Genetic Differentiation of Wild Boar Populations in a Region Endangered by African Swine Fever

For areas at risk for African swine fever (ASF) introduction from neighboring regions, it is important for epidemic control to know how wild boar (Sus scrofa) dispersion dynamics could be used to combat the spread of ASF. In this regard, long-term information based on population genetic data makes an important contribution. We selected our study area as Rhineland-Palatinate, Germany, because it had a high density of wild boars and was threatened by ASF via infected wild boars from neighboring Belgium. On an area of around 20,000 km², we collected almost 1,200 blood samples from 22 wild boar hunting grounds. The study area included a network of potential barriers to movement, including roads and rivers. We assessed genetic differentiation based on microsatellite data. We used 2 spatial (Bayesian Analysis of Population Structure [BAPS] and TESS) and 1 non-spatial (STRUCTURE) Bayesian model-based approaches to analyze the data. Each of the algorithms detected 4 clusters with different cluster compositions in different areas and identified the highest degrees of differentiation between hunting grounds east and west of the Rhine River, between Pfalz and Eifel-Hunsrück, and to a lesser degree between Westerwald and Taunus and between Eifel and Hunsrück. Thus, genetic evidence suggests barriers of different strength that might be helpful in a setup of complex and expensive measures against the spread of animal diseases such as ASF. The described approach could also provide valuable information for other threatened regions to contain ASF. © 2021 The Authors. The Journal of Wildlife Management published by Wiley Periodicals LLC on behalf of The Wildlife Society.     

Simulating the effect of quarantine on the spread of the 1918–19 flu in Central Canada

Quarantine is often proposed and sometimes used to control the spread of infectious diseases through a human population. Yet there is usually little or no information on the effectiveness of attempting to quarantine humans that is not of an anecdotal or conjectural nature. This paper describes how a compartmental model for the geographic spread of infectious diseases can be used to address the potential effectiveness of human quarantine. The model is applied to data from the historical record in central Canada around the time of the 1918–19 influenza epidemic. Information on the daily mobility patterns of individuals engaged in the fur trade throughout the region prior to, during, and immediately after the epidemic are used to determine whether rates of travel were affected by informal quarantine policies imposed by community leaders. The model is then used to assess the impact of observed differences in travel on the spread of the epidemic. Results show that when mobility rates are very low, as in this region, quarantine practices must be highly effective before they alter disease patterns significantly. Simulation results suggest, though, that effectiveness varies depending on when the limitation on travel between communities is implemented and how long it lasts, and that a policy of introducing quarantine at the earliest possible time may not always lead to the greatest reduction in cases of a disease.     

Genetic effects of human migrations and isolation

This paper analyses how migrations, environment and epidemics interact to shape genetic variation in the moder human species. The gene mutation that makes humans resistant to malaria is a striking example of how disease can shape the human genome. In Europe malaria spread in coincidence with the arrival of populations from Asia Minor and eastern Mediterranean and was favoured by the spread of agriculture, by the sedentary conditions of life and the related demographic increase. Natural selection, generally, shape the gene pool of a population in order to fit a different environment. This is the reason because hemoglobinopathies and enzyme G6PD deficit are greatly spread in areas hit by malaria epidemic. These effects are particularly evident in isolated regions or in islands with low population density, e.g. Sardinia. Disasters such as epidemics may drastically reduced the size of a population, and the victims under such circumstances are not selected. As a result the survivors within this small population are unlikely to be representative of the original population in its genetic makeup, and this occurrence is known as “bottleneck effect”. Sardinia, for instance, was hit between 1300 and 1700 by several plague epidemics. Such events drastically reduced the total number of inhabitants; creating a local alteration in the gene frequencies, that have moulded the genetics of the population. This has brought about not only a differentiation with respect to other Mediterranean populations, but creating a variability inside the island.     

