José Henrique Hildebrand Grisi-Filho

Detecting livestock production zones.

Communities are sets of nodes that are related in an important way, most likely sharing common properties and/or playing similar roles within a network. Unraveling a network structure, and hence the trade preferences and pathways, could be useful to a researcher or a decision maker. We implemented a community detection algorithm to find livestock communities, which is consistent with the definition of a livestock production zone, assuming that a community is a group of farm premises in which an animal is more likely to stay during its lifetime than expected by chance. We applied this algorithm to the network of animal movements within the state of Mato Grosso for 2007. This database holds information concerning 87,899 premises and 521,431 movements throughout the year, totaling 15,844,779 animals moved. The community detection algorithm achieved a network partition that shows a clear geographical and commercial pattern, two crucial features for preventive veterinary medicine applications; this algorithm provides also a meaningful interpretation to trade networks where links emerge based on trader node choices.

Scale-Free Networks with the Same Degree Distribution: Different Structural Properties

We have analysed some structural properties of scale-free networks with the same degree distribution. Departing from a degree distribution obtained from the Barabasi-Albert (BA) algorithm, networks were generated using four additional different algorithms (Molloy-Reed, Kalisky, and two new models named A and B) besides the BA algorithm itself. For each network, we have calculated the following structural measures: average degree of the nearest neighbours, central point dominance, clustering coefficient, the Pearson correlation coefficient, and global efficiency. We found that different networks with the same degree distribution may have distinct structural properties. In particular, model B generates decentralized networks with a larger number of components, a smaller giant component size, and a low global efficiency when compared to the other algorithms, especially compared to the centralized BA networks that have all vertices in a single component, with a medium to high global efficiency. The other three models generate networks with intermediate characteristics between B and BA models. A consequence of this finding is that the dynamics of different phenomena on these networks may differ considerably.

Dog and cat management through sterilization: Implications for population dynamics and veterinary public policies.

The present study aimed to compare different sterilization scenarios allowing the adoption of the most adequate strategy to control owned dog and cat population sizes as the official veterinary public policy for animal control in an urban area of Campinas municipality, Brazil. To achieve this goal, the vital parameters of the owned pet population were measured in a neighborhood of Campinas called Jardim Vila Olimpia through questionnaires used in two census studies performed in February 2012 and June 2013. Different hypothetical sterilization scenarios were compared with the scenario of a single sterilization campaign performed in the study area between the census studies. Using a deterministic mathematical model, population dynamics were simulated for these different scenarios. We have observed that for both owned dogs and cats, the impact on the population size achieved by a single sterilization campaign would be diluted over the years, equating to the impact achieved by the usual sterilization rate practiced before the sterilization campaign yearly. Moreover, using local and global sensitivity analyses, we assessed the relative influence on animal population evolution of each vital parameter used in the mathematical models. The more influential parameters for both species were the carrying capacity of the environment and sterilization rates of males and females (for both species). We observed that even with sterilizing 100% of the intact animals annually, it would not be possible to obtain proportions greater than 86% and 88% of sterilized dogs and cats, respectively, after 20 years due to the high introduction of new intact animals. There is no public dog and cat sterilization service in place in the city, and sporadic and local sterilization campaigns are performed with a prior communication to the owners to bring their animals to be sterilized in a selected veterinary facility. If a sterilization campaign was performed annually in the study area, it would have the most favorable cost effectiveness ratio after 20 years compared to the scenarios of 50% and 100% sterilization of intact animals annually. These results allowed the veterinary public policy stakeholders to make decisions based on scientific evidence to implement adequate control of dog and cat populations in urban areas, aiming to reduce zoonosis transmission to humans and other problems associated with uncontrolled animal populations.

