations, we establish novel network reconstruction algorithms, applicable to general dynamical networks. We also provide specialized algorithms for specific network dynamics, such as the well-known consensus and adjacency dynamics.Comment: 8 page

Data bases and data base systems related to NASA's aerospace program. A bibliography with indexes

This bibliography lists 1778 reports, articles, and other documents introduced into the NASA scientific and technical information system, 1975 through 1980