Epidemic Behavior Research Articles

Modeling and Analysis of Worm Propagation in Wireless Sensor Networks

The wireless sensor networks (WSNs) have imminent constrains that makes security a crucial issue. Weak defense capability makes WSN a soft target against worm attacks. A single compromised node can spread the worm via communication in the entire network. In this paper, we propose a mathematical model that studies the epidemic behavior of such digital worms. Furthermore, we study the effect of these worms with various communication radius and node distributed density. We investigate the proposed model using the stability theory of differential equations. Basic reproduction number is found that helps us to find the threshold values for communication radius and node density distribution. The proposed model is checked and validated through extensive simulation results. Finally, we compare our scheme with the existing schemes. Comparison analysis shows that the proposed model is efficient as it has the low rate of the infectious node for different communication radius.

Indicadores epidemiológicos de malaria en el área Ixil, Guatemala. 2012–2015

Se realizó un estudio observacional descriptivo para determinar algunas variables epidemiológicas de Malaria en el área Ixil de los años 2012-2015, de una muestra, de 171 pacientes que representaron el 100% de la ocurrencia; para el análisis y procesamiento se incluyó el cálculo de medidas descriptivas, para la estratificación del riesgo se hicieron cálculos matemáticos, ponderados con los objetivos de estratificar el riesgo de Malaria, determinar tendencia histórica de la enfermedad, distribuir los casos según variables socio demográficas, identificar tiempo transcurrido de los primeros síntomas al diagnóstico y precisar antecedentes de la enfermedad en los pacientes. Concluyendo en el comportamiento epidémico para los años 2012 y 2013, disminuyendo el riesgo de enfermar en los últimos años, con tendencia descendente, identificación de casos autóctonos, el municipio de Chajul el más afectado en los años 2012 y 2014 y Cotzal en el 2013 y 2015, todos los pacientes positivos a Plasmodium Vivax, se afectan edades jóvenes, sexo masculino, solo 12 casos con diagnóstico oportuno y 27 con antecedentes de la enfermedad.

Risk to Develop Type 2 Diabetes Mellitus according to FINDRISC tool in Guatemalan Physicians aged 40-60 years

Background: In Latin America 22.4 million people has abnormal tolerance to insulin, these ones could turn into diabetics if they do not change their lifestyles. Added to this, there are 15 million who present Diabetes Mellitus and this amount will increase to 20 million in 10 years. This epidemic behavior is caused by many factors in which stand out lifestyles, the population aging, and lack of prevention programs. Since 1994, physicians in Guatemala have demonstrated to have inadequate lifestyles in different researches, standing out sedentarism, overweight and obesity, and hypercaloric diets. Objective: To evaluate the risk of developing type 2 Diabetes Mellitus using the Finnish Diabetes Risk Score (FINDRISC) in Guatemalan doctors of three medical institutions in the months of June and July 2016. Methods: Cross-sectional study, where 176 doctors were interviewed using the FINDRISC. Participant’s body mass index and abdominal circumference were measured. Results: Mean age was 50 years, 63% (110) male; 55% (96) were sedentary, more than three quarters consumed fruits and vegetables daily, 22% (38) were hypertensive, 10% (17) had a history of impaired glucose and 61% family history of diabetes (108); 47% (82) were overweight and 31% (54) had some degree of obesity. Central obesity was present in 63% (111). There was a statistically significant relationship between age and risk of type 2 diabetes (OR: 3.4 p: 0.001) as well as a relationship between physical activity and abdominal circumference (OR: 2.84, p: 0.001). Out of the total population, 80% (141) of doctors were in some degree of risk, from these, 53% with slightly elevated, 29% moderate, 16% with high and 2% very high risk. Conclusions: Eight out of ten doctors studied were at risk of developing type 2 diabetes over a period of ten years. There is a relationship between: age and risk of disease, as well as between physical activity and abdominal circumference.

