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Horses are a highly mobile population, with many travelling locally, nationally, and internationally to participate in shows and sporting events. However, the nature and extent of these movements, as well as the potential impact they may have on disease introduction and spread, is not well documented. The objective of this study was to characterise the movement network of a sample of horses in Ontario, Canada, over a 7-month equestrian season. Horse owners (n = 141) documented their travel patterns with their horse(s) (n = 330) by completing monthly online questionnaires between May and November 2015. Directed networks were constructed to represent horse movements in 1-month time periods. A total of 1754 horse movements met the inclusion criteria for analysis. A variety of location types were included in each monthly network, with many including non-facilities such as parks, trails, and private farms. Only 34.3% of competitions attended by participants during the study period were regulated by an official equestrian organisation. Comparisons of the similarity between monthly networks indicated that participants did not travel to the same locations each month, and the most connected locations varied between consecutive months. While the findings should not be generalized to the wider horse population, they have provided greater insight into the nature and extent of observed horse movement patterns. The results support the need to better understand the variety of locations to which horses can travel in Ontario, as different types of locations may have different associated risks of disease introduction and spread. [ABSTRACT FROM AUTHOR]

Background: Contact networks can be used to assess disease spread potential within a population. However, the data required to generate the networks can be challenging to collect. One method of collecting this type of data is by using radio-frequency identification (RFID) tags. The OpenBeacon RFID system generally consists of tags and readers. Communicating tags should be within 10m of the readers, which are powered by an external power source. The readers are challenging to implement in agricultural settings due to the lack of a power source and the large area needed to be covered. Methods: OpenBeacon firmware was modified to use the tag’s onboard flash memory for data storage. The tags were deployed within an equine facility for a 7-day period. Tags were attached to the horses’ halters, worn by facility staff, and placed in strategic locations around the facility to monitor which participants had contact with the specified locations during the study period. When the tags came within 2m of each other, they recorded the contact event participant IDs, and start and end times. At the end of the study period, the data were downloaded to a computer and analyzed using network analysis methods. Results: The resulting networks were plausible given the facility schedule as described in a survey completed by the facility manager. Furthermore, changes in the daily facility operations as described in the survey were reflected in the tag-collected data. In terms of the battery life, 88% of batteries maintained a charge for at least 6 days. Lastly, no consistent trends were evident in the horses’ centrality metrics. Discussion: This study demonstrates the utility of RFID tags for the collection of equine contact data. Future work should include the collection of contact data from multiple equine facilities to better characterize equine disease spread potential in Ontario. [ABSTRACT FROM AUTHOR]

Surgical sterilization programs for dogs have been proposed as interventions to control dog population size. Models can be used to help identify the long-term impact of reproduction control interventions for dogs. The objective of this study was to determine the projected impact of surgical sterilization interventions on the owned dog population size in Villa de Tezontepec, Hidalgo, Mexico. A stochastic, individual-based simulation model was constructed and parameterized using a combination of empirical data collected on the demographics of owned dogs in Villa de Tezontepec and data available from the peer-reviewed literature. Model outcomes were assessed using a 20-year time horizon. The model was used to examine: the effect of surgical sterilization strategies focused on: 1) dogs of any age and sex, 2) female dogs of any age, 3) young dogs (i.e., not yet reached sexual maturity) of any sex, and 4) young, female dogs. Model outcomes suggested that as surgical capacity increases from 21 to 84 surgeries/month, (8.6% to 34.5% annual sterilization) for dogs of any age, the mean dog population size after 20 years was reduced between 14% and 79% compared to the base case scenario (i.e. in the absence of intervention). Surgical sterilization interventions focused only on young dogs of any sex yielded greater reductions (81% - 90%) in the mean population size, depending on the level of surgical capacity. More focused sterilization targeted at female dogs of any age, resulted in reductions that were similar to focusing on mixed sex sterilization of only young dogs (82% - 92%). The greatest mean reduction in population size (90% - 91%) was associated with sterilization of only young, female dogs. Our model suggests that targeting sterilization to young females could enhance the efficacy of existing surgical dog population control interventions in this location, without investing extra resources. [ABSTRACT FROM AUTHOR]

Cryptosporidium is a waterborne parasite that causes diarrheal disease in humans and in cattle. Risk factors for human illness include contact with surface water such as lakes and rivers, exposure to contaminated municipal drinking water, as well as zoonotic transmission from livestock and agriculture. The objectives of this study are twofold: 1) to describe the temporal distribution of cryptosporidiosis in Southwestern Ontario; and 2) to determine the distribution of human cryptosporidiosis, in relation to exposures such as cryptosporidium positive cattle farms, weather events, and hydrological factors. Seasonal trends in 214 bovine and 87 human cases were assessed using regression models that predicted monthly case counts in relation to observed monthly case counts. A case-crossover approach was used to evaluate acute associations between daily environmental exposures, such as weather, hydrology, the presence of Cryptosporidium positive cattle farms within the region, and the risk of human Cryptosporidium infection. Annual seasonality was found for both human cases and bovine cases with human cases peaking in mid-summer and bovine cases peaking in late winter to early spring. Bovine cases that occurred 21 days prior to human cases were associated with a three-fold increase in the odds of human case occurrence. At both 9 and 14 days prior to human case onset, the odds of a human case increased twofold per 10-degree Celsius increase in air temperature. These results provide a preliminary hypothesis for the zoonotic transmission of cryptosporidiosis from cattle to humans via the environment and suggest that the timing of environmental conditions in relation to case occurrence is biologically plausible. [ABSTRACT FROM AUTHOR]

