Quantitative Models of the Dose-Response and Time Course of Inhalational Anthrax in Humans

Anthrax poses a community health risk due to accidental or intentional aerosol release. Reliable quantitative dose-response analyses are required to estimate the magnitude and timeline of potential consequences and the effect of public health intervention strategies under specific scenarios. Analyses of available data from exposures and infections of humans and non-human primates are often contradictory. We review existing quantitative inhalational anthrax dose-response models in light of criteria we propose for a model to be useful and defensible. To satisfy these criteria, we extend an existing mechanistic competing-risks model to create a novel Exposure–Infection–Symptomatic illness–Death (EISD) model and use experimental non-human primate data and human epidemiological data to optimize parameter values. The best fit to these data leads to estimates of a dose leading to infection in 50% of susceptible humans (ID₅₀) of 11,000 spores (95% confidence interval 7,200–17,000), ID₁₀ of 1,700 (1,100–2,600), and ID₁ of 160 (100–250). These estimates suggest that use of a threshold to human infection of 600 spores (as suggested in the literature) underestimates the infectivity of low doses, while an existing estimate of a 1% infection rate for a single spore overestimates low dose infectivity. We estimate the median time from exposure to onset of symptoms (incubation period) among untreated cases to be 9.9 days (7.7–13.1) for exposure to ID₅₀, 11.8 days (9.5–15.0) for ID₁₀, and 12.1 days (9.9–15.3) for ID₁. Our model is the first to provide incubation period estimates that are independently consistent with data from the largest known human outbreak. This model refines previous estimates of the distribution of early onset cases after a release and provides support for the recommended 60-day course of prophylactic antibiotic treatment for individuals exposed to low doses.     

The statistical analysis of truncated data: application to the Sverdlovsk anthrax outbreak

An outbreak of anthrax occurred in the city of Sverdlovsk in Russia in the spring of 1979. The outbreak was due to the inhalation of spores that were accidentally released from a military microbiology facility. In response to the outbreak a public health intervention was mounted that included distribution of antibiotics and vaccine. The objective of this paper is to develop and apply statistical methodology to analyse the Sverdlovsk outbreak, and in particular to estimate the incubation period of inhalational anthrax and the number of deaths that may have been prevented by the public health intervention. The data available for analysis from this common source epidemic are the incubation periods of reported deaths. The statistical problem is that incubation periods are truncated because some individuals may have had their deaths prevented by the public health interventions and thus are not included in the data. However, it is not known how many persons received the intervention or how efficacious was the intervention. A likelihood function is formulated that accounts for the effects of truncation. The likelihood is decomposed into a binomial likelihood with unknown sample size and a conditional likelihood for the incubation periods. The methods are extended to allow for a phase-in of the intervention over time. Assuming a lognormal model for the incubation period distribution, the median and mean incubation periods were estimated to be 11.0 and 14.2 days respectively. These estimates are longer than have been previously reported in the literature. The death toll from the Sverdlovsk anthrax outbreak could have been about 14% larger had there not been a public health intervention; however, the confidence intervals are wide (95% CI 0-61%). The sensitivity of the results to model assumptions and the parametric model for the incubation period distribution are investigated. The results are useful for determining how long antibiotic therapy should be continued in suspected anthrax cases and also for estimating the ultimate number of deaths in a new outbreak in the absence of any public health interventions.     

Rumen-protected conjugated linoleic acid supplementation to dairy cows in late pregnancy and early lactation: effects on milk composition,milk yield,blood metabolites and gene expression in liver

After 27 years with no detected cases, an outbreak of anthrax occurred in a beef cattle herd in the south of Sweden. The outbreak was unusual as it occurred in winter, in animals not exposed to meat-and-bone meal, in a non-endemic country. The affected herd consisted of 90 animals, including calves and young stock. The animals were kept in a barn on deep straw bedding and fed only roughage. Seven animals died during 10 days, with no typical previous clinical signs except fever. The carcasses were reportedly normal in appearance, particularly as regards rigor mortis, bleeding and coagulation of the blood. Subsequently, three more animals died and anthrax was suspected at necropsy and confirmed by culture and PCR on blood samples. The isolated strain was susceptible to tetracycline, ciprofloxacin and ampicillin. Subtyping by MLVA showed the strain to cluster with isolates in the A lineage of Bacillus anthracis. Environmental samples from the holding were all negative except for two soil samples taken from a spot where infected carcasses had been kept until they were picked up for transport. The most likely source of the infection was concluded to be contaminated roughage, although this could not be substantiated by laboratory analysis. The suspected feed was mixed with soil and dust and originated from fields where flooding occurred the previous year, followed by a dry summer with a very low water level in the river allowing for the harvesting on soil usually not exposed. In the early 1900s, animal carcasses are said to have been dumped in this river during anthrax outbreaks and it is most likely that some anthrax spores could remain in the area. The case indicates that untypical cases in non-endemic areas may be missed to a larger extent than previously thought. Field tests allowing a preliminary risk assessment of animal carcasses would be helpful for increased sensitivity of detection and prevention of further exposure to the causative agent.     

