Spatial distribution of foot-and-mouth disease in Pakistan estimated using imperfect data

We estimated the spatial distribution of foot-and-mouth disease (FMD) in Pakistan; we used a probability co-kriging model and the number of FMD outbreaks reported between 1996 and 2000 by Pakistan to the Office International des Epizooties. We used a k-Bessel model and small-ruminant and human densities as surrogate covariates for the population at risk and for livestock markets and movements, respectively. Compared to no or only one covariate, the co-kriging model with both densities provided the best fit to independently obtained data on the spatial distribution of virus isolations (P = 0.57). The estimated probability of an FMD outbreak per 25 km² cell ranged from 0.017 to 0.812, with the maximum relative probability of 47.8 (0.812/0.017). Areas with the highest relative probability of having an FMD outbreak were located in the Punjab region; this is a major animal-production area located along a traditional international animal-trade route.     

Factors associated with spatial clustering of foot-and-mouth disease in Nepal

The purpose of this study was to quantify associations between hypothesized epidemiological factors and the spatial distribution of foot-and-mouth disease (FMD) in Nepal. Spatial clustering of reports of at least one FMD case by Village Development Committee (VDC) in 2004 was examined by use of the spatial scan statistic. A Bayesian Poisson multivariate regression model was used to quantify the association between the number of reports and 25 factors hypothesized to be associated with FMD risk. The spatial scan statistic identified (P < 0.01) two clusters of FMD reports. Large numbers of people, buffalo, and animal technicians in a district were associated with an elevated risk of a VDC reporting ≥1 FMD case. The knowledge of high-risk areas and factors associated with the risk of FMD in Nepal could be applied in future disease control programs.     

An evaluation of Foot-and-Mouth Disease outbreak reporting in mainland South-East Asia from 2000 to 2010

Foot and Mouth Disease (FMD) is considered to be endemic throughout mainland South-East Asia (SEA). The South-East Asia and China FMD (SEACFMD) campaign is a regional control programme which has been ongoing since 1997. The programme encourages countries to submit reports of outbreaks regularly. This paper evolved from a collaboration with SEACFMD to evaluate 10 years worth of reporting. All publicly available outbreak reports (5237) were extracted from the ASEAN Region Animal Health Information System (ARAHIS) for the period from 2000 to mid 2010. These reports included date, outbreak location (at the province and district level) and serotype (if known) plus information on the outbreak size and affected species. Not all records had complete information on the population at-risk or the number of animals affected. This data was transferred into a spatially enabled database (along with data from other sources) and analysed using R and SaTScan. Outbreak serotype was unknown in 2264 (43%) of reports and some countries had very few laboratory confirmed cases (range <1-86%). Outbreak reports were standardised by number of villages in each province. Outbreak intensity varied however there did not appear to be a consistent pattern, nor was there any seasonal trend in outbreaks. Spatial and spatio-temporal cluster detection methods were applied. These identified significant clusters of disease reports. FMD is endemic across the region but is not uniformly present. ARAHIS reports can be regarded as indicators of disease reporting: there may be reports in which laboratory confirmation has not occurred, and in some cases clinical signs are inconsistent with FMD. This raises questions about the specificity of the data. Advances in decentralised testing techniques offer hope for improved verification of FMD as the cause of disease outbreaks. Advances in molecular typing may provide a substantial leap forward in understanding the circulation of FMD in South East Asia.     

Temporal-spatial epidemiology of foot-and-mouth disease outbreaks in Mongolia, 2000 – 2002

Prior to 2000, foot-and-mouth disease (FMD) had not been observed in Mongolia since 1973; however, between April 2000 and July 2002, Mongolia reported 44 FMD outbreaks that affected cattle, sheep, goats, and camels. The objectives of this study were to describe the distributions of the 44 reported FMD outbreaks in Mongolia and to assess their spatial clustering and directions of movement. Official reports were collected to obtain the number and species of animals both affected and at risk, and the date and geographical coordinates of each outbreak. Significant global and local spatial clusters of reported FMD outbreaks were identified. Disease spread during the second epidemic moved 76° northeast and the spread of the disease during the third epidemic moved 110° northwest. FMD outbreaks were clustered intensely close to other FMD-positive counties. These findings can be used in the future to help plan prevention and control measures in high risk areas.     

