Swine Flu Part 3B- Why is it so scary?

We have finally come to the reason why I started writing this series of posts. I mentioned this in my last post, but the swine flu is actually less deadly than the annual influenza outbreak with an estimated mortality of 0.2% as opposed to the combined influenza and pneumonia mortality which ranges from 7-9%/year. However, swine flu is highly infectious, infecting a mind-blowing 60% of the mexican village in which it originated. I found an excellent answer to my question in the editor's comment on a CDC Morbidity and Mortality Weekly Report article published on May 7, 2009.

The scare-factor of swine flu is four-fold.

1. This virus has gone pandemic in a very short amount of time.
   
2. Higher percentage of patients with H1N1 are requiring hospitalization than with the normal flu.
   
3. The sickest patients are working-aged people.
   
4. Influenza season is about to start in the southern hemisphere.

I will explain each in more detail:
1. H1N1 has gone pandemic in a very short amount of time.
The seasonal influenza outbreaks tend to hover around the epidemic threshold. Each country/region has its own influenza virus subtype causing its localized, contained epidemic. Remember my analogy about flu from different regions of the world have different RNAs and therefore "look" different? This also helps to prevent one particular influenza virus from going global and causing a pandemic. H1N1 threw all of that out the window. It is so contagious that it has created a pandemic almost overnight.

2. Higher percentage of patients with H1N1 are requiring hospitalization.
But remember, they aren’t dying at the same rate. This increase in required hospitalization represents a huge change in morbidity (sickness) that our global healthcare system is completely unprepared to accommodate. We literally physically do not have enough beds to put people on. Not to mention lack of enough staff or medical supplies to treat the projected numbers of people who may need hospitalization. The CDC and public health officials are going to great lengths to change this potential outcome and I will discuss what they are doing below.

3. The sickest patients are working-aged people.
The highest rates of hospitalization are among 30-44 year olds. The seasonal flu tends to hospitalize children <2,>65 and patients with defective immune systems. The change in who is very sick can have a global economic impact as the workforce is affected. I don't think I need to go on about bad economic stuff.

4. Influenza season is about to start in the southern hemisphere.
This is bad news for them – there will be a whole jumble of influenza viruses going around. Differentiating who has H1N1 from others is going to be extremely difficult. Added to that is the issue of increased succeptibility to H1N1 transmission because the other viruses going around will weaken patient's immune systems and vice versa. It is unclear how H1N1 will interact with the seasonal flu but there is a huge amount of potential for reassortment and recombination as people become infected with more than one type of influenza virus at a time. The CDC is anticipating tremendous outbreaks of H1N1 in the southern hemisphere from June – October.

There are some things listed above that we can try to wrestle some control over. The fact that H1N1 is pandemic is over. The cat is out of the bag and there's nothing to be done about it. The fact that influenza season is about to start in the southern hemisphere is unstoppable. Sun rises every morning, sets every night, influenza season happens, fact of life. #2 and #3, however, are things that the healthcare community can try to effect change over.

One more science lesson for you, this time on epidemiology.

Outbreaks of an illness follow a bell-curve. First one person gets infected, they infect 5 more. Those 5 go on to infect 5 more each, etc. You get an exponential rise in the number of sick people in a given community/area/globe/whatnot. The bell-curve peaks and the height of the peak is determined by how infectious a disease is and how long it lasts. The peak represents the highest number of infected people in a population at one moment in time. You may be wondering, why does the curve come back down? For the same reason why you can't catch the chicken pox twice. After a person has been infected with the disease in question and has either a) recovered or b) died, they cannot get the diesease again. There are literally fewer people to are suceptible to the infection and therefore the number of people who get sick falls off until everyone has gotten it or there are too few people still succeptible to allow the disease to continue to propogate.

Important facts about the epidemic curve: 1) the line/bar represents number of active cases at that point in time. 2) area under the curve = total # of cases for the entire outbreak.

It is often difficult ot affect provision #2-- the total number of cases for the entire outbreak. However, we have a number of methods for adjusting the number of cases at any given time and lowering the peak of the curve. These things consist primarily of community mitigation (school closures, quarantine), vaccination and prevention with antiviral drugs. The ultimate goal is to get a picture like what we see on the right. This figure is EXTREMELY idealized but it makes the point well. Control measures will make the pandemic last longer and probably will NOT reduce the total # of people infected (area under the curve) but they will hopefully reduce the upslope and peak to allow for a manageable outbreak that our global healthcare system can absorb. The three goals listed on the figure are 1) delay outbreak peak (allows for vaccine and prophylactic strategies to be put into effect) 2) Decompress peak burden on hospitals/healthcare and 3) diminish overall # of cases.

What do school closures do? They are simply a delaying tactic. By reducing these reservoirs of transmission, public health officials hope that the peak of the pandemic can be delayed until a vaccine is developed and administration strategy is worked out. Slowing virus transmission will also reduce hospital burden and help our healthcare system to absorb H1N1 patients. It is an attempt to reduce volume of patients at any given time along the pandemic curve.

Where is the vaccine? Being worked on. Laboratories are working as fast as they can to develop and test a swine flu vaccine. If one is distributed (we were burned in the 1976 epidemic) it will be two separate shots that cannot be given in conjunction with the seasonal flu shot. Why two? Because good vaccines make your arm hurt. Patients would rather get sick than have their arm hurt -- it's a medical fact of life -- so by diluting the vaccine and spreading it out over two shots, it becomes publically acceptible. Patient's arms won't hurt.

There is a second problem with vaccination. Vaccination decreases numbers of people infected when initally given, but there will be a resurgence of disease later down the line due to the impossibility of vaccinating an entire population. You will get a bell curve that abruptly drops during the upslope only to peak later on. In some mathematical models, if vaccination is done incorrectly, this second peak can be even larger than what the original was projected to be! However, a correctly timed vaccination strategy targeting the correct population and lasting for the correct duration (4 weeks is better than 2 days) will significantly decrease the second peak. Even if a vaccine to H1N1 is developed and approved tomorrow, public health officials may correctly hold it until the appropriate moment in the pandemic.

The figure on the left shows how the number of hospital admissions would be projected to decrease using different durations of vaccination campaign from 2 days to 10 days. This particular graphic is for a theoretical smallpox outbreak, but the curve holds for all epidemics for which a vaccine is available. The timing and duration of any vaccination campaign is critical to its success in both protecting the public and reducing hospital burden.

That's all, folks! Write a comment if you have more questions!!

Bibliography:
Brownstein JS, Influenza A (H1N1) Virus, 2009 – online monitoring. NEJM. 2009 May 7 [epub ahead of print]

http://cdc.gov/flu/weekly/weeklyarchives2007-2008/07-08summary.htm

Update: Novel influenza A (H1N1) Virus Infections – Worldwide, May 6 2009. MMWR May 8, 2009 / 58(17);453-458 http://www.cdc.gov/mmwr/preview/mmwrhtml/mm5817a1.htm

Hupert N, Wattson D et al. Anticipating demand for emergency health services due to medication-related adverse events after rapid mass prophylaxis campaigns. Acad Emerg Med March 2007, 14(3), 268-274.

For informaiton on mathematical modeling for epidemiology, any articles by Nathaniel Hupert.
New England Journal of Medicine H1N1 center
CDC H1N1 center