Risk maps for the spread of highly pathogenic avian influenza in poultry

Devastating epidemics of highly contagious animal diseases such as avian influenza, classical swine fever, and foot-and-mouth disease underline the need for improved understanding of the factors promoting the spread of these pathogens. Here the authors present a spatial analysis of the between-farm transmission of a highly pathogenic H7N7 avian influenza virus that caused a large epidemic in The Netherlands in 2003. The authors developed a method to estimate key parameters determining the spread of highly transmissible animal diseases between farms based on outbreak data. The method allows for the identification of high-risk areas for propagating spread in an epidemiologically underpinned manner. A central concept is the transmission kernel, which determines the probability of pathogen transmission from infected to uninfected farms as a function of interfarm distance. The authors show how an estimate of the transmission kernel naturally provides estimates of the critical farm density and local reproduction numbers, which allows one to evaluate the effectiveness of control strategies. For avian influenza, the analyses show that there are two poultry-dense areas in The Netherlands where epidemic spread is possible, and in which local control measures are unlikely to be able to halt an unfolding epidemic. In these regions an epidemic can only be brought to an end by the depletion of susceptible farms by infection or massive culling. The analyses provide an estimate of the spatial range over which highly pathogenic avian influenza viruses spread between farms, and emphasize that control measures aimed at controlling such outbreaks need to take into account the local density of farms.     

The impact of seasonal and year-round transmission regimes on the evolution of influenza A virus

Punctuated antigenic change is believed to be a key element in the evolution of influenza A; clusters of antigenically similar strains predominate worldwide for several years until an antigenically distant mutant emerges and instigates a selective sweep. It is thought that a region of East-Southeast Asia with year-round transmission acts as a source of antigenic diversity for influenza A and seasonal epidemics in temperate regions make little contribution to antigenic evolution. We use a mathematical model to examine how different transmission regimes affect the evolutionary dynamics of influenza over the lifespan of an antigenic cluster. Our model indicates that, in non-seasonal regions, mutants that cause significant outbreaks appear before the peak of the wild-type epidemic. A relatively large proportion of these mutants spread globally. In seasonal regions, mutants that cause significant local outbreaks appear each year before the seasonal peak of the wild-type epidemic, but only a small proportion spread globally. The potential for global spread is strongly influenced by the intensity of non-seasonal circulation and coupling between non-seasonal and seasonal regions. Results are similar if mutations are neutral, or confer a weak to moderate antigenic advantage. However, there is a threshold antigenic advantage, depending on the non-seasonal transmission intensity, beyond which mutants can escape herd immunity in the non-seasonal region and there is a global explosion in diversity. We conclude that non-seasonal transmission regions are fundamental to the generation and maintenance of influenza diversity owing to their epidemiology. More extensive sampling of viral diversity in such regions could facilitate earlier identification of antigenically novel strains and extend the critical window for vaccine development.     

Development of a Novel Rabies Simulation Model for Application in a Non-endemic Environment

Domestic dog rabies is an endemic disease in large parts of the developing world and also epidemic in previously free regions. For example, it continues to spread in eastern Indonesia and currently threatens adjacent rabies-free regions with high densities of free-roaming dogs, including remote northern Australia. Mathematical and simulation disease models are useful tools to provide insights on the most effective control strategies and to inform policy decisions. Existing rabies models typically focus on long-term control programs in endemic countries. However, simulation models describing the dog rabies incursion scenario in regions where rabies is still exotic are lacking. We here describe such a stochastic, spatially explicit rabies simulation model that is based on individual dog information collected in two remote regions in northern Australia. Illustrative simulations produced plausible results with epidemic characteristics expected for rabies outbreaks in disease free regions (mean R₀ 1.7, epidemic peak 97 days post-incursion, vaccination as the most effective response strategy). Systematic sensitivity analysis identified that model outcomes were most sensitive to seven of the 30 model parameters tested. This model is suitable for exploring rabies spread and control before an incursion in populations of largely free-roaming dogs that live close together with their owners. It can be used for ad-hoc contingency or response planning prior to and shortly after incursion of dog rabies in previously free regions. One challenge that remains is model parameterisation, particularly how dogs’ roaming and contacts and biting behaviours change following a rabies incursion in a previously rabies free population.     

