Determinants of Dehydration Status and Associated Risk Factors of Cholera Outbreak in Oromia, Ethiopia

Introductions: Cholera is a diarrheal disease caused by infection of the intestine with the gram-negative bacteria Vibrio cholera. According to updated global burden of cholera estimate 2019 in Ethiopia 68,805,272 populations are at risk of cholera with incidence rate of 4 per 1000 population and case fatality of 3.8% estimated annual number of cases 275,221. Methods: The main objective of this study is to identify the signicant risk factors of dehydration status of cholera outbreak in Oromia regional state of Ethiopia. Ordinal logistic regression was used to model the data by incorporating the assumption behind this novel model. Results: The results of the study indicated that of the total 965 cholera patients, most of them 560(58%) were severely dehydrated by cholera. The overall goodness of model (p-valu=0.07) shows that the model ts the data well. Besides, the proportional odds assumption also revealed that the slop coecients in the model are the same across dehydration status (p-value=0.094). For those have history of travel, the odds of severely dehydrated versus the combined some dehydrated and no dehydrated was exp(1.133804)=3.11 times higher than those have no history of travel (p-value<0.01). All the other factors like history of contact with other patients, other sick patients in the family, Intravenous and Antibiotics drugs are statistically signicant with 5% level of signicance to determine the status of dehydration. Conclusions: The ordinal logistic regression was tted the data well and most of the included factors were signicant for the dehydration status of cholera outbreak.


Backgrounds
Cholera is a diarrheal disease caused by infection of the intestine with the gram-negative bacteria Vibrio cholerae, either type O1 or O139. Both children and adults can be infected. It is one of the key indicators of social development and remains a challenge to countries where access to safe drinking water and adequate sanitation cannot be guarantee [1] Reports revealed that approximately 1.3 billion people are at risk for cholera in the 69 cholera endemic countries. An estimated 2.86 million cholera cases occur annually in those countries [2]. Among these cases, there are an estimated 95,000 deaths has been occurred with majority burden was accounted by Sub -Saharan Africa. According to updated global burden of cholera estimate 2018 in Ethiopia 68,805,272 populations are at risk of cholera with incidence rate of 4 per 1000 population and case fatality of 3.8% estimated annual estimated number of cases 275,221 [2,3] According to WHO weekly Bulletin on outbreaks and other emergencies issued on that was 7 July 2019, from 25 April to 23 June 2019, 688 cholera cases, 23 con rmed and 15 associated deaths (Cholera case facility rate: 2.30%) have been reported from ve regions in Ethiopia. The most affected of all seven regions is Oromia (360 cases, 41%), followed by Amhara (202 cases, 23%), Afar (131 cases, 15%), Addis Ababa (125 cases, 14%), Somali (33 cases, 4%) and Tigray (19 cases, 2%). The main identi ed risk factor is said to be the contaminated water sources [4].
Different studies revealed that hand-washing, proper waste disposal, personal hygiene and making drinking water safe, health education, preparedness and surveillance at times and after outbreaks are recognized as important measures in the control of the disease [2][3][4]. Now a day the problems of acute watery diarrhea are becoming the leading health cases in Ethiopia. As Ethiopia is one of WHO regions in having cholera epidemic and is among countries that have high risked peoples, this study was fully focused on modeling the dehydration of cholera with different factors. Thus, this study was aimed to identify all signi cant factors that are responsible for the cholera outbreak. At the same time the rapid difference in the dehydration status on the peoples with cholera also discussed so that the focus of its stage was identi ed. Therefore, the research questions on identifying the risk factors of cholera, addressing the difference in the dehydration status and application of appropriate statistical model has been covered in this study.

Study Area
This study was conducted in Oromia regional state of Ethiopia. The Oromia region is one of the nine regional states of Ethiopia, the homeland of the Oromo. It is bordered by the Somali Region to the east; the Amhara Region, the Afar Region and the Benishangul-Gumuz Region to the north; South Sudan, Gambela Region, and Southern Nations, Nationalities, and Peoples' Region to the west; and Kenya to the south. It is also the largest regional state covering 286,612 square kilometers.

Source Data
The data for this study was secondary data which is obtained from Ethiopian Public Health Institute (EPHI). All cholera patients reported in for a year in 2019 has been considered for this study. Thus, 965 patients in the study area and period were considered for the study.

