Disasters and Public Health: Learning from Recent History

1. Disasters and Public Health:Learning from Recent History Richard Keller, PhD Dept. of Medical History and Bioethics University of Wisconsin-Madison rckeller@wisc.edu

2. Public Health and the History of Disasters • What can we learn about public health by studying recent natural and environmental disasters? • What do disasters teach us about risk and vulnerability? • What about this research is “translatable” to public health practice?

3. Poll Question In your opinion, are there any practical things that can be done to enhance a community’s resilience prior to the experience of a disaster? A. Yes B. No

4. Examples • Bhopal: 3 December 1984 • Chernobyl: 26 April 1986 • Chicago heat wave: July 1995 • European heat wave: August 2003 • Hurricane Katrina: August–September 2005 • Each with important lessons on risk, vulnerability, and coupling of human-natural systems

5. Objectives This presentation will help participants: • Develop the ability to recognize social dimensions of risk • Understand how environmental and technological hazards are often linked to poor health outcomes • Define policy initiatives that could promote greater resilience among vulnerable populations

6. Vulnerability and Resentment Bhopal and Katrina

7. Disaster in a Social Frame Much study of disaster is conducted in fields such as physical geography, geology, seismology, volcanology, meteorology, toxicology. Great Sumatra/ Andaman Earthquake

8. But… Recent episodes demonstrate importance of understanding social and cultural dimensions of disaster. Hurricane Katrina

9. Bhopal • Internationalization of risk and responsibility • Critical factors • Uncontrolled urbanization • Outsourcing of risk • Engineered unpreparedness • Outcomes • Unclear m&m • Nonexistent management • Aimless litigation and resentment

10. Hurricane Katrina • Revelation of unequal burden of vulnerability • Poor management • Public health consequences ongoing • Q: Who is a disaster victim?

11. Poll Question In your opinion, which of the following are victims of a disaster? A. Someone stranded on a rooftop by a flood B. Someone who drowns in a flood C. Someone displaced by a flood, who commits suicide years later D. All of the above

12. Cities and Vulnerability

13. Mapping Resilience and Vulnerability • Neighborhood studies • Corollary to epidemiological case-control studies • How does one neighborhood experience relatively little damage or bounce back quickly, while a nearby neighborhood experiences utter devastation? • Examples • Fire in Southern California • Heat in Chicago • Heat in Paris

14. Fire in Greater Los Angeles (Davis 1999) • Malibu • Regular wildfires; insurance and federal/state programs cover damage and ensure rapid response • Downtown LA • Regular building fires; poorly funded fire stations, disregard for building codes, absence of funding mean greater aggregate damage and failure of state to respond • Movie stars vs. immigrants, ethnic minorities • Socioeconomic, cultural, and political inequality

15. Heat Wave in Chicago, July 1995 (Klinenberg 2002) • ~700 excess deaths, mostly African-American, very few whites and Latinos • City, public health officials offer dubious cultural explanation for divergent mortality • Latinos more habituated to heat • Latinos have closer family ties, therefore less isolated (questionable)

16. Neighborhood Study • Qualitative analysis of two neighborhoods • North Lawndale (African-American) • Little Village (Latino) • Abutting communities • Identical microclimates • Similar socioeconomic conditions • Similar age of populations

17. North Lawndale • Degraded infrastructure and decaying housing stock: Economic decline in aftermath of “white flight” and industrial relocation • Aging and unfit population: High rates of obesity, hypertension, heart disease • Drug trafficking, gang warfare, high crime rate creates climate of fear • Result: Difficult for aging populations to leave home, poor social integration of most vulnerable populations • Isolation in brick apartments/houses, with windows shut out of fear

18. Little Village • Similar population size, income level, age, lower, significant crime rate and gang activity • Less white flight • Most important: Significant economic/commercial activity and street life • Result: Vulnerable populations leave apartments, even at night, for air-conditioned/cooler locations, lowering risk factors • Not ethnic protection factor: Lower mortality even among whites in Little Village • Not socioeconomic: More a function of different behavior than one of different incomes

