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The first case of HIV in Pakistan was documented in 1987, with multiple subtypes and circulating recombinant forms being introduced and currently circulating in the country. Since then, there has been a shift in the country from a low prevalence/high risk to a high-risk concentrated epidemic. Pakistan’s epidemic is concentrated among key populations at greater risk of HIV infection including people who inject drugs (PWID), Hijra sex workers (HSW), female sex workers (FSW), male sex workers (MSW), and men who have sex with men (MSM). This study focused on the geographical aspect as well as on the interactions between key populations at higher risk of contracting HIV. We aimed at understanding the behavior of these key populations at a molecular level with high granularity as well as investigating the possibility of multiple HIV-1 introductions in Pakistan. In this cross-sectional biological and behavioral survey, we collected dried blood spots (DBS) for the purposes of seroprevalence estimates and molecular epidemiology from individuals in 17 cities in Pakistan representing four key populations: PWID, HSW, MSW, and FSW. A total of 1153 envelope sequences (reference positions in HXB2: 7860-8274) of HIV were sequenced using a Sanger-based sequencing approach. To identify clusters based on the introduction of the virus in Pakistan from foreign countries we added 3623 publicly available HIV envelope sequences to our dataset. Phylogeographic inference suggests at least 15 independent introductions of the virus into Pakistan, with a total of 12 clusters ranging from 3 to 675 sequences in size containing sequences from Pakistan and neighboring countries exclusively. Our phylogenetic analysis shows a significant degree of connectivity and directionality suggesting broad and overlapping networks of HIV-1 transmission among cities and key populations in Pakistan.

Background: The geographic range of the tick Amblyomma americanum, a vector of diseases of public health significance such as ehrlichiosis, has expanded from the southeast of the United States northward during the 20th century. Recently, populations of this tick have been reported to be present close to the Canadian border in Michigan and New York states, but established populations are not known in Canada. Previous research suggests that changing temperature patterns with climate change may influence tick life cycles and permit northward range expansion of ticks in the northern hemisphere. Objectives: We aimed to estimate minimal temperature conditions for survival of A. americanum populations at the northern edge of the tick’s range and to investigate the possibility of range expansion of A. americanum into northern U.S. states and southern Canada in the coming decades. Methods: A simulation model of the tick A. americanum was used, via simulations using climate data from meteorological stations in the United States and Canada, to estimate minimal temperature conditions for survival of A. americanum populations at the northern edge of the tick’s range. Results: The predicted geographic scope of temperature suitability [≥3,285 annual cumulative degree days (DD) >0°C] included most of the central and eastern U.S. states east of longitude 110°W, which is consistent with current surveillance data for the presence of the tick in this region, as well as parts of southern Quebec and Ontario in Canada. Regional climate model output raises the possibility of northward range expansion into all provinces of Canada from Alberta to Newfoundland and Labrador during the coming decades, with the greatest northward range expansion (up to 1,000km by the year 2100) occurring under the greenhouse gas (GHG) emissions of Representative Concentration Pathway (RCP) 8.5. Predicted northward range expansion was reduced by approximately half under the reduced GHG emissions of RCP4.5. Discussion: Our results raise the possibility of range expansion of A. americanum into northern U.S. states and southern Canada in the coming decades, and conclude that surveillance for this tick, and the diseases it transmits, would be prudent. https://doi.org/10.1289/EHP5668

Background: The geographic range of the tick Amblyomma americanum, a vector of diseases of public health significance such as ehrlichiosis, has expanded from the southeast of the United States nort...

SUMMARYWidespread access to the internet is offering new possibilities for data collection in surveillance. We explore, in this study, the possibility of using an electronic tool to monitor occurrence of the tick vector of Lyme disease, Ixodes scapularis. The study aimed to compare the capacity for ticks to be identified in web-based submissions of digital images/photographs, to the traditional specimen-based identification method used by the provincial public health laboratory in Quebec, Canada. Forty-one veterinary clinics participated in the study by submitting digital images of ticks collected from pets via a website for image-based identification by an entomologist. The tick specimens were then sent to the provincial public health laboratory to be identified by the ‘gold standard’ method using a microscope. Of the images submitted online, 74·3% (284/382) were considered of high-enough quality to allow identification. The laboratory identified 382 tick specimens from seven different species, with I. scapularis representing 76% of the total submissions. Of the 284 ticks suitable for image-based species identification, 276 (97·2%) were correctly identified (Kappa statistic of 0·92, Z = 15·46, P < 0·001). This study demonstrates that image-based tick identification may be an accurate and useful method of detecting ticks for surveillance when images are of suitable quality.

