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outbreaks, we examined the effect of the timing of administration of oseltamivir chemoprophylaxis for the control of influenza A H3N2 outbreaks among residents in LTC facilities in Manitoba, Canada, after controlling for other institutional factors.
Methods
A retrospective cohort design was used with 4 data sources: (1) epidemic curves, (2) hand hygiene audits, (3) lists of private and public LTC facilities in each studied region, and (4) Statistics Canada census data. In Manitoba, all LTCFs monitor influenza-like illness (ILI).
Influenza-like illness is characterized as acute onset of respiratory illness with fever and cough and with 1 or more of the following symptoms: sore throat, arthralgia, myalgia, or prostration that could be due to influenza.9 An institutional influenza outbreak is defined as “2 or more cases of ILI (including at least 1 laboratory-confirmed case) occurring within a 7-day period in an institution.”9 If an institutional ILI outbreak is suspected, naso- pharyngeal swabs are conducted on a sampling of up to 6 ill residents or staff to identify the causative pathogen. Staff also keep records of daily case counts and symptoms present
during outbreaks to monitor their development and resolution. Once no new cases have occurred for 2 incubation periods of influenza, up to 8days,1 the outbreak can be declared over. Outbreaks were included (1) if they occurred between October
2014 and May 2015, (2) if they occurred in an LTCF in Manitoba, and (3) if influenza type was determined. Only the first influenza A H3N2 outbreak in an institution was included in the analysis because a prior outbreak during the same influenza season with the same virus may significantly alter the immunity of the resi- dents to that strain of influenza and thus alter the attack rate of the virus and, thus, the subsequent likelihood of symptomatic infections.
Outbreaks were excluded if either the dependent variable or
main independent variable could not be determined. The University of Manitoba Human Research Ethics Board
approved this study. The main independent variable was how many days passed
between the true start of the outbreak (ie, the date that the second person became ill) and commencement of oseltamivir chemo- prophylaxis. The dependent variable was whether each person in the institution developed ILI (yes or no). The following control variables were used:
1. The number of days between declaring an outbreak and the start of oseltamivir chemoprophylaxis
2. The number of days between the first and second cases of ILI 3. The prevalence of symptomatic infection among residents at the start of the outbreak
4. The prevalence of symptomatic infection among staff at the start of the outbreak
5. The number of at-risk residents at the start of the outbreak 6. The percentage of residents vaccinated 7. The percentage of staff vaccinated 8. Rural (yes or no) 9. Publicly operated facility (yes or no)
10. Percent compliance during hand hygiene audit.
Rural was defined as 10,000 people or less. Population size was determined using Canadian Census data from 2011.20 The hand
Davinder Singh et al
hygiene audit conducted closest to the study period was used to determine percent hand hygiene compliance.
Data analysis
For each outbreak, the secondary attack rate is calculated with the following equation21: 20 attackrate
= Total#cases#Cases on or before day of 2nd case of illness
ðÞ ðTotal#residents#Cases on or before day of 2nd case of illnessÞ
The number of days until oseltamivir prophylaxis was started was calculated by determining the date of chemoprophylaxis and subtracting the date of the second case of ILI. The data were analyzed at the individual level (level 1) and institutional level (level 2) using a hierarchical (also known as multilevel) logistic regression model with Laplace maximum likelihood approximation. This analysis was conducted using the following stepwise approach.
1. An empty model was used to determine the variation within institutions and between institutions (ie, intraclass correlation or ICC).
2. The 11 independent variables listed above were included in the model as level 2 variables and were individually modeled with the outcome variable.
3. The independent variables were added in a stepwise forward modelling strategy to determine the best multivariable main- effects model, including both statistically and clinically significant variables.
4. The continuous variables were assessed for linearity to determine whether any variable transformations were needed.
5. Model variables were assessed for a collinearity problem. 6. The final main-effects model was extended by adding any significant interactions between the time to oseltamivir prophylaxis and other main-effects model variables.
All analyses were 2-tailed and were conducted at an α of 0.05. The power was >99%.
Results
We identified 94 influenza A H3N2 outbreaks in LTC facilities during the 2014–2015 influenza season. After applying the exclusion criteria, 53 influenza outbreaks remained for analysis (Fig. 1). The summary of the characteristics of those 53 influenza outbreaks can be seen in Table 1. In total, there were 5,258 residents in the 53 facilities. A plot of the secondary attack rate versus time from the start of the outbreak to initiation of che- moprophylaxis can be seen in Fig. 2.
Data analysis
The ICC was calculated by taking an empty model and dividing the between-group variance by the sum of the within-group variance plus the between-group variance. The ICC for these data was 27%. Therefore, the outcomes were significantly correlated with the institutions that the residents resided in and hierarchical logistic regression was needed to analyze these data. Using a univariate analysis, 5 of the 11 independent vari-
ables were statistically significant (Table 2): the number of days from the second case to starting oseltamivir (t=5.41; df=51;
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