Weber

The Anatomy of an Epidemic: A Rational Approach to Understanding, Preventing and Combating Infectious Diseases : 

The Anatomy of an Epidemic: A Rational Approach to Understanding, Preventing and Combating Infectious Diseases Stephen Weber, MD, MS Assistant Professor Section of Infectious Diseases Hospital Epidemiologist Director, Infection Control Program University of Chicago Hospitals

Overview: 

Overview Introduction Modeling and the Anatomy of Epidemics Preventing and Controlling Epidemics Epidemics and Luck

Slide4: 

Smallpox SARS Anthrax Monkeypox Mumps Antibiotic-resistant Acinetobacter Community-associated MRSA Supertoxigenic Clostridium difficile Avian influenza Bordatella pertussis Measles West Nile Virus Highly-resistant Pseudomonas aeruginosa

Defining an epidemic: 

Defining an epidemic An outbreak of a contagious disease that spreads rapidly and widely. An increased frequency of infection above the normal or usual level

Epidemic Surveillance: 

Epidemic Surveillance World Health Organization (WHO) Centers for Disease Control and Prevention Illinois Department of Public Health Chicago Department of Public Health UCH Infection Control Program Individual Clinicians

Modeling and the Anatomy of Epidemics: 

Modeling and the Anatomy of Epidemics

Modeling Measles: 

Modeling Measles Keeling, et al. Proc R Soc Lond. 2002

Modeling Malaria: 

Modeling Malaria McKenzie and Samba, et al. Am J Trop Med Hyg. 2004 dX/dt = A B Y (N - X) - r X dY/dt = A C X (M - Y) - m Y

Progression of an Epidemic: 

Progression of an Epidemic Basic reproductive number (R0) Expected number of secondary cases on the introduction of one infected individual in a susceptible population R0 > 1 Epidemic disease R0 = 1 Endemic disease R0 < 1 Disease dies out

Slide13: 

Generation # R0 1 2 3 …10 2 1 2 4 512 1 1 1 1 1 0.5 4 2 1 0

Basic Reproductive Numbers: 

Basic Reproductive Numbers SARS in general population: 0.49 SARS (hospital transmission): 2.6 Smallpox in a vulnerable population: 3.0-5.2 Measles (pre-vaccine): 10-15 Measles in Belgian schools (1996): 6.2-7.7 1918 pandemic influenza: 1.8-2.0 Influenza on a commercial airliner: 10.4 Liao, et al. Risk Anal. 2005; Chowell, et al. Emerg Inf Dis. 2004; Mossong, et al. Epidemiol Infect. 2005; Meltzer, et al. Emerg Inf Dis. 2001.

R0 = p x k x d: 

R0 = p x k x d p = transmissibility k = contacts d = duration of contagiousness

Transmissibility (p): 

Transmissibility (p) Quantity of pathogen released Mechanism of dissemination Inherent infectiousness of the pathogen R0 = p x k x d

Quantity of pathogen released: 

Quantity of pathogen released Varies with state of disease Early chickenpox Herpes simplex Cattarhal phase of viral infections Varies with activity Coughing vs. sneezing vs. talking R0 = p x k x d

Mechanism of dissemination: 

Mechanism of dissemination Respiratory Influenza, tuberculosis Contact Seasonal viruses Antibiotic-resistant bacteria Fecal-oral Salmonella, shigella, hepatitis A Blood and body fluid HIV, Hepatitis B and C R0 = p x k x d

Respiratory dissemination: 

Respiratory dissemination Droplet Droplet nuclei Pathogen Bacteria TB Size ≥ 5µ < 5µ Distance < 3 feet ? Persistence < 10 min. > 1 hr. Destination Upper airways Alveoli R0 = p x k x d

Inherent infectiousness: 

Inherent infectiousness R0 = p x k x d E. coli infecting bladder epithelium Biological differences between organisms Adhesions, proteinases Variation in host response Expressed as the minimal infectious dose

Contacts: 

Contacts Number of contacts May be facilitated by environmental factors Intensity of contacts R0 = p x k x d

Slide22: 

R0 = p x k x d

Duration of Contagiousness (d): 

Duration of Contagiousness (d) Assuming a constant frequency of contacts and an unchanging degree of transmissibility, the longer the period of time that a patient is contagious the more likely he/she is to transmit the pathogen. For some infections, the period of contagiousness may not always be associated with symptoms of illness. R0 = p x k x d

Duration of Contagiousness (d): 

Duration of Contagiousness (d) The Ebola paradox Rapid mortality reduces period of contagiousness R0 = p x k x d

Preventing and Controlling Epidemics: 

Preventing and Controlling Epidemics

Childbed fever: Vienna, 1847: 

Childbed fever: Vienna, 1847 Robert A. Thom (1966)

Cholera: London 1854: 

Cholera: London 1854

Slide28: 

R0 = p x k x d Interventions to prevent the spread of epidemics target transmissibility (p), contacts (k) or duration of contagiousness (d). Modeling and Infection Control

Limiting transmissibility (p): 

Limiting transmissibility (p) Reduce the quantity of pathogen released Symptom control Anti-tussives Barrier precautions Masks for patients

Limiting transmissibility: 

Limiting transmissibility Act on the mechanism of dissemination Environmental controls Reduce inherent infectiousness Difficult to reduce, but possible to increase Overall, 63% of VRE (+) patient rooms are contaminated Sheets: 40% Bedside Tables: 20% Bed rails: 26% Blood pressure cuffs: 14%

Preventing Contact: 

Preventing Contact

Quarantine and Isolation: 

Quarantine and Isolation “une quarantaine de jours (a period of forty days)” S M T W R F S Exposed Symptoms Begin Contagious Quarantine Isolation

Social Controls: 

Social Controls Restriction on public events and gatherings Travel limitations Building quarantines Import/Export controls

Reducing duration of contagiousness: 

Reducing duration of contagiousness Antimicrobial therapy Influenza control Anti-HIV therapy Enhanced case recognition Syndromic surveillance Limit contacts

Ebola revisited: 

Ebola revisited 0 Death 1 2 Days of illness Ebola: Natural History 3

Ebola revisited: 

Ebola revisited 0 Death 1 2 Days of illness Ebola: Current Practice 3

Ebola revisited: 

Ebola revisited 0 Death 1 2 Days of illness Ebola: USA 3

Epidemics and Luck: 

Epidemics and Luck

Epidemic Misfortune: 

Epidemic Misfortune Epidemics do not conform to the predictions of deterministic models. Stochastic phenomena prevail. Monkeypox: Co-transport of Ghanan giant rat with prairie dogs West Nile Virus: Survival of carrier mosquito through transatlantic flight SARS: Co-mixing of viruses between humans, fowl and civets HIV: Single African ancestral event

Improving the Odds: 

Improving the Odds Understanding the role of chance in epidemics permits the deployment of manageable strategies to prevent spread. Improved performance of day to day practices may be more important than an elaborate emergency response system.

Conclusions: 

Conclusions Epidemics are driven by a relatively understandable interplay of pathogens, infected and susceptible hosts. Understanding the mathematical as well as the biological underpinnings of epidemics is critical to prevention and control. Sometimes, it really is better to be lucky than to be good.