Cross-Species Virus Transmission and the Emergence of New Epidemic Diseases

Summary: Host range is a viral property reflecting natural hosts that are infected either as part of a principal transmission cycle or, less commonly, as “spillover” infections into alternative hosts. Rarely, viruses gain the ability to spread efficiently within a new host that was not previously exposed or susceptible. These transfers involve either increased exposure or the acquisition of variations that allow them to overcome barriers to infection of the new hosts. In these cases, devastating outbreaks can result. Steps involved in transfers of viruses to new hosts include contact between the virus and the host, infection of an initial individual leading to amplification and an outbreak, and the generation within the original or new host of viral variants that have the ability to spread efficiently between individuals in populations of the new host. Here we review what is known about host switching leading to viral emergence from known examples, considering the evolutionary mechanisms, virus-host interactions, host range barriers to infection, and processes that allow efficient host-to-host transmission in the new host population.     

Transmission of new CRF07_BC strains with 7 amino acid deletion in Gag p6

A 7 amino acid deletion in Gag p6 (P6delta7) emerged in Chinese prevalent HIV-1 strain CRF07_BC from different epidemic regions. It is important to determine whether this mutation could be transmitted and spread. In this study, HIV-1 Gag sequences from 5 different epidemic regions in China were collected to trace the transmission linkage and to analyze genetic evolution of P6delta7 strains. The sequence analysis demonstrated that P6delta7 is a CRF07_BC specific deletion, different P6delta7 strains could be originated from different parental CRF07_BC recombinants in different epidemic regions, and the transmission of P6delta7 strain has occurred in IDU populations. This is for the first time to identify the transmission linkage for P6delta7 strains and serves as a wake-up call for further monitoring in the future; In addition, P6delta7 deletion may represent an evolutionary feature which might exert influence on the fitness of CRF07_BC strain.     

Stochastic epidemics in dynamic populations: quasi-stationarity and extinction

Empirical evidence shows that childhood diseases persist in large communities whereas in smaller communities the epidemic goes extinct (and is later reintroduced by immigration). The present paper treats a stochastic model describing the spread of an infectious disease giving life-long immunity, in a community where individuals die and new individuals are born. The time to extinction of the disease starting in quasi-stationarity (conditional on non-extinction) is exponentially distributed. As the population size grows the epidemic process converges to a diffusion process. Properties of the limiting diffusion are used to obtain an approximate expression for τ, the mean-parameter in the exponential distribution of the time to extinction for the finite population. The expression is used to study how τ depends on the community size but also on certain properties of the disease/community: the basic reproduction number and the means and variances of the latency period, infectious period and life-length. Effects of introducing a vaccination program are also discussed as is the notion of the critical community size, defined as the size which distinguishes between the two qualitatively different behaviours. Received: 14 February 2000 / Revised version: 5 June 2000 / Published online: 24 November 2000     

Limits of a multi-patch SIS epidemic model

 We start from a stochastic SIS model for the spread of epidemics among a population partitioned into M sites, each containing N individuals; epidemic spread occurs through within-site (`local') contacts and global contacts. We analyse the limit behaviour of the system as M and N increase to ∞. Two limit procedures are considered, according to the order in which M and N go to ∞; independently of the order, the limiting distribution of infected individuals across sites is a probability measure, whose evolution in time is governed by the weak form of a PDE. Existence and uniqueness of the solutions to this problem is shown. Finally, it is shown that the infected distribution converges, as time goes to infinity, to a Dirac measure at the value x ^* , the equilibrium of a single-patch SIS model with contact rate equal to the sum of local and global contacts. Received: 18 July 2001 / Revised version: 16 March 2002 / Published online: 26 September 2002 Mathematics Subject Classification (2000): 92D30, 60F99 Key words or phrases: SIS epidemic – Metapopulation – Markov population processes – Weak convergence of measures     

