| scholarly article | Q13442814 |
| P356 | DOI | 10.1890/09-1409.1 |
| P698 | PubMed publication ID | 21830694 |
| P50 | author | Shannon LaDeau | Q51706473 |
| Richard S. Ostfeld | Q56813897 | ||
| N. Thompson Hobbs | Q87347771 | ||
| Gregory E Glass | Q101542163 | ||
| Andrew M. Latimer | Q37605251 | ||
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| Local and Global Effects of Climate on Dengue Transmission in Puerto Rico | Q27487874 | ||
| REMOTE SENSING, ECOLOGICAL VARIABLES, AND WILD BIRD MIGRATION RELATED TO OUTBREAKS OF HIGHLY PATHOGENIC H5N1 AVIAN INFLUENZA | Q27489428 | ||
| Origin of the West Nile virus responsible for an outbreak of encephalitis in the northeastern United States | Q27860919 | ||
| Experimental infection of North American birds with the New York 1999 strain of West Nile virus | Q29616255 | ||
| Emerging infectious diseases of wildlife--threats to biodiversity and human health | Q29617659 | ||
| Effect of temperature on the vector efficiency of Aedes aegypti for dengue 2 virus | Q29618179 | ||
| Superspreading and the effect of individual variation on disease emergence | Q29618989 | ||
| Predicting the global spread of H5N1 avian influenza | Q30358667 | ||
| Epidemic modelling: aspects where stochasticity matters. | Q30381741 | ||
| Disease ecology and the global emergence of zoonotic pathogens | Q30397221 | ||
| Using remotely sensed data to identify areas at risk for hantavirus pulmonary syndrome | Q30596759 | ||
| Effects of global climate on infectious disease: the cholera model | Q30736492 | ||
| Simulating the SARS outbreak in Beijing with limited data | Q30912279 | ||
| Epidemiology of West Nile virus in Connecticut: a five-year analysis of mosquito data 1999-2003. | Q30981765 | ||
| A dynamic population model to investigate effects of climate on geographic range and seasonality of the tick Ixodes scapularis. | Q30985309 | ||
| Characterizing population dynamics of Aedes sollicitans (Diptera: Culicidae) using meteorological data | Q31036892 | ||
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| Predictability and epidemic pathways in global outbreaks of infectious diseases: the SARS case study | Q33306756 | ||
| Epidemiology of West Nile infection in Volgograd, Russia, in relation to climate change and mosquito (Diptera: Culicidae) bionomics | Q33386895 | ||
| Order-free co-regionalized areal data models with application to multiple-disease mapping | Q33730210 | ||
| Transmission intensity and impact of control policies on the foot and mouth epidemic in Great Britain | Q33955038 | ||
| Different epidemic curves for severe acute respiratory syndrome reveal similar impacts of control measures | Q33981191 | ||
| Co-circulating microorganisms in questing Ixodes scapularis nymphs in Maryland | Q34152681 | ||
| Epidemiological determinants of spread of causal agent of severe acute respiratory syndrome in Hong Kong | Q34202150 | ||
| Early-Season Avian Deaths from West Nile Virus as Warnings of Human Infection | Q34215958 | ||
| Intensive early season adulticide applications decrease arbovirus transmission throughout the Coachella Valley, Riverside County, California | Q34298842 | ||
| West Nile virus emergence and large-scale declines of North American bird populations | Q34629040 | ||
| Towards a comprehensive simulation model of malaria epidemiology and control. | Q34806993 | ||
| Epidemiology, transmission dynamics and control of SARS: the 2002-2003 epidemic | Q35214004 | ||
| West Nile virus risk assessment and the bridge vector paradigm | Q35817345 | ||
| Enhancing West Nile virus surveillance, United States | Q35880447 | ||
| Wildlife trade and global disease emergence | Q36022010 | ||
| New approaches to quantifying the spread of infection | Q36182958 | ||
| Alternatives to statistical hypothesis testing in ecology: a guide to self teaching | Q36480853 | ||
| Transmission assumptions generate conflicting predictions in host-vector disease models: a case study in West Nile virus | Q36481191 | ||
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| Correlation between tick density and pathogen endemicity, New Hampshire | Q37164680 | ||
| Accounting for uncertainty in ecological analysis: the strengths and limitations of hierarchical statistical modeling. | Q37474682 | ||
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| The dynamics of measles in sub-Saharan Africa | Q39003152 | ||
| Impact of climate variation on mosquito abundance in California | Q39103459 | ||
| Space, persistence and dynamics of measles epidemics | Q39419097 | ||
| Network theory and SARS: predicting outbreak diversity | Q39698246 | ||
| Disease mapping in veterinary epidemiology: a Bayesian geostatistical approach | Q39764407 | ||
| Vaccination and herd immunity to infectious diseases | Q39835584 | ||
| Remotely-sensed vegetation indices identify mosquito clusters of West Nile virus vectors in an urban landscape in the northeastern United States | Q39845037 | ||
| Urban land use predicts West Nile virus exposure in songbirds | Q39856178 | ||
| Estimating population size and hidden demographic parameters with state-space modeling | Q39988917 | ||
| Tree growth inference and prediction from diameter censuses and ring widths | Q40158334 | ||
| Dynamically modeling SARS and other newly emerging respiratory illnesses: past, present, and future | Q40381636 | ||