Lyme disease, the most commonly reported vector-borne disease in North America, is caused by the spirochete Borrelia burgdorferi sensu stricto, which is transmitted by Ixodes scapularis in eastern Canada and Ixodes pacificus in western Canada. Recently, the northward range expansion of I. scapularis ticks, in south-eastern Canada, has resulted in a dramatic increase in the incidence of human Lyme disease. Detecting emerging areas of Lyme disease risk allows public health to target disease prevention efforts. We analysed passive tick surveillance data from Ontario and Manitoba to i) assess the relationship between the total numbers of I. scapularis submissions in passive surveillance from humans, and the number of human Lyme disease cases, and ii) develop province-specific acarological indicators of risk that can be used to generate surveillance-based risk maps. We also assessed associations between numbers of nymphal I. scapularis tick submissions only and Lyme disease case incidence. Using General Estimating Equation regression, the relationship between I. scapularis submissions (total numbers and numbers of nymphs only) in each census sub-division (CSD) and the number of reported Lyme disease cases was positively correlated and highly significant in the two provinces (P ≤ 0.001). The numbers of I. scapularis submissions over five years discriminated CSDs with ≥ 3 Lyme disease cases from those with < 3 cases with high accuracy when using total numbers of tick submission (Receiver Operating Characteristics area under the curve [AUC] = 0.89) and moderate accuracy (AUC = 0.78) when using nymphal tick submissions only. In Ontario the optimal cut-off point was a total 12 tick submissions from a CSD over five years (Sensitivity = 0.82, Specificity = 0.84), while in Manitoba the cut-off point was five ticks (Sensitivity = 0.71, Specificity = 0.79) suggesting regional variability of the risk of acquiring Lyme disease from an I. scapularis bite. The performances of the acarological indicators developed in this study for Ontario and Manitoba support the ability of passive tick surveillance to provide an early signal of the existence Lyme disease risk areas in regions where ticks and the pathogens they transmit are expanding their range.

Background Zika virus (ZIKV) spread rapidly in the Americas in 2015. Targeting effective public health interventions for inhabitants of, and travellers to and from, affected countries depends on understanding the risk of ZIKV emergence (and re-emergence) at the local scale. We explore the extent to which environmental, social and neighbourhood disease intensity variables influenced emergence dynamics. Our objective was to characterise population vulnerability given the potential for sustained autochthonous ZIKV transmission and the timing of emergence. Logistic regression models estimated the probability of reporting at least one case of ZIKV in a given municipality over the course of the study period as an indicator for sustained transmission; while accelerated failure time (AFT) survival models estimated the time to a first reported case of ZIKV in week t for a given municipality as an indicator for timing of emergence. Results Sustained autochthonous ZIKV transmission was best described at the temporal scale of the study period (almost one year), such that high levels of study period precipitation and low mean study period temperature reduced the probability. Timing of ZIKV emergence was best described at the weekly scale for precipitation in that high precipitation in the current week delayed reporting. Both modelling approaches detected an effect of high poverty on reducing/slowing case detection, especially when inter-municipal road connectivity was low. We also found that proximity to municipalities reporting ZIKV had an effect to reduce timing of emergence when located, on average, less than 100 km away. Conclusions The different modelling approaches help distinguish between large temporal scale factors driving vector habitat suitability and short temporal scale factors affecting the speed of spread. We find evidence for inter-municipal movements of infected people as a local-scale driver of spatial spread. The negative association with poverty suggests reduced case reporting in poorer areas. Overall, relatively simplistic models may be able to predict the vulnerability of populations to autochthonous ZIKV transmission at the local scale. Electronic supplementary material The online version of this article (10.1186/s13071-018-2867-8) contains supplementary material, which is available to authorized users.

