Statistical analysis on the number of patient reported for malaria and typhoid fever at federal medical center Gusau (FMC)
Statistical analysis on the number of patient reported for malaria and typhoid fever at federal medical center Gusau (FMC)
`1.0 INTRODUCTION
Health is one of the most important areas of human lives. The whole activities human being performed are only possible when people are able, capable of performing them. That is to say when people are free from diseases or healthy. It is in lined with these that the world health organization (WHO) and other relevant agencies and organization were formed. These organization carryout there activities to every part of the world via its representatives and to the local communities to enlighten the whole of world of the danger that is behind those countries that refuse to focus attention on the health care to its citizens, particularly the developing world which Nigeria is In view of these the Federal Government of Nigeria focus more attention on the health sector by establishing federal medical centers, specialist hospitals and expansion of its university teaching hospitals across the nation. And also in collaboration with the world health organization and other related agencies Program like the roll back malaria, expanded programme on immunization etc. mere introduced. In addition primary health care (PHC) was established for health care delivery as adopted by member states of the world health organization (WHO) after the Alma Ata conferences of 1978.
It is a part of effort of the federal government of Nigeria among others the establishment of Federal Medical Center Gusau, which started General Hospital to specialist and then later upgraded as federal medical center Gusau (FMC) Gusau Zamfara State.
Health statistic is very important it is widely accepted that the most important criteria for accessing the health condition of the community and standard of the social condition of country is by statistics. Hence health data on diseases becomes very important and cannot be over emphasized when planning health programme. However, critical analysis of health becomes difficult due to lack of sufficient data obviously; it is difficult to properly execute health plans without statistical data is needed for such plans.
According to report W. BUGELL (1966) of the fundamental gospel of statistic is to push back the domain of ignorance prejudice, rule of thumb and to increase the domain in which decisions are made and principles formulated on the basis of analyzed quantitative fact.
OBJECTIVES OF ESTABLISHING THE HOSPITAL
To provide a board range services to meet with the health care need of the people from the catchment areas and the community at large.
To conduct relevant research in to prevalent health and health problems.
To provide technical support to primary health care facilities within the area of operation.
The hospital was established to provide health care services and also to bring health care services to the grassroots level.
NATURE OF HEALTH STATISTICS
For proper planning the government needs to have a fundamental knowledge of the total number of the peoples in the country, the geographical distributions of the people in relation to rural and urban composition.
However demographic data on health planning is particular, indispensable. Data on fertility, mortality and diseases used in decision and for the improvement of health condition and its development in an area. Any registration system should provide adequate statistics, which could form the basis for informed national decision. There should also be provision for a central or local agency, which among other things could gather analyzed and disseminate basic vital statistics.
1.3 GENERAL AIM AND OBJECTIVES
This project is aimed at presenting to the public the rate at which the cases of malaria fever are reported in Zamfara state (with special attention to Hospital).While, the specific objectives are:
1. To see if the rate infection by the diseases is the same between the sexes
2. To investigate if the infection of the diseases between sex depend on the quarter of the year.
3. To investigated the significance difference on the rate of infection of malaria within the investigated periods.
4. To show the trend analysis on the rate of infection of malaria over the year under study.
1.4 SIGNIFICANCE OF THE STUDY
It will enable the management of federal medical center (FMC Gusau) ,Farida
General Hospital Gusau (FGH), and king Fahad ibn Abdulaziz Hospital Gusau (KFAGH), and the entire people of Zamfara state to have awareness about malaria fever and to make provision on how to able to curb the adverse effect of this dangerous diseases and in addition, to provide reliable information to the government of Zamfara state on the rate at which these diseases, that is malaria and affect its communities and the state at large 1.5SCOPE AND LIMITATION
Due to time fact, this project work is limited to only three hospital, that is federal medical center (FMC Gusau), farida general hospital (FGH Gusau), and king fahad ibn Abdulaziz General Hospital (KFAGH Gusau) because the condition in three hospital can hardly be generalized to cover those in the then said of similar hospitals in the country. This research work has been limited to statistical analysis of malaria.
1.6 DEFINITIONS OF TERMNS
1.6.1 FEVER
Fever is an increase in body temperature over the normal range which is caused by diseases. It is often described as any rise above normal body temperature due to diseases and not from environmental exposure, pregnancy, emotion and eating. Over the country, medical scientist has provided drugs and vaccines to try and fight these diseases. Quinine is one of the drugs provided it is reliable, affordable and accessible. But the war to fight these diseases has had its casualties among us. Our environment is the number one contributor of these diseases, bushes, stagnant water, just to mention but a few are the agent for breeding mosquitoes. Our government so far has tried to fight these diseases by advising its citizens to take care of their environment. But the battle still continues that is why statistics comes in.
