Modelling disease spread and control in networks: implications for plant sciences

Networks are ubiquitous in natural, technological and social systems. They are of increasing relevance for improved understanding and control of infectious diseases of plants, animals and humans, given the interconnectedness of today's world. Recent modelling work on disease development in complex networks shows: the relative rapidity of pathogen spread in scale-free compared with random networks, unless there is high local clustering; the theoretical absence of an epidemic threshold in scale-free networks of infinite size, which implies that diseases with low infection rates can spread in them, but the emergence of a threshold when realistic features are added to networks (e.g. finite size, household structure or deactivation of links); and the influence on epidemic dynamics of asymmetrical interactions. Models suggest that control of pathogens spreading in scale-free networks should focus on highly connected individuals rather than on mass random immunization. A growing number of empirical applications of network theory in human medicine and animal disease ecology confirm the potential of the approach, and suggest that network thinking could also benefit plant epidemiology and forest pathology, particularly in human-modified pathosystems linked by commercial transport of plant and disease propagules. Potential consequences for the study and management of plant and tree diseases are discussed.

Control of cocoa swollen shoot disease by eradicating infected trees in Ghana: A survey of treated and replanted areas

Cocoa farms that had been treated and replanted in Ghana during the most recent phase of the cocoa swollen shoot virus (CSSV) eradication campaign were surveyed. Farms that were replanted close to adjoining old cocoa farms or which contained old trees were common in most (38) of the 41 cocoa farms surveyed. CSSV infections were apparent in 20 (53%) out of these 38 farms and they pose a serious risk of causing early infections of the re-planted farms. Control strategies that isolate the newly planted farms by a boundary of immune crops as barriers to reduce CSSV re-infection are discussed. (c) 2005 Elsevier Ltd. All rights reserved.

Modelling of Johne's disease control options in beef cattle: a decision support approach

Johne's disease in cattle is a contagious wasting disease caused by Mycobacterium avium subspecies paratuberculosis (MAP). Johne's infection is characterised by a long subclinical phase and can therefore go undetected for long periods of time during which substantial production losses can occur. The protracted nature of Johne's infection therefore presents a challenge for both veterinarians and farmers when discussing control options due to a paucity of information and limited test performance when screening for the disease. The objectives were to model Johne's control decisions in suckler beef cattle using a decision support approach, thus implying equal focus on ‘end user’ (veterinarian) participation whilst still focusing on the technical disease modelling aspects during the decision support model development. The model shows how Johne's disease is likely to affect a herd over time both in terms of physical and financial impacts. In addition, the model simulates the effect on production from two different Johne's control strategies; herd management measures and test and cull measures. The article also provides and discusses results from a sensitivity analysis to assess the effects on production from improving the currently available test performance. Output from running the model shows that a combination of management improvements to reduce routes of infection and testing and culling to remove infected and infectious animals is likely to be the least-cost control strategy.

Parkinson’s Disease tremor classification – a comparison between Support Vector Machines and neural networks

Deep Brain Stimulation has been used in the study of and for treating Parkinson’s Disease (PD) tremor symptoms since the 1980s. In the research reported here we have carried out a comparative analysis to classify tremor onset based on intraoperative microelectrode recordings of a PD patient’s brain Local Field Potential (LFP) signals. In particular, we compared the performance of a Support Vector Machine (SVM) with two well known artificial neural network classifiers, namely a Multiple Layer Perceptron (MLP) and a Radial Basis Function Network (RBN). The results show that in this study, using specifically PD data, the SVM provided an overall better classification rate achieving an accuracy of 81% recognition.

Economic rationale for interventions to control livestock disease

Disease in farm animals has significant economic impacts on livestock production and incurs substantial costs for societies. Impacts affect not only livestock farms and the livestock industries but also sectors outside of farming. Important negative externalities of livestock disease include impacts on the health of other producers’ livestock, on human health, and on animal welfare. Good disease risk management/biosecurity and good animal welfare are public goods. Not taking account of these externality and public good aspects can lead to a misallocation of resources for livestock disease control. In such instances, there may be a strong case for government or other authority to intervene to ensure a better use of resources. There are a number of policy instruments that can be implemented for this purpose. One potential instrument is a Farm Animal Health and Welfare Stewardship Scheme funded under Pillar II of the CAP. A number of countries have public–private partnership cost-sharing schemes that aim to share appropriately both responsibilities and costs of epidemic livestock disease. There is a strong future agenda for appropriate intervention by governments in the management of livestock disease risks, including responsibility and cost sharing for livestock disease control, within the European Union and elsewhere.

