Several watershed protection programs target threats to the drinking water-consuming public of NYC, particularly from waterborne microbial pathogens. As discussed in Chapter 3, to maintain its filtration avoidance determination the New York City Department of Environmental Protection (NYC DEP) must ensure that there are low levels of fecal bacteria in the source water and low levels of total coliform bacteria in the distribution system. Along with enteric viruses, the protozoan pathogens Giardia and Cryptosporidium must be inactivated by disinfection. Finally, the drinking water cannot be a source of waterborne disease outbreaks. This chapter considers the three watershed protection programs that aim to accomplish these goals: the Waterborne Disease Risk Assessment Program, microbial monitoring in the Catskill/Delaware system, and the Waterfowl Management Program.
Waterborne disease surveillance activities in the United States are tracked via the Centers for Disease Control and Prevention’s (CDC;s) Waterborne Disease and Outbreak Surveillance System,1 which gathers data on outbreaks caused by drinking water, recreational water, and other environmental waters. This system, initiated in 1971, is a partnership between the CDC, the Council of Territorial and State Epidemiologists, and the U.S. Environmental Protection Agency (EPA). Although there are many possible etiologic agents (causes) of waterborne disease, the waterborne protozoa Giardia and Cryptosporidium have been a major focus of the Surface Water Treatment Rule (SWTR), and consequently of drinking water supplies, for the last 30 years. These protozoa can cause gastrointestinal illness (e.g., diarrhea and vomiting) and other health risks when ingested in drinking water. Both organisms are of particular concern in unfiltered water supplies because they form cysts or oocysts with varying degrees of resistance to chlorine disinfection. Giardia cysts are relatively resistant to chlorine (Jarroll et al., 1981), while Cryptosporidium oocysts are totally resistant to chlorine (Faver, 1995; Barbee et al., 1999). It is these organisms, and their associated infections (giardiasis and cryptosporidiosis), that form the basis of waterborne disease surveillance programs of large unfiltered water supplies.
Figure 11-1 shows how the etiologic agent of reported waterborne disease outbreaks has shifted in the past 35 years, demonstrating the continued important role of the parasitic protozoa. In an analysis of waterborne disease outbreaks associated with drinking water in the United States from 1971 to 2006, parasites were found to be responsible for the largest proportion of all outbreaks (18 percent) identified during that time period (Craun et al., 2010). Despite this continued role, the relative role of protozoan parasites in reported waterborne disease outbreaks has decreased, as seen in Figure 11-1 and discussed in Craun (2012). Craun (2012)
also identified a shift in the type of water system deficiency associated with waterborne disease outbreaks, with a decrease in inadequate water treatment (which might account for an outbreak caused by fecal pathogens) and an increase in deficiencies in premise plumbing and distribution systems that may be more likely to be associated with Legionella. These etiologic shifts from the 1970s to the modern era likely reflect successful efforts mandated by the Safe Drinking Water Act of 1974 to control fecal and enteric bacterial pathogens and parasitic protozoa. Nonetheless, because the focus of the Filtration Avoidance Determination (FAD) is to ensure that ingested drinking water is not responsible for outbreaks of protozoan parasites, the FAD encompasses Escherichia coli, Giardia, Cryptosporidium, and viruses but not Legionella. Given its increasing and leading role in waterborne disease outbreaks, Legionella was comprehensively reviewed in NASEM (2020), which showed that the reported cases in the U.S. are likely to be ten times lower than the actual number of legionellosis cases. This gross underestimate is typical of reported waterborne diseases, including giardiasis and cryptosporidiosis, because the disease surveillance methods are passive and outbreaks are often not investigated in sufficient detail (Craun et al., 2006). Few studies have been performed to assess the sensitivity of surveillance methods to detect unreported outbreaks (Blackburne et al., 2004).
NYC Waterborne Disease Risk Assessment Program Description
The Waterborne Disease Risk Assessment Program (WDRAP) is a joint agency program supported by the New York City Department of Environmental Protection (NYC DEP) and the NYC Department of Health and Mental Hygiene (DOHMH) and is a requirement of the FAD. The WDRAP started in 1993 when the initial Memorandum of Agreement between NYC DEP and DOHMH was signed. The interagency agreement was recently updated and signed again in 2017 with continuation until 2022 (NYC DOHMH and NYC DEP, 2018). As a component of the 2017 FAD and to comply with the SWTR, “the City must continue to demonstrate that water consumers served by the NYC water supply are adequately protected against waterborne disease. In particular, the City’s water must not be identified as a source of outbreaks of giardiasis or cryptosporidiosis.” The overall goal of the WDRAP is to demonstrate the safety of the city’s water supply via two methods: disease surveillance and outbreak detection.
The program funds five staff at the DOHMH and one staff person dedicated to the program at NYC DEP. There are also ancillary costs for supplies at DOHMH. The total cost per year for the program is $774,490 ($754,490 personnel costs including fringe and $20,000 supplies, the latter of which is the value found in Table 1-1 because that table does not include staff time). There are two designated coordinators, one for each department, and an assistant coordinator. Annual reports are issued jointly and supported by both NYC DEP and DOHMH. Since 1997, annual reports have been made available on the NYC WDRAP website.2
Disease Surveillance Activities
Infectious disease surveillance activities can take two forms: passive and active. Passive surveillance systems rely on reports of diagnostic test results by healthcare providers and can suffer from incomplete data and large variability in reporting. Active surveillance systems involve health agency follow-up with healthcare providers and are more complete than passive surveillance systems. Since the implementation of electronic laboratory reporting systems, both passive and active disease surveillance data can be gathered more rapidly.
Disease surveillance relying on clinical laboratory systems can be subject to a number of challenges or limitations. The largest limitation is the loss of information during disease surveillance. In particular, case detection not only relies on the infected individual experiencing symptoms and seeking care but on the appropriate referral for laboratory testing. In a survey of more than 400 clinical laboratories in the United States in 2000, 89 percent did not perform a parasite test on a patient’s stool unless it was specifically requested by a physician (Jones et al., 2004). An additional challenge faced with surveillance is the time lag associated with the incubation time of the etiologic agent. For cryptosporidiosis, the incubation period is seven days, on average, and can be as long as two weeks. There can be additional delays in seeking medical care, receiving the appropriate diagnosis, and rapid reporting. In their simulation study of outbreak detection in France, researchers found that outbreak size, duration, and season all impacted the ability of a surveillance system to detect waterborne disease outbreaks (Mouly et al., 2018). As a result of these challenges, infectious disease surveillance is often combined with other surveillance systems in an attempt to identify and respond to outbreaks in a timelier and more effective manner.