MALARIA
Malaria fever is a disease caused by the protozoan plasmodium spp. It is spread by a type of mosquito known as the anopheles mosquito, which becomes the vector after biting an infected person. There are two types of malaria which are as follows
1, Acute Malaria or uncomplicated: is symptomatic infection with malaria parasitaemia without signs of severity and is very common among people. Patients with symptoms such as fever, headache, cough, vomiting and diarrhea etc.
2, Chronic Malaria or complicated(severe malaria): any malaria with a high mortality rate (more than 5%), even with parental treatment is defined as severe malaria and This is not common among people but skills Easily. Patients with serious of body hot, consciousness, convulsions and severe anemia.
1.7 THE EFFECT AND ERADICATION OF MALARIA IN NIGERIA
Malaria fever are very common in Nigeria, year ago, these diseases has done more harm than good to our great country Nigeria by killing many Nigerians. This is attributed to the fact that Nigeria is a third world nation, as is in the tropic region, the entire factor stated above have contributed to the coolness of these diseases. One other factor that also contributes to these diseases in the past is lack of effective drugs that can help for the control of these diseases. Unfortunately, there is more reported cases of malaria in our hospitals, and if care is not taken, there will be an increase in the rate at which these disease will go more harm to our dear country.
Above all, government can eradicate these diseases, if all necessary measures are put in place, like problems of environment protection using pesticide poverty etc. if the standard of living of families is improved, the rate at which these diseases is affecting the communities and the country at large will reduce to minimum or completely eradicated. And this will make Nigeria a healthy and a healthy nation is a wealthy nation.
CHAPTER TWO
2.0 LITERATURE REVIEW
The most important tool a researcher should put in placed on carrying research work is to outline the study of its related literature, this help to research work is to outline the study of its related literature, this help to provide a basis for guidelines and as well help to show that researcher is familiar with what is already known or still unknown since effective research work is based on past knowledge, therefore help to minimized or eliminated duplication.
As part of the research work, the report of world health organization (WHO) and United Nation International Children Education Fund on Malaria (2005), which is the first comprehensive effort by the Roll Back Malaria Partnership, emphasized on the stand of the world in relation to its most devastating diseases. It reveals that the tide may be beginning to turn against malaria as control and prevention programme start to take effect. It also said, during the past five years real progress has been make in scaling up malaria control and prevention efforts. It says; over 3 billion people live under the threat of malaria it kills over a million each year mostly children.
The World Bank summit in Paris September 7, (2005) in a bid to secure more resources and better condition in the fight against malaria in Africa. The summit chaired by the Vice president for the Africa region, Gobind Nankani, describes the social and the economics costs of malaria on Africa as enormous. He said the social cost are tremendous, every 30 seconds an Africa child dies on account of malaria he says, hundred of thousand of people suffer because of the burden of malaria. In addition, the economics costs are severe. Our estimate is that some $12billion a year is lost in Africa due to malaria and economics growth is reduced by about one point two percent a year. And he finally said for many countries, controlling malaria is crucial to reducing the human suffering and deaths of mothers and young children, and securing of economics growth.
In the World Health Journal of (2004) February and March), Eric Gloating stated that the problems of ill health in the world are strongly related to an Independent factors like poverty, poor environment, malnutrition, illiteracy, unemployment, in accessibility of social services among others.
In paper on (June 24 2005) by Omolola Oso she said malaria is a disease discovered to be prevalent infection, affecting inhabitant of Abuja she also said that the phenomena is attributed to lack of personal hygiene among inhabitant and also due to the fact that Nigeria is a tropical country.
According to Global partnership on roll back malaria, in a paper by the World Bank President Paul Wolfowitz, he says the Paris (8 October, 2005) re-energize the International Community to help provide African families with enough supplies of the right anti malaria drugs, especially the new and effective act or Artemisinin based combination therapy and also to invest in malaria research to ensure more effective prevention and treatment, including new drugs to which malaria parasites will have no resistance and hopefully an affective malaria vaccine. He further said, the need for a new generation of affordable anti malaria drugs (Act drugs is reinforced by evidence that malaria has made a resurgence because of resistance to tradition) first line anti malaria treatment, such as chloroquine (ce), Arthemeter, Arthesunate, and sulfadoxine pyrimethamine (sp or Fansider) by plasmodium falciparum, the parasite that causes a severe form of malaria faced with increasing resistance to these first line treatment, countries are revising their anti malaria drug policies and exploring alternative treatment options.
