The Sentiworld project: global mapping of sentinel surveillance networks in general practice

BACKGROUND

Sentinel networks composed of general practitioners (GPs) represent a powerful tool for epidemiologic surveillance and ad-hoc studies. Globalization necesitates greater international cooperation among sentinel networks. The aim of this study was to inventory GP sentinel networks involved in epidemiological surveillance on a global scale.

METHODS

GP sentinel surveillance networks were inventoried globally between July 2016 and December 2019. Each identified network was required to fill out an electronic descriptive survey for inclusion.

RESULTS

A total of 148 networks were identified as potential surveillance networks in general practice and were contacted. Among them, 48 were included in the study. Geographically, 33 networks (68.8%) were located in Europe and 38 (79.2%) had national coverage. The number of GPs registered in these networks represented between 0.1 and 100% of the total number of GPs in the network's country or region, with a median of 2.5%. All networks were involved in continuous epidemiologic surveillance and 47 (97.9%) monitored influenza-like illness. Data collection methods were paper-based forms (n = 26, 55.3%), electronic forms on a dedicated website (n = 18, 38.3%), electronic forms on a dedicated software program (n = 14, 29.8%), and direct extraction from electronic medical records (n = 14, 29.8%). Along with this study, a website has been created to share all data collected.

CONCLUSIONS

This study represents the first global geographic mapping of GP sentinel surveillance networks. By sharing this information, collaboration between networks will be easier, which can strengthen the quality of international epidemiologic surveillance. In the face of crises like that of COVID-19, this is more imperative than ever before.

Parental socioeconomic and psychological determinants of the 2009 pandemic influenza A(H1N1) vaccine uptake in children

BACKGROUND

Before COVID-19, the previous pandemic was caused by influenza A(H1N1)pdm09 virus in 2009. Identification of factors behind parental decisions to have their child vaccinated against pandemic influenza could be helpful in planning of other pandemic vaccination programmes. We investigated the association of parental socioeconomic and psychosocial factors with uptake of the pandemic influenza vaccine in children in 2009-2010.

METHODS

This study was conducted within a prospective birth-cohort study (STEPS Study), where children born in 2008-2010 are followed from pregnancy to adulthood. Demographic and socioeconomic factors of parents were collected through questionnaires and vaccination data from electronic registers. Before and after the birth of the child, the mother's and father's individual and relational psychosocial well-being, i.e. depressive symptoms, dissatisfaction with the relationship, experienced social and emotional loneliness, and maternal anxiety during pregnancy, were measured by validated questionnaires (BDI-II, RDAS, PRAQ, and UCLA).

RESULTS

Of 1020 children aged 6-20 months at the beginning of pandemic influenza vaccinations, 820 (80%) received and 200 (20%) did not receive the vaccine against influenza A(H1N1)pdm09. All measures of parents' psychosocial well-being were similar between vaccinated and non-vaccinated children. Children of younger mothers had a higher risk of not receiving the influenza A(H1N1)pdm09 vaccine than children of older mothers (OR 2.59, 95% CI 1.52-4.43, for mothers < 27.7 years compared to ≥ 33.6 years of age). Children of mothers with lower educational level had an increased risk of not receiving the vaccine (OR 1.46, 95% CI 1.00-2.14).

CONCLUSIONS

Mother's younger age and lower education level were associated with an increased risk for the child not to receive the 2009 pandemic influenza vaccine, but individual or relational psychosocial well-being of parents was not associated with children's vaccination. Our findings suggest that young and poorly educated mothers should receive targeted support in order to promote children's vaccinations during a pandemic.