The WDRAP has prioritized detection and reporting of giardiasis and cryptosporidiosis because this is a specific requirement of the FAD and the pathogens most likely to be of concern in an unfiltered water supply. Starting in 1993 and 1994 for giardiasis and cryptosporidiosis, respectively, the WDRAP conducted active surveillance by contacting laboratories to determine the number of cases of each disease. In 2011, electronic laboratory reporting systems were implemented, and the WDRAP program now uses the electronic laboratory report system data to assess cases of giardiasis and cryptosporidiosis. In addition to case detection, WDRAP collects demographic and risk factor information for cases. For giardiasis (since 1995), WDRAP collects detailed demographic information only for patients that are suspected to be a secondary transmission risk such as food handlers or day care workers. For cryptosporidiosis (since 1994), telephone interviews of all cases are used to collect demographic and risk factor information. Data collected from disease surveillance are assessed for trends over time and seasonal distribution and to analyze risk factors for the disease.
Syndromic and sentinel surveillance can be useful in measuring disease trends in the general population by identifying signals that might indicate a waterborne disease outbreak more rapidly than disease surveillance alone. Syndromic surveillance uses indicators other than physician-diagnosed cases, such as preclinical or prediagnostic data. Preclinical data such as over-the-counter medication sales for antidiarrheal medicines or calls to nurse hotlines are two indicators that have been measured in an attempt to identify increases in gastrointestinal disease. Preclinical data have the advantage of providing a timelier signal but they lack specificity.
Clinical, prediagnostic data, such as emergency department visits for gastrointestinal illness, are more specific but there is a greater time lag as a result. Often, there is a tradeoff between specificity and timeliness of syndromic indicators (Berger et al., 2006). Sentinel surveillance relies on monitoring of specific subpopulations that can represent geographic areas or key populations of interest. Sentinel sites can include specific laboratories that represent geographic areas or populations such as the elderly or young children that may be more at risk for enteric infections and more likely to experience the illness prior to the general population.
The WDRAP employs outbreak detection activities that include both syndromic and sentinel surveillance. They include four distinct detection systems: (1) hospital emergency department chief complaint logs, (2) purchase of antidiarrheal medication, (3) clinical specimen submission for laboratory analysis, and (4) monitoring of gastrointestinal illness in eight sentinel nursing homes (NYC DOHMH and NYC DEP, 2018). Each system is described below, and a summary of the outbreak detection systems is provided in Table 11-1.
The hospital emergency department monitoring program, which began in 2001, is the system relied most heavily upon for detection of an outbreak (NYC DOHMH and NYC DEP, 2019). NYC emergency departments transmit records to DOHMH with information on chief complaints and patient demographics from the preceding 24 hours. For analysis of waterborne disease outbreaks, two chief syndromes are analyzed: diarrhea and vomiting. Space/time cluster analyses are completed, a threshold of significance is assigned (currently p < 0.005 for spatial signals and p < 0.01 for citywide), and signals are assessed.
Over-the-Counter Medication Sales.
Measurement of antidiarrheal medication began in 1995 and was originally managed by NYC DEP. Modifications and enhancements have been made, and the system currently in use is called the over-the-counter antidiarrheal medication system, which was the result of the merging of two separate systems in 2012. DOHMH currently manages the system. The system tracks the sale of over-the-counter non-bismuth- and bismuth-containing subsalicylates and includes more than 560 stores (as of 2018). Analysis of the information is daily via the cumulative sums method.
Clinical Laboratory Monitoring.
The clinical laboratory monitoring system collects information from a large laboratory in NYC (since 1995). Approximately three to four times per week, the laboratory sends information to DOHMH regarding the number of stool samples submitted for analysis for bacterial culture and sensitivity, ova and parasites, and Cryptosporidium. Data analysis via the cumulative sums methods is performed to determine if an increase is statistically significant.
TABLE 11-1 Summary of Waterborne Disease Risk Assessment Program Outbreak Detection Approaches
|System||Data Frequency||Geographic Unit||Data Analysis|
|Emergency departments (EDs)
~ 53 EDs (out of 53)
~ 11,500 visits/day
|7 days/week||Citywide, zip code, hospital||Space/time cluster analysis|
|Over-the-counter antidiarrheal medication
|7 days/week||Citywide||Cumulative sums method|
|Clinical laboratory monitoring||~ 3 days/week||Metro New York City||Cumulative sums method|
-8 sentinel nursing homes
|Outbreaks||Each borough, except Staten Island||Signal = Outbreak|
SOURCE: Seeley (2018).
Nursing Home Surveillance.
The nursing home surveillance system has been in place since 1997 and has been modified multiple times. Eight nursing homes in various geographic locations in the city are participating. When a nursing home identifies an outbreak of gastrointestinal illness, they are required to notify the New York State Department of Health. In addition, the nursing home should notify the WDRAP coordinators. The nursing home staff have instructions and sample collection containers for stool, which are analyzed at a laboratory for bacterial culture and sensitivity, ova and parasites, Cryptosporidium, virus, and Clostridium difficile. The WDRAP program staff also visits nursing homes annually to ensure compliance with the surveillance system.
Additional components of the WDRAP include information sharing and response planning. Information on Cryptosporidium and Giardia is available on the websites of NYC DEP and DOHMH as listed in Part III of the WDRAP Annual Reports. Included are annual program activities, fact sheets on giardiasis and cryptosporidiosis, and results from the NYC DEP’s source water protozoa monitoring program. Regarding to response planning, in May 2017, NYC DEP held a functional exercise of NYC’s Hillview Reservoir Cryptosporidium & Giardia Action Plan (NYC DEP, 2018a). A revised and updated version of the plan is issued by December each year to ensure that contacts and information are current.
Current Rates of Waterborne Disease
As reported in the 2017 WDRAP Annual Report (NYC DOHMH and NYC DEP, 2018), cases of giardiasis have declined overall during the 23-year surveillance period. Cases of giardiasis declined rapidly in the first ten years of surveillance, going from 32.3 cases per 100,000 people per year in 1994 to 10.7 cases per 100,000 people per year in 2005. Since 2005, the case rate has not decreased substantially but ranged from the lowest rate of 9.2/100,000 in 2013 to as high as 11.4/100,000 in 2017. In 2017, 975 cases of giardiasis were recorded in NYC, which was an 8 percent increase over 2016. Of the 975 cases, 48 were investigated because those patients were potentially at risk for secondary transmission.