From the information obtained we can said that it goes hand in hand with the director general of the world health organization. Mr. Nakajuna, where he said that it becomes more and more clear that health goes hand in hand with economics and social development, and that every men and women should be in a position to choose a healthy way of life. He said health is our precious possession, both individually and collectively. On the Africa live Roll Back, malaria held in Daker (earlier this year) the United Nation (UN) envoy on Roll back malaria Youssou NDour he says we should United against malaria and proposed subsiding for new anti malarial drugs, especially Artemisinin based combination therapies, and that the World Bank will work closely with professor Arrow and his colleagues to further develop the design of the Global subsidy. He said, the believe the concept has strong merit and could potentially have a significant impact in terms of accessibility to treatment, delaying resistance and ultimate by reducing malaria related death and illness
Follow typhoid this complication has been reported particularly in adolescents and young adults in Nigeria services. In out series we have not fund this complication. However, an olds child or an adolescent presenting only with Sevier malaria as a cause should be kept in mine; it was striking in Nigerian series as in the patients presenting with the Sevier malaria the diagnosis we made at autopsy in which characteristics of malaria lessons were found in the intestinal tract.
CHAPTER III
METHODOLOGY
This section consist of method of data collection used in this research work, methodology is known to be a powerful tool in the carrying out of any research work. In research work, method of data collection is of great importance hence, we are going to considered method of collection and sources. There are two main sources of data collection, the two main sources are associated to different sources of data, and they include primary and secondary sources and this two main sources are classified into published sources and unpublished sources. Since we are dealing with statistical formed of research work, it is better at this point in time to know what statistics is all about, hence statistics can be defined as the scientific method of collecting, organizing, presenting, analyzing and interpreting any numerical data in order to draw inference and for right decision making. Despite the two main sources of data mention above, the sources of the data used in this write up was from the Primary sources. This is because of limited time and financial need that involves.
The data is Primary in the sense that it was collect to the Patients in to the three hospital in Gusau zamfara State.
3.1 METHODS OF DATA COLLECTION
3.1.1 INTERVIEW
The study was a community based cross-sectional study. A structured questionnaire was designed and face to face interview by the researcher. The first part of the questionnaire included socio demographic characteristics of the respondent and the second part assessed household head knowledge on malaria parasite, include symptoms, preventive measure the attitude of respondent toward malaria and its control. Lastly, this questionnaire assessed the respondent towards practice against malaria and its control and treatment seeking patterns. The questionnaire was administered to 2oo randomly selected to three hospitals Gusau in June 2013.only one person was interviewed three hospital in their own. The interviewed were asked the patient and rests of the people in hospital pertaining to malaria parasite. The questionnaire was prepared in English language and communication with lettered and illetared people.various studies about human health are carried out through this method of data collection. Here the enumerator ask personally for the require information. The medical worker should want to know when, how, where and other similar request concerning the patients. The question and answer may be in written or oral forms. This method disadvantage is that false data may be given to enumerator.
3.1.2 SOURCES OF DATA COLLECTION
The source of this data were collected through questionnaire and the questionnaires were distributed according to three hospital in Gusau
POSTAL QUESTIONNAIRE
This is the method of data collection in which list of questions is sent through post, unless however, the respondents i.e the person who is required to answer the questions has an interest in answering it or not. This method is generally unsatisfactory because of the biased nature of the method, sometimes, bias of some sort is rare as it used to be and so cannot be allowed for any analysis of returned questionnaires. Postal questionnaire therefore, are not recommended unless all the non responders are subsequently inter viewed in order to obtain the required information, and on appropriate sample of the non responders is under viewed and it is established that the failure to replied is in no way connected with any bias
ABSTRACTED FROM PUBLISHED STATISTICS
In this method of data collection, any data that a researcher obtained by him is termed primary data, because the researcher knows the condition under which the data is collected. Data taken from other peoples finding are refers to as secondary data. Users of secondary data cannot have an idea of the background like the original investigator. In many government and non government organization publication, the information are compile in the knowledge that they will be used in the production of secondary statistics. Such a statistics are carefully an noted and explained so that users will not be mislead, the secondary statistic may be prepared from them with reasonable confidence.
