Session 44 PD, Pestilence: Getting to Know the Fourth Horseman. Moderator: Jean Marc Fix, FSA, MAAA. Presenters: Martin Meltzer, Ph.D.

Transcription

1 Session 44 PD, Pestilence: Getting to Know the Fourth Horseman Moderator: Jean Marc Fix, FSA, MAAA Presenters: Jean Marc Fix, FSA, MAAA Martin Meltzer, Ph.D. SOA Antitrust Disclaimer SOA Presentation Disclaimer

2 Jean-Marc Fix, FSA, MAAA Vice President R&D Optimum Re Insurance Martin I. Meltzer, MS, Ph.D. Senior Health Economist & Distinguished Consultant Lead: Health Economics and Modeling Unit, CDC SOA ANNUAL MEETING 2016 Las Vegas Disclaimer: The findings and conclusions in this presentation are those of the authors and do not necessarily represent the views of the Centers for Disease Control and Prevention

3 2 The Four Horsemen of the Apocalypse by Albrecht Durer Death, Famine, War and Conquest/Pestilence

4 Current threats What makes a threat a threat? CDC threat evaluation Modeling threat impact Factors impacting results CDC Response- Ebola 3

5 Agents Reservoirs Vectors Disease of the week/pandemic fatigue 4

6 Agent needs to: Access Enter Replicate Damage Impact of environment Victim becomes Immune Carrier Dead 5

7 Single cell organism Bacteria (no nucleus) Protozoa (has a nucleus) Yeasts Virus (needs a host) Prion (just a molecule) Mold Parasites 6

8 Gets the infectious agent from a reservoir and pass it to a host (for us: human) Mosquitoes, ticks, flies and sandflies, fleas, snails Fellow humans Airborne/ contact Food supply Sex Ignorance 7

9 The primary target for the agent A safe place to grow and mutate 8

10 Pandemic fear in the 24/7 news cycle environment Increasing awareness or crying wolf too many times Public (including upper management) may have a hard time prioritizing Reality: we travel fast and so does disease Outbreak -> epidemic -> pandemic 9

11 The Justinian plague (around AD): bubonic plague; estimated to have decreased the earth s human population by 10-15% (25 million dead) Smallpox in Japan in killed 1/3 of population Black Death (bubonic plague): Europe: : 30 60% of Europe's total population; Globally, million dead In the flu pandemic 25% of the US population was infected Globally, +50 million dead - 3-6% world population 10

12 HIV treatment Hepatitis C treatment 11

13 Fast international travel Vector colonization due to global warming Impact of isolated population on new diseases As a source (polio) As a vulnerable population (Zika) Antibiotic resistance 12

14 CDC s Emerging Infectious Diseases journal If you don t want to sleep at night: 13

15 Surveillance Quick identification Triage/Quarantine Vaccine development Immunization campaigns Palliative care Health security Need world communication and cooperation 14

16 Availability Reservoir/Vector spread Agent spread Disability Lethality Impact on health care workers Sequelae Treatment resistance Societal support breakdown Impact on your company! 15

17 Advertising Warning! Check out Plague Inc app 16

18 Initial questions leadership ask: How many cases will there be at any point and in total (with frequent updates)? What would be the impact of interventions? When will the epidemic end? With an intervention Without an intervention 17

19 When will the next pandemic occur? How many deaths, hospitalizations, outpatients, and ill, self care? Economic and other impacts Implications for policy 18

20 1918 Spanish Flu Approx. 675,000 deaths (U.S.), young adults affected million worldwide 1957 Asian Flu 69,800 deaths (U.S.), mostly elderly & chronically ill 1968 Hong Kong Flu 33,800 deaths (U.S.), mostly elderly and chronically ill 2009: Swine flu: 12,470 deaths (range;8,870 18,300) (U.S.)* Interpandemic Flu (U.S.) 3,349 deaths (in ) to 48,614 (in )** *Source: Shrestha et al CID; 2011:52 (S1): S75-S82 **MMWR Morb Mortal Wkly Rep Aug 27;59(33):

21 20 Not a pandemic

22 21

23 Diagnostic tests slow and/ or inaccurate During pandemic: widespread use of RT-PCR Still takes time Rapid bedside diagnostics - Not accurate Patients often come in after peak of viral load Doctors can often successfully treat empirically No need for lab confirmed basis flu very similar symptoms to other respiratory diseases Similar treatments Many patients stay home and self treat (approx. 50%) 22

24 Source: 23

25 Total Rate, per 100 Median 90% Range Median Total deaths ~12,470 8,870-18, yrs ~1, , yrs ~9,570 6,800-14, yrs ~1,620 1,160-2, Total hospitalizations ~274, , , yrs ~87,000 62,000-28, yrs ~160, , , yrs ~27,000 19,000-40, Total Cases ~61 million million yrs ~20 million million yrs ~35 million million yrs ~6 million 4-9 million 15.2 Source: Shrestha et al CID; 2011:52 (S1): S75-S82 24

26 Source: 25

27 Age (years) Numbers per 100,000 (ranges) Deaths Hospitalizations Median Average Median Average ph1n to 1999 ph1n to ( ) ( ) ( ) ( ) 18 to ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) All ( ) ( ) ( ) ( ) Source: Shrestha et al CID; 2011:52 (S1): S75-S82 26

28 Modeling threat Impact Success stories: Simple models and influenza pandemic planning 27

29 FluAid: Calculate deaths, hospitalizations, outpatients FluSurge: demand hospital space Instructions: Calculate 1968 and 1918-type pandemics FluWorkLoss: calculate work days lost 28

30 29

31 30 Can use default values or alter

32 Describe spread of disease Not an epi model- no when or how Calculate cost of impact Make a cup of tea Part of the process not the entire answer! 31

33 Total deaths ('000) th percentile Maximum Mean th percentile Minimum % 0 2 % 5 3 % 0 3 % 5 National, 1-year gross attack rate 32

34 Criteria for prioritization Priority Risk of death $ to vaccination 1 (top) H.R. 65+ yrs H.R yrs 2 non-h.r. 65+ yrs H.R yrs 3 H.R yrs non-h.r yrs 4 H.R yrs non-h.r yrs 5 non-h.r yrs H.R. 65+ yrs 6 non-h.r yrs non-h.r. 65+ yrs H.R. = high risk Source: Meltzer et al. Emerg Infect Dis, , 5:

35 CDC Response Ebola 34

36 Photo by Spencer Lowell for TIME magazine 35 CDC Emergency Operations Center

37 Liberia: August 2014 Estimates MMWR SurveillSumm 2014;63 Suppl 3:1-14. Corrected for potential underreporting by multiplying reported cases by a factor of

38 MMWR Surveill Summ 2014;63 Suppl 3:1-14. Not corrected for potential underreporting. 37

39 Liberia Estimates Based on August 2014 Data Reported cases, ~8,500 through mid-january, were within 23% of model estimates. Corrected for Underreporting Uncorrected Blue vertical bar represents correction for underreporting by factor of 2.5. MMWR Surveill Summ 2014;63 Suppl 3:1-14. WHO Situation Report 21 January

40 70% The epidemic begins to decrease and eventually end if approximately 70% of persons with Ebola are in medical care facilities or Ebola treatment units (ETUs) or, when these settings are at capacity, in a non-etu setting such that there is a reduced risk for disease transmission (including safe burial when needed). MMWR Surveill Summ 2014;63 Suppl 3:

41 Frieden & Damon; Emerg Infect Dis 2015; 21:

42 The Four Horsemen of the Apocalypse by Viktor Vanetsov 1887