Conceived and designed the experiments: CA LR JBG SD DW IJ JW CY NSC. Performed the experiments: JBG AR TM ML CJ CA. Analyzed the data: CA LR NSC JBG JF AR. Contributed reagents/materials/analysis tools: AR TM JBG. Wrote the paper: AM CA LR NSC SD ML JBG JF.
None of the authors has any conflict of interest to declare. Dr Gubbay has received research grants from GlaxoSmithKline Inc. and Hoffman-La Roche Ltd to study antiviral resistance in influenza, however, this is not relevant to this study. This does not alter the authors′ adherence to all the PLoS ONE policies on sharing data and materials.
We designed a seroprevalence study using multiple testing assays and population sources to estimate the community seroprevalence of pH1N1/09 and risk factors for infection before the outbreak was recognized and throughout the pandemic to the end of 2009/10 influenza season.
Residual serum specimens from five time points (between 01/2009 and 05/2010) and samples from two time points from a prospectively recruited cohort were included. The distribution of risk factors was explored in multivariate adjusted analyses using logistic regression among the cohort. Antibody levels were measured by hemagglutination inhibition (HAI) and microneutralization (MN) assays.
Residual sera from 3375 patients and 1024 prospectively recruited cohort participants were analyzed. Pre-pandemic seroprevalence ranged from 2%–12% across age groups. Overall seropositivity ranged from 10%–19% post-first wave and 32%–41% by the end of the 2009/10 influenza season. Seroprevalence and risk factors differed between MN and HAI assays, particularly in older age groups and between waves. Following the H1N1 vaccination program, higher GMT were noted among vaccinated individuals. Overall, 20–30% of the population was estimated to be infected.
Combining population sources of sera across five time points with prospectively collected epidemiological information yielded a complete description of the evolution of pH1N1 infection.
In Canada, the first cases of pandemic H1N1 2009 (pH1N1/09) were reported on April 26, 2009; two days later the first cases were reported in the province of Ontario
Surveillance data based on laboratory confirmed cases capture only a fraction of the true cases of influenza since not all infected individuals are symptomatic, seek medical attention and provide specimens for laboratory testing. The extent to which surveillance reflects the true burden of disease was also affected by changes in the laboratory testing recommendations. Given the limitations in these data we designed a seroprevalence study with the following objectives: to estimate the community seroprevalence of pH1N1/09 in January 2009 before the outbreak was formally recognized; to assess the extent of community transmission of pH1N1/09 at multiple time points from January 2009 to the end of influenza season in April/May 2010; to identify the risk factors for infection with pH1N1/09, and; to assess the antibody response in individuals that were vaccinated during the second wave. Our aim was to develop an as complete as possible picture of the evolution of seroprevalence over the whole course of the 2009 H1N1 pandemic in Ontario.
The research protocol entitled “A Seroprevalence study of novel swine influenza A H1N1 among Ontarians” (protocol reference #24130) was granted approval by the Health Sciences Research Ethics Board at the University of Toronto, Canada. Written informed consent was obtained from participants.
We obtained specimens from two sources and three populations at multiple time periods (
Jan-09 | Feb-09 | Mar-09 | Apr–May-09 | Jun-09 | Jul-09 | Aug–Sep-09 | Oct-09 | Nov-09 | Dec-09 | Jan-10 | Feb-10 | Mar-10 | Apr–May-10 | |
Timing of pH1N1 activity | - First cases in Ontario (04/28)- Peak of 1st wave (mid-May) | - Peak of 2nd wave (end Oct)- Priority groups pH1N1 vaccination program (10/26) | - General populationpH1N1 vaccination program (11/16) | -Significant decline in pH1N1 activity | 1.1% pH1N1 positive of all respiratory specimens week of April 5th |
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Cohort Study | 1024 | 373 |
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Preventable disease screening |
383 | 383 | 505 | 838 | 790 | |||||||||
Prenatal screening |
105 | 120 | 136 | 115 |
*Specimens obtained from Toronto, Kingston, Windsor and Hamilton public health laboratories.
