Teleagro: software architecture of georeferencing and detection of heat of cattle

The systems of livestock production contribute in a preponderant way to improve the quality of life of the communities, since it allows to support the production of the daily sustenance of the communities, to conserve the ecosystems, to promote the conservation of the wild life and to satisfy the values and traditions cultural Latin America, with its large wilderness areas, and a privileged climate favors the maintenance of livestock, to meet the demands of food and ensure regional and global food security. In Colombia, the agricultural sector contributes approximately 11.83% of the national GDP at current prices, according to the Bank of the Republic. Likewise, the livestock industry participates with 3.6%, in comparison with other sectors of the agricultural economy, the production of Colombian cattle doubles and triples to other sectors, such as poultry, coffee and floriculture. In addition, it contributes to the generation of employment in more than 25% of the total jobs generated in the agricultural sector and approximately 7% of the total employment of the Colombian economy (http://www.banrep.gov.co/is/pib). Within agricultural production, livestock occupy 38 million hectares, being 9 times larger than the area dedicated to agriculture. However, agriculture contributes 63% of the value of agricultural production, while livestock, mainly extensive, contributes 26% (FEDEGAN, Strategic Livestock Plan 2019). The large proportion of the área with agricultural vocation dedicated to precarious extensive livestock has explained the low agricultural productivity in Colombia, with very serious consequences for human and sustainable development. This document shows the results of the communications, software and hardware platforms to help the livestock sector to manage production

Concepts for risk-based surveillance in the field of veterinary medicine and veterinary public health: Review of current approaches

BACKGROUND: Emerging animal and zoonotic diseases and increasing international trade have resulted in an increased demand for veterinary surveillance systems. However, human and financial resources available to support government veterinary services are becoming more and more limited in many countries world-wide. Intuitively, issues that present higher risks merit higher priority for surveillance resources as investments will yield higher benefit-cost ratios. The rapid rate of acceptance of this core concept of risk-based surveillance has outpaced the development of its theoretical and practical bases. DISCUSSION: The principal objectives of risk-based veterinary surveillance are to identify surveillance needs to protect the health of livestock and consumers, to set priorities, and to allocate resources effectively and efficiently. An important goal is to achieve a higher benefit-cost ratio with existing or reduced resources. We propose to define risk-based surveillance systems as those that apply risk assessment methods in different steps of traditional surveillance design for early detection and management of diseases or hazards. In risk-based designs, public health, economic and trade consequences of diseases play an important role in selection of diseases or hazards. Furthermore, certain strata of the population of interest have a higher probability to be sampled for detection of diseases or hazards. Evaluation of risk-based surveillance systems shall prove that the efficacy of risk-based systems is equal or higher than traditional systems; however, the efficiency (benefit-cost ratio) shall be higher in risk-based surveillance systems. SUMMARY: Risk-based surveillance considerations are useful to support both strategic and operational decision making. This article highlights applications of risk-based surveillance systems in the veterinary field including food safety. Examples are provided for risk-based hazard selection, risk-based selection of sampling strata as well as sample size calculation based on risk considerations

Conceptualising the technical relationship of animal disease surveillance to intervention and mitigation as a basis for economic analysis

<p>Abstract</p> <p>Background</p> <p>Surveillance and intervention are resource-using activities of strategies to mitigate the unwanted effects of disease. Resources are scarce, and allocating them to disease mitigation instead of other uses necessarily involves the loss of alternative sources of benefit to people. For society to obtain the maximum benefits from using resources, the gains from disease mitigation must be compared to the resource costs, guiding decisions made with the objective of achieving the optimal net outcome.</p> <p>Discussion</p> <p>Economics provides criteria to guide decisions aimed at optimising the net benefits from the use of scarce resources. Assessing the benefits of disease mitigation is no exception. However, the technical complexity of mitigation means that economic evaluation is not straightforward because of the technical relationship of surveillance to intervention. We argue that analysis of the magnitudes and distribution of benefits and costs for any given strategy, and hence the outcome in net terms, requires that mitigation is considered in three conceptually distinct stages. In Stage I, 'sustainment', the mitigation objective is to sustain a free or acceptable status by preventing an increase of a pathogen or eliminating it when it occurs. The role of surveillance is to document that the pathogen remains below a defined threshold, giving early warning of an increase in incidence or other significant changes in risk, and enabling early response. If a pathogen is not contained, the situation needs to be assessed as Stage II, 'investigation'. Here, surveillance obtains critical epidemiological information to decide on the appropriate intervention strategy to reduce or eradicate a disease in Stage III, 'implementation'. Stage III surveillance informs the choice, timing, and scale of interventions and documents the progress of interventions directed at prevalence reduction in the population.</p> <p>Summary</p> <p>This article originates from a research project to develop a conceptual framework and practical tool for the economic evaluation of surveillance. Exploring the technical relationship between mitigation as a source of economic value and surveillance and intervention as sources of economic cost is crucial. A framework linking the key technical relationships is proposed. Three conceptually distinct stages of mitigation are identified. Avian influenza, salmonella, and foot and mouth disease are presented to illustrate the framework.</p

A method of determining where to target surveillance efforts in heterogeneous epidemiological systems

The spread of pathogens into new environments poses a considerable threat to human, animal, and plant health, and by extension, human and animal wellbeing, ecosystem function, and agricultural productivity, worldwide. Early detection through effective surveillance is a key strategy to reduce the risk of their establishment. Whilst it is well established that statistical and economic considerations are of vital importance when planning surveillance efforts, it is also important to consider epidemiological characteristics of the pathogen in question—including heterogeneities within the epidemiological system itself. One of the most pronounced realisations of this heterogeneity is seen in the case of vector-borne pathogens, which spread between ‘hosts’ and ‘vectors’—with each group possessing distinct epidemiological characteristics. As a result, an important question when planning surveillance for emerging vector-borne pathogens is where to place sampling resources in order to detect the pathogen as early as possible. We answer this question by developing a statistical function which describes the probability distributions of the prevalences of infection at first detection in both hosts and vectors. We also show how this method can be adapted in order to maximise the probability of early detection of an emerging pathogen within imposed sample size and/or cost constraints, and demonstrate its application using two simple models of vector-borne citrus pathogens. Under the assumption of a linear cost function, we find that sampling costs are generally minimised when either hosts or vectors, but not both, are sampled