The relationships between message passing, pairwise, Kermack\u2013McKendrick and stochastic SIR epidemic models

We consider a very general stochastic model for an SIR epidemic on a network which allows an individual’s infectious period, and the time it takes to contact each of its neighbours after becoming infected, to be correlated. We write down the message passing system of equations for this model and prove, for the first time, that it has a unique feasible solution. We also generalise an earlier result by proving that this solution provides a rigorous upper bound for the expected epidemic size (cumulative number of infection events) at any fixed time t>0. We specialise these results to a homogeneous special case where the graph (network) is symmetric. The message passing system here reduces to just four equations. We prove that cycles in the network inhibit the spread of infection, and derive important epidemiological results concerning the final epidemic size and threshold behaviour for a major outbreak. For Poisson contact processes, this message passing system is equivalent to a non-Markovian pair approximation model, which we show has well-known pairwise models as special cases. We show further that a sequence of message passing systems, starting with the homogeneous one just described, converges to the deterministic Kermack–McKendrick equations for this stochastic model. For Poisson contact and recovery, we show that this convergence is monotone, from which it follows that the message passing system (and hence also the pairwise model) here provides a better approximation to the expected epidemic size at time t>0 than the Kermack–McKendrick model.

180-Nucleotide Duplication in the G Gene of Human metapneumovirus A2b Subgroup Strains Circulating in Yokohama City, Japan, since 2014.

Human metapneumovirus (HMPV), a member of the family Paramyxoviridae, was first isolated in 2001. Seroepidemiological studies have shown that HMPV has been a major etiological agent of acute respiratory infections in humans for more than 50 years. Molecular epidemiological, genetic, and antigenetic evolutionary studies of HMPV will strengthen our understanding of the epidemic behavior of the virus and provide valuable insight for the control of HMPV and the development of vaccines and antiviral drugs against HMPV infection. In this study, the nucleotide sequence of and genetic variations in the G gene were analyzed in HMPV strains prevalent in Yokohama City, in the Kanto area, Japan, between January 2013 and June 2016. As a part of the National Epidemiological Surveillance of Infectious Diseases, Japan, 1308 clinical specimens (throat swabs, nasal swabs, nasal secretions, and nasal aspirate fluids) collected at 24 hospitals or clinics in Yokohama City were screened for 15 major respiratory viruses with a multiplex reverse transcription–PCR assay. HMPV was detected in 91 specimens, accounting for 7.0% of the total specimens, and the nucleotide sequences of the G genes of 84 HMPV strains were determined. Among these 84 strains, 6, 43, 10, and 25 strains were classified into subgroups A2a, A2b, B1, and B2, respectively. Approximately half the HMPV A2b subgroup strains detected since 2014 had a 180-nucleotide duplication (180nt-dup) in the G gene and clustered on a phylogenic tree with four classical 180nt-dup-lacking HMPV A2b strains prevalent between 2014 and 2015. The 180nt-dup causes a 60-amino-acid duplication (60aa-dup) in the G protein, creating 23–25 additional potential acceptor sites for O-linked sugars. Our data suggest that 180nt-dup occurred between 2011 and 2013 and that HMPV A2b strains with 180nt-dup (A2b180nt-dup HMPV) became major epidemic strains within 3 years. The detailed mechanism by which the A2b180nt-dup HMPV strains gained an advantage that allowed their efficient spread in the community and the effects of 60aa-dup on HMPV virulence must be clarified.

Estimating enhanced prevaccination measles transmission hotspots in the context of cross-scale dynamics

A key question in clarifying human–environment interactions is how dynamic complexity develops across integrative scales from molecular to population and global levels. Apart from its public health importance, measles is an excellent test bed for such an analysis. Simple mechanistic models have successfully illuminated measles dynamics at the city and country levels, revealing seasonal forcing of transmission as a major driver of long-term epidemic behavior. Seasonal forcing ties closely to patterns of school aggregation at the individual and community levels, but there are few explicit estimates of school transmission due to the relative lack of epidemic data at this scale. Here, we use data from a 1904 measles outbreak in schools in Woolwich, London, coupled with a stochastic Susceptible-Infected-Recovered model to analyze measles incidence data. Our results indicate that transmission within schools and age classes is higher than previous population-level serological data would suggest. This analysis sheds quantitative light on the role of school-aged children in measles cross-scale dynamics, as we illustrate with references to the contemporary vaccination landscape.