**Specimens obtained from Toronto public health laboratories only.
***Only sero-negatives from wave 1 were invited to participate in the final phase.
We invited Ontario residents who were 18 years or older, available for follow–up in August/September 2009, able to communicate in English and answer an online questionnaire to participate in the study. Participants provided informed consent and completed a web-based questionnaire on health behaviours, health history and demographic information. Blood specimens were collected in serum separator tubes (SST tubes) at medical laboratory locations throughout Ontario. We aimed to recruit 1800 participants (600 from each of 3 age groups: 18–29, 30–64 and 65 years of age and older) in order to have 80% power to detect a difference in seroprevalence of 10%. We recruited through news releases, news articles, newspaper advertisements, emails to stakeholders, Google ad words and Facebook. Newspaper readership in the selected newspapers was over 1 million individuals per day, and at the time, the term “H1N1 flu virus” demonstrated a high percentage of all Google searches. In April 2010, study participants who were seronegative by hemagglutination inhibition assay (HAI) assay after wave 1 were invited to provide a second blood sample and complete another online questionnaire on risk factors, health status and vaccination history.
In Ontario, all preventable disease and prenatal screening tests are performed by OAHPP laboratories. These specimens are submitted for a variety of reasons including occupational screening, requiring proof of immunity for school purposes, and screening of new immigrants. Prenatal screening is recommended for all pregnant women in the province. Residual sera held by OAHPP were randomly selected and had complete information on sex, age, and residence (
Sera were extracted from blood specimens and tested by HAI to determine antibody titres against the pH1N1/09 influenza strain (A/California/07/2009–like) and the 2008–2009 seasonal H1N1 influenza strain A/Brisbane/59/07 (Brisbane H1N1) to identify potential cross-reactivity. The HAI and microneutralization (MN) protocols were adapted from previously published World Health Organization (WHO) methods
We calculated the proportion of seropositive participants for each age group, time period and study population with 95% confidence intervals according to the binomial distribution.
To assess the strength of the association between risk factors and positive seroprevalence status in the cohort study, we calculated unadjusted and age-adjusted odds ratios (OR) with 95% confidence intervals using logistic regression analysis. Multivariate logistic regression was fit to determine independent predictors and variable selection done was completed using the Hosmer-Lemeshow forward model building strategy. Briefly, univariate logistic regression for each independent variable was conducted. Variables that were significant using a cut-off of 0.2 were considered as candidates in the multivariate model. Variables were added based on level of importance using magnitude of the odds ratio and a priori variables (age and sex). Variables were retained in the final multivariate model if they were significant (P<0.05) or determined a priori. Geometric mean titres (GMTs) were calculated for cohort study participants who provided samples post-wave 1 and at the end of the 2009/10 influenza season. For titres lower than 10 (<1∶10), GMTs were estimated by assigning a value of 5. Sensitivity and specificity of the HAI was calculated using the MN assay as gold standard. All analyses were completed in SAS version 9.1.
We collected residual serum specimens from 3375 individuals who had submitted during our time periods of interest. For the cohort study, 1486 people registered to take part in the study and of those, 53 (3.6%) withdrew primarily due to difficulties scheduling appointments to provide a blood specimen. Among the remainder, 1245 (86.9%) completed the online questionnaire and 1069 (74.6%) had a blood specimen collected. Forty-five participants who provided blood specimens after October 5, 2009 were excluded, leaving 1024 or 68.9% for analysis post wave 1. In April 2010, 941 seronegative individuals who were asked to provide another specimen. Thirty-eight (4.0%) actively withdrew and 518 (57.4%) did not respond leaving 385 in the cohort study for the post-wave 2 analysis (
Compared with the general population, preventable disease residual specimens were more likely to be female and living in the Toronto region (
Category | Number and Proportion of Participants n (%) | Proportion of Ontario's Population, % |
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Preventable Disease Residual Specimens (N = 2899) | Prenatal Residual Specimens (N = 476) | Cohort Study (N = 1024) | |||||
<18 |
494 | (17) | 93 | (20) | - | 24 | |
18–29 years |
480 | (17) | 127 | (27) | 160 | (17) | 14 |
30–64 years |
1387 | (48) | 256 | (54) | 525 | (56) | 49 |
65+ years | 538 | (19) | – | 259 | (27) | 13 | |
Female | 2010 | (69) | 476 | (100) | 551 | (58) | 51 |
Male | 887 | (31) | 0 | (0) | 392 | (42) | 49 |
Toronto | 1128 | (39) | 249 | (52) | 232 | (23) | 21 |
Central East | 820 | (28) | 154 | (32) | 227 | (23) | 29 |
Eastern | 202 | (7) | 2 | (<1) | 207 | (21) | 13 |
Central West | 486 | (17) | 55 | (12) | 175 | (18) | 19 |
South West | 207 | (7) | 1 | (<1) | 115 | (12) | 12 |
North East | 40 | (1) | 9 | (2) | 34 | (3) | 4 |
North West | 10 | (<1) | 4 | (1) | 7 | (1) | 2 |
White | – | – | 875 | (93) | 77 | ||
Non-white | – | – | 70 | (7) | 23 | ||
University degree | – | – | 553 | (59) | 20 | ||
No university degree | – | – | 392 | (41) | 80 | ||
Health-care worker | – | – | 138 | (15) | 5 | ||
Teacher (pre-school to grade 12) | – | – | 42 | (4) | 4 | ||
Child care worker | – | – | 5 | (<1) | 1 | ||
Other | – | – | 750 | (80) | 90 |
*For prenatal residual specimens, only ages 10 to 17 years are included. For the Ontario population, includes those <20 years of age.
