Details:

Alternative Title:
PLoS One
Personal Author:
Archer, Brett N. ; Tempia, Stefano ; White, Laura F. ; Pagano, Marcello ; Cohen, Cheryl
Archer, Brett N. ; Tempia, Stefano ; White, Laura F. ; Pagano, Marcello ; Cohen, Cheryl Less -
Description:
Background/Objective

Describing transmissibility parameters of past pandemics from diverse geographic sites remains critical to planning responses to future outbreaks. We characterize the transmissibility of influenza A(H1N1)pdm09 (hereafter pH1N1) in South Africa during 2009 by estimating the serial interval (SI), the initial effective reproductive number (initial Rt) and the temporal variation of Rt.

Methods

We make use of data from a central registry of all pH1N1 laboratory-confirmed cases detected throughout South Africa. Whenever date of symptom onset is missing, we estimate it from the date of specimen collection using a multiple imputation approach repeated 100 times for each missing value. We apply a likelihood-based method (method 1) for simultaneous estimation of initial Rt and the SI; estimate initial Rt from SI distributions established from prior field studies (method 2); and the Wallinga and Teunis method (method 3) to model the temporal variation of Rt.

Results

12,360 confirmed pH1N1 cases were reported in the central registry. During the period of exponential growth of the epidemic (June 21 to August 3, 2009), we simultaneously estimate a mean Rt of 1.47 (95% CI: 1.30–1.72) and mean SI of 2.78 days (95% CI: 1.80–3.75) (method 1). Field studies found a mean SI of 2.3 days between primary cases and laboratory-confirmed secondary cases, and 2.7 days when considering both suspected and confirmed secondary cases. Incorporating the SI estimate from field studies using laboratory-confirmed cases, we found an initial Rt of 1.43 (95% CI: 1.38–1.49) (method 2). The mean Rt peaked at 2.91 (95% CI: 0.85–2.91) on June 21, as the epidemic commenced, and Rt>1 was sustained until August 22 (method 3).

Conclusions

Transmissibility characteristics of pH1N1 in South Africa are similar to estimates reported by countries outside of Africa. Estimations using the likelihood-based method are in agreement with field findings.


Subjects:
[+]
Algorithms Computer Simulation Disease Outbreaks Humans Influenza, Human Influenza A Virus, H1N1 Subtype Models, Statistical Pandemics Registries
Source:
PLoS One. 2012; 7(11).
Pubmed ID:
23166682
Pubmed Central ID:
PMC3500305
Document Type:
Journal Article
Funding:
5U51/IP000155/IP/NCIRD CDC HHS/United States ; U54GM088558/GM/NIGMS NIH HHS/United States
5U51/IP000155/IP/NCIRD CDC HHS/United States ; U54GM088558/GM/NIGMS NIH HHS/United States Less -
Place as Subject:
South Africa
Collection(s):
CDC Public Access
Main Document Checksum:
[+]
urn:sha256:3cdb566251bafffc6e6c18886ab16f292ee1b4acc109a84b70883a894255eeae
Download URL:
https://stacks.cdc.gov/view/cdc/11088/cdc_11088_DS1.pdf
File Type:

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