Investigating Leptospira dynamics in a multi-host community using an agent-based modelling approach.

Leptospirosis, a neglected bacterial zoonosis, is a global public health issue disproportionately affecting impoverished communities such as urban slums in the developing world. A variety of animal species, including peridomestic rodents and dogs, can be infected with different strains of leptospirosis. Humans contract leptospirosis via exposure to water or soil contaminated with the urine of infected animals. Due to the unavailability of safe and effective vaccines, preventive strategies mainly focus on minimizing human exposure to contaminated environment. In marginalized communities, this approach is ineffective due to infrastructure deficiencies and the difficulties in implementing sanitation and hygiene practices. Moreover, continuing the expansion of urban slums worldwide will likely contribute to the increase in outbreaks of leptospirosis. Effective prevention of leptospirosis outbreaks will therefore require a thorough understanding of Leptospira transmission dynamics in impoverished, high-density settings. We developed the agent-based model MHMSLeptoDy to investigate Leptospira dynamics in a realistic, in silico high-density community of rodents, dogs and human hosts, and two host-adapted Leptospira strains. Virtual explorations using MHMSLeptoDy were undertaken to evaluate alternate interventions and to assess the zoonotic transmission risk of leptospirosis. A key finding from model explorations is that rodents are the main contributors of rodent-adapted as well as dog-adapted strains in the environment, whereas dogs play an important role in distributing the rodent-adapted strain. Alternate leptospirosis control strategies can be evaluated using the open-source, customizable agent-based model, MHMSLeptoDy. This modelling approach provides a sophisticated mechanism to quantitatively evaluate nuanced intervention strategies and inform the design of rational, locally relevant leptospirosis control programmes.

Harvest strategies for the elimination of low prevalence wildlife diseases.

The intensive harvesting of hosts is often the only practicable strategy for controlling emerging wildlife diseases. Several harvesting approaches have been explored theoretically with the objective of lowering transmission rates, decreasing the transmission period or specifically targeting spatial disease clusters or high-risk demographic groups. Here, we present a novel model-based approach to evaluate alternative harvest regimes, in terms of demographic composition and rates, intended to increase the probability to remove all infected individuals in the population during the early phase of an outbreak. We tested the utility of the method for the elimination of chronic wasting disease based on empirical data for reindeer (Rangifer tarandus) in Norway, in populations with (Nordfjella) and without (Hardangervidda) knowledge about exact disease prevalence and population abundance. Low and medium harvest intensities were unsuccessful in eliminating the disease, even at low prevalence. High-intensity harvesting had a high likelihood of eliminating the disease, but probability was strongly influenced by the disease prevalence. We suggest that the uncertainty about disease prevalence can be mitigated by using an adaptive management approach: forecast from models after each harvest season with updated data, derive prevalence estimates and forecast further harvesting. We identified the problems arising from disease surveillance with large fluctuations in harvesting pressure and hence sample sizes. The elimination method may be suitable for pathogens that cause long-lasting infections and with slow epidemic growth, but the method should only be attempted if there is a low risk of reinfection, either by a new disease introduction event (e.g. dispersing hosts) or due to environmental reservoirs. Our simulations highlighted the short time window when such a strategy is likely to be successful before approaching near complete eradication of the population.

Modelling the challenges of managing free-ranging dog populations.

Free-ranging domestic dogs (FRD) are not only vectors of zoonoses of public health concern, but also pose direct threats to humans, livestock, and endangered wildlife. Many developing countries have struggled to control FRD, despite using both lethal and non-lethal methods. India has amongst the highest FRD populations globally and the highest incidences of dog-mediated human rabies, but only deploys Catch-Neuter-Vaccinate-Release (CNVR) for FRD control as a humane alternative to lethal methods, without evidence of it working successfully. Here, we use an agent-based dog population dynamics model to examine the time, effort, financial resources, and conditions needed to successfully control FRD in a typical urban setting. We simulate several scenarios, from an "ideal world" closed population with easily accessible dogs, to a more realistic open population with heterogeneity in catchability of dogs. In only one "best-case" scenario, CNVR resulted in a significant and lasting reduction in FRD, but with vaccination rates peaking only at 35%, which is half the WHO-recommended coverage. The customisable and portable modelling tool that we have developed allows managers to simulate real world processes and understand the expected effort needed to reduce regional dog populations, and assess methods for achieving effective anti-rabies vaccination coverage.

Size matters: Sample size assessments for chronic wasting disease surveillance using an agent-based modeling framework.

