Insights from FluTracking Analyses
Throughout the year, we will post interesting FluTracking analyses for your feedback.
1. FluTracking Pilot Emergency Survey of NSW Bushfire Smoke Health Impacts
These results relate to our pilot study conducted relating to the time period December 2nd to December 15th. The results for the Australia wide survey will be posted here once data analysis has been completed.
Large parts of the Eastern coast of Australia are currently experiencing extreme and catastrophic bushfire events. The prolonged presence of visible smoke in the air across much of NSW has caused significant media attention to be directed at the possible health impacts of prolonged exposure to smoke. In NSW, hospital and Emergency Department presentations for smoke related breathing problems have increased, but the community burden of smoke-related symptoms remained unknown.
In response to the growing community concern, and to assess the community level burden of smoke-related symptoms, the FluTracking team composed a one-off bushfire smoke symptom survey to send to a small group of participants. The aim of this survey was to use the strengths of Flutracking as an existing community surveillance program to assess the community burden of smoke-related symptoms, and gauge whether members of the community with increased risk (those with existing respiratory illnesses) were more affected by the smoke.
We asked a random sample of 1,200 participants in the Hunter New England local health district (Figure 1) if they experienced any symptoms during the two week period including Monday December 2nd to Sunday December 15th. We also sent the same survey to a random sample of 1,200 participants in the Hobart Region. Hobart had not seen elevated particle matter in the air, and had little-to-no smoke in the period we surveyed. Surveying these two different regions allowed us to determine the proportion of symptoms that might be related to smoke in the Hunter New England area.
Participants in the smoke-affected Hunter New England local health district reported much higher rates of symptoms.
By 11:30am Wednesday December 18, 44 hours after the survey was sent, 1,962 participants had responded to the survey, 1231 from Hunter New England and 731 from Hobart. The percentage of participants in Hunter New England (66.5%) reporting at least one of the symptoms assessed was four times higher than in Hobart (16.2%). The most commonly reported symptoms (by percentage of participants reporting each symptom) in the Hunter New England local health district were Eye Irritation (49.2%), Throat Irritation/Dry Throat (46.3%), and Cough (36.2%). Eye and Throat Irritation rates were more than 9 times higher in the Hunter New England local health district compared with Hobart. In the Hunter New England local health district most participants (87.0%) reported their symptoms were related to the bushfire smoke. Figure 3 shows the percentage of participants reporting each symptom by location.
Although many participants in the Hunter New England local health district reported experiencing bushfire smoke related symptoms, the symptoms appear to be mild in severity for most participants. Only 10.8% of participants who reported experiencing symptoms in the Hunter New England local health district sought advice from a General Practitioner, Emergency Department, or reported being admitted as a hospital in-patient. Only 22.0% of participants in the Hunter New England local health district who reported symptoms required time off work or normal activities. In the 2019 FluTracking season 70.1% of our participants with fever and cough reported taking at least one day off work or normal activities. These findings suggest a wide-reaching, but mild in severity, health effect of bushfire smoke in the community.
We also asked survey participants about their history of respiratory disease. Among the participants who responded, 22.3% reported having asthma, COPD or another respiratory illness. Symptoms such as wheeze, breathlessness, and chest pain, were much more prevalent among participants who reported having a history of respiratory illness, particularly in the Hunter New England local health district where smoke was an issue. In Hobart, participants reporting a history of respiratory illness had much higher rates of almost all symptoms than those who without a respiratory illness.
Over the period including Monday December 2nd to Sunday December 15th the Hunter New England region experienced poor air quality coinciding with visible bushfire smoke. We surveyed 1,962 Flutracking participants and found that participants located in the Hunter region experienced a much higher rate of a range of respiratory and other symptoms (compared to participants located in Hobart). The majority of participants attributed at least one of their symptoms to bushfire smoke. Participants with a history of respiratory illness had elevated symptom levels in both locations (compared to those with no history), but those in the Hunter region experienced symptoms including wheeze, chest pain and breathlessness at a much higher rate than participants without a history of respiratory problems – suggesting the smoke had a particularly strong impact on this group.
2. Out of Order Surveys Analysis
|What did we do?||We checked how many people do their FluTracking surveys out of order (for example missing a few weeks and then doing the most recent survey before the earlier ones) and whether this influenced when FluTrackers report being vaccinated.|
|What did we find?||Only a small fraction of people completed their survey out of order sequence and even smaller fraction changed their vaccination status at the same time.|
|So what?||We are now more confident that FluTracking data on the timing of vaccination is not being largely influenced by surveys being done out of order.|
One question the FluTracking team had was how many of our participants complete their surveys in chronological order. More specifically, we wanted to find out how many participants complete their surveys out of order and whether that has any impact on collected data used for analysis. This question was especially important for participants who want to update their vaccination status, as they may inadvertently tell us they were vaccinated at a time they weren’t if they are answering several surveys out of order.
Out of order survey completion refers to surveys which are completed before other surveys that were sent earlier. For example; you could miss one or more surveys (perhaps you were away on holiday), and when you get back you click on the latest FluTracking email. However; because newer emails appear at the top of your inbox you probably complete the latest survey before the earlier ones that you missed. As a result; your responses would be 3-4 weeks out of order.
Normally it doesn’t make any difference to our data as long you remember to complete all the surveys; however, it makes a big difference if you change your vaccination status in an out of date survey because your vaccination time may be incorrectly recorded, and this could impact on certain analyses.
Because of the way the FluTracking platform sends out the surveys, it is likely many people have completed at least one survey out of date if they simply click the latest email they receive. However, because we allow our participants to ‘back fill’ up to five additional weeks they may have missed, it is possible that completing surveys out of order could mean our recorded ‘vaccination dates’ are out by up to 6 weeks! It was therefore quite important that we check the extent to which this problem might be present in our data.
|Year Analysed||Number of Weeks||Country||Method Used to Analyse Data and Produce Charts|
|2018||20||Australia||We used 11 SQL queries and VBA code to select, collate, and analyse the data, Microsoft Excel to produce charts from generated statistical data , and TechSmith Snagit (screenshot program) to convert generated charts into graphics we posted on this page.|
Figure 1 – Analysis Method
NOTE: As a further precaution, we checked the length of time people generally back filled when they completed surveys out of order. Most participants (83.99%) who completed a survey out of order only missed 1 week, and only 8.50% participants filled back 4 weeks. Nobody was out by 5 or 6 weeks. Looking at all the collected data for 2018; there is really nothing to worry about. These analyses help us be confident in our analyses, particularly when we look at how Influenza Like Illnesses might differ for people who have been vaccinated against the flu.