Cases of cryptosporidiosis have also declined during 22 years of surveillance. As with giardiasis, the largest period of decline in cases for cryptosporidiosis was during the early period of surveillance (Figure 11-2). Case rates declined from 6.1/100,000 in 1995 (the first complete year of surveillance) to 1.5/100,000 in 2001, although the rate of decline decreased shortly after 1997. Since 2001, case rates have fluctuated from 1.0/100,000 in 2013 to 2.2/100,000 in 2016. The great decline in cases of cryptosporidiosis for those persons living with HIV/AIDS during the early part of the surveillance period (going from 392 cases in 1995 to 39 cases in 2017—NYC DOHMH and NYC DEP, 2018) may be attributed to the introduction of highly effective antiretroviral therapy in 1996-1997 for persons living with HIV/AIDS (Alleyne et al., 2020).
In 2017, 163 cases of cryptosporidiosis were reported (1.9/100,000), a 17.8 percent decrease from 2016. However, rates for 2015-2017 are higher than for the preceding 14 years. This increase is suspected to be the result of an increased number of tests and not an increase in cases of cryptosporidiosis (NYC DOHMH and NYC DEP, 2018). Starting in 2015, the use of culture-independent diagnostic testing has increased, and it is possible that more of these tests were ordered for Cryptosporidium compared to the traditional ova and parasite test.
Through an analysis of demographic information, neighborhoods were compared for rates of giardiasis and cryptosporidiosis, using the United Hospital Fund neighborhood categories. In 2017, the highest case rate for giardiasis was in the Greenwich Village Soho neighborhood of Manhattan (47.7/100,000) followed by the Chelsea-Clinton neighborhood (42.6/100,000). For cryptosporidiosis, the highest case rate was in Chelsea-Clinton (8.9/100,000) followed by the Greenwich Village Soho neighborhood (7.3/100,000). For both diseases, the highest case rates were for males, 20 to 44 years of age.
Additional analyses to examine risk factors for cryptosporidiosis were completed by the WDRAP staff (Alleyne et al., 2020). Although the comparisons lack a true control group, making it difficult to draw substantial
conclusions, the results suggest that international travel and exposure to recreational water are likely risk factors for cryptosporidiosis. In addition, among male cryptosporidiosis cases there were increased reports of high-risk sexual practices for some years for those persons living with HIV/AIDS. Because of this finding, the NYC DOHMH has initiated a program to target prevention programs for high-risk sexual practices (which is outside the WDRAP) (NYC DOHMH and NYC DEP, 2018; Seeley, 2018).
Figures 11-3 and 11-4 show the number of cases of cryptosporidiosis and giardiasis, respectively, (annual and monthly totals) from the last 20 years. As shown in Figure 11-3(B), cases clearly spike in the summer as a result of exposure to recreational water during that time period (Gharpure et al., 2019). In 2018, the total number of cases of giardiasis increased to 1,112, which represented a 14 percent increase in cases and a case rate (12.9/100,000) that exceeded the range of observed rates for the last decade. There were 250 cases of cryptosporidiosis, which represented a 53 percent increase in case counts and a rate (2.9/100,000) that also exceeded the range of observed rates for the last two decades. As mentioned above, NYC DEP has hypothesized that these increases in incidence are the result of more use of new culture-independent diagnostic tests; since 2015, the proportion of cases of cryptosporidiosis diagnosed with such tests has increased from 20 to 75 percent (NYC DOHMH and NYC DEP, 2019). This hypothesis has yet to be confirmed.
The syndromic surveillance system includes the four systems described above, which are used to identify trends or signals that might indicate possible disease outbreaks linked to the drinking water supply. As the signals in these systems can often be the result of a statistical aberration or a non-public health related event, the systems are used in concert to detect an outbreak. In 2018, multiple citywide signals occurred in January, March and April that indicated gastrointestinal illness, as shown in Figure 11-5. However, none of these signals indicated a sustained outbreak, and most were consistent with seasonal signals related to viral gastrointestinal recreational exposures. (It is noted that the y-axis in Figure 11-5 presents each of the four systems over time during but does not indicate magnitude or importance of the signal.)
Program Strengths and Weaknesses
The NYC DEP has invested significant resources in waterborne disease surveillance, as evidenced by supporting the WDRAP with six full-time employees as well as a commitment to extend the program until at least 2022. In addition to providing financial support, NYC DEP has also made the results of the surveillance available to the public through their website. In a search of three other U.S. cities (Boston, San Francisco, and Seattle) that currently have a FAD, no annual reports regarding a comprehensive waterborne disease risk assessment program were readily identified via their websites for watershed protection. One annual report for cryptosporidiosis disease surveillance was found on San Francisco’s website, indicating that the San Francisco Department of Public Health in cooperation with the San Francisco Public Utilities Commission and local health departments has an active surveillance program for cryptosporidiosis and provides an annual summary along with quarterly updates. In 2019, the Bay Area Cryptosporidiosis Surveillance project3 documented a total of 118 cases of cryptosporidiosis (2.2 cases/100,000). That same year the WDRAP documented a total of 395 cases (4.7/100,000), which is greater than in San Francisco (and greater than the cases documented by WDRAP in 2018) (NYC DOHMH and NYC DEP, 2020). However, without additional information it would be difficult to determine whether this difference was statistically significant.
The NYC DEP should be commended for their commitment to a collaborative, transparent, and sustained waterborne disease surveillance program. Over more than two decades of disease surveillance and syndromic and sentinel surveillance, no apparent outbreaks of giardiasis or cryptosporidiosis attributable to drinking water have occurred. The large amount of baseline data available as the result of the long-standing surveillance system can enhance the accuracy of detecting a signal that is likely the result of waterborne exposure. Furthermore, as documented in the disease surveillance for two protozoan pathogens, there has been a decline in cases of giardiasis and cryptosporidiosis for almost two decades (notwithstanding the increase in recent years). Additional benefits of the program include interagency collaboration, strong lines of communication, and developed and practiced action plans. As discussed below, the WDRAP could benefit by improvements to the syndromic and sentinel surveillance tools and by overall program evaluation.
