Criteria for selecting sentinel unit locations in a surveillance system for vector-borne disease: A decision tool.

Objectives: With vector-borne diseases emerging across the globe, precipitated by climate change and other anthropogenic changes, it is critical for public health authorities to have well-designed surveillance strategies in place. Sentinel surveillance has been proposed as a cost-effective approach to surveillance in this context. However, spatial design of sentinel surveillance system has important impacts on surveillance outcomes, and careful selection of sentinel unit locations is therefore an essential component of planning. Methods: A review of the available literature, based on the realist approach, was used to identify key decision issues for sentinel surveillance planning. Outcomes of the review were used to develop a decision tool, which was subsequently validated by experts in the field. Results: The resulting decision tool provides a list of criteria which can be used to select sentinel unit locations. We illustrate its application using the case example of designing a national sentinel surveillance system for Lyme disease in Canada. Conclusions: The decision tool provides researchers and public health authorities with a systematic, evidence-based approach for planning the spatial design of sentinel surveillance systems, taking into account the aims of the surveillance system and disease and/or context-specific considerations.

A Portrait of Sentinel Surveillance Networks for Vector-Borne Diseases: A Scoping Review Supporting Sentinel Network Design.

Vector-borne diseases (VBDs) are continuing to emerge globally, requiring new surveillance systems to follow increasing VBD risk for human populations. Sentinel surveillance is an approach that allows tracking of disease risk through time using limited resources. However, there is no consensus on how best to design a sentinel surveillance network in the context of VBDs. We conducted a scoping review to compare VBD sentinel surveillance systems worldwide with the aim of identifying key design features associated with effective networks. Overall, VBD surveillance networks were used most commonly for malaria, West Nile virus, and lymphatic filariasis. A total of 45 criteria for the selection of sentinel unit location were identified. Risk-based criteria were the most often used, and logistic regression showed that using risk-based criteria dependent on host animals is particularly correlated with surveillance system sensitivity (p < 0.018). We identify tools that could prove valuable for sentinel surveillance network design, including a standardized approach for evaluating surveillance systems and a tool to prioritize criteria for selecting optimal geographic locations for spatial sentinel units.

Modelling scenarios of the epidemic of COVID-19 in Canada.

BACKGROUND: Severe acute respiratory syndrome virus 2 (SARS-CoV-2), likely a bat-origin coronavirus, spilled over from wildlife to humans in China in late 2019, manifesting as a respiratory disease. Coronavirus disease 2019 (COVID-19) spread initially within China and then globally, resulting in a pandemic. OBJECTIVE: This article describes predictive modelling of COVID-19 in general, and efforts within the Public Health Agency of Canada to model the effects of non-pharmaceutical interventions (NPIs) on transmission of SARS-CoV-2 in the Canadian population to support public health decisions. METHODS: The broad objectives of two modelling approaches, 1) an agent-based model and 2) a deterministic compartmental model, are described and a synopsis of studies is illustrated using a model developed in Analytica 5.3 software. RESULTS: Without intervention, more than 70% of the Canadian population may become infected. Non-pharmaceutical interventions, applied with an intensity insufficient to cause the epidemic to die out, reduce the attack rate to 50% or less, and the epidemic is longer with a lower peak. If NPIs are lifted early, the epidemic may rebound, resulting in high percentages (more than 70%) of the population affected. If NPIs are applied with intensity high enough to cause the epidemic to die out, the attack rate can be reduced to between 1% and 25% of the population. CONCLUSION: Applying NPIs with intensity high enough to cause the epidemic to die out would seem to be the preferred choice. Lifting disruptive NPIs such as shut-downs must be accompanied by enhancements to other NPIs to prevent new introductions and to identify and control any new transmission chains.

Assessing the impact of varying levels of case detection and contact tracing on COVID-19 transmission in Canada during lifting of restrictive closures using a dynamic compartmental model.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic began with a detected cluster of pneumonia cases in Wuhan, China in December 2019. Endemic transmission was recognized in Canada in early February 2020, making it urgent for public health stakeholders to have access to robust and reliable tools to support decision-making for epidemic management. The objectives of this paper are to present one of these tools-an aged-stratified dynamic compartmental model developed by the Public Health Agency of Canada in collaboration with Statistics Canada-and to model the impact of non-pharmaceutical interventions on the attack rate of COVID-19 infection in Canada. METHODS: This model simulates the impact of different levels of non-pharmaceutical interventions, including case detection/isolation, contact tracing/quarantine and changes in the level of physical distancing in Canada, as restrictive closures began to be lifted in May 2020. RESULTS: This model allows us to highlight the importance of a relatively high level of detection and isolation of cases, as well as tracing and quarantine of individuals in contact with those cases, in order to avoid a resurgence of the epidemic in Canada as restrictive closures are lifted. Some level of physical distancing by the public will also likely need to be maintained. CONCLUSION: This study underlines the importance of a cautious approach to lifting restrictive closures in this second phase of the epidemic. This approach includes efforts by public health to identify cases and trace contacts, and to encourage Canadians to get tested if they are at risk of having been infected and to maintain physical distancing in public areas.

