Simulating pandemic spread with a phone app?

Source: BBC News

Researchers at the University of Cambridge Computer Laboratory have developed (along with 7 other institutions) the FluPhone app that tracks how people interact and potentially spread influenza or other pathogens.  The app uses Bluetooth technology to anonymously record interactions between volunteers. When cellphones come into close proximity, the interaction is recorded and data is sent to the researchers.

A just-released version of the FluPhone app can transmit fake pathogens to other phones so that the team can randomly "infect" one phone and see how it spreads within the volunteer community. Pretty cool. I wouldn't head to your favorite app store to volunteer just yet, since this study appears confined to the UK and Nokia phones. I actually forgot that Nokia made mobile phones.

Source: BBC News, May 4, 2011

Predicting flu in 140 characters or less

Early on in the 2009 H1N1 epidemic, I posted about how some of our Iowa colleagues were tracking public interest in H1N1 (then still called “swine flu”) by tracking tweets in real time. Well, they’ve now published their findings, which are extremely cool, in PLoS ONE.

Following public opinion about an emerging infection is interesting enough, but I especially like their use of Twitter to predict influenza-like illness (ILI) rates. Check out figures 9 and 10 to see how closely Twitter traffic tracked reported ILI cases (once models were developed to determine the relative contributions of each influenza-related Twitter term to predicting ILI rates). As these authors point out, real-time Twitter data precedes traditional surveillance information by a couple weeks, which could be quite useful in public health planning and preparedness.

Check out other cool stuff from the computational epidemiology group at Iowa

Pandemic Flu: Hit hard, but should we hit early?

Image courtesy of CU Boulder Applied Math
Mathematical Biology Group

When a new pandemic flu strain emerges, as happened in Mexico in 2009, public health interventions such as social distancing are often implemented in the hope of reducing transmission. It is often assumed that the more measures that can be implemented early in the epidemic, the better. However, social distancing policies, while sounding simple, are very costly and typically of finite duration.  It is also unclear, what the policy 'objectives' of the intervention should be. Is the aim to reduce total morbidity/mortality or is it to reduce peak prevalence? How are these aims to be balanced against the societal impact of the interventions? Heady questions indeed.  Fortunately, a new paper in PLoS Computational Biology by Deirdre Hollingsworth and colleagues (including Roy Anderson) poses many of these questions and attempts to explore the intertwined policy objectives of various pandemic flu mitigation strategies.

Using a mathematical model (deterministic SIR model) and assuming a mean infectious period of 2.6 days, an Ro=1.8 and a population size of 58 million (the population of the island of Great Britain), the authors estimated the impact of social distancing interventions on influenza dynamics. They looked at a three possible durations of the intervention: (1) indefinite (2) 12 weeks - the current US policy maximum and (3) until a pandemic vaccine becomes available at 6 months. The also incorporated the use of a limited stockpile of antiviral drugs to limit disease severity and reduce transmission and also looked at the utilization of a partially protective pre-pandemic vaccine during the first 6 months of the pandemic.

What did they find? Well, it is pretty messy, like the truth typically is. One finding that sticks out is that in long-term interventions, there is very little disease incidence before week five, so there is little overall benefit from starting social distancing policies too early. The authors estimate that a few weeks delay in implementing a long-term intervention may result in a higher peak prevalence, but a considerably shorter duration of the epidemic.

What about short-term (12-week) interventions, such as those recommended by the current US pandemic plan? In this scenario, strategies that might contain an epidemic size below a certain level would not be the same ones that could limit peak prevalence. In these scenarios there would be a second peak after the intervention is lifted and they may even result in almost no change in overall epidemic size. For these "short" duration interventions there are no easy answers. For example, if the social distancing intervention is 33% effective in reducing transmission and is started at week 5, it might minimize peak prevalence. However, the same intervention with 22% effectiveness and similar timing would be expected to minimize the epidemic size.

The authors describe and discuss various other scenarios and provide a multitude of estimates for what the effects might be.  However, I think their key contribution is to force us to confront very important policy questions head on.  We need to have discussions about what our policy objectives should be in a pandemic.  Should we aim to limit the total number of cases or should we care about the peak size of the pandemic when our hospital and other public health services are stretched to the limit?  Maybe we should just want the epidemic to end as quickly as possible, so that society can get back to the new normal? We should probably have these discussions before the next pandemic, so we can design the optimal policy to achieve our goal(s). 

