Title: Mosquito Surveillance 101
Speaker: Paul Proctor
Supervisor, Environmental Health,
Vector-Borne Disease Team Region of Peel, Ontario
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Abstract: Mosquito surveillance is a key component of an effective West Nile Virus program. Surveillance is used to define the nature and extent of the mosquito population which assists in guiding larviciding activities and educational measures. Mosquito surveillance data is also valuable when developing predictive models for human cases.
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Title: An overview of health economic projects on West Nile virus and Lyme disease
Speaker: Beate Sander
Public Health Ontario
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Abstract: With warming temperatures and changing precipitation patterns, vector-borne diseases including West Nile virus (WNv) and Lyme disease are of increasing concern in North America. In one study, we evaluate the cost-effectiveness of WNv mitigation strategies. One component is to predict downstream health outcomes and cost of WNv illness using a microsimulation. We model the course of illness in patients over their lifetime including hospitalizations, recovery and death using parameters from laboratory data, clinical data, administrative data and public health unit data.
The objective of our study on Lyme disease is two-fold. First, we aim to use data from the provincial reportable disease registry and public health laboratories to assess the overall quality of Lyme disease reporting in Ontario. Second, we will apply a retrospective matched cohort design to estimateincidence-based attributable cost per case of acute Lyme disease as well as long-term sequelae.
Understanding the current health and economic burden of West Nile virus and Lyme disease contributes to the growing body of research on emerging diseases in Canada and supports strategic public health planning and effective interventions.
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Title: Statistical Modelling of Mosquito Abundance with Weather Conditions
Speaker: Yurong Cao
LAMPS, Department of Mathematics, York University
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Abstract: Weather affects the abundance of mosquito vectors of mosquito-borne infectious diseases such as West Nile virus (WNv). Study and prediction of these effects could be used to develop disease forecasting methods. In this research, the mosquito data of Culex pipens /restuans species from the surveillance program in Peel Region, Ontario for the period from 2004 to 2011 was used to study the effect of weather conditions. We proposed to combine the finite mixture model and Markov regression models to build model-based clustering with generalized linear regression for the time series of the mosquito abundance data in Peel Region. The parameter estimation is performed by the maximum likelihood method through the Expectation-Maximization (EM) algorithm. Results from the simulation showed that the proposed clustering algorithm can successfully estimate the model parameters and the standard the error of the estimation was quite small. Moreover, the algorithm was used to predict the mosquito abundance in 2012 and the forecasting result from the model based clustering outperformed the traditional clustering method. This is a joint work with Professor Xin Gao and Huaiping Zhu.
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Title: Modeling and forecasting of culex mosquito abundance, virus risk and cases of human infection
Speaker: Wenzhe Li
LAMPS, Department of Mathematics, York University
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Abstract: West Nile virus (WNv) is a mosquito borne virus that can cause severe illness including encephalitis and can sometimes result in long-term complications and death. The risk of WNv varies from year to year based on temperature, precipitation, mosquito populations and other factors. So it is essential to predict the mosquito population and even the risk of WNv during mosquito seasons which can directly give a forewarning. Based on the surveillance program conducted by the government of Great Toronto Area, records of mosquito abundance and positive pools are collected weekly and we can get the data in Peel region and Halton region. Based on these surveillance data, weather data, we develop forecasting models for the mosquito abundance and risk index MIR as well as cases of human infection of the virus. The real time forecasting results are reported to Public Health agencies and health units weekly, and available to public through Lamps web.
