Project Identifies Potential Super-Spreaders of Infection

Transmission of healthcare-acquired infections (HAI) depends mainly on contacts between patients, between healthcare workers (HCWs) and between patients and HCWs. The objective of this study by Payet, et al. was to combine contacts data and virological data for studying influenza transmission during an outbreak occurring in a hospital unit.

Face-to-face proximity between persons was collected during 10 consecutive days using electronic RFID badges. Virological data on influenza infection status were also collected. Each patient and each HCW had two nasal swabs, one at admission and one at discharge for patients, and two swabs at seven days interval for HCWs, from which laboratory confirmation of influenza infection was performed.

A total of 18,766 contacts were recorded among 37 patients and 47 HCWs. Nurses, medical doctors and patients were involved in 82 percent, 26 percent and 24 percent of all the contacts respectively. In parallel, during the 10 days, an outbreak occurred involving 15 laboratory-confirmed influenza cases diagnosed among 10 patients (attack rate 27 percent) and  five HCWs (attack rate 10 percent).

The researchers identified five (14 percent) patients and 10 (20 percent) HCWs who accumulated nearly 50 percent of all the contacts involving patients and HCWs. Among these persons with a high number of contacts, three (60 percent) patients and one (10 percent) HCW had confirmed influenza. Among those with a lower number of contacts, seven (22 percent) patients and four (11 percent) HCWs had confirmed influenza. Further statistical analyses are ongoing to assess the relationship between the number and duration of contacts and the risk of influenza transmission.

Collecting contacts data in the hospital setting and combining this information with virological data could be an interesting approach to study the transmission of HAIs. The researchers  identified patients and HCWs with a high number of contacts, who could be considered as potential super-spreaders of infections. This is key information that may help to implement prevention and control measures.

Reference:  Payet C, Barrat A, et al. Oral abstract O023 presented at ICPIC 2013: Combining electronic contacts data and virological data for studying the transmission of infections at hospital. Antimicrobial Resistance and Infection Control 2013, 2(Suppl 1):O23.