For the Ontario population, includes those 20–29 years of age.
For prenatal residual specimens, only ages 30 to 49 years are included.
For each study population, pH1N1/09 seroprevalence levels increased until after the second wave with the largest increases occurring in the younger age groups. Overall pre-existing seropositive levels ranged from 2.0 to 12.0%, with those 65 years and older having the highest levels. Following wave 1, seroprevalence in study populations ranged from 10.9 to 18.3% overall with the highest proportions seen in the prenatal residual samples and generally among those in younger age groups. At the end of the 2009/10 influenza season, overall seroprevalence levels ranged from 32.2% to 40.9%, but varied greatly between age groups. In the residual samples seropositivity dropped slightly between the end of the second wave and the end of the influenza season (January to May 2010) (
Study population | Time period | % Seropositive (95%CI) | ||||
<18 yrs | 18–29 yrs | 30–64 yrs | 65+ yrs | Total | ||
Cohort Study | 3. Post-wave 1 pandemic | 14.4 (8.9–19.8) | 10.7 (8.0–13.3) | 8.9 (5.4–12.3) | 10.9 (9.0–12.8) | |
5. End of flu season (only seronegatives from period 3) | 45.2 (30.2–60.3) | 43.7 (36.6–50.7) | 33.3 (25.3–41.4) | 40.0 (35.1–44.9) |
<18 yrs | 18–29 yrs | 30–64 yrs | 65+ yrs | Total | ||
Preventable disease residual samples | 1. Pre-pandemic | 2.0 (0.0–5.8) | 7.4 (0.4–14.4) | 4.1 (1.3–6.9) | 12.0 (5.0–19.1) | 6.0 (3.6–8.4) |
2. Early Wave 1 pandemic | 3.7 (0.0–8.7) | 7.4 (0.4–14.4) | 8.1 (4.3–11.9) | 15.6 (7.5–23.7) | 8.9 (6.0–11.7) | |
3. Post-wave 1 pandemic | 21.6 (13.0–30.2) | 12.5 (5.6–19.4) | 11.0 (7.1–14.9) | 19.0 (10.7–27.4) | 14.5 (11.4–17.5) | |
4. Post-wave 2 pandemic | 63.8 (56.3–71.2) | 38.8 (30.7–47.0) | 36.8 (32.0–41.6) | 35.9 (28.4–43.4) | 42.1 (38.8–45.5) | |
5. End of flu season | 61.7 (53.7–69.7) | 37.9 (30.0–45.8) | 36.3 (31.4–41.3) | 34.8 (26.8–42.7) | 40.9 (37.5–44.3) |
<18 yrs | 18–29 yrs | 30–64 yrs | 65+ yrs | Total | ||
1. Pre-pandemic | n/a | n/a | n/a | n/a | n/a | |
Prenatal residual samples | 2. Early wave 1 pandemic | 4.2 (0.0–12.2) | 11.1 (0.0–23.0) | 9.3 (1.5–17.0) | n/a | 8.6 (3.2–13.9) |
3. Post-wave 1 pandemic | 27.6 (11.3–43.9) | 10.0 (0.0–20.7) | 18.0 (8.4–27.7) | n/a | 18.3 (11.4–25.3) | |
4. Post-wave 2 pandemic | 29.4 (14.1–44.7) | 48.5 (31.4–65.5) | 43.5 (31.6–56.0) | n/a | 41.2 (32.9–49.4) | |
5. End of flu season | 83.3 (35.9–99.6) | 32.4 (17.3–47.5) | 27.8 (17.4–38.1) | n/a | 32.2 (23.6–40.7) |
The MN assay indentified a larger number of infections compared with HAI, particularly among those 65 years of age and older (P<0.0001) (
Risk factor | HAI assay | Microneutralization assay | ||
Age-adjusted OR (95% CI) | Multivariate |
Age-adjusted OR (95% CI) | Multivariate |
|
Male | 0.91 (0.59–1.39) | 0.93 (0.59–3.11) | 1.02 (0.71–1.46) | 1.11 (0.76–1.62) |
Age group | ||||