Farmers’ perceptions of the effectiveness of the Cocoa Disease and Pest Control Programme (CODAPEC) in Ghana and its effects on poverty reduction

The study examined the contribution of the Cocoa Disease and Pest Control Programme (CODAPEC), which is a cocoa production-enhancing government policy, to reducing poverty and raising the living standards of cocoa farmers in Ghana. One hundred and fifty (150) cocoa farmers were randomly selected from five communities in the Bibiani-Anhwiaso-Bekwai district of the Western Region of Ghana and interviewed using structured questionnaires. Just over half of the farmers (53%) perceived the CODAPEC programme as being effective in controlling pests and diseases, whilst 56.6% felt that their yields and hence livelihoods had improved. In some cases pesticides or fungicides were applied later in the season than recommended and this had a detrimental effect on yields. To determine the level of poverty amongst farmers, annual household consumption expenditure was used as a proxy indicator. The study found that 4.7% of cocoa farmers were extremely poor having a total annual household consumption expenditure of less than GH¢ 623.10 ($310.00) while 8.0% were poor with less than GH¢ 801.62 ($398.81). An amount of money ranging from GH¢ 20.00 ($9.95) to GH¢ 89.04 ($44.29) per annum was needed to lift the 4.7% of cocoa farmers out of extreme poverty, which could be achieved through modest increases in productivity. The study highlighted how agricultural intervention programmes, such as CODAPEC, have the potential to contribute to improved farmer livelihoods.

An LDA and probability-based classifier for the diagnosis of Alzheimer's Disease from structural MRI

In this paper a custom classification algorithm based on linear discriminant analysis and probability-based weights is implemented and applied to the hippocampus measurements of structural magnetic resonance images from healthy subjects and Alzheimer’s Disease sufferers; and then attempts to diagnose them as accurately as possible. The classifier works by classifying each measurement of a hippocampal volume as healthy controlsized or Alzheimer’s Disease-sized, these new features are then weighted and used to classify the subject as a healthy control or suffering from Alzheimer’s Disease. The preliminary results obtained reach an accuracy of 85.8% and this is a similar accuracy to state-of-the-art methods such as a Naive Bayes classifier and a Support Vector Machine. An advantage of the method proposed in this paper over the aforementioned state of the art classifiers is the descriptive ability of the classifications it produces. The descriptive model can be of great help to aid a doctor in the diagnosis of Alzheimer’s Disease, or even further the understand of how Alzheimer’s Disease affects the hippocampus.

Farmer attitudes and livestock disease: exploring citizenship behaviour and peer monitoring across two BVD control schemes in the UK

The eradication of BVD in the UK is technically possible but appears to be socially untenable. The following study explored farmer attitudes to BVD control schemes in relation to advice networks and information sharing, shared aims and goals, motivation and benefits of membership, notions of BVD as a priority disease and attitudes toward regulation. Two concepts from the organisational management literature framed the study: citizenship behaviour where actions of individuals support the collective good (but are not explicitly recognised as such) and peer to peer monitoring (where individuals evaluate other’s behaviour). Farmers from two BVD control schemes in the UK participated in the study: Orkney Livestock Association BVD Eradication Scheme and Norfolk and Suffolk Cattle Breeders Association BVD Eradication Scheme. In total 162 farmers participated in the research (109 in-scheme and 53 out of scheme). The findings revealed that group helping and information sharing among scheme members was low with a positive BVD status subject to social censure. Peer monitoring in the form of gossip with regard to the animal health status of other farms was high. Interestingly, farmers across both schemes supported greater regulation with regard to animal health, largely due to the mistrust of fellow farmers following voluntary disease control measures. While group cohesiveness varied across the two schemes, without continued financial inducements, longer-term sustainability is questionable

5-Lipoxygenase plays a role in the control of parasite burden and contributes to oxidative damage of erythrocytes in murine Chagas` disease