Role of New Test Methods
One of the immediate challenges faced by the WDRAP disease surveillance program is how to interpret data from the culture-independent diagnostic tests (CIDT) for cryptosporidiosis and giardiasis. These tests will be utilized more often and have increased sensitivity of detection compared to traditional microscopy (Jothikumar et al., 2008). In an analysis of the active disease surveillance system for foodborne disease, researchers found a marked increase in the number of CIDT-only positive infections since 2013, including cryptosporidiosis cases (Marder et al., 2017). The WDRAP estimates that 75 percent of all cryptosporidiosis cases since 2018 were detected by such tests, which rely on a syndromic multiplex polymerase chain reaction (PCR) panel (NYC DOHMH and NYC DEP, 2020). Furthermore, Alleyne et al. (2020) documented a statistically significant increase in age-adjusted incidence of cryptosporidiosis in NYC following the introduction of the syndromic multiplex panels. Yet, cryptosporidiosis case rates between 2018 and 2019 doubled (2.2 to 4.7/100,000). Hence, a thorough understanding of the scale and coverage of culture-independent diagnostic testing in the NYC laboratories used for disease surveillance is needed to better understand what portion of the changes in rates of these diseases is a result of the increased diagnostic sensitivity.
The increase in detection for giardiasis and cryptosporidiosis will influence how surveillance information is analyzed against historical trends. Researchers at NYC DOHMH recently employed a method to refine the historical limits used for assessing disease clusters for many of the enteric infections detected via the multiplex assays (Peterson et al., 2018). Innovative approaches to deal with the increased detection due to the shift toward CIDT should be incorporated into the WDRAP. The CDC’s Emerging Infection Program has identified a plan to deal with emerging infections surveillance in the era of culture-independent testing, which includes 11 steps
(Langley et al., 2015). These steps range from periodic laboratory surveys to adopting analytical methods to account for changes in testing.
Recommendations from the 2000 Report
In the National Academies’ first review of the NYC strategy for watershed protection (NRC, 2000), the waterborne disease surveillance program was reviewed and six recommendations were made, some of which have been addressed since 2000. Specific changes include the use of hospital emergency department visits for gastrointestinal illness for inclusion in the outbreak detection system. In addition, an action and response plan has been developed and put into place as evidenced by the NYC Hillview Reservoir Giardia and Cryptosporidium Action Plan (NYC DEP, 2018a). Additional recommendations that have not been fully addressed should be reconsidered. For example, in NRC (2000) a quantitative microbial risk assessment identified the estimated daily risk of Cryptosporidium infection to be 3.4 × 10-5 based on monitoring data from the 18 monitoring locations in the Kensico Reservoir (NRC, 2000). Given two additional decades of pathogen monitoring data, the WDRAP could update this assessment and consider how the installation of the ultraviolet (UV) treatment system in 2012 has likely affected concentrations of protozoan parasites. A new assessment could take advantage of more enhanced methodologies for risk assessment and account for both new dose-response models for Cryptosporidium (Messner and Berger, 2016) and the fact that highly effective antiretroviral therapy has been introduced in the meanwhile. The WDRAP is well positioned to incorporate a formal risk assessment to better understand the potential risks that these pathogens pose to public health. In addition to complementing the WDRAP, the risk assessment could also help the overall watershed protection program evaluate the most effective tools for reducing risk to human health in the watershed.
Other recommendations from NRC (2000) have yet to be addressed: Cryptosporidium testing for all stool samples, determination of the lowest incidence of disease that the outbreak detection systems can detect, and additional epidemiologic studies to address the role of tap water in gastrointestinal infections. Not all of these issues remain relevant today, but a better understanding of the frequency of stool testing for Cryptosporidium and a formal evaluation of the surveillance system, including an understanding of the sensitivity of the outbreak detection system, is warranted (as elaborated on further below).
Low Incidence of Giardiasis and Cryptosporidiosis and Sensitivity of Surveillance
A challenge that the disease surveillance program faces is the low number of reported cases overall, especially for cryptosporidiosis. Since 2000, the case rate for cryptosporidiosis has only exceeded 2.0/100,000 twice, in 2016 and 2018. The decrease in cases of cryptosporidiosis in NYC is in contrast to the overall trend in the United States where there has been an increase in reported cases of cryptosporidiosis during the last two decades (Painter et al., 2016). These low counts make it difficult to assess for impacts of the Watershed Protection Program and associated decreases in cryptosporidiosis. Yet, disease surveillance remains critical to maintaining filtration avoidance, as other key FAD metrics such as turbidity and E. coli may not be reliable indicators. In a recent drinking water-related outbreak of cryptosporidiosis in a small, agriculturally impacted, unfiltered water supply in Oregon, the first indication of a problem was laboratory diagnosis of cryptosporidiosis; neither turbidity nor E. coli counts increased to indicate fecal contamination of the supply (DeSilva et al., 2015).
The WDRAP program has enhanced the outbreak detection system to include additional sources of data. There are more than 500 pharmacies that provide information on over-the-counter sales of antidiarrheal medication, which is a pre-clinical measure and has the potential for being timely. Unfortunately, evidence on the ability of these methods to detect an outbreak is varied. Kirian and Weintraub (2010, 2011) report no significant correlations between weekly diarrheal remedy sales and diarrhea illness case counts, outbreak counts, or the number of outbreak-associated cases in a detailed review of data in the San Francisco area. However, their analysis was limited to small outbreaks and they could not rule out the value of this approach for larger outbreaks. In a literature review by Pivette et al. (2014), drug sales data were found to be somewhat useful for
surveillance of gastrointestinal disease, with some potential for early outbreak detection. Edge et al. (2004) performed a retrospective analysis of over-the-counter medication sales and two waterborne disease outbreaks in Canada and found that over-the-counter sales were data were more reflective of cases than emergency department data, especially for the outbreak of cryptosporidiosis. In their own report, WDRAP indicated that the signals for anti-diarrheal medication sales identified in April/May of 2018 (Figure 11-5) were related to promotional sales of the products, not outbreaks.
There is also conflicting evidence about the ability of other syndromic surveillance systems to successfully detect an outbreak of gastrointestinal illness. NYC has included the emergency department visits for gastrointestinal illness in the program because this method has the potential to provide clinical, prediagnostic data that have a more specific signal for gastrointestinal illness. In an analysis of the first three years of emergency department surveillance for gastrointestinal illness performed in New York City, the authors found that only City-wide signals were identified as outbreaks and routinely reported to the DOHMH, and the gastrointestinal outbreaks that were reported during that time period did not generate syndromic signals (Balter et al., 2005).
In their retrospective analyses of syndromic surveillance data and outbreaks in Sweden, Andersson et al. (2014) and Bjelmkar et al (2017) found that systematic monitoring of a nurse triage line would have likely provided an outbreak signal at earlier stages. More specifically, Andersson et al. (2014) found the largest outbreaks (two of which were due to cryptosporidiosis) were detectable by a 24h nurse-on-call triage phone service comprising healthcare advice. Because of the nature of the symptoms associated with enteric pathogens, it is possible that detection of other pathogens such as norovirus could delay detection of an outbreak of cryptosporidiosis, as was found in an analysis of the cryptosporidiosis outbreak in Sweden in 2011 (Bjelkmar et al., 2017).