Seasonal influenza vaccines induced high levels of neutralizing cross-reactive antibody responses against different genetic group influenza A(H1N1)pdm09 viruses

Influenza A(H1N1)pdm09 viruses have been circulating throughout the world since the 2009 pandemic. A/California/07/2009 (H1N1) virus was included in seasonal influenza vaccines for seven years altogether, providing a great opportunity to analyse vaccine-induced immunity in relation to the postpandemic evolution of the A(H1N1)pdm09 virus. Serum antibodies against various epidemic strains of influenza A(H1N1)pdm09 viruses were measured among health care workers (HCWs) by haemagglutination inhibition and microneutralization tests before and after 2010 and 2012 seasonal influenza vaccinations. We detected high responses of vaccine-induced neutralizing antibodies to six distinct genetic groups. Our results indicate antigenic similarity between vaccine and circulating A(H1N1)pdm09 strains, and substantial vaccine-induced immunity against circulating epidemic viruses.

Pandemic vaccination strategies and influenza severe outcomes during the influenza A(H1N1)pdm09 pandemic and the post-pandemic influenza season: the Nordic experience

During the 2009/10 influenza A(H1N1)pdm09 pandemic, the five Nordic countries adopted different approaches to pandemic vaccination. We compared pandemic vaccination strategies and severe influenza outcomes, in seasons 2009/10 and 2010/11 in these countries with similar influenza surveillance systems. We calculated the cumulative pandemic vaccination coverage in 2009/10 and cumulative incidence rates of laboratory confirmed A(H1N1)pdm09 infections, intensive care unit (ICU) admissions and deaths in 2009/10 and 2010/11. We estimated incidence risk ratios (IRR) in a Poisson regression model to compare those indicators between Denmark and the other countries. The vaccination coverage was lower in Denmark (6.1%) compared with Finland (48.2%), Iceland (44.1%), Norway (41.3%) and Sweden (60.0%). In 2009/10 Denmark had a similar cumulative incidence of A(H1N1)pdm09 ICU admissions and deaths compared with the other countries. In 2010/11 Denmark had a significantly higher cumulative incidence of A(H1N1)pdm09 ICU admissions (IRR: 2.4; 95% confidence interval (CI): 1.9-3.0) and deaths (IRR: 8.3; 95% CI: 5.1-13.5). Compared with Denmark, the other countries had higher pandemic vaccination coverage and experienced less A(H1N1)pdm09-related severe outcomes in 2010/11. Pandemic vaccination may have had an impact on severe influenza outcomes in the post-pandemic season. Surveillance of severe outcomes may be used to compare the impact of influenza between seasons and support different vaccination strategies.

Revealing the True Incidence of Pandemic A(H1N1)pdm09 Influenza in Finland during the First Two Seasons - An Analysis Based on a Dynamic Transmission Model

The threat of the new pandemic influenza A(H1N1)pdm09 imposed a heavy burden on the public health system in Finland in 2009-2010. An extensive vaccination campaign was set up in the middle of the first pandemic season. However, the true number of infected individuals remains uncertain as the surveillance missed a large portion of mild infections. We constructed a transmission model to simulate the spread of influenza in the Finnish population. We used the model to analyse the two first years (2009-2011) of A(H1N1)pdm09 in Finland. Using data from the national surveillance of influenza and data on close person-to-person (social) contacts in the population, we estimated that 6% (90% credible interval 5.1 – 6.7%) of the population was infected with A(H1N1)pdm09 in the first pandemic season (2009/2010) and an additional 3% (2.5 – 3.5%) in the second season (2010/2011). Vaccination had a substantial impact in mitigating the second season. The dynamic approach allowed us to discover how the proportion of detected cases changed over the course of the epidemic. The role of time-varying reproduction number, capturing the effects of weather and changes in behaviour, was important in shaping the epidemic.

In 2009, the threat of the new pandemic influenza A(H1N1)pdm09 (referenced in media as ‘swine flu’) created a heavy burden to the public health systems wordwide. In Finland, an extensive vaccination campaign was set up in the middle of the first pandemic season 2009/2010. However, the true number of infected individuals remains uncertain as the surveillance missed a large portion of mild infections. We built a probabilistic model of influenza transmission that accounts for observation bias and the possible impact of the changing weather and population behaviour. We used the model to simulate the spread of influenza in Finland during the two first years (2009-2011) of A(H1N1)pdm09 in Finland. Using data from the national surveillance of influenza and data on social contacts in the population, we estimated that 9% of the population was infected with A(H1N1)pdm09 during the studied period. Vaccination had a substantial impact in mitigating the second season.