Two-mode network modeling and analysis of dengue epidemic behavior in Gombak, Malaysia

Many complex systems in the form of network structures have been a great focus of research in the last decade. In fact, various domains have been modeled and analyzed as complex networks ranging from biological, technological, transportation, social and many others. The phenomenon of distribution of many dengue cases has been a great concern in Malaysia in recent years. Therefore, in this work we formalize and analyze the dengue spreading phenomenon from the perspective of complex network and model the dataset of dengue affected cases in Gombak, Selangor (Malaysia) into two-mode network. By using real dataset of dengue cases in Malaysian states obtained from the Malaysian Health Ministry, we observe this network with global (Closeness, Betweenness and Short path-length) and local (Degree and Clustering coefficient) structure perspectives. We further formalize it by projecting from two-mode to one-mode network using three methods of network projection. From the network analysis, we found that there are few localities that were affected again and again throughout the year. Further, few localities have high number of dengue cases as compared to others. From the global structures perspective, very few localities have shown closeness to all other localities and therefore easing the route for the propagation of dengue virus that has the highest weight in terms of number of dengue cases.

Development of a DNA aptamer that binds specifically to group A Streptococcus serotype M3.

Group A streptococcus (GAS) is an important Gram-positive pathogen that causes various human diseases ranging from peripheral lesions to invasive infections. The M protein is one of the main virulence factors present on the cell surface and is associated with invasive GAS infections. Compared with other M types, serotype M3 has a predominant role in lethal infections and demonstrates epidemic behaviors, including streptococcal toxic shock syndrome, bacteremia, and necrotizing fasciitis. Traditional methods for M typing are time-consuming, tedious, contradictory, and generally restricted to reference laboratories. Therefore, development of a new M-typing technique is needed. Aptamers with the ability to detect their target with a high degree of accuracy and specificity can be ideal candidates for specific M-typing of Streptococcus pyogenes. In this study DNA aptamers with a high binding affinity towards S. pyogenes serotype M3 were selected through 12 iterative rounds of the Systematic Evolution of Ligands by EXponential (SELEX) enrichment procedure using live cells as a target. We monitored the progress of the SELEX procedure by flow cytometry analysis. Of several aptamer sequences analyzed, 12L18A showed the highest binding efficiency towards S. pyogenes type M3, with an apparent dissociation constant (Kd) of 7.47 ± 1.72 pmol/L being the lowest. Therefore the isolated aptamer can be used in any tool, such as a biosensor, for the detection of S. pyogenes and can be used in the development of a novel M-typing system.

Epidemic spreading on dual-structure networks with mobile agents

Abstract The rapid development of modern society continually transforms the social structure which leads to an increasingly distinct dual structure of higher population density in urban areas and lower density in rural areas. Such structure may induce distinctive spreading behavior of epidemics which does not happen in a single type structure. In this paper, we study the epidemic spreading of mobile agents on dual structure networks based on SIRS model. First, beyond the well known epidemic threshold for generic epidemic model that when the infection rate is below the threshold a pertinent infectious disease will die out, we find the other epidemic threshold which appears when the infection rate of a disease is relatively high. This feature of two thresholds for the SIRS model may lead to the elimination of infectious disease when social network has either high population density or low population density. Interestingly, however, we find that when a high density area is connected to a low density may cause persistent spreading of the infectious disease, even though the same disease will die out when it spreads in each single area. This phenomenon indicates the critical role of the connection between the two areas which could radically change the behavior of spreading dynamics. Our findings, therefore, provide new understanding of epidemiology pertinent to the characteristic modern social structure and have potential to develop controlling strategies accordingly.

Epidemic History of Hepatitis C Virus among Patients with Inherited Bleeding Disorders in Iran.

