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Williamson County Cryptosporidiosis Updates
As of 12/2/2008, 138 confirmed and probable cases of cryptosporidiosis have been reported to the
Williamson County and Cities Health District (WCCHD) for 2008. The symptoms for
all but four of these cases started in July or later.
2008 Cryptosporidiosis Statistics (as of 12/2/08)
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Hospitalizations:
2008 Williamson County hospitalizations due to Crypto
infections= 2 |
On 8/20/08, in response to increased incidence of crypto throughout Texas,
the Texas Department of State Health Services (DSHS) has requested that public
health departments report both confirmed and probable crypto cases to DSHS.
Case Classification of 2008 Williamson County
Cryptosporidiosis Cases
|
Case Classification |
% Cases (Case Count) |
|
Probable |
40% (55/138) |
|
Laboratory Confirmed |
60% (83/138) |
Gender of 2008 Williamson County Cryptosporidiosis
|
Gender |
% Cases (Case Count) |
|
Female |
46% (64/138) |
|
Male |
54% (74/138) |
Age of 2008 Williamson County
Cryptosporidiosis Cases
|
Age Range (Years) |
% Cases (Case Count) |
|
<1 |
1% (2/138) |
|
1 - 4 |
23% (31/138) |
|
5 - 14 |
30% (41/138) |
|
15 - 24 |
7% (10/138) |
|
25 - 39 |
31% (43/138) |
|
40 - 64 |
7% (10/138) |
|
>64 |
1% (1/138) |
Williamson County 2008
Cryptosporidiosis Cases by Area
|
Area* |
# of Cases |
|
Round Rock |
50 |
|
Cedar Park |
27 |
|
Hutto |
17 |
|
Leander |
16 |
|
Georgetown |
12 |
|
Austin |
11 |
|
Taylor |
3 |
|
Granger |
1 |
|
Liberty Hill |
1 |
|
Total |
138 |
*Areas defined by one or more zip code boundaries. Parts of zip codes located outside Williamson County are excluded.
Epidemic Curve (Epi Curve)
The epidemic curve (epi curve) shows progression of an outbreak over time. The horizontal axis represents the date when a person became ill, also called the date of onset. The vertical axis is the number of persons who became ill on each date. The epi curve is updated as new data come in. Epi curves are complex and may be incomplete. Consider the following issues when interpreting epi curves:
- There is an inherent delay between the date that an illness starts, and the date that the case is reported to public health authorities.
- For most conditions, some background cases of illness are likely to occur that would have occurred even without an outbreak. This makes it difficult to say exactly which case is the first case in an outbreak.
- For some cases, the date when they became ill is not known.
- It can be difficult to determine when cases start to decline because of the reporting delay. This can become clearer as time passes.
- It can be difficult to say when an outbreak is over, because of the reporting delay.
Additional Charts
Because previous years required reporting of confirmed cases only, in the
charts below comparisons across years were limited to confirmed cases.
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