Determinants of Cholera Outbreak in Bati District and Bati Town, Oromo Special Zone, Amhara Region, Ethiopia (2024): An Unmatched Case-Control Study

Determinants of Cholera Outbreak in Bati District and Bati Town, Oromo Special Zone, Amhara Region, Ethiopia (2024): An Unmatched Case-Control Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Determinants of Cholera Outbreak in Bati District and Bati Town, Oromo Special Zone, Amhara Region, Ethiopia (2024): An Unmatched Case-Control Study Tenaw Yibeltal Desalegn¹, Melaku Girma Haile2, Abtew Abera Abebe¹, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8307931/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Background: Cholera continues to pose a threat to public health and is frequently linked to injustice and a lack of social development. The study area has a history of recurrent cholera outbreaks. However, local risk factors remain unidentified, which challenges the targeted prevention and control measures. Therefore, this study identifies the potential risk factors and makes it easier to apply targeted interventions. Methods: We conducted a 1:1 unmatched case-control study (117 cases and 117 controls). An interviewer-administered questionnaire was used to collect data. SPSS version 27 was used to calculate frequencies and odds ratios. We performed the enter method for binary logistic regression to determine the independent factors associated with cholera infection. Results: Interviews with 234 study participants showed a 1.7% case fatality rate and an overall attack rate of 32 per 10,000. Males had a higher chance of being affected by cholera [AOR = 2.3, 95% CI: 1.1-5.1]. Attending a gathering increased the risk of cholera infection [AOR = 42.2, 95% CI: 13.6-55.1]. Those who didn’t wash their hands before a meal was more likely to contract cholera than those who did [AOR = 4.2, 95% CI: 1.6-10.7]. Similarly, those who did not wash their hands with soap at key periods had an increased chance of contracting cholera [AOR = 4.2, 95% CI: 1.6-10.7]. Consumption of water from an unprotected source increased the risk of cholera infection (AOR = 2.9, 95% CI: 1.3-6.4). Conclusions: In this study, the primary risk factors for the cholera outbreak were participating in social gatherings, using water from unprotected sources, and poor hygiene practices. Therefore, increasing access to safe drinking water sources, improving community awareness on good hygiene and sanitation practices, and promoting healthy social gatherings are priority interventions in the study area. Bati District Bati Town Risk factors case-control study cholera outbreak Figures Figure 1 Figure 2 Figure 3 Introduction Cholera is a serious disease that causes sudden and intense diarrhea, most often spread through dirty water or contaminated food. It mainly affects people living in places where clean water and sanitation are limited, and it affects the poorest communities the hardest. Without quick treatment, cholera can make people dangerously dehydrated and even lead to death, especially in areas where healthcare is hard to access. Even though there are vaccines to help prevent cholera, many people are still at risk, and new forms of the bacteria that resist antibiotics are making it harder to control (1, 2). This makes it crucial to find new ways to protect people and stop the spread of the disease. Cholera outbreaks often happen where people live in crowded conditions, face poverty, or don’t have reliable access to clean water and toilets. Since 1817, there have been seven major worldwide cholera outbreaks, and the disease still affects many poor communities today. The real number of people who get sick or die from cholera is probably much higher than what’s reported, because many cases go uncounted, and some areas don’t have the resources to test for the disease. Every year, cholera is believed to make between 1.3 and 4 million people sick, and it causes anywhere from 21,000 to 143,000 deaths. Tragically, about half of those who die are children under five. Cholera remains a serious and ongoing threat to public health in many parts of the world (3). Prevention and control of cholera involve a combination of measures, including improving access to safe water and sanitation, promoting good hygiene practices, and providing vaccination in high-risk areas. The following are some of the strategies that have been used to prevent and control cholera: Provision of safe water and sanitation facilities. Access to safe water and sanitation facilities is essential in preventing cholera. This can be achieved through the provision of clean water sources, such as wells and boreholes, and the construction of latrines and handwashing stations. Promotion of good hygiene practices: good hygiene practices, such as handwashing with soap and water, can help prevent the spread of cholera. Health education campaigns can be used to promote these practices. Vaccination: Vaccination is an effective way to prevent cholera in high-risk areas. Oral cholera vaccines are available and are effective in reducing the incidence of cholera. Early detection and treatment: Early detection and treatment of cholera cases can help prevent the spread of the disease. Treatment involves rehydration with oral rehydration solution or intravenous fluids and the use of antibiotics in severe cases. Surveillance and outbreak response: Surveillance systems can help detect cholera outbreaks early, allowing for a rapid response to prevent further spread of the disease. In summary, prevention and control of cholera require a combination of measures, including improving access to safe water and sanitation, promoting good hygiene practices, providing vaccination in high-risk areas, early detection and treatment, and surveillance and outbreak response (4, 5). The global burden of cholera is largely unknown because the majority of cases are not reported. The low reporting can be attributed to the limited capacity of epidemiological surveillance and laboratories, as well as social, political, and economic disincentives for reporting. We previously estimated 2.8 million cases and 91,000 deaths annually due to cholera in 51endemic countries. A major limitation in our previous estimate was that the endemic and non-endemic countries were defined based on the countries’ reported cholera cases. We overcame the limitation with the use of a spatial modeling technique in defining endemic countries and accordingly updated the estimates of the global burden of cholera(6). This research aims to assess the situation of the outbreak, determine the cause and source, describe cases epidemiologically, and apply intervention measures to overcome the current outbreak and prevent similar events in the future. Methods Study Setting Bati Town and Bati district are found in the Oromo Special Zone, Amhara region. Bati Woreda is one of the second largest districts in the Oromo Special Zone, which is administered by a total of 26 kebeles, and Bati town consists (4 urban and 2 rural). Both have a total population of 143,015 population of which females constituted 70,793 (49.5%) from the 2007 census estimate. These two districts have one primary hospital, 8 HC, and 28 health posts, which are currently in service. The physical health service coverage of the two districts was 100%. Study Design and Period An unmatched community-based case-control study was conducted between April 10 -30/2024 with a ratio of 1:1 case to controls. Source Population The study populations were all community members living in cholera-affected kebeles of Bati district and Bati town. Study Population The study population consisted of all cholera cases that met the standard case definition, as well as selected control individuals who were at risk of cholera exposure but did not develop any signs or symptoms of the disease in Bati Town and Bati District between April 4 and April 30, 2024. Eligibility criteria Inclusion Criteria Cases: All individuals who were positive for cholera and epidemiologically linked to cholera cases in the outbreak period, and those who agreed to participate in the study were included. Controls : Any resident of Bati District and Bati Town who lives with a cholera case, either as a household member or neighbor, and who does not exhibit signs or symptoms of cholera and agrees to participate, was included. Exclusion criteria Cases: Individuals not residing in the study area during and three weeks before the period of an outbreak were excluded. Controls: Individuals who were not residing in the study area, such as temporary visitors and those who refused to participate, were excluded. Data source Medical records of cases (patient charts) at Bati Health Center, Bati Rural CTCs, and cholera patient line lists were reviewed as secondary data. A face-to-face interview, using a structured questionnaire, was conducted to obtain data from adult cases and controls. Data from children was obtained by interviewing caregivers. Sample Size Determination The sample size was computed using Epi Info version 7.2 statistical software, considering the following assumptions: 95% CI, power 85%, 1:1 ratio of controls to cases. The sample size was 117 cases and 117 controls. Sampling process We conducted an unmatched case-control study to identify determinants of the cholera outbreak in 15 kebeles of Bati Woreda and 6 kebeles of Bati Town. A total of 117 confirmed and epidemiologically linked cases were recruited from the official line list. Controls were randomly selected from the same source population among individuals who had not developed cholera. For each case, a control was chosen using a lottery method. Whenever possible, neighbors were selected to ensure similar environmental exposures. If multiple eligible neighbors were available, one was randomly drawn. If no suitable neighbors were found, a non-affected family member was randomly selected. Trained field data collectors facilitated the selection process and obtained informed consent. The random selection minimized selection bias and improved comparability by ensuring both cases and controls were exposed to similar community conditions. Study Variables Dependent variable Cholera Case (Yes, No) Independent variable Socio-demographic factors: Such as Age, sex, educational level of the participant, occupational status of the participant, marital status, and family size. Clinical Factors: Such as signs of diarrhea, vomiting, back pain, joint pain, date of onset of illness, date of seen health facility, contact history, treatment taken, travel history, awareness on prevention and control of cholera, and mode of transmission. Exposure Information: Exposure to raw food (Yes/No); Eating outside the home (Yes/No); Attendance at gatherings (Yes/No); Travel history outside the village (Yes/No) Sanitation and Hygiene Practices: Handwashing practices (Yes/No) ; Frequency of handwashing before meals (Sometimes/Always) ; Soap use for handwashing (Yes/No) ; Latrine availability (Yes/No) ; Latrine utilization (Used by all, some, or not used) ; Handwashing facility near the toilet (Yes/No) Water-Related Practices: Water source (Pipe/Spring/River/Hand Dug) ; Water purification method (Yes/No, and method details) ; Treated water usage in the past week (Yes/No) ; Water storage container type (Jerry can/Bucket) ; Water fetching method (Deeping/Incling with cup/Always inside) ; Water storage cleaning frequency (Every day/Every other day/Every week/Other) Clinical Exposure: Family members with similar symptoms (Yes/No) ; Number of family members sick (Numerical) ; Contact with patients with similar symptoms (Yes/No) Awareness: Awareness of transmission of AWD/cholera (Yes/No) ; Awareness of prevention methods (Yes/No) Case definitions Community case definition Suspected cholera case : If any person 2 years or older with profuse acute watery diarrhea and vomiting. Standard case definition Suspected case: In areas where a cholera outbreak has not been declared, any person aged 2 years or more presenting with acute watery diarrhea and severe dehydration or dying from acute watery diarrhea. In areas where a cholera outbreak has been declared, any person aged 2 years or more presenting with or dying from acute watery diarrhea. Confirmed case: A suspected case in which Vibrio cholera O1 or O139 has been isolated from their stool . Epidemiologically linked cases : A case in which the patient has had contact with one or more individuals who have the disease, and where transmission of the agent through the usual modes of transmission is plausible. A case may be considered epidemiologically linked to a laboratory-confirmed case if at least one case in the chain of transmission is laboratory-confirmed(14). Operational definition s Cholera contact: exposure to the bacterium Vibrio cholera, which can occur through various means such as consuming contaminated food or water, or being near an infected individual(15) Cholera outbreak: a cholera outbreak involves the detection of confirmed cholera cases in a specific area. Incubation period: The incubation period is usually 1 to 3 days, but can range from several hours to 5 days. Symptoms usually last 2 to 3 days, although in some patients they can continue up to 5 days. Infectious period: Infected persons, whether they are symptomatic or not, can carry and transmit Vibrio for 1 to 4 weeks; a small number of individuals can remain healthy carriers for several months Control: Any resident of Bati Town and Bati district during the study period who was living together with a case at home or a neighbor who did not develop signs and symptoms of cholera. Exposure Information: Refers to data