Disaster Risk Management Practices among Households in Selected Kebeles of South Gondar Administrative Zone

Disaster Risk Management Practices among Households in Selected Kebeles of South Gondar Administrative Zone | 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 Disaster Risk Management Practices among Households in Selected Kebeles of South Gondar Administrative Zone Temesgen Alemu Tilahun, Abraham Mebrat Asemare, Tesfahun Asmamaw Kassie This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6233979/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Although disaster risk management has evolved as an interdisciplinary field and a community driven practice, disasters in Ethiopia have continued to grow in both scale and impact. One of the major challenges in addressing this issue is the lack of scientific knowledge about local disaster management practices and a limited understanding of the underlying factors. This mixed study assesses the disaster management practices of 635 households in locations affected by different hazards in South Gondar zone. The results showed that 66% of households exhibit very low levels of disaster management preparedness. Alarmingly, only 20% of households are engaged in disaster preparedness, while 35% are involved in prevention activities, and 39% in mitigation efforts. Statistical analysis revealed significant differences in disaster management practices based on location (kebeles, p = 0.001; woreda, p = 0.001) and economic status (p = 0.04). Younger, more educated, and higher-income households were found to be less involved in risk management activities. To improve disaster management practices, there needs to be a stronger emphasis on community ownership and active participation throughout all key phases. In particular, more efforts are required to promote disaster preparedness among households. Disaster Risk Management Disaster Preparedness Disaster Prevention Risk Mitigation Figures Figure 1 1. Introduction Disasters have significantly impacted Africa, including Ethiopia, for a long time. In Ethiopia, the 2021/22 drought affected over 2 million people, while inter-communal conflicts displaced 2 million and impacted over 5 million (Sheganew et al., 2022). The Amhara region, particularly South Gondar Zone and districts like Fogera, Ebenat, and Estie, is highly vulnerable to food insecurity and disasters, including floods and droughts. In 2021, more than 12,000 people were affected by these hazards (UNOCHA, 2022 ). Despite progress in disaster risk management (DRM), there remains a gap in understanding how formal (government led) and informal (community driven) disaster responses translate into practice. While there has been a shift towards community-owned DRM, particularly in Ethiopia, the implementation of these practices has not been adequately studied, especially at the household level in regions like Amhara. Studies show that even when people are aware of natural hazards, they often lack the resources to prepare and respond effectively (REACH, 2015 ). The challenge of integrating scientific knowledge into actionable policies and practices also persists, both globally and locally (Kristoffer et al., 2020 ). In Africa, countries like Rwanda have shown that many DRM workers lack preparedness, with 58.6% of Red Cross staff reporting no experience in disaster readiness (Kayiranga, 2019 ). In Ethiopia, research on disaster management practices, particularly at the household level, has been limited. Existing studies often focus on specific sectors such as hospitals, schools, and emergency workers, neglecting the broader context of households and their roles in disaster preparedness and response. Furthermore, most studies rely on quantitative methods, which fail to capture the deeper, qualitative insights needed to fully understand these practices. This study aims to address these gaps by providing comprehensive quantitative data on household disaster management practices, alongside in-depth qualitative insights into the roles, strengths, and challenges of households in managing disaster risks. 2. Materials and Methods 2.1. Study Design This study employed qualitative and quantitative mixed research method. Through quantitative methodology, this study used cross-sectional design to collect, organize, analyze, and present results from a disaster practice survey with a focus on assessing the levels of households’ practice, and to identify and present the influence of relevant factor influencing household practice. Qualitative data was collected using key informant interview (KII), in-depth interviews (IDI) and focus group discussions (FGDs). Qualitative data was transