A parallel approach to social network generation and agent-based epidemic simulation

Understanding the dynamics of disease spread is essential in contexts such as estimating load on medical services, as well as risk assessment and interven- tion policies against large-scale epidemic outbreaks. However, most of the information is available after the outbreak itself, and preemptive assessment is far from trivial. Here, we report on an agent-based model developed to investigate such epidemic events in a stylised urban environment. For most diseases, infection of a new individual may occur from casual contact in crowds as well as from repeated interactions with social partners such as work colleagues or family members. Our model therefore accounts for these two phenomena. Given the scale of the system, efficient parallel computing is required. In this presentation, we focus on aspects related to paralllelisation for large networks generation and massively multi-agent simulations.

Impact of Mobility Constraints on Epidemic Broadcast in DTNs

In this paper, we investigate the effect of mobility constraints on epidemic broad-cast mechanisms in DTNs (Delay-Tolerant Networks). Major factors affecting epidemic broadcast performances are its forwarding algorithm and node mobility. The impact of forwarding algorithm and node mobility on epidemic broadcast mechanisms has been actively studied in the literature, but those studies use generally unconstrained mobility models. The objective of this paper is therefore to quantitatively investigate the effect of mobility constraints on epidemic broadcast mechanisms. We evaluate the performances of P-BCAST (PUSH-based BroadCast), SA-BCAST (Self-Adaptive BroadCast), and HP-BCAST (History-based P-BCAST) with a random waypoint mobility model with mobility constraints.

Impact of mobility constraints on epidemic broadcast mechanisms in delay-tolerant networks

In this paper, we investigate the effect of mobility constraints on epidemic broadcast mechanisms in DTNs (Delay-Tolerant Networks). Major factors affecting epidemic broadcast performances are its forwarding algorithm and node mobility. The impact of forwarding algorithm and node mobility on epidemic broadcast mechanisms has been actively studied in the literature, but those studies generally use unconstrained mobility models. The objective of this paper is therefore to quantitatively investigate the effect of mobility constraints on epidemic broadcast mechanisms. We evaluate the performances of three classes of epidemic broadcast mechanisms - P-BCAST (PUSH-based BroadCast), SA-BCAST (Self-Adaptive BroadCast), and HP-BCAST (History-based P-BCAST) - with a random waypoint mobility model with mobility constraints. Our finding includes that the existence of mobility constraints significantly improves the reach ability and dissemination speed of epidemic broadcast mechanisms while degrading their efficiency.

Developing an epidemic forecasting model for Influenza A in Brisbane, Australia, based on climate and Hong Kong Influenza A surveillance data

Influenza is associated with substantial disease burden [ 1]. Development of a climate-based early warning system for in fluenza epidemics has been recommended given the signi fi - cant association between climate variability and influenza activity [2]. Brisbane is a subtropical city in Australia and offers free in fluenza vaccines to residents aged ≥65 years considering their high risks in developing life-threatening complications, especially for in fluenza A predominant seasons. Hong Kong is an international subtropical city in Eastern Asia and plays a crucial role in global infectious diseases transmission dynamics via the international air transportation network [3, 4]. We hypothesized that Hong Kong in fluenza surveillance data could provide a signal for in fluenza epidemics in Brisbane [ 4]. This study aims to develop an epidemic forecasting model for influenza A in Brisbane elders, by combining climate variability and Hong Kong in fluenza A surveillance data. Weekly numbers of laboratoryconfirmed influenza A positive isolates for people aged ≥65 years from 2004 to 2009 were obtained for Brisbane from Queensland Health, Australia, and for Hong Kong from Queen Mary Hospital (QMH). QMH is the largest public hospital located in Hong Kong Island, and in fluenza surveillance data from this hospital have been demonstrated to be representative for influenza circulation in the entirety of Hong Kong [ 5]. The Brisbane in fluenza A epidemics occurred during July –September, whereas the Hong Kong in fluenza A epidemics occurred during February –March and May –August.