or details about factors that might have made individuals or populations vulnerable to contracting cholera. Data collection method Data was collected by trained health professionals through face-to-face interviews with cases and controls using structured and semi-structured questionnaires developed for this study. Additional data were gathered from the cholera line list. The WHO case definition was used to classify study participants as either cases or controls. Data Processing and Analysis The data were coded, entered, and cleaned into EPI Data version 4.6.6 and then exported to SPSS version 27 for analysis. The result was presented by words, tables, and figures. An epidemic curve was constructed to examine the development of epidemics over time. We executed the enter method for simple and multivariable binary logistic regression to determine the independent factors associated with the development of Cholera. A variable with a p-value less than or equal to 0.25 in the bivariable analysis was considered to be a candidate variable for multivariable logistic regression to identify the independent predictors of Cholera. And then variables that are significant with a P- P-value of less than or equal to 0.05 at a 95% confidence interval in multivariable binary logistic regression were considered statistically significant. Both 95% CI and P-values were used to assess the associations between dependent and independent variables. In all cases, odds ratios were used to assess the strength of the association. The model goodness of fit was checked by the Hosmer and Lemeshow Test. Data Quality Control Before data collection, a half-day training was given for health workers who were assigned at Bati and Fura CTCs. Each question was asked clearly for cases and controls in a similar manner during the interview. Data was also cleaned for any missing and logically inconsistent values before analysis by running the frequency and cross-tabulation of each variable with the outcome variable. Ethical consideration A permission letter was written from the Oromo Special Zone Health Department to Bati Town and the Bati district health office. For those study participants aged 18 and above, written consent forms were taken and for children’s parents or caretakers took consent forms to take part in the study. Participants' right to withdraw from the study as they wish was also clearly stated before the interview started. The responses were confidential and analysis were as groups not for individual case or control. Dissemination of the findings The result of the study will be shared with the Bati district and Bati town health offices, Oromo Special Zone health department, and Amhara Public Health Institute. The findings will be presented at district and zonal level review meetings, and also it could also be prepared for publication. Results Descriptive Analysis This study included a total of 234 study participants, 117 cholera cases, and 117 controls. Among the total cholera cases, 14 tested positive by rapid diagnostic test (RDT), and 11 of these were confirmed by culture. The remaining cases were classified based on the standard case definition and epidemiological linkage. All cases were admitted to a Cholera Treatment Center (CTC) or an Oral Rehydration Point (ORP). A total of five cholera-related deaths were recorded, with four occurring at healthcare facilities and one in the community before admission to the CTC. Sociodemographic Characteristics A total of 264c individuals, 117 cases, and 117 controls were interviewed. The response rate of this study was 100%. Out of the 234 study participants, 119 (50.9%) were females, and the rest were males. Family size of the study participants: 129(55%) had less than five families per household, and the rest 105(45%) of the participants had greater than 5 families per household. The majority of study Participants, 194 (82.9%), were aged greater than 15 years. Among all 234 participants, 27 (29.3%) were unable to read or write, followed by 21 (22.8%) who could read and write. Nearly half of the participants, 116 (49.5%), were farmers (Table 1). Table 1: Socio-demographic characteristics of Cholera cases and controls in Bati district and Bati town, Oromo zone, Amhara region, 2024 Variables Cases(N=117) Controls(N=117) Total N=134 Number Percent Number Percent Number (%) Sex Male 64 55% 51 44% 115(49.1%) Female 53 45% 66 56% 119(50.9%) Age Less than 5 years 15 13% 10 9% 15(6.4%) 5-14 years 28 24% 11 9% 25(10.7%) >=15 years 74 63% 96 82% 192(82.9%) Occupation Student 13 11% 1 1% 14(6%) Farmer 52 44% 64 55% 116(49.5%) Merchant 2 2% 7 6% 9(3.8%) Teacher 2 2% 0 0% 2(1%) Housewife 14 12% 45 38% 59(25.2%) Other 34 29% 0 0% 34(14.5%) Educational status Not read and write 63 54% 92 79% 155(66.2%) Read and write 13 11% 5 4% 18(7.7%) Primary 18 15% 14 12% 32(13.7%) Secondary 6 5% 6 5% 12(5%) College and above 2 2% 0 0% 2(1%) NA 15 13% 0 0% 15(6.4%) Number of family members 5 76 65% 53 45% 129(55%) Marital status Married 60 45% 89 70% 149(63.6%) Single 18 15% 4 3% 24(10.2%) Divorced 2 2% 5 4% 7(3%) Widowed 6 3% 9 5% 13(5.6%) NA 21 35% 20 17% 41(17.6%) Clinical Presentation of Cases Among all suspected cases, 116 (99%) had both diarrhea and vomiting, 99 (89%) had vomiting, and 19 cases (12.6%) had back pain, 17 cases (14.5%) had arthralgia, and 17 cases (14.5%) had muscle pain (myalgia). Regarding dehydration status among suspected cholera cases, 22 patients (18.8%) had no dehydration, 42 (35.9%) had some dehydration, and 53 (45.3%) suffered from severe dehydration (Figure 2). Of the total cholera cases, 105 (89.7%) received treatment after being admitted to a Cholera Treatment Center (CTC) or as inpatients. All patients diagnosed with severe dehydration received antibiotics and IV fluids, while the remaining cases were treated with oral rehydration solution (ORS). Distribution of Cholera cases by place This cholera outbreak has affected two districts within the Oromo Special Zone administration. As shown in Table 2 below, the highest number of cases was reported from Bati district, with 230 cases (78.2%) from 15 kebeles (57.7%) and 64 cases (21.8%) from 6 kebeles in Bati town (Table 2). Among the total cholera cases, five individuals died from four kebeles, resulting in a case fatality rate (CFR) of 1.7%. The overall Attack Rate (AR) was 32 per 10,000 people. A total of 302 people were affected between April 6 and May 17, 2024. Additionally, six cases were reported from the Dewe Harewa district, and two cases from the Afar region. Out of the total cases in Bati district, 19 were treated at the Bati town Cholera Treatment Center (CTC)(Figure 3). Distribution of cholera cases by Person Over 96,000 people were at risk for a cholera outbreak in Bati Town and Bati District, which has resulted in 294 cases and 5 fatalities (1.7% CFR). Bati district was more affected, as evidenced by 78.23% of cholera cases being reported from the district. Most cholera-affected kebeles were Chekorti (80 cases) and Cheleleka (52 cases). The greatest fatality rate was 10.5% for Teamelka. Table 2.Distribution of Cholera Cases, Population at Risk, Attack Rate (AR), and Case Fatality Rate (CFR) in Bati District and Bati Town, Oromo Zone, Amhara Region, 2024. Name of affected District Kebele Risk population Number of Cholera cases Attack rate per 10,0000 Number of deaths Case fatality rate (%) Remark Bati Town Bati 01 6826 6 9 0 0.0 Bati 02 7471 20 27 1 5.0 Bati 03 7684 27 35 1 3.7 Bati 04 6315 3 5 0 0.0 Kame 4391 6 14 0 0.0 Salmene 9278 2 2 0 0.0 Bati Town 41965 64 15 2 3.1 Bati District Bira 5,942 11 19 0 0.0 Bofa 3,562 1 3 0 0.0 Burka 1,847 1 5 0 0.0 Chekorti 3,254 80 246 0 0.0 Cheleleka 2,376 52 219 1 1.9 Damto 3,966 2 5 0 0.0 Fura 4,080 48 118 0 0.0 Gerfa Urene 4,281 3 7 0 0.0 Gure 3,025 1 3 0 0.0 Hato 3,146 3 10 0 0.0 Kebele 3,697 4 11 0 0.0 Kurkura 3,914 2 5 0 0.0 Melka Lugo 4,993 1 2 0 0.0 Teamelka 3,776 19 50 2 10.5 Uungu 4,109 2 5 0 0.0 Bati District 54,124 230 42 3 1.3 Total 96,089 294 31 5 1.7 Distribution of Cholera Cases by Time Among all 117 cholera cases that were included in the study, 64 cases (54.7%) were male, and 53 cases (45.3%) were female. The age of the study participants, cholera patients, ranged from 1 to 90 years. In the two study areas, the overall case fatality rate (CFR) was 1.7%, with an Attack Rate (AR) of 32 per 10,000 population. Age-specific case distributions were as follows: 15 cases (8.5%) were in children under five years old, 25 cases (21.4%) were in the 5- 14-year age group, and 77 cases (65.8%) were in individuals aged 15 years and older. After receiving reports from Genda Habure Gotte, on April 2, 2024, Hato Health Center admitted the first four cases of food poisoning. The identification of these four cases as the index cases was verified by the detection of 15 additional suspected cholera cases from the same outbreak, after four days. These 15 cases were reported on April 6, 2024. The highest number of cholera cases was reported on April 20, 2024, with 32 cases. The last date of the outbreak was on May 15, 2024, when 15 cholera cases were reported (Figure 4). Risk factors for cholera outbreak : The presence of several predictive factors for a cholera outbreak posed significant challenges in containing and controlling it within a short period before it spread to other kebeles. Less than one-quarter of respondents had access to a latrine, and two-thirds were unaware of cholera prevention methods. The risk factor distribution among cholera cases and controls is presented in Table 3. Table 3: Risk factors distribution among cholera cases and controls in Bati district and Bati town, Oromo zone, Amhara region, Ethiopia, May 2024 Risk factors Category Cases(n=117) Controls(n=117) Total(N=234) Number % Number % Number % Eat anything outside the home in the past 5 days Yes 17 15% 1 1% 18 8% No 100 85% 116 99% 216 92% Attending gatherings Yes 68 58% 5 4% 73 31% No 49 42% 112 96% 161 69% History of travel outside of the village 5 days before the onset of illness Yes 6 5% 3 3% 9 4% No 111 95% 114 97% 225 96% Hand washing before a meal Yes 65 56% 100 85% 165 71% No 52 44% 17 15% 69 29% Use of soap for hand washing Yes 20 17% 40 34% 60 26% No 97 83% 77 66% 174 74% Latrine Ownership Yes 23 20% 25 21% 48 21% No 94 80% 92 79% 186 79% Hand washing practice after using the toilet (defecating) Yes 8 7% 21 18% 29 12% No 109 93% 96 82% 205 88% The water source for drinking Pipe 11 9% 17 15% 28 12% Spring 7 6% 8 7% 15 6% River 51 44% 27 23% 78 33% Hand Dug 48 41% 65 56% 113 48% The presence of a family member with the same illness Yes 52 44% 11 9% 63 27% No 65 56% 106 91% 171 73% History of patients having the same signs and symptoms Yes 43 37% 12 10% 55 24% No 74 63% 105 90% 179 76% Know the mode of transmission of AWD/cholera Yes 37 32% 43 37% 80 34% No 80 68% 74 63% 154 66% know the methods of prevention of AWD/cholera Yes 37 32% 46 39% 83 35% No 80 68% 71 61% 151 65% Factors associated with a cholera outbreak in Bati town and Bati woreda Simple and multivariable binary logistic regression analyses were used to calculate odds ratios and 95% confidence intervals for the predictors of the Cholera outbreak. In the first step, bivariable analysis was used to select candidate variables for multivariable analysis at a P-value less than 0.25. The candidate variables analyzed in multivariable analysis with a P-value less than 0.05 were considered significant. The final model was used to analyze variables related to sociodemographic factors, cholera exposure factors, Sanitation and Hygiene practices, Water utilization practices, Clinical exposure, and factors related to the knowledge of the study participants. In the final multivariable logistic regression analysis model, the following variables were associated using the enter method. The odds of developing cholera were more than twice as high in males compared to females (AOR = 2.3, 95% CI: 1.1–5.1). The likelihood of being infected with cholera was 42 times higher among individuals who attended gatherings compared to those who did not (e.g., those who did not attend gatherings like Sodeka) (AOR = 42.24, 95% CI: 13.615–55.1). Study participants who did not wash their hands before meals were four times more likely to contract cholera compared to those who practiced handwashing (AOR = 4.2, 95% CI: 1.6–10.6). The odds of contracting cholera were four times higher among study participants who did not wash their hands with soap compared to those who used soap for handwashing (AOR = 4.2, 95% CI: 1.6–10.6). Participants with a family member who was ill with cholera were twelve times more likely to contract cholera than those without a sick family member (AOR = 12, 95% CI: 4.7–30.9). The likelihood of becoming infected with cholera was three times higher among individuals who drank from unprotected water sources compared to those who drank from protected water sources (AOR = 2.9, 95% CI: 1.3–6.4) (Table 4). Table 4: Bivariate and multivariable logistic regression analysis of factors associated with cholera outbreaks, Bati District and Bati town, Oromo special zone, Amhara region, Ethiopia,2024. Variables Categories Disease status COR (95%CI) AOR (95%CI) P-value Case Controls Sex Male 64(54.7%) 51(43.6%) 1.56(0.93,2.62) 2.32(1.06,5.07) 0.036* Females 53(45.3%) 66(56.4%) 1 1 Family Size 5 76(65%) 53(45.3%) 2.29(1.35,3.89) 0.5(0.229,1.11) Attending Gathering (Sodeka) Yes 68(58%) 5(4.3%) 31.09(11.81,81.86) 42.24(13.62,55.07) 0.0001* No 49(42%) 112(95.7%) 1 1 Hand washing before meals Yes 65(55.6%) 100(85.5%) 1 1 0.003* No 52(44.4%) 17(14.5%) 4.71(2.51,8.84) 4.16(1.64,10.56) Hand washing with soaps Yes 20(17%) 40(34.2%) 1 1 0.044* No 