18–29 | n/a | 1.55 (0.77–3.11) | n/a | 0.80 (0.45–1.43) |
30–64 | n/a | 1.21 (0.70–2.11) | n/a | 0.65 (0.43–0.99) |
65+ | Reference | Reference | ||
Toronto resident | 1.62 (1.03–2.53) | 1.91 (1.18–3.10) | 1.01 (0.66–1.54) | |
Non-white ethnicity | 1.56 (0.79–3.10) | 0.87 (0.41–1.83) | ||
Canadian-born | 0.76 (0.45–1.29) | 0.77 (0.49–1.19) | ||
Secondary level/technical education only | 0.54 (0.27–1.06) | 0.95 (0.59–1.54) | ||
Experienced ‘flu-like symptoms’ since April 1, 2009 | 2.28 (1.45–3.57) | 1.90 (1.31–2.77) | ||
Experienced fever and cough since April 1, 2009 | 2.69 (1.69–4.29) | 2.52 (1.54–4.06) | 1.99 (1.30–3.05) | 1.99 (1.29–3.07) |
Received 08/09 Seasonal flu vaccine | 1.81 (1.15–2.86) | 1.68 (1.04–2.70) | 1.48 (1.01–2.18) | |
Received 07/08 seasonal flu vaccine | 1.67 (1.02–2.75) | 1.17 (0.77–1.77) | ||
Received 06/07 seasonal flu vaccine | 1.48 (0.88–2.48) | 1.01 (0.65–1.55) | ||
Flu vaccine doses | ||||
Three | 2.30 (1.20–4.42) | 1.33 (0.79–2.23) | ||
Two | 1.53(0.71–3.29) | 1.10 (0.59–2.06) | ||
One | 2.02 (0.88–4.63) | 1.23 (0.59–2.57) | ||
None | Reference | Reference | ||
Previously tested for pH1N1/09 | 2.65 (0.95–7.38) | 1.20 (0.40–3.61) | ||
Chronic medical condition | 1.29 (0.82–2.02) | 1.35 (0.92–1.97) | ||
Currently pregnant | 1.37 (0.38–5.00) | 0.36 (0.05–2.81) | ||
Health care worker | 1.33 (0.77–2.29) | 0.79 (0.45–1.36) | ||
Lives in a household of 4+ individuals | 0.98 (0.59–1.61) | 0.83 (0.52–1.33) | ||
Lives with school-aged children | 1.23 (0.75–2.02) | 1.08 (0.68–1.72) | ||
Visited a school or child care centre since April 1, 2009 | 1.14 (0.75–1.74) | 1.23 (0.85–1.78) | ||
Attended a large public gathering since April 1, 2009 | 0.85 (0.55–1.33) | 0.63 (0.43–0.91) | ||
Attended a large family gathering since April 1, 2009 | 1.60 (0.97–2.63) | 1.76 (1.03–3.01) | 0.97 (0.66–1.42) | |
Transit | ||||
Everyday | 1.26 (0.65–2.46) | 1.06 (0.57–1.95) | ||
More than once a week | 1.42 (0.77–2.62) | 0.94 (0.52–1.70) | ||
Once a week | 0.82 (0.43–1.59) | 0.69 (0.39–1.21) | ||
Never | Reference | Reference | ||
Hand washing | ||||
7 or more times/day | 0.92 (0.37–2.28) | 0.94 (0.42–2.08) | ||
3 to 6 times/day | 0.79 (0.32–1.97) | 0.86 (0.39–1.94) | ||
0 to 2 times/day | Reference | Reference |
*Aside from age and sex all variables in multivariate model are significant at p<0.05.
Among the 385 seronegative individuals that were followed in the cohort study, 270 received the pH1N1/09 vaccine (
Vaccine | Total | No. (%) pH1N1/09 seropositive HAI | No. (%) pH1N1/09 seropositive Microneutralization | GMT pre-vaccine (95% CI) | GMT 6–8 month post-vaccine (95% CI) | ||
Received pH1N1/09 vaccine | No | 95 | 13 | (13.7) | 10 (10.1) | 8.5 (5.1–12.0) | 10.8 (6.3–15.3) |
Yes | 270 | 133 | (49.3) | 120 (44.3) | 8.3 (5.0–11.7) | 30.1 (24.2–35.9) | |
Total |
385 | 154 | (40.0) | 134 (34.8) | 8.4 (5.0–11.7) | 23.4 (17.4–29.5) |
*pH1N1/09 vaccine status was unknown for 20 participants.