Hollingsworth et al. PLoS Computational Biology February 2011

H1N1 Flu Deaths in the UK on the rise

Per a government report in the BBC and other UK papers, there have been 39 deaths from the flu this winter with 36 confirmed as H1N1-related while the other three were caused by influenza B.  Unlike here in the US, the UK vaccination committee does not recommend a flu "jab" for healthy children less than 5 and other children ages 5 to 15.  All but one of the deaths occurred in people <65yo. Around 20% of all ICU beds in England are now filled with confirmed or suspected influenza patients.

Health Secretary Andrew Lansley said "the people we would wish to vaccinate are people in at-risk groups and over 65s who can be contacted via their GP." Which makes some sense since 23/38 deaths (one patients data wasn't available yet) were from high-risk groups. However, that still leaves 40% of patients without any risk factors. Since there is no vaccine shortage, I wonder why they aren't broadening their vaccine strategy to include younger children. As it is, only 23% of currently eligible children <5 get vaccinated.

The H1N1 virus continues to attack younger children and not older adults. In English children <4yo, the influenza incidence is 184 cases/100,000 while it is only 36 cases/100,000 in those >65yo. An epidemic is defined as an incidence >200 cases/100,000.  Seems like rapid vaccination of children might be a good idea, particularly when you look at the graph below showing 2010-2011 as an active year, similar to the spring of 2008-2009 season when H1N1 began.  If H1N1 vaccine was available in spring 2009, I bet they would have promoted it more than they are promoting the vaccine now.

Oh, Happy New Year!

BBC report (12/30/2010)
Guardian report (1/1/2011)

UK Health Protection Agency Epidemiological Report 30 December 2010

ILI Activity with 2010-11 in red  - taken from UK HPA report (link above)

Influenza not taking year off, again! - 3 flu strains in Iowa

Iowa is below Minnesota, to the left of Illinois with a large nose
and small mouth; most consider it the most handsome state.

I thought after last year, influenza would finally take a year off and not cause any problems.  It seems that influenza's streak is getting into Cal Ripken territory.

I also thought that moving to Iowa would limit my exposure to these sorts of transmissible pathogens.  It's not like I see people most days; ain't nobody here but us chickens.  I even thought Dan was joking about measles and mumps.  We have vaccines, we can't possibly have measles and mumps around here!  Apart from what people say, I really do think wishful thinking can prevent influenza if we wish REALLY really hard. If even one of us gives up hope - bam, pandemic.

So I was surprised (not really) to learn that we currently have 3 influenza strains circulating in Iowa (H3N2, H1N1 and Influenza B). From what I gather, there is a good match with the vaccine. So perhaps now would be a good time to get vaccinated.  As Dan said, we are doing well at UIHC with a 93% vaccination rate. Not sure what the vaccine uptake is in the community, but I guess we are about to find out.

Chicago Tribune article

Oseltamivir+Zanamivir combination therapy vs monotherapy for seasonal influenza

A Combination Lock

In infectious diseases, there is always the trade-off between treating the individual patient and the population effects of antimicrobial resistance.  One way to counteract the development of resistance might be combination therapy (eg HIV ART) but this would only apply if the combination provided an added benefit to the individual patient with minimal side effects.  To answer this question for influenza, researchers in France in fall 2009 (85% H3N2 virus) conducted an RCT comparing oral oseltamivir 75 mg twice daily plus zanamivir 10 mg by inhalation twice daily to oral oseltamivir monotherapy or inhaled zanamivir monotherapy. The primary outcome was the proportion of patients with nasal influenza reverse transcription (RT)-PCR below 200 copies genome equivalent (cgeq)/µl at day 2. They also tracked symptom resolution out to day 14 among other outcomes.

The researchers planned to enroll 900 patients with ILI<36 hours and a positive rapid influenza A test, however the RCT was halted after only 541 (447 with confirmed virus) were enrolled.  In the intention to treat analysis, 46% in the O+Z group reached RCT-PCR<200, while this was achieved in 59% of the oseltamivir monotherapy and 34% of the zanamivir monotherapy groups.  Nausea and/or vomiting was more frequent in the combination arm.  Thus, the trial was ended early. The authors concluded: "Despite the theoretical potential for the reduction of the emergence of antiviral resistance, the lower effectiveness of this combination calls for caution in its use in clinical practice."