Molecular Characterization of Viruses Causing the Cassava Brown Streak Disease Epidemic in Eastern Africa

Cassava brown streak disease (CBSD) was described for the first time in Tanganyika (now Tanzania) about seven decades ago. Tanganyika (now Tanzania) about seven decades ago. It was endemic in the lowland areas of East Africa and inland parts of Malawi and caused by Cassava brown streak virus (CBSV; genus Ipomovirus; Potyviridae). However, in 1990s CBSD was observed at high altitude areas in Uganda. The causes for spread to new locations were not known.The present work was thus initiated to generate information on genetic variability, clarify the taxonomy of the virus or viruses associated with CBSD in Eastern Africa as well as to understand the evolutionary forces acting on their genes. It also sought to develop a molecular based diagnostic tool for detection of CBSD-associated virus isolates. Comparison of the CP-encoding sequences of CBSD-associated virus isolates collected from Uganda and north-western Tanzania in 2007 and the partial sequences available in Genbank revealed occurrence of two genetically distinct groups of isolates. Two isolates were selected to represent the two groups. The complete genomes of isolates MLB3 (TZ:Mlb3:07) and Kor6 (TZ:Kor6:08) obtained from North-Western (Kagera) and North-Eastern (Tanga) Tanzania, respectively, were sequenced. The genomes were 9069 and 8995 nucleotides (nt), respectively. They translated into polyproteins that were predicted to yield ten mature proteins after cleavage. Nine proteins were typical in the family Potyviridae, namely P1, P3, 6K1, CI, 6K2, VPg, NIa-Pro, NIb and CP, but the viruses did not contain HC-Pro. Interestingly, genomes of both isolates contained a Maf/HAM1-like sequence (HAM1h; 678 nucleotides, 25 kDa) recombined between the NIb and CP domains in the 3’-proximal part of the genomes. HAM1h was also identified in Euphorbia ringspot virus (EuRSV) whose sequence was in GenBank. The HAM1 gene is widely spread in both prokaryotes and eukaryotes. In yeast (Saccharomyces cerevisiae) it is known to be a nucleoside triphosphate (NTP) pyrophosphatase. Novel information was obtained on the structural variation at the N-termini of polyproteins of viruses in the genus Ipomovirus. Cucumber vein yellowing virus (CVYV) and Squash vein yellowing virus (SqVYV) contain a duplicated P1 (P1a and P1b) but lack the HC-Pro. On the other hand, Sweet potato mild mottle virus (SPMMV), has a single but large P1 and has HC-Pro. Both virus isolates (TZ:Mlb3:07 & TZ:Kor6:08) characterized in this study contained a single P1 and lacked the HC-Pro which indicates unique evolution in the family Potyviridae. Comparison of 12 complete genomes of CBSD-associated viruses which included two genomes characterized in this study, revealed genetic identity of 69.0–70.3% (nt) and amino acid (aa) identities of 73.6–74.4% at polyprotein level. Comparison was also made among 68 complete CP sequences, which indicated 69.0-70.3 and 73.6-74.4 % identity at nt and aa levels, respectively. The genetic variation was large enough for dermacation of CBSD-associated virus isolates into two distinct species. The name CBSV was retained for isolates that were related to CBSV isolates available in database whereas the new virus described for the first time in this study was named Ugandan cassava brown streak virus (UCBSV) by the International Committee on Virus Taxonomy (ICTV). The isolates TZ:Mlb3:07 and TZ:Kor6:08 belong to UCBSV and CBSV, respectively. The isolates of CBSV and UCBSV were 79.3-95.5% and 86.3-99.3 % identitical at nt level, respectively, suggesting more variation amongst CBSV isolates. The main sources of variation in plant viruses are mutations and recombination. Signals for recombination events were detected in 50% of isolates of each virus. Recombination events were detected in coding and non-coding (3’-UTR) sequences except in the 5’UTR and P3. There was no evidence for recombination between isolates of CBSV and UCBSV. The non-synonomous (dN) to synonomous (dS) nucleotide substitution ratio (ω) for the HAM1h and CP domains of both viruses were ≤ 0.184 suggesting that most sites of these proteins were evolving under strong purifying selection. However, there were individual amino acid sites that were submitted to adaptive evolution. For instance, adaptive evolution was detected in the HAM1h of UCBSV (n=15) where 12 aa sites were under positive selection (P< 0.05) but not in CBSV (n=12). The CP of CBSV (n=23) contained 12 aa sites (p<0.01) while only 5 aa sites in the CP gene of UCBSV were predicted to be submitted to positive selection pressure (p<0.01). The advantages offered by the aa sites under positive selection could not be established but occurrence of such sites in the terminal ends of UCBSV-HAMIh, for example, was interpreted as a requirement for proteolysis during polyprotein processing. Two different primer pairs that simultaneously detect UCBSV and CBSV isolates were developed in this study. They were used successfully to study distribution of CBSV, UCBSV and their mixed infections in Tanzania and Uganda. It was established that the two viruses co-infect cassava and that incidences of co-infection could be as high as 50% around Lake Victoria on the Tanzanian side. Furthermore, it was revealed for the first time that both UCBSV and CBSV were widely distributed in Eastern Africa. The primer pair was also used to confirm infection in a close relative of cassava, Manihot glaziovii (Müller Arg.) with CBSV. DNA barcoding of M. glaziovii was done by sequencing the matK gene. Two out of seven M. glaziovii from the coastal areas of Korogwe and Kibaha in north eastern Tanzania were shown to be infected by CBSV but not UCBSV isolates. Detection in M. glaziovii has an implication in control and management of CBSD as it is likely to serve as virus reservoir. This study has contributed to the understanding of evolution of CBSV and UCBSV, which cause CBSD epidemic in Eastern Africa. The detection tools developed in this work will be useful in plant breeding, verification of the phytosanitary status of materials in regional and international movement of germplasm, and in all diagnostic activities related to management of CBSD. Whereas there are still many issues to be resolved such as the function and biological significance of HAM1h and its origin, this work has laid a foundation upon which the studies on these aspects can be based.