In a recent evaluation of six syndromic surveillance programs, Thomas et al. (2018) found that utility of the syndromic surveillance methods relying on emergency departments (ED) has been low, often due to dependence on local features of the detection systems to produce a high enough signal-to-noise ratio. That is, the ability of syndromic surveillance to detect an outbreak depends on such features as the magnitude and shape of the epidemic curve; the background frequency of the syndrome among ED patients; the timeliness, completeness, and accuracy of transmitting and consuming ED data; and the likelihood that a disease will result in an emergency room visit, especially for mild presentations that could be possible with cryptosporidiosis. Two improvements to enhance early detection of outbreaks were suggested: accessing and analyzing text from electronic health records and broader data exchange between health care and public health (Thomas et al., 2018). As some seasoned health departments such as DOHMH have now gained decades of experience using syndromic surveillance systems, there is a growing effort to more clearly understand the utility, sensitivity, and specificity of these systems—an area that could be explored in more detail by the WDRAP program.
Wastewater-based epidemiology to monitor population health is a growing field that has gained considerable attention in recent years. While it has been employed in research settings to examine drug abuse (Castiglioni et al., 2013; Choi et al., 2018) or for polio surveillance (Berchenko et al., 2017; Hovi et al., 2012; Lago et al., 2003; Lodder et al., 2012), there is increasing interest in using it as another tool to examine infectious disease surveillance (Sims and Kasprzyk-Hordern; 2020). This approach has the added advantage of the ability to detect cases that may be asymptomatic—something that the current systems do not detect. This increased detection may result in increased sensitivity and timeliness to detect an outbreak, and hence deserves further consideration as a method for early outbreak detection for giardiasis and cryptosporidiosis. The ability to detect oocysts of Cryptosporidium in wastewater was documented during a large waterborne disease outbreak in Sweden where researchers found increased oocysts in wastewater during the outbreak time period (Widerström et al., 2014). The NYCDEP and NYCDOHMH might consider developing tools to measure Cryptosporidium and Giardia in the wastewater of NYC as an additional surveillance tool.
Overall Program Evaluation
A documented and cohesive analysis of the overall impacts of the WDRAP is lacking, as is any clear process by which the program is or can be enhanced and improved. Undertaking a systematic evaluation of the pro-
gram could enhance its efficiency, identify and accelerate priority areas for improvement, and strengthen the capability of these systems to better detect outbreaks at an earlier stage. Using a framework such as the CDC’s Framework for Evaluating Public Health Surveillance Systems for Early Detection of Outbreaks (Buehler et al., 2004) could provide substantial insights for the program. The CDC’s framework suggests evaluation of outbreak detection systems using four categories: system description, outbreak detection, system experience, and conclusions and recommendations for improvement. The framework guides analysis of all aspects ranging from the source and type of data to validation of outbreak detection and analysis of system utilization. Performing a rigorous and detailed evaluation of the program would enable the WDRAP to carefully review and address or enhance components of the system. To date, no such evaluation has yet to be completed.
More specifically, a systematic evaluation of the data used in the WDRAP could allow NYC DEP to assess all components of the surveillance system including the relevance of each tool. The clinical laboratory monitoring component currently replies on only weekly reports; determination of the needed frequency and timescales of the data sources could enable more useful analysis for disease detection. As shown in Figure 11-5, the nursing home sentinel surveillance system produced one signal in June 2018, making its value questionable. Although systematic monitoring of a nurse triage line, as was done in Sweden (see above), is unlikely to work for NYC given the fragmented U.S. healthcare system, identification of additional sources of preclinical data should be considered. In their analysis of six syndromic surveillance systems in the United States (New York City being one), researchers found that the perceived predictive value and utility of these systems for detecting outbreaks was low (Thomas et al., 2018). As a leader in the field, the WDRAP could substantially enhance their program, and broadly, public health practice, by performing a review of their program to help determine which sources of data are the most useful and informative and sharing the results with others working in the field.
The monitoring of microorganisms in the streams, reservoirs and watersheds that are the source of New York City’s drinking water is extensive and designed to comply with EPA regulations and to guide NYC DEP operations. In particular, the SWTR and its enhancements, along with FAD requirements, identify when, where, and how often samples of total and fecal coliform, E. coli, human enteric viruses (HEVs), heterotrophic plate counts (HPCs), and the protozoans Giardia and Cryptosporidium are collected. This monitoring of microbiological parameters includes both pathogenic organisms (i.e., Giardia, Cryptosporidium, and enteric viruses) and indicator organisms (i.e., total coliforms, fecal coliforms, and E. coli) that are used as surrogates of pathogens in water.
Microbial monitoring, which began in the early 1990s, differs between the Cat/Del supply and the Croton supply mainly because of the presence of the Croton Water Filtration Plant. Another distinction within the microbial monitoring program is that the “terminal” or “source” reservoirs (see Chapter 3) are monitored more frequently for indicator bacteria and protozoa than non-terminal, non-source reservoirs. Table 11-2 shows the microbial compliance monitoring performed for the NYC water supply reservoirs and tributaries, organized by waterbody, along with the rationale for monitoring, which may stem from several sources. Individual parameters included in the table are discussed below.
