SCHISTOSOMIASIS RESEARCH PROJECT
EPI 123
FINAL ANALYSIS REPORT
ROUND ONE DATA
FAYOUM GOVERNORATE
SUBMITTED :
TO SECRETARIAT OF SRP
BY CORE TEAM
Members of The Core Team:
Prof. Dr. Mohamed Hasan Husein, PI
Prof. F. DeWolfe Miller, USA Collaborator
Dr. Medhat Kamal ElSayed, Deputy PI
Dr. Maha Talaat, Co-PI
Prof. Dr. Amal El-Badawy, Co-PI
Prepared by: Prof. Dr. Amal El-Badawy
TABLE OF CONTENT
INTRODUCTION .......................................................
OBJECTIVES ...................................................
SAMPLE DESIGN AND SAMPLE SELECTION ...........................
DATA COLLECTION AND DATA RECORDING ...........................
DATA ANALYSIS ................................................
DROP OUT RATES ...............................................
COMMENTS .....................................................
1
1
2
2
3
5
6
RESULTS ............................................................
TESTING SAMPLE VERSUS TOTAL CENSUS ...........................
OBJECTIVE EPI 1 ..............................................
PREVALENCE OF S. haematobium IN URINE AND GEOMETRIC
MEAN EGG COUNT IN DIFFERENT EZBAS OR SATELLITES ...
PREVALENCE OF S. haematobium IN URINE AND
GEOMETRIC MEAN EGG COUNT BY DISTRICT ..............
AGE AND SEX DISTRIBUTION OF S. haematobium IN URINE
AND GEOMETRIC MEAN EGG COUNT ......................
AGE AND SEX DISTRIBUTION OF S. haematobium AND
GEOMETRIC MEAN EGG COUNT ..........................
PREVALENCE OF S. haematobium IN URINE AND GEOMETRIC
MEAN EGG COUNT BY LEVEL OF EDUCATION ..............
PREVALENCE OF S. haematobium IN URINE AND GEOMETRIC
MEAN EGG COUNT BY OCCUPATION ......................
PREVALENCE OF S. haematobium IN URINE AND GEOMETRIC
MEAN EGG COUNT BY HISTORY OF PREVIOUS TREATMENT
FOR BILHARZIASIS ..................................
PREVALENCE OF S. haematobium IN URINE AND GEOMETRIC
MEAN EGG COUNT BY HISTORY OF PREVIOUS INFECTION
WITH BILHARZIASIS .................................
PREVALENCE OF S. haematobium IN URINE AND GEOMETRIC
MEAN EGG COUNT BY BATHING IN CANAL WATER ..........
PREVALENCE OF S. haematobium IN URINE AND GEOMETRIC
MEAN EGG COUNT BY WASHING IN CANAL WATER ..........
PREVALENCE OF S. haematobium IN URINE AND GEOMETRIC
MEAN EGG COUNT ACCORDING TO THE DEGREE OF USING
CANAL IN WASHING ..................................
PREVALENCE OF S. haematobium IN URINE AND GEOMETRIC
MEAN EGG COUNT BY PLAYING IN CANAL WATER ..........
PREVALENCE OF S. haematobium IN URINE AND GEOMETRIC
MEAN EGG COUNT ACCORDING TO THE DEGREE OF PLAYING
IN CANAL WATER ....................................
PREVALENCE OF S. mansoni IN STOOL AND GEOMETRIC MEAN
EGG COUNT IN DIFFERENT EZBAS OR SATELLITES ........
PREVALENCE OF S. mansoni IN STOOL AND GEOMETRIC MEAN
EGG COUNT BY DISTRICT .............................
PREVALENCE OF S. mansoni IN STOOL AND GEOMETRIC MEAN
EGG COUNT BY AGE AND SEX ..........................
AGE AND SEX DISTRIBUTION OF S. mansoni AND GEOMETRIC
MEAN EGG COUNT ...................................
PREVALENCE OF S. mansoni IN STOOL AND GEOMETRIC MEAN
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EGG COUNT BY LEVEL OF EDUCATION ...................
PREVALENCE OF S. mansoni IN STOOL AND GEOMETRIC MEAN
EGG COUNT BY OCCUPATION ...........................
PREVALENCE OF S. mansoni IN STOOL AND GEOMETRIC MEAN
EGG COUNT BY HISTORY OF PREVIOUS TREATMENT FOR
BILHARZIASIS ......................................
PREVALENCE OF S. mansoni IN STOOL AND GEOMETRIC MEAN
EGG COUNT BY HISTORY OF PREVIOUS INFECTION WITH
BILHARZIASIS ......................................
PREVALENCE OF S. mansoni IN STOOL AND GEOMETRIC MEAN
EGG COUNT BY BATHING IN CANAL WATER ...............
PREVALENCE OF S. mansoni IN STOOL AND GEOMETRIC MEAN
EGG COUNT BY WASHING IN CANAL WATER ...............
PREVALENCE OF S. mansoni IN STOOL AND GEOMETRIC
MEAN EGG COUNT ACCORDING TO THE DEGREE OF
USING CANAL WATER IN WASHING ......................
PREVALENCE OF S. mansoni IN STOOL AND GEOMETRIC MEAN
EGG COUNT BY PLAYING IN CANAL WATER ...............
PREVALENCE OF S. mansoni IN STOOL AND GEOMETRIC MEAN
EGG COUNT ACCORDING TO THE DEGREE OF PLAYING IN
CANAL WATER .......................................
OBJECTIVE EPI 2 ..............................................
ENVIRONMENTAL CHARACTERISTICS OF DWELLING UNITS
(HOUSES) AND ITS RELATIONSHIP TO SCHISTOSOMIASIS
INFECTION INSIDE THE HOUSE ........................
RESULTS OF MULTIPLE REGRESSION ANALYSIS USING STEPWISE
METHOD FOR ENVIRONMENTAL CHARACTERISTICS OF
HOUSES AND ITS RELATION TO INFECTION INSIDE THE
HOUSE ............................................
OBJECTIVE EPI 3 ..............................................
DISTRIBUTION OF LIVER FIBROSIS IN THE DIFFERENT EZBAS
OR SATELLITES .....................................
AGE SEX DISTRIBUTION OF LIVER FIBROSIS ..................
DISTRIBUTION OF LIVER FIBROSIS ACCORDING TO HISTORY OF
PREVIOUS INFECTION WITH BILHARZIASIS ..............
AGE SEX DISTRIBUTION OF LIVER MORBIDITY .................
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33
34
35
36
37
38
39
41
42
43
40
45
46
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ANALYSIS REPORT FOR EPI 123
FAYOUM GOVERNORATE
INTRODUCTION
The present document reports on the findings in the data
collected for the epidemiological study EPI 123 for the Fayoum
Governorate. The field team was lead by Dr. M. Farid Abdel-Wahab.
Other members of the field team included Drs. Eman Medhat, Gamal
Esmat, Shaker Narooz, Iman Ramzy, and Yasser El-Boraey.
The report starts by a brief reminder of the objectives,
sample design and data recording. It also includes a description
of the direction of analysis with limitations found in the data
collected. Finally; the document include the findings tabulated
and organized according to the objectives.
