Abstract
BackgroundEfficient and reliable surveillance and notification systems are vital for monitoring public health and disease outbreaks. However, most surveillance and notification systems are affected by a degree of underestimation (UE) and therefore uncertainty surrounds the 'true’ incidence of disease affecting morbidity and mortality rates. Surveillance systems fail to capture cases at two distinct levels of the surveillance pyramid: from the community since not all cases seek healthcare (under-ascertainment), and at the healthcare-level, representing a failure to adequately report symptomatic cases that have sought medical advice (underreporting). There are several methods to estimate the extent of under-ascertainment and underreporting.MethodsWithin the context of the ECDC-funded Burden of Communicable Diseases in Europe (BCoDE)-project, an extensive literature review was conducted to identify studies that estimate ascertainment or reporting rates for salmonellosis and campylobacteriosis in European Union Member States (MS) plus European Free Trade Area (EFTA) countries Iceland, Norway and Switzerland and four other OECD countries (USA, Canada, Australia and Japan). Multiplication factors (MFs), a measure of the magnitude of underestimation, were taken directly from the literature or derived (where the proportion of underestimated, under-ascertained, or underreported cases was known) and compared for the two pathogens.ResultsMFs varied between and within diseases and countries, representing a need to carefully select the most appropriate MFs and methods for calculating them. The most appropriate MFs are often disease-, country-, age-, and sex-specific.ConclusionsWhen routine data are used to make decisions on resource allocation or to estimate epidemiological parameters in populations, it becomes important to understand when, where and to what extent these data represent the true picture of disease, and in some instances (such as priority setting) it is necessary to adjust for underestimation. MFs can be used to adjust notification and surveillance data to provide more realistic estimates of incidence.
Highlights
Efficient and reliable surveillance and notification systems are vital for monitoring public health and disease outbreaks
The search was restricted to articles written in English and to the years 1990–2011 since surveillance systems, reporting protocols and epidemiological patterns may have been different in the years preceding 1990, Multiplication factors (MFs) would be less appropriate for adjusting current surveillance and notification data
While age-stratified MFs are preferred since ascertainment and reporting are affected by age; stratification into age bands was only found for UA of salmonellosis (S.braenderup) in Japan in one study [48]
Summary
Efficient and reliable surveillance and notification systems are vital for monitoring public health and disease outbreaks. Most surveillance and notification systems are affected by a degree of underestimation (UE) and uncertainty surrounds the ‘true’ incidence of disease affecting morbidity and mortality rates. Efficient and reliable surveillance and notification systems are vital for monitoring public health trends and disease outbreaks. They often form the backbone of evidencebased decision-making processes, as well as infectious disease (ID) public health policies that deal with prioritisation, and the planning of intervention measures and healthcare services [1]. A major prerequisite of DALY calculations is ‘true’ incidence data but since data are often obtained from (inter)national-level routine surveillance datasets that are frequently incomplete, data must be adjusted before serving as input for computing disease burden
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