Application of Probabilistic Multiple-Bias Analyses to a Cohort- and a Case-Control Study on the Association between Pandemrix™ and Narcolepsy

Background

An increase in narcolepsy cases was observed in Finland and Sweden towards the end of the 2009 H1N1 influenza pandemic. Preliminary observational studies suggested a temporal link with the pandemic influenza vaccine Pandemrix™, leading to a number of additional studies across Europe. Given the public health urgency, these studies used readily available retrospective data from various sources. The potential for bias in such settings was generally acknowledged. Although generally advocated by key opinion leaders and international health authorities, no systematic quantitative assessment of the potential joint impact of biases was undertaken in any of these studies.

Methods

We applied bias-level multiple-bias analyses to two of the published narcolepsy studies: a pediatric cohort study from Finland and a case-control study from France. In particular, we developed Monte Carlo simulation models to evaluate a potential cascade of biases, including confounding by age, by indication and by natural H1N1 infection, selection bias, disease- and exposure misclassification. All bias parameters were evidence-based to the extent possible.

Results

Given the assumptions used for confounding, selection bias and misclassification, the Finnish rate ratio of 13.78 (95% CI: 5.72–28.11) reduced to a median value of 6.06 (2.5^th- 97.5^th percentile: 2.49–15.1) and the French odds ratio of 5.43 (95% CI: 2.6–10.08) to 1.85 (2.5^th—97.5^th percentile: 0.85–4.08).

Conclusion

We illustrate multiple-bias analyses using two studies on the Pandemrix^™-narcolepsy association and advocate their use to better understand the robustness of study findings. Based on our multiple-bias models, the observed Pandemrix^™-narcolepsy association consistently persists in the Finnish study. For the French study, the results of our multiple-bias models were inconclusive.

Forecasts of health care utilization related to pandemic A(H1N1)2009 influenza in the Nord-Pas-de-Calais region, France

OBJECTIVES

To describe and evaluate the forecasts of the load that pandemic A(H1N1)2009 influenza would have on the general practitioners (GP) and hospital care systems, especially during its peak, in the Nord-Pas-de-Calais (NPDC) region, France.

STUDY DESIGN

Modelling study.

METHODS

The epidemic curve was modelled using an assumption of normal distribution of cases. The values for the forecast parameters were estimated from a literature review of observed data from the Southern hemisphere and French Overseas Territories, where the pandemic had already occurred. Two scenarios were considered, one realistic, the other pessimistic, enabling the authors to evaluate the 'reasonable worst case'. Forecasts were then assessed by comparing them with observed data in the NPDC region--of 4 million people.

RESULTS

The realistic scenarios forecasts estimated 300,000 cases, 1500 hospitalizations, 225 intensive care units (ICU) admissions for the pandemic wave; 115 hospital beds and 45 ICU beds would be required per day during the peak. The pessimistic scenario's forecasts were 2-3 times higher than the realistic scenario's forecasts. Observed data were: 235,000 cases, 1585 hospitalizations, 58 ICU admissions; and a maximum of 11.6 ICU beds per day.

CONCLUSIONS

The realistic scenario correctly estimated the temporal distribution of GP and hospitalized cases but overestimated the number of cases admitted to ICU. Obtaining more robust data for parameters estimation--particularly the rate of ICU admission among the population that the authors recommend to use--may provide better forecasts.

Meeting the International Health Regulations (2005) surveillance core capacity requirements at the subnational level in Europe: the added value of syndromic surveillance

Background

The revised World Health Organization’s International Health Regulations (2005) request a timely and all-hazard approach towards surveillance, especially at the subnational level. We discuss three questions of syndromic surveillance application in the European context for assessing public health emergencies of international concern: (i) can syndromic surveillance support countries, especially the subnational level, to meet the International Health Regulations (2005) core surveillance capacity requirements, (ii) are European syndromic surveillance systems comparable to enable cross-border surveillance, and (iii) at which administrative level should syndromic surveillance best be applied?