Background: Due to the lack of timely access to resources for critical care, strategic use of antiviral drugs is crucial for mitigating the impact of novel influenza viruses with pandemic potential in remote and isolated communities. We sought to evaluate the effect of antiviral treatment and prophylaxis of close contacts in a Canadian remote northern community. Methods: We used an agent-based, discrete-time simulation model for disease spread in a remote community, which was developed as an in-silico population using population census data. Relative and cumulative age-specific attack rates, and the total number of infections in simulated model scenarios were obtained. Results: We found that early initiation of antiviral treatment is more critical for lowering attack rates in a remote setting with a low population-average age compared to an urban population. Our results show that a significant reduction in the relative, age-specific attack rates due to increasing treatment coverage does not necessarily translate to a significant reduction in the overall arrack rate. When treatment coverage varies from low to moderate, targeted prophylaxis has a very limited impact in reducing attack rates and should be offered at a low level (below 10%) to avoid excessive waste of drugs. Conclusions: In contrast to previous work, for conservative treatment coverages, our results do not provide any convincing evidence for the implementation of targeted prophylaxis. The findings suggest that public health strategies in remote communities should focus on the wider availability (higher coverage) and timely distribution of antiviral drugs for treatment of clinically ill individuals. [ABSTRACT FROM AUTHOR]

Background: Communicable disease outbreaks of novel or existing pathogens threaten human health around the globe. It would be desirable to rapidly characterize such outbreaks and develop accurate projections of their duration and cumulative size even when limited preliminary data are available. Here we develop a mathematical model to aid public health authorities in tracking the expansion and contraction of outbreaks with explicit representation of factors (other than population immunity) that may slow epidemic growth. Methodology: The Incidence Decay and Exponential Adjustment (IDEA) model is a parsimonious function that uses the basic reproduction number R0, along with a discounting factor to project the growth of outbreaks using only basic epidemiological information (e.g., daily incidence counts). Principal Findings: Compared to simulated data, IDEA provides highly accurate estimates of total size and duration for a given outbreak when R0 is low or moderate, and also identifies turning points or new waves. When tested with an outbreak of pandemic influenza A (H1N1), the model generates estimated incidence at the i+1th serial interval using data from the ith serial interval within an average of 20% of actual incidence. Conclusions and Significance: This model for communicable disease outbreaks provides rapid assessments of outbreak growth and public health interventions. Further evaluation in the context of real-world outbreaks will establish the utility of IDEA as a tool for front-line epidemiologists. [ABSTRACT FROM AUTHOR]

Background: The Canadian National Antiviral Stockpile (NAS) contains treatment for 17.5% of Canadians. This assumes no concurrent intervention strategies and no wastage due to non-influenza respiratory infections. A dynamic model can provide a mechanism to consider complex scenarios to support decisions regarding the optimal NAS size under uncertainty. Methods: We developed a dynamic model for pandemic influenza in Canada that is structured by age and risk to calculate the demand for antivirals to treat persons with pandemic influenza under a wide-range of scenarios that incorporated transmission dynamics, disease severity, and intervention strategies. The anticipated per capita number of acute respiratory infections due to viruses other than influenza was estimated for the full pandemic period from surveys based on criteria to identify potential respiratory infections. Results: Our results demonstrate that up to two thirds of the population could develop respiratory symptoms as a result of infection with a pandemic strain. In the case of perfect antiviral allocation, up to 39.8% of the population could request antiviral treatment. As transmission dynamics, severity and timing of the emergence of a novel influenza strain are unknown, the sensitivity analysis produced considerable variation in potential demand (median: 11%, IQR: 2–21%). If the next pandemic strain emerges in late spring or summer and a vaccine is available before the anticipated fall wave, the median prediction was reduced to 6% and IQR to 0.7–14%. Under the strategy of offering empirical treatment to all patients with influenza like symptoms who present for care, demand could increase to between 65 and 144%. Conclusions: The demand for antivirals during a pandemic is uncertain. Unless an accurate, timely and cost-effective test is available to identify influenza cases, demand for antivirals from persons infected with other respiratory viruses will be substantial and have a significant impact on the NAS. [ABSTRACT FROM AUTHOR]