Experiences with vaccination and epidemiological investigations on an anthrax outbreak in Australia in 1997

Between January and February 1997, there was a severe outbreak of anthrax on 83 properties in north-central Victoria, Australia. Vaccination was used as a major tool to control the outbreak by establishing a vaccination buffer zone 30 km by 20 km. In all, 78, 649 cattle in 457 herds were vaccinated in a three week program. In the face of the outbreak, there was a delay before vaccination was able to stop deaths. In the 10 days following vaccination 144 cases of confirmed anthrax occurred and 38 cases occurred more than 10 days after vaccination. When all cattle on at-risk properties were revaccinated in October and early November 1997, there were only two confirmed cases of anthrax in vaccinated seven and nine month old calves in the following anthrax season. Investigations into the epidemiology of the outbreak were unable to establish a single major association for the spread of the disease by flies, biting insects, carrion scavengers, wind, manufactured feed, milk factory tanker routes, veterinary visits, animal treatments, movements of personnel between farms or burning of carcases. The weather conditions in the outbreak area were part of a long dry spell with periods of high daily and night temperatures, continuing high humidity over the period and higher than normal soil temperatures. It is possible that extensive earth works in the district involving irrigated pasture renovation and water channel and drainage renovation could have disturbed old anthrax graves. It is postulated that these works released spores that were dispersed in the preceding wet winter across poorly drained areas that formed the axis for the outbreak. The earth moving renovations establishing irrigation in the area were conducted in the late 1890s, and before the occurrence of anthrax outbreaks were recorded. The axis of the outbreak was the major stock route for cattle and sheep moving from southern Victoria to northern Victoria and southern New South Wales, and undoubtedly there would have been extensive anthrax outbreaks before vaccine became available in the 1890s. In respect of other outbreaks, the events in Victoria most resembled outbreaks of anthrax recorded in the United States of America in the 1950s, 1960s and 1970s.     

Variational data assimilation with epidemic models

Mathematical modelling is playing an increasing role in developing an understanding of the dynamics of communicable disease and assisting the construction and implementation of intervention strategies. The threat of novel emergent pathogens in human and animal hosts implies the requirement for methods that can robustly estimate epidemiological parameters and provide forecasts. Here, a technique called variational data assimilation is introduced as a means of optimally melding dynamic epidemic models with epidemiological observations and data to provide forecasts and parameter estimates. Using data from a simulated epidemic process the method is used to estimate the start time of an epidemic, to provide a forecast of future epidemic behaviour and estimate the basic reproductive ratio. A feature of the method is that it uses a basic continuous-time SIR model, which is often the first point of departure for epidemiological modelling during the early stages of an outbreak. The method is illustrated by application to data gathered during an outbreak of influenza in a school environment.     

Using models to identify routes of nosocomial infection: a large hospital outbreak of SARS in Hong Kong

Two factors dominated the epidemiology of severe acute respiratory syndrome (SARS) during the 2002-2003 global outbreak, namely super-spreading events (SSE) and hospital infections. Although both factors were important during the first and the largest hospital outbreak in Hong Kong, the relative importance of different routes of infection has not yet been quantified. We estimated the parameters of a novel mathematical model of hospital infection using SARS episode data. These estimates described levels of transmission between the index super-spreader, staff and patients, and were used to compare three plausible hypotheses. The broadest of the supported hypotheses ascribes the initial surge in cases to a single super-spreading individual and suggests that the per capita risk of infection to patients increased approximately one month after the start of the outbreak. Our estimate for the number of cases caused by the SSE is substantially lower than the previously reported values, which were mostly based on self-reported exposure information. This discrepancy suggests that the early identification of the index case as a super-spreader might have led to biased contact tracing, resulting in too few cases being attributed to staff-to-staff transmission. We propose that in future outbreaks of SARS or other directly transmissible respiratory pathogens, simple mathematical models could be used to validate preliminary conclusions concerning the relative importance of different routes of transmission with important implications for infection control.     