A Comparison of Continuous and Discrete-time West Nile Virus Models

The first recorded North American epidemic of West Nile virus was detected in New York state in 1999, and since then the virus has spread and become established in much of North America. Mathematical models for this vector-transmitted disease with cross-infection between mosquitoes and birds have recently been formulated with the aim of predicting disease dynamics and evaluating possible control methods. We consider discrete and continuous time versions of the West Nile virus models proposed by Wonham et al. [Proc. R. Soc. Lond. B 271:501–507, 2004] and by Thomas and Urena [Math. Comput. Modell. 34:771–781, 2001], and evaluate the basic reproduction number as the spectral radius of the next-generation matrix in each case. The assumptions on mosquito-feeding efficiency are crucial for the basic reproduction number calculation. Differing assumptions lead to the conclusion from one model [Wonham, M.J. et al., [Proc. R. Soc. Lond. B] 271:501–507, 2004] that a reduction in bird density would exacerbate the epidemic, while the other model [Thomas, D.M., Urena, B., Math. Comput. Modell. 34:771–781, 2001] predicts the opposite: a reduction in bird density would help control the epidemic.     

Stochastic two-group models with transmission dependent on host infectivity or susceptibility

ABSTRACT

Stochastic epidemic models with two groups are formulated and applied to emerging and re-emerging infectious diseases. In recent emerging diseases, disease spread has been attributed to superspreaders, highly infectious individuals that infect a large number of susceptible individuals. In some re-emerging infectious diseases, disease spread is attributed to waning immunity in susceptible hosts. We apply a continuous-time Markov chain (CTMC) model to study disease emergence or re-emergence from different groups, where the transmission rates depend on either the infectious host or the susceptible host. Multitype branching processes approximate the dynamics of the CTMC model near the disease-free equilibrium and are used to estimate the probability of a minor or a major epidemic. It is shown that the probability of a major epidemic is greater if initiated by an individual from the superspreader group or by an individual from the highly susceptible group. The models are applied to Severe Acute Respiratory Syndrome and measles.     

The Modeling of Global Epidemics: Stochastic Dynamics and Predictability

The global spread of emergent diseases is inevitably entangled with the structure of the population flows among different geographical regions. The airline transportation network in particular shrinks the geographical space by reducing travel time between the world's most populated areas and defines the main channels along which emergent diseases will spread. In this paper, we investigate the role of the large-scale properties of the airline transportation network in determining the global propagation pattern of emerging diseases. We put forward a stochastic computational framework for the modeling of the global spreading of infectious diseases that takes advantage of the complete International Air Transport Association 2002 database complemented with census population data. The model is analyzed by using for the first time an information theory approach that allows the quantitative characterization of the heterogeneity level and the predictability of the spreading pattern in presence of stochastic fluctuations. In particular we are able to assess the reliability of numerical forecast with respect to the intrinsic stochastic nature of the disease transmission and travel flows. The epidemic pattern predictability is quantitatively determined and traced back to the occurrence of epidemic pathways defining a backbone of dominant connections for the disease spreading. The presented results provide a general computational framework for the analysis of containment policies and risk forecast of global epidemic outbreaks. On leave from CEA-Centre d'Etudes de Bruyères-Le-Chatel, France.     

Predictive spatial dynamics and strategic planning for raccoon rabies emergence in Ohio

Rabies is an important public health concern in North America because of recent epidemics of a rabies virus variant associated with raccoons. The costs associated with surveillance, diagnostic testing, and post-exposure treatment of humans exposed to rabies have fostered coordinated efforts to control rabies spread by distributing an oral rabies vaccine to wild raccoons. Authorities have tried to contain westward expansion of the epidemic front of raccoon-associated rabies via a vaccine corridor established in counties of eastern Ohio, western Pennsylvania, and West Virginia. Although sporadic cases of rabies have been identified in Ohio since oral rabies vaccine distribution in 1998, the first evidence of a significant breach in this vaccine corridor was not detected until 2004 in Lake County, Ohio. Herein, we forecast the spatial spread of rabies in Ohio from this breach using a stochastic spatial model that was first developed for exploratory data analysis in Connecticut and next used to successfully hind-cast wave-front dynamics of rabies spread across New York. The projections, based on expansion from the Lake County breach, are strongly affected by the spread of rabies by rare, but unpredictable long-distance translocation of rabid raccoons; rabies may traverse central Ohio at a rate 2.5-fold greater than previously analyzed wildlife epidemics. Using prior estimates of the impact of local heterogeneities on wave-front propagation and of the time lag between surveillance-based detection of an initial rabies case to full-blown epidemic, specific regions within the state are identified for vaccine delivery and expanded surveillance effort.     

