3.4 Sentinel surveillance

Sentinel surveillance methodology is often employed in resource-constraint contexts, such as in LMICs, where it is difficult to include all health facilities within a surveillance system. In such circumstances, a limited number of health facilities (or farms, or veterinary clinics or laboratories), often those that already have the capacity to undertake surveillance duties and collect detailed information, are used by the surveillance programme. The type of surveillance undertaken in the sentinel sites may be active or passive. Often incentives are provided to facilities undertaking sentinel surveillance to drive participation. A key consideration is the generalisability of findings from these sentinel sites: how well does the incidence of disease in patients at this hospital (or animals attending this clinic or reared on these farms) relate to the incidence of the disease in the rest of the population in that country?

Example: In Rwanda, in central Africa, sentinel surveillance was used successfully to characterise, for the first time, the seasonality and epidemiology of influenza in the country. In 2008, the Rwandan Ministry of Health, in collaboration with the US CDC, established an influenza sentinel surveillance system in four hospitals across the country. Hospital sites were selected to represent each of the country’s five regions and for their ability to collect influenza samples and transport them to a centralised laboratory. Any patient who met the symptom profile (outlined by the surveillance definition), such as fever, cough or sore throat, was flagged by dedicated surveillance officers. Demographic, clinical and disease epidemiology data were collected on each case, meeting the surveillance definition. Samples included swabs, which could be sent to the central laboratory for confirmation. Once submitted, the samples were processed, confirming the presence or absence of disease. The resulting data were shared via the surveillance system periodically. The system enabled an understanding of the epidemiology of influenza in Rwanda, showing the occurrence of two distinct periods of increased influenza transmission, matching the peak rainy seasons. Information such as this is crucial in helping a country build effective interventions to tackle disease spread (Nyatanyi et al., 2012).

It is important to note that a surveillance system may use methods from more than one type of surveillance. For example, using routinely collected laboratory data from a specified number of sites would be passive, laboratory-based sentinel surveillance.