METHOD OF DATA ANALYSIS
In the past, analysis of research work of this form were carried out manually, but these days, with the improvement in computer applications, various statistical analytical softwares/programmes has been developed to improve the accuracy of output of analysis and reduce errors made white analyzing data manually due to cumbersome nature of data been analyzed.
The computer method of analysis is fast, cost affect use. Example of soft ware for computer based
Statistical package for social sciences (SPSS)
Minitab
Statistical
Statistical Analysis System (SAS)
For the analysis in this project work the researcher finds the Minitab more continuant to be applied. Therefore, all the analysis in this project were done using the Minitab and the interpretations were made from the result of the output obtained from the Minitab and on this results and other finding are based our conclusion and recommendations.
STATISTICAL TOOLS EMPLOYED
Chi Square
Analysis of variance (one way)
Time series analysis
Student t-test
CHI SQUARE TEST FOR INDEPENDENCE
Chi square is defined as the sum of independent standard normal variable. The test is giving by:
X2 =
Where Oij is the observer frequency
Eij is the expected frequency
Uses of Chi Square
Test of independence: This important used of chi square distribution is in testing the null hypothesis that two variables/attributes of classification are independent.
To obtain confidence limits for the population variance.
Test of goodness of fit: A test in which the observed frequencies are compare or fitted to a hypothesis.
To test the equality of several correlation co efficient
ANALYSIS OF MXN CONTINGENCY TABLE
Considered two variable A and B is divided in to M classes (i.e A1, A2,AM) and B is divided into N classes (i.e. B1, B2,BN). The various cells can be expressed in the table known as the contingency table as given below.
Where Ai = is the number of persons possessing the variable Ai (i= 1,2,3, - M)
Bj= is the numbers of persons possessing the variable Bj(j= 1,2,3---N)
AiBj = is the number of persons possessing the variable AiBj (i= 1, 2, 3, ---m, j= 1,2,3,--------n).
N = the grand total
In order to analyze if the two variables A and B are independent or not on the contingency table, we need to test the hypothesis.
Ho: The variable A and B are independent
H1: The variables A and B are dependent
Decision Criteria
Reject Ho if with a given level of significance otherwise do not reject.
TIMES SERRIES ANALYSIS
A time series is a set of observation taken at specific timer, usually at equal interval. Mathematically a time series is represent or defined by the value Y1, Y2, Y3,--------of a variable Y at time t1,t2,t3-----thus is a function of t.
3.4.1 COMPONENT OF TIME SERRIES
Fluctuation of a time series may be classified into four basic type of various, which account for changes in the series over a period of time. These fluctuation or variation are due to the influence of physical, economics, sociological and other forces, Analysis of these movement helps in forecasting future movements. The four components of time series are as follows:
SECULAR TREND (Tt)
This refers to the general direction in which the graph of a time series appear to be going over a long interval of time. It is also called secular variation or long term movement. E.g. of secular trend which show up word movement in population trend, death rate down ward trend.
CYCLICAL VARIATION (Ct)
The recurrent up and down wave make variation from secular trend. These circular may or not be periodic. Examples of cyclical movements are cycles (repenting intervals of property recession, depression ande recovery).
SEASONAL VARIATION (St)
The up and down variation from secular trend that occur within a year and reoccur annually, annual reoccur of events are therefore responsible for seasonal movements. Such variations typically are identified with monthly or quarterly data. The factor that causes seasonal variation are draft and weather conditions, customers, tradition and habits. Daily, hourly, weekly occurrence of event can also produce seasonal movement.
IRREGULAR OR RANDOM MOVEMENT
This refer to as erratic or sporadic motions of time series due to chance event such as floats, strike, etc. Though such events produce variations lasting only a short time, it is conversable that they may be so intense as to result in new cyclical or other movements.
In traditional time series analysis it is assumed that there is multiplicative relationship between the four components. That is, it is assumed that any particular value in a series is the product of factors that can be attributed to various components. It is given by
Y = Tt X St X Ct X It
The addition model is given by
Y = Tt + St + Ct + It
3.5.1 ANALYSIS OF VARIANCE (ANOVA)
Analysis of variance is used to compare simultaneously three or more sample means based on interval or ration data. As the names implies is a procedure that tries to analyzed the variation of response and assign portions of these variation to each of a set of independent variable in a study and to determine how they interest and effect the response. It is also a method of splitting the total variation of data into meaningful components that measure different source of variation.
