Biology Reference
In-Depth Information
complaints in the emergency department to respiratory discharge diagnoses
(Ivanov et al. 2003). The mean timeliness calculated across different values
of the weighting parameter in the EWMA analysis varied from −11.7 to 32.7
days with an overall mean of 10.3 days (95% CI -15.2:35.5). Cross-correlation
analyses of the three outbreaks studied resulted in an average timeliness of
7.4 days (95% CI: −8.3, 43.3) (Ivanov et al. 2003).
This combined aberration detection-correlation method was also used by
Hogan and colleagues (2003). The CCF and EWMA algorithm were used to
determine the timeliness of sales of OTC electrolyte products for the detec-
tion of respiratory and diarrheal outbreaks (Hogan et al. 2003). Over the
3-year study period, the correlation of electrolyte sales to hospital diagnoses
based on raw data was 0.9 (95% CI 0.87-0.93) and OTC sales preceded diag-
noses by 1.7 weeks (95% CI 0.5-2.9) for respiratory and diarrheal outbreaks.
Doroshenko and colleagues (2005) applied an autoregressive moving aver-
age model and Spearman rank correlation to assess the timeliness of calls to
a national telephone advice service and ILI sentinel reporting. They found
statistically significant but weak correlations up to 21 days lag, suggesting
that ILI calls occurred 7-21 days earlier than an increase in consultations
recorded by a sentinel surveillance network (Doroshenko et al. 2005).
Lemay and colleagues (2008) applied an autoregressive moving average
model and CCF to assess the timeliness of emergency department ILI presen-
tations and laboratory-confirmed influenza by age group. This retrospective
study showed a strong correlation between the isolation of influenza viruses
and patient consultations to the ED for ILI in four of five seasons. When the
ILI consultations were divided by age group, consultations for children less
than five years were more likely to be correlated with laboratory-confirmed
influenza cases than consultations for other age groups. Statistically signifi-
cant correlations were found for the fever and respiratory/fever syndromes
in four seasons with a lag of 7-28 days (lags of greater than 28 days were not
included in the analyses) for children under 5 years.
Suyama and colleagues (2003) determined whether any temporal correlations
existed between emergency department (ED) symptom presentations (nausea,
vomiting, headache, etc.), and health department (HD) data for infectious dis-
ease (e.g., meningitis). Cross-correlation functions were calculated for a 3-day
crossover period between ED syndrome presentation and HD disease identifi-
cation. This was based on the period in which a temporal relationship between
ED and HD data may be of clinical significance. Syndrome presentations were
based on 73 infectious diseases (class A) reportable to the Ohio Department
of Health. CCFs were found to be significant (CCF > 0.074) for all syndromes
combined, gastrointestinal syndromes, pulmonary syndromes, and central
nervous system syndromes. It was found that for all syndromes combined, ED
presentations preceded HD identification by 1 day (CCF = 0.112).
Lazarus et al. (2002) investigated correlation using the Spearman rank cor-
relation between ambulatory-care episodes of lower respiratory syndrome
and hospital admissions for lower respiratory syndrome over a 3-year period.