19. Poll Question In your opinion, which of the following goals of public policy is most important to your local community’s resilience in the face of a disaster? A. Robust local economic/commercial activity B. Equity of social and physical infrastructures C. Community cohesion and social integration D. Clear plans for disaster response

20. Heat Wave in Paris: Beaugrenelle

21. Heat Wave in Paris: Auteuil

22. Deaths from Heat Wave Deaths by Age and Sex, 1–20 August 2003 16,000 14,000 12,000 10,000 Women 8,000 Men Total 6,000 4,000 2,000 0 44 and 45–74 75 and Total under over Source: INSERM

23. Ile-de-France • 32.9% of excess mortality concentrated in one region (4866 unanticipated deaths) • Paris: 7.2% (1066) • But only roughly 3.33% of French population • Other hard-hit areas: • Hauts-de-Seine (5.4%) • Val-de-Marne (5.1%) • Seine-Saint-Denis (3.9%)

24. Why Did They Die? • Poor thermoregulation • Lower perception of thirst • Highest risk groups: those over 75 years of age and psychiatric/neurological patients

25. Risk Factors: Socioeconomic Status 4.0 3.5 Management, executive 3.0 Middle management 2.5 Employee 2.0 1.5 Artisan, skilled labor 1.0 Worker, other 0.5 0.0 Source: InVS

26. Risk Factors: SES and Its Markers Housing situation Odds ratio Other than top floor 1.12 Top floor 2.33 No elevator 1.39 Bath facilities Odds ratio Shower 1.00 Shower and bath 0.86 Bath 1.49 None 2.47 Source: InVS

27. Risk Factors: Behavior During Heat Wave Departure from home Odds ratio Regular, no reason specified 1.00 Seeking a cool place 0.54 Rare (weekly or less) 3.90 Grocery delivery 4.97 Shower/bath frequency Odds ratio More than daily 1.00 Daily 3.14 Every other day 12.09 Weekly 15.61 Never 20.76 Source: InVS Media exposure: TV/Radio 0.47

28. Risk Factors: Social Integration Degree of social interaction OR Living alone 0.59 Frequency of visitors OR Never or rarely 1.00 2–4 x weekly 2.81 Daily or more 3.60 No social activity 6.12

29. Poverty, Isolation, Accumulation of Risk Risk factor OR Rare departure 3.90 No social interaction 6.12 Top floor of building 2.33 No bath facilities 2.47 SES: Worker/other 3.64

30. Marginalization and Social Citizenship “You know, the elderly, they don’t have very good memories, often from one moment to another, so the preventive messages that we could air…well, they’d forget them the same day!” —Jean-François Mattéi 15 August 2003 Source: INA

31. A Science of Resilience: Critical Themes and Concepts • Integrating social scientific and humanistic knowledge in disaster risk reduction and assessments of vulnerability and resilience • Mapping resilience and vulnerability • Intersections of health, citizenship, and resilience • Violence and vulnerability: Research problems and possibilities • Goal: A societal resilience index?

32. Political/Social Dimensions of Resilience Problem: “Biological citizenship” and cultures of reparation • Claims to citizenship based on vulnerability • Chernobyl Chernobyl memorial, Vilnius. Photo: Alma Pater

33. Other Examples • Bhopal • Brazil’s AIDS program • What potential mechanisms can ensure other forms of security to avoid replication of such patterns, particularly in developing countries?

34. Opportunity? • Relative dearth of research on basic social factors promoting vulnerability or resilience • Ultimate vs. proximate causes • Importance of civic, economic, political, and practical equality as components of resilient societies, vs. prevalence of structural violence (economic, social, political marginalization; inhibited agency) as critical factor determining vulnerability

35. Goal: A Societal Resilience Index? • Building on models of vulnerability • Can we determine an index of resilience • To what uses can this index be put (insurance, resource allocation)? • Critical variables • Age, personal wealth, ethnicity, occupation, and infrastructure dependence • Density of the built environment, housing stock, and tenancy • Coupling of technological systems

36. We are now going to open the phone lines and ask people to verbally share one thing you might do differently in your practice in light of today’s discussion. Simply raise your hand by clicking on the “hand raise” icon. We will call on you.

37. Conclusions