97(83%) 77(65.8%) 2.52(1.36-4.67) 4.16(1.64,10.56) Hand washing after toilet Yes 8(6.8%) 21(18%) 1 1 0.26 No 109(93.2%) 96(82%) 2.98(1.262,7.04) 2.55(0.50,12.97) Presence of an ill family member Yes 52(44.4%) 11(9.4%) 1 1 0.0001* No 65(55.6%) 106(90.6%) 7.71(3.752,15.838) 12.04(4.69,30.89) Water sources Protected 59(50.4%) 82(70%) 1 1 0,009* Un protected 58(49.6%) 35(30%) 2.30(1.47,3.94) 2.88(1.30,6.37) Contact history Yes 43(36.8%) 12(10.3%) 1 1 0.725 No 74(63.2%) 105(89.7%) 5.08(2.511,10.30 0.7(0.096,5.12) Know prevention mechanisms Yes 37(31.6%) 46(39.3%) 1 1 0.469 No 80(68.4%) 71(60.7%) 1.40(0.818,2.39) 0.72(0.291,1.77) Discussion This study revealed that the overall attack rate (AR) was found to be 31 per 10,000 population. This is lower than studies conducted in Uganda (32/10,0000)( 8 ), Western Kenya ( 9 ), Mile district of Afar region, (83/10,000) ( 16 )and west Arsi, Oromia region, Ethiopia (230/10,000)( 17 ), But it is higher than a study done in Kirkos sub city, Addis Ababa, Ethiopia (14.3/10,000)( 13 ). This variation might be due to source of outbreak, early detection or surveillance system and response activities. The case fatality rate (CFR) was 1.7% which is lower than the WHO African region February 2024 report (1.9%)( 18 ), Uganda (2.1%)( 8 ), Mile district (7.8%)( 16 ), and Werst Arsi (2.3%)( 17 ). However, it is higher than a study conducted in Kirkos sub-city of Addis Ababa, Ethiopia, showed that there were no deaths reported due to a cholera outbreak. Possible explanations for this difference could be the strength of surveillance activity, the quality of case management, and the availability of supplies and drugs. In this study, males were more attacked by cholera disease than females. This was supported by a study conducted in Kirkos Sub City, Addis Ababa( 13 ). This might be justified by the fact that males most of the time, work, eat food, and drink water outside their home, which may expose them to cholera infection. Those who attended any gathering were 42 times more likely to be infected with cholera than those who didn’t participate in gatherings. A possible explanation for this might be that any gathering increases the transmission of cholera because there will be a high probability of eating food and drinking water contaminated by Vibrio cholera. In the current investigation, study participants who didn’t use soap to wash their hands were four times become ill with cholera than their counterparts. This is in line with studies done in Addis Ababa, Ethiopia( 13 ) and Yemen( 7 ). This could be due lack of water, a lack of toilets, an increase in soap prices, or a lack of awareness. This study found that using water from unprotected sources, such as rivers and spring water, was a significant predictor of the cholera outbreak. This aligns with findings from studies conducted in Yemen, Uganda ( 8 ), Benishangul Gumuz ( 12 ), and the Mile district of the Afar region ( 16 ). The higher risk associated with these sources may be due to their increased susceptibility to contamination compared to protected water sources, such as piped water and hand-dug wells. These findings support the hypothesis proposed by healthcare workers, who identified unprotected river water as the source of the outbreak. This hypothesis was formed after observing that most cholera cases were among individuals who used river water for drinking and washing, due to limited access to safe water in the area. Furthermore, the geographic distribution of cholera cases closely followed the river basins. Collectively, this evidence suggests that the primary source of the outbreak in the study area was the consumption of river water. The findings of this study indicate that the likelihood of contracting cholera was 42 times higher among individuals who attended gatherings compared to those who did not, such as those who avoided gatherings like Sodeka (AOR = 42.24, 95% CI: 13.615–55.1). This significant association suggests that social gatherings played a critical role in the transmission of cholera, likely due to close contact and the shared consumption of contaminated food or water. These findings align with previous studies that have shown an increased risk of cholera transmission in crowded settings or during large gatherings. For instance, a study conducted in Yemen during a cholera outbreak found that attendees of public gatherings, including religious festivals and weddings, were at a higher risk of infection due to the lack of sanitation and safe drinking water [,35]. Similarly, in a study in Bangladesh, it was observed that cholera outbreaks were frequently linked to mass gatherings, where limited access to safe water and poor hygiene practices contributed to the rapid spread of the disease [36]. The high risk associated with attending gatherings in this study could be attributed to several factors, including the sharing of food and drink in unsanitary conditions, overcrowding, and inadequate access to hygiene facilities. These factors likely facilitated the transmission of Vibrio cholerae, the bacteria responsible for cholera, among attendees. Furthermore, these results highlight the importance of public health interventions focused on improving hygiene practices and water and sanitation at mass gatherings to prevent future outbreaks. This finding supports the second hypothesis proposed by healthcare workers, which suggests that the outbreak was waterborne and resulted from the consumption of unsafe water and food during a social gathering event, locally known as 'Sodeka.' The food served at this gathering was prepared with water fetched from a contaminated river on April 1, 2024, in Genda Habure Gotte of Fura Kebele, Bati District. Approximately 150 people from neighboring kebeles and districts attended the Sodeka program, and most of them contracted the disease. In this study, participants with a family member affected by cholera were twelve times more likely to contract the disease than those without a sick family member. This finding is consistent with studies conducted in the Afar ( 16 ) and Oromia ( 17 ) regions of Ethiopia. This increased risk may be attributed to low awareness among family members regarding the modes of transmission and prevention methods for cholera. Conclusion The cholera outbreak was primarily caused by drinking contaminated water from unprotected sources, participating in social gatherings, and practicing poor hygiene, such as not washing hands with soap. The findings support the hypothesis that river water poisoning played a significant role in the outbreak due to the fact that a significant number of the illnesses were caused by drinking water consumed during a crowd. Therefore, in order to prevent and early containment of future cholera outbreaks early, various governmental and non-governmental organizations, such as government health sectors, water and sanitation sectors, municipalities, district administrative bodies, local community administrations, and the affected community, have to work in collaboration. Increasing access to safe drinking water sources, improving community awareness on good hygiene and sanitation practices, and promoting healthy social gatherings might minimize the risk for cholera spread and hence prevent the occurrence of similar outbreaks in the future. Declarations Ethical Approval and Consent to Participate: Ethical approval and consent to participate were obtained from the Amhara Public Health Institute, Dessie Branch. Verbal or written informed consent was obtained from all participants data collection, in accordance with ethical guidelines. Consent for Publication : Not applicable. Funding : This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Availability of Data and Materials : The datasets generated and/or analyzed during the current study are not publicly available due to government and institutional restrictions on data sharing related to outbreak surveillance data, but may be made available from the corresponding author upon reasonable request and subject to approval by the relevant authorities. Author Contribution **Tenaw Yibeltal Desalegn** : Conceptualization, study design, data collection, data analysis, manuscript drafting.**Melaku Girma:** Conceptualization, study design, data collection, data analysis, manuscript drafting. **Abtew Abera Abebe:** Data collection, data analysis, manuscript review. **Anteneh Demelash Abate:** Data collection, interpretation, manuscript review. **Melaku Girma Haile:** Supervision, technical support, manuscript review. **Mohamed Ahmed Seid:** Data analysis support, interpretation, and manuscript review. **Seid Mohamed Seid** : Senior supervision, critical manuscript review, and approval.All authors reviewed and approved the final manuscript. Acknowledgement I would like to offer my gratitude for the Amhara Public Health Institute, Dessie branch, Oromo Special Zone health department for their support during the study period. I would also like to express my appreciation to the community in Bati Woreda and Bati Town for their cooperation during data collection. References Naidu A, Lulu SS. Mucosal and systemic immune responses to Vibrio cholerae infection and oral cholera vaccines (OCVs) in humans: a systematic review. Expert Rev Clin Immunol. 2022 Dec;18(12):1307-18. PubMed PMID: 36255170. Epub 2022/10/19. eng. Platts-Mills JA, Babji S, Bodhidatta L, Gratz J, Haque R, Havt A, et al. Pathogen-specific burdens of community diarrhoea in developing countries: a multisite birth cohort study (MAL-ED). The Lancet Global Health. 2015;3(9):e564-e75. Deen J, Mengel MA, Clemens JD. Epidemiology of cholera. Vaccine. 2020 Feb 29;38 Suppl 1:A31-a40. PubMed PMID: 31395455. Epub 2019/08/10. eng. Bartram JK, Howard G, editors. Prevention and control of cholera1994. Mel DM. [Modern aspects in the prevention and control of cholera]. Glas Srp Akad Nauka Med. 1981 (33):105-12. PubMed PMID: 6927228. Epub 1981/01/01. Ali M, Nelson AR, Lopez AL, Sack DA. Updated global burden of cholera in endemic countries. PLoS Negl Trop Dis. 2015;9(6):e0003832. PubMed PMID: 26043000. Pubmed Central PMCID: PMC4455997. Dureab F, Jahn A, Krisam J, Dureab A, Zain O, Al-Awlaqi S, et al. Risk factors associated with the recent cholera outbreak in Yemen: a case-control study. Epidemiology and Health. 2019;41. Monje F, Ario AR, Musewa A, Bainomugisha K, Mirembe BB, Aliddeki DM, et al. A prolonged cholera outbreak caused by drinking contaminated stream water, Kyangwali refugee settlement, Hoima District, Western Uganda: 2018. Infectious Diseases of Poverty. 2020;9:1-10. Oyugi EO, Boru W, Obonyo M, Githuku J, Onyango D, Wandeba A, et al. An outbreak of cholera in western Kenya, 2015: a case control study. The Pan African Medical Journal. 2017;28(Suppl 1). Matapo B, Chizema E, Hangombe B, Chishimba K, Mwiinde A, Mwanamwalye I, et al. Successful multi- partner response to a cholera outbreak in Lusaka, Zambia 2016: a case control study. Medical Journal of Zambia. 2016;43(3):116-22. Alemayehu E, Tilahun T, Mebrate E. Determinants of Dehydration Status and Associated Risk Factors of Cholera Outbreak in Oromia Ethiopia. Biomed Stat Inform. 2020;5(3):60. Ayalew F, Abebe G. Acute Watery Diarrhea/Cholera outbreak Investigation in Wenbera District, Metekel Zone, Benishangul Gumuz Region, Western Ethiopia September 1-October20/2016. Journal of American Science. 2020;16(8). Tadesse T, Zawdie B. Cholera outbreak investigation in four districts of Kirkos sub-city in Addis Ababa, Ethiopia: A case-control study. 2019. Case Definitions A. Case Definitions for Public Health Surveillance. George CM, Hasan K, Monira S, Rahman Z, Saif-Ur-Rahman KM, Rashid MU, et al. A prospective cohort study comparing household contact and water Vibrio cholerae isolates in households of cholera patients in rural Bangladesh. PLoS Negl Trop Dis. 2018 Jul;12(7):e0006641. PubMed PMID: 30052631. Pubmed Central PMCID: PMC6063393. Epub 2018/07/28. eng. Abye T, Mekonen H, Amene K, Bisrat S. Cholera outbreak investigation report in Mille woreda, Afar region, Ethiopia, 2019. 2022. Bartels SA, Greenough PG, Tamar M, VanRooyen MJ. Investigation of a cholera outbreak in Ethiopia's Oromiya region. Disaster medicine and public health preparedness. 2010;4(4):312-7. World Health Organization, Weekly Regional Cholera Bulletin: 26 February 2024 Additional Declarations No competing interests reported. Supplementary Files ANNEX.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 13 Jan, 2026 Reviewers invited by journal 13 Jan, 2026 Editor assigned by journal 12 Jan, 2026 Editor invited by journal 22 Dec, 2025 Submission checks completed at journal 21 Dec, 2025 First submitted to journal 21 Dec, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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08:43:53","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":337659,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 3: Spot map of cholera cases by kebeles in Bati district and Bati town, Oromo zone, Amhara region,\u003c/p\u003e\n\u003cp\u003eEthiopia, May 2024\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8307931/v1/0bb8cb37d2de14bcd9295d7b.png"},{"id":100560918,"identity":"e72baffc-9b69-4637-867e-bdd47927e39e","added_by":"auto","created_at":"2026-01-19 08:43:53","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":239302,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 4: Distribution of cholera cases by date of onset at Bati district and Bati Town, Oromo Special Zone, Amhara, Ethiopia, 2024.