The high rate of hepatitis C virus (HCV) infection among transfusion related risk groups such as patients with inherited bleeding disorders highlighting the investigation on prevalent subtypes and their epidemic history among this group. In this study, 166 new HCV NS5B sequences isolated from patients with inherited bleeding disorders together with 29 sequences related to hemophiliacs obtained from a previous study on diversity of HCV in Iran were analyzed. The most prevalent subtype was 1a (65%), followed by 3a (18.7%),1b (14.5%),4(1.2%) and 2k (0.6%). Subtypes 1a and 3a showed exponential expansion during the 20th century. Whereas expansion of 3a started around 20 years earlier than 1a among the study patients, the epidemic growth of 1a revealed a delay of about 10 years compared with that found for this subtype in developed countries. Our results supported the view that the spread of 3a reached the plateau 10 years prior to the screening of blood donors for HCV. Rather, 1a reached the plateau when screening program was implemented. The differences observed in the epidemic behavior of HCV-1a and 3a may be associated with different transmission routes of two subtypes. Indeed, expansion of 1a was more commonly linked to blood transfusion, while 3a was more strongly associated to drug use and specially IDU after 1960. Our findings also showed HCV transmission through blood products has effectively been controlled from late 1990s. In conclusion, the implementation of strategies such as standard surveillance programs and subsiding antiviral treatments seems to be essential to both prevent new HCV infections and to decline the current and future HCV disease among Iranian patients with inherited bleeding disorders.

SIR model with local and global infective contacts: A deterministic approach and applications

An epidemic model with births and deaths is considered on a two-dimensional L×L lattice. Each individual can have global infective contacts according to the standard susceptible–infected–recovered (SIR) model rules or local infective contacts with their nearest neighbors. We propose a deterministic approach to this model and, for the parameters corresponding to pertussis and rubella in the prevaccine era, verify that there is a close agreement with the stochastic simulations when epidemic spread or endemic stationarity is considered. We also find that our approach captures the characteristic features of the dynamic behavior of the system after a sudden decrease in global contacts that may arise as a consequence of health care measures. By using the deterministic approach, we are able to characterize the exponential growth of the epidemic behavior and analyze the stability of the system at the stationary values. Since the deterministic approximation captures the essential features of the disease transmission dynamics of the stochastic model, it provides a useful tool for performing systematic studies as a function of the model parameters. We give an example of this potentiality by analyzing the likelihood of the endemic state to become extinct when the weight of the global contacts is drastically reduced.

Worm Propagation with Differential Infectivity under Quarantine Control Strategy

Malwares have sharp resemblance with the biological pathogens in terms of propagation. Biological pathogens spread from one living being to another in very short span of time. Similarly malwares also propagate rapidly from one host to another host and one network to another network, in order to spread infection in major scale. This spread can be epidemic if control strategies are not called in time. In order to timely intervene, study of epidemic behavior is very important. In this paper we develop SI1I2Q1Q2R1R2 model of worm propagation under quarantine control strategy. We have considered different infective, quarantined and recovered (or removed) group in our model. The motivation of such model came from the study of propagation dynamics of HIV. Our worm propagation and its quarantined based defense is based on stagedprogression (SP) hypothesis of HIV. We have studied in this paper the stability of worm free equilibrium condition and analyzed the epidemic state condition in terms of reproduction number. When reproduction number is greater than one the worm propagation become epidemic. If it is less than one then infection diminishes. Extensive analysis and simulation has been done to validate our system. Simulation result shows that effective quarantine strategy helps in controlling the epidemic outbreak of worms in networks.

MOSES: A Matlab-based open-source stochastic epidemic simulator.

This paper presents an open-source stochastic epidemic simulator. Discrete Time Markov Chain based simulator is implemented in Matlab. The simulator capable of simulating SEQIJR (susceptible, exposed, quarantined, infected, isolated and recovered) model can be reduced to simpler models by setting some of the parameters (transition probabilities) to zero. Similarly, it can be extended to more complicated models by editing the source code. It is designed to be used for testing different control algorithms to contain epidemics. The simulator is also designed to be compatible with a network based epidemic simulator and can be used in the network based scheme for the simulation of a node. Simulations show the capability of reproducing different epidemic model behaviors successfully in a computationally efficient manner.

Critical behavior in a stochastic model of vector mediated epidemics.

