[The real-time pharmacy surveillance and its estimation of patients in 2009 influenza A (H1N1)]

Infection Control in Nursery Schools and Schools Using a School Absenteeism Surveillance System

Infection control in nursery schools and schools is important for community health and the health of children. In Japan, caregivers of children or students usually report the absence due to illness to their attending nurseries or schools, including symptoms and diagnosed diseases. The (Nursery) School Absenteeism Surveillance System, (N)SASSy, covers about 60% of schools and 40% of nurseries in Japan. In this paper, we evaluated the benefits of (N)SASSy as an infection control measure by a public health center. Mito Public Health Center (MPHC) covers 58 nurseries and 186 schools, as of May 2015, and called the nurseries and/or schools to confirm the situation, in case of aberration detected through (N)SASSy. The outcome was defined as the proportion of cluster avoidance by advice from MPHC. A cluster was identified, when the number of patients at the same facility with the same symptom or diagnosed disease was greater than ten during the prior seven days. During the study period (April 2015-March 2016), MPHC advised 85 times, and clusters were avoided 82 times (96.5%). The proportion of cluster avoidance was 100% for fever, enterohemorrhagic Escherichia coli infection, respiratory syncytial virus infection, or streptococcal pharyngitis infection. The proportion of cluster avoidance for diarrhea, vomiting or gastroenteritis infection, mumps, hand-foot-mouth disease (HFMD), and influenza was 78.8, 50.0, 20.0, and 6.7%, respectively. In conclusion, advice from a public health center given by phone based on information from (N)SASSy will be helpful for reducing the number of clusters of infectious diseases, except for HFMD and influenza.

Enhanced Surveillance for the Sports Festival in Tokyo 2013: Preparation for the Tokyo 2020 Olympic and Paralympic Games

Enhanced surveillance was conducted during the Sports Festival in Tokyo 2013 (September 28-October 14, 2013) for early detection of outbreaks of infectious diseases and other health emergencies. Through this enhanced surveillance, 15 cases were found that required additional gathering of information outside the routine process of creating/evaluating the Daily Report. However, none of these was assessed as critical. Through the enhanced surveillance, we structured a framework that allows for earlier response when detecting aberrations. It includes the role of the Tokyo Metropolitan Government in communications and contacts with relevant parties such as public health centers, as well as in monitoring of surveillance data. However, some issues need to be further considered toward the Tokyo 2020 Olympic and Paralympic Games, such as establishing the criteria for additional response steps, increasing the number of participating bodies in syndromic surveillance, and strengthening of cooperation with related departments, including those for crisis management assuming potential biological/chemical terrorism.

Real-time prescription surveillance and its application to monitoring seasonal influenza activity in Japan

Background

Real-time surveillance is fundamental for effective control of disease outbreaks, but the official sentinel surveillance in Japan collects information related to disease activity only weekly and updates it with a 1-week time lag.

Objective

To report on a prescription surveillance system using electronic records related to prescription drugs that was started in 2008 in Japan, and to evaluate the surveillance system for monitoring influenza activity during the 2009–2010 and 2010–2011 influenza seasons.

Methods

We developed an automatic surveillance system using electronic records of prescription drug purchases collected from 5275 pharmacies through the application service provider’s medical claims service. We then applied the system to monitoring influenza activity during the 2009–2010 and 2010–2011 influenza seasons. The surveillance system collected information related to drugs and patients directly and automatically from the electronic prescription record system, and estimated the number of influenza cases based on the number of prescriptions of anti-influenza virus medication. Then it shared the information related to influenza activity through the Internet with the public on a daily basis.

Results

During the 2009–2010 influenza season, the number of influenza patients estimated by the prescription surveillance system between the 28th week of 2009 and the 12th week of 2010 was 9,234,289. In the 2010–2011 influenza season, the number of influenza patients between the 36th week of 2010 and the 12th week of 2011 was 7,153,437. The estimated number of influenza cases was highly correlated with that predicted by the official sentinel surveillance (r = .992, P < .001 for 2009–2010; r = .972, P < .001 for 2010–2011), indicating that the prescription surveillance system produced a good approximation of activity patterns.

Conclusions

Our prescription surveillance system presents great potential for monitoring influenza activity and for providing early detection of infectious disease outbreaks.