Public health risks related to the microbial contamination of recreational waters are increased by global environmental change. Intensification of agriculture, urban sprawl, and climate change are some of the changes which can lead to favorable conditions for the emergence of waterborne diseases. Earth observation (EO) images have several advantages for the characterization and monitoring of environmental determinants that could be associated with the risk of microbial contamination of recreational waters in vast territories like Canada. There are a large number of EO systems characterized by different spatial, temporal, spectral, and radiometric resolutions. Also, they have different levels of accessibility. In this study, we compared several EO systems for the estimation of environmental determinants to assess their usefulness and their added value in monitoring programs of recreational waters. Satellite images from EO systems WorldView-2, GeoEye-1, SPOT-5/HRG, Landsat-5/TM, Envisat/MERIS, Terra/MODIS, NOAA/AVHRR, and Radarsat-2 were acquired in 2010 and 2011 in southern Quebec, Canada. A supervised classification of these images with a maximum likelihood algorithm was used to estimate five key environmental determinants (agricultural land, impervious surfaces, water, forest, and wetlands) within the area of influence of 78 beaches. Logistic regression models were developed to establish the relationship between fecal contamination of beaches and environmental determinants derived from satellite images. The power prediction of these models and criteria such as accuracy of classified images, the ability of the sensor to detect environmental determinants in the area of influence of beaches, the correlation between the estimated environmental determinants in the area of influence by the sensor with those estimated by very high spatial resolution reference sensors (WorldView-2 and GeoEye-1), and general criteria of accessibility (cost of the images, imaging swath, satellite revisit interval, hours of work, and expertise and material required to process the images) were used to evaluate the EO systems. The logistic regression model establishing the relationship between environmental determinants from Landsat-5/TM images and the level of fecal contamination of beaches is the one which performs best. These images are also those that best meet all of the evaluation criteria. This study showed that environmental determinants like agricultural lands and impervious surfaces present in the area of influence of beaches are those which contribute the most to the microbial contamination of beaches. Our study demonstrated the utility and the added value that EO images could bring to programs monitoring the microbial contamination of recreational waters.

Background: The risk of contracting Lyme disease (LD) can vary spatially because of spatial heterogeneity in risk factors such as social-behavior and exposure to ecological risk factors. Integrating these risk factors to inform decision-making should therefore increase the effectiveness of mitigation interventions. Objectives: The objective of this study was to develop an integrated social-behavioral and ecological risk-mapping approach to identify priority areas for LD interventions. Methods: The study was conducted in the Montérégie region of Southern Quebec, Canada, where LD is a newly endemic disease. Spatial variation in LD knowledge, risk perceptions, and behaviors in the population were measured using web survey data collected in 2012. These data were used as a proxy for the social-behavioral component of risk. Tick vector population densities were measured in the environment during field surveillance from 2007 to 2012 to provide an index of the ecological component of risk. Social-behavioral and ecological components of risk were combined with human population density to create integrated risk maps. Map predictions were validated by testing the association between high-risk areas and the current spatial distribution of human LD cases. Results: Social-behavioral and ecological components of LD risk had markedly different distributions within the study region, suggesting that both factors should be considered for locally adapted interventions. The occurrence of human LD cases in a municipality was positively associated with tick density (p

A mechanistic model of the tick vector of Lyme disease, Ixodes scapularis, was adapted to a deterministic structure. Using temperature normals smoothed by Fourier analysis to generate seasonal temperature-driven development rates and host biting rates, and a next generation matrix approach, the model was used to obtain values for the basic reproduction number (R(0)) for I. scapularis at locations in southern Canada where the tick is established and emerging. The R(0) at Long Point, Point Pelee and Chatham sites where I. scapularis are established, was estimated at 1.5, 3.19 and 3.65, respectively. The threshold temperature conditions for tick population survival (R(0)=1) were shown to be the same as those identified using the mechanistic model (2800-3100 cumulative annual degree days >0°C), and a map of R(0) for I. scapularis, the first such map for an arthropod vector, was drawn for Canada east of the Rocky Mountains. This map supports current risk assessments for Lyme disease risk emergence in Canada. Sensitivity analysis identified host abundance, tick development rates and summer temperatures as highly influential variables in the model, which is consistent with our current knowledge of the biology of this tick. The development of a deterministic model for I. scapularis that is capable of providing values for R(0) is a key step in our evolving ability to develop tools for assessment of Lyme disease risk emergence and for development of public health policies on surveillance, prevention and control.