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Title: Mosquito abundance and West Nile Virus prediction by using Meteorological Services Canada seasonal prediction model data
Speaker: Khalid Malik
Lamps, York University
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Abstract: A climate based model for predicting mosquito abundance and West Nile Virus (WNV) has been developed for different municipalities including Halton, Toronto, York, Peel and Durham regions of Great Toronto Area (GTA). The mosquito population dynamics are driven by major environmental factors including temperature and precipitation. The statistical model of mosquito abundance and WNV risk assessment is based on MSC observed climate data and mosquito surveillance data of respective municipalities from mid-June to early October (weeks 24-40) for the period of 2002-2014. Results show good correlation among weather conditions (temperature and precipitation), mosquito abundance and WNV risk assessment. This statistical model is then used to predict mosquito abundance and WNV dynamics on regional basis by using 15 days weather prediction data of the North American Ensemble Forecast System (NAEFS) of Meteorological Services Canada (MSC). The weather prediction data of 1.0 x1.0 horizontal resolution is then downscaling at 20 km resolution and constructs dataset of each sub-region of GTA by grouping grid points located in respective sub regions. Prediction model showed well associated of 12 preceding mean degree–days temperature (only) with mosquito abundance in Peel region, and precipitation of 49 preceding days and 17 preceding mean degree–days temperature (both) with Halton region. These associations permit real-time monitoring and prediction of mosquito abundance and risk of WNV dynamics on spatial and temporal resolution. These predictions will enable health agencies to establish control measures before the mosquitoes emerge in the region
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Title: Assessing Climate Change Impacts on Mosquito Abundance in Ontario
Part 2: Including the Normalized Differentiate Water Index
Speaker: Yuehua Liu
Leslie Dan Faculty of Pharmacy, University of Toronto
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Abstract: The latest Inter-government Panel for Climate Change (IPCC) 5th Assessment Report (AR5) provided more confidence that climate has been changing and will continue to change. Weather/climate variations affect mosquito populations. Mosquito abundance is a key risk factor in outbreak and spread of vector-borne diseases such as West Nile Virus (WNV). The primary objective of this study is to explore how future mosquito abundance would evolve under the changing climate in Ontario, Canada. This is one of the few studies on mosquito abundance predictive model development at monthly-temporal and provincial-spatial scales in Ontario. First, relations between climate indicators, temperature and precipitation, water index, and Culex pipiens L. and Culex restuans Theobald mosquito abundance was investigated in the province of Ontario, Canada, using the best available 2002-2012 mosquito abundance data. A predictive statistical model for monthly mosquito population was developed based on monthly averages of temperature, precipitation, water index and mosquito counts from 2002 to 2010, and then validated using surveillance data in 2011 and 2012. Results showed that monthly mosquito abundance could be predicted with reasonable accuracy from monthly mean temperature, one-month lagged temperature, precipitation, one-month and two-month lagged precipitation, water index, one-month and two-month lagged water index. The constructed model was subsequently used to project the potential spatial and temporal distribution of mosquito abundance over the entire Province of Ontario under a range of potential future climate and land use conditions. Three time periods were selected to represent future climate conditions, i.e., 2030s (2015–2045), 2050s (2035–2065) and 2080s (2065–2095). Under the potential future climate changes, the developed model projected a general increasing trend in mosquito abundance over almost the entire province with obvious northward spatial expansion, as well as temporal expansion-longer mosquito seasons. This indicates potentially increased risks of WNV and more intensive mosquito monitoring and controlling measures would be needed in Ontario considering future climate change.
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Title: Modeling Discrete Environmental Processes with Unobservable Information through Dimension Expansion and application to model the mosquito abundance in Ontario
Speaker: Longbin Chen
LAMPS, Department of Mathematics, York University
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Abstract: In this study, we extend the dimension expansion method by Bornn et al. (2012) to discrete spatial and temporal processes. The proposed method works by modelling the collective impact of unobservable information by exploring extra dimension at each spatial location. We evaluate the proposed method by modelling mosquito abundance patterns in Peel Region, Ontario in Canada. Results from data analysis and simulation studies have suggested that the proposed model can significantly improve the generalized linear model based on incomplete information. This is a work supervised by Professor Steven Wang and Professor Huaiping Zhu.
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Title: IS THERE A RISK OF CHIKUNGUNYA TRANSMISSION IN CANADA?
Speaker: Min Weng
York University
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Abstract: In this talk, I will introduce a survey of mosquito-borne diseases, Chikungunya and presented the four key aspects to examine the risk of Chikungunya transmission within Canada. Based on the analysis of the risk of a Chikungunya outbreak in Canada and the mechanism of its transmission, we establish a compartmental model which takes the temperature factor into consideration, to study the transmission of Chikungunya between human and vector mosquitoes. By some preliminary analysis, we investigate the conditions from the model with delay and conclude that the risk will be increasing if the daily average temperature becomes higher.