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8307931/v1/4e704686534658be583a6eee.png"},{"id":100804009,"identity":"ab24293f-d2d3-483d-b01b-56fcc0d0761e","added_by":"auto","created_at":"2026-01-21 14:34:34","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1950644,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8307931/v1/7769869d-79c0-4b62-8261-3b3f3cb9e2bb.pdf"},{"id":100561176,"identity":"901da16e-658d-4c41-b339-be0190bcbca7","added_by":"auto","created_at":"2026-01-19 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It mainly affects people living in places where clean water and sanitation are limited, and it affects the poorest communities the hardest. Without quick treatment, cholera can make people dangerously dehydrated and even lead to death, especially in areas where healthcare is hard to access. Even though there are vaccines to help prevent cholera, many people are still at risk, and new forms of the bacteria that resist antibiotics are making it harder to control (1, 2). This makes it crucial to find new ways to protect people and stop the spread of the disease.\u003c/p\u003e\n\u003cp\u003eCholera outbreaks often happen where people live in crowded conditions, face poverty, or don\u0026rsquo;t have reliable access to clean water and toilets. Since 1817, there have been seven major worldwide cholera outbreaks, and the disease still affects many poor communities today. The real number of people who get sick or die from cholera is probably much higher than what\u0026rsquo;s reported, because many cases go uncounted, and some areas don\u0026rsquo;t have the resources to test for the disease. Every year, cholera is believed to make between 1.3 and 4 million people sick, and it causes anywhere from 21,000 to 143,000 deaths. Tragically, about half of those who die are children under five. Cholera remains a serious and ongoing threat to public health in many parts of the world (3).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePrevention and control of cholera involve a combination of measures, including improving access to safe water and sanitation, promoting good hygiene practices, and providing vaccination in high-risk areas. The following are some of the strategies that have been used to prevent and control cholera: Provision of safe water and sanitation facilities. Access to safe water and sanitation facilities is essential in preventing cholera. This can be achieved through the provision of clean water sources, such as wells and boreholes, and the construction of latrines and handwashing stations.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Promotion of good hygiene practices: good hygiene practices, such as handwashing with soap and water, can help prevent the spread of cholera. Health education campaigns can be used to promote these practices. Vaccination: Vaccination is an effective way to prevent cholera in high-risk areas. Oral cholera vaccines are available and are effective in reducing the incidence of cholera. Early detection and treatment: Early detection and treatment of cholera cases can help prevent the spread of the disease. Treatment involves rehydration with oral rehydration solution or intravenous fluids and the use of antibiotics in severe cases. Surveillance and outbreak response: Surveillance systems can help detect cholera outbreaks early, allowing for a rapid response to prevent further spread of the disease.\u003c/p\u003e\n\u003cp\u003eIn summary, prevention and control of cholera require a combination of measures, including improving access to safe water and sanitation, promoting good hygiene practices, providing vaccination in high-risk areas, early detection and treatment, and surveillance and outbreak response (4, 5).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe global burden of cholera is largely unknown because the majority of cases are not reported. The low reporting can be attributed to the limited capacity of epidemiological surveillance and laboratories, as well as social, political, and economic disincentives for reporting. We previously estimated 2.8 million cases and 91,000 deaths annually due to cholera in 51endemic countries. A major limitation in our previous estimate was that the endemic and non-endemic countries were defined based on the countries\u0026rsquo; reported cholera cases. We overcame the limitation with the use of a spatial modeling technique in defining endemic countries and accordingly updated the estimates of the global burden of cholera(6). This research aims to assess the situation of the outbreak, determine the cause and source, describe cases epidemiologically, and apply intervention measures to overcome the current outbreak and prevent similar events in the future. \u0026nbsp;\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy Setting\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBati Town and Bati district are found in the Oromo Special Zone, Amhara region. Bati Woreda is one of the second largest districts in the Oromo Special Zone, which is administered by a total of 26 kebeles, and Bati town consists (4 urban and 2 rural). Both have a total population of 143,015 population of which females constituted 70,793 (49.5%) from the 2007 census estimate. These two districts have one primary hospital, 8 HC, and 28 health posts, which are currently in service. The physical health service coverage of the two districts was 100%.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy Design and Period\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAn unmatched community-based case-control study was conducted between April 10 -30/2024 with a ratio of 1:1 case to controls.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSource Population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study populations were all community members living in cholera-affected kebeles of Bati district and Bati town.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Study Population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study population consisted of all cholera cases that met the standard case definition, as well as selected control individuals who were at risk of cholera exposure but did not develop any signs or symptoms of the disease in Bati Town and Bati District between April 4 and April 30, 2024. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEligibility criteria\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eInclusion Criteria\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCases:\u003c/strong\u003e All individuals who were positive for cholera and epidemiologically linked to cholera cases in the outbreak period, and those who agreed to participate in the study were included. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eControls\u003c/strong\u003e: Any resident of Bati District and Bati Town who lives with a cholera case, either as a household member or neighbor, and who does not exhibit signs or symptoms of cholera and agrees to participate, was included.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eExclusion criteria \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCases:\u003c/strong\u003e Individuals not residing in the study area during and three weeks before the period of an outbreak were excluded.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eControls:\u003c/strong\u003e Individuals who were not residing in the study area, such as temporary visitors and those who refused to participate, were excluded.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData source\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMedical records of cases (patient charts) at Bati Health Center, Bati Rural CTCs, and cholera patient line lists were reviewed as secondary data. A face-to-face interview, using a structured questionnaire, was conducted to obtain data from adult cases and controls. Data from children was obtained by interviewing caregivers. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample Size Determination\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe sample size was computed using Epi Info version 7.2 statistical software, considering the following assumptions: 95% CI, power 85%, 1:1 ratio of controls to cases. The sample size was 117 cases and 117 controls. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSampling process\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe conducted an unmatched case-control study to identify determinants of the cholera outbreak in 15 kebeles of Bati Woreda and 6 kebeles of Bati Town. A total of 117 confirmed and epidemiologically linked cases were recruited from the official line list. Controls were randomly selected from the same source population among individuals who had not developed cholera.\u003c/p\u003e\n\u003cp\u003eFor each case, a control was chosen using a lottery method. Whenever possible, neighbors were selected to ensure similar environmental exposures. If multiple eligible neighbors were available, one was randomly drawn. If no suitable neighbors were found, a non-affected family member was randomly selected. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTrained field data collectors facilitated the selection process and obtained informed consent. The random selection minimized selection bias and improved comparability by ensuring both cases and controls were exposed to similar community conditions.\u003c/p\u003e\n\u003cp id=\"_Toc192117613\"\u003e\u003cstrong\u003eStudy Variables\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Dependent variable\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Cholera Case\u003c/strong\u003e (Yes, No)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp;Independent variable\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Socio-demographic\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;factors:\u003c/strong\u003e Such as Age, sex, educational level of the participant, occupational status of the participant, marital status, and family size.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Clinical\u0026nbsp;Factors:\u0026nbsp;\u003c/strong\u003eSuch as signs of diarrhea, vomiting, back pain, joint pain, date of onset of illness, date of seen health facility, contact history, treatment taken, travel history, awareness on prevention and control of cholera, and mode of transmission.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExposure Information:\u0026nbsp;\u003c/strong\u003eExposure to raw food (Yes/No); Eating outside the home (Yes/No); Attendance at gatherings (Yes/No); Travel history outside the village (Yes/No)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSanitation and Hygiene Practices:\u0026nbsp;\u003c/strong\u003eHandwashing practices (Yes/No)\u003cstrong\u003e;\u0026nbsp;\u003c/strong\u003eFrequency of handwashing before meals (Sometimes/Always)\u003cstrong\u003e;\u0026nbsp;\u003c/strong\u003eSoap use for handwashing (Yes/No)\u003cstrong\u003e;\u0026nbsp;\u003c/strong\u003eLatrine availability (Yes/No)\u003cstrong\u003e;\u0026nbsp;\u003c/strong\u003eLatrine utilization (Used by all, some, or not used)\u003cstrong\u003e;\u0026nbsp;\u003c/strong\u003eHandwashing facility near the toilet (Yes/No)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWater-Related Practices:\u0026nbsp;\u003c/strong\u003eWater source (Pipe/Spring/River/Hand Dug)\u003cstrong\u003e;\u0026nbsp;\u003c/strong\u003eWater purification method (Yes/No, and method details)\u003cstrong\u003e;\u0026nbsp;\u003c/strong\u003eTreated water usage in the past week (Yes/No)\u003cstrong\u003e;\u0026nbsp;\u003c/strong\u003eWater storage container type (Jerry can/Bucket)\u003cstrong\u003e;\u0026nbsp;\u003c/strong\u003eWater fetching method (Deeping/Incling with cup/Always inside)\u003cstrong\u003e;\u0026nbsp;\u003c/strong\u003eWater storage cleaning frequency (Every day/Every other day/Every week/Other)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Exposure:\u003c/strong\u003e Family members with similar symptoms (Yes/No)\u003cstrong\u003e;\u0026nbsp;\u003c/strong\u003eNumber of family members sick (Numerical)\u003cstrong\u003e;\u0026nbsp;\u003c/strong\u003eContact with patients with similar symptoms (Yes/No)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAwareness:\u0026nbsp;\u003c/strong\u003eAwareness of transmission of AWD/cholera (Yes/No)\u003cstrong\u003e;\u0026nbsp;\u003c/strong\u003eAwareness of prevention methods (Yes/No)\u003c/p\u003e\n\u003cp id=\"_Toc192117614\"\u003e\u003cstrong\u003eCase definitions\u003c/strong\u003e\u003c/p\u003e\n\u003cp id=\"_Toc167595321\"\u003e\u003cstrong\u003eCommunity case definition\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSuspected cholera case\u003c/strong\u003e: If any person 2 years or older with profuse acute watery diarrhea and vomiting.\u003c/p\u003e\n\u003cp id=\"_Toc167595322\"\u003e\u003cstrong\u003e\u0026nbsp;Standard case definition\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Suspected case:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;In areas where a cholera outbreak has not been declared,\u003c/strong\u003e any person aged 2 years or more presenting with acute watery diarrhea and severe dehydration or dying from acute watery diarrhea.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;In areas where a cholera outbreak has been declared,\u003c/strong\u003e any person aged 2 years or more presenting with or dying from acute watery diarrhea.\u003c/p\u003e\n\u003cp id=\"_Toc167595324\"\u003e\u003cstrong\u003e\u0026nbsp;Confirmed case:\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp;A suspected case in which Vibrio cholera O1 or O139 has been isolated from their stool\u003cstrong\u003e. Epidemiologically linked cases\u003c/strong\u003e: A case in which the patient has had contact with one or more individuals who have the disease, and where transmission of the agent through the usual modes of transmission is plausible.