Transmission dynamics and risk factors for pandemic H1N1‐related illness: outbreak investigation in a rural community of British Columbia, Canada

Abstract

Please cite this paper as: Janjua et al. (2012) Transmission dynamics and risk factors for pandemic H1N1‐related illness: outbreak investigation in a rural community of British Columbia, Canada. Influenza and Other Respiratory Viruses 6(3), e54–e62. Objective To characterize the first‐wave epidemiologic features of influenza‐like illness (ILI) associated with the novel pandemic A/H1N1 [A(H1N1)pdm09] virus. Methods We used generalized linear mixed models (GLMM) to assess risk factors and non‐parametric and/or parametric distributions to estimate attack rates, secondary attack rates (SAR), duration of illness, and serial interval during a laboratory‐confirmed community outbreak of A(H1N1)pdm09 clustered around on‐reserve residents and households of an elementary school in rural British Columbia, Canada, in late April/early May 2009. ILI details were collected as part of outbreak investigation by community telephone survey in early June 2009. Results Overall, 92/408 (23%) of participants developed ILI and 36/408 (9%) experienced medically attended ILI (MAILI). The overall SAR in households was 22%: highest among participants 1–4 years of age (yoa) (50%) followed by <1 yoa (38%), 5–8 yoa (20%), 10–19 yoa (13%), 20–49 yoa (20%), and 50–64 yoa (0%). The median serial interval was estimated at 3·5 days (95% CI: 2·1–5·1). In multivariable GLMM analysis, having a chronic condition (OR: 2·58; 95% CI: 1·1–6·04), younger age [1–8 yoa: OR: 4·63; 95% CI: 2·25–9·52; 9–19 yoa: OR: 1·95; 95% CI: 0·97–3·9 (referent: ≥20 yoa)] and receipt of 2008–2009 influenza vaccine (OR: 2·68; 95% CI: 1·37–5·25) were associated with increased risk of ILI. Median duration of illness was 9 days, longer among those with chronic conditions (21 days). Median time to seeking care after developing illness was 4·5 days. On‐reserve participants had higher chronic conditions, household density, ILI, MAILI, and SAR. Conclusions During a community outbreak of A(H1N1)pdm09‐related illness, we identified substantial clinical ILI attack rates exceeding 20% with secondary household attack rates as high as 50% in young children. The serial interval was short suggesting a narrow period to prevent transmission.

An outbreak of influenza A (H1N1) virus in a remote Aboriginal community post‐pandemic: implications for pandemic planning and health service policy

“…Secondly, female cases predominated in the adult age group, potentially a reflection of differences in health seeking behaviour between genders, and/or differences in child‐care responsibilities. Thirdly, as reported elsewhere, there were high age‐specific attack rates in the younger age groups 7,11,29,30 …”

“…While the epidemiology of A(H1N1)pdm09 has been well described in many populations, 22,30–32 data regarding the effect of H1N1 on remote Australian Aboriginal populations have remained scarce 1 . To our knowledge there are no other published reports of a pandemic influenza outbreak in a remote Australian community for comparison.…”

Household Transmission of Influenza Virus

“…We conducted a review of household transmission studies of influenza, explored the typical design and implementation of these studies, and contrasted and compared their major findings. We identified 56 relevant published studies (see Tables S1 and S2 in the supplemental information online) 34 , 35 , 38 , 40 , 42 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 . In the following sections, we describe the key design features of transmission studies and summarize the scientific findings of these studies in terms of the basic transmissibility of influenza viruses in households, the factors affecting transmission, and the effectiveness of specific control measures in household settings.…”

“…Factors affecting susceptibility can be explored by comparing the number of secondary cases in household contacts with or without a particular characteristic, while factors affecting infectivity can be explored by comparing the number of secondary cases from index cases with or without a specific characteristic. Most studies explored the factors affecting susceptibility or infectivity using Fisher's exact test, Chi-squared tests, or logistic regression, with 35 , 45 , 47 , 58 , 64 , 65 , 71 , 76 , 82 , 90 or without 49 , 50 , 51 , 57 , 59 , 60 , 61 , 78 , 79 , 85 adjustment for clustering of secondary infections within households, although these approaches assumed that all infections in household contacts were secondary cases infected from index cases and ignored the possibility of tertiary cases or infections acquired from outside the household. In a few studies, more complex models were used to relax these assumptions, such as household transmission models that estimated the probability of person-to-person transmission in households and community infection acquired from outside the household 38 , 42 , 52 , 88 or other type of transmission models based on final size data 62 , 89 .…”

“…It suggested that treatment could reduce onwards transmission. In those observational studies that explored the protection associated with vaccination, only two studies reported significant protection among vaccinated persons 64 , 88 . Possible reasons included insufficient sample sizes to identify moderate vaccine effectiveness, mismatches between circulating strains and vaccine strains, or lower vaccine effectiveness against infection in the household setting.…”