Spatial clustering analysis of the foot-and-mouth disease outbreaks in Mato Grosso do Sul state, Brazil - 2005

Negreiros, R. L.; Amaku, Marcos; Dias, Ricardo Augusto; Ferreira, Fernando; Cavalléro, João Crisostomo Manuad; Neto, José Soares Ferreira

doi:10.1590/s0103-84782009005000203

Cited by 7 publications

(6 citation statements)

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“…In addition to the fact that surveillance at the international border is not 100% effective, the most recent FMD outbreaks in the region occurred in areas that were recognized as being free of FMD with vaccination (MS in 2005/2006 and Paraguay in 2011) and these outbreaks origin is still unknown (37,38).…”

Section: Discussionmentioning

confidence: 99%

Network Analysis of Cattle Movement in Mato Grosso Do Sul (Brazil) and Implications for Foot-and-Mouth Disease

2020

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Foot-and mouth disease (FMD) is an animal disease that generates many economic impacts and sanctions on the international market. In 2018, Brazil, the world's largest beef exporter, had the recognition by World Organization for Animal Health (OIE) as a country free of FMD with vaccination and proposed to withdraw FMD vaccination throughout the country, based on a 10-year schedule, beginning in 2019. Therefore, Brazil needs studies to help the decision-making process, particularly regarding the availability of resources for strengthening of official animal health services. The state of Mato Grosso do Sul (MS) was chosen to be analyzed for three reasons: the size of its herd, the economic importance of its livestock and its location-which lies on the border with Paraguay and Bolivia. The current study adopted the Social Network Analysis and performed an exploratory analysis of cattle movement in MS. The most central municipalities in the networks were identified and they can be seen as crucial in strategies to monitor animal movement and to control outbreaks. The cattle movement networks demonstrated to be strongly connected, implying a high-speed potential FMD diffusion, in case of reintroduction. In a second stage, we performed an exploratory analysis of animal movement within the state, assuming distinct points in time for the identification of animal origin. The results of the analysis underlined the need and relevance of investing in animal control, sanitary education for producers and equipment and technologies to assist in the early detection, diagnosis, and eradication of outbreaks in a fast and efficient manner, preventing a possible outbreak from spreading to other regions.

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Section: Discussionmentioning

confidence: 99%

Network Analysis of Cattle Movement in Mato Grosso Do Sul (Brazil) and Implications for Foot-and-Mouth Disease

2020

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“…With the null hypothesis that the outbreaks were randomly distributed against an alternate hypothesis that the outbreaks were clustered, we investigated global spatial clustering analysis using the Ripley's K-difference function. The K-function at a distance K(s) estimates the expected number of events of same type occurring within a distance s of a randomly chosen event, divided by the overall intensity of the points [21,22]. When spatial autocorrelation is present, each event is likely to be closer to other members of the same event type and for small values of distances s, K(s) will be greater than expected [23].…”

Section: Spatial Autocorrelation and Clustering Analysismentioning

confidence: 99%

Spatial and temporal epidemiology of FMD in Bhutan (2011-2019)

Letho

Compton

2023

Preprint

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Background Foot and Mouth Disease (FMD) is an important disease in livestock in Bhutan due to its significant social and economic impacts to the farmers as well as to the government. FMD outbreaks continue to occur every year with greater frequency in some parts of the country despite the implementation of control measures. It is imperative to understand the current patterns of the disease for planning effective control programs. Therefore, this study aimed to investigate the spatial and temporal patterns of FMD in Bhutan since the most recent national survey. Methodology Nine year’s (2011–2019) of national FMD outbreak data was used for this study. An investigation of global spatial autocorrelation was undertaken using the K difference function statistic and local spatial clusters of FMD outbreaks using Kulldorff’s spatial scan statistic. Retrospective spatio-temporal analysis was conducted using a Bernoulli probability model with monthly aggregation of data. A non-stationary cosinor model was used to examine seasonality and trend of outbreaks. Results The K function statistic detected significant global spatial autocorrelation of FMD outbreaks (p < 0.01) and Kulldorff’s spatial scan statistic identified two outbreak clusters in west Bhutan- the first primary cluster (p < 0.02) with relative risk (RR) of 5.22 and radius of 19.77km in Paro and Thimphu districts and the second primary cluster (p < 0.02, RR = 8.44 radius: 8.98km) in Punakha and Wangdue Phodrang districts. The spatio-temporal scan test detected a single significant (P < 0.001) space-time cluster of 22 FMD outbreaks centred in south-west Bhutan with a radius of 60 km over an 8-month period in 2018–2019. The temporal analysis indicated that, on an average there were 0.5 (95% CI: 0.2–0.8) additional outbreaks per month in the seasonal winter peaks at 1.9 months (95% CI: 12.55–3.64) compared with the overall monthly average. Conclusion The western and southern regions of Bhutan have experienced the greatest overall incidence and significant spatial and spatio-temporal clusters of outbreaks of FMD during the period 2011–2019, These findings in districts in the western medium FMD risk surveillance zone threaten progress to control of FMD in Bhutan.

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“…When there is a large number of farm holdings in the network and a data bank of animal movements is not available, we might assess the degree distribution using a questionnaire. From the estimated degree distribution, one may be interested in recovering approximately the real network to simulate, for instance, the potential spread of infectious diseases such as foot-andmouth disease and bovine brucellosis, for which the network of animal movements is an important means of dissemination [6][7][8]. Nevertheless, the process of recovering a possible real network from the estimated degree distribution may lead to a misleading inference.…”

Section: Introductionmentioning

confidence: 99%

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

Grisi-Filho

Ossada

Ferreira

et al. 2013

Physics Research International

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We have analysed some structural properties of scale-free networks with the same degree distribution. Departing from a degree distribution obtained from the Barabási-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.

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Spatial clustering analysis of the foot-and-mouth disease outbreaks in Mato Grosso do Sul state, Brazil - 2005

Abstract: In the southern region of Mato Grosso do Sul state, Brazil, a foot-and-mouth disease (FMD) epidemic started in

Cited by 7 publications

References 9 publications

Network Analysis of Cattle Movement in Mato Grosso Do Sul (Brazil) and Implications for Foot-and-Mouth Disease

Network Analysis of Cattle Movement in Mato Grosso Do Sul (Brazil) and Implications for Foot-and-Mouth Disease

Spatial and temporal epidemiology of FMD in Bhutan (2011-2019)

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

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