Anthrax explodes in an Australian summer

Anthrax occurred on 83 properties in an area of north central Victoria between 26 January and 26 March in the summer of 1997. Anthrax had not been recorded in the outbreak area since records were initiated in 1914, although anthrax did occur in the general area in the 1880s to 1890s. Standard Australian control measures were applied to the properties, including quarantine, tracing movements of animals on and off affected properties, secure disposal of carcases by burning, enhanced surveillance of stock generally in the area and the use of local disaster control procedures including an alert of health authorities. As affected property numbers began to increase dramatically from 8 February, it was decided to use blanket area vaccination to control the disease. By 26 February, the epidemic curve had returned to the base line and a buffer vaccination zone of 457 farms holding 78,649 cattle was formed by early March 1997. Between 26 January and 26 March when the outbreak was declared over, 202 cattle and 4 sheep were confirmed to have died of anthrax. Between 27 March and early November a further 26 cattle were confirmed as dying due to anthrax and 14 of these had not had previous vaccination, including four young calves and one horse. One new property within the vaccination buffer zone had an anthrax case in a cow in early November 1997. By mid-November 1997, all previously infected and all neighbouring properties within 1 km were compulsorily re-vaccinated, as were all calves when two months of age and all introduced cattle. In 1998, only two confirmed cases of anthrax were diagnosed; both were vaccinated calves on farms which had had multiple cases during the outbreak. The public reaction and attention fueled by unprecedented media attention led to intense international scrutiny from countries where anthrax is a particular zoonotic problem. Very strong representations had to be made about the safety of livestock and livestock products that came from Victoria. This event has demonstrated that there is a need to review OIE and other requirements and recommendations covering anthrax where strict restrictions are placed on livestock and livestock products to protect livestock and human populations against anthrax infection.     

Avoidable errors in the modelling of outbreaks of emerging pathogens, with special reference to Ebola

As an emergent infectious disease outbreak unfolds, public health response is reliant on information on key epidemiological quantities, such as transmission potential and serial interval. Increasingly, transmission models fit to incidence data are used to estimate these parameters and guide policy. Some widely used modelling practices lead to potentially large errors in parameter estimates and, consequently, errors in model-based forecasts. Even more worryingly, in such situations, confidence in parameter estimates and forecasts can itself be far overestimated, leading to the potential for large errors that mask their own presence. Fortunately, straightforward and computationally inexpensive alternatives exist that avoid these problems. Here, we first use a simulation study to demonstrate potential pitfalls of the standard practice of fitting deterministic models to cumulative incidence data. Next, we demonstrate an alternative based on stochastic models fit to raw data from an early phase of 2014 West Africa Ebola virus disease outbreak. We show not only that bias is thereby reduced, but that uncertainty in estimates and forecasts is better quantified and that, critically, lack of model fit is more readily diagnosed. We conclude with a short list of principles to guide the modelling response to future infectious disease outbreaks.     

Does the punishment fit the crime? Consequences and diagnosis of misspecified detection functions in Bayesian spatial capture–recapture modeling

Spatial capture–recapture (SCR) analysis is now used routinely to inform wildlife management and conservation decisions. It is therefore imperative that we understand the implications of and can diagnose common SCR model misspecifications, as flawed inferences could propagate to policy and interventions. The detection function of an SCR model describes how an individual''s detections are distributed in space. Despite the detection function''s central role in SCR, little is known about the robustness of SCR‐derived abundance estimates and home range size estimates to misspecifications. Here, we set out to (a) determine whether abundance estimates are robust to a wider range of misspecifications of the detection function than previously explored, (b) quantify the sensitivity of home range size estimates to the choice of detection function, and (c) evaluate commonly used Bayesian p‐values for detecting misspecifications thereof. We simulated SCR data using different circular detection functions to emulate a wide range of space use patterns. We then fit Bayesian SCR models with three detection functions (half‐normal, exponential, and half‐normal plateau) to each simulated data set. While abundance estimates were very robust, estimates of home range size were sensitive to misspecifications of the detection function. When misspecified, SCR models with the half‐normal plateau and exponential detection functions produced the most and least reliable home range size, respectively. Misspecifications with the strongest impact on parameter estimates were easily detected by Bayesian p‐values. Practitioners using SCR exclusively for density estimation are unlikely to be impacted by misspecifications of the detection function. However, the choice of detection function can have substantial consequences for the reliability of inferences about space use. Although Bayesian p‐values can aid the diagnosis of detection function misspecification under certain conditions, we urge the development of additional custom goodness‐of‐fit diagnostics for Bayesian SCR models to identify a wider range of model misspecifications.     