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Title: Temperature-driven, single-season mosquito abundance model for West Nile virus vector species Culex pipiens and Culex resturans
Speaker: Don Yu
LAMPS, Department of Mathematics, York University
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Abstract: Vector-borne diseases account for more than 17% of all infectious diseases worldwide and cause more than 1 million deaths annually. Understanding the relationship between environmental factors and their influence on vector biology is imperative in the fight against vector-borne diseases such as West Nile virus. We develop a temperature driven mosquito abundance model for West Nile vector species, Culex pipiens and Culex restuans. Temperature dependent response functions for mosquito development, mortality, and diapause were formulated based on results from published field and laboratory studies. Preliminary results of model simulations compared to observed mosquito traps counts from 2004-2014 demonstrate the capacity of our model to predict the observed variability of the mosquito population in the Peel Region of southern Ontario over a single season. The proposed model has potential to be used as a real-time mosquito abundance forecasting tool and would have direct application in mosquito control programs. This is a work under the supervision of Professor Neal Madras and Huaiping Zhu.
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Title: The influence of pesticide on the dynamic of mosquito population with difference model
( Does pesticide help the control of mosquito abundance?)
Speaker: Lie Wang
Shannxi Normal University and Lamps York University
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Abstract: In this talk, I will introduce a temperature forced vente viagra au senegal difference model considering the effect of chemical control on the dynamics of mosquito population. First, the control on the mosquitoes and mosquito surveillance program are introduced. Next a temperature forced difference model with chemical control for the abundance of mosquitoes is formulated. Finally, through the modeling and numerical simulations we will try to explore the different scenarios of mosquito control under different weather patterns.
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Title: A diffusion logistic model with a free boundary for mosquitoes' movement driven by climate warming
Speaker: Wendi Bao
China University of Petroleum and Lamps York University
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Abstract: As mosquitoes are vectors of major pathogens worldwide, the control of mosquito populations is one way to fight vector borne diseases. Its spread is of increasing public health concern, and there is a need for appropriate monitoring tools. In this paper, we propose a diffusive logistic problem with the free boundary representing an expanding front to model range shifts of mosquitoes. The model is temperature-driven, takes into account mosquitoes' response to climate change by shifting their range boundaries and mosquitoes' diapause during unfavourable periods. We then give the parameter values based on temperature data, and apply the finite difference method and Newton-Raphson method to solve the model. Lastly, we performed a numerical sensitivity analysis to identify the key parameters of the mosquito population dynamics. Numerical simulation of the model shows that mosquitoes' response to increasing latitudes makes the free boundary h(t) is bounded as time t goes to infinity. Meanwhile, results illustrate some known conclusions are true.
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Title: Projection of Extreme Weather Indicators for Rural Resilience in Southern Ontario
Speaker: Ziwang Deng
LAMPS, Department of Mathematics, York University
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Abstract: Through a literature survey, fifteen indicators representing annual frequencies of extreme heat, cold and wet weather/climate events were identified. These climatological indicators were calculated on 20 grid points in the Greater Toronto Area and eastern Ontario. Statistical downscaling data from 14 GCMs under RCP8.5 scenario were used for validation and projection. The third generation high-resolution NCEP reanalysis data (CFSR) was used as observation for validation. Some nonparametric statistical methods were used to examine whether the downscaling data can capture the statistical characteristics of these indicators. The results show that the downscaling data captured key statistics of some extreme indicators but with much narrow PDFs than observations. As the globe is continuing warming, the PDFs of frequencies of extreme heat (cold) events shift to higher (lower) value. Thus, the frequencies of some extreme heat events will significantly increase in the 21st century. The increasing amplitudes of frequencies of extreme heat events are larger in GTA than in the eastern Ontario. Under the scenario RCP8.5, frequencies of extreme storms will significantly increase, for example, current 100-year storms may become 50-year storms in both area in Southern Ontario by the end of the century. The N-year period levels will significantly increase as well. There is significant uncertainty in the indicators due to many different analytical and theoretical assumptions associated with each dataset and further research is needed. This is a joint work with Huaiping Zhu, Xiaolan Zhou, Harris Switzman, Shelley Hazen and Waldick Ruth.