| Estimates of worst case baseline West Nile virus disease effects in a suburban New York county. | Q40395650 | ||
| Higher temperature and urbanization affect the spatial patterns of dengue fever transmission in subtropical Taiwan | Q40399194 | ||
| Threshold conditions for west nile virus outbreaks | Q40401592 | ||
| Naturally induced humoral immunity to West Nile virus infection in raptors | Q40412876 | ||
| West Nile virus-infected dead corvids increase the risk of infection in Culex mosquitoes (Diptera: Culicidae) in domestic landscapes | Q40433306 | ||
| Modelling the control strategies against dengue in Singapore. | Q40448561 | ||
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| Effects of temperature on the transmission of west nile virus by Culex tarsalis (Diptera: Culicidae). | Q40481183 | ||
| Forecasting clinical disease in pigs: comparing a naive and a Bayesian approach | Q40487620 | ||
| Avian hosts for West Nile virus in St. Tammany Parish, Louisiana, 2002. | Q40491158 | ||
| An update on the potential of north American mosquitoes (Diptera: Culicidae) to transmit West Nile Virus | Q40515612 | ||
| Bayesian analysis of severe acute respiratory syndrome: the 2003 Hong Kong epidemic | Q40798840 | ||
| Rainfall, abundance of Aedes aegypti and dengue infection in Selangor, Malaysia | Q40813617 | ||
| The biological and social phenomenon of Lyme disease | Q40911998 | ||
| Global climate and infectious disease: the cholera paradigm | Q41254076 | ||
| Chain reactions linking acorns to gypsy moth outbreaks and Lyme disease risk | Q42061128 | ||
| Temperature-dependent development and survival rates of Culex quinquefasciatus and Aedes aegypti (Diptera: Culicidae). | Q42988324 | ||
| Failure to predict abundance of saltmarsh mosquitoes Aedes sollicitans and A. taeniorhynchus (Diptera: Culicidae) by using variables of tide and weather | Q42988325 | ||
| Previous infection with West Nile or St. Louis encephalitis viruses provides cross protection during reinfection in house finches | Q43031336 | ||
| Dynamic life table model for Aedes aegypti (Diptera: Culicidae): analysis of the literature and model development | Q43048750 | ||
| Effects of acorn production and mouse abundance on abundance and Borrelia burgdorferi infection prevalence of nymphal Ixodes scapularis ticks | Q43216554 | ||
| Cross correlation maps: a tool for visualizing and modeling time lagged associations | Q43219227 | ||
| Stage-structured infection transmission and a spatial epidemic: a model for Lyme disease | Q44721326 | ||
| On the application of multilevel modeling in environmental and ecological studies | Q45895098 | ||
| P433 | issue | 5 | |
| P921 | main subject | infectious disease | Q18123741 |
| emerging pathogen | Q108429945 | ||
| P1104 | number of pages | 18 | |
| P304 | page(s) | 1443-1460 | |
| P577 | publication date | 2011-07-01 | |
| P1433 | published in | Ecological Applications | Q3047086 |
| P1476 | title | Data-model fusion to better understand emerging pathogens and improve infectious disease forecasting | |
| P478 | volume | 21 |
| Q30670492 | Bayesian calibration of simulation models for supporting management of the elimination of the macroparasitic disease, Lymphatic Filariasis |
| Q26821909 | Climate change and Ixodes tick-borne diseases of humans |
| Q46856033 | Climate change and species interactions: ways forward |
| Q28087411 | Climate, environmental and socio-economic change: weighing up the balance in vector-borne disease transmission |
| Q36463745 | Coinfection by Ixodes Tick-Borne Pathogens: Ecological, Epidemiological, and Clinical Consequences |
| Q41670370 | Continental-scale, data-driven predictive assessment of eliminating the vector-borne disease, lymphatic filariasis, in sub-Saharan Africa by 2020. |
| Q90118287 | Data-driven modelling and spatial complexity supports heterogeneity-based integrative management for eliminating Simulium neavei-transmitted river blindness |
| Q59340275 | Demographic stochasticity drives epidemiological patterns in wildlife with implications for diseases and population management |
| Q64109488 | Forecasting Zoonotic Infectious Disease Response to Climate Change: Mosquito Vectors and a Changing Environment |
| Q30696947 | Improving the modeling of disease data from the government surveillance system: a case study on malaria in the Brazilian Amazon |
| Q91015735 | Individual and temporal variation in pathogen load predicts long-term impacts of an emerging infectious disease |
| Q35123441 | Integrated assessment of biological invasions |
| Q56934133 | Observing changing ecological diversity in the Anthropocene |
| Q31071755 | Projection of Climate Change Influences on U.S. West Nile Virus Vectors |
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| Q28534282 | Sequential modelling of the effects of mass drug treatments on anopheline-mediated lymphatic filariasis infection in Papua New Guinea |
| Q34282227 | Surveillance of dengue fever virus: a review of epidemiological models and early warning systems |
| Q58318410 | The role of data assimilation in predictive ecology |
| Q56773512 | Tick-, mosquito-, and rodent-borne parasite sampling designs for the National Ecological Observatory Network |
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