Criteria derived from simulations can be used to assess which waterborne diseases may be appropriate for identification by syndromic surveillance.36
(1) The disease should have a narrow incubation period distribution.
Incubation periods of waterborne disease agents vary widely depending on dose, host susceptibility, and other factors.
(2) The disease should have a steep epidemic curve and a long prodromal phase.
Most waterborne diseases do not have a prodromal phase and an outbreak will not necessarily have a steep epidemic curve.
(3) The disease should not have a specific disease identifying clinical feature.
Initial symptoms of most potentially waterborne diseases are non‐specific and generally include diarrhoea and other GI distress. Most of these illnesses do not have a disease identifying clinical or historical feature that allows clinicians to pinpoint the cause before performing laboratory tests.46
(4) The disease should not be included in routine diagnostic tests.
Laboratory tests are not routinely ordered for many waterborne diseases,46
and acute GI illnesses are generally under diagnosed and underreported.47,48,49
What this paper adds
To date, little attention has been paid to the possibility of using syndromic surveillance for monitoring waterborne disease incidence. This review of the benefits and shortcomings of syndromic surveillance may prove useful to public health practitioners and planners who are considering approaches to improve traditional surveillance systems.
Table 1 lists characteristics of potentially waterborne pathogens. Because many waterborne diseases lack clinically identifying features and are not part of routine testing, they may be good candidates for detection by syndromic surveillance, based on the four criteria listed above. However, many of the diseases that fit these criteria, while good candidates for syndromic surveillance, are often commonly occurring and nor necessarily of high public health importance.
Table 1Characteristics of potentially waterborne disease agents
Waterborne disease surveillance in the San Francisco Bay Area
In the San Francisco Bay Area four counties receive water from a common water utility. With the exception of a multi‐county cryptosporidiosis surveillance project, surveillance for potentially waterborne disease in the San Francisco Bay Area is conducted by each county separately. There is no formal, timely coordination of waterborne disease surveillance across county lines. A system with multi‐jurisdictional disease monitoring capabilities could provide public health benefit by permitting early detection of a multi‐county waterborne outbreak. Surveillance data captured from multiple jurisdictions and interpreted centrally may lead to earlier outbreak detection than data gathered and interpreted by staff in separate counties who may not be aware of disease incidence in neighbouring jurisdictions.
Syndromic surveillance data sources may potentially provide cross‐jurisdictional data, information about the geographical scope of an outbreak once one was identified, and additional reassurance that an outbreak was not occurring. However, the practical utility of syndromic data sources is uncertain; their outbreak detection benefits are currently theoretical and will remain so until accurate electronic capture of data and signal detection algorithms are refined or data sensitivity increases. The benefits of a regional waterborne disease surveillance system must be weighed against the resources required to set up such a system and the true risk of a waterborne disease outbreak in the San Francisco Bay Area. Based on the absence of any known waterborne outbreaks in the history of the water utility, extensive watershed protection measures, and a protected water source located in a national park it would seem that the risk of a waterborne disease outbreak occurring in the San Francisco Bay Area is quite small.
This review will help policy makers weigh the costs and benefits of implementing a syndromic surveillance system and will clarify the drawbacks and advantages of potential data sources.
Potential waterborne disease syndromic surveillance data sources
Table 2 lists the potential waterborne disease syndromic surveillance data sources along with indicators of data quality and utility. Potential data sources in the table are divided into data that are currently available and accessible in electronic format in the San Francisco Bay Area and data that are not currently automated or electronically available but could be useful once they became automated and electronic.
Table 2Potential syndromic surveillance data sources
Compared with other options, OTC surveillance for waterborne disease is currently the most feasible source of syndromic surveillance data available in the San Francisco metropolitan area because of the relative ease of implementing an existing, nationally funded system. Nursing home surveillance entails large inputs in terms of health department and on‐site staff and fiscal resources for specimen testing, data monitoring, and signal investigation. Water utility complaint, nurse call line, and school and worker absenteeism logs are currently not compiled electronically in a central location; setting up a system to electronically capture these data would entail considerable commitments of will and resources from the department of public health, other city agencies, and private and public partnerships with water utilities, insurance providers, hospitals and clinics, and large employers in the San Francisco Bay Area. Mechanisms for data storage, sharing, and retrieval would need to be established for each partnership. Finally and most importantly, dedicated public health staff who would compile, manage, and analyse syndromic data on a regular basis, and respond to syndromic surveillance signals would be needed. Signal verification and response activities may include: (1) determining data import and aberration detection algorithm problems that may lead to erroneous signals (for example, duplicate data, batch transfers from certain institutions, miscoding of information at the point of entry, text‐string search algorithms that are too specific or not specific enough, etc); (2) verifying the validity of the signal by looking for the presence of signals in other data sources; (3) if the signal is deemed to be composed of possible true cases, hospital logs and charts may need to be manually reviewed by hospital or public health department staff and a line list compiled for clinical and/or laboratory based case verification; (4) traditional outbreak investigation activities and application of interventions. Timeliness provided by a syndromic surveillance system can only be useful if all of the above functions are supported by and integrated into the activities of the local health department on a sustained basis.
It is possible that outbreaks of cryptosporidiosis, cyclosporiasis, legionellosis, hepatitis A, and others may be detected through monitoring of OTC sales or that a suspected outbreak may be confirmed or better characterised through the use of these data. If OTC surveillance is to be used primarily as a back up data source to traditional surveillance, staff time for checking the web based interface would not exceed 15 minutes per day. Signal investigation would require additional resources. While the usefulness of OTC monitoring for waterborne diseases is only theoretical, given the availability of multi‐county data and the low amount of staff time and effort needed to monitor the data, utilisation and prospective evaluation of these data may be recommended for two purposes: (1) reassurance of the absence of a waterborne disease outbreak and (2) establishing baseline familiarity that may prove helpful in the event of a waterborne disease outbreak. OTC data need to be correlated with known outbreaks in the geographical area where surveillance is occurring to clarify the validity and representativeness of these data before they can be used for prospective outbreak detection.