Lyme disease is emerging in Canada due to geographic range expansion of the tick vector Ixodes scapularis Say. Recent areas of emergence include parts of the southeastern Canadian Prairie region. We developed a map of potential risk areas for future I. scapularis establishment in the Canadian Prairie Provinces. Six I. scapularis risk algorithms were developed using different formulations of three indices for environmental suitability: temperature using annual cumulative degree-days 0 °C (DD 0 °C; obtained from Moderate Resolution Imaging Spectroradiometer satellite data as an index of conditions that allow I. scapularis to complete its life cycle), habitat as a combined geolayer of forest cover and agricultural land use, and rainfall. The relative performance of these risk algorithms was assessed using receiver-operating characteristic (ROC) area under the curve (AUC) analysis with data on presence-absence of I. scapularis obtained from recent field surveillance in the Prairie Provinces accumulated from a number of sources. The ROC AUC values for the risk algorithms were significantly different (P 0.01). The algorithm with six categories of DD 0 °C, habitat as a simple dichotomous variable of presence or absence of forest, and normalized rainfall had the highest AUC of 0.74, representing "fair to good" performance of the risk algorithm. This algorithm had good (80%) sensitivity in predicting positive I. scapularis surveillance sites, but low (50%) specificity as expected in this region where not all environmentally suitable habitats are expected to be occupied. Further prospective studies are needed to validate and perhaps improve the risk algorithm.

Lyme disease (LD) is emerging in Canada. A key preventive strategy is promoting the adoption by the general public of personal preventive behaviors regarding tick bites. The aim of this study was to measure the changes in public awareness toward ticks and LD before and after the launch of a national communication campaign in Canada using data from two surveys conducted in March and December 2014. The results show a significant increase in awareness of LD after compared to before the campaign, but also suggest that the importance of this increase is not equal amongst Canadian regions. Moreover, respondents whose level of awareness increased most significantly were those who lived in regions with low entomologic risk. The findings underline the importance of risk communications for emerging diseases and reinforce the need to understand the specific characteristics of the targeted populations before the implementation of communication campaigns to increase their efficacy.

Summary 1. Over the past two decades, Ixodes scapularis, the primary tick vector of the Lyme disease pathogen Borrelia burgdorferi in North America has expanded its range northward from the USA to colonize new regions in southern Canada. We have previously projected range increases for I. scapularis based on temperature suitability, but to what extent this is matched by actual tick range expansion is unknown. 2. Since 1990, I. scapularis ticks have been collected across Canada offering a unique opportunity to track the range expansion of an arthropod vector. We used these data to model time-to-establishment for tick populations across Canada to identify factors influencing the rate of spread. 3. Our results point to both long-distance dispersal of ticks by migratory birds and local dispersal by resident hosts as important potential mechanisms underlying patterns of tick range expansion. 4. Temperature (accumulated degree days > 0 � C) was the most important determinant of environmental suitability for tick population establishment, suggesting that climate warming may facilitate range expansion. 5. Model projections suggest that I. scapularis range will expand c. 46 km year )1 in the coming decade, with climate warming expected to increase the rate of spread. This expansion is likely to result in a substantial increase in human Lyme disease risk, with the proportion of the human population of eastern Canada inhabiting areas with established tick populations increasing from 18% in 2010 to over 80% by 2020. 6. This first empirical model of I. scapularis invasion supports theoretical range projections based on climate suitability and provides a unique data-driven estimate of the speed of northward range expansion for I. scapularis at the continental scale. 7. Synthesis and applications .B y trackingI. scapularis invasion in Canada over the past two decades, we show that I. scapularis is rapidly expanding its range and is likely to colonize the most densely populated areas of southern Canada in the coming decade. These projections suggest that prompt action is necessary to prepare the Canadian public for a likely epidemic of Lyme disease, with emphasis on focusing surveillance activities to confirm the locations of emerging Lyme disease risk.