\u003c/p\u003e\n\u003cp\u003eA case may be considered epidemiologically linked to a laboratory-confirmed case if at least one case in the chain of transmission is laboratory-confirmed(14).\u0026nbsp;\u003c/p\u003e\n\u003cp id=\"_Toc167595325\"\u003e\u003cstrong\u003eOperational definition\u003c/strong\u003e\u003cstrong\u003es\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCholera contact:\u0026nbsp;\u003c/strong\u003e exposure to the bacterium Vibrio cholera, which can occur through various means such as consuming contaminated food or water, or being near an infected individual(15)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCholera outbreak:\u0026nbsp;\u003c/strong\u003ea cholera outbreak involves the detection of confirmed cholera cases in a specific area.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eIncubation period:\u0026nbsp;\u003c/strong\u003eThe incubation period is usually 1 to 3 days, but can range from several hours to 5 days. Symptoms usually last 2 to 3 days, although in some patients they can continue up to 5 days.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInfectious period:\u0026nbsp;\u003c/strong\u003eInfected persons, whether they are symptomatic or not, can carry and transmit Vibrio for 1 to 4 weeks; a small number of individuals can remain healthy carriers for several months\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eControl:\u0026nbsp;\u003c/strong\u003eAny resident of Bati Town and Bati district during the study period who was living together with a case at home or a neighbor who did not develop signs and symptoms of cholera.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExposure Information:\u003c/strong\u003e Refers to data or details about factors that might have made individuals or populations vulnerable to contracting cholera.\u0026nbsp;\u003c/p\u003e\n\u003cp id=\"_Toc192117616\"\u003e\u003cstrong\u003eData collection method\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData was collected by trained health professionals through face-to-face interviews with cases and controls using structured and semi-structured questionnaires developed for this study. Additional data were gathered from the cholera line list. The WHO case definition was used to classify study participants as either cases or controls.\u0026nbsp;\u003c/p\u003e\n\u003cp id=\"_Toc192117617\"\u003e\u003cstrong\u003eData Processing and Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe\u0026nbsp;data were coded, entered, and cleaned into EPI Data version 4.6.6 and then exported to SPSS version 27 for analysis. The result was presented by words, tables, and figures. An epidemic curve was constructed to examine the development of epidemics over time.\u003c/p\u003e\n\u003cp\u003eWe executed the enter method for simple and multivariable binary logistic regression to determine the independent factors associated with the development of Cholera. A variable with a p-value less than or equal to 0.25 in the bivariable analysis was considered to be a candidate variable for multivariable logistic regression to identify the independent predictors of Cholera. And then variables that are significant with a P- P-value of less than or equal to 0.05 at a 95% confidence interval in multivariable binary logistic regression were considered statistically significant. Both 95% CI and P-values were used to assess the associations between dependent and independent variables. In all cases, odds ratios were used to assess the strength of the association. The model goodness of fit was checked by the Hosmer and Lemeshow Test.\u003c/p\u003e\n\u003cp id=\"_Toc192117618\"\u003e\u003cstrong\u003eData Quality Control\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBefore data collection, a half-day training was given for health workers who were assigned at Bati and Fura CTCs. Each question was asked clearly for cases and controls in a similar manner during the interview. Data was also cleaned for any missing and logically inconsistent values before analysis by running the frequency and cross-tabulation of each variable with the outcome variable.\u003c/p\u003e\n\u003cp id=\"_Toc192117619\"\u003e\u003cstrong\u003eEthical consideration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA permission letter was written from the Oromo Special Zone Health Department to Bati Town and the Bati district health office. For those study participants aged 18 and above, written consent forms were taken and for children\u0026rsquo;s parents or caretakers took consent forms to take part in the study. Participants\u0026apos; right to withdraw from the study as they wish was also clearly stated before the interview started. The responses were confidential and analysis were as groups not for individual case or control.\u003c/p\u003e\n\u003cp id=\"_Toc167595329\"\u003e\u003cstrong\u003eDissemination of\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ethe\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003efindings\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe result of the study will be shared with the Bati district and Bati town health offices, Oromo Special Zone health department, and Amhara Public Health Institute. The findings will be presented at district and zonal level review meetings, and also it could also be prepared for publication.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eDescriptive Analysis\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003cem\u003e\u0026nbsp;\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study included a total of 234 study participants, 117 cholera cases, and 117 controls. Among the total cholera cases, 14 tested positive by rapid diagnostic test (RDT), and 11 of these were confirmed by culture. The remaining cases were classified based on the standard case definition and epidemiological linkage.\u003c/p\u003e\n\u003cp\u003eAll cases were admitted to a Cholera Treatment Center (CTC) or an Oral Rehydration Point (ORP). A total of five cholera-related deaths were recorded, with four occurring at healthcare facilities and one in the community before admission to the CTC.\u0026nbsp;\u003c/p\u003e\n\u003cp id=\"_Toc192117623\"\u003e\u003cstrong\u003eSociodemographic Characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 264c individuals, 117 cases, and 117 controls were interviewed. The response rate of this study was 100%. Out of the 234 study participants, 119 (50.9%) were females, and the rest were males. Family size of the study participants: 129(55%) had less than five families per household, and the rest 105(45%) of the participants had greater than 5 families per household. The majority of study Participants, 194 (82.9%), were aged greater than 15 years. Among all 234 participants, 27 (29.3%) were unable to read or write, followed by 21 (22.8%) who could read and write. Nearly half of the participants, 116 (49.5%), were farmers (Table 1).\u003c/p\u003e\n\u003cp id=\"_Toc192113528\"\u003eTable\u0026nbsp;1: Socio-demographic characteristics of Cholera cases and controls in Bati district and Bati town, Oromo zone, Amhara region, 2024\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"675\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" style=\"width: 274px;\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 149px;\"\u003e\n \u003cp\u003eCases(N=117)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 148px;\"\u003e\n \u003cp\u003eControls(N=117)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003eTotal N=134\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003eNumber\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003ePercent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eNumber\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003ePercent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Number (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 105px;\"\u003e\n \u003cp\u003eSex\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e55%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e44%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e115(49.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e45%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e56%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e119(50.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 105px;\"\u003e\n \u003cp\u003eAge\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003eLess than 5 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e13%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e15(6.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e5-14 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e24%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e25(10.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026gt;=15 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e63%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e82%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e192(82.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" style=\"width: 105px;\"\u003e\n \u003cp\u003eOccupation\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003eStudent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e11%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e14(6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003eFarmer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e44%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e55%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e116(49.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003eMerchant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e9(3.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003eTeacher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e2(1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003eHousewife\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e12%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e38%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e59(25.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e29%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e34(14.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" style=\"width: 105px;\"\u003e\n \u003cp\u003eEducational status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003eNot read and write\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e54%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e79%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e155(66.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003eRead and write\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e11%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e18(7.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003ePrimary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e15%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e12%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e32(13.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003eSecondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e12(5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003eCollege and above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e2(1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003eNA\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e13%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e15(6.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 105px;\"\u003e\n \u003cp\u003eNumber of family members\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026lt;=5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e35%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e55%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e105(45%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026gt;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e65%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e45%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e129(55%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" style=\"width: 105px;\"\u003e\n \u003cp\u003eMarital status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e45%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e70%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e149(63.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e15%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e24(10.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003eDivorced\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e7(3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003eWidowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e13(5.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e35%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e17%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e41(17.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp id=\"_Toc166620440\"\u003e\u003cstrong\u003eClinical Presentation of\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eCases\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong all suspected cases, 116 (99%) had both diarrhea and vomiting, 99 (89%) had vomiting, and 19 cases (12.6%) had back pain, 17 cases (14.5%) had arthralgia, and 17 cases (14.5%) had muscle pain (myalgia).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRegarding dehydration status among suspected cholera cases, 22 patients (18.8%) had no dehydration, 42 (35.9%) had some dehydration, and 53 (45.3%) suffered from severe dehydration (Figure 2).\u003c/p\u003e\n\u003cp\u003eOf the total cholera cases, 105 (89.7%) received treatment after being admitted to a Cholera Treatment Center (CTC) or as inpatients. All patients diagnosed with severe dehydration received antibiotics and IV fluids, while the remaining cases were treated with oral rehydration solution (ORS). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDistribution of Cholera cases by place\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis cholera outbreak has affected two districts within the Oromo Special Zone administration. As shown in Table 2 below, the highest number of cases was reported from Bati district, with 230 cases (78.2%) from 15 kebeles (57.7%) and 64 cases (21.8%) from 6 kebeles in Bati town (Table 2). Among the total cholera cases, five individuals died from four kebeles, resulting in a case fatality rate (CFR) of 1.7%. The overall Attack Rate (AR) was 32 per 10,000 people. A total of 302 people were affected between April 6 and May 17, 2024. Additionally, six cases were reported from the Dewe Harewa district, and two cases from the Afar region. Out of the total cases in Bati district, 19 were treated at the Bati town Cholera Treatment Center (CTC)(Figure 3). \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDistribution of cholera cases by Person\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOver 96,000 people were at risk for a cholera outbreak in Bati Town and Bati District, which has resulted in 294 cases and 5 fatalities (1.7% CFR). Bati district was more affected, as evidenced by 78.23% of cholera cases being reported from the district. \u0026nbsp;Most cholera-affected kebeles were Chekorti (80 cases) and Cheleleka (52 cases). The greatest fatality rate was 10.5% for Teamelka.\u0026nbsp;\u003c/p\u003e\n\u003cp id=\"_Toc192113529\"\u003eTable\u0026nbsp;2.Distribution of Cholera Cases, Population at Risk, Attack Rate (AR), and Case Fatality Rate (CFR) in Bati District and Bati Town, Oromo Zone, Amhara Region, 2024.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"683\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eName of affected District\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026nbsp;Kebele\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eRisk population\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003eNumber of Cholera cases\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003eAttack rate per 10,0000\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003eNumber of deaths\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003eCase fatality rate (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003eRemark\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"7\" style=\"width: 77px;\"\u003e\n \u003cp\u003eBati Town\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eBati 01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e6826\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eBati 02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e7471\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eBati 03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e7684\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e3.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eBati 04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e6315\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eKame\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e4391\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eSalmene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e9278\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eBati Town\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e41965\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e3.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"16\" style=\"width: 77px;\"\u003e\n \u003cp\u003eBati District\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eBira\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e5,942\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eBofa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e3,562\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eBurka\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e1,847\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eChekorti\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e3,254\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e246\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eCheleleka\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e2,376\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e219\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eDamto\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e3,966\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eFura\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e4,080\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eGerfa Urene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e4,281\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eGure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e3,025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eHato\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e3,146\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eKebele\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e3,697\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eKurkura\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e3,914\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eMelka Lugo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e4,993\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eTeamelka\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e3,776\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e10.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eUungu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e4,109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eBati District\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e54,124\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e230\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e96,089\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e294\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp id=\"_Toc192117627\"\u003e\u003cstrong\u003eDistribution of Cholera Cases by Time\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong all 117 cholera cases that were included in the study, 64 cases (54.7%) were male, and 53 cases (45.3%) were female. \u0026nbsp; The age of the study participants, cholera patients, ranged from 1 to 90 years. In the two study areas, the overall case fatality rate (CFR) was 1.7%, with an Attack Rate (AR) of 32 per 10,000 population. Age-specific case distributions were as follows: 15 cases (8.5%) were in children under five years old, 25 cases (21.4%) were in the 5- 14-year age group, and 77 cases (65.8%) were in individuals aged 15 years and older.\u003c/p\u003e\n\u003cp\u003eAfter receiving reports from Genda Habure Gotte, on April 2, 2024, Hato Health Center admitted the first four cases of food poisoning. The identification of these four cases as the index cases was verified by the detection of 15 additional suspected cholera cases from the same outbreak, after four days. \u0026nbsp;These 15 cases were reported on April 6, 2024. The highest number of cholera cases was reported on April 20, 2024, with 32 cases. The last date of the outbreak was on May 15, 2024, when 15 cholera cases were reported (Figure 4).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRisk factors for cholera outbreak\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eThe presence of several predictive factors for a cholera outbreak posed significant challenges in containing and controlling it within a short period before it spread to other kebeles. Less than one-quarter of respondents had access to a latrine, and two-thirds were unaware of cholera prevention methods. The risk factor distribution among cholera cases and controls is presented in Table 3.\u0026nbsp;\u003c/p\u003e\n\u003cp id=\"_Toc192113530\"\u003eTable 3: Risk factors distribution among cholera cases and controls in Bati district and Bati town, \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Oromo zone, Amhara region, Ethiopia, May 2024\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"693\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 235px;\"\u003e\n \u003cp\u003eRisk factors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 84px;\"\u003e\n \u003cp\u003eCategory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 126px;\"\u003e\n \u003cp\u003eCases(n=117)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 126px;\"\u003e\n \u003cp\u003eControls(n=117)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 122px;\"\u003e\n \u003cp\u003eTotal(N=234)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003eNumber\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eNumber\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eNumber\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 235px;\"\u003e\n \u003cp\u003eEat anything outside the home in the past 5 days\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e15%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e85%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e116\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e99%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e92%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 235px;\"\u003e\n \u003cp\u003eAttending gatherings\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e58%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e31%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e42%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e112\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e96%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e161\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e69%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 235px;\"\u003e\n \u003cp\u003eHistory of travel outside of the village 5 days before the onset of illness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e111\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e95%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e97%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e225\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e96%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 235px;\"\u003e\n \u003cp\u003eHand washing before a meal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e56%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e85%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e165\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e71%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e44%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e15%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e29%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 235px;\"\u003e\n \u003cp\u003eUse of soap for hand washing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e17%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e34%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e26%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e83%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e66%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e174\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e74%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 235px;\"\u003e\n \u003cp\u003eLatrine Ownership\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e20%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e21%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e21%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e80%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e79%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e186\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e79%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 235px;\"\u003e\n \u003cp\u003eHand washing practice after using the toilet (defecating)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e18%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e12%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e93%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e82%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e205\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e88%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 235px;\"\u003e\n \u003cp\u003eThe water source for drinking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003ePipe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e15%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e12%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eSpring\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eRiver\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e44%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e23%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e33%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eHand Dug\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e41%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e56%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e48%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 235px;\"\u003e\n \u003cp\u003eThe presence of a family member with the same illness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e44%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e27%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e56%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e91%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e171\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e73%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 235px;\"\u003e\n \u003cp\u003eHistory of patients having the same signs and