Monitoring techniques in the capture and adoption of dogs and cats

The continuous improvement of the information systems of organizations that work toward the control of stray dog and cat populations facilitates the implementation of programs aimed at reducing the number of animals that roam free in public streets. This study aimed to present techniques to improve the understanding of the spatial distribution of stray dogs and cats and of people who adopt these animals and the fate of these animals in zoonosis control centers (ZCC). Ripleys K function was used with a Euclidean distance graph to detect the distribution pattern of dogs and cats captured and of the people who adopted these animals. An estimate of the kernel density was used to allow a better assessment of the spatial distribution of the phenomenon studied. The results showed that the distribution of captured animals and of the people who adopted these animals form a spatial cluster (p = 0.01). Most of the animals were captured near the premises of the ZCC and near the downtown area. Factors such as the abandonment of animals near animal control agencies and the availability of food sources are the main hypotheses associated to the distribution of the captures. The awareness of the people who live in places where there is a greater number of stray animals and the distribution of the urban population are the main hypotheses to explain the distribution of the adoptions. The results will help to implement control measures over these populations in the most problematic areas.

Predictive qualitative risk model of bovine rabies occurrence in Brazil

Bovine rabies remains endemic in Brazil and despite control efforts, the disease still spreads insidiously. The main vector is the hematophagous bat, Desmodus rotundus. The present work aimed to create a predictive qualitative model of the occurrence of bovine rabies in each municipality in 25 of the 27 Brazilian States. The risk of rabies transmission from bats to bovine was estimated using decision-tree models of receptivity and vulnerability. Questionnaires, which covered a number of questions related to the surveillance of possible risk factors, such as bovine rabies outbreaks in the previous year, the presence of bat roosts, bat rabies positivity and environmental changes, were sent to the local veterinary units of each State. The bovine density and geomorphologic features were obtained from national databases and geographic information systems. Of the 433 municipalities presenting bovine rabies outbreaks in 2010, 178 (41.1%) were classified by the model as high risk, 212 (49.0%) were classified as moderate risk, 25 (5.8%) were classified as low risk, whereas the risk was undetermined in 18 municipalities (4.1%). An ROC curve was built to determine if the risk evaluated by the model could adequately discriminate between municipalities with and without rabies occurrence in future years. The risk estimator for the year 2011 was classified as moderately accurate. In the future, these models could allow the targeting of rabies control efforts, with the adoption of control measures directed to the higher risk locations and the optimization of the field veterinary staff deployment throughout the country. Additionally, efforts must be made to encourage continuous surveillance of risk factors.

Uso de sistemas de informação geográfica em campanhas de vacinação contra a raiva

OBJETIVO: Desenvolver metodo para planejamento e avaliacao de campanhas de vacinacao contra a raiva animal. METODOS: O desenvolvimento da metodologia baseou-se em sistemas de informacao geografica para estimar a populacao e a densidade animal (canina e felina) por setores censitarios e subprefeituras do municipio de Sao Paulo, em 2002. O numero de postos de vacinacao foi estimado para atingir uma dada cobertura vacinal. Foram utilizadas uma base de dados censitarios para a populacao humana, e estimativas para razoes cao:habitante e gato:habitante. RESULTADOS: Os numeros estimados foram de 1.490.500 caes e 226.954 gatos em Sao Paulo, uma densidade populacional de 1.138,14 animais domiciliados por km². Foram vacinados, na campanha de 2002, 926.462 animais, garantindo uma cobertura vacinal de 54%. O numero total estimado de postos no municipio para atingir uma cobertura vacinal de 70%, vacinando em media 700 animais por posto foi de 1.729. Estas estimativas foram apresentadas em mapas de densidade animal, segundo setores censitarios e subprefeituras. CONCLUSOES: A metodologia desenvolvida pode ser aplicada de forma sistematica no planejamento e no acompanhamento das campanhas de vacinacao contra a raiva, permitindo que sejam identificadas areas de cobertura vacinal critica.