Duval et al. PLoS Medicine November 2, 2010

Prior seasonal influenza infections protective against 2009 Pandemic flu (if you're a ferret)

Looking back at the 2009 flu season, I realize how calm it is now compared to then.  I hope it stays that way!  In that pandemic, the attack rate was 50% in young populations compared to perhaps 10% in adults.  Why would this be the case? Serologic analysis showed little cross-reactivity between recent seasonal influenza A(H1N1) viruses and pandemic A(H1N1). The authors of a recent JID paper postulated that the lower attack rate in adults could result from multiple past exposures to viruses with similar B epitopes or since there is conservation of T cell epitopes between pandemic H1N1 and seasonal influenza A, then cellular immunity may also reduce disease severity. There's also the fact that adults responded to a single dose of pandemic H1N1 vaccine, while children did not, suggesting that past exposure to seasonal strains is important.

To examine the role of prior immune reponses in seasonal influenza on exposure to pandemic H1N1, Laurie et al. in the Oct 1 JID, studied the impact of one or two prior infections in a ferret model.  The found that a single prior infection with a seasonal influenza A virus, A/Fukushima/141/2006 (H1N1) or A/Panama/2007/1999 (H3N2), reduced the duration of shedding following challenge with 2009 pandemic H1N1, but not reduce the infection rate nor did it reduce the transmission to other ferrets.

The authors then tested whether two prior infections with seasonal influenza was protective against pandemic H1N1.  They determined that infection with seasonal A(H1N1) followed by A(H3N2) reduced the infection rate along with the amount and duration of shedding in ferrets challenged with pandemic A(H1N1). Interestingly, no virus was transmitted to other ferrets, nor did the exposed naïve ferrets experience seroconversion to pandemic flu.

Good news, if you're a ferret.

Laurie KL, et al JID, October 1, 2010.

Home humidification and influenza virus

A new report out in Environmental Health evaluates the effect of using portable humidifiers on absolute humidty levels and influenza virus survival in Northeast United States residences using an indoor air quality model. A portable humidifier in the bedroom was associated with a decrease in influenza virus survival from 17.5 – 31.6% and given the water vapor distribution throughout the entire residence they estimated a 7.8-13.9% house-wide reduction in influenza virus survival.  Something to think about as fall/winter approaches?

Environmental Health article

Presenteeism: It plagues us

The August edition of the Journal of General Internal Medicine has a paper and editorial on presenteeism that are important for the infection prevention community. Presenteeism is the situation that occurs when workers report to work ill. In the case of communicable diseases in the healthcare setting, presenteeism has the potential to spark outbreaks of illness such as norovirus gastroenteritis, influenza, and other respiratory infections.

As I mentioned in a previous posting, our influenza control plan for the upcoming season is to encourage (but not mandate) vaccination of healthcare workers, coupled with a greater emphasis on avoiding presenteeism. Unlike vaccination, reducing presenteeism is a multipotent intervention, and a great example of the horizontal approach to infection control.

Don't wait in a doctor's waiting room

I should have said don't wait too long in the "waiting area of healthcare premises" especially if another occupant/patient has measles, as the authors of a new study in BMC Infectious Diseases report.  The authors analyzed the likelihood of acquiring TB, influenza or measles during stays of 30 or 60 minutes in a standard waiting room using a mathematical model simulation.  One caveat is that they assumed one person in the waiting room was infectious with one of the organisms. Thus, while the results provide nice theoretical estimates of airborne transmission for these highly (measles), moderately (influenza) and minimally (TB) infectious organisms, they don't adjust for the probability of an occupant having the infection in the first place (influenza>TB>measles).   

With that important caveat, the likelihood of acquiring TB during a 30 minute stay in a waiting room was 0.3% and was 0.8% for a 60 minute stay.  For influenza, the numbers were 2.6% and 6.6% at 30 and 60 minutes and were 13% and 31% for measles.  With those numbers, if there is measles in the community at all, it's probably best to avoid any waiting area (unless you've been vaccinated). Nothing surprising in the results, really, but still worth quantifying and thinking about.  During the H1N1 season last year, I was always worried about transmission in the various hospital waiting areas.  In those situations, it was likely that >1 person had infectious influenza in the waiting room.  I hope future studies analyze the impact of # of infectious occupants and likelihood of those infectious occupants being present during various seasons (RSV, Influenza etc).