Epidemiological surveillance for many important wildlife diseases relies on samples obtained from hunter-harvested animals. Statistical methods used to calculate sample size requirements assume that the target population is randomly sampled, and therefore the samples are representative of the population. But hunter-harvested samples may not be representative of the population due to disease distribution heterogeneities (e.g. spatial clustering of infected individuals), and harvest-related non-random processes like regulations, hunter selectivity, variable land access, and uneven hunter distribution. Consequently, sample sizes necessary for detection of disease are underestimated and disease detection probabilities are overestimated, resulting in erroneous inferences about disease presence and distribution. We have developed a modeling framework to support the design of efficient disease surveillance programs for wildlife populations. The constituent agent-based models can incorporate real-world heterogeneities associated with disease distribution, harvest, and harvest-based sampling, and can be used to determine population-specific sample sizes necessary for prompt detection of important wildlife diseases like chronic wasting disease and bovine tuberculosis. The modeling framework and its application has been described in detail by Belsare et al. [1]. Here we describe how model scenarios were developed and implemented, and how model outputs were analyzed. The main objectives of this methods paper are to provide users the opportunity to a) assess the reproducibility of the published model results, b) gain an in-depth understanding of model analysis, and c) facilitate adaptation of this modeling framework to other regions and other wildlife disease systems.•The two agent-based models, MOOvPOP and MOOvPOPsurveillance, incorporate real-world heterogeneities underpinned by host characteristics, disease spread dynamics, and sampling biases in hunter-harvested deer.•The modeling framework facilitates iterative analysis of locally relevant disease surveillance scenarios, thereby facilitating sample size calculations for prompt and reliable detection of important wildlife diseases.•Insights gained from modeling studies can be used to inform the design of effective wildlife disease surveillance strategies.

An agent-based framework for improving wildlife disease surveillance: A case study of chronic wasting disease in Missouri white-tailed deer.

Epidemiological surveillance for important wildlife diseases often relies on samples obtained from hunter-harvested animals. A problem, however, is that although convenient and cost-effective, hunter-harvest samples are not representative of the population due to heterogeneities in disease distribution and biased sampling. We developed an agent-based modeling framework that i) simulates a deer population in a user-generated landscape, and ii) uses a snapshot of the in silico deer population to simulate disease prevalence and distribution, harvest effort and sampling as per user-specified parameters. This framework can incorporate real-world heterogeneities in disease distribution, hunter harvest and harvest-based sampling, and therefore can be useful in informing wildlife disease surveillance strategies, specifically to determine population-specific sample sizes necessary for prompt detection of disease. Application of this framework is illustrated using the example of chronic wasting disease (CWD) surveillance in Missouri's white-tailed deer (Odocoileus virginianus) population. We show how confidence in detecting CWD is grossly overestimated under the unrealistic, but standard, assumptions that sampling effort and disease are randomly and independently distributed. We then provide adjusted sample size recommendations based on more realistic assumptions. Wildlife agencies can use these open-access models to design their CWD surveillance. Furthermore, these models can be readily adapted to other regions and other wildlife disease systems.

Getting in Front of Chronic Wasting Disease: Model-Informed Proactive Approach for Managing an Emerging Wildlife Disease.

Continuing geographic spread of chronic wasting disease (CWD) poses a serious threat to the sustainable future of cervids and hunting in North America. Moreover, CWD has been detected in captive cervids in South Korea and, in recent years, in free-ranging reindeer in Europe (Norway). Management of this disease is limited by logistical, financial, and sociopolitical considerations, and current strategies primarily focus on reducing host densities through hunter harvest and targeted culling. The success of such strategies in mitigating the spread and prevalence of CWD only upon detection is questionable. Here, we propose a proactive approach that emphasizes pre-emptive management through purposeful integration of virtual experiments (simulating alternate interventions as model scenarios) with the aim of evaluating their effectiveness. Here, we have used a published agent-based model that links white-tailed deer demography and behavior with CWD transmission dynamics to first derive a CWD outbreak trajectory and then use the trajectory to highlight issues associated with different phases of the CWD outbreak (pre-establishment/transition/endemic). Specifically, we highlight the practical constraints on surveillance in the pre-establishment phase and recommend that agencies use a realistic detection threshold for their CWD surveillance programs. We further demonstrate that many disease introductions are "dead ends" not leading to a full epidemic due to high stochasticity and harvesting in the pre-establishment phase of CWD. Model evaluated pre-emptive (pre-detection) harvest strategies could increase the resilience of the deer population to CWD spread and establishment. We conclude it is important to adaptively position CWD management ahead of, rather than behind, the CWD front.

Genetic polymorphism of Baylisascaris procyonis in host infrapopulations and component populations in the Central USA.