OBJECTIVES
EPI 123 survey was designed to provide epidemiological data
about schistosomiasis in Egypt that could be combined with data
from other directed research to allow MOH to more effectively
control schistosomiasis.
The EPI 123 survey, therefore, had three study objectives
which were as follows:
I. The First Objective (EPI 1):
The first objective was to describe the changing
patterns of S. haematobium and S. Mansoni infection and
intensity of infection independently in each of the nine
purposively selected governorates and also to identify major
transmission factors that could explain these changes.
II. The Second Objective (EPI 2):
The second objective was to identify factors that
explain the variation in schistosomiasis prevalence and
intensity of infection among villages.
Analysis Report Fayoum Gov
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III. The Third Objective (EPI 3):
The third objective was to describe the public health
impact of schistosomiasis morbidity. The ultrasonographic
measures of morbidity were the main outcome of interest.
Also to identify determinants of this morbidity.
SAMPLE DESIGN AND SAMPLE SELECTION
In brief, the sample selection; designed to achieve the
above stated objectives, was a multi-stage probability sample
selection. Within each governorate, villages were selected by
stratified random sampling technique. Stratification of villages
was made by District. Ezbas (satellites) were selected within
each village by a stratified random selection process.
Stratification of ezbas within villages was based on the number
of houses in each ezba. Houses were selected within each ezba by
a systematic random sampling techniques. Finally; all individuals
living in the selected houses were recruited in the sample.
Individuals living in only 20% of the selected houses were
identified for ultrasound and clinical examination.
DATA COLLECTION AND DATA RECORDING
Data were collected on specially developed data forms. The
forms included:
. Roster
:
Considered as a complete list of all
individuals selected in the sample.
. House
:
Included environmental data about houses (and
dwelling units) selected in the sample.
. Person
:
Included personal demographic data, history
of previous infection, previous treatment and
water contact behavior.
. Stool
:
There were three stool forms that included
data about stool characteristics,
schistosomiasis ova count as well as other
parasitic infection.
. Urine
:
There were two urine forms for the collection
Analysis Report Fayoum Gov
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of urine data that included the
schistosomiasis ova count and dip stick
findings in the urine.
. Ultrasound:
Included data about ultrasound measurements
for the liver, spleen and urinary system.
. Clinical
Included some clinical findings.
:
Special computer screen data forms were developed in Arabic
and English languages to enter data on computers. These forms
were complied in a specially developed program. Data entry used
the software called EPI INFO 5.
DATA ANALYSIS
The software called Survey Data Analysis (SUDAAN) was used
in the final analysis. This software has the advantage of
including the probability of selection and thereby can provide
estimate that are representative to the population from which the
sample was drawn. It also has the advantage of adjusting for non
response. The use of this software was essential because of the
complexity of the sample design.
Table 1 shows the identified sample distributed by district,
village and ezba. The table shows the number of households
identified through the sample design in each ezba.
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TABLE 1:
DISTRICT
ABSHAWAY
SENNORES
EL-FAYOUM
SAMPLE SELECTED
VILLAGE
Kafr-Abboud
Monshaat
Sennores
Senofar
EZBA
Kafr-Abboud
92
Abdel-Alim Ibrahim
93
Wahdan
87
Amin Fanous El-Bahria
14
Mohamed Mostafa Osman
12
Senofar
El-Wabour
TAMIA
Khalaf Fayoum
Sersena
Monshaat Seif
El-Nasr
118
46
5
Khalaf Fayoum
79
Shaker
72
Badr-Khan
21
El-Bitar
20
Sersena
100
Abu-Kelib
48
Besseis Mohamed
34
Mahgoub El-Gebali
ATSA
110
El-Tamawi
Mohamed Genedy
ATSA
NUMBER OF
SAMPLED
HOUSES
9
Monshaat Seifel-Nasr
77
El-Kashaf Abdel Gelil
62
Hafaz Hussein
17
Abdel-Hafiz Allak
TOTAL SAMPLED HOUSHOLDS
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1151
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DROP OUT RATES
The sample design lead to the identification of 1151
households to be recruited. The number of households actually
recruit in the sample was 1210 households. Only 90 households
were either found empty or refused co-operation and these
represented 7.4% household drop out. The number of individuals
living in the households actually recruit were 7733 individuals.
Individuals that did not respond to person interview were 550
individuals representing 7.1% person drop out. Of the 7733
individuals, only 2591 individuals did not have stool results
representing 33.5% stool drop out and 2509 individuals did not
have urine results representing 32.4% urine drop out. The number
of individuals identified for ultrasound examination were 1584
individuals. Only 1089 individuals had ultrasound data.
Accordingly the drop out rate for ultrasound examination was
31.3%. Table 2 summarizes the drop out rate for different
parameters.
TABLE 2:
DROP OUT RATES
ITEM
REFERENCE FOR DROP OUT CALCULATION
HOUSE
SAMPLE OF HOUSEHOLDS
7.4%
PERSON
INDIVIDUALS IDENTIFIED TO BE LIVING
THE RECRUITED HOUSEHOLDS
7.1%
STOOL
INDIVIDUALS IDENTIFIED TO BE LIVING
THE RECRUITED HOUSEHOLDS
33.5%
URINE
INDIVIDUALS IDENTIFIED TO BE LIVING
THE RECRUITED HOUSEHOLDS
32.4%
ULTRASOUND
INDIVIDUALS SAMPLED FOR ULTRASOUND
31.3%
% DROP OUT
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COMMENTS

There was limited involvement by the Core design and
analysis team in the implementation of the Fayoum field work
and data collection phase. This constraint was placed on the
Core team at the request of the Fayoum team leaders. The
impacted on the study in a number of ways some of which are
indicated below.

The number of households recruited was more than that
identified by the sample selection. The census carried out
by the field team was most probably inaccurate especially in
small villages.

The number of individuals recorded to be living in each
households was different in different forms (Roster, House
and Person).

The drop out rates were only acceptable for house and person
data. Stool, urine and ultrasonographic data had a high drop
out rates reaching 33.5%, 32.4% and 31.4% respectively.

Two villages number 9 and 21 had no ultrasonographic data.
RESULTS
TESTING SAMPLE VERSUS TOTAL CENSUS
The actual sample of individuals were examined for the age
and sex distribution. Age groups of five years were used. The age
and sex distribution of the whole rural population was obtained
from the 1986 census of the Central Agency for Population
Mobilization and Statistics (CAPMAS). This was used as an
indication for how far the sample drawn was representative of the
population from which it was drawn.
Figure 1 shows the age and sex distribution of the actually
sampled individuals versus the total census. The figure gives a
clear idea for how far the actual sample was representative for
the total rural population for the governorate. The largest
differences were in the two youngest age groups. The 0 to 4 were
under represented and the 5 to 9 were over represented. The large
size of these two age groups must also be borne in mind.