Risk factors for foot-and-mouth disease in Zambia, 1981–2012

The aim of this study was to describe the spatial distribution of foot-and-mouth disease (FMD) outbreaks in Zambia for the period January 1981–December 2012 and to quantify the association between geographical features (proximity to roads, national parks, wetland areas) and the spatial distribution of FMD using a Poisson point process model.     

Spatial and spatial-temporal clustering analysis of hemorrhagic disease in white-tailed deer in the southeastern USA: 1980-2003

We used the space-time K function and Kulldorff's scan statistic to analyze the spatial and spatial-temporal clustering of hemorrhagic disease (HD) in white-tailed deer in Alabama, Georgia, South Carolina, North Carolina, and Tennessee. The HD occurrence data were binary presence/absence data acquired annually on a county basis from 1980 to 2003. Space-time K function was employed to globally examine the existence of spatial-temporal clustering in the HD data. Three approaches of Kulldorff's scan statistic, i.e., spatial clustering analysis for the entire period, spatial-temporal clustering analysis, and spatial clustering analysis by individual years, were applied to detect potential HD clusters. Statistically significant spatial clusters and spatial-temporal clusters were detected in the five southeastern states during the 24-year study period. Some clusters were observed in multiple years. Clusters were most evident in west Alabama, south Alabama, central South Carolina, and along the border between South Carolina and North Carolina. The identification of HD clusters may provide a means to better understand the causal factors related to the HD outbreaks. Results also have potential application in improving or designing effective surveillance programs for this disease.     

Spatio‐Temporal Scan Statistics for the Detection of Outbreaks Involving Common Molecular Subtypes: Using Human Cases of Escherichia coli O157:H7 Provincial PFGE Pattern 8 (National Designation ECXAI.0001) in Alberta as an Example

Molecular typing methods have become a common part of the surveillance of foodborne pathogens. In particular, pulsed‐field gel electrophoresis (PFGE) has been used successfully to identify outbreaks of Escherichia coli O157:H7 in humans from a variety of food and environmental sources. However, some PFGE patterns appear commonly in surveillance systems, making it more difficult to distinguish between outbreak and sporadic cases based on molecular data alone. In addition, it is unknown whether these common patterns might have unique epidemiological characteristics reflected in their spatial and temporal distributions. Using E. coli O157:H7 surveillance data from Alberta, collected from 2000 to 2002, we investigated whether E. coli O157:H7 with provincial PFGE pattern 8 (national designation ECXAI.0001) clustered in space, time and space–time relative to other PFGE patterns using the spatial scan statistic. Based on our purely spatial and temporal scans using a Bernoulli model, there did not appear to be strong evidence that isolates of E. coli O157:H7 with provincial PFGE pattern 8 are distributed differently from other PFGE patterns. However, we did identify space–time clusters of isolates with PFGE pattern 8, using a Bernoulli model and a space–time permutation model, which included known outbreaks and potentially unrecognized outbreaks or additional outbreak cases. There were differences between the two models in the space–time clusters identified, which suggests that the use of both models could increase the sensitivity of a quantitative surveillance system for identifying outbreaks involving isolates sharing a common PFGE pattern.     

Spatial clustering of swine influenza in Ontario on the basis of herd-level disease status with different misclassification errors

This approach maximizes sensitivity of serology-based monitoring systems by considering spatial clustering of herds classified as false positive by herd testing, allowing outbreaks to be detected in an early phase. The primary objective of this study was to determine whether swine herds infected with influenza viruses cluster in space, and if so, where they cluster. The secondary objective was to investigate the combining of a multivariate spatial scan statistic with herd test results to maximize the sensitivity of the surveillance system for swine influenza. We tested for spatial clustering of swine influenza using the Cuzick–Edwards test as a global test. The location of the most likely spatial clusters of cases for each subtype and strain in a sample of 65 sow and 72 finisher herds in 2001 (Ontario, Canada), and 76 sow herds in 2003 (Ontario, Canada) was determined by a spatial scan statistic in a purely spatial Bernoulli model based on single and multiple datasets.