Baylisascaris procyonis is a nematode of significant concern to public and domestic animal health as well as wildlife management. The population genetics of B. procyonis is poorly understood. To gain insights into patterns of genetic diversity within (infrapopulation level) and among (component population level) raccoon (Procyon lotor) hosts, and specifically to assess the relative importance of indirect and direct transmission of the parasite for explaining observed population structure, we collected 69 B. procyonis from 17 wild raccoons inhabiting five counties in Missouri and Arkansas, USA. Informative regions of mitochondrial (CO1, CO2) and nuclear (28S, ITS2) genes were amplified and the distribution and genetic variability of these genes were assessed within and across raccoons. Concatenation of the CO1 and CO2 mtDNA sequences resulted in 5 unique haplotypes, with haplotype diversity 0.456 ±â€¯0.068. The most common haplotype occurred in 94% of raccoons and 72.5% of B. procyonis. Sequences for 28S rDNA revealed four unique nuclear genotypes, the most common found in 100% of raccoons and 82.6% of B. procyonis. ITS2 genotypes were assessed using fragment analysis, and there was a 1:1 correspondence between 28S and ITS-2 genotypes. Infrapopulation variation in haplotypes and genotypes was high and virtually all hosts infected with multiple sequenced nematodes also harbored multiple haplotypes and genotypes. There was a positive relationship between the size of the analyzed infrapopulation (i.e., the number of nematodes analyzed) and the number of haplotypes identified in an individual. Collectively this work emphasizes the importance of indirect transmission in the lifecycle to this parasite.

Use of xylazine hydrochloride-ketamine hydrochloride for immobilization of Indian fox (Vulpes bengalensis) in field situations.

Reports on doses of anesthetic agents for safe and effective immobilization of most wild species occurring in India are very limited. Further, the anesthetic agents available in India for field immobilizations are limited to xylazine hydrochloride and ketamine hydrochloride. A safe and effective dosage of xylazine-ketamine for Indian fox (Vulpes bengalensis) is reported, based on 37 wild Indian fox immobilizations between April 2006 and May 2007. Foxes captured for a radiotelemetry and health monitoring study were immobilized with a mixture of xylazine (2.27 +/- 0.44 mg/kg) and ketamine (13.39 +/- 2.26 mg/kg). Induction and recovery was smooth and uneventful in all foxes. The duration of anesthesia was sufficient for the fitting of radiotransmitters, morphometric measurements, and blood sampling. No life-threatening adverse effects of immobilization were documented for at least 1 mo postimmobilization. The results suggest that field immobilization of Indian foxes with 2 mg/kg xylazine and 13 mg/kg ketamine is effective and safe.

Assessing demographic and epidemiologic parameters of rural dog populations in India during mass vaccination campaigns.

Mass vaccination of dogs is a mainstay for efforts to control rabies and other viral pathogens. The success of such programs is a function of the ability to vaccinate sufficient proportions of animals to develop herd immunity. However, fully assessing success in reaching target vaccination-levels and in understanding the outcome of mass vaccination efforts is hindered if insufficient information is available on the demographics of dog populations and the prevalence of the targeted pathogens. While such information can sometimes be gained from questionnaire surveys, greater precision requires direct assessment of the dog populations. Here we show how such information can be gained from surveys of dogs conducted in association with mass-vaccination programs. We conducted surveys of dogs in six villages in rural Maharashtra, India, between February and July 2011 as part of an effort to reduce the risk of human rabies and virus transmission from dogs to wildlife. Mass vaccination efforts were conducted in each village, and paired with blood sample collection and photographic mark-recapture approaches to gain epidemiologic and demographic data. This data in turn facilitated estimates of dog abundance, population density and structure, vaccination coverage, and seroprevalence of antibodies against canine adenovirus (CAV), canine parvovirus (CPV), and canine distemper virus (CDV). The median dog population size for the six villages was 134 (range 90-188), the median dog population density was 719 dogs per km(2) (range 526-969), and the median human:dog ratio for these six villages was 34 (range 30-47). The median household:dog ratio for the six villages was 6 (range 5-8). Following vaccination efforts, the median vaccination coverage achieved was 34% (range 24-42%). The dog populations consisted mostly of adult dogs (67-86%) and the median sex ratio for the study area was male biased (1.55 males per female; range 0.9-2.5). The seroprevalence of antibodies against CAV, CPV and CDV was 68, 88 and 73%, respectively. Mass vaccination campaigns provide an opportunity to obtain vital epidemiological and demographic data, and develop a clearer understanding of the threats and impacts of diseases and disease control measures.

Use of xylazine hydrochloride-ketamine hydrochloride for immobilization of wild leopards (Panthera pardus fusca) in emergency situations.

In India, leopards (Panthera pardus fusca) inhabit human-dominated landscapes, resulting in encounters that require interventions to prevent harm to people, as well as the leopards. Immobilization is a prerequisite for any such intervention. Such emergency field immobilizations have to be carried out with limited tools, often amidst large uncontrollable crowds. An effective and practicable approach is discussed, based on 55 wild leopard immobilizations undertaken between January 2003 and April 2008. A xylazine hydrochloride (1.4 +/- 0.3 mg/kg)--ketamine hydrochloride (5 +/- 2 mg/kg) mixture was used for immobilization of leopards, based on estimated body weight. When weight could not be estimated, a standard initial dose of 50 mg of xylazine--150 mg of ketamine was used. Supplemental doses (50-75 mg) of only ketamine were used as required. No life-threatening adverse effects of immobilization were documented for at least 1 mo postimmobilization.