1 / 23

Seasonality and Infectious Disease

Seasonality and Infectious Disease. Presented by Jessica Beckham 3/3/11. Altizer, Sonia, Andrew Dobson, Parviez Hosseini, Peter Hudson, Mercedes Pascual, and Pejman Rohani. "Seasonality and the Dynamics of Infectious Diseases." Ecology Letters 9.4 (2006): 467-84.

davis
Download Presentation

Seasonality and Infectious Disease

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Seasonality and Infectious Disease Presented by Jessica Beckham 3/3/11

  2. Altizer, Sonia, Andrew Dobson, Parviez Hosseini, Peter Hudson, Mercedes Pascual, and Pejman Rohani. "Seasonality and the Dynamics of Infectious Diseases."Ecology Letters 9.4 (2006): 467-84. Word cloud created at wordle.net

  3. Beier, John C. "Malaria Parasite Development In Mosquitoes." Annual Review of Entomology 43.1 (1998): 519-43. Word cloud created at wordle.net

  4. Infectious Diseases Exhibiting Seasonality • Malaria • Dengue • West Nile • Cholera • Measles • Influenza • Ebola • Rabies (in skunks) • Intestinal nematodes (in livestock) • Bot fly (in reindeer)

  5. “Vector-borne diseases, including those caused by viruses, protozoa and filarial nematodes, are among those parasites most likely to covary with environmental conditions (Altizier et al, 2006; Dobson&Carper 1992; Hay et al 2000). ”

  6. Experiments… Varied transmissibility, β (beta) Varied recovery,  (gamma) Varied birth rate,  (lambda) Varied death rate SEIR Revisited

  7. Ro • Basic reproductive number of a parasite • Number of cases that arise from one case • Ro > 1 … epidemic likely • Ro < 1 … epidemic unlikely • Spatial and temporal variation • Affected by parasite transmissibility, susceptible host availability, host susceptibility

  8. Measles • Data: measles notifications in Glasgow 1901-1917 • Soper (1929) • Deterministic models of measles predicted damped oscillations • BUT, Glasgow data showed large sustained oscillations • “perturbing influences” lacking in basic model • Peak in October – start of school • Other studies corroborate – increase in childhood disease when school opens, decrease during vacation

  9. Cholera • Data: 1893-1940 records of deaths in India • Seasonal and long-term fluctuations • Moisture, temperature • Models needed: • Primary transmission (reservoir  human) • Secondary transmission (human  human)

  10. Modeling Seasonal Dynamics • Big Question: How do seasonal dynamics alter the dynamics of infectious disease? • Transmission oscillates with time • Seasonal forcing functions • How to deal with multiple seasonal processes relative to one another? • Noise?

  11. Future… • HOW does seasonality affect processes? • Incorporate seasonality into mathematical models • How do processes interact? • Better stats, more data • “Be aware of evolution”

  12. “Bottlenecks occur at every stage of the [malaria parasite] cycle in the mosquito.” -Beier

  13. Sporogonic Development of Plasmodium parasites • Occurs in mosquito • Three main phases where bottlenecks occur: • Gametocyte to ookinete transition • Fertilization, differentiation • Ookinete to oocyst transition • Midgut traversing, abortion of early-stage oocysts • Oocyst to sporozoites in salivary glands • Oocyst production of sp, invasion/survival in salivary gl

  14. Temperature and Sporogony • Plasmodium development varies with temp. • range of temperatures: ~20-30 Celsius • 9-21 days

  15. Seasonality Implemented…

  16. Seasonality Implemented, cont. x axis = temp (days); Y axis = time to complete cycle (days)

  17. In 1991, the Institute of Medicine published a report onmalaria. Each component chapter contained a section on “where we want to be in the year 2010,” with the chapter on “Vector Biology, Ecology, and Control” stressing the following: Vector biology will play a major role in the battle against malaria. Improved vector surveillance networks will allow most countries, particularly those in Africa, to mount effective control efforts and to predict outbreaks of disease. Researchers will be able to conduct epidemiologic surveys and track drug resistance simply by analyzing mosquito populations. Simple techniques will be used in the field to identify morphologically indistinguishable mosquitoes that have different capabilities to transmit malaria parasites, leading to more effective application of vector control measures. The entomological risk factors for severe disease and death will be identified, and interventions will be implemented. The development of environmentally safe antimosquito compounds will complement traditional residual insecticide spraying, and genetically engineered microbial agents will be used to kill mosquito larvae. An antimosquito vaccine will add to the growing arsenal of malaria control weapons. Feasibility studies will be carried out to replace populations of malaria vectors with natural or genetically altered forms that cannot transmit human malaria.

More Related