Using age-specific seropositivity rates as well as population estimates in Ontario and baseline seroprevalence in the population, the total outbreak size is estimated between 2.4 and 3.9 million, or 18–30% of the population, implying that routine laboratory surveillance detected approximately 1 in 350 cases of infection Ontario. It is estimated that the infection rate in the second wave was 2.0–3.2 times the size of the first wave. (details provided in
Our results draw a near-complete picture of the evolution of seropositivity to pandemic H1N1from before the onset to the end of the 2009/10 influenza seasons in a large Canadian province, using a variety of study populations and prospectively collected epidemiologic data. Our estimates of infection using the serological data indicate that approximately 24% of the population were infected with pH1N1, which is higher than Hong Kong
Our findings are consistent with laboratory surveillance such that the highest rates of infection were noted in younger age groups, particularly school-aged children
Seroprevalence levels among our preventable disease and prenatal screening populations were similar to two other smaller seroprevalence studies conducted in Canada; however there were important differences
We estimated of the second wave to be approximately 2.6-fold larger than the first, which is considerably lower than the reported five-fold higher rate in hospitalizations in wave 2 versus wave 1 in Canada
Study participants who reported receiving seasonal influenza vaccine in 2008/09 were significantly more likely to be seropositive by HAI after adjusting for other factors. Cross-reactivity of vaccine induced antibodies with pH1N1/09 antigen in the HAI assay is an unlikely explanation because the effect size was similar using MN, albeit non-significant. Previous studies have shown increased pH1N1/09 antibody titres among adults who received seasonal influenza vaccinations
Ontario distributed Arepanrix™ H1N1 vaccine, an adjuvanted influenza vaccine made by GlaxoSmithKline (GSK). Vaccine coverage within our seronegative cohort study population was 70%, as compared to 33% reported in the general population
Several limitations should be considered when interpreting the results of this study. The residual serum specimens were obtained from predominantly female individuals who were more likely to live in the Toronto region. Some of the selection biases in the overall cohort are likely the result of our web-based methods for recruitment and data collection. Individuals with limited computer skills or access to the internet and individuals who were not fluent in English would have been less likely to participate. The high proportion of health care workers included in the cohort may be due to an increased awareness of our relatively new organization compared to the rest of the population. In addition, our blood collection sites were primarily located in urban centres limiting participants from rural and more isolated Northern communities. Furthermore, we chose the cut-off of 1∶40 for our assays in order to ensure comparability with other studies; different cut-offs would have altered our findings. In a study of the sensitivity and specificity of pH1N1 tests, we found that HI may not be as sensitive as MN even though HI is the commonly accepted method for the detection of antibodies
There are various approaches to serological testing in the population, including active population recruitment and passive testing of blood specimens, both of which have for potential selection biases. The advantage of active recruitment is the ability to collect epidemiological information, which can reveal bias and determine risk factors and patterns of serostatus in the population that is not possible through passive data collection. While the selection bias of residual specimens, such as those for prenatal and preventable disease screening, cannot be measured, it may differ from those actively recruited and may not be associated with the outcome. We adopted multiple approaches in order to be more representative of the population. We found synthesizing data from both sources over time extremely useful to represent a more complete picture of the pandemic. Methods to reduce selection bias in serosurveys and the establishment of biorepositories are important future considerations.
This study synthesizes a range of different sources of serological data with prospectively collected epidemiologic information. The collection of data across different time points allows us to observe the evolution of the pandemic, both prior to and after the vaccination program. The results of this seroprevalence study were important because they allowed decision makers to use estimates of susceptibility in the local population to plan resources and support public health action, including vaccination programs, during the second wave and the subsequent influenza season. Before another infectious disease emerges it would be wise to incorporate the need for seroprevalence studies into planning processes and public health emergency plans, establish biorepositories of representative sera as well as the laboratory capacity to test specimens quickly to answer such questions. This experience using multiple assays and population sources will facilitate the introduction of a provincial serosurvey in the event of widespread outbreaks, a future pandemic or other public health emergency. Results are currently being applied to the evaluation of the pandemic response and for pandemic planning.
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We would like to thank the following individuals for their support in a number of areas. For laboratory testing support: Reg Bangcaya, Angela Chiodo, Angela Garcia, Reza Jafari, Katrina Jinon, Rama Kandiah, Lily Shi, Emmanuel Ugwuegbulem and Gang Wang. For knowledge exchange and communications support: Amanda Chudak, Rashi Sharma and Helen Simeon. For IT support of the study website: Sevaan Franks, Cary Luner, Jason Percival and Jim Tom.