A case herd was defined by true herd-disease status for sow or finisher herds tested for H1N1, and by apparent herd-disease status for sow herds tested for two H3N2 strains (A/Swine/Colorado/1/77 (Sw/Col/77) and A/Swine/Texas/4199-2/98 (Sw/Tex/98)). In sow herds, there was no statistically significant clustering of H1N1 influenza after adjustment for pig-farm density. Similarly, spatial clustering was not found in finisher herds. In contrast, clustering of H3N2 Sw/Col/77 (prevalence ratio = 12.5) and H3N2 Sw/Tex/98 (prevalence ratio = 15) was identified in an area close to a region with documented isolation of avian influenza isolates from pigs.

For the H1N1 subtype tested by ELISA, we used an approach that minimized overall misclassification at the herd level. This could be more applicable for detecting clusters of positive farms when herd prevalence is moderate to high than when herd prevalence is low. For the H3N2 strains we used an approach that maximized herd-level sensitivity by minimizing the herd cut-off. This is useful in situations where prevalence of the pathogen is low. The results of applying a multivariate spatial scan statistic approach, led us to generate the hypothesis that an unknown variant of influenza of avian origin was circulating in swine herds close to an area where avian strains had previously been isolated from swine. Maximizing herd sensitivity and linking it with the spatial information can be of use for monitoring of pathogens that exhibit the potential for rapid antigenic change, which, consequently, might then lead to diminished cross-reactivity of routinely used assays and lower test sensitivity for the newly emerged variants. Veterinary authorities might incorporate this approach into animal disease surveillance programs that either substantiate freedom from disease, or are aimed at detecting early incursion of a pathogen, such as influenza virus, or both.     

Herd demographics correlated with the spatial distribution of a foot-and-mouth disease epidemic in Buenos Aires province, Argentina

During a recent foot-and-mouth disease epidemic in Argentina, cattle herds affected in 2001 were located mainly (69%) in Buenos Aires province. The densities of outbreaks (no. of outbreaks per km²) and cattle-demographic variables in the province were estimated using a geographical information system and kernel function. Before the epidemic officially was recognized, the density of outbreaks was correlated (r_sp = 0.28–0.47) with the geographic distribution of small (≤100 cattle), dairy and fattening herds. During the mass-vaccination campaign to control the epidemic (April–July), the density of outbreaks was most strongly correlated (r_sp = 0.20–0.25) with the distribution of large (>500 cattle) and breeding herds. After the end of the mass-vaccination campaign, large herds and number of cows were most strongly correlated (r_sp = 0.16–0.26) with outbreak density. These relationships might indicate that: (1) the disease spread more rapidly or was more easily detected in intensive production systems at the beginning of the epidemic; (2) vaccination and other control methods applied were less effective in large, semi-intensive production systems; (3) incomplete vaccine protection was responsible for herd outbreaks that occurred after the end of the mass-vaccination campaign.     

A temporal-spatial analysis of bovine spongiform encephalopathy in Irish cattle herds, from 1996 to 2000

This study investigated the distribution of bovine spongiform encephalopathy (BSE) in herds of cattle in Ireland over the years 1996 through 2000, prior to the introduction of widespread active surveillance. Mappings of index herds, herd density, and standardized morbidity ratios, by county, were employed to help visualize areas of potential clustering of BSE. The hypothesis of spatial clustering was tested using a spatial scan statistic applied to the location of the herd where exposure likely occurred. Both Bernoulli and Poisson spatial models indicated marked clustering of BSE herds centred on Monaghan county, with secondary clusters detected by Bernoulli approaches and some Poisson models in Wexford and Cork. The number of cases increased with time, but clear temporal-spatial clusters were rarely detected, except in the case of a cluster in Wexford. The focussed spatial scan analyses using the location of large-scale feed suppliers provided support for the hypothesis that clustering of BSE may be associated with feed source. The results of our analyses provided strong evidence in support of the hypothesis that herds, in which animals were most likely to have been exposed to the BSE agent, cluster geographically.     