Estimating individual and household reproduction numbers in an emerging epidemic

Reproduction numbers, defined as averages of the number of people infected by a typical case, play a central role in tracking infectious disease outbreaks. The aim of this paper is to develop methods for estimating reproduction numbers which are simple enough that they could be applied with limited data or in real time during an outbreak. I present a new estimator for the individual reproduction number, which describes the state of the epidemic at a point in time rather than tracking individuals over time, and discuss some potential benefits. Then, to capture more of the detail that micro-simulations have shown is important in outbreak dynamics, I analyse a model of transmission within and between households, and develop a method to estimate the household reproduction number, defined as the number of households infected by each infected household. This method is validated by numerical simulations of the spread of influenza and measles using historical data, and estimates are obtained for would-be emerging epidemics of these viruses. I argue that the household reproduction number is useful in assessing the impact of measures that target the household for isolation, quarantine, vaccination or prophylactic treatment, and measures such as social distancing and school or workplace closures which limit between-household transmission, all of which play a key role in current thinking on future infectious disease mitigation.     

A Model for a Chikungunya Outbreak in a Rural Cambodian Setting: Implications for Disease Control in Uninfected Areas

Following almost 30 years of relative silence, chikungunya fever reemerged in Kenya in 2004. It subsequently spread to the islands of the Indian Ocean, reaching Southeast Asia in 2006. The virus was first detected in Cambodia in 2011 and a large outbreak occurred in the village of Trapeang Roka Kampong Speu Province in March 2012, in which 44% of the villagers had a recent infection biologically confirmed. The epidemic curve was constructed from the number of biologically-confirmed CHIKV cases per day determined from the date of fever onset, which was self-reported during a data collection campaign conducted in the village after the outbreak. All individuals participating in the campaign had infections confirmed by laboratory analysis, allowing for the identification of asymptomatic cases and those with an unreported date of fever onset. We develop a stochastic model explicitly including such cases, all of whom do not appear on the epidemic curve. We estimate the basic reproduction number of the outbreak to be 6.46 (95% C.I. [6.24, 6.78]). We show that this estimate is particularly sensitive to changes in the biting rate and mosquito longevity. Our model also indicates that the infection was more widespread within the population on the reported epidemic start date. We show that the exclusion of asymptomatic cases and cases with undocumented onset dates can lead to an underestimation of the reproduction number which, in turn, could negatively impact control strategies implemented by public health authorities. We highlight the need for properly documenting newly emerging pathogens in immunologically naive populations and the importance of identifying the route of disease introduction.     

Spatially resolved simulations of the spread of COVID-19 in three European countries

We explore the spatial and temporal spread of the novel SARS-CoV-2 virus under containment measures in three European countries based on fits to data of the early outbreak. Using data from Spain and Italy, we estimate an age dependent infection fatality ratio for SARS-CoV-2, as well as risks of hospitalization and intensive care admission. We use them in a model that simulates the dynamics of the virus using an age structured, spatially detailed agent based approach, that explicitly incorporates governmental interventions and changes in mobility and contact patterns occurred during the COVID-19 outbreak in each country. Our simulations reproduce several of the features of its spatio-temporal spread in the three countries studied. They show that containment measures combined with high density are responsible for the containment of cases within densely populated areas, and that spread to less densely populated areas occurred during the late stages of the first wave. The capability to reproduce observed features of the spatio-temporal dynamics of SARS-CoV-2 makes this model a potential candidate for forecasting the dynamics of SARS-CoV-2 in other settings, and we recommend its application in low and lower-middle income countries which remain understudied.     

Key Role of Sequencing to Trace Hepatitis A Viruses Circulating in Italy During a Large Multi-Country European Foodborne Outbreak in 2013

Background

Foodborne Hepatitis A Virus (HAV) outbreaks are being recognized as an emerging public health problem in industrialized countries. In 2013 three foodborne HAV outbreaks occurred in Europe and one in USA. During the largest of the three European outbreaks, most cases occurred in Italy (>1,200 cases as of March 31, 2014). A national Task Force was established at the beginning of the outbreak by the Ministry of Health. Mixed frozen berries were early demonstrated to be the source of infection by the identity of viral sequences in patients and in food. In the present study the molecular characterization of HAV isolates from 355 Italian cases is reported.