Chagas` disease is accompanied by severe anemia and oxidative stress, which may contribute to mortality. In this study, we investigated the role of 5-lipoxygenase (5-LO) in the control of parasitism and anemia associated with oxidative damage of erythrocytes in experimental Trypanosoma cruzi infection. Wild-type C57BL/6, 129Sv mice treated or not with nordihydroguaiaretic acid (NDGA, 5-LO inhibitor), mice lacking the 5-LO enzyme gene (5-LO(-/-)) and inducible nitric oxide synthase gene (iNOS(-/-)) were infected with the Y strain of T cruzi. impairment of 5-LO resulted in increased numbers of trypomastigote forms in the blood and amastigote forms in the heart of infected mice. We assessed oxidative stress in erythrocytes by measuring oxygen uptake, induction time and chemiluminescence following treatment with tert-butyl hydroperoxide (TBH). Our results show that 5-LO metabolites increased lipid peroxidation levels in erythrocytes during the early phase of murine T cruzi infection. NDGA treatment reduced oxidative damage of erythrocytes in C57BL/6 T cruzi-infected mice but not in C57BL/6 iNOS-/- infected mice, showing that the action of NDGA is dependent on endogenous nitric oxide (NO). In addition, our results show that 5-LO metabolites do not participate directly in the development of anemia in infected mice. We conclude that 5-LO products may not only play a major role in controlling heart tissue parasitism, i.e., host resistance to acute infection with T cruzi in vivo, but in the event of an infection also play an important part in erythrocyte oxidative stress, an NO-dependent effect. (C) 2009 Elsevier B.V. All rights reserved.

Acaricides used in conventional and organic citrus orchard: leprosis and phytoseiid mites population control

The citrus leprosis control in São Paulo state is performed exclusively by acaricides to control the vector mite, Brevipalpus phoenicis, which increases the production costs and may affect the beneficial organism's population. Therefore, the aim of this trial was to evaluate during four seasons, the effects of acaricides recommended to control the mite B. phoenicis in conventional and organic citrus over evolution of citrus leprosis and over phytoseiids' population. The experiment was installed in October of 2003 in a citrus orchard in Reginopolis city, state of São Paulo. The experimental design used randomized blocks, the dosages was expressed as mL c.p./100L of water and the treatments were the following: spirodiclofen (20 mL); cyhexatin (50 mL) (used in rotation), lime sulfur (4,000 mL) and control (without pesticide application). However, the rotation between spirodiclofen and cyhexatin began in September 2006. Prior to that time, only spirodiclofen had been used. Surveys were conducted every 15 days on the B. phoenicis, Iphiseioides zuluagai, and Euseius populations. The control level adopted by the B. phoenicis was 8.3%, and the pesticide applications were conducted using tractor-sprayers. During the 2007-08 seasons, 10 infected fallen fruits per plot were collected and the number of leprosis lesions was quantified by each fruit. By the end of the 2007-08 seasons, the productivity, harvest losses, the disease incidence and severity were evaluated. It was found that the lesions' location over the fruit is more important in determining its drop than the lesions' number. The more intense the mite infestation, the greater is the number of lesions, resulting in increased premature fruit drop. A strategy using acaricides spirodiclofen and cyhexatin in rotation promoted more efficient control of B. phoenicis compared to lime sulfur, resulting in greater productivity, lower fruit losses and severity levels. The lime sulfur applications reduced the mite population incidence below the control level; however it did not prevent the lesions' occurrence. The acaricides applicarevented adverse effects on phytoseiid population because there was a reduction of their density.

Control charts for monitoring the mean vector and the covariance matrix of bivariate processes

In this article, we propose new control charts for monitoring the mean vector and the covariance matrix of bivariate processes. The traditional tools used for this purpose are the T (2) and the |S| charts. However, these charts have two drawbacks: (1) the T (2) and the |S| statistics are not easy to compute, and (2) after a signal, they do not distinguish the variable affected by the assignable cause. As an alternative to (1), we propose the MVMAX chart, which only requires the computation of sample means and sample variances. As an alternative to (2), we propose the joint use of two charts based on the non-central chi-square statistic (NCS statistic), named as the NCS charts. Once the NCS charts signal, the user can immediately identify the out-of-control variable. In general, the synthetic MVMAX chart is faster than the NCS charts and the joint T (2) and |S| charts in signaling processes disturbances.