Epidemiological investigations of the 2001 foot-and-mouth disease outbreak in Argentina

A total of 2126 herds, an attack rate of 0.82 per cent, were affected during an epidemic of foot-and-mouth disease in Argentina in 2001. The spatial and temporal distribution of the epidemic was investigated using nearest-neighbour and spatial scan tests and by estimating the frequency distributions of the times to intervention, and distances and times between outbreaks. The outbreaks were clustered and associated significantly (P<0.01) with herd density; 94 per cent were located in the Pampeana region, where the cattle population is concentrated, which had an attack rate of 1.4 per cent. The clustering results suggested that the virus had spread locally between outbreaks. Most of the outbreaks were separated by one day and the maximum distance between outbreaks was almost 2000 km, indicating that the infection spread rapidly over large distances. The index outbreak was detected more than 15 days after the primary outbreak, and restrictions on the movement of cattle were probably not enforced until about one month after infection occurred. As in other major epidemics, the period between the first outbreaks and the effective application of control strategies was probably crucial in determining the progress of the epidemic.     

多年生人工草地矮生嵩草(Kobresia humilis)种群空间格局与种内关联性

植物种群空间分布格局不仅反映植物的空间分布特点,还有助于研究者了解植物利用资源的现状和生存能力。本研究以矮生嵩草(Kobresia humilis)为研究对象,按株丛斑块面积将矮生嵩草分为小斑块级株丛(0～30 cm²)、中斑块级株丛(30～80 cm²)和大斑块级株丛(>80 cm²)3个株丛级,采用点格局分析的g函数统计方法,分析了矮生嵩草各级株丛的空间格局及关联性。结果表明：矮生嵩草种群中小斑块级株丛占比高于中斑块、大斑块级株丛占比,种群中幼苗充足,正处于稳定的增长阶段;矮生嵩草小斑块、中斑块、大斑块级株丛在小尺度范围内表现为聚集分布,随着尺度的增大,所有株丛斑块的聚集程度减弱,逐渐趋向于随机分布;小斑块与中斑块、大斑块的矮生嵩草株丛在小尺度内表现为正关联。斑块聚集分布和相互共存是矮生嵩草的一种生存策略。     

Geographic distribution of BSE in Switzerland

Visual evaluation of the occurrence of BAB (born after ban) cases pointed towards spatial clustering. Therefore a statistical analysis of spatial case clustering was conducted using GIS technology. In the initial analysis, all 376 cases (135 BAB, 241 BBB/born before ban) diagnosed through mid of March 2001 were investigated using the spatial scan statistic. Two clusters of BBB cases were identified in the western part of Switzerland, and two clusters of BAB cases in the eastern part. Epidemiological investigations performed within the BAB clusters showed an increased pig density in these cluster regions. Pig density is considered an indicator for the probability of contamination of cattle feed with feed containing meat-and-bone meal that is intended for other species (cross-contamination). In an updated cluster analysis including all cases reported until end of June 2002 (data set B), clusters were identified in the same regions as previously. It was shown that the BAB clusters occurred in different time periods. The small scale differences in cluster size and location are discussed, with an emphasis on the implications for following epidemiological investigations.     

Effectiveness of vaccines and vaccination programs for the control of foot-and-mouth disease in Uganda, 2001–2010