symptoms\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e37%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e24%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e63%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e105\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e90%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e179\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e76%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 235px;\"\u003e\n \u003cp\u003eKnow the mode of transmission of AWD/cholera\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e32%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e37%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e34%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e68%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e63%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e66%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 235px;\"\u003e\n \u003cp\u003eknow the methods of prevention of AWD/cholera\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e32%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e39%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e35%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e68%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e61%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e151\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e65%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp id=\"_Toc192117629\"\u003e\u003cstrong\u003eFactors associated with a cholera outbreak in Bati town and Bati woreda\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSimple and multivariable binary logistic regression analyses were used to calculate odds ratios and 95% confidence intervals for the predictors of the Cholera outbreak. In the first step, bivariable analysis was used to select candidate variables for multivariable analysis at a P-value less than 0.25. The candidate variables analyzed in multivariable analysis with a P-value less than 0.05 were considered significant. The final model was used to analyze variables related to sociodemographic factors, cholera exposure factors, Sanitation and Hygiene practices, Water utilization practices, Clinical exposure, and factors related to the knowledge of the study participants. In the final multivariable logistic regression analysis model, the following variables were associated using the enter method.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe odds of developing cholera were more than twice as high in males compared to females (AOR = 2.3, 95% CI: 1.1\u0026ndash;5.1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe likelihood of being infected with cholera was 42 times higher among individuals who attended gatherings compared to those who did not (e.g., those who did not attend gatherings like Sodeka) (AOR = 42.24, 95% CI: 13.615\u0026ndash;55.1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eStudy participants who did not wash their hands before meals were four times more likely to contract cholera compared to those who practiced handwashing (AOR = 4.2, 95% CI: 1.6\u0026ndash;10.6).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe odds of contracting cholera were four times higher among study participants who did not wash their hands with soap compared to those who used soap for handwashing (AOR = 4.2, 95% CI: 1.6\u0026ndash;10.6).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eParticipants with a family member who was ill with cholera were twelve times more likely to contract cholera than those without a sick family member (AOR = 12, 95% CI: 4.7\u0026ndash;30.9).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe likelihood of becoming infected with cholera was three times higher among individuals who drank from unprotected water sources compared to those who drank from protected water sources (AOR = 2.9, 95% CI: 1.3\u0026ndash;6.4) (Table 4).\u0026nbsp;\u003c/p\u003e\n\u003cp id=\"_Toc192113531\"\u003eTable 4: Bivariate and multivariable logistic regression analysis of factors associated with cholera outbreaks, \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Bati District and Bati town, Oromo special zone, Amhara region, Ethiopia,2024.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"698\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eCategories\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003eDisease status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eCOR (95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eAOR (95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eCase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eControls\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e64(54.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e51(43.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e1.56(0.93,2.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e2.32(1.06,5.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.036*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003eFemales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e53(45.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e66(56.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eFamily Size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026lt;=5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e40(35%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e64(54.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.089\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026gt;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e76(65%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e53(45.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e2.29(1.35,3.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e0.5(0.229,1.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eAttending Gathering\u003c/p\u003e\n \u003cp\u003e(Sodeka)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e68(58%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e5(4.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e31.09(11.81,81.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e42.24(13.62,55.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.0001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e49(42%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e112(95.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eHand washing before meals\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e65(55.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e100(85.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.003*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e52(44.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e17(14.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e4.71(2.51,8.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e4.16(1.64,10.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eHand washing with soaps\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e20(17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e40(34.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.044*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e97(83%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e77(65.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e2.52(1.36-4.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e4.16(1.64,10.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eHand washing after toilet\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e8(6.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e21(18%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e109(93.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e96(82%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e2.98(1.262,7.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e2.55(0.50,12.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003ePresence of an ill family member\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e52(44.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e11(9.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.0001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e65(55.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e106(90.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e7.71(3.752,15.838)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e12.04(4.69,30.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eWater sources\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003eProtected\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e59(50.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e82(70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0,009*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003eUn protected\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e58(49.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e35(30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e2.30(1.47,3.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e2.88(1.30,6.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eContact history\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e43(36.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e12(10.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.725\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e74(63.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e105(89.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e5.08(2.511,10.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e0.7(0.096,5.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eKnow prevention mechanisms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e37(31.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e46(39.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.469\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e80(68.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e71(60.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e1.40(0.818,2.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e0.72(0.291,1.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study revealed that the overall attack rate (AR) was found to be 31 per 10,000 population. This is lower than studies conducted in Uganda (32/10,0000)(\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e8\u003c/span\u003e), Western Kenya (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e9\u003c/span\u003e), Mile district of Afar region, (83/10,000) (\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e16\u003c/span\u003e)and west Arsi, Oromia region, Ethiopia (230/10,000)(\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e17\u003c/span\u003e), But it is higher than a study done in Kirkos sub city, Addis Ababa, Ethiopia (14.3/10,000)(\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e13\u003c/span\u003e). This variation might be due to source of outbreak, early detection or surveillance system and response activities. The case fatality rate (CFR) was 1.7% which is lower than the WHO African region February 2024 report (1.9%)(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e), Uganda (2.1%)(\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e8\u003c/span\u003e), Mile district (7.8%)(\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e16\u003c/span\u003e), and Werst Arsi (2.3%)(\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e17\u003c/span\u003e). However, it is higher than a study conducted in Kirkos sub-city of Addis Ababa, Ethiopia, showed that there were no deaths reported due to a cholera outbreak. Possible explanations for this difference could be the strength of surveillance activity, the quality of case management, and the availability of supplies and drugs.\u003c/p\u003e \u003cp\u003eIn this study, males were more attacked by cholera disease than females. This was supported by a study conducted in Kirkos Sub City, Addis Ababa(\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e13\u003c/span\u003e). This might be justified by the fact that males most of the time, work, eat food, and drink water outside their home, which may expose them to cholera infection. Those who attended any gathering were 42 times more likely to be infected with cholera than those who didn\u0026rsquo;t participate in gatherings. A possible explanation for this might be that any gathering increases the transmission of cholera because there will be a high probability of eating food and drinking water contaminated by Vibrio cholera.\u003c/p\u003e \u003cp\u003e In the current investigation, study participants who didn\u0026rsquo;t use soap to wash their hands were four times become ill with cholera than their counterparts. This is in line with studies done in Addis Ababa, Ethiopia(\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e13\u003c/span\u003e) and Yemen(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). This could be due lack of water, a lack of toilets, an increase in soap prices, or a lack of awareness.\u003c/p\u003e \u003cp\u003eThis study found that using water from unprotected sources, such as rivers and spring water, was a significant predictor of the cholera outbreak. This aligns with findings from studies conducted in Yemen, Uganda (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e8\u003c/span\u003e), Benishangul Gumuz (\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e12\u003c/span\u003e), and the Mile district of the Afar region (\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e16\u003c/span\u003e). The higher risk associated with these sources may be due to their increased susceptibility to contamination compared to protected water sources, such as piped water and hand-dug wells.