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Vector-borne pathogens (VBPs) causing vector-borne diseases (VBDs) can circulate among humans, domestic animals, and wildlife, with cattle in particular serving as an important source of exposure risk to humans. The close associations between humans and cattle can facilitate the transmission of numerous VBPs, impacting public health and economic security. Published studies demonstrate that cattle can influence human exposure risk positively, negatively, or have no effect. There is a critical need to synthesize the information in the scientific literature on this subject, in order to illuminate the various ecological mechanisms that can affect VBP exposure risk in humans. Therefore, the aim of this systematic review was to review the scientific literature, provide a synthesis of the possible effects of cattle on VBP risk to humans, and propose future directions for research. This study was performed according to the PRISMA 2020 extension guidelines for systematic review. After screening 470 peer-reviewed articles published between 1999–2019 using the databases Web of Science Core Collection, PubMed Central, CABI Global Health, and Google Scholar, and utilizing forward and backward search techniques, we identified 127 papers that met inclusion criteria. Results of the systematic review indicate that cattle can be beneficial or harmful to human health with respect to VBDs depending on vector and pathogen ecology and livestock management practices. Cattle can increase risk of exposure to infections spread by tsetse flies and ticks, followed by sandflies and mosquitoes, through a variety of mechanisms. However, cattle can have a protective effect when the vector prefers to feed on cattle instead of humans and when chemical control measures (e.g., acaricides/insecticides), semio-chemicals, and other integrated vector control measures are utilized in the community. We highlight that further research is needed to determine ways in which these mechanisms may be exploited to reduce VBD risk in humans. Author summary: Vector-borne diseases (VBDs) are caused by pathogens spread by blood-feeding arthropods from an infected to an uninfected organism. These infections may be caused by pathogenic bacteria, viruses, or protozoans and arthropod vectors may spread these pathogens to humans, domestic animals, and wildlife. Humans and cattle spend a significant amount of time in close proximity with each other through various activities such as agriculture, animal husbandry, trading, and animal farming, which can potentially increase risk to human health. Previously published studies indicated cattle can impact vector-borne pathogen (VBP) transmission both positively and negatively, however, there has not been a recent synthesis of the scientific literature on this subject. Through this global systematic review of the scientific literature, we found that cattle could have either harmful or beneficial impacts on human health when it comes to VBDs, but most often increase exposure risk to VBPs in humans. We identified various mechanisms from the scientific literature by which cattle can impact VBP risk in humans. Further research is needed to better understand specific ecological mechanisms by which cattle impact human health and develop measures that will prevent and reduce VBP exposure risk in humans. [ABSTRACT FROM AUTHOR]

Enteric viruses are often detected in water used for crop irrigation. One concern is foodborne viral disease via the consumption of fresh produce irrigated with virus‐contaminated water. Although the food industry routinely uses chemical sanitizers to disinfect post‐harvest fresh produce, it remains unknown how sanitizer and fresh produce properties affect the risk of viral illness through fresh produce consumption. A quantitative microbial risk assessment model was conducted to estimate (i) the health risks associated with consumption of rotavirus (RV)‐contaminated fresh produce with different surface properties (endive and kale) and (ii) how risks changed when using peracetic acid (PAA) or a surfactant‐based sanitizer. The modeling results showed that the annual disease burden depended on the combination of sanitizer and vegetable type when vegetables were irrigated with RV‐contaminated water. Global sensitivity analyses revealed that the most influential factors in the disease burden were RV concentration in irrigation water and postharvest disinfection efficacy. A postharvest disinfection efficacy of higher than 99% (2‐log10) was needed to decrease the disease burden below the World Health Organization (WHO) threshold, even in scenarios with low RV concentrations in irrigation water (i.e., river water). All scenarios tested here with at least 99.9% (3‐log10) disinfection efficacy had a disease burden lower than the WHO threshold, except for the endive treated with PAA. The disinfection efficacy for the endive treated with PAA was only about 80%, leading to a disease burden 100 times higher than the WHO threshold. These findings should be considered and incorporated into future models for estimating foodborne viral illness risks. [ABSTRACT FROM AUTHOR]

Even as the incidence of mosquito-borne diseases like West Nile Virus (WNV) in North America has risen over the past decade, effectively modelling mosquito population density or, the abundance has proven to be a persistent challenge. It is critical to capture the fluctuations in mosquito abundance across seasons in order to forecast the varying risk of disease transmission from one year to the next. We develop a process-based mechanistic weather-driven Ordinary Differential Equation (ODE) model to study the population biology of both aqueous and terrestrial stages of mosquito population. The progression of mosquito lifecycle through these stages is influenced by different factors, including temperature, daylight hours, intra-species competition and the availability of aquatic habitats. Weather-driven parameters are utilised in our work, are a combination of laboratory research and literature data. In our model, we include precipitation data as a substitute for evaluating additional mortality in the mosquito population. We compute the \textit{Basic offspring number} of the associated model and perform sensitivity analysis. Finally, we employ our model to assess the effectiveness of various adulticides strategies to predict the reduction in mosquito population. This enhancement in modelling of mosquito abundance can be instrumental in guiding interventions aimed at reducing mosquito populations and mitigating mosquito-borne diseases such as the WNV.

Enteric viruses are often detected in water used for crop irrigation. One concern is foodborne viral disease via the consumption of fresh produce irrigated with virus-contaminated water. Although the food industry routinely uses chemical sanitizers to disinfect post-harvest fresh produce, it remains unknown how sanitizer and fresh produce properties affect the risk of viral illness through fresh produce consumption. A quantitative microbial risk assessment model was conducted to estimate (i) the health risks associated with consumption of rotavirus (RV)-contaminated fresh produce with different surface properties (endive and kale) and (ii) how risks changed when using peracetic acid (PAA) or a surfactant-based sanitizer. The modeling results showed that the annual disease burden depended on the combination of sanitizer and vegetable type when vegetables were irrigated with RV-contaminated water. Global sensitivity analyses revealed that the most influential factors in the disease burden were RV concentration in irrigation water and postharvest disinfection efficacy. A postharvest disinfection efficacy of higher than 99% (2-log 10 ) was needed to decrease the disease burden below the World Health Organization (WHO) threshold, even in scenarios with low RV concentrations in irrigation water (i.e., river water). All scenarios tested here with at least 99.9% (3-log 10 ) disinfection efficacy had a disease burden lower than the WHO threshold, except for the endive treated with PAA. The disinfection efficacy for the endive treated with PAA was only about 80%, leading to a disease burden 100 times higher than the WHO threshold. These findings should be considered and incorporated into future models for estimating foodborne viral illness risks., (© 2019 Society for Risk Analysis.)