Lyme disease (LD) is emerging in Canada because of the northward expansion of the geographic range of the tick vector Ixodes scapularis (Say). Early detection of emerging areas of LD risk is critical to public health responses, but the methods to do so on a local scale are lacking. Passive tick surveillance has operated in Canada since 1990 but this method lacks specificity for identifying areas where tick populations are established because of dispersion of ticks from established LD risk areas by migratory birds. Using data from 70 field sites in Quebec visited previously, we developed a logistic regression model for estimating the risk of I. scapularis population establishment based on the number of ticks submitted in passive surveillance and a model-derived environmental suitability index. Sensitivity-specificity plots were used to select an optimal threshold value of the linear predictor from the model as the signal for tick population establishment. This value was used to produce an "Alert Map" identifying areas where the passive surveillance data suggested ticks were establishing in Quebec. Alert Map predictions were validated by field surveillance at 76 sites: the prevalence of established I. scapularis populations was significantly greater in areas predicted as high-risk by the Alert map (29 out of 48) than in areas predicted as moderate-risk (4 out of 30) (P < 0.001). This study suggests that Alert Maps created using this approach can provide a usefully rapid and accurate tool for early identification of emerging areas of LD risk at a geographic scale appropriate for local disease control and prevention activities.

Climate change is driving emergence and establishment of Ixodes scapularis, the main vector of Lyme disease in Québec, Canada. As for the black-legged tick, I. scapularis Say, global warming may also favor northward expansion of other species of medically important ticks. The aims of this study were to determine (1) current diversity and abundance of ticks of public health significance other than I. scapularis, (2) sex and age of the human population bitten by these ticks (3), and the seasonal and geographic pattern of their occurrence. From 2007 to 2015, twelve tick species other than I. scapularis were submitted in the Québec passive tick surveillance program. Of these 9243 ticks, 91.2% were Ixodes cookei, 4.1% were Dermacentor variabilis, 4.0% were Rhipicephalus sanguineus and 0.7% were Amblyomma americanum. The combined annual proportion of submitted I. cookei, D. variabilis, R. sanguineus and A. americanum ticks in passive surveillance rose from 6.1% in 2007 to 16.0% in 2015 and an annual growing trend was observed for each tick species. The number of municipalities where I. cookei ticks were acquired rose from 104 to 197 during the same period. Of the 862 people bitten by these ticks, 43.3% were I. cookei ticks removed from children aged < 10 years. These findings demonstrate the need for surveillance of all the tick species of medical importance in Québec, particularly because climate may increase their abundance and geographic ranges, increasing the risk to the public of the diseases they transmit.

The optimal time to acquire remote sensing imagery to relate to grain yield has not been thoroughly investigated for the Canadian prairies. Remotely sensed data collected when there is the best relationship with yield should provide useful information on the in-field spatial variability of biophysical factors affecting crop productivity relevant to site-specific management. The correlations of normalized difference vegetation index (NDVI) with grain yield for three dates in 2000 at Indian Head and Swift Current, SK, for field pea, canola, and spring wheat were compared. No single date consistently had the highest NDVI-yield correlation for all crops. The period between Jul. 10 to 30 was optimal to obtain NDVI to relate to grain yield for springseeded crops that typically mature in August. Significant NDVI-yield correlations for this period were confirmed in three additional site-years. In a further site-year, however, NDVI-yield correlation was significant for wheat and pea, but not for canola. Occasional problems relating the NDVI to canola yield were attributed to characteristics of the canola canopy, namely, the highly reflective flowers and the dropping of leaves after flowering. In terms of both magnitude and temporal stability of the NDVI-yield correlation, we ranked the crops as: spring wheat, then pea, and then canola. Key words: Remote sensing; grain yield, field pea, canola, wheat, normalized difference vegetation index