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FIGURE 1:
TESTING SAMPLE VERSUS RURAL POPULATION
20
18
16
TOTAL CENSUS
TOTAL SAMPLE
14
12
10
8
6
4
2
0
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60+
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OBJECTIVE EPI 1
Objective EPI 123 was achieved as a description of the
prevalence and intensity of infection for both S. mansoni and S.
haematobium according to different parameters. First, the pattern
of distribution of the type of infection and its intensity over
the governorate will be presented in different ezbas (or
satellites).
The burden of infection will be described in different age
groups, sex, occupation, level of education and according to some
water contact behavior (e.g. bathing in canals, washing clothes
in canals and playing in canals).
Analysis Report Fayoum Gov
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TABLE 3: PREVALENCE OF S. haematobium IN URINE AND GEOMETRIC
MEAN EGG COUNT IN DIFFERENT EZBAS OR SATELLITES
VILLAGE / SATELLITE
N1
EXAMINED
PREV.  S.E.
GMEC
 S.E.
10ml URINE
%
KAFR ABBOUD
557
14.52  0.35
6.37  0.23
EZBET EL-TAMAWI
396
19.26  0.41
11.92  0.47
ABDEL-ALIM IBRAHIM
552
20.51  0.18
10.26  0.14
WAHDAN
426
5.13  0.05
5.05  0.06
AMIN FANOUS EL-BAH
73
0  0
...
MOHAMED MOSTAFA OSMAN
85
3.24  0.09
1.26  0.01
SENOFAR
553
14.06  0.33
10.93  0.36
EZBET MOHAMED GENEDY
229
13.61  0.23
8.85  0.17
19
24.82  0.41
8.21  0.26
EZBET EL-WABOUR
KHALAF FAYOUM
340
1.34  0.07
1.70  0.04
EZBET SHAKER
240
5.45  0.12
3.46  0.10
EZBET EL-BITAR
86
0  0
...
EZBET BADR-KHAN
83
4.92  0.20
5.03  0.05
SERSENA
439
6.47  0.27
8.21  0.83
EZBET ABOU-KELIB
170
13.51  0.64
13.81  0.98
EZBET BESSEIS MOHAMED
163
12.34  0.22
26.57  0.89
EZBET MAHGOUB EL-GEBALI
141
26.97  0.31
22.53  0.59
MONSHAAT SEIF EL-NASR
307
27.15  0.30
11.82  0.23
EZBET EL-KASHEF & ABDEL-GELIL ELSE'EDAWY
270
23.11  0.55
23.13  1.05
EZBET HAFEZ HUSSEIN
70
20.28  0.42
13.17  0.23
EZBET ABDEL-HAFIZ ALAK
25
20.51  0.50
16.81  0.78
5224
13.69  1.40
9.95  1.11
TOTAL
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TABLE 4:
DISTRICT
PREVALENCE OF S. haematobium IN URINE AND
GEOMETRIC MEAN EGG COUNT BY DISTRICT
NUMBER
EXAMINED
PREV.%  S.E.
GMEC
 S.E.
10ml URINE
ABSHAWAY
953
15.16  0.31
7.10  0.22
SENNORAS
1136
14.91  1.31
9.43  0.29
EL-FAYOUM
801
14.11  0.29
10.64  0.31
ATSA
1421
11.46  8.95
13.63  7.38
TAMIA
913
10.08  0.45
14.19  0.70
5224
13.69  1.40
9.95  1.11
TOTAL
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TABLE 5:
AGE AND SEX DISTRIBUTION OF S. haematobium IN URINE
AND GEOMETRIC MEAN EGG COUNT
AGE / SEX
N1
EXAMINED
PREV.  S.E.
%
8.16  1.73
6.56  2.87
9.91  2.58
15.24  3.64
14.06  3.90
16.17  4.41
GMEC
 S.E.
10ml URINE
0-4
TOTAL
MALE
FEMALE
645
348
297
5-9
TOTAL
MALE
FEMALE
1097
584
513
18.61  2.58
19.01  2.97
18.14  3.37
12.37  2.38
13.71  3.23
10.93  2.20
10-14 TOTAL
MALE
FEMALE
807
419
388
24.20  2.16
27.15  2.22
20.90  2.77
10.42  0.69
11.66  1.00
8.85  0.85
15-19 TOTAL
MALE
FEMALE
519
288
231
18.94  2.47
21.47  3.13
15.29  2.97
10.27  2.28
10.43  2.30
9.95  3.29
20-24 TOTAL
MALE
FEMALE
349
142
207
17.77  1.05
23.15  2.36
11.15  2.94
9.26  2.05
11.97  2.81
4.79  1.22
25-29 TOTAL
MALE
FEMALE
337
131
206
10.28  0.84
12.14  1.65
8.52  1.05
5.21  2.32
4.70  2.03
6.00  3.40
30-34 TOTAL
MALE
FEMALE
260
110
150
7.60  3.13
12.19  5.86
2.12  1.20
17.98  6.72
25.60  5.29
1.59  0.31
35-39 TOTAL
MALE
FEMALE
263
102
161
5.74  1.44
8.51  4.06
3.24  1.45
4.03  1.46
4.69  1.86
2.81  1.02
40-44 TOTAL
MALE
FEMALE
208
106
102
11.16  2.23
13.81  1.44
7.38  4.04
3.63  0.95
3.70  1.18
3.45  2.11
45-49 TOTAL
MALE
FEMALE
165
72
93
3.49  1.76
6.57  3.29
0.60  0.68
2.96  1.56
2.66  1.32
8.74  0.22
50-54 TOTAL
MALE
FEMALE
164
65
99
8.73  2.39
10.68  4.59
7.16  1.05
5.16  1.21
8.97  7.35
2.65  1.24
55-59 TOTAL
MALE
FEMALE
125
67
58
3.33  1.84
5.88  3.29
0.21  0.24
8.86  2.63
9.15  2.68
3.00  0
60-64 TOTAL
MALE
FEMALE
127
50
77
7.50  1.66
7.67  5.06
7.36  2.74
10.03  2.54
6.10  0.89
12.61  2.92
65-69 TOTAL
MALE
FEMALE
51
27
24
3.66  3.40
6.29  5.21
1.00  0
1.00  0
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70
+
TOTAL
MALE
FEMALE
107
52
55
1.31  1.34
1.00  0
1.37  0.68
2.41  1.46
0.53  0.58
1.00  0
1.00  0
1.00  0
5224
13.69  1.40
9.95  1.11
MALE
2563
15.75  1.71
10.67  1.49
FEMALE
2661
11.38  1.91
8.94  0.99
TOTAL
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FIGURE 2: AGE AND SEX DISTRIBUTION OF S. haematobium AND GEOMETRIC
MEAN EGG COUNT
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TABLE 6:
PREVALENCE OF S. haematobium IN URINE AND GEOMETRIC
MEAN EGG COUNT BY LEVEL OF EDUCATION
N1
EXAMINED
PREV.  S.E.
%
PRIMARY
963
14.57  2.07
8.62  1.74
PREPARATORY &
SECONDARY
478
12.77  2.53
8.49  1.33
UNIVERSITY
20
7.92  7.02
1.38  0.54
BELOW AGE
1010
11.18  1.92
12.77  3.38
DIDN'T VISIT SCHOOL
2646
15.03  1.89
10.10  1.72
TOTAL
5117
13.92  1.38
9.93  1.11
LEVEL OF EDUCATION
GMEC
 S.E.