ONE WAY ANOVA
Though there are two types ANOVA (we have one way ANOVA and two way ANOVA. One way analysis of variance is a method for splitting the total variation of our data into meaningful component that measures sources of variation. One analysis of variance can be characterized when a normal population represent different variation of a single factor e.g. types of food crops grown in a farm land, high school attended by students etc.
The one way classification of ANOVA is shown below
1
2
3
J
N
Total
1
Y11
Y12
Y13
---------
Y
---------
Y1n
Y1.
2
Y21
Y22
Y23
---------
Y2J
---------
Y2n
Y2.
3
Y31
Y32
Y33
---------
Y3J
---------
Y3n
Y3.
I
Yi1
Yi2
Yi3
YiJ
---------
Yin
Yi.
P
Yp1
Yp2
Yp3
---------
YpJ
---------
Ypn
Yp.
Total
Y.1
Y.2
Y.3
---------
Y.j
---------
Y.n
Y..
From the above table, the model for the one way analysis of variance could be written as:
Yij = + ti + eij
i = 1,2,-----p
j = 1,2,-----n
where
Yij is the overall yield of experiment or overall outcome of experiment.
is the experimental mean effect
ti is the experimental ith effect
eij is the experimental error assumes normally and independently distributed with mean zero and variance 2.
At the end of the computation, the analysis of variance table will be prepared and prior to this, we have to determine the element of the table.
ANOVA TABLE
Sources of variation
Degree of variation
Sum of square
Mean
square
F
Treatment Error
p-1
p(n-1)
SSt
SSE
SST/p-1
SSE/p(n-1)
MSt/MSE
Total
np-1
SST
Hypothesis
HO: ti = 0 (there is no significance difference between the treatment)
H1: ti 0 for sum is (there is significance difference between the treatment)
= 1%,5%,10% Level of significance
Test Statistics = F
Decision Rule
Reject Ho at a given level of significance if calculated value of F is
greater than the tabulated F value, otherwise do not reject.
TUKEY TEST
For balanced one-way analysis of variance where the turkey student zed range (T) interval are
Where is the upper percentage point of the studentized range distribution for k means with v degree of freedom?
The probability that the intervals for all are simultaneously correct is exactly. This follows from the fact that the maximum pair wise mean difference is precisely the range.
Note that it uses the factor rather than the more standard given by the standard deviation of the difference.
Any pair of means whose corresponding confidence interval does not cover zero is declared significantly different. The interval can be extended to encompass contracts as well.
Tukey carried the phase wholly significance difference (WSD) for the term to contrast with the least significant difference (LSD) term vs used in non simultaneous testing.
The tukey studentized range procedure gives the shortest simultaneous confidence interval for pair wide mean difference when it is applicable; that is, when the experimental design is balanced. In the unbalanced where the are not all equal, there are approximate tukey type procedure.
STUDENT t-TEST
The student t-test distribution is used in testing the hypothesis such that Ho: i 2 against H1: . This is usually called the test of difference or equality of two sample means.
Suppose we have the sample below:
Popn1
Popn2
X11
X21
X31
Xi1
X12
X22
X32
Xn2
xi1
xi1
Hypothesis
: There is no significance difference between typhoid and malaria patients.
H1: There is significance difference between typhoid and malaria patients.
Test Statistics
tc where
and
Decision Rule
Reject Ho if tcal > ttab otherwise do not reject.
CHAPTER IV
4.0 DATA PRESENTATION AND DATA ANALYSIS
4.1 DATA PRESENTATION
The data collected for the research work are presented below:
TABLE1: QUALITY REPORTED CASES OF MALARIA FEVER WITH RESPECT TO SEX.
Qtrs
Male
Female
Total
1993
1
2
3
4
610
817
1472
785
543
863
1095
885
1153
1680
2567
1670
1994
1
2
3
4
700
1067
1509
931
844
832
1057
860
1544
1899
2566
1791
1995
1
2
3
4
1140
628
1001
332
966
503
875
213
2106
1131
1876
545
1996
1
2
3
4
785
993
1184
509
530
924
1161
477
1315
1917
2345
986
1997
1
2
3
4
1335
739
1276
966
1331
493
1345
1079
2666
1232
2621
2045
1998
1
2
3
4
873
604
669
546
909
536
576
414
1782
1140
1245
960
1999
1
2
3
4
2305
1663
1723
1631
1635
938
1135
1655
3937
2601
2861
3286
2000
1
2
3
4
843
1017
826
706
987
1068
826
1015
1830
2085
1652
1724
2002
1
2
3
4
760
578
599
618
1008
784
683
513
1768
1362
1282
1131
2003
1
2
3
4
650
650
789
775
900
737
839
704
1550
1387
1628
1479
1998
1
2
3
4
815
1089
1932
1739
816
1370
2318
1613
1631
2459
4250
3352
Source: Federal Medical Center Gusau
TABLE2: QUALITY REPORTED CASES OF TYPOID FEVER WITH RESPECT TO SEX.