The extreme vulnerability of humans to new and old pathogens is constantly highlighted by unbound outbreaks of epidemics. This vulnerability is both direct, producing illness in humans (dengue, malaria), and also indirect, affecting its supplies (bird and swine flu, Pierce disease, and olive quick decline syndrome). In most cases, the pathogens responsible for an illness spread through vectors. In general, disease evolution may be an uncontrollable propagation or a transient outbreak with limited diffusion. This depends on the physiological parameters of hosts and vectors (susceptibility to the illness, virulence, chronicity of the disease, lifetime of the vectors, etc.). In this perspective and with these motivations, we analyzed a stochastic lattice model able to capture the critical behavior of such epidemics over a limited time horizon and with a finite amount of resources. The model exhibits a critical line of transition that separates spreading and non-spreading phases. The critical line is studied with new analytical methods and direct simulations. Critical exponents are found to be the same as those of dynamical percolation.

Epidemic behavior of the etiological agent of infectious coryza in layer chicken of Bangladesh with isolation, identification and pathogenicity study

The present study was selected as infectious coryza is one of the major problems affecting poultry industry in the developing country like Bangladesh and the reports regarding infectious coryza are yet not be documented considering epidemiological investigation, proper isolation, identification and pathogenicity study. The epidemic behavior of the etiological agent of this disease were studied based on age, sex, breed, spatial and temporal differences after collection of samples suspected to be infected with infectious coryza in layer chicken of Bangladesh. The incidence rate of infectious coryza from field cases were recorded as per information received from farmers by using a structured questionnaire and also clinical signs and symptoms. The disease was very high in laying hen (18.38%) in Sylhet and growing birds (7.25%) in Khulna in comparing with prelaying stage (2.07%) also in Sylhet region of Bangladesh. In this study no significant differences was observed as their location variation except Sylhet (9.2%) in comparison with other areas (Rangpur – 8.76%, Rajshahi -8.82%, Khulna - 8.83%, Dhaka – 8.72 and Chittagong - 8.65% respectively) of Bangladesh but significant differences was observed as their age group. However, the incidence rate of this disease was found to be very high during winter (8.77%) in compare with summer (0.42%) season. Moreover, during investigation a total of 122 samples were collected from different areas of Bangladesh for the period of March 2011 to February 2014. The higher rate of incidence of A. paragallinarum was found in Sylhet (66.66%) and lowest in Dhaka (43.75%). The association of A. paragallinarum with different seasons revealed that higher incidence rate was found in winter season (52.26%) in comparison with summer season (1.85%). The suspected positive isolates were subjected to experimental pathogenicity study in natural host for there – isolation of A. paragallinarum was done as per Kotch postulates.Asian J. Med. Biol. Res. March 2016, 2(1): 82-94

Epidemic spreading with time delay on complex networks

In this paper, we propose a susceptible-infected-susceptible (SIS) model on complex networks, small-world (WS) networks and scale-free (SF) networks, to study the epidemic spreading behavior with time delay which is added into the infected phase. Considering the uniform delay, the basic reproduction number R 0 on WS networks and $$\bar R_0$$ on SF networks are obtained respectively. On WS networks, if R 0 ≤ 1, there is a disease-free equilibrium and it is locally asymptotically stable; if R 0 > 1, there is an epidemic equilibrium and it is locally asymptotically stable. On SF networks, if $$\bar R_0 \leqslant 1$$ , there is a disease-free equilibrium; if $$\bar R_0 > 1$$ , there is an epidemic equilibrium. Finally, we carry out simulations to verify the conclusions and analyze the effect of the time delay τ, the effective rate λ, average connectivity 〈k〉 and the minimum connectivity m on the epidemic spreading.

Optimal vaccination strategies and rational behaviour in seasonal epidemics.