HIV infection in India: Epidemiology, molecular epidemiology and pathogenesis

The year 1986 saw first case of HIV infection as well as first report of AIDS case in India. Since then the epidemic has spread throughout the country. In the recent years there is evidence of epidemic being stabilized with decrease in new infections reported from some parts of the country. The absolute number of HIV infections in the country is expected to be close to 2.5 million and National AIDS Control Programme, phase III is geared to contain the epidemic. HIV viruses circulating in India predominantly belong to HIV-1 subtype C. However, there have been occasional reports of HIV-1 subtype A and B. Matter of concern is reports of A/C and B/C mosaic viruses that are being reported from different parts of the country. The data on HIV drug resistance from India is rather limited. Most of the studies have shown that the virus strains from drug naïve patients do not show significant level of drug resistance mutations. The few immunological studies in Indian patients show that the Indian HIV infected patients show both HIV-specific CTL responses as well as neutralizing antibody response. Mapping of CTL epitopes showed that while Indian patients identify same regions of Gag antigen as recognized by South African subtype C infected patients, some regions are uniquely recognized by Indian patients. There are very few studies on host genetic factors in India in context with HIV infection. However there are evidences reported of association of host genetic factors such as HLA types and haplotypes and HIV disease.     

Rates of spread of marine pathogens

Epidemics of marine pathogens can spread at extremely rapid rates. For example, herpes virus spread through pilchard populations in Australia at a rate in excess of 10 000 km year^?1, and morbillivirus infections in seals and dolphins have spread at more than 3000 km year^?1. In terrestrial environments, only the epidemics of myxomatosis and calicivirus in Australian rabbits and West Nile Virus in birds in North America have rates of spread in excess of 1000 km year^?1. The rapid rates of spread of these epidemics has been attributed to flying insect vectors, but flying vectors have not been proposed for any marine pathogen. The most likely explanation for the relatively rapid spread of marine pathogens is the lack of barriers to dispersal in some parts of the ocean, and the potential for long‐term survival of pathogens outside the host. These findings caution that pathogens may pose a particularly severe problem in the ocean. There is a need to develop epidemic models capable of generating these high rates of spread and obtain more estimates of disease spread rate.     

Prediction and Control of Brucellosis Transmission of Dairy Cattle in Zhejiang Province,China

Brucellosis is a bacterial disease caused by brucella; mainly spread by direct contact transmission through the brucella carriers, or indirect contact transmission by the environment containing large quantities of bacteria discharged by the infected individuals. At the beginning of 21st century, the epidemic among dairy cows in Zhejiang province, began to come back and has become a localized prevalent epidemic. Combining the pathology of brucellosis, the reported positive data characteristics, and the feeding method in Zhejiang province, this paper establishes an dynamic model to excavate the internal transmission dynamics, fit the real disease situation, predict brucellosis tendency and assess control measures in dairy cows. By careful analysis, we give some quantitative results as follows. (1) The external input of dairy cows from northern areas may lead to high fluctuation of the number of the infectious cows in Zhejiang province that can reach several hundreds. In this case, the disease cannot be controlled and the infection situation cannot easily be predicted. Thus, this paper encourages cows farms to insist on self-supplying production of the dairy cows. (2) The effect of transmission rate of brucella in environment to dairy cattle on brucellosis spreading is greater than transmission rate of the infectious dairy cattle to susceptible cattle. The prevalence of the epidemic is mainly aroused by environment transmission. (3) Under certain circumstances, the epidemic will become a periodic phenomenon. (4) For Zhejiang province, besides measures that have already been adopted, sterilization times of the infected regions is suggested as twice a week, and should be combined with management of the birth rate of dairy cows to control brucellosis spread.     