Use of geographic information systems in rabies vaccination campaigns

OBJETIVO: Desenvolver metodo para planejamento e avaliacao de campanhas de vacinacao contra a raiva animal. METODOS: O desenvolvimento da metodologia baseou-se em sistemas de informacao geografica para estimar a populacao e a densidade animal (canina e felina) por setores censitarios e subprefeituras do municipio de Sao Paulo, em 2002. O numero de postos de vacinacao foi estimado para atingir uma dada cobertura vacinal. Foram utilizadas uma base de dados censitarios para a populacao humana, e estimativas para razoes cao:habitante e gato:habitante. RESULTADOS: Os numeros estimados foram de 1.490.500 caes e 226.954 gatos em Sao Paulo, uma densidade populacional de 1.138,14 animais domiciliados por km². Foram vacinados, na campanha de 2002, 926.462 animais, garantindo uma cobertura vacinal de 54%. O numero total estimado de postos no municipio para atingir uma cobertura vacinal de 70%, vacinando em media 700 animais por posto foi de 1.729. Estas estimativas foram apresentadas em mapas de densidade animal, segundo setores censitarios e subprefeituras. CONCLUSOES: A metodologia desenvolvida pode ser aplicada de forma sistematica no planejamento e no acompanhamento das campanhas de vacinacao contra a raiva, permitindo que sejam identificadas areas de cobertura vacinal critica.

The friendship paradox as a strategy for scenarios with incomplete network data: Comment on "Coupled disease-behavior dynamics on complex networks: A review" by Z. Wang et al.

Wang et al. [1] reviewed the coupled disease–behavior dynamics on complex networks and reported how certain empirical contact patterns of real-world networks were estimated. However, if surveying the network is not possible, approaches based on the knowledge of the entire network are not useful. This limitation poses a challenge in applying the knowledge obtained with disease–behavior coupled models in scenarios where data are incomplete or unavailable. On average, “your friends have more friends than you do”. This paradox is known as the “friendship paradox” [2–4] and is related to an interesting property of social networks: on average, ‘friends’ of individuals selected at random from the network have more connections and occupy more central positions in the network than the randomly selected individuals who named them [4,5]. Strategies based on the friendship paradox (FP), in which the neighbors of randomly selected nodes are sampled for surveillance or control, such as the ones described in [5], may help to find hub nodes either in the disease or in the behavior network or even in both networks simultaneously, depending on the main routes of disease transmission. A schematic description of how the friendship paradox strategies might reach the hub nodes is depicted in Fig. 1. The coupled disease–behavior dynamics reviewed by Wang et al. [1] also applies to animal diseases. As an example, bovine brucellosis, an infectious disease that causes abortion, is transmitted among farm premises primarily through the network of animal movements. Premises with cows infected by brucellosis may experience a higher abortion rate than brucellosis-free farm premises. To avoid economic losses due to abortions, cattle farmers might intend to replace the cows that aborted with healthy cows. However, other farmers could avoid buying animals from a farmer whom they suspect has infected animals. These mechanisms are examples of how brucellosis could affect the dynamics of an animal movement network. To implement animal disease control policies based on models such as the ones described by Wang et al. [1], it is necessary to know the entire network, which is not always available.

The friendship paradox in scale-free networks

Our friends have more friends than we do. That is the basis of the friendship paradox. In mathematical terms, the mean number of friends of friends is higher than the mean number of friends. In the present study, we analyzed the relationship between the mean degree of vertices (individuals), , and the mean number of friends of friends, , in scale-free networks with degrees ranging from a minimum degree (k_min) to a maximum degree (k_max). We deduced an expression for - for scale-free networks following a power-law distribution with a given scaling parameter (alpha). Based on this expression, we can quantify how the degree distribution of a scale-free network affects the mean number of friends of friends.

On the risk of introduction of an emerging infectious disease

published in Revista Brasileira de Epidemiologia ad-dresses the threat of an influenza pandemic and mentions “the information technology that makes it possible to monitor the dis-tribution of new cases in real time”. We are aware that the risk of spread of an emerg-ing infectious disease from one country to another depends on the number of travelers and on the ability of the monitoring system to detect infected passengers. In this letter, we describe a quantitative methodology to estimate the risk of introduction of an emerging infectious disease into a disease-free country through the movement of persons between countries in international flights. Our aim is to contribute to the dis-cussion about the importance of factors that influence the spread of influenza and other emerging diseases.Let us suppose that