Total Coliform and Fecal Coliform Monitoring
Both total coliforms and fecal coliforms are used as indicators of potential pathogen contamination (NYC DEP, 2016). Total coliforms include fecal coliforms and other coliforms derived from human and animal waste that can be found in water influenced by surface water, soil, and sediments. Fecal coliforms, a sub-group of total coliforms, are generally present in the gut and feces of warm-blooded animals. E. coli is a subgroup of fecal coliforms that persist in the intestines of people and warm-blooded animals. Determinations of coliform concentrations are governed by two sections of the NYC Watershed Rules & Regulations (WR&R) for terminal basins as well as by the SWTR. The terminal basin regulations apply to Kensico, West Branch, New Croton,
TABLE 11-2 Regulatory Compliance Microbial Monitoring
|Site||Parameters||Frequency||Rational for Analysis|
|Total coliform (TC)||5/month||WR&R|
|TC/fecal coliform (FC)||4/week||Operational decisions|
|TC non-sheen||1/month||Operational decisions|
|TC non-sheen||1/month||Operational decisions|
|TC non-sheen||1/month||Operational decisions|
|TC/FC||4/week||IESWTR and Operations decisions|
|TC non-sheen||1/month||IESWTR and Operations decisions|
|West Branch Reservoir||Cryptosporidium||1/month||IESWTR|
|TC/FC||5/week||IESWTR and operations decisions|
|TC non-sheen||1/month||Operational decisions|
|TC/FC||4/week||IESWTR and operations decisions|
|West-of-Hudson tributaries||Cryptosporidium||1/month||Operational decisions|
|New Croton Reservoir||Cryptosporidium||quarterly||IESWTR|
|TC/FC||5/week||IESWTR and operations decisions|
|TC non-sheen||1/month||Operational decisions|
|East-of-Hudson Tributaries||Cryptosporidium||1/month||Operational decisions|
|TC/FC||7/week||IESWTR operations decisions|
|TC non-sheen||1/week||IESWTR operations decisions|
|HPC||1/week||IESWTR operations decisions|
|Kensico Reservoir tributaries||Cryptosporidium||1/month||IESWTR|
|TC/FC||1/month||IESWTR and operations decisions|
|Hillview Reservoir||Cryptosporidium||1/week||Hillview Administrative Order|
|Giardia||1/week||Hillview Administrative Order|
|Jerome Park Reservoir||Cryptosporidium||weekly||IESWTR|
|Downsville (Public water system [PWS]; Downsville entry point)||TC||quarterly||TCR|
|Downsville Police Barracks (PWS; Police barracks distribution point)||TC||quarterly||TCR|
|Grahamsville (PWS; office kitchen distribution point)||TC||quarterly||TCR|
Cryptosporidium and Giardia now analyzed by EPA method 1623.1 with Easy stain and heat dissociation.
Virus samples (human enteric virus, HEV) are analyzed by EPA 600/4-84/013 (N14).
Source water total coliform (TC) + fecal coliform (FC) + non-sheen/non-blue standard method (SM) membrane filtration: 9222B + 9222D reported as CFU/mL.
Upstate reservoirs E. coli method Colilert 18 reported as MPN/100 mL
Distribution/prefinish total coliform (TC/E. coli) Colilert SM9223B04 reported as MPN/100 mL
Sample volumes: Cryptosporidium and Giardia 50 L, HEV up to 240 L, potable TC/FC 100 mL, source water TC/FC/non-sheen various CFU = colony-forming units
MPN = most probable number
IESWTR = Interim Enhanced Surface Water Treatment Rule
WR&R = Watershed Rules and Regulations
TCR = Total Coliform Rule
Ashokan, and Rondout reservoirs. The coliform assessments for these basins are based on compliance with federally imposed SWTR limits on fecal coliforms (< 20 CFU/100 mL) or total coliforms (<100 CFU/100 mL) collected from waters within 500 feet of the reservoirs’ aqueduct effluent chamber. The terminal basin assessments require a minimum of five samples each week over two consecutive six-month periods. If 10 percent or more of the water samples have fecal coliform concentrations greater than 20 CFU/100 mL, which is the threshold for violation of the SWTR, and the source of the coliforms is determined to be human-related or anthropogenic (i.e., wastewater), the associated waterbody is rated as “coliform-restricted” (NYC DEP, 2019a). If a reservoir in the watershed is determined to be “coliform restricted,” then no new sewage treatment plants can be built in that basin (NYC DEP, 2016). Note that a variance from building a new wastewater treatment plant or expanding a treatment plant can be granted in a coliform-restricted basin if it is determined that the area to be served is discharging inadequately treated sewage and that there are no other feasible methods of correcting the release of this discharge.
Until the EPA validates a method for determining anthropogenic sources, the source of fecal coliforms is reported annually as undefined (NYC DEP, 2016). During the 2018 reporting period, all terminal reservoirs reported fecal coliform counts below the threshold (NYC DEP, 2019a), such that all terminal reservoirs are currently non-restricted, including Kensico Reservoir. For all of the other reservoirs and controlled lakes, including Lakes Gilead and Gleneida, coliform-restricted assessments are based on compliance with NYS ambient water quality standard limits on total coliform bacteria (TC < 100 CFU/100 mL; NYC DEP, 2019a). All non-terminal reservoirs are monitored for total coliform with a required minimum of five samples per month. If both the median value and more than 20 percent of the total coliform counts for a given month exceed the values ascribed to the reservoir class, and it is determined that the coliforms are human-related, then the non-terminal reservoir is designated as “coliform-restricted” (NYC DEP, 2019a). During the 2018 reporting period, approximately, 65 percent (i.e., 11 out of 17) of the non-terminal basins exceeded regulatory limits.
Commonly used culture methods for both fecal coliforms and E. coli cannot differentiate between human and animal sources of the bacteria. In addition, fecal coliform bacteria can derive from point sources that enter the reservoirs through a known route (e.g., sewage treatment plant) or through nonpoint sources that are less easily assessed (e.g., urban or agricultural runoff, septic systems, and waterfowl and other wildlife). Coliform bacteria from anthropogenic sources are regarded as a greater public health risk than those from nonhuman sources, although zoonotic pathogens are known to exist.
Microbial source tracking (MST), using host-specific markers or employing DNA sequencing, has been successfully used to characterize and identify bacteria from either human or animal sources in a watershed. Sowah et al. (2017) used MST markers (i.e., Bacteroidales markers), land use characterization, and coliform bacteria concentrations to understand the impact of septic systems in a watershed. Similar studies would be useful in the NYC watershed to better understand the roles of various animal sources of fecal coliforms, from humans to waterfowl to livestock, if the reservoirs or tributaries exceed regulatory limits for fecal or total coliforms or are designated as coliform-restricted. Several specific and sensitive MST markers are available to identify sources (e.g., human, bird, livestock), to establish a correlation between coliform bacteria and anthropogenic activity, and to better understand the impact of human and animal contributions in a watershed. Depending on the results of such a study, the NYC DEP could gain information that would be valuable for the Watershed Agricultural Program, the Septic Program, and the Stormwater Program. For example, if high concentrations of fecal coliforms of human origin were detected in base flows, one might implicate failing septic systems. Increases in microbial loading from stormwater would be more likely to be detected during high-runoff events.
