Incorporating retrospective clustering into a prospective cusum methodology for anthrax: Evaluating the effects of disease expectation

Kracalik, Ian; Lukhnova, Larissa; Aikimbayev, Alim; Pazilov, Yerlan; Temiralyeva, Gulnara; Blackburn, Jason K.

doi:10.1016/j.sste.2010.06.001

Cited by 15 publications

(8 citation statements)

References 53 publications

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“…Future research should focus on collecting individual level data on human and livestock anthrax following Roth et al [19] and Zinsstag et al [54] to better formulate public health interventions for anthrax in Azerbaijan and the neighboring countries. The changing patterns of anthrax identified here illustrates the need for dynamic surveillance that takes into account alterations in the distribution of disease over time [55]. Areas of high incidence identified in this study can be used to target interventions such as livestock vaccination, veterinary outreach, and education campaigns targeting the human population at risk.…”

Section: Discussionmentioning

confidence: 90%

Changing Patterns of Human Anthrax in Azerbaijan during the Post-Soviet and Preemptive Livestock Vaccination Eras

Kracalik

Abdullayev²,

Asadov³

et al. 2014

PLoS Negl Trop Dis

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We assessed spatial and temporal changes in the occurrence of human anthrax in Azerbaijan during 1984 through 2010. Data on livestock outbreaks, vaccination efforts, and human anthrax incidence during Soviet governance, post-Soviet governance, preemptive livestock vaccination were analyzed. To evaluate changes in the spatio-temporal distribution of anthrax, we used a combination of spatial analysis, cluster detection, and weighted least squares segmented regression. Results indicated an annual percent change in incidence of +11.95% from 1984 to 1995 followed by declining rate of −35.24% after the initiation of livestock vaccination in 1996. Our findings also revealed geographic variation in the spatial distribution of reporting; cases were primarily concentrated in the west early in the study period and shifted eastward as time progressed. Over twenty years after the dissolution of the Soviet Union, the distribution of human anthrax in Azerbaijan has undergone marked changes. Despite decreases in the incidence of human anthrax, continued control measures in livestock are needed to mitigate its occurrence. The shifting patterns of human anthrax highlight the need for an integrated “One Health” approach that takes into account the changing geographic distribution of the disease.

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Section: Discussionmentioning

confidence: 90%

Changing Patterns of Human Anthrax in Azerbaijan during the Post-Soviet and Preemptive Livestock Vaccination Eras

Kracalik

Abdullayev²,

Asadov³

et al. 2014

PLoS Negl Trop Dis

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“…These data were obtained from a larger database development effort in collaboration with the Kazakh Science Center for Quarantine and Zoonotic Disease in Almaty, Kazakhstan, described in detail elsewhere (Aikembayev et al, 2010;Joyner et al, 2010;Kracalik et al, 2011). The data were divided into livestock groups based on results of Aikimbayev et al (2010), which suggested that cases within each group where distributed differently.…”

Section: Geographical Information Systems (Gis) Database Developmentmentioning

confidence: 99%

“…However, researchers have shown that incorporating cluster analyses with statistical models such as logistic regression may better assess the level of risk (Ruiz et al, 2004). We used a long historical record of anthrax outbreaks in livestock from Kazakhstan (Aikembayev et al, 2010;Kracalik et al, 2011) to uncover possible spatial clustering while also trying to elucidate environmental factors associated with areas of high anthrax outbreaks.…”

