Modelling the transmission of dengue, zika and chikungunya: a scoping review protocol.

INTRODUCTION: Aedes mosquitoes are the primary vectors for the spread of viruses like dengue (DENV), zika (ZIKV) and chikungunya (CHIKV), all of which affect humans. Those diseases contribute to global public health issues because of their great dispersion in rural and urban areas. Mathematical and statistical models have become helpful in understanding these diseases' epidemiological dynamics. However, modelling the complexity of a real phenomenon, such as a viral disease, should consider several factors. This scoping review aims to document, identify and classify the most important factors as well as the modelling strategies for the spread of DENV, ZIKV and CHIKV. METHODS AND ANALYSIS: We will conduct searches in electronic bibliographic databases such as PubMed, MathSciNet and the Web of Science for full-text peer-reviewed articles written in English, French and Spanish. These articles should use mathematical and statistical modelling frameworks to study dengue, zika and chikungunya, and their cocirculation/coinfection with other diseases, with a publication date between 1 January 2011 and 31 July 2023. Eligible studies should employ deterministic, stochastic or statistical modelling approaches, consider control measures and incorporate parameters' estimation or considering calibration/validation approaches. We will exclude articles focusing on clinical/laboratory experiments or theoretical articles that do not include any case study. Two reviewers specialised in zoonotic diseases and mathematical/statistical modelling will independently screen and retain relevant studies. Data extraction will be performed using a structured form, and the findings of the study will be summarised through classification and descriptive analysis. Three scoping reviews will be published, each focusing on one disease and its cocirculation/co-infection with other diseases. ETHICS AND DISSEMINATION: This protocol is exempt from ethics approval because it is carried out on published manuscripts and without the participation of humans and/or animals. The results will be disseminated through peer-reviewed publications and presentations in conferences.

Identification of the elements of models of antimicrobial resistance of bacteria for assessing their usefulness and usability in One Health decision making: a protocol for scoping review.

INTRODUCTION: Antimicrobial resistance (AMR) is a complex problem that requires the One Health approach, that is, a collaboration among various disciplines working in different sectors (animal, human and environment) to resolve it. Mathematical and statistical models have been used to understand AMR development, emergence, dissemination, prediction and forecasting. A review of the published models of AMR will help consolidate our knowledge of the dynamics of AMR and will also facilitate decision-makers and researchers in evaluating the credibility, generalisability and interpretation of the results and aspects of AMR models. The study objective is to identify and synthesise knowledge on mathematical and statistical models of AMR among bacteria in animals, humans and environmental compartments. METHODS AND ANALYSIS: Eligibility criteria: Original research studies reporting mathematical and statistical models of AMR among bacteria in animal, human and environmental compartments that were published until 2022 in English, French and Spanish will be included in this study. SOURCES OF EVIDENCE: Database of PubMed, Agricola (Ovid), Centre for Agriculture and Bioscience Direct (CABI), Web of Science (Clarivate), Cumulative Index to Nursing and Allied Health Literature (CINAHL) and MathScinet. Data charting: Metadata of the study, the context of the study, model structure, model process and reporting quality will be extracted. A narrative summary of this information, gaps and recommendations will be prepared and reported in One Health decision-making context. ETHICS AND DISSEMINATION: Research ethics board approval was not obtained for this study as neither human participation nor unpublished human data were used in this study. The study findings will be widely disseminated among the One Health Modelling Network for Emerging Infections network and stakeholders by means of conferences, and publication in open-access peer-reviewed journals.

Spatio-Temporal Variation in the Prevalence of Major Mastitis Pathogens Isolated From Bovine Milk Samples Between 2008 and 2017 in Ontario, Canada.

An understanding of the spatio-temporal distribution of several groups of mastitis pathogens can help to inform programs for the successful control and management of mastitis. However, in the absence of an active surveillance program such information is not readily available. In this retrospective study we analyzed passive surveillance data from a diagnostic laboratory with an aim to describe the spatio-temporal trend of major mastitis pathogens between 2008 and 2017 in Ontario dairy cattle. Data for all milk culture samples submitted to the Animal Health Laboratory (AHL) at the University of Guelph between 2008 and 2017 was accessed. Descriptive analyses were conducted to identify the major pathogens and Chi-square goodness-of-fit tests were used to compare between multiple proportions. Likewise, univariable logistic regression analysis was performed to determine if there was a change in the probability of isolating the major mastitis pathogens depending on geography or time. Seasonality was assessed by calculating the seasonal relative risk (RR). Of a total of 85,979 milk samples examined, more than half of the samples (61.07%) showed no growth and the proportion of samples that showed no growth almost halved during the study period. Of the samples (36.21%, n = 31,133) that showed any growth, the major bacterial pathogens were Staphylococcus aureus (15.60%), Non-aureus Staphylococci (NAS) (5.04%), Corynebacterium spp. (2.96%), and Escherichia coli (2.00%). Of the NAS, the major species reported were Staphylococcus chromogenes (69.02%), Staphylococcus simulans (14.45%), Staphylococcus epidermidis (12.99%), and Staphylococcus hyicus (2.13%). A temporal change in the prevalence of contagious pathogens like S. aureus and Corynebacterium spp. was observed with an increasing odds of 1.06 and 1.62, respectively. Likewise, except for Trueperella pyogenes, the prevalence of all the major environmental mastitis pathogens increased during the study period. The isolation of most of the pathogens peaked in summer, except for S. aureus, T. pyogenes, and Streptococcus dysgalactiae which peaked in spring months. Interestingly, a regional pattern of isolation of some bacterial pathogens within Ontario was also observed. This study showed a marked spatio-temporal change in the prevalence of major mastitis pathogens and suggests that a regional and seasonal approach to mastitis control could be of value.

Evaluation of an automated feedback intervention to improve antimicrobial prescribing among primary care physicians (OPEN Stewardship): protocol for an interrupted time-series and usability analysis in Ontario, Canada and Southern Israel.

INTRODUCTION: Antimicrobial resistance undermines our ability to treat bacterial infections, leading to longer hospital stays, increased morbidity and mortality, and a mounting burden to the healthcare system. Antimicrobial stewardship is increasingly important to safeguard the efficacy of existing drugs, as few new drugs are in the developmental pipeline. While significant progress has been made with respect to stewardship in hospitals, relatively little progress has been made in the primary care setting, where the majority of antimicrobials are prescribed. OPEN Stewardship is an international collaboration to develop an automated feedback platform to improve responsible antimicrobial prescribing among primary care physicians and capable of being deployed across heterogeneous healthcare settings. We describe the protocol for an evaluation of this automated feedback intervention with two main objectives: assessing changes in antimicrobial prescribing among participating physicians and determining the usability and usefulness of the reports. METHODS AND ANALYSIS: A non-randomised evaluation of the automated feedback intervention (OPEN Stewardship) will be conducted among approximately 150 primary care physicians recruited from Ontario, Canada and Southern Israel, based on a series of targeted stewardship messages sent using the platform. Using a controlled interrupted time-series analysis and multilevel negative binomial modelling, we will compare the antimicrobial prescribing rates of participants before and after the intervention, and also to the prescribing rates of non-participants (from the same healthcare network) during the same period. We will examine outcomes targeted by the stewardship messages, including prescribing for antimicrobials with duration longer than 7 days and prescribing for indications where antimicrobials are typically unnecessary. Participants will also complete a series of surveys to determine the usability and usefulness of the stewardship reports. ETHICS AND DISSEMINATION: All sites have obtained ethics committee approval to recruit providers and access anonymised prescribing data. Dissemination will occur through open-access publication, stakeholder networks and national/international meetings.

Evaluation of an OPEN Stewardship generated feedback intervention to improve antibiotic prescribing among primary care veterinarians in Ontario, Canada and Israel: protocol for evaluating usability and an interrupted time-series analysis.

INTRODUCTION: Antimicrobial resistance (AMR) impacts the health and well-being of animals, affects animal owners both socially and economically, and contributes to AMR at the human and environmental interface. The overuse and/or inappropriate use of antibiotics in animals has been identified as one of the most important drivers of the development of AMR in animals. Effective antibiotic stewardship interventions such as feedback can be adopted in veterinary practices to improve antibiotic prescribing. However, the provision of dedicated financial and technical resources to implement such systems are challenging. The newly developed web-based Online Platform for Expanding Antibiotic Stewardship (OPEN Stewardship) platform aims to automate the generation of feedback reports and facilitate wider adoption of antibiotic stewardship. This paper describes a protocol to evaluate the usability and usefulness of a feedback intervention among veterinarians and assess its impact on individual antibiotic prescribing. METHODS AND ANALYSIS: Approximately 80 veterinarians from Ontario, Canada and 60 veterinarians from Israel will be voluntarily enrolled in a controlled interrupted time-series study and their monthly antibiotic prescribing data accessed. The study intervention consists of targeted feedback reports generated using the OPEN Stewardship platform. After a 3-month preintervention period, a cohort of veterinarians (treatment cohort, n=120) will receive three feedback reports over the course of 6 months while the remainder of the veterinarians (n=20) will be the control cohort. A survey will be administered among the treatment cohort after each feedback cycle to assess the usability and usefulness of various elements of the feedback report. A multilevel negative-binomial regression analysis of the preintervention and postintervention antibiotic prescribing of the treatment cohort will be performed to evaluate the impact of the intervention. ETHICS AND DISSEMINATION: Research ethics board approval was obtained at each participating site prior to the recruitment of the veterinarians. The study findings will be disseminated through open-access scientific publications, stakeholder networks and national/international meetings.