Discussion

Despite the ongoing criticism on the usefulness of syndromic surveillance which is related to its clinically nonspecific output, we demonstrate that it was a suitable supplement for timely assessment of the impact of three different public health emergencies affecting Europe. Subnational syndromic surveillance analysis in some cases proved to be of advantage for detecting an event earlier compared to national level analysis. However, in many cases, syndromic surveillance did not detect local events with only a small number of cases.

The European Commission envisions comparability of surveillance output to enable cross-border surveillance. Evaluated against European infectious disease case definitions, syndromic surveillance can contribute to identify cases that might fulfil the clinical case definition but the approach is too unspecific to comply to complete clinical definitions. Syndromic surveillance results still seem feasible for comparable cross-border surveillance as similarly defined syndromes are analysed.

We suggest a new model of implementing syndromic surveillance at the subnational level. In this model, syndromic surveillance systems are fine-tuned to their local context and integrated into the existing subnational surveillance and reporting structure. By enhancing population coverage, events covering several jurisdictions can be identified at higher levels. However, the setup of decentralised and locally adjusted syndromic surveillance systems is more complex compared to the setup of one national or local system.

Summary

We conclude that syndromic surveillance if implemented with large population coverage at the subnational level can help detect and assess the local and regional effect of different types of public health emergencies in a timely manner as required by the International Health Regulations (2005).

Effectiveness of pandemic and seasonal influenza vaccines in preventing laboratory-confirmed influenza in adults: a clinical cohort study during epidemic seasons 2009-2010 and 2010-2011 in Finland

Background

One dose of pandemic influenza vaccine Pandemrix (GlaxoSmithKline) was offered to the entire population of Finland in 2009–10. We conducted a prospective clinical cohort study to determine the vaccine effectiveness in preventing febrile laboratory-confirmed influenza infection during the influenza season 2009–10 and continued the study in 2010–11.

Methods

In total, 3,518 community dwelling adults aged 18–75 years living in Tampere city were enrolled. The participants were not assigned to any vaccination regimen, but they could participate in the study regardless of their vaccination status or intention to be vaccinated with the pandemic or seasonal influenza vaccine. They were asked to report if they received Pandemrix in 2009–10 and/or trivalent influenza vaccine in 2010–11. Vaccinations were verified from medical records. The participants were instructed to report all acute symptoms of respiratory tract infection with fever (at least 38°C) and pneumonias to the study staff. Nasal and oral swabs were obtained within 5–7 days after symptom onset and influenza-specific RNA was identified by reverse transcription polymerase chain reaction.

Results

In 2009–10, the estimated vaccine effectiveness was 81% (95%CI 30–97). However, the vaccine effectiveness could not be estimated reliably, because only persons in prioritized groups were vaccinated before/during the first pandemic wave and many participants were enrolled when they already had the symptoms of A(H1N1)pdm09 influenza infection. In 2010–11, 2,276 participants continued the follow-up. The vaccine effectiveness, adjusted for potential confounding factors was 81% (95%CI 41–96) for Pandemrix only and 88% (95%CI 63–97) for either Pandemrix or trivalent influenza vaccine 2010–11 or both, respectively.

Conclusion

Vaccination with an AS03-adjuvanted pandemic vaccine in 2009–10 was still effective in preventing A(H1N1)pdm09 influenza during the following epidemic season in 2010–11.

Trial Registration

ClinicalTrials.gov NCT01024725. NCT01206114.

Estimating the burden of A(H1N1)pdm09 influenza in Finland during two seasons

In Finland, the pandemic influenza virus A(H1N1)pdm09 was the dominant influenza strain during the pandemic season in 2009/2010 and presented alongside other influenza types during the 2010/2011 season. The true number of infected individuals is unknown, as surveillance missed a large portion of mild infections. We applied Bayesian evidence synthesis, combining available data from the national infectious disease registry with an ascertainment model and prior information on A(H1N1)pdm09 influenza and the surveillance system, to estimate the total incidence and hospitalization rate of A(H1N1)pdm09 infection. The estimated numbers of A(H1N1)pdm09 infections in Finland were 211 000 (4% of the population) in the 2009/2010 pandemic season and 53 000 (1% of the population) during the 2010/2011 season. Altogether, 1·1% of infected individuals were hospitalized. Only 1 infection per 25 was ascertained.