Qtrs
Male
Female
Total
1993
1
2
3
4
176
131
123
87
125
161
199
161
301
292
322
248
1994
1
2
3
4
234
158
170
229
252
144
178
255
486
302
348
484
1995
1
2
3
4
224
33
137
77
230
67
183
73
454
100
320
150
1996
1
2
3
4
201
167
189
189
193
273
216
201
394
440
405
390
1997
1
2
3
4
126
124
221
195
157
135
175
211
283
259
396
406
1998
1
2
3
4
92
100
169
103
100
162
162
121
192
262
331
224
1999
1
2
3
4
256
231
266
108
119
74
68
74
375
305
334
182
2000
1
2
3
4
30
49
68
21
38
52
61
9
68
101
129
30
2001
1
2
234
146
135
86
369
232
3
4
99
61
106
63
205
124
2002
1
2
3
4
158
118
266
118
139
138
184
115
297
256
450
233
2003
1
2
3
4
140
149
64
33
159
161
73
12
299
310
137
45
TABLE3: QUARTERLY REPORTED CASES OF MALARIA FEVER
Quarters
Male
Female
Total
Q1
10813
10469
21282
Q2
9845
9048
18893
Q3
12983
11910
24893
Q4
9541
9428
18969
Total
43182
40855
84037
Source: Federal Medical Center Gusau
TABLE3: QUARTERLY REPORTED CASES OF MALARIA FEVER
Quarters
Male
Female
Total
Q1
1871
1647
3518
Q2
1406
1453
2859
Q3
1772
1605
3377
Q4
1221
1295
2516
Total
6270
6000
12270
Source: Federal Medical Center Gusau
TABLE 5: REPORTED CASES OF MALARIA FEVER ON MONTHLY BASIS
Months
1993
1994
1995
1996
1997
1998
Jan
399
142
463
344
1136
750
Feb
351
979
875
591
800
741
Mar
402
408
833
380
730
283
Apr
447
475
346
738
412
381
May
592
723
319
514
384
155
Jun
641
701
325
665
436
604
Jul
899
789
235
832
891
653
Aug
482
848
777
707
977
219
Sep
1186
929
864
806
753
375
Oct
701
884
208
537
550
212
Nov
188
158
139
164
737
449
Dec
781
749
198
285
758
299
Months
1999
2000
2001
2002
2003
Jan
1058
227
411
544
712
Feb
1450
826
588
632
529
Mar
1427
676
769
470
390
Apr
590
428
300
276
551
May
873
875
558
545
424
Jun
1090
680
404
566
1484
Jul
1085
479
556
480
1871
Aug
905
876
335
703
1574
Sep
872
297
391
445
805
Oct
1439
435
458
494
1569
Nov
1089
657
349
312
934
Dec
758
630
324
673
859
Source: Federal Medical Center Gusau
TABLE 5: REPORTED CASES OF TYPHOID FEVER ON MONTHLY BASIS
Months
1993
1994
1995
1996
1997
1998
Jan
99
94
268
114
138
55
Feb
86
320
161
149
60
137
Mar
117
72
25
131
84
Apr
112
64
42
148
48
73
May
110
126
29
186
123
79
Jun
73
112
29
95
88
110
Jul
108
87
62
132
129
180
Aug
128
182
200
154
49
66
Sep
86
79
58
117
212
85
Oct
80
85
95
248
103
68
Nov
70
101
3
102
143
106
Dec
98
297
52
39
161
50
Months
1999
2000
2001
2002
2003
Jan
160
38
252
105
121
Feb
65
-
-
139
88
Mar
150
40
117
52
90
Apr
64
43
84
86
158
May
102
33
-
119
96
Jun
139
25
148
51
56
Jul
81
53
123
118
66
Aug
184
50
33
202
49
Sep
69
26
49
130
22
Oct
134
13
35
108
30
Nov
48
9
60
104
12
Dec
-
8
29
21
3
Source: Federal Medical Center Gusau
INTERPRETATION
Test of Significance Difference Between The Rate of Infection of The Diseases By Sex.