10ml URINE
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TABLE 7: PREVALENCE OF S. haematobium IN URINE AND GEOMETRIC
MEAN EGG COUNT BY OCCUPATION
N1
EXAMINED
PREV.  S.E.
%
FARMER
686
18.78  2.19
8.18  1.41
FARMING LABORER
30
22.62  16.76
3.98  0.49
SKILLED LABORER
24
22.46  5.82
6.86  3.57
1319
8.10  1.99
6.66  0.57
PROFESSIONAL
28
0  0
...
CLERK
19
10.10  5.56
3.81  4.61
STUDENT
887
15.17  2.34
9.23  1.47
LABORER
49
20.10  1.80
3.12  0.34
ORZOKI
63
16.58  3.27
28.26  8.41
MERCHANT
11
7.65  8.45
MEKAWEL
2
30.31  29.70
FISHERMEN
4
0  0
...
OTHER JOB
106
8.36  5.53
45.78  23.51
NOT WORKING
250
17.57  2.90
22.01  6.45
NOT APPLIED
1639
15.23  2.09
11.88  1.1
TOTAL
5117
13.92  1.38
OCCUPATION
HOUSEWIFE
 S.E.
GMEC
10ml URINE
18.00  0
3.00  0
9.93  1.11
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TABLE 8:
PREVALENCE OF S. haematobium IN URINE AND GEOMETRIC
MEAN EGG COUNT BY HISTORY OF PREVIOUS TREATMENT
FOR BILHARZIASIS
N1
EXAMINED
PREV.  S.E.
%
YES
973
15.97  2.06
NO
4051
13.58  1.55
10.27  1.24
90
6.54  2.39
5.75  2.88
5114
13.93  1.38
9.95  1.09
WERE YOU TREATED
FOR SCHISTO
BEFORE ?
DON'T KNOW
TOTAL
TABLE 9:
GMEC
 S.E.
10ml URINE
9.08  2
PREVALENCE OF S. haematobium IN URINE AND GEOMETRIC MEAN
EGG COUNT BY HISTORY OF PREVIOUS INFECTION WITH
BILHARZIASIS
N1
EXAMINED
PREV.  S.E.
YES
994
15.83  1.98
9.39  1.97
NO
2470
14.45  1.81
10.15  2.16
DON'T KNOW
1650
11.87  1.71
10.05  1.22
TOTAL
5114
13.92  1.38
9.95  1.09
DID YOU GET
SCHISTO BEFORE ?
%
GMEC
 S.E
10ml URINE
Analysis Report Fayoum Gov
16
TABLE 10: PREVALENCE OF S. haematobium IN URINE AND GEOMETRIC MEAN
EGG COUNT BY BATHING IN CANAL WATER
N1
EXAMINED
PREV.  S.E.
%
NO
3413
11.98  1.46
9.65  1.36
< 1 WEEK
325
18.67  4.01
11.20  4.29
1-4 WEEKS
169
18.77  4.11
5.83  2.66
1-12 MONTHS
520
23.70  2.97
12.88  1.63
1 YEAR AND MORE
660
13.29  1.68
9.10  1.11
DON'T REMEMBER
2
0  0
...
OTHER
25
10.15  0.94
2.96  0.30
NOT APPLIED
2
0  0
...
5116
13.93  1.38
9.94  1.09
LAST TIME TO
BATH IN CANAL
TOTAL
GMEC
 S.E.
10ml URINE
TABLE 11: PREVALENCE OF S. haematobium IN URINE AND GEOMETRIC MEAN
EGG COUNT BY WASHING IN CANAL WATER
LAST TIME TO
WASH CLOTHES IN
CANAL
N1
EXAMINED
PREV.  S.E. %
GMEC
 S.E.
10ml URINE
NO
3567
14.56  1.50
10.60  1.11
< 1 WEEK
835
16.18  1.99
9.79  2.60
1-4 WEEKS
204
9  2.28
5.70  0.93
1-12 MONTHS
186
14.26  1.47
6.26  1.94
1 YEAR AND MORE
307
5.03  1.29
5.81  1.47
DON'T REMEMBER
0
...
...
OTHER
7
28.60  2.40
4.22  0.77
NOT APPLIED
1
0  0
...
Analysis Report Fayoum Gov
17
TOTAL
5107
13.93  1.38
9.95  1.09
TABLE 12: PREVALENCE OF S. haematobium IN URINE AND GEOMETRIC MEAN
EGG COUNT ACCORDING TO THE DEGREE OF USING CANAL IN
WASHING
DO YOU ALWAYS USE
CANAL IN WASHING ?
N1
EXAMINED
PREV.  S.E.%
GMEC 
S.E.
10ml URINE
ALWAYS
545
14.55  2.82
6.58  1.47
SOMETIMES
784
12.11  1.35
8.70  0.77
RARELY
167
4.80  1.13
4.77  1.71
NEVER
1
0  0
...
TOTAL
1497
11.93  1.58
7.56  1.09
TABLE 13: PREVALENCE OF S. haematobium IN URINE AND GEOMETRIC MEAN
EGG COUNT BY PLAYING IN CANAL WATER
LAST TIME TO
PLAY IN CANAL
N1
EXAMINED
PREV. 
S.E.%
GMEC
 S.E.
10ml URINE
NO
3937
12.77  1.40
8.83  1.01
< 1 WEEK
818
17.96  2.25
11.98  2.91
1-4 WEEKS
148
18.76  6.72
14.63  9.37
1-12 MONTHS
160
23.68  4.57
20.07  6.10
1 YEAR AND MORE
34
3.74  3.13
5  0
DON'T REMEMBER
1
0  0
...
OTHER
10
5.75  0.96
2  0
NOT APPLIED
0
...
...
5108
13.92  1.38
9.93  1.1
TOTAL
Analysis Report Fayoum Gov
18
TABLE 14: PREVALENCE OF S. haematobium IN URINE AND GEOMETRIC MEAN
EGG COUNT ACCORDING TO THE DEGREE OF PLAYING IN CANAL
WATER
DO YOU ALWAYS PLAY
IN CANAL?
N1
EXAMINED
PREV.  S.E. %
GMEC 
S.E.
10ml URINE
ALWAYS
462
20.97  3.27
14.79  2.31
SOMETIMES
608
17.53  2.50
14.24  2.04
RARELY
62
12.49  2.23
5.94  0.61
NEVER
0
...
...
TOTAL
1132
18.44  2.62
13.91  1.89
Analysis Report Fayoum Gov
19
TABLE 15: PREVALENCE OF S. mansoni IN STOOL AND GEOMETRIC MEAN
EGG COUNT IN DIFFERENT EZBAS OR SATELLITES
VILLAGE / SATELLITE
N1
PREV.  S.E.
EXAMINED
%
GMEC
 S.E.
/gm STOOL
KAFR ABBOUD
542
1.06  0.10
24.40  1.94
EZBET EL-TAMAWI
386
0  0
...
ABDEL-ALIM IBRAHIM
569
8.85  0.12
40.33  0.63
WAHDAN
423
0.30  0.01
12.00  0
AMIN FANOUS EL-BAH
68
0  0
...