Once last thought.  Next time a clinician keeps you waiting, you might mention that he/she has put you at increased risk for getting sick.


Beggs et al. BMC ID article

Killer Flu!!!! - the video game

Do we need another distraction in our lives? I thought blogs were the last straw, but to the list of distractions we can add an educational influenza game.  Killer Flu is an Adobe Flash-based game (sorry no i-device version yet) which "allows you to learn more about how the influenza virus is transmitted and how it changes every year - which explains why you can get more than one dose of the flu over your lifetime and why vaccines need changing every year." The game gives you 180 days to infect as many people as possible using one of three scenarios: seasonal flu, re-assortment and H5N1 avian influenza.  I guess you can waste time and learn at the same time. What could be better?

Link to UK Clinical Virology Site
Lancet ID review

New CDC proposed guidance for influenza control

CDC recently posted proposed guidance on prevention of seasonal influenza in the healthcare setting. Written comments on the proposed standards will be accepted through July 22, 2010. The intent of these guidelines is to replace prior CDC infection control recommendations for seasonal and H1N1 influenza. In a nutshell, CDC is proposing droplet precautions, except when aerosol generating procedures are being performed, in which case airborne precautions should be followed. To see the document click here.

Why your friends spread influenza and you don't

There was a really interesting study by Nicholas Christakis and James Fowler in the May 15th Economist (here) and posted online (full manuscript here). The general thought behind the study was that people in the center of social networks, the ones with more friends or connections, would be more likely to be infected with influenza sooner. Thus, if you could identify people in the center they could serve as an early warning system for flu. The problem is, this would take a significant amount of effort. The insight into this problem comes in the form of what is called the friendship paradox. This 'paradox' suggests that your friends have more friends than you do.

To test this theory, Christakis and Fowler identified 319 students and then 425 of their friends. If friendship paradox would work in identifying influenza then the 425 should get flu earlier. So they followed the 744 students from September to December 2009 during the H1N1 epidemic and found that the friends, the 425 more likely to be in the center of the network, developed influenza (self-diagnosed and confirmed) around 2 weeks earlier. In fact, self-reported symptoms peaked 83 days earlier and visits to healthcare facilities peaked 46 days earlier in the connected group. Maybe this is a new method that could be added to other monitoring systems. Either way, come influenza season, stay away from your friends, especially the ones who are really friendly.

Healthcare worker vaccination programs: what works?

There is a new study out in ICHE by Tom Talbot and colleagues that looked at which factors of an influenza vaccination program were associated with a higher proportion of healthcare workers being vaccinated for seasonal influenza. The survey was completed during June 2008 and looked at programs in place during the 2007-2008 influenza season at 50 hospitals within the 78-hospital University HeathSystem Consortium (UHC) Benchmarking Program. The proportion vaccinated was the same whether or not hospitals required a signed declination from refusers. Factors association with higher compliance were weekend provision of vaccine, train-the trainer programs, report of vaccination rates to administrators or to the board of trustees, a letter sent to employees emphasizing the importance of vaccination, and any form of visible leadership support. Sadly, the median compliance was 55% and ranged from 26% to 81%. Perhaps I should have titled my post, "what didn't work" because it's hard to say anything really worked with compliance this low.

Herd Immunity in Influenza

Mark Loeb and colleagues have produced another fine study. They report in JAMA the results of a cluster-randomized trial where they vaccinated children aged 3-15 in 49 small communities in rural Canada. Children were vaccinated with either inactivated trivalent influenza vaccine or hepatitis A vaccine as a control. Confirmed influenza (RT-PCR) was 61% lower in non-recipients in the communities where children were vaccinated (3.1%) compared to non-recipients in unvaccinated communities (7.6%). Their main conclusion was that "a significant herd immunity effect can be achieved when the uptake of vaccine is approximately 80% in clusters in which children and adolescents aged 3 to 15 years are immunized." One note: this study was completed during the 2008-2009 season.