Vector borne disease and Dengue
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Vector borne disease and Dengue Presentation Transcript

  • 1. Vector Borne Disease and the Environment: A Transdisciplinary Cumulative Risk Model Associated with Dengue Diana Hamer, MSc, PhD(c)
  • 2. Different Trends in Disease… WHO, 2011
  • 3. The Range of Infectious Diseases  Bacteria   HOST Influenza, chicken pox, HIV, poliomyelitis, ebola Parasites   The Disease Triangle Viruses   Cholera, leprosy, tetanus Filariasis, giardiasis, ameobasis DISEASE Fungi  Fungal meningitis, mycosis PATHOGEN ENVIRONMENT
  • 4. What are vector-borne diseases?     Definite host Intermediate host Reservoir host HOST Vector: an agent that carries and transmits and infectious pathogen into another organism  Mosquitos and flies, other arthropods, bats, copepods, cats, fleas, ticks, rats, dogs VECTOR DISEASE PATHOGEN ENVIRONMENT
  • 5.  Factors affecting the Emergence / Resurgence of Vector Borne Diseases Genetic and Biological    Physical Environmental    Urbanization Climate change Ecological   Human susceptibility to disease Pathogen adaptation Encroachment Social / Political / Economical    Poverty War Lack of political will / money
  • 6. Strategies to curve disease incidence Vector Control Options • Biological Control • • • • Lack of surveillance / monitoring  Sterilization techniques  Environmental manipulation / reduction Chemical Control • • Immature and mature stages Predators / pathogens Physical Control • •  Genetic Control • • Challenges Oils, insecticides Personal Protection Education Population dynamics   At all stages of intervention Migration, poverty, urbanization Climate change  Increase in habitats, vector expansion
  • 7. Reemergence of Vector Borne Diseases  Global Problems with local challenges  Dengue Fever in Florida   Reemerged in 2009 (Monroe County) Currently Martin & St. Lucie County
  • 8. Significance  Dengue Worldwide    First recognized in 1950 Currently 2.5 million at risk 50 - 100 million dengue fever / year DengueMap-CDC-HealthMap Collaboration
  • 9. Dengue: The Spectrum of Disease • No clinical signs • • • • Fever Headache Myalgia / athralgia Leukopenia • Rash • Petechiae • Thrombocytopenia • Hematemesis • Plasma leakage • Hypovolemia
  • 10. Dengue Virus (DENV)    Genus flavivirus +, single stranded RNA 4 types (DENV1-4)    Homotypic immunity Heterotypic immunity Antibody-dependent enhancement Cann, 2007 Mayo Foundation for Medical Research, 2012
  • 11. The Vector  Aedes aegypti    Urban Tropical / Subtropical Vector Control Ae. aegypti WHO, 2012
  • 12. Dengue in the Americas   hy po hy pe re n en de m ic de m ic  Incidence Severity Understudied From San Martin, et al., 2010
  • 13. Suriname    Population Climate Ae. aegypti endemic   Hyperendemic dengue Bureau of Public Health (BOG)
  • 14. Dengue in Suriname  Frequency and severity (BOG)
  • 15. A Neglected Tropical Disease • Shifting the focus to prevent the emergence and resurgence of infectious diseases • Where do you start? • • Lack of political will • • • Not a priority Vertical command structure Complicated diseases • • • Diseases of Poverty No good vaccine Uneducated populations Globalization • • • Urbanization Vector importation New emerging diseases
  • 16. Transmission of Disease Influencing factors Competitors Age Human Host Ethnicity Gender Immune status Density Breeding Sites Dengue Virus Serotype Virulence Vector Climate Environment Sanitation Urbanization
  • 17. Hypotheses    Hypothesis 1: There is a statistical association between demographic and clinical factors and the progression of dengue into the severe forms for the disease in Suriname Hypothesis 2: Spatio-temporal trends and relationships of factors influencing dengue incidence and severity will identify disease hotspots in Suriname Hypothesis 3: Prediction models and dengue disease cluster analysis can identify effective prevention methods and risk reduction strategies for dengue in Suriname
  • 18. Study Population