MOHAMED MOSTAFA OSMAN
86
1.02  0
...
SENOFAR
555
0.17  0.03
EZBET MOHAMED GENEDY
235
0  0
...
EZBET EL-WABOUR
18
0  0
...
KHALAF FAYOUM
351
25.70  0.29
62.39  1.00
EZBET SHAKER
246
34.30  0.27
48.65  0.45
EZBET EL-BITAR
90
30.79  0.37
47.13  0.88
EZBET BADR-KHAN
80
28.33  0.37
34.71  0.52
SERSENA
425
0.22  0.06
72.00  0
EZBET ABOU-KELIB
140
0.91  0.21
36.00  0
EZBET BESSEIS MOHAMED
144
0  0
...
EZBET MAHGOUB EL-GEBALI
132
0  0
...
MONSHAAT SEIF EL-NASR
301
0  0
...
EZBET EL-KASHEF &
ABDEL-GELIL EL-SE'EDAWY
261
0.50  0.08
EZBET HAFEZ HUSSEIN
65
24.00  0
12.00  0
...
Analysis Report Fayoum Gov
20
0  0
EZBET ABDEL-HAFIZ ALAK
TOTAL
25
4.08  0.20
24.00  0
5142
4.33  2.70
44.00  4.02
TABLE 16: PREVALENCE OF S. mansoni IN STOOL AND GEOMETRIC MEAN
EGG COUNT BY DISTRICT
NUMBER
EXAMINED
PREV.%  S.E.
ABSHAWAY
928
0.91  0.09
24.40  1.94
SENNORAS
1146
6.01  0.71
39.72  0.67
EL-FAYOUM
808
0.15  0.03
24.00  0
ATSA
1419
19.28  13.96
49.62  1.51
TAMIA
841
0.21  0.04
61.48  2.62
5142
4.33  2.70
44.00  4.02
DISTRICT
TOTAL
GMEC
 S.E.
/gm STOOL
Analysis Report Fayoum Gov
21
TABLE 17: PREVALENCE OF S. mansoni IN STOOL AND GEOMETRIC MEAN
EGG COUNT BY AGE AND SEX
AGE / SEX
N1
EXAMINED
PREV.  S.E.
GMEC
 S.E.
/gm STOOL
%
0-4
TOTAL
MALE
FEMALE
674
352
322
2.81  2.38
1.77  1.86
3.95  2.99
37.47  5.25
34.58  4.06
38.98  8.85
5-9
TOTAL
MALE
FEMALE
1068
571
497
6.58  4.68
8.78  6.17
4.03  3.03
43.65  8.55
44.78  10.85
40.93  4.00
75.19  9.97
86.78  9.93
39.49  17.21
10-14 TOTAL
MALE
FEMALE
804
420
384
7.49  4.88
11.93  7.58
2.52  1.85
15-19 TOTAL
MALE
FEMALE
512
282
230
5.11  3.44
7.84  5.24
1.19  0.81
27.33  5.73
29.13  6.12
14.90  2.53
20-24 TOTAL
MALE
FEMALE
330
137
193
2.10  1.37
3.80  2.55
0  0
37.88  4.16
37.88  4.16
...
25-29 TOTAL
MALE
FEMALE
332
131
201
4.90  2.02
8.00  3.27
1.97  0.94
40.72  9.68
42.20  14.02
35.49  8.92
30-34 TOTAL
MALE
FEMALE
252
110
142
2.07  1.20
2.12  1.25
2.00  1.20
59.07  25.51
174.06  133.07
14.96  2.66
35-39 TOTAL
MALE
FEMALE
259
100
159
3.59  1.83
5.67  2.75
1.71  1.05
28.90  4.39
26.58  6.09
37.12  7.54
40-44 TOTAL
MALE
FEMALE
198
107
91
2.16  1.25
3.36  1.91
0.44  0.45
29.50  5.28
30.07  6.26
24.00  0
45-49 TOTAL
MALE
FEMALE
164
69
95
1.86  1.31
2.24  2.19
1.51  1.39
44.07  16.87
68.21  15.71
24.00  0
50-54 TOTAL
MALE
FEMALE
161
65
96
1.34  1.50
2.57  2.85
0.36  0.41
53.14  2.90
48.00  1.97
96.00  0
55-59 TOTAL
MALE
FEMALE
120
64
56
5.66  2.51
9.66  4.14
0.76  0.81
32.06  3.03
34.15  4.96
12.00  0
60-64 TOTAL
MALE
FEMALE
121
50
71
3.35  1.72
6.98  3.32
0.53  0.55
33.72  21.39
37.30  22.97
12.00  0
65-69 TOTAL
MALE
FEMALE
49
25
24
2.76  2.93
5.85  6.25
0  0
19.43  0.97
19.43  0.97
...
Analysis Report Fayoum Gov
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70+ TOTAL
MALE
FEMALE
98
49
49
0  0
0  0
0  0
...
...
...
TOTAL
5142
4.33  2.70
44.00  4.02
MALE
2532
6.21  3.75
47.43  4.55
FEMALE
2610
2.23  1.56
35.05  7.11
TOTAL
Analysis Report Fayoum Gov
23
FIGURE 3: AGE AND SEX DISTRIBUTION OF S. mansoni AND GEOMETRIC MEAN
EGG COUNT
Analysis Report Fayoum Gov
24
TABLE 18: PREVALENCE OF S. mansoni IN STOOL AND GEOMETRIC MEAN
EGG COUNT BY LEVEL OF EDUCATION
LEVEL OF EDUCATION
N1
EXAMINED
PREV.  S.E.
%
GMEC
 S.E.
/gm STOOL
PRIMARY
955
5.37  3.68
52.76  7.30
PREPARATORY &
SECONDARY
470
3.68  3.01
51.31  9.21
UNIVERSITY
20
0  0
...
BELOW AGE
1022
4.99  3.41
44.06  3.85
DIDN'T VISIT SCHOOL
2567
4.01  2.25
37.02  2.91
TOTAL
5034
4.41  2.79
43.05  4.65
TABLE 19: PREVALENCE OF S. mansoni IN STOOL AND GEOMETRIC MEAN
EGG COUNT BY OCCUPATION
PREV.  S.E.
%
GMEC
677
8.10  3.73
41.17  5.42
FARMING LABORER
28
3.88  4.52
20.17  0.46
SKILLED LABORER
23
2.22  2.44
17.54  0.48
1276
0.92  0.57
32.92  5.66
PROFESSIONAL
29
2.15  2.31
12.00  0
CLERK
21
0  0
...
STUDENT
877
6.33  5.18
55.58  7.66
LABORER
47
6.34  2.35
21.08  5.07
ORZOKI
67
1.18  1.39
55.29  0.98
MERCHANT
11
0  0
...
MEKAWEL
1
0  0
...
FISHERMEN
4
0  0
...
OTHER JOB
104
3.74  1.69
27.23  12.92
NOT WORKING
242
0.17  0.20
12.00  0
NOT APPLIED
1627
5.42  3.45
43.45  6.15
OCCUPATION
FARMER
HOUSEWIFE
N1
EXAMINED
 S.E.
