Sentinel Surveillance: A Reliable Way To Track Antibiotic Resistance in Communities?

Methods

Invasive pneumococcal surveillance was conducted from 1996 to 1998 as part of the Active Bacterial Core Surveillance/ Emerging Infections Program Network (ABCs) using previously described methods^[1]. Briefly, project personnel communicated at least twice each month with contacts in all participating microbiology laboratories serving acute-care hospitals in San Francisco County, California; Connecticut; eight counties in Georgia (Cobb, Clayton, De Kalb, Douglas, Fulton, Gwinnett, Newton, and Rockdale) with 12 additional Atlanta-area counties starting in 1997; six counties in Maryland (Anne Arundel, Baltimore, Baltimore City, Carroll, Harford, and Howard); seven counties in Minnesota (Anoka, Carver, Dakota, Hennepin, Ramsey, Scott, and Washington); seven counties in New York starting in 1997 (Genesee, Livingston, Monroe, Ontario, Orleans, Wayne, and Yates); three counties in Oregon (Clackamas, Multnomah, and Washington); and five counties in Tennessee (Davidson, Hamilton, Knox, Shelby, and Williamson).

A case was defined as the isolation of Streptococcus pneumoniae from a normally sterile site (e.g., blood or cerebrospinal fluid) from a resident of a surveillance area. Periodic audits were conducted in each area. Any cases newly identified by audits were included in the surveillance database.

All isolates were sent to one of two centralized laboratories for susceptibility testing by broth microdilution, with a panel of drugs that included (in 1998) penicillin, amoxicillin, cefotaxime, cefuroxime, meropenem, erythromycin, clindamycin, chloramphenicol, vancomycin, rifampin, levofloxacin, trovafloxacin, and quinupristin-dalfopristin (Synercid7). Nonsusceptibility (resistance and intermediate susceptibility) was determined according to criteria of the National Committee for Clinical Laboratory Standards^[13].

In each surveillance area for 1998, we generated all possible simple random samples of three, four, and five laboratories, excluding laboratories with <10 isolates. We limited our selection to up to five laboratories because a central objective of sentinel surveillance is to reduce required resources by reducing the number of facilities participating in the surveillance system. We refer to these simple random samples as sentinel groups of laboratories. We then calculated the percent of penicillin-nonsusceptible (MIC ≥0.1 µg/mL) pneumococci (%PNSP) among isolates in each of these sentinel groups and compared these percentages to the area's actual %PNSP, as measured by ABCs. The %PNSP in sentinel groups was considered to be accurate if it was within 5 percentage points of the area's actual %PNSP. We chose this interval because variation in the %PNSP within this range is unlikely to influence public health decisions^[12].

We used a finite population correction based on the total number of isolates in each surveillance area to assess the number of randomly sampled isolates that would be needed to estimate an area's actual %PNSP within 5 percentage points^[14]. We compared that number with the number of isolates in sentinel groups in each area.

In each surveillance area, we subtracted the %PNSP in each possible group of five laboratories in 1996 from that measured for the group of five laboratories in 1998. We included only laboratories with ≥10 isolates in each of the 2-year periods. We then measured how often the change in %PNSP in sentinel groups was within 5 percentage points of the area's actual change in %PNSP during the same time periods, based on ABCs data. We performed a similar analysis using the percentage of erythromycin-nonsusceptible (MIC ≥0.5 µg/mL) isolates as the outcome measure.

Using data from 1998, we measured the proportion of all possible groups of five sentinel laboratories within each surveillance area that captured any pneumococcal isolates with fluoroquinolone (levofloxacin or trovafloxacin) nonsusceptibility. We then compared that proportion with area-specific data on the presence of pneumococcal fluoroquinolone resistance from ABCs in 1998.

We merged ABCs data from 1997 and 1998 with purchased data on hospital characteristics collected by the American Hospital Association (AHA) as part of the AHA Annual Survey of Registered American Hospitals in 1997. We categorized each hospital that matched between the two datasets into the following PNSP classes: ≥5 percentage points above the surveillance area proportion PNSP (high PNSP), <5 percentage points above or below the surveillance area PNSP (average PNSP), or ≥5 percentage points below the surveillance area PNSP (low PNSP). We used logistic regression to perform univariate analyses. We compared hospital characteristics in the high group with those in the average group, separately comparing hospital characteristics in the low group with those in the average group. We categorized continuous variables according to their quartiles or medians based on their distributions. We limited our analysis to hospital characteristics that might plausibly influence a hospital's %PNSP based on findings of previous studies^[15,16].

Emerging Infectious Diseases. 2002;8(5) © 2002 Centers for Disease Control and Prevention (CDC)

Cite this: Sentinel Surveillance: A Reliable Way To Track Antibiotic Resistance in Communities? - Medscape - May 01, 2002.