Accelerating Information Diffusion in Social Networks Under the Susceptible-Infected-Susceptible Epidemic Model

Standard Susceptible-Infected-Susceptible (SIS) epidemic models assume that a message spreads from the infected to the susceptible nodes due to only susceptible-infected epidemic contact. We modify the standard SIS epidemic model to include direct recruitment of susceptible individuals to the infected class at a constant rate (independent of epidemic contacts), to accelerate information spreading in a social network. Such recruitment can be carried out by placing advertisements in the media. We provide a closed form analytical solution for system evolution in the proposed model and use it to study campaigning in two different scenarios. In the first, the net cost function is a linear combination of the reward due to extent of information diffusion and the cost due to application of control. In the second, the campaign budget is fixed. Results reveal the effectiveness of the proposed system in accelerating and improving the extent of information diffusion. Our work is useful for devising effective strategies for product marketing and political/social-awareness/crowd-funding campaigns that target individuals in a social network.

An observer-based vaccination control law for an SEIR epidemic model based on feedback linearization techniques for nonlinear systems

This paper presents a vaccination strategy for fighting against the propagation of epidemic diseases. The disease propagation is described by an SEIR (susceptible plus infected plus infectious plus removed populations) epidemic model. The model takes into account the total population amounts as a refrain for the illness transmission since its increase makes the contacts among susceptible and infected more difficult. The vaccination strategy is based on a continuous-time nonlinear control law synthesised via an exact feedback input-output linearization approach. An observer is incorporated into the control scheme to provide online estimates for the susceptible and infected populations in the case when their values are not available from online measurement but they are necessary to implement the control law. The vaccination control is generated based on the information provided by the observer. The control objective is to asymptotically eradicate the infection from the population so that the removed-by-immunity population asymptotically tracks the whole one without precise knowledge of the partial populations. The model positivity, the eradication of the infection under feedback vaccination laws and the stability properties as well as the asymptotic convergence of the estimation errors to zero as time tends to infinity are investigated.

Random propagation in complex systems : nonlinear matrix recursions and epidemic spread

This dissertation studies long-term behavior of random Riccati recursions and mathematical epidemic model. Riccati recursions are derived from Kalman filtering. The error covariance matrix of Kalman filtering satisfies Riccati recursions. Convergence condition of time-invariant Riccati recursions are well-studied by researchers. We focus on time-varying case, and assume that regressor matrix is random and identical and independently distributed according to given distribution whose probability distribution function is continuous, supported on whole space, and decaying faster than any polynomial. We study the geometric convergence of the probability distribution. We also study the global dynamics of the epidemic spread over complex networks for various models. For instance, in the discrete-time Markov chain model, each node is either healthy or infected at any given time. In this setting, the number of the state increases exponentially as the size of the network increases. The Markov chain has a unique stationary distribution where all the nodes are healthy with probability 1. Since the probability distribution of Markov chain defined on finite state converges to the stationary distribution, this Markov chain model concludes that epidemic disease dies out after long enough time. To analyze the Markov chain model, we study nonlinear epidemic model whose state at any given time is the vector obtained from the marginal probability of infection of each node in the network at that time. Convergence to the origin in the epidemic map implies the extinction of epidemics. The nonlinear model is upper-bounded by linearizing the model at the origin. As a result, the origin is the globally stable unique fixed point of the nonlinear model if the linear upper bound is stable. The nonlinear model has a second fixed point when the linear upper bound is unstable. We work on stability analysis of the second fixed point for both discrete-time and continuous-time models. Returning back to the Markov chain model, we claim that the stability of linear upper bound for nonlinear model is strongly related with the extinction time of the Markov chain. We show that stable linear upper bound is sufficient condition of fast extinction and the probability of survival is bounded by nonlinear epidemic map.