/gm STOOL
Analysis Report Fayoum Gov
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TOTAL
5034
4.41  2.79
43.05  4.65
Analysis Report Fayoum Gov
26
TABLE 20: PREVALENCE OF S. mansoni IN STOOL AND GEOMETRIC MEAN
EGG COUNT BY HISTORY OF PREVIOUS TREATMENT FOR
BILHARZIASIS
N1
EXAMINED
PREV.  S.E.
%
YES
964
4.53  2.63
40.36  6.11
NO
3979
4.45  2.89
43.96  4.68
89
1.03  1.26
66.76  69.04
5032
4.41  2.79
43.39  4.50
WERE YOU TREATED
FOR S. mansoni
BEFORE ?
DON'T KNOW
TOTAL
GMEC
 S.E.
/gm STOOL
TABLE 21: PREVALENCE OF S. mansoni IN STOOL AND GEOMETRIC MEAN
EGG COUNT BY HISTORY OF PREVIOUS INFECTION WITH
BILHARZIASIS
DID YOU GET S.
mansoni BEFORE ?
N1
EXAMINED
PREV. 
S.E.%
GMEC
 S.E
/gm STOOL
YES
985
4.45  2.60
40.36  6.11
NO
2405
4.22  2.68
38.71  5.35
DON'T KNOW
1641
4.67  3.15
52.87  2.03
TOTAL
5031
4.41  2.79
43.39  4.50
Analysis Report Fayoum Gov
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TABLE 22: PREVALENCE OF S. mansoni IN STOOL AND GEOMETRIC MEAN
EGG COUNT BY BATHING IN CANAL WATER
N1
EXAMINED
PREV.  S.E.
%
NO
3369
3.51  2.14
37.01  5.85
< 1 WEEK
314
9.23  5.72
38.47  3.37
1-4 WEEKS
166
9.44  8.03
42.91  6.12
1-12 MONTHS
510
8.59  5.13
60.46  2.04
1 YEAR AND MORE
643
2.76  2.32
66.28  17.74
DON'T REMEMBER
2
0  0
...
OTHER
27
0  0
...
NOT APPLIED
2
0  0
...
5033
4.41  2.79
43.39  4.50
LAST TIME TO
BATH IN CANAL
TOTAL
GMEC
 S.E.
/gm STOOL
TABLE 23: PREVALENCE OF S. mansoni IN STOOL AND GEOMETRIC MEAN
EGG COUNT BY WASHING IN CANAL WATER
N1
EXAMINED
PREV.  S.E.
%
3529
5.35  3.40
44.65  4.43
< 1 WEEK
811
2.02  1.33
38.98  3.21
1-4 WEEKS
204
1.78  1.20
18.53  4.46
1-12 MONTHS
182
0.86  0.91
39.56  4.82
1 YEAR AND MORE
290
2.34  1.46
36.32  16.77
DON'T REMEMBER
0
...
...
OTHER
8
0  0
...
NOT APPLIED
1
0  0
...
5025
4.41  2.79
43.39  4.50
LAST TIME TO WASH
CLOTHES IN CANAL
NO
TOTAL
GMEC
 S.E.
/gm STOOL
Analysis Report Fayoum Gov
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TABLE 24: PREVALENCE OF S. mansoni IN STOOL AND GEOMETRIC MEAN
EGG COUNT ACCORDING TO THE DEGREE OF USING CANAL WATER IN WASHING
DO YOU ALWAYS USE
CANAL IN WASHING?
N1
EXAMINED
PREV. 
S.E.%
GMEC 
S.E.
/gm STOOL
ALWAYS
524
1.12  0.71
32.74  6.99
SOMETIMES
776
2.14  1.24
31.94  8.11
RARELY
155
2.38  2.54
49.36  3.74
NEVER
1
0  0
...
TOTAL
1456
1.85  1.19
34.78  6.84
TABLE 25: PREVALENCE OF S. mansoni IN STOOL AND GEOMETRIC MEAN
EGG COUNT BY PLAYING IN CANAL WATER
LAST TIME TO
PLAY IN CANAL
N1
EXAMINED
PREV. 
S.E.%
GMEC
 S.E.
/gm STOOL
NO
3890
4.03  2.57
42.35  3.99
< 1 WEEK
785
5.74  3.94
55.62  6.27
1-4 WEEKS
148
8.63  5.05
50.02 
18.83
1-12 MONTHS
161
5.83  3.61
24.02  6.11
1 YEAR AND MORE
32
0  0
...
DON'T REMEMBER
1
0  0
...
OTHER
12
0  0
...
NOT APPLIED
0
...
...
5029
4.41  2.79
43.39  4.50
TOTAL
Analysis Report Fayoum Gov
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Analysis Report Fayoum Gov
30
TABLE 26: PREVALENCE OF S. mansoni IN STOOL AND GEOMETRIC MEAN
EGG COUNT ACCORDING TO THE DEGREE OF PLAYING IN
CANAL WATER
N1
EXAMINED
PREV.  S.E.
%
ALWAYS
443
2.33  2.25
43.61  13.75
SOMETIMES
595
8.56  5.18
48.39  4.39
RARELY
59
5.07  2.84
32.30  25.91
NEVER
0
...
...
TOTAL
1097
6.10  3.93
46.54  6.46
DO YOU ALWAYS PLAY
IN CANAL ?
GMEC 
S.E.
/gm STOOL
OBJECTIVE EPI 2
Objective EPI 2 was achieved through describing the
environmental characteristics of households within each ezba and
relating these characteristics to the number of infected houses
within ezbas with a fashion similar to ecological analysis. Table
27 shows the percentage of houses with a particular
characteristic and the percentage of houses with more than one
member infected with schistosomiasis. The correlation coefficient
(r) and its level of significance (p value) are presented in the
table.
Stepwise multiple regression analysis was performed to
identify the variables most likely to explain the variation among
villages. The results of multiple regression are shown in table
28.
Analysis Report Fayoum Gov
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TABLE 27: ENVIRONMENTAL CHARACTERISTICS OF DWELLING UNITS (HOUSES) AND ITS RELATIONSHIP TO
SCHISTOSOMIASIS INFECTION INSIDE THE HOUSE
VILLAGE / SATELLITE
N1 OF
HOUSES
TAP IN
WASH
CANAL
MUD
BRICK
ZERIBA
ELECTRICITY
WASHER
RADIO
TV
LATRINE
INFECTION
KAFR ABBOUD
93
32.3
48.4
34.1
53.8
74.2
15.1
55.9
36.
6
38.7
23.7
EZBET EL-TAMAWI
82
24.4
58.5
75.9
52.4
75.6
7.3
39
17.
1
19.8
24.4
ABDEL-ALIM IBRAHIM
94
27.7
76.6
89.4
85.1
63.8
4.3
46.8
21.
3
12.8
35.1
WAHDAN
74
40.5
79.7
54.8
68.9
79.7
17.6
82.4
10.
8
32.9
5.4
AMIN FANOUS EL-BAH
11
63.6
27.3
90.9
72.7
9.1
0
63.6
27.