Test of Significance Difference Between The Rate of Typhoid on Both Sex.
Hypothesis
Ho: There is significance difference between the rate of infection of typhoid by sex.
H1 There is no significance difference between the rate of infection of typhoid by sex.
Decision Criteria
Reject Ho if tcal > ttab otherwise do not reject.
Conclusion
Since from the analysis carried out it shows that t tabulated is greater
than t-calculated. That is t-tab 2.371>0.43 t-cal, we accept null hypothesis that there is significance difference between the rate of infection by sex.
Test of Significance Difference Between The Rate of Infection of Malaria on Both Sex.
Hypothesis
Ho: There is significance difference between the rate of infection of malaria by sex.
H1 There is no significance difference between the rate of infection of malaria by sex.
Decision Criteria
Reject Ho if tcal > ttab otherwise do not reject.
Conclusion
Since from the analysis carried out it shows that t tabulated = 2.371 is greater than t-calculated = 0.60 we accept null hypothesis that there is significance difference between the rate of infection of malaria by sex.
4.3 INTERPRETATION
4.3.1 Investigate If The Rate of Infection of The Diseases Among Sex Depend on The Quarter of The Year.
4.3.2 Investigate If The Rate of Infection of The Malaria Among Sex Depend on The Quarter of The Year.
Hypothesis
Ho: The rate of infection of malaria among sex depends on quarter of the year.
H1 The rate of infection of malaria among sex does not depend on quarter of the year.
Decision Criteria
Reject Ho if cal > tab with a given level of significance otherwise do not reject.
Conclusion
Since the analysis carried out shows that the value of chi-square calculated is 21.688 greater than chi-square tabulated 11.385 at 1% level of significance, we accept alternative hypothesis, which means that the rate of infection by malaria among sex do not depend on quarter of the year.
4.3.3 Investigate If The Rate of Infection of The Typhoid Among Sex Depend on The Quarter of The Year.
Hypothesis
Ho: The rate of infection of typhoid among sex depends on quarter of the year.
H1 The rate of infection of typhoid among sex does not depend on quarter of the year.
Decision Criteria
Reject Ho if cal > tab with a given level of significance otherwise do not reject.
Conclusion
Since the analysis carried out shows that the value of chi-square calculated is 19.538 greater than chi-square tabulated 11.385 at 1% level of significance, we accept alternative hypothesis, which means that the rate of infection by typhoid among sex do not depend on quarter of the year.
4.4 INTERPRETATION
4.4.1 Investigation of The Significance Difference on The Rate of Infection of Typhoid and Malaria Among Years.
4.4.2 Investigation of The Significance Difference on The Rate of Infection of Typhoid Among Years.
Hypothesis
Ho: There is no significance difference between the rate of infection of typhoid among year.
H1 There is significance difference between the rate of infection of typhoid among year.
Decision Criteria
Reject Ho at a given level of significance if calculated value of F is greater than the tabulated F value, otherwise do not reject.
Conclusion
Since from the analysis carried out it shows that the value of F calculated is 3.58 is greater than the F tabulated 2.32 at 1% level of significance we accept the alternative hypothesis that there is significance difference on the rate of infection of typhoid fever among year.
4.4.2 Investigation of The Significance Difference on The Rate of Infection of Malaria Among Years.
Hypothesis
Ho: There is no significance difference between the rate of infection of malaria among year.
H1 There is significance difference between the rate of infection of malaria among year.
Decision Criteria
Reject Ho at a given level of significance if calculated value of F is greater than the tabulated F value, otherwise do not reject.
Conclusion
Since from the analysis carried out it shows that the value of F calculated is 6.92 is greater than the F tabulated 2.32 at 1% level of significance we accept the alternative hypothesis that there is significance difference on the rate of infection of malaria fever among year.
As a result of rejection of null hypothesis, if facilitate the used of further test which will show that year that is significantly difference on the reported cases of typhoid and malaria fever.
The further test carried out is the tukey test
INVESTIGATION USING TUKEY TEST FOR MALARIA
Hypothesis
Ho: There is no significance difference between the rate of infection of malaria among year.