We consider a SIRS model with time dependent transmission rate. We assume time dependent vaccination which confers the same immunity as natural infection. We study two types of vaccination strategies: (i) optimal vaccination, in the sense that it minimizes the effort of vaccination in the set of vaccination strategies for which, for any sufficiently small perturbation of the disease free state, the number of infectious individuals is monotonically decreasing; (ii) Nash-equilibria strategies where all individuals simultaneously minimize the joint risk of vaccination versus the risk of the disease. The former case corresponds to an optimal solution for mandatory vaccinations, while the second corresponds to the equilibrium to be expected if vaccination is fully voluntary. We are able to show the existence of both optimal and Nash strategies in a general setting. In general, these strategies will not be functions but Radon measures. For specific forms of the transmission rate, we provide explicit formulas for the optimal and the Nash vaccination strategies.

Discrete-time moment closure models for epidemic spreading in populations of interacting individuals

Understanding the dynamics of spread of infectious diseases between individuals is essential for forecasting the evolution of an epidemic outbreak or for defining intervention policies. The problem is addressed by many approaches including stochastic and deterministic models formulated at diverse scales (individuals, populations) and different levels of detail. Here we consider discrete-time SIR (susceptible–infectious–removed) dynamics propagated on contact networks. We derive a novel set of ‘discrete-time moment equations’ for the probability of the system states at the level of individual nodes and pairs of nodes. These equations form a set which we close by introducing appropriate approximations of the joint probabilities appearing in them. For the example case of SIR processes, we formulate two types of model, one assuming statistical independence at the level of individuals and one at the level of pairs. From the pair-based model we then derive a model at the level of the population which captures the behavior of epidemics on homogeneous random networks. With respect to their continuous-time counterparts, the models include a larger number of possible transitions from one state to another and joint probabilities with a larger number of individuals. The approach is validated through numerical simulation over different network topologies.

Percolation Thresholds on Tree-Based Communities of Wireless Sensor Networks

Many efficient deployments of large-scale wireless sensor networks based on the tree-based community rise into view recently. Sensor nodes are severely resource constrained, and lack sophisticated defense mechanisms to fight virus attacks. Cyber viruses spread through node populations over the networks, and a number of results about the prevalence have been derived in recent years by exploiting epidemic behaviors and the percolation processes on networks. A network model based on the Cayley tree is proposed to depict the underlying tree-based architectures of the network and the community. The percolation thresholds are calculated and analyzed in two cases. Due to random links in the communities, the sensor virus extends drastically on the network. The analysis and evaluation shows that the percolation threshold keeps decreasing with the increase of the shortcut probability. There is the smallest percolation threshold in a random network, where the virus easily attacks the network from one side to another. The conclusions can further our understanding of epidemic dynamics on tree-based communities of wireless sensor networks.

Isolation and sequence analysis of the complete NS1 and VP2 genes of canine parvovirus from domestic dogs in 2013 and 2014 in China

Canine parvovirus (CPV) can cause severe disease in animals and continuously generates new variant and recombinant strains in dogs that have a strong impact on sanitation. It is therefore necessary to investigate epidemic CPV strains to improve our understanding of CPV transmission and epidemic behavior. However, most studies have focused on the analysis of VP2, and therefore, information about recombination and relationships between strains is still lacking. Here, 14 strains of CPV were isolated from domestic dogs suspected of hosting CPV between 2013 and 2014 in China. The complete NS1 and VP2 genes were sequenced and analyzed. The results suggest that the new CPV-2a and new CPV-2b types are the prevalent strains in China. In addition to a few mutations (residues 19, 544, 545, 572 and 583 of NS1 and residues 267, 370, 377 and 440 of VP2) that were preserved during transmission, new mutations (residues 60, 630 of NS1, and residues 21, 310 of VP2) were found in the isolated strains. A phylogenetic tree based on VP2 sequences illustrated that the new CPV-2a and new CPV-2b strains from China form single clusters that are distinct from lineages from other countries. Moreover, recombination between the new CPV-2a and new CPV-2b types was also identified in the isolated strains. Due to differences in selection pressures or recombination, there were a small number of inconsistencies between the phylogenetic trees for VP2 and NS1, which indicated that phylogenetic relationships based on VP2 might not be representative of those based on NS1. The data indicated that mutations and recombination are constantly occurring along with the spread of CPV in China.