3
18.2
0
MOHAMED MOSTAFA OSMAN
12
16.7
0
25
66.7
100
50
83.3
58.
3
58.3
0
SENOFAR
94
54.3
14.9
8.5
56.4
71.3
20.2
56.4
40.
4
31.9
20.2
EZBET MOHAMED GENEDY
30
6.7
63.3
24.1
70
80
6.7
46.7
46.
7
23.3
23.3
5
0
100
80
60
0
0
0
0
0
0
KHALAF FAYOUM
65
46.2
16.9
41.5
72.3
83.1
24.6
70.8
43.
1
36.9
0
EZBET SHAKER
56
1.8
48.2
64.3
75
0
1.8
50
1.8
5.4
8.9
EZBET EL-BITAR
19
5.3
47.4
11.1
73.7
78.9
5.3
63.2
36.
8
31.6
0
EZBET BADR-KHAN
20
0
65
50
85
0
0
25
0
0
5
SERSENA
77
49.4
16.9
72.7
58.4
81.8
28.6
50.6
49.
4
59.7
2.6
EZBET ABOU-KELIB
40
22.5
45
43.6
57.5
60
12.5
45
42.
5
25
15
EZBET BESSEIS MOHAMED
30
0
50
48.3
76.7
90
20
76.7
66.
7
23.3
16.7
EZBET MAHGOUB EL-GEBALI
27
29.6
81.5
29.6
74.1
74.1
7.4
44.4
33.
3
14.8
40.7
MONSHAAT SEIF EL-NASR
66
4.5
83.3
36.4
72.7
68.2
9.1
65.2
40.
9
10.6
36.4
EZBET EL-KASHEF & ABDEL-GELIL ELSE'EDAWY
55
0
92.7
1.9
76.4
1.8
0
20
10.
9
1.8
27.3
EZBET HAFEZ HUSSEIN
15
6.7
66.7
13.3
53.3
0
0
100
60
46.7
20
EZBET EL-WABOUR
EZBET ABDEL-HAFIZ ALAK
7
r
0
0.142
p
71.4
0
85.7
0
0
0
0
0.07
5
0.0
81
-0.276
0.7
26
0.226
30.
9
25.7
0.480
-0.195
0.047
0.117
-0.274
0.028
0.397
0.840
0.613
0.229
0.539
TOTAL
972
26.6
0.74
6
52.9
46.2
67.1
62.0
12.7
54.0
0
14.3
18.3
ALL CELL ENTRIES ARE PER CENTS EXCEPT FOR No OF HOUSE WHICH IS
THE NUMBER OF HOUSES (DWELLING UNITS) SAMPLE FOR THAT EZBA OR
SATELLITE AND THE r (CORRELATION COEFFICIENT) AND p (p VALUE)
TAP IN
:TAP WATER INSIDE THE HOUSE
WASH CANAL
:USE CANAL WATER IN WASHING
MUD BRICK
:HOUSE BUILT OF MUD BRICK
ZEREBA
:HOUSE HAS AN ANIMAL SHED ATTACHED TO OR PART OF IT
ELECTRICITY
:THE HOUSE HAS ELECTRICITY
WASHER
:A WASHING MACHINE IS AVAILABLE INSIDE THE HOUSE
RADIO
:A RADIO IS AVAILABLE INSIDE THE HOUSE
TV
:A TV IS AVAILABLE INSIDE THE HOUSE
LATRINE
:A LATRINE IS AVAILABLE INSIDE THE HOUSE
INFECTION
:THE PERCENT OF HOUSES WITH AT LEAST ONE HOUSE
MEMBER INFECTED WITH S. haematobium
r
p
:CORRELATION COEFFICIENT
:p VALUE FOR THE r
Analysis Report Fayoum Gov
34
Multiple regression analysis was performed using stepwise method.
The analysis revealed that the presence radio is important as a
determinant of infection in households. Results of this variable
is shown below.
TABLE 28: RESULTS OF MULTIPLE REGRESSION ANALYSIS USING STEPWISE
METHOD FOR ENVIRONMENTAL CHARACTERISTICS OF HOUSES AND ITS
RELATION TO INFECTION INSIDE THE HOUSE
Multiple R
R Square
Adjusted R square
Standard Error
0.61776
0.38163
0.31292
10.91649
Analysis of Variance
DF Sum of Squares
Mean Square
2
1323.82325
661.91162
Residual
18
F
=
5.55436
Regression
2145.05715
Signif F =
0.0132
---------- Variables in the equation ---------------Variable
B
SE B
Beta
WASHCANAL
0.342775
TV
0.285351
(constant)-12.392000
0.1.3748
0.136136
8.965010
119.16984
0.717436
0.455154
T
3.304
2.096
-1.382
Analysis Report Fayoum Gov
Sig T
0.0039
0.0505
0.1838
35
OBJECTIVE EPI 3
Objective EPI 3 was to estimate the public health impact of morbidity
due to schistosomiasis. The distribution of liver fibrosis and its staging is
presented in different ezba and by age and sex distribution. The relationships
of liver fibrosis to history of previous infection and treatment are
presented.
Liver morbidity describing liver fibrosis, cirrhosis and mixed infection
will be presented by age and sex distribution.