Foot-and-mouth disease (FMD) is a highly contagious disease of cloven-hoofed animals. In Uganda, FMD outbreaks are mainly controlled by ring vaccination and restriction of animal movements. Vaccination stimulates immunity and prevents animals from developing clinical signs which include lameness, inappetence, and decreased production. Ring vaccination and restriction of animal movements have, however, not successfully controlled FMD in Uganda and outbreaks reoccur annually. The objective of this study was to review the use of FMD virus (FMDV) vaccines and assess the effectiveness of vaccination programs for controlling FMD in Uganda (2001–2010), using retrospective data. FMD vaccine distribution patterns in Uganda (2001–2010) matched occurrence of outbreaks with districts reporting the highest number of outbreaks also receiving the largest quantity of vaccines. This was possibly due to “fire brigade” response of vaccinating animals after outbreaks have been reported. On average, only 10.3 % of cattle within districts that reported outbreaks during the study period were vaccinated. The average minimum time between onset of outbreaks and vaccination was 7.5 weeks, while the annual cost of FMDV vaccines used ranged from US $58,000 to 1,088,820. Between 2001 and 2010, serotyping of FMD virus was done in only 9/121 FMD outbreaks, and there is no evidence that vaccine matching or vaccine potency tests have been done in Uganda. The probability of FMDV vaccine and outbreak mismatch, the delayed response to outbreaks through vaccination, and the high costs associated with importation of FMDV vaccines could be reduced if virus serotyping and subtyping as well as vaccine matching were regularly done, and the results were considered for vaccine manufacture.     

A review of geospatial and ecological factors affecting disease spread in wild pigs: considerations for models of foot-and-mouth disease spread

Around the world, wild boar or feral pigs are infected by a range of infectious organisms with important, productivity, public health or economic consequences. Consequently, the potential role of wild pigs in outbreaks of important exotic diseases, like foot-and-mouth disease (FMD), has been a significant consideration in many countries. Disease modelling is one means to study the epidemiology of disease and has been used to assess the potential role of wild pigs in FMD incursions. Many of these models have been strategic in nature. They have contributed to a broad understanding of disease control in wild pigs (e.g. the concept of threshold densities and the need to cull pigs below this density for disease fadeout to occur), but have not incorporated many of the key drivers affecting disease behaviour. Some of these drivers include important ecological, behavioural and geospatial relationships, such as interaction between different host species and the distribution, density and connectivity of pig populations. New approaches to modelling disease spread such as spatial simulation models use spatial data and explicitly incorporate geospatial relationships. These approaches can provide useful quantitative models that can be used to explore mitigation strategies under specific disease outbreak conditions. However, to date, most studies have been limited by inadequate data, and computational issues or have not explored mitigation strategies. To inform management strategies for emergency epidemics such as FMD in wild pigs, there is scope to further develop and use models to explore a range of incursion scenarios and investigate the efficacy of different mitigation strategies.     

Epidemiological simulation modeling and spatial analysis for foot-and-mouth disease control strategies: a comprehensive review

Foot-and-mouth disease (FMD) is one of the most serious transboundary, contagious viral diseases of cloven-hoofed livestock, because it can spread rapidly with high morbidity rates when introduced into disease-free herds or areas. Epidemiological simulation modeling can be developed to study the hypothetical spread of FMD and to evaluate potential disease control strategies that can be implemented to decrease the impact of an outbreak or to eradicate the virus from an area. Spatial analysis, a study of the distributions of events in space, can be applied to an area to investigate the spread of animal disease. Hypothetical FMD outbreaks can be spatially analyzed to evaluate the effect of the event under different control strategies. The main objective of this paper is to review FMD-related articles on FMD epidemiology, epidemiological simulation modeling and spatial analysis with the focus on disease control. This review will contribute to the development of models used to simulate FMD outbreaks under various control strategies, and to the application of spatial analysis to assess the outcome of FMD spread and its control.     

Estimating the risk of importation of foot-and-mouth disease into Europe

The opinions of a number of recognised world experts on foot-and-mouth disease (FMD) were sought in order to answer key questions relating to the importation of the disease into European countries from countries outside Europe. In addition, their opinions were sought on where in Europe a primary outbreak of FMD was most likely to occur and the number of outbreaks likely to occur within European countries in the next five years. The Balkans group of countries was considered to be the most likely group within Europe to have a primary outbreak of FMD and also most likely to have the highest number of primary outbreaks. Turkey was considered to be the country outside Europe which was most likely to be the source of an outbreak within Europe as a whole, and the illegal importation of livestock was considered to be the most likely route of introduction of FMD into Europe. Results specific to the Islands group of countries, which included the UK and Ireland, suggested that this group was likely to have a mean of one primary outbreak of FMD in the five years from September 2000, and that the importation of foodstuffs by people entering those countries from Turkey was the most likely source of an outbreak.