Methods

Molecular characterization was carried out by PCR/sequencing (VP1/2A region), comparison with reference strains and phylogenetic analysis.

Results

A unique strain was responsible for most characterized cases (235/355, 66.1%). Molecular data had a key role in tracing this outbreak, allowing 110 out of the 235 outbreak cases (46.8%) to be recognized in absence of any other link. The data also showed background circulation of further unrelated strains, both autochthonous and travel related, whose sequence comparison highlighted minor outbreaks and small clusters, most of them unrecognized on the basis of epidemiological data. Phylogenetic analysis showed most isolates from travel related cases clustering with reference strains originating from the same geographical area of travel.

Conclusions

In conclusion, the study documents, in a real outbreak context, the crucial role of molecular analysis in investigating an old but re-emerging pathogen. Improving the molecular knowledge of HAV strains, both autochthonous and circulating in countries from which potentially contaminated foods are imported, will become increasingly important to control outbreaks by supporting trace back activities, aiming to identify the geographical source(s) of contaminated food, as well as public health interventions.     

基于CiteSpace的全球炭疽研究演化及其热点可视化分析

最新研究估算全球约有18.3亿人生活在炭疽风险区域内。经过几十年的发展,全球炭疽研究成果数量丰硕且总量在增长。【目的】对全球炭疽研究文献进行探析,以获取其研究领域演化趋势及热点变化。【方法】基于WOS来源文献,运用科学计量方法,对1998–2018年全球炭疽研究进行可视化分析,综合运用CiteSpace可视化分析软件中文献共被引、文献突现、关键词共现等工具,探析全球炭疽研究领域演化趋势及其热点变化。【结果】全球炭疽研究可分为1998–2004年"多维暴发"、2005–2013年"持续探索"和2014–2018年"新兴热点"3个研究阶段。【结论】炭疽快速实时痕量检测和新型炭疽疫苗有可能成为未来全球炭疽研究热点。     

Statistical deconvolution for superresolution fluorescence microscopy

Superresolution microscopy techniques based on the sequential activation of fluorophores can achieve image resolution of ～10 nm but require a sparse distribution of simultaneously activated fluorophores in the field of view. Image analysis procedures for this approach typically discard data from crowded molecules with overlapping images, wasting valuable image information that is only partly degraded by overlap. A data analysis method that exploits all available fluorescence data, regardless of overlap, could increase the number of molecules processed per frame and thereby accelerate superresolution imaging speed, enabling the study of fast, dynamic biological processes. Here, we present a computational method, referred to as deconvolution-STORM (deconSTORM), which uses iterative image deconvolution in place of single- or multiemitter localization to estimate the sample. DeconSTORM approximates the maximum likelihood sample estimate under a realistic statistical model of fluorescence microscopy movies comprising numerous frames. The model incorporates Poisson-distributed photon-detection noise, the sparse spatial distribution of activated fluorophores, and temporal correlations between consecutive movie frames arising from intermittent fluorophore activation. We first quantitatively validated this approach with simulated fluorescence data and showed that deconSTORM accurately estimates superresolution images even at high densities of activated fluorophores where analysis by single- or multiemitter localization methods fails. We then applied the method to experimental data of cellular structures and demonstrated that deconSTORM enables an approximately fivefold or greater increase in imaging speed by allowing a higher density of activated fluorophores/frame.     

Climatic Factors Influencing the Anthrax Outbreak of 2016 in Siberia,Russia

In 2016, an outbreak of anthrax killing thousands of reindeer and affecting dozens of humans occurred on the Yamal peninsula, Northwest Siberia, after 70 years of epidemiological situation without outbreaks. The trigger of the outbreak has been ascribed to the activation of spores due to permafrost thaw that was accelerated during the summer heat wave. The focus of our study is on the dynamics of local environmental factors in connection with the observed anthrax revival. We show that permafrost was thawing rapidly for already 6 years before the outbreak. During 2011–2016, relatively warm years were followed by cold years with a thick snow cover, preventing freezing of the soil. Furthermore, the spread of anthrax was likely intensified by an extremely dry summer of 2016. Concurrent with the long-term decreasing trend in the regional annual precipitation, the rainfall in July 2016 was less than 10% of its 30-year mean value. We conclude that epidemiological situation of anthrax in the previously contaminated Arctic regions requires monitoring of climatic factors such as warming and precipitation extremes.