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Title: SEMI-WAVE AND SPREADING SPEED FOR THE DIFFUSIVE
COMPETITION MODEL WITH A FREE BOUNDARY
Speaker: Yihong Du
University of New England, Australia
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Abstract: We determine the asymptotic spreading speed of an invasive species, which invades the territory of a native competitor, governed by a diffusive competition model with a free boundary in a spherically symmetric setting. We show that there exists an asymptotic spreading speed, which is determined by a certain traveling wave type system of one space dimension, called a semi-wave. This appears to be the first result that gives the precise asymptotic spreading speed for a two species system with free boundaries. This talk is based on recent joint work with Zhigui Lin (Yangzhou Univ), Mingxin Wang (Harbin Inst Tech) and Maolin Zhou (University of New England).
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Title: The spreading front of West Nile virus and its basic reproduction numbers
Speaker: Zhigui Lin
Yangzhou University
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Abstract: In this talk, a diffusion reaction system is proposed to study the spatial spreading of West Nile virus in North America. The free boundary is introduced to describe the spreading front of virus. To check the effect of spatial heterogeneity and habitat characteristic on the spreading of the virus, four basic reproduction numbers $R_0$, $R_0^N$, $R_0^D$ and $R_0^F(t)$ are given for the simplified WNv model, which defined in homogenies environment, in a bounded environment with no flux, in a bounded environment with hostile boundary and in an expanding environment, respectively. Our results show that the virus will spread in the high-risk habitat if the diffusion is slow or the infected habitat is large; In a low-risk habitat, small initial infected habitat, small initial numbers of the virus and fast diffusion are benefit for the virus to vanish. When the virus spreads in the whole habitat, the asymptotic spreading speed is given.
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Title: Compartmental modeling for the transmission of Dengue in Guanzhou, China
Speaker: Wenjing Zhang
Lamps, York University
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Abstract: Dengue, a mosquito-borne viral disease, hit a Chinese metropolis capital city Guangzhou in 2014, and caused the worst outbreak in two decades. Epidemiological and serological studies reveal three main reasons, which are unusual hot and warm weather, subsequent infection caused by co-circulation of multiple serotypes of dengue viruses, and imported infected cases from international travelling. Compartmental model is formulated to express the subsequent infection and imported cases, and then associated with a predictive statistic model [1] to describe the impact of weather conditions on mosquito abundance. The basic reproduction number [2, 3], R0, is derived to measure the ability of dengue outbreak in human population. Incorporating the local weather conditions and travelling cases, our simulation results demonstrate the complex dynamics of the dengue transmission, in particularly, reveal the triggering factors responsible for the Guangzhou dengue outbreak in 2014.
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Title: Mosquito augmentation and control of mosquitoes and dengue fever: the questions and challenge
Speaker: Huaiping Zhu
York University
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Speakers:
Wendi Bao, China University of Petroleum and Lamps York University
Rick Bello, York University
Yurong Cao, Lamps, York University
Longbin Chen, Lamps, York University
Ziwang Deng, Lamps, York University
Yihong Du, University of New England, Australia
Xin Gao, Lamps, York University
Khalid Malik, Lamps, York University
Wenzhe Li, Lamps, York University
Zhigui Lin, Yangzhou University, China
Yuehua Liu, Leslie Dan Faculty of Pharmacy, University of Toronto
Paul Proctor, Supervisor, Environmental Health, Vector-Borne Disease Team Region of Peel, Ontario
Beate Sander, Public Health Ontario (PHO), University of Toronto
Emily Shing, Public Health Ontario (PHO)
Lie Wang, Shannxi Normal University and Lamps York University
Steven Wang, Lamps, York University
Min Weng, York University
Man Wah Yeung, Public Health Ontario (PHO),
Don Yu, Lamps, York University
Wenjing Zhang, Lamps, York University
Hui Zheng, Public Health Agency of Canada
Huaiping Zhu, Lamps, York University
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