Robust Sliding Control of SEIR Epidemic Models

This paper is aimed at designing a robust vaccination strategy capable of eradicating an infectious disease from a population regardless of the potential uncertainty in the parameters defining the disease. For this purpose, a control theoretic approach based on a sliding-mode control law is used. Initially, the controller is designed assuming certain knowledge of an upper-bound of the uncertainty signal. Afterwards, this condition is removed while an adaptive sliding control system is designed. The closed-loop properties are proved mathematically in the nonadaptive and adaptive cases. Furthermore, the usual sign function appearing in the sliding-mode control is substituted by the saturation function in order to prevent chattering. In addition, the properties achieved by the closed-loop system under this variation are also stated and proved analytically. The closed-loop system is able to attain the control objective regardless of the parametric uncertainties of the model and the lack of a priori knowledge on the system.

Stability analysis and observer design for discrete-time SEIR epidemic models

This paper applies Micken's discretization method to obtain a discrete-time SEIR epidemic model. The positivity of the model along with the existence and stability of equilibrium points is discussed for the discrete-time case. Afterwards, the design of a state observer for this discrete-time SEIR epidemic model is tackled. The analysis of the model along with the observer design is faced in an implicit way instead of obtaining first an explicit formulation of the system which is the novelty of the presented approach. Moreover, some sufficient conditions to ensure the asymptotic stability of the observer are provided in terms of a matrix inequality that can be cast in the form of a LMI. The feasibility of the matrix inequality is proved, while some simulation examples show the operation and usefulness of the observer.

On the Stability and Equilibrium Points of Multistaged SI (n) R Epidemic Models

This paper relies on the concept of next generation matrix defined ad hoc for a new proposed extended SEIR model referred to as SI(n)R-model to study its stability. The model includes n successive stages of infectious subpopulations, each one acting at the exposed subpopulation of the next infectious stage in a cascade global disposal where each infectious population acts as the exposed subpopulation of the next infectious stage. The model also has internal delays which characterize the time intervals of the coupling of the susceptible dynamics with the infectious populations of the various cascade infectious stages. Since the susceptible subpopulation is common, and then unique, to all the infectious stages, its coupled dynamic action on each of those stages is modeled with an increasing delay as the infectious stage index increases from 1 to n. The physical interpretation of the model is that the dynamics of the disease exhibits different stages in which the infectivity and the mortality rates vary as the individual numbers go through the process of recovery, each stage with a characteristic average time.

Molecular epidemiology of the heterosexual HIV-1 transmission in Kunming, Yunnan Province of China suggests origin from the local IDU epidemic

Molecular epidemiological investigation was conducted among injecting drug users (IDUs) (n = 11) and heterosexuals (n = 15) in Kunming, Yunnan Province of China. HIV-1 genotypes were determined based on the nucleotide sequences of 2.6-kb gag-RT region. The distribution of genotypes among IDUs was as follows: CRF07_BC (5/11) and CRF08_BC (5/11); subtype B' (1/11). Similarly, a majority of Kunming heterosexuals (14/15) were infected with CRF07_BC (4/15), CRF08_BC (6/15), or subtype B' (4/15), known to predominate among IDUs in China. This contrasts with trends in the coastal regions of China and surrounding southeastern Asian countries, where CRF01_AE predominates among heterosexuals. The heterosexual HIV-1 epidemic in Kunming thus appears to derive from the local IDU epidemic. Of note, subtype B' was the most prevalent strain among heterosexuals before 1997, while CRF07_BC and CRF08_BC became predominant in 2002, indicating a transition of HIV-1 genotype distribution between the early and the more recent samples from Kunming heterosexuals.