Detection of varying influenza circulation within England in 2012/13: informing antiviral prescription and public health response

Burden and Seasonality of Viral Acute Respiratory Tract Infections among Outpatients in Southern Sri Lanka

In tropical and subtropical settings, the epidemiology of viral acute respiratory tract infections varies widely between countries. We determined the etiology, seasonality, and clinical presentation of viral acute respiratory tract infections among outpatients in southern Sri Lanka. From March 2013 to January 2015, we enrolled outpatients presenting with influenza-like illness (ILI). Nasal/nasopharyngeal samples were tested in duplicate using antigen-based rapid influenza testing and multiplex polymerase chain reaction (PCR) for respiratory viruses. Monthly proportion positive was calculated for each virus. Bivariable and multivariable logistic regression were used to identify associations between sociodemographic/clinical information and viral detection. Of 571 subjects, most (470, 82.3%) were ≥ 5 years of age and 53.1% were male. A respiratory virus was detected by PCR in 63.6% (N = 363). Common viral etiologies included influenza (223, 39%), human enterovirus/rhinovirus (HEV/HRV, 14.5%), respiratory syncytial virus (RSV, 4.2%), and human metapneumovirus (hMPV, 3.9%). Both ILI and influenza showed clear seasonal variation, with peaks from March to June each year. RSV and hMPV activity peaked from May to July, whereas HEV/HRV was seen year-round. Patients with respiratory viruses detected were more likely to report pain with breathing (odds ratio [OR] = 2.60, P = 0.003), anorexia (OR = 2.29, P < 0.001), and fatigue (OR = 2.00, P = 0.002) compared with patients with no respiratory viruses detected. ILI showed clear seasonal variation in southern Sri Lanka, with most activity during March to June; peak activity was largely due to influenza. Targeted infection prevention activities such as influenza vaccination in January-February may have a large public health impact in this region.

Illness absenteeism rates in primary and secondary schools in 2013–2014 in England: was there any impact of vaccinating children of primary-school age against influenza?

A phased introduction of routine influenza vaccination of healthy children was recommended in the UK in 2012, with the aim of protecting both vaccinated children and the wider population through reducing transmission. In the first year of the programme in 2013–2014, 4- to 11-year-olds were targeted in pilot areas across England. This study assesses if this was associated with school absenteeism, an important societal burden of influenza. During the spring 2014 term when influenza predominantly circulated, the proportion of absence sessions due to illness was compared between vaccination pilot and non-pilot areas for primary schools (to measure overall impact) and secondary schools (to measure indirect impact). A linear multilevel regression model was applied, adjusting for clustering within schools and potential school-level confounders, including deprivation, past absenteeism, and ethnicity. Low levels of influenza activity were reported in the community in 2013–2014. Primary schools in pilot areas had a significantly adjusted decrease in illness absenteeism of 0·05% relative to non-pilot schools; equivalent to an average of 4 days per school. In secondary schools, there was no significant indirect impact of being located in a pilot area on illness absenteeism. These insights can be used in conjunction with routine healthcare surveillance data to evaluate the full benefits of such a programme.

Success Factors of European Syndromic Surveillance Systems: A Worked Example of Applying Qualitative Comparative Analysis

INTRODUCTION

Syndromic surveillance aims at augmenting traditional public health surveillance with timely information. To gain a head start, it mainly analyses existing data such as from web searches or patient records. Despite the setup of many syndromic surveillance systems, there is still much doubt about the benefit of the approach. There are diverse interactions between performance indicators such as timeliness and various system characteristics. This makes the performance assessment of syndromic surveillance systems a complex endeavour. We assessed if the comparison of several syndromic surveillance systems through Qualitative Comparative Analysis helps to evaluate performance and identify key success factors.

MATERIALS AND METHODS

We compiled case-based, mixed data on performance and characteristics of 19 syndromic surveillance systems in Europe from scientific and grey literature and from site visits. We identified success factors by applying crisp-set Qualitative Comparative Analysis. We focused on two main areas of syndromic surveillance application: seasonal influenza surveillance and situational awareness during different types of potentially health threatening events.

RESULTS

We found that syndromic surveillance systems might detect the onset or peak of seasonal influenza earlier if they analyse non-clinical data sources. Timely situational awareness during different types of events is supported by an automated syndromic surveillance system capable of analysing multiple syndromes. To our surprise, the analysis of multiple data sources was no key success factor for situational awareness.

CONCLUSIONS

We suggest to consider these key success factors when designing or further developing syndromic surveillance systems. Qualitative Comparative Analysis helped interpreting complex, mixed data on small-N cases and resulted in concrete and practically relevant findings.