Response Variable
The response variable of the study was dehydration status which is coded as: Dehydration is the loss of water and uids from the body which leads to immediate death. The degree of dehydration is graded according to symptoms and signs that re ect the amount of uid lost under different criteria 3

Explanatory Variables
According to different literature and records of patient history, the following factors were identi ed. The independent variables are sex of patients, age categories of patients, travel history of patients, patients' history of contacts with other peoples, whether other sick person in the family, whether the patients vomiting, Intravenous, Antibiotics and whether the patients had lab test. The factors are coded as follow Mostly considering the method is natural for multiple categorical response having more than two possible values. And also the most well-known of these ordinal logistic regression methods is the proportional odds model. The main idea under proportional odds model is that re-expressing the categorical variable regarding a number of tertiary variables based on internal cut-points in the ordinal scale.
Therefore, the ordinal logistic regression model can be formulated as: -ln γ = β i − β 1 X 1 + β 2 X 2 + ⋯ + β n X n where I goes to the number categories minus one. As it is known, this is the part the researchers really want to investigate. So having seen the status of cholera diseases, it is clear to make ordinal response like no dehydrated, some dehydrated and severe dehydrated.
Consequently, if the researchers know that a category is ordinal then there are special models that tell us how the covariate relates to someone being higher or lower on the scale. A proportional odds model that deals limiting some factors to have common parameters and leaves other factors free to have separate parameters is called a partial proportional odds model. Therefore, the basic form the generalized linear written as follow:linkγ i = β i − β 1 X 1 + β 2 X 2 + ⋯ + β K X k exp α 1 y 1 α 2 y 2 + ⋯ + α m y m Where γ i is the cumulative probability for thei th category and β i is the threshold fori th categories,β 1 ,

Results
The results of the study indicated that of the total 965 cholera patients, most of them 560(58%) were severely dehydrated by cholera; whereas only 123(12.7%) was not dehydrated and the other 282(29.2%) was registered as somewhat dehydrated.
The graphical presentation in the Fig. 1 below is classi cation of dehydration status by age category expressed for male and female patients separately. It clearly shows that both male and female patients aged 15-44 were the most severely dehydrated compared to the other age groups. In all dehydration status, the 15-44 age groups were counted to be the largest group included as cholera infected in the study area and/or period. The graphical results supported the frequency results above that the severe dehydrated were exceeding the other stages.
The Table1 below is the summary of chi-square test of association between dehydration status and the identi ed factors. It indicated that there is no enough evidence to say that sex of patients their age group and whether they vomiting have signi cant association with dehydration status. Despite, history of travel, history of contact, other sick person in the family, IV, antibiotics and lab test has statistically signi cant  level of signi cance. Thus, the researcher can conclude that those factors are potential in determining the status of dehydration. The goodness of model t of Table 3 (Appendix) shows that the model t the data well. The test of parallel lines of Table 4(in the appendix) is also revealed that the assumption is ful lled.

Discussions
The descriptive results of the study indicated that of the total 965 cholera patients, most of them 560(58%) were severely dehydrated by cholera. Many other previous studies also revealed that the status of dehydration of patients was categorized under severity.
Most the factors included in study have signi cant association with severity of cholera and its dehydration status. However, sex of patients and their age categories was no signi cant to determine the status of cholera dehydration. The results of Pearson chi-square test of association indicated that history of travel of patients (p-value < 0.001), history of patients contact with other patients (p-value < 0.001), whether there is other sick patients in the family (p-value < 0.001), whether intravenous was given (pvalue < 0.05), whether antibiotics was given (p-value < 0.01) and whether the patients had lab test (pvalue < 0.01) have signi cant association with the dehydration status of cholera outbreak at 1% and 5% level of signi cance. Hence, the result was consistent with the previous work by [2,4] The ordinal logistic regression, model presented in Table 2 [5,6] Likewise the other factors like whether the patients had intravenous injection and whether the antibiotics treatment was given by the patients was included in the study and found signi cant with 1% and 5% level of signi cance. Other previous studies are also consistent with this result [7][8][9] The results of cut1 (-1.738741) in Table 2 above refers to the estimated cut-point on latent variable to differentiate no dehydrated from some dehydrated and severe dehydrated when the value of all predictors are evaluated at their reference categories. Whereas cut2 (.186633) is the estimated cut-point used to differentiate some dehydrated from no dehydrated and severe dehydrated keeping the factors to be at their reference.
Proportional odds assumption of ordinal logistic regression was meet for this study (p-value = 0.094) which is to mean that the effects of explanatory variables over all the categories of dehydration status was expected to be similar.

Conclusions
This study was aimed to identify the risk factors of cholera dehydration status in Oromia regional state with the secondary data obtained from EPHI. The ordinal logistic regression was used to determine the Classi cation of dehydration status by age category expressed for male and female patients