H1: There is significance difference between the rate of infection of malaria among year
Conclusion
Since from the analysis carried out using the tukey test, it says that any pair of means whose corresponding confidence interval does not cover zero is declared significantly different, we can said that the rate of infection by malaria is significantly different in the year 1999 and the year 2003, mean while there is no significance difference among the remaining years under study. It means that there is high rate of infection of malaria in the year 1999 and 2003.
INVESTIGATION USING TUKEY TEST FOR TYPHOID
Hypothesis
Ho: There is no significance difference between the rate of infection of typhoid fever among years.
H1: There is significance difference between the rate of infection of malaria among year
Conclusion
Since from the analysis carried out using the tukey test, it says that any pair of means whose corresponding confidence interval does not cover zero is declared significantly different, therefore conclude that among the year under study, which is from the year 1993 2003, only the year 2003 is significantly difference, that is to day that rate of infection by typhoid in the year 2000 reduced to minimum or reduce drastically.
Interpretation
To show rate at which malaria and typhoid is infecting persons among year using the trend analysis.
` Conclusion
From the analysis carried out using time series trend it shows clearly that the rate of infection by malaria is risen, while the rate of infection by typhoid is decreasing among the years under study.
CHAPTER V
5.0 SUMMARY, CONCLUSION AND RECOMMENDATION
5.1 SUMMARY
The research was aims at analyzing the recorded number of patient reported for malaria and typhoid fever at federal medical center Gusau (FMC) Zamfara state by employing some statistical tools
The researcher is aims at investigating weather or not the rate of infection of malaria and typhoid fever among sex is significantly different, to investigate weather or not the rate of infection by the diseases among sex depend on the quarter of the year and also to investigate weather or not the rate of infection of malaria and typhoid is significantly different among years.
In the analysis using t-test it was aimed at investigating the significant different between the rate of infection of the diseases by sex.
In addition the analysis using chi-square was carried out to investigate if the rate of infection of the diseases among sex, depend on the quarter of the year.
Furthermore, the analysis using ANOVA, was aimed at investigation the significant difference on the rate of infection of diseases among years.
Finally, time series analysis also carried out is to show clearly on the trend line using the movement of the graph which among the is significantly deferent.
CONCLUSION
From the various analysis carried out, the researcher is able to come to a conclusion as follows:
From the analysis using T-test it was discovered that there is significant difference between the rate of infection of malaria by sex and also there is significant deference between the rate of infection of typhoid by sex in the analysis using chi-square, it reveal that the rate of infection of malaria among sex does not depend on the quarter of the year, and also the rate of infection of typhoid fever among sex does not depend on the quarter of the year.
One again, the analysis using ANOVA revealed that there is significance deference on the rate of infection of malaria fever among year; and further test using Tukey, revealed the year 1999 and 2003 to be the year that are significantly different, this means that the year 1999 and 2003 have the highest rate of infection which is alarming. Also it revealed that there is significance deference on the rate of infection of typhoid among the years, and the further test using tukey revealed the year 2000 to be significance difference, this means that the rate of infection by typhoid has reduce deistically in the year 2000 which we can say is a progress in the fight against typhoid fever.
Finally, the analysis using time series, show the clear picture of the rate of infection of malarial that the year 1999 and 2003 have highest rate also shows, the rate of infection of typhoid among the years, that the year 2000 is significantly different that is. It has the minimum rate infection of typhoid, which we said is a remarkable achievement in the tight against typhoid fever.
RECOMMENDATION
From the result obtained after using deferent statistical tools we have seen the rate at which malaria fever and typhoid fever affect our communities. With regard to the result obtained, we call with a strong voice on the federal government state government and even the local government in this country. To put more effort, give more attention to this deadly diseases. We are saying this because malaria only responsible for over one million death annually mostly children from Africa and also Typhoid, we are appealing to the Federal Government of Nigeria to join the rest of African countries on the global fight against these diseases, because they are deadly and health is wealth.
REFERENCES
Anumba J.U (2005): Time Series Analysis Lecture Note
Unpublished.
Fedric B.C and Donald B. (1978): Children in health And Diseases
First Edition published By cassel and
Collier Macmillan Publisher Ltd
New York.
Geneva (1894) Malaria Control As Part of Primary
Health Care
World Health Organization Study Report
KOTZ .J. (1982): Encyclopedia of Statistical Sciences
Vol. 4 A wiley inter science Publication.
Patric I.O. (2004): Design of Experiment lecture Note
Unpublished
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