Potential number of human cases of H5N1 avian influenza in Egypt.
OBJECTIVE
H5N1 is one of the avian influenza virus subtypes that has the potential to evolve into a global pandemic that could cause millions of human deaths and great economic losses. Cases involving humans have occurred in 15 countries. Costly interventions have been used by governments and health organisations. Thus, a challenging question arises regarding how many cases of the disease may actually have been prevented as a result of such interventions.


METHODS
This paper answers such a question by applying a statistical model to the 2006-January 2009 outbreak in Egypt. Egypt was chosen as it had the highest number of human avian influenza cases outside Asia, and the second highest number in that period worldwide.


METHODS
Brookmeyer and Blades' statistical model was applied. The sensitivities of the estimated number of human cases and exposure dates to the assumed incubation period, the delay in intervention and the coverage/effectiveness of the intervention were investigated.


RESULTS
In the absence of intervention, it appears that the outbreak could have been approximately 1.5 times as large, but it is unlikely it would have exceeded 150 cases.


CONCLUSIONS
The results underscore the importance of early detection of an outbreak and intervention, together with effective public health control measures.
Tseng
W-C
WC
Department of Applied Economics, National Chung-Hsing University, 250 Kuo-Kuang Road, Taichung 40246, Taiwan. tweichun2@hotmail.com
Li
H-A
HA
Huang
W-C
WC
Liang
L-H
LH
D000328:Adult; D000818:Animals; D001717:Birds; D002648:Child; D002675:Child, Preschool; D016000:Cluster Analysis; D016001:Confidence Intervals; D004196:Disease Outbreaks / Q000706:statistics & numerical data; D004534:Egypt / Q000453:epidemiology; D005260:Female; D006801:Humans; D053124:Influenza A Virus, H5N1 Subtype; D007251:Influenza, Human / Q000175:diagnosis / Q000453:epidemiology*; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D018570:Risk Assessment