During the 2018 annual review of the total coliform data, it was determined by NYC DEP that the status of designating coliform-restricted reservoirs was being complicated by changes in the methods and how the data are reported, making it difficult to compare regulatory exceedances to those from previous years (NYC DEP, 2019a). To overcome these challenges, it is recommended that the levels of both total coliforms and fecal coliforms at each basin be analyzed by comparing geometric means for several years (minimum of five years). This analysis is especially important in basins where the number of samples used to assess concentrations vary at each site (i.e., n varies from 5 to 16), or the number of samples analyzed is low (i.e., n = 5). For a better understanding of the temporal variations, especially at basins where a large number of samples exceed regulatory limits (e.g., Diverting Reservoir during 2018), additional sampling (greater than five samples) is strongly recommended.
Because monitoring of coliforms does not necessarily indicate whether an unfiltered water supply is contaminated with Cryptosporidium or Giardia (NRC, 2004), these protozoan parasites are routinely monitored throughout the NYC water supply system (see Table 11-2).4 Approximately, 63 percent of the samples analyzed during 2018 were from streams and source water locations. Additional protozoan samples were collected at Hillview Reservoir, at the UV plant, and at wastewater treatment plants. The 1998 Interim Enhanced SWTR added a maximum contaminant level goal (MCLG) of zero for Cryptosporidium and required that unfiltered systems control potential sources of Cryptosporidium in their watershed, in addition to a 3-log inactivation of Giardia and a 4-log removal or inactivation of viruses. The Long-Term 2 Enhanced SWTR (LT2) requires that unfiltered systems use two primary disinfectants and achieve 2-log inactivation of Cryptosporidium. If the average source-water concentration exceeds 0.01 oocysts/L, an unfiltered system must provide at least 3-log (i.e., 99.9 percent) inactivation of Cryptosporidium.
EPA Method 1623.1 with Easy Stain and heat dissociation is currently being used by NYC DEP to identify both Cryptosporidium oocysts and Giardia cysts. This “new method,” which is widely employed for drinking water systems, has been refined to specifically improve detection, assess viability, and identify sources of Cryptosporidium. For the two-year period ending December 2018, source-water concentrations of Cryptosporidium were below the LT2 threshold (0.01 oocyst/L) for both the filtered and unfiltered parts of the NYC water supply (Figure 4-17; NYC DEP, 2019a). Fluctuations in the reported concentrations of protozoa were thought to be due to a change in methods and not reflective of an actual change in Cryptosporidium prevalence in the environment (NYC DEP, 2019a). It is recommended that data collected using the new method be collected at the same frequency (i.e., time period) as the old method (Method 1623) to allow for a statistically significant data set that can be evaluated for long-term concentrations, fluctuations, and trends.
Because Kensico Reservoir is the terminal reservoir for the unfiltered Cat/Del water supply before chemical and UV disinfection, its protection is particularly important to preventing water quality degradation and maintaining compliance with the revised FAD. Hence, NYC DEP has an extensive routine pathogen monitoring strategy for streams such Bear Gutter Creek, Malcolm Brook, and Whippoorwill Creek that feed into Kensico Reservoir; indeed this monitoring comprises approximately 40 percent of the entire watershed sampling effort for pathogens (NYC DEP, 2016). Approximately eight perennial streams that flow into Kensico Reservoir are sampled monthly for Cryptosporidium and Giardia (NYC DEP, 2019a). If elevated concentrations of protozoa are identified, additional samples may be collected and additional analysis may be performed to determine the source of the protozoa. That is, samples that are positive for both Cryptosporidium and Giardia are PCR-amplified and genotyped to provide further information about the source of the isolate (i.e., human or animal) and the likely public health risk. Wildlife scat samples collected from the streams within the Kensico watershed and analyzed for the presence of oocysts may be included in this source tracking analysis.
In 2018, an increase in Giardia cysts was observed at the upper end of the Delaware Aqueduct (at the Rondout Reservoir outflow) that serves as the inflow to Kensico Reservoir (NYC DEP, 2019a). Additional samples were collected and analyses were performed at upstream locations to identify the source(s) and transport of the Giardia cysts. With respect to identifying sources, water-bird population counts, wildlife surveys, and trapping were performed in order to test scat samples and to genotype the Giardia cysts. The genotype investigation to identify sources of Giardia cysts was inconclusive, suggesting multiple different sources (NYC DEP, 2019b). Levels of Giardia at the outflows of Kensico and Hillview reservoirs have remained within the normal seasonal range and below levels that require further action.
4 Protozoan monitoring data are available at https://data.cityofnewyork.us/Environment/DEP-Cryptosporidium-And-Giardia-Data-Set/x2s6-6d2j.
Hillview Reservoir is uniquely important because it is the last reservoir for the City’s treated source water from the Cat/Del water supply, being just downstream from the UV disinfection facility. Hillview is under an administrative order requiring weekly monitoring of protozoa until the reservoir is covered. If an elevated5 protozoan concentration is found, additional sampling is performed as per the Cryptosporidium and Giardia Action Plan (NYC DEP, 2018a). The Cryptosporidium and Giardia sampling at Hillview Reservoir covers approximately 10 percent of the total sampling effort for pathogens across the watersheds (NYC DEP, 2016). In addition to using Method 1623.1 with Easy Stain and heat dissociation, Cryptosporidium infectivity methods using cell culture have been tested that may provide greater sensitivity at low concentrations. The positive Cryptosporidium samples from Hillview tested negative for infectivity in 2018; therefore, NYC DEP hypothesized that the oocysts were being inactivated by UV treatment (Alderisio, 2018).
Additional Microbial Monitoring
E. coli, HEV, HPC, and total coliform-non sheen colonies are also monitored at various NYC reservoirs for potential water quality issues (see Table 11-2). The E.coli test is performed when total coliforms are detected at Ashokan, Downsville, and Grahamsville (Table 11-2). All virus samples analyzed at Kensico and New Croton reservoirs use the EPA 600/4-84/013 method, a culture-based assay that indicates viability. As stated in the 2018 Watershed Water Quality Annual Report (NYC DEP, 2019a), HEVs were identified in approximately 8.3 percent of samples taken at the Catskill inflow to Kensico Reservoir in 2018. Additionally, about 8.3 percent of samples taken within the reservoir were positive, and concentrations have remained consistent for two monitoring years, from 2017 to 2018 (NYC DEP, 2018b).
The New Croton Reservoir outflow was also sampled for HEV during 2018, but HEV were not detected in any of the samples. Data on E. coli, HPCs, and total coliform-non sheen were not available in the NYC DEP 2018 Watershed Water Quality Annual Report or in previous annual reports analyzed by the Committee.