\u003c/p\u003e \u003cp\u003eThese findings support the hypothesis proposed by healthcare workers, who identified unprotected river water as the source of the outbreak. This hypothesis was formed after observing that most cholera cases were among individuals who used river water for drinking and washing, due to limited access to safe water in the area. Furthermore, the geographic distribution of cholera cases closely followed the river basins. Collectively, this evidence suggests that the primary source of the outbreak in the study area was the consumption of river water.\u003c/p\u003e \u003cp\u003eThe findings of this study indicate that the likelihood of contracting cholera was 42 times higher among individuals who attended gatherings compared to those who did not, such as those who avoided gatherings like Sodeka (AOR\u0026thinsp;=\u0026thinsp;42.24, 95% CI: 13.615\u0026ndash;55.1). This significant association suggests that social gatherings played a critical role in the transmission of cholera, likely due to close contact and the shared consumption of contaminated food or water.\u003c/p\u003e \u003cp\u003eThese findings align with previous studies that have shown an increased risk of cholera transmission in crowded settings or during large gatherings. For instance, a study conducted in Yemen during a cholera outbreak found that attendees of public gatherings, including religious festivals and weddings, were at a higher risk of infection due to the lack of sanitation and safe drinking water [,35]. Similarly, in a study in Bangladesh, it was observed that cholera outbreaks were frequently linked to mass gatherings, where limited access to safe water and poor hygiene practices contributed to the rapid spread of the disease [36].\u003c/p\u003e \u003cp\u003eThe high risk associated with attending gatherings in this study could be attributed to several factors, including the sharing of food and drink in unsanitary conditions, overcrowding, and inadequate access to hygiene facilities. These factors likely facilitated the transmission of Vibrio cholerae, the bacteria responsible for cholera, among attendees. Furthermore, these results highlight the importance of public health interventions focused on improving hygiene practices and water and sanitation at mass gatherings to prevent future outbreaks.\u003c/p\u003e \u003cp\u003eThis finding supports the second hypothesis proposed by healthcare workers, which suggests that the outbreak was waterborne and resulted from the consumption of unsafe water and food during a social gathering event, locally known as 'Sodeka.' The food served at this gathering was prepared with water fetched from a contaminated river on April 1, 2024, in Genda Habure Gotte of Fura Kebele, Bati District. Approximately 150 people from neighboring kebeles and districts attended the Sodeka program, and most of them contracted the disease.\u003c/p\u003e \u003cp\u003eIn this study, participants with a family member affected by cholera were twelve times more likely to contract the disease than those without a sick family member. This finding is consistent with studies conducted in the Afar (\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e16\u003c/span\u003e) and Oromia (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e17\u003c/span\u003e) regions of Ethiopia. This increased risk may be attributed to low awareness among family members regarding the modes of transmission and prevention methods for cholera.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe cholera outbreak was primarily caused by drinking contaminated water from unprotected sources, participating in social gatherings, and practicing poor hygiene, such as not washing hands with soap. The findings support the hypothesis that river water poisoning played a significant role in the outbreak due to the fact that a significant number of the illnesses were caused by drinking water consumed during a crowd.\u003c/p\u003e \u003cp\u003eTherefore, in order to prevent and early containment of future cholera outbreaks early, various governmental and non-governmental organizations, such as government health sectors, water and sanitation sectors, municipalities, district administrative bodies, local community administrations, and the affected community, have to work in collaboration. Increasing access to safe drinking water sources, improving community awareness on good hygiene and sanitation practices, and promoting healthy social gatherings might minimize the risk for cholera spread and hence prevent the occurrence of similar outbreaks in the future.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical Approval and Consent to Participate:\u0026nbsp;\u003c/strong\u003e Ethical approval and consent to participate were obtained from the Amhara Public Health Institute, Dessie Branch. Verbal or written informed consent was obtained from all participants data collection, in accordance with ethical guidelines.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u003c/strong\u003e: Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e: This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of Data and Materials\u003c/strong\u003e: The datasets generated and/or analyzed during the current study are not publicly available due to government and institutional restrictions on data sharing related to outbreak surveillance data, but may be made available from the corresponding author upon reasonable request and subject to approval by the relevant authorities.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003e**Tenaw Yibeltal Desalegn** : Conceptualization, study design, data collection, data analysis, manuscript drafting.**Melaku Girma:** Conceptualization, study design, data collection, data analysis, manuscript drafting. **Abtew Abera Abebe:** Data collection, data analysis, manuscript review. **Anteneh Demelash Abate:** Data collection, interpretation, manuscript review. **Melaku Girma Haile:** Supervision, technical support, manuscript review. **Mohamed Ahmed Seid:** Data analysis support, interpretation, and manuscript review. **Seid Mohamed Seid** : Senior supervision, critical manuscript review, and approval.All authors reviewed and approved the final manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgement\u003c/h2\u003e\n\u003cp\u003eI would like to offer my gratitude for the Amhara Public Health Institute, Dessie branch, Oromo Special Zone health department for their support during the study period. I would also like to express my appreciation to the community in Bati Woreda and Bati Town for their cooperation during data collection.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eNaidu A, Lulu SS. Mucosal and systemic immune responses to Vibrio cholerae infection and oral cholera vaccines (OCVs) in humans: a systematic review. Expert Rev Clin Immunol. 2022 Dec;18(12):1307-18. PubMed PMID: 36255170. Epub 2022/10/19. eng.\u003c/li\u003e\n\u003cli\u003ePlatts-Mills JA, Babji S, Bodhidatta L, Gratz J, Haque R, Havt A, et al. Pathogen-specific burdens of community diarrhoea in developing countries: a multisite birth cohort study (MAL-ED). The Lancet Global Health. 2015;3(9):e564-e75.\u003c/li\u003e\n\u003cli\u003eDeen J, Mengel MA, Clemens JD. Epidemiology of cholera. Vaccine. 2020 Feb 29;38 Suppl 1:A31-a40. PubMed PMID: 31395455. Epub 2019/08/10. eng.\u003c/li\u003e\n\u003cli\u003eBartram JK, Howard G, editors. Prevention and control of cholera1994.\u003c/li\u003e\n\u003cli\u003eMel DM. [Modern aspects in the prevention and control of cholera]. Glas Srp Akad Nauka Med. 1981 (33):105-12. PubMed PMID: 6927228. Epub 1981/01/01. \u003c/li\u003e\n\u003cli\u003eAli M, Nelson AR, Lopez AL, Sack DA. Updated global burden of cholera in endemic countries. PLoS Negl Trop Dis. 2015;9(6):e0003832. PubMed PMID: 26043000. Pubmed Central PMCID: PMC4455997. \u003c/li\u003e\n\u003cli\u003eDureab F, Jahn A, Krisam J, Dureab A, Zain O, Al-Awlaqi S, et al. Risk factors associated with the recent cholera outbreak in Yemen: a case-control study. Epidemiology and Health. 2019;41.\u003c/li\u003e\n\u003cli\u003eMonje F, Ario AR, Musewa A, Bainomugisha K, Mirembe BB, Aliddeki DM, et al. A prolonged cholera outbreak caused by drinking contaminated stream water, Kyangwali refugee settlement, Hoima District, Western Uganda: 2018. Infectious Diseases of Poverty. 2020;9:1-10.\u003c/li\u003e\n\u003cli\u003eOyugi EO, Boru W, Obonyo M, Githuku J, Onyango D, Wandeba A, et al. An outbreak of cholera in western Kenya, 2015: a case control study. The Pan African Medical Journal. 2017;28(Suppl 1).\u003c/li\u003e\n\u003cli\u003eMatapo B, Chizema E, Hangombe B, Chishimba K, Mwiinde A, Mwanamwalye I, et al. Successful multi- partner response to a cholera outbreak in Lusaka, Zambia 2016: a case control study. Medical Journal of Zambia. 2016;43(3):116-22.\u003c/li\u003e\n\u003cli\u003eAlemayehu E, Tilahun T, Mebrate E. Determinants of Dehydration Status and Associated Risk Factors of Cholera Outbreak in Oromia Ethiopia. Biomed Stat Inform. 2020;5(3):60.\u003c/li\u003e\n\u003cli\u003eAyalew F, Abebe G. Acute Watery Diarrhea/Cholera outbreak Investigation in Wenbera District, Metekel Zone, Benishangul Gumuz Region, Western Ethiopia September 1-October20/2016. Journal of American Science. 2020;16(8).\u003c/li\u003e\n\u003cli\u003eTadesse T, Zawdie B. Cholera outbreak investigation in four districts of Kirkos sub-city in Addis Ababa, Ethiopia: A case-control study. 2019.\u003c/li\u003e\n\u003cli\u003eCase Definitions A. Case Definitions for Public Health Surveillance. \u003c/li\u003e\n\u003cli\u003eGeorge CM, Hasan K, Monira S, Rahman Z, Saif-Ur-Rahman KM, Rashid MU, et al. A prospective cohort study comparing household contact and water Vibrio cholerae isolates in households of cholera patients in rural Bangladesh. PLoS Negl Trop Dis. 2018 Jul;12(7):e0006641. PubMed PMID: 30052631. Pubmed Central PMCID: PMC6063393. Epub 2018/07/28. eng.\u003c/li\u003e\n\u003cli\u003eAbye T, Mekonen H, Amene K, Bisrat S. Cholera outbreak investigation report in Mille woreda, Afar region, Ethiopia, 2019. 2022.\u003c/li\u003e\n\u003cli\u003eBartels SA, Greenough PG, Tamar M, VanRooyen MJ. Investigation of a cholera outbreak in Ethiopia\u0026apos;s Oromiya region. Disaster medicine and public health preparedness. 2010;4(4):312-7.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization, Weekly Regional Cholera Bulletin: 26 February 2024\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Bati District, Bati Town, Risk factors, case-control study, cholera outbreak","lastPublishedDoi":"10.21203/rs.3.rs-8307931/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8307931/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eCholera continues to pose a threat to public health and is frequently linked to injustice and a lack of social development. The study area has a history of recurrent cholera outbreaks. However, local risk factors remain unidentified, which challenges the targeted prevention and control measures. Therefore, this study identifies the potential risk factors and makes it easier to apply targeted interventions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003eWe conducted a 1:1 unmatched case-control study (117 cases and 117 controls). An interviewer-administered questionnaire was used to collect data. SPSS version 27 was used to calculate frequencies and odds ratios. We performed the enter method for binary logistic regression to determine the independent factors associated with cholera infection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003eInterviews with 234 study participants showed a 1.7% case fatality rate and an overall attack rate of 32 per 10,000. Males had a higher chance of being affected by cholera [AOR = 2.3, 95% CI: 1.1-5.1]. Attending a gathering increased the risk of cholera infection [AOR = 42.2, 95% CI: 13.6-55.1]. Those who didn’t wash their hands before a meal was more likely to contract cholera than those who did [AOR = 4.2, 95% CI: 1.6-10.7]. Similarly, those who did not wash their hands with soap at key periods had an increased chance of contracting cholera [AOR = 4.2, 95% CI: 1.6-10.7]. Consumption of water from an unprotected source increased the risk of cholera infection (AOR = 2.9, 95% CI: 1.3-6.4).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003eIn this study, the primary risk factors for the cholera outbreak were participating in social gatherings, using water from unprotected sources, and poor hygiene practices. Therefore, increasing access to safe drinking water sources, improving community awareness on good hygiene and sanitation practices, and promoting healthy social gatherings are priority interventions in the study area.\u003c/p\u003e","manuscriptTitle":"Determinants of Cholera Outbreak in Bati District and Bati Town, Oromo Special Zone, Amhara Region, Ethiopia (2024): An Unmatched Case-Control Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-19 08:28:51","doi":"10.21203/rs.3.rs-8307931/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"16142634373036127492298321433645727723","date":"2026-01-13T13:01:02+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-13T12:51:19+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-13T03:54:30+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-12-22T12:29:44+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-21T13:41:58+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2025-12-21T13:32:57+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"45c9da9c-c2c3-4615-a8c2-b9c4b32dd3b5","owner":[],"postedDate":"January 19th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-01-19T08:28:52+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-19 08:28:51","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8307931","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8307931","identity":"rs-8307931","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}