     

The 2012 Madeira Dengue Outbreak: Epidemiological Determinants and Future Epidemic Potential

Dengue, a vector-borne viral disease of increasing global importance, is classically associated with tropical and sub-tropical regions around the world. Urbanisation, globalisation and climate trends, however, are facilitating the geographic spread of its mosquito vectors, thereby increasing the risk of the virus establishing itself in previously unaffected areas and causing large-scale epidemics. On 3 October 2012, two autochthonous dengue infections were reported within the Autonomous Region of Madeira, Portugal. During the following seven months, this first ‘European’ dengue outbreak caused more than 2000 local cases and 81 exported cases to mainland Europe. Here, using an ento-epidemiological mathematical framework, we estimate that the introduction of dengue to Madeira occurred around a month before the first official cases, during the period of maximum influx of airline travel, and that the naturally declining temperatures of autumn were the determining factor for the outbreak''s demise in early December 2012. Using key estimates, together with local climate data, we further propose that there is little support for dengue endemicity on this island, but a high potential for future epidemic outbreaks when seeded between May and August—a period when detection of imported cases is crucial for Madeira''s public health planning.     

Bayesian Reconstruction of Disease Outbreaks by Combining Epidemiologic and Genomic Data

Recent years have seen progress in the development of statistically rigorous frameworks to infer outbreak transmission trees (“who infected whom”) from epidemiological and genetic data. Making use of pathogen genome sequences in such analyses remains a challenge, however, with a variety of heuristic approaches having been explored to date. We introduce a statistical method exploiting both pathogen sequences and collection dates to unravel the dynamics of densely sampled outbreaks. Our approach identifies likely transmission events and infers dates of infections, unobserved cases and separate introductions of the disease. It also proves useful for inferring numbers of secondary infections and identifying heterogeneous infectivity and super-spreaders. After testing our approach using simulations, we illustrate the method with the analysis of the beginning of the 2003 Singaporean outbreak of Severe Acute Respiratory Syndrome (SARS), providing new insights into the early stage of this epidemic. Our approach is the first tool for disease outbreak reconstruction from genetic data widely available as free software, the R package outbreaker. It is applicable to various densely sampled epidemics, and improves previous approaches by detecting unobserved and imported cases, as well as allowing multiple introductions of the pathogen. Because of its generality, we believe this method will become a tool of choice for the analysis of densely sampled disease outbreaks, and will form a rigorous framework for subsequent methodological developments.     

Early Bacillus anthracis-macrophage interactions: intracellular survival survival and escape

This study describes early intracellular events occurring during the establishment phase of Bacillus anthracis infections. Anthrax infections are initiated by dormant endospores gaining access to the mammalian host and becoming engulfed by regional macrophages (Mφ). During systemic anthrax, late stage events include vegetative growth in the blood to very high titres and the synthesis of the anthrax exotoxin complex, which causes disease symptoms and death. Experiments focus on the early events occurring during the first few hours of the B. anthracis infectious cycle, from endospore germination up to and including release of the vegetative cell from phagocytes. We found that newly vegetative bacilli escape from the phagocytic vesicles of cultured Mφ and replicate within the cytoplasm of these cells. Release from the Mφ occurs 4–6 h after endospore phagocytosis, timing that correlates with anthrax infection of test animals. Genetic analysis from this study indicates that the toxin plasmid pXO1 is required for release from the Mφ, whereas the capsule plasmid pXO2 is not. The transactivator atxA , located on pXO1, is also found to be essential for release, but the toxin genes themselves are not required. This suggests that Mφ release of anthrax bacilli is atxA regulated. The putative 'escape' genes may be located on the chromosome and/or on pXO1.     

Naturally acquired anthrax antibodies in a cheetah (Acinonyx jubatus) in Botswana

An outbreak of anthrax in the Jwana Game Reserve in Jwaneng, Botswana, was first observed when three cheetahs (Acinonyx jubatus) died of the disease in November 2004. In the aftermath of this event, banked serum samples collected from 23 wild-caught cheetahs were examined, by the inhibition enzyme-linked immunoassay (ELISA), for antibodies to the protective antigen (PA) of Bacillus anthracis. Of the 23 cheetahs, 16 regularly accessed the reserve. Antibodies to PA were detected in one cheetah collected in May 2004, indicating the disease was occurring well before it was first noticed. This appears to be the first demonstration of naturally acquired anthrax antibodies in cheetahs. The finding of one antibody-positive animal amongst at least 16 potentially exposed individuals is consistent with existing reports that it is uncommon for cheetahs to develop natural immunity to anthrax.