A potentially significant contribution of bacteria and other microbial pathogens to the NYC water supply is from migratory waterfowl that breed, nest, roost, and defecate in the reservoirs and the lands adjacent to them, as well as from other wildlife and their excretions. The NYC reservoirs lie in the Atlantic Flyway, an important migratory pathway for many waterfowl species such as geese, gulls, cormorants, swans, mallards, ducks, and other duck-like birds, which use the reservoirs as temporary staging areas and wintering grounds. The management of water-bird populations, therefore, is important to meeting water quality regulations for fecal coliform bacteria limits in the SWTR. Untreated water samples have shown fecal coliform increases concurrent with avian populations at several NYC reservoirs in the past (NYC DEP, 2016). Hence, the NYC DEP established a Waterfowl Management Program at Kensico and Hillview reservoirs in the early 1990s followed by program enhancements dictated by the 2007 FAD (NYC DEP, 2016).
The primary objective of the Waterfowl Management Program is to reduce or eliminate water-bird activity, in order to minimize microbial pathogen loading to the reservoirs from roosting birds. Water-bird population monitoring and dispersal activities are conducted daily at Kensico and Hillview reservoirs. A variety of bird deterrent and dispersal methods are employed that have successfully reduced the presence of waterfowl (NYC DEP, 2017, 2019d). The program also includes waterfowl population monitoring and an “as needed” waterfowl dispersal program for West Branch, Rondout, Ashokan, Croton Falls, and Cross River reservoirs, which are implemented based on water quality data and the operational configuration of the water supply at any given time (NYC DEP, 2016). Avian management measures are implemented at these reservoirs based on criteria including fecal coliform concentrations approaching or exceeding 20 CFU per 100 milliliters at reservoir effluent structures coincident with elevated bird populations; current bird populations, including roosting
or staging locations relative to water intakes; and weather and reservoir flow conditions. Another component of the program focuses on avian deterrence management, using water-bird egg and nest depredations to reduce fecundity and future recruitment of new nesting waterfowl, as well as bird exclusion wires and netting at critical intake chambers at Kensico, Hillview, West Branch, Rondout, Ashokan, Croton Falls, and Cross Rivers reservoirs (NYC DEP, 2019d). Wildlife sanitation surveys are conducted routinely at Kensico and Hillview, inspecting facilities and grounds and cleaning up of animal feces (NYC DEP, 2019d). Wildlife management efforts employed at Hillview Reservoir were expanded in 2011 and currently include additional monitoring, removal of mammals (potential sources of fecal matter) and alewife baitfish (a potential food source for waterfowl), and sparrow management (NYC DEP, 2017).
Long-term observations show that waterfowl management activities have had a high level of success eliminating or reducing water-bird populations within and surrounding the reservoirs. NYC DEP began collecting avian data prior to implementing the bird dispersal program in August 1992 at Kensico Reservoir (NYC DEP, 2016). The results of both bird counts and fecal coliform bacteria (see Figure 11-6) show a substantial decline in both metrics once waterfowl management began in 1993. For this reason, NYC DEP considers the Waterfowl Management Program to be critical to maintaining compliance with the SWTR criteria for fecal coliform bacteria at Kensico Reservoir (NYC DEP, 2016).
The waterfowl and wildlife management activities at Hillview Reservoir are meant to identify and reduce potential impacts of protozoa in addition to fecal coliform bacteria. Analyses of wildlife scat samples from around Hillview have demonstrated that most (92 percent) of the samples are negative for Cryptosporidium, with the positive samples being Cryptosporidium oocysts associated with rodents and birds (and not humans). Hence, Cryptosporidium is not currently considered by NYC DEP to be a significant human health risk at Hillview Reservoir (Alderisio, 2018). Nonetheless, it should be noted that Cryptosporidium species derived from animals have the potential to infect and sicken humans (Chalmers et al., 2009).
These waterfowl management programs exist at Hillview Reservoir because it is currently uncovered; covering of the reservoir in the future would provide a better long-term solution toward protection of water quality.
The Waterborne Disease Risk Assessment Program should determine whether the recent increase in protozoan parasitic infections observed via the disease surveillance system is from increased use of culture-independent diagnostic tests. A survey of the laboratories included in the surveillance system and an analysis of the proportion of tests that are culture-independent diagnostic tests are essential to understanding this apparent increase.
The New York City Department of Environmental Protection should undertake a quantitative microbial risk assessment for Crytosporidium infection risk. Utilizing two additional decades of Cryptosporidium monitoring, an updated risk assessment will complement existing epidemiologic surveillance data. In addition, the risk assessment can also provide a tool to evaluate and understand the activities in the watershed that could reduce the risks of pathogenic microbes to public health.
The Waterborne Disease Risk Assessment Program should determine the lowest incidence of disease that the outbreak surveillance systems can detect and their timeliness. This recommendation was made in NRC (2000) and should be revisited. While the current reports suggest no waterborne disease outbreaks have occurred, it is not clear what size of outbreak would be necessary to produce a signal. The timeliness of the various outbreak detection systems is also uncertain.
The New York City Department of Environmental Protection should undertake a formal evaluation of the Waterborne Disease Risk Assessment Program to ensure that the system is meeting the current and future needs. With the inclusion of UV treatment and subsequent removal of Cryptosporidium in
the treatment train, now is an opportunity to evaluate and consider if the priorities set in the initial program remain. Undertaking a systematic evaluation of the program could enhance its efficiency; identify and accelerate priority areas for improvement; strengthen the capability of the existing surveillance systems; and accommodate new surveillance methods such as wastewater-based epidemiology, to better detect outbreaks at an earlier stage.
Although the microbial monitoring program is well-structured and meets all regulatory requirements, the data it collects could be better analyzed and used to inform the Watershed Protection Program. For example, if reservoirs or tributaries exceed regulatory limits for fecal or total coliforms, or are designated as coliform-restricted, NYC DEP should use Microbial Source Tracking studies to identify sources, determine the relative importance of anthropogenic versus animal sources, and inform control strategies within the Watershed Agricultural Program, the Septic System Program, and the Stormwater Program. Also, the microbial monitoring program should routinely analyze data using proper statistical methods, such as comparing both fecal and total coliform geometric mean concentrations for a minimum of five years to accurately determine trends and fluctuations. Finally, when new methods are employed, as was done to identify Cryptosporidium oocysts, a statistically significant data set should be collected before attempting to compare the data with previously collected data and to identify long-term trends.
The Waterfowl Management Program has demonstrated effectiveness at reducing fecal coliform bacteria loads to reservoirs from water birds and other wildlife. The program is important to meet the water quality regulations and should be continued at this time. The future covering of Hillview Reservoir will still provide better long-term protection of that waterbody from fecal coliform bacteria than the Hillview Waterfowl Management Program.
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