Network epidemic models with two levels of mixing

The study of epidemics on social networks has attracted considerable attention recently. In this paper, we consider a stochastic SIR (susceptible-->infective-->removed) model for the spread of an epidemic on a finite network, having an arbitrary but specified degree distribution, in which individuals also make casual contacts, i.e. with people chosen uniformly from the population. The behaviour of the model as the network size tends to infinity is investigated. In particular, the basic reproduction number R(0), that governs whether or not an epidemic with few initial infectives can become established is determined, as are the probability that an epidemic becomes established and the proportion of the population who are ultimately infected by such an epidemic. For the case when the infectious period is constant and all individuals in the network have the same degree, the asymptotic variance and a central limit theorem for the size of an epidemic that becomes established are obtained. Letting the rate at which individuals make casual contacts decrease to zero yields, heuristically, corresponding results for the model without casual contacts, i.e. for the standard SIR network epidemic model. A deterministic model that approximates the spread of an epidemic that becomes established in a large population is also derived. The theory is illustrated by numerical studies, which demonstrate that the asymptotic approximations work well, even for only moderately sized networks, and that the degree distribution and the inclusion of casual contacts can each have a major impact on the outcome of an epidemic.     

Modelling the social dynamics of a sex industry: Its implications for spread of HIV/AIDS

A theoretical model is proposed for a community which has the structure of two classes (direct and indirect) of commercial sex workers (CSW), and two classes of sexually active male customers with different levels of sexual activity. The direct CSW’s work in brothels while the indirect CSW’s are based in commercial establishments such as bars, cafes, and massage parlours where sex can be bought on request and conducted elsewhere. Behaviour change and the resulting change of activity class occurs between the two classes of CSW’s and two classes of males under the setting of the proliferation of human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome epidemic and the subsequent intervention programmes. In recently years, this phenomenon has been observed in several countries in Asia. Given the lower levels of condom use and higher HIV prevalence of the indirect CSW’s, ascertaining the impact of this change in the structure of the sex industry on the spread of HIV is the main focus of this paper. The complete analysis of the disease-free model is given. For the full model, local analysis will be performed for the case of preferred mixing without activity class change, as well as the case with activity class change and restricted mixing. The basic reproduction number for the spread of epidemic will be derived for each case. Results of biological significance include: (i) the change of behaviour by the CSW’s has a more direct effect on the spread of HIV than that of the male customers; (ii) the basic reproduction number is obtained by considering all possible infection cycles of the heterosexual transmission of HIV which indicates the importance of understanding the sexual networking in heterosexual transmission of HIV; (iii) the social dynamics of the sex industry is not just a simple ’supply and demand’ mechanism driven by the demand of the customers, hence highlighting the need for further understanding of the changing structure of the sex industry. The main points of this work will be illustrated with numerical examples using the HIV data of Thailand.     

Human vs. Animal Outbreaks of the 2009 Swine-Origin H1N1 Influenza A epidemic

The majority of emerging infectious diseases are zoonotic in origin, including recently emerging influenza viruses such as the 2009 swine-origin H1N1 influenza A epidemic. The epidemic that year affected both human and animal populations as it spread globally. In fact, before the end of 2009, 14 different countries reported H1N1 infected swine. In order to better understand the zoonotic nature of the epidemic and the relationship between human and animal disease surveillance data streams, we compared 2009 reports of H1N1 infection to define the temporal relationship between reported cases in animals and humans. Generally, human cases preceded animal cases at a country-level, supporting the potential of H1N1 infection to be a “reverse zoonosis”, and the value of integrating human and animal disease report data.