  • 19. Data Sources  Electronic databases Source Type of Information Aims Saint Vincent Hospital Paramaribo (SVZ) n ≈ 2092 -Demographic -Clinical Aim 1.1 Aim 1.2 Bureau of Public Health (BOG) n ≈ 5298 -Demographic -Clinical Aim 2.1 Aim 2.2 Academic Hospital Paramaribo Laboratory (AZPL) -Demographic -Clinical Aim 1.1 Aim 1.2 Meteorological Service Suriname (MDS) -Meteorological Aim 2.1 General Bureau of Statistics (ABS) -Census Aim 2.1 Aim 2.2
  • 20. Data Sources Type of Information  Case data   Inclusion / Exclusion Criteria  Demographic Clinical Context Inclusion criteria    Additional Data   Meteorological Census  Probable (hospital or clinic) cases of dengue fever Admitted into a hospital / clinic - 2001 to 2012 Exclusion criteria   No available date of birth No source or address
  • 21. Case Classification Definition Criteria Probable Clinical -Acute febrile illness -Two or more of the following: headache, retro-orbital pain, myalgia, arthralgia, rash, hemorrhagic manifestations, leucopenia Laboratory -Compatible serology (reciprocal hemagglutination-inhibition antibody titer > 1280, comparable IgG EAI titer or positive IgM antibody test in serum specimen Confirmed -Clinically compatibility and -DENV isolation in cell culture -RT-PCR detection of nucleic acid in serum Peeling et al. 2010
  • 22. Methodology: Hypothesis 1      Aim 1.1: Characterize the incidence, prevalence and severity of dengue – with an emphasis of pediatric dengue – in Suriname from 2001 to 2012 Frequency distributions, incidence and mortality of DF & DHF Aim 1.2: Examine the demographic and clinical factors that influence the development of severe dengue Univariate analysis to identify difference between groups Multivariate analysis to test for associations Significance • Background • Transmission of Disease • Hypotheses • Study Population • Methodology • Data Analysis
  • 23. Hypothesis 2  Aim 2.1: Integrate clinical and demographic information of all dengue cases reported in Suriname since 2001 into a GIS platform    Generate a Geodatabase Identify historic spatial and temporal trends Aim 2.2: Identify spatial and temporal historic clusters of DF and DHF from 2001 to 2012   Global clusters / local clusters Poisson-model to assess spatial random distribution Significance • Background • Transmission of Disease • Hypotheses • Study Population • Methodology • Data Analysis
  • 24. Hypothesis 3  Aim 3.1: Characterize dengue-related entomological and environmental data in previously identified high transmission risk areas    Use the maps to identify areas of high dengue transmission And conduct entomological and environmental surveys to further assess the situation Aim 3.2: Propose effective, low-cost dengue intervention activities based on local information to reduce the risk of dengue transmission in Suriname Significance • Background • Transmission of Disease • Hypotheses • Study Population • Methodology • Data Analysis
  • 25. Data Analysis
  • 26. Hypothesis 1   Aim 1.1: Characterize the incidence, prevalence and severity of dengue – with an emphasis of pediatric dengue – in Suriname from 2001 to 2012  Prevalence Data cleaning / transforming   Incidence   In each district and resort District and resort with available census data Stratified by gender, age, ethnicity, type Significance • Background • Transmission of Disease • Hypotheses • Study Population • Methodology • Data Analysis
  • 27. Hypothesis 1  Aim 1.2: Examine the demographic and clinical factors that influence the development of severe dengue ADE Prior Infection Increased risk for DHF Age Human Host Dengue Virus Virulence Ethnicity Gender Serotype Significance • Background • Transmission of Disease • Hypotheses • Study Population • Methodology • Data Analysis
  • 28. Hypothesis 1 (Aim 1.2)  Univariate analysis  Predetermined sample    Presence of absence of severe disease (DHF) P1 : did not develop DHF; P2 : did develop DHF Chi-square test for homogeneity  Ho: Pi = Pj  H a: Pi ≠ Pj  Significance: p < 0.05 Significance • Background • Transmission of Disease • Hypotheses • Study Population • Methodology • Data Analysis