Section: Introductionmentioning

confidence: 99%

Analysing the spatial patterns of livestock anthrax in Kazakhstan in relation to environmental factors: a comparison of local (Gi*) and morphology cluster statistics

et al. 2012

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Abstract. We compared a local clustering and a cluster morphology statistic using anthrax outbreaks in large (cattle) and small (sheep and goats) domestic ruminants across Kazakhstan. The Getis-Ord (G i *) statistic and a multidirectional optimal ecotope algorithm (AMOEBA) were compared using 1 st , 2 nd and 3 rd order Rook contiguity matrices. Multivariate statistical tests were used to evaluate the environmental signatures between clusters and non-clusters from the AMOEBA and G i * tests. A logistic regression was used to define a risk surface for anthrax outbreaks and to compare agreement between clustering methodologies. Tests revealed differences in the spatial distribution of clusters as well as the total number of clusters in large ruminants for AMOEBA (n = 149) and for small ruminants (n = 9). In contrast, G i * revealed fewer large ruminant clusters (n = 122) and more small ruminant clusters (n = 61). Significant environmental differences were found between groups using the Kruskall-Wallis and MannWhitney U tests. Logistic regression was used to model the presence/absence of anthrax outbreaks and define a risk surface for large ruminants to compare with cluster analyses. The model predicted 32.2% of the landscape as high risk. Approximately 75% of AMOEBA clusters corresponded to predicted high risk, compared with ~64% of G i * clusters. In general, AMOEBA predicted more irregularly shaped clusters of outbreaks in both livestock groups, while G i * tended to predict larger, circular clusters. Here we provide an evaluation of both tests and a discussion of the use of each to detect environmental conditions associated with anthrax outbreak clusters in domestic livestock. These findings illustrate important differences in spatial statistical methods for defining local clusters and highlight the importance of selecting appropriate levels of data aggregation.

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“…15 The modeling system has been defined in detail elsewhere. 16 Briefly, GARP is an iterative algorithm that searches for nonrandom relationships between point occurrences and environmental data. GARP develops a series of if/then logic statements, called rules that use one of four types (range, negated range, atomic, or logistic regression) to describe presence or absence of the target species in ecological space.…”

Section: Methodsmentioning

confidence: 99%

Modeling the Ecological Niche of Bacillus anthracis to Map Anthrax Risk in Kyrgyzstan

Blackburn¹,

Matakarimov²,

Kozhokeeva³

et al. 2017

The American Society of Tropical Medicine and Hygiene

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Abstract. Anthrax, caused by the environmental bacterium Bacillus anthracis, is an important zoonosis nearly worldwide. In Central Asia, anthrax represents a major veterinary and public health concern. In the Republic of Kyrgyzstan, ongoing anthrax outbreaks have been reported in humans associated with handling infected livestock and contaminated animal by-products such as meat or hides. The current anthrax situation has prompted calls for improved insights into the epidemiology, ecology, and spatial distribution of the disease in Kyrgyzstan to better inform control and surveillance. Disease control for both humans and livestock relies on annual livestock vaccination ahead of outbreaks. Toward this, we used a historic database of livestock anthrax reported from 1932 to 2006 mapped at high resolution to develop an ecological niche model-based prediction of B. anthracis across Kyrgyzstan and identified spatial clusters of livestock anthrax using a cluster morphology statistic. We also defined the seasonality of outbreaks in livestock. Cattle were the most frequently reported across the time period, with the greatest number of cases in late summer months. Our niche models defined four areas as suitable to support pathogen persistence, the plateaus near Talas and Bishkek, the valleys of western Kyrgyzstan along the Fergana Valley, and the low-lying areas along the shore of Lake Isyk-Kul. These areas should be considered "at risk" for livestock anthrax and subsequent human cases. Areas defined by the niche models can be used to prioritize anthrax surveillance and inform efforts to target livestock vaccination campaigns.

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Incorporating retrospective clustering into a prospective cusum methodology for anthrax: Evaluating the effects of disease expectation

Cited by 15 publications

References 53 publications

Changing Patterns of Human Anthrax in Azerbaijan during the Post-Soviet and Preemptive Livestock Vaccination Eras

Changing Patterns of Human Anthrax in Azerbaijan during the Post-Soviet and Preemptive Livestock Vaccination Eras

Analysing the spatial patterns of livestock anthrax in Kazakhstan in relation to environmental factors: a comparison of local (Gi*) and morphology cluster statistics

Modeling the Ecological Niche of Bacillus anthracis to Map Anthrax Risk in Kyrgyzstan

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