Analysis Report Fayoum Gov
36
TABLE 29:
SATELLITES
DISTRIBUTION OF LIVER FIBROSIS IN THE DIFFERENT EZBAS OR
VILLAGE / SATELLITE
KAFR ABBOUD
N1
NO
FIBROSIS
STAGE 1
STAGE 2
STAGE 3
0.9
116
71.6
21.6
6.0
70
61.4
32.9
5.7
100
38.0
44.0
18.0
0.0
WAHDAN
85
58.8
35.3
5.9
0.0
AMIN FANOUS EL-BAH
12
16.7
66.7
16.7
0.0
MOHAMED MOSTAFA OSMAN
22
63.6
36.4
0.0
0.0
SENOFAR
81
72.8
23.5
3.7
0.0
EZBET MOHAMED GENEDY
62
79.0
19.4
1.6
0.0
EZBET EL-TAMAWI
ABDEL-ALIM IBRAHIM
0.0
EZBET EL-WABOUR
KHALAF FAYOUM
101
59.4
38.6
2.0
0.0
EZBET SHAKER
45
60.0
33.3
6.7
0.0
EZBET EL-BITAR
17
23.5
58.8
17.6
0.0
EZBET BADR-KHAN
19
78.9
21.1
0.0
0.0
SERSENA
78
70.5
23.1
5.1
1.3
EZBET ABOU-KELIB
24
91.7
8.3
0.0
0.0
EZBET BESSEIS MOHAMED
32
50.0
50.0
0.0
0.0
EZBET MAHGOUB EL-GEBALI
38
76.3
13.2
10.5
0.0
MONSHAAT SEIF EL-NASR
68
70.6
23.5
5.9
0.0
EZBET EL-KASHEF & ABDELGELIL EL-SE'EDAWY
53
75.5
20.8
3.8
0.0
EZBET HAFEZ HUSSEIN
24
87.5
12.5
0.0
0.0
1047
64.5
29.4
5.9
0.2
EZBET ABDEL-HAFIZ ALAK
TOTAL
Analysis Report Fayoum Gov
37
TABLE 30:
AGE SEX DISTRIBUTION OF LIVER FIBROSIS
AGE / SEX
N1
NO
LIVER
FIBROS
IS
STAGE
1
STAGE
2
STAGE 3
TOTAL
MALE
FEMALE
5-9
TOTAL
MALE
FEMALE
10-14 TOTAL
MALE
FEMALE
80
40
40
236
135
101
184
112
72
88.8
87.5
90.0
75.4
70.4
82.2
67.4
65.2
70.8
11.3
12.5
10.0
23.3
27.4
17.8
31.0
32.1
29.2
0.0
0.0
0.0
1.3
2.2
0.0
1.6
2.7
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
15-19
TOTAL
MALE
FEMALE
112
63
49
60.7
50.8
73.5
34.8
44.4
22.4
4.5
4.8
4.1
0.0
0.0
0.0
20-24
TOTAL
MALE
FEMALE
74
37
37
55.4
40.5
70.3
31.1
37.8
24.3
13.5
21.6
5.4
0.0
0.0
0.0
25-29
TOTAL
MALE
FEMALE
75
27
48
52.0
37.0
60.4
34.7
37.0
33.3
10.7
22.2
4.2
2.7
3.7
2.1
30-34
TOTAL
MALE
FEMALE
51
21
30
62.7
47.6
73.3
33.3
42.9
26.7
3.9
9.5
0.0
0.0
0.0
0.0
35-39
TOTAL
MALE
FEMALE
53
22
31
43.4
40.9
45.2
45.3
36.4
51.6
11.3
22.7
3.2
0.0
0.0
0.0
40-44
TOTAL
MALE
47
23
24
51.1
30.4
70.8
36.2
47.8
25.0
12.8
21.7
4.2
0.0
0.0
0.0
MALE
40
18
22
62.5
61.1
63.6
20.0
11.1
27.3
17.5
27.8
9.1
0.0
0.0
0.0
MALE
23
15
8
65.2
53.3
87.5
26.1
33.3
12.5
8.7
13.3
0.0
0.0
0.0
0.0
MALE
25
17
8
40.0
17.6
87.5
40.0
52.9
12.5
20.0
29.4
0.0
0.0
0.0
0.0
MALE
26
7
19
57.7
57.1
57.9
23.1
14.3
26.3
19.2
28.6
15.8
0.0
0.0
0.0
4
50.0
50.0
0.0
0.0
0-4
FEMALE
45-49
TOTAL
FEMALE
50-54
TOTAL
FEMALE
55-59
TOTAL
FEMALE
60-64
TOTAL
FEMALE
65-69
TOTAL
Analysis Report Fayoum Gov
38
70+
TOTAL
MALE
FEMALE
3
1
33.3
100
66.7
0.0
0.0
0.0
0.0
0.0
TOTAL
MALE
FEMALE
17
10
7
47.1
40.0
57.1
52.9
60.0
42.9
0.0
0.0
0.0
0.0
0.0
0.0
TOTAL
MALE
FEMALE
104
7
550
497
TABLE 32:
64.5
57.6
72.0
29.4
33.3
25.2
5.9
8.9
2.6
0.2
0.2
0.2
DISTRIBUTION OF LIVER FIBROSIS ACCORDING TO HISTORY
OF PREVIOUS INFECTION WITH BILHARZIASIS
DID YOU GET
BILHARZIA
BEFORE?
N1
YES
210
NO
448
DON'T KNOW
357
TOTAL
1015
NO LIVER
FIBROSIS
60.5
65.2
66.7
64.7
STAGE 1
32.9
29.9
26.6
29.4
STAGE
2
6.7
4.7
6.4
5.7
STAGE 3
0.0
0.2
0.3
0.2
Analysis Report Fayoum Gov
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TABLE 33:
AGE SEX DISTRIBUTION OF LIVER MORBIDITY
AGE / SEX
N1
NO LIVER
AFFECTION
PURE
FIBROSIS
PURE
CIRRHOSIS
MIXED
FIBROSIS
AND
CIRRHOSIS
0-4
TOTAL
MALE
FEMALE
78
39
39
88.5
87.2
89.7
11.5
12.8
10.3
0.0
0.0
0.0
0.0
0.0
0.0
5-9
TOTAL
MALE
FEMALE
236
135
101
75.4
70.4
82.2
24.6
29.6
17.8
0.0
0.0
0.0
0.0
0.0
0.0
10-14
TOTAL
MALE
FEMALE
184
112
72
67.4
65.2
70.8
32.6
34.8
29.2
0.0
0.0
0.0
0.0
0.0
0.0
15-19
TOTAL
MALE
FEMALE
112
63
49
60.7
50.8
73.5
38.4
47.6
26.5
0.0
0.0
0.0
0.9
1.6
0.0
20-24
TOTAL
MALE
FEMALE
25-29
TOTAL
MALE
FEMALE
74
37
37
55.4
40.5
70.3
44.6
59.5
29.7
0.0
0.0
0.0
0.0
0.0
0.0
75
27
48
50.7
37.0
58.3
46.7
63.0
37.5
1.3
0.0
2.1
1.3
0.0
2.1
30-34
TOTAL
MALE
FEMALE
50
20
30
62.0
45.0
73.3
38.0
55.0
26.7
0.0
0.0
0.0
0.0
0.0
0.0
35-39
TOTAL
MALE
FEMALE
53
22
31
43.4
40.9
45.2
54.7
54.5
54.8
0.0
0.0
0.0
1.9
4.5
0.0
40-44
TOTAL
MALE
FEMALE
46
23
23
50.0
30.4
69.6
47.8
65.2
30.4
0.0
0.0
0.0
2.2
4.3
0.0
45-49 TOTAL
MALE
FEMALE
40
18
22
62.5
61.1
63.6
32.5
33.3
31.8
0.0
0.0
0.0
5.0
5.6
0.0
50-54
TOTAL
MALE
23
15
8
65.2
53.3
87.5
30.4
40.0
12.5
0.0
0.0
0.0
4.3
6.7
4.5
55-59 TOTAL
MALE
25
17
40.0
17.6
52.0
70.6
0.0
0.0
8.0
11.8
FEMALE
Analysis Report Fayoum Gov
40
FEMALE
8
87.5
12.5
0.0
0.0
60-64
TOTAL
MALE
FEMALE
65-69
TOTAL
MALE
FEMALE
26
7
19
57.7
57.1
57.9
42.3
42.9
42.1
0.0
0.0
0.0
0.0
0.0
0.0
4
3
1
50.0
33.3
100
50.0
66.7
0.0
0.0
0.0
0.0
0.0
0.0
0.0
70+
TOTAL
MALE
FEMALE
17
10
7
47.1
40.0
57.1
52.9
60.0
42.9
0.0
0.0
0.0
0.0
0.0
0.0
1043
548
495
64.2
57.5
71.7
34.8
41.2
27.7
0.1
0.0
0.2
0.9
1.3
0.4
TOTAL
MALE
FEMALE
Analysis Report Fayoum Gov
41