A(H1N1)pdm09 hemagglutinin D222G and D222N variants are frequently harbored by patients requiring extracorporeal membrane oxygenation and advanced respiratory assistance for severe A(H1N1)pdm09 infection

Background

In patients with A(H1N1)pdm09 infection, severe lung involvement requiring admission to intensive care units (ICU) has been reported. Mutations at the hemagglutinin (HA) receptor binding site (RBS) have been associated with increased virulence and disease severity, representing a potential marker of critical illness.

Objectives

To assess the contribution of HA‐RBS variability in critically ill patients, A(H1N1)pdm09 virus from adult patients with severe infection admitted to ICU for extracorporeal membrane oxygenation support (ECMO) during influenza season 2009–2011 in Piemonte (4·2 million inhabitants), northwestern Italy, was studied.

Patients and methods

We retrospectively analyzed HA‐RBS polymorphisms in ICU patients and compared with those from randomly selected inpatients with mild A(H1N1)pdm09 disease and outpatients with influenza from the local surveillance program.

Results

By HA‐RBS direct sequencing of respiratory specimens, D222G and D222N viral variants were identified in a higher proportion in ICU patients (n = 8/24, 33·3%) than in patients with mild disease (n = 2/34, 6%) or in outpatients (n = 0/44) (Fisher's exact test P < 0·0001; OR 38·5; CI 95% 4·494–329·9). Eleven ICU patients died (42%), three of them carrying the D222G variant, which was associated with RBS mutation S183P in two. D222G and D222N mutants were identified in upper and lower respiratory samples.

Conclusions

A(H1N1)pdm09 HA substitutions D222G and D222N were harbored in a significantly higher proportion by patients with acute respiratory distress for A(H1N1)pdm09 severe infection requiring ICU admission and ECMO. These data emphasize the importance of monitoring viral evolution for understanding virus–host adaptation aimed at the surveillance of strain circulation and the study of viral correlates of disease severity.

Antibody responses against influenza A(H1N1)pdm09 virus after sequential vaccination with pandemic and seasonal influenza vaccines in Finnish healthcare professionals

Background  Influenza A(H1N1)pdm09 virus has been circulating in human population for three epidemic seasons. During this time, monovalent pandemic and trivalent seasonal influenza vaccination against this virus have been offered to Finnish healthcare professionals. It is, however, unclear how well vaccine‐induced antibodies recognize different strains of influenza A(H1N1)pdm09 circulating in the population and whether the booster vaccination with seasonal influenza vaccine would broaden the antibody cross‐reactivity.

Objectives  Influenza vaccine‐induced humoral immunity against several isolates of influenza A(H1N1)pdm09 virus was analyzed in healthcare professionals. Age‐dependent responses were also analyzed.

Methods  Influenza viruses were selected to represent viruses that circulated in Finland during two consecutive influenza epidemic seasons 2009–2010 and 2010–2011. Serum samples from vaccinated volunteers, age 20–64 years, were collected before and after vaccination with AS03‐adjuvanted pandemic and non‐adjuvanted trivalent seasonal influenza vaccine that was given 1 year later.

Results  Single dose of pandemic vaccine induced a good albeit variable antibody response. On day 21 after vaccination, depending on the virus strain, 14–75% of vaccinated had reached antibody titers (≥1:40) considered seroprotective. The booster vaccination 1 year later with a seasonal vaccine elevated the seroprotection rate to 57–98%. After primary immunization, younger individuals (20–48 years) had significantly higher antibody titers against all tested viruses than older persons (49–64 years) but this difference disappeared after the seasonal booster vaccination.

Conclusions  Even a few amino acid changes in influenza A HA may compromise the vaccine‐induced antibody recognition. Older adults (49 years and older) may benefit more from repeated influenza vaccinations.