  • 29. Hypothesis 1 (Aim 1.2)  Multivariate analysis   Test for association of indicators on the development of DHF Logistic regression model    Test for indicators and interaction variables (α = 0.5)    Binary outcome: [Y = 0]: no DHF; [Y = 1]: DHF Stepwise forward selection of categorical indicator variables Maximum Likelihood method / likelihood ratio Odds ratio (95% confidence interval) Chi Square goodness of fit (α = 0.5)  Significance: p < 0.05 Significance • Background • Transmission of Disease • Hypotheses • Study Population • Methodology • Data Analysis
  • 30. Hypothesis 2  Aim 2.1: Integrate clinical and demographic information of all dengue cases reported in Suriname since 2001 into a GIS platform  Geodatabase includes   Suriname basemap (administrative level) Layers    Cases of DF and DHF Hospitals and clinics in Suriname Attribute table (for data exploration)    Demographic and clinical information of cases Weekly meteorological data- relative humidity, precipitation, average temp Additional district / resort characteristics- SES, access to piped water, etc. Significance • Background • Transmission of Disease • Hypotheses • Study Population • Methodology • Data Analysis
  • 31. Hypothesis 2  Aim 2.2: Identify spatial and temporal historic clusters of DF and DHF from 2001 to 2012  Identify IF clusters exist Global clustering – obtain Moran’s I (-1 to +1) Yes No Identify specific clustering (SatScan) Poisson regression analysis (log(pop)) is an offset for the population Local Moran’s I Overdispersion Ho: No spatial association between the ith region and its neighbors Ha: There is spatial association between the ith region and its neighbors Ho: The data follow a Poisson distribution Ha: The data do not follow a Poisson distribution Create cluster map Map Predicted values Significance • Background • Transmission of Disease • Hypotheses • Study Population • Methodology • Data Analysis
  • 32. Hypothesis 3  Aim 3.1: Characterize dengue-related entomological and environmental data in previously identified high transmission risk areas  Epidemiological Maps    Sample size Unit classification Replicates  Wet v dry season  Environmental Surveys  Unit Classification     Residential v non-residential Rural v urban Local characteristics Container classification     Non traditional v traditional Non disposable v disposable Size & location Water source Significance • Background • Transmission of Disease • Hypotheses • Study Population • Methodology • Data Analysis
  • 33. Hypothesis 3 (Aim 3.1)  Surveys   Immature Ae. aegypti Larval and Pupae indices Container Index # of containers w/ larvae or pupa # of containers examined x 100 House Index # of houses w/ larvae or pupae # of houses inspected x100 Breteau Index Pupae / person survey # of containers w/ larvae or pupae 100 houses inspected # of pupae in a community # of people in a community Significance • Background • Transmission of Disease • Hypotheses • Study Population • Methodology • Data Analysis
  • 34. Hypothesis 3  Aim 3.2: Propose effective, low-cost dengue intervention activities based on local evidence-based information to reduce the risk of dengue transmission in Suriname    Historical cases of dengue help identify spatial and temporal patterns of transmission The importance of environmental and entomological data collection in elucidating populations at higher risk of transmission Epidemiological, entomological and environmental surveillance is necessary to move from an ad hoc basis to a more prevention oriented approach Significance • Background • Transmission of Disease • Hypotheses • Study Population • Methodology • Data Analysis
  • 35. Increased risk for DHF Prior Infection Age Competitors Human Host Adult Larva Pupae Race Gender Temperature Density Rainfall Vector Dengue Virus Serotype Breeding Sites Virulence Climate Humidity Environment Sanitation Urbanization Pop. Density
  • 36. Acknowledgements    Dr. Lichtveld Dr. A. Jessurun at the Saint Vincent Hospital Dr. Hiwat and Dr. Jubithana at the Bureau of Public Health
  • 37. Questions & Comments