A scoping review of published literature on chikungunya virus.

Chikungunya virus (CHIKV) has caused several major epidemics globally over the last two decades and is quickly expanding into new areas. Although this mosquito-borne disease is self-limiting and is not associated with high mortality, it can lead to severe, chronic and disabling arthritis, thereby posing a heavy burden to healthcare systems. The two main vectors for CHIKV are Aedes aegypti and Aedes albopictus (Asian tiger mosquito); however, many other mosquito species have been described as competent CHIKV vectors in scientific literature. With climate change, globalization and unfettered urban planning affecting many areas, CHIKV poses a significant public health risk to many countries. A scoping review was conducted to collate and categorize all pertinent information gleaned from published scientific literature on a priori defined aspects of CHIKV and its competent vectors. After developing a sensitive and specific search algorithm for the research question, seven databases were searched and data was extracted from 1920 relevant articles. Results show that CHIKV research is reported predominantly in areas after major epidemics have occurred. There has been an upsurge in CHIKV publications since 2011, especially after first reports of CHIKV emergence in the Americas. A list of hosts and vectors that could potentially be involved in the sylvatic and urban transmission cycles of CHIKV has been compiled in this scoping review. In addition, a repository of CHIKV mutations associated with evolutionary fitness and adaptation has been created by compiling and characterizing these genetic variants as reported in scientific literature.

Campylobacter in recreational lake water in southern Quebec, Canada: presence, concentration, and association with precipitation and ruminant farm proximity.

Campylobacter is an important cause of gastrointestinal illness and exposure to recreational water is one potential source of infection. The objective of this study was to investigate the presence and concentrations of Campylobacter, and determine the influence of agricultural activities and precipitation on their presence, at lake beaches used for water recreation in southern Quebec, Canada. A total of 413 water samples were collected from June to August, from 22 beaches, between 2011 and 2013. The overall proportion of positive water samples was estimated to be 33.9% (95% CI: 27.7, 40.1) for C. jejuni and 49.7% (95% CI: 41.8, 57.6) for Campylobacter spp. The concentrations of both thermotolerant Campylobacter spp. and C. jejuni ranged from 20 to 900 bacteria/L of water. Logistic regressions showed that the presence of C. jejuni and Campylobacter spp. was significantly associated with the year and season. Other significant predictors of C. jejuni, but not Campylobacter spp., included the presence of precipitation the day before sampling and the presence of ruminant farms within a 5 km radius of the beach. The present study provides insights into the risk of Campylobacter presence in recreational lake water for better understanding public health risks.

Identifying associations in Escherichia coli antimicrobial resistance patterns using additive Bayesian networks.

While the genesis of antimicrobial resistance (AMR) in animal production is a high profile topic in the media and the scientific community, it is still not well understood. The epidemiology of AMR is complex. This complexity is demonstrated by extensive biological and evolutionary mechanisms which are potentially impacted by farm management and husbandry practices - the risk factors. Many parts of this system have yet to be fully described. Notably, the occurrence of multiple resistance patterns is the rule rather than exception - the multivariate problem. A first essential step in the development of any comprehensive risk factor analysis - whose goal is the prevention or reduction of AMR - is to describe those associations between different patterns of resistance which are systematic. That is, have sufficient statistical support for these patterns to be considered robust features of the underlying epidemiological system, and whose presence must therefore be incorporated into any risk factor analysis of AMR for it to be meaningful with respect to the farm environment. Presented here is a case study that seeks to identify systematic associations between patterns of resistance to 13 different antimicrobials in Escherichia coli isolates obtained from composite finisher (>80 kg) pig faecal samples obtained from Canada's five major pork producing provinces. The use of a Bayesian network analysis approach allowed us to identify many systematic associations between individual antimicrobial resistances. Sixteen of these resistances are corroborated with existing literature. These associations are distributed between several important classes of antimicrobials including the ß-lactams, folate biosynthesis inhibitors, tetracyclines, aminoglycosides and quinolones. This study presents an exciting first step towards the larger and far more ambitious goal of developing generic and holistic risk factor analyses for on-farm occurrence of AMR. Analyses of this nature would combine multivariate response variables (joint patterns of resistance) with multi-factorial causal factors from within the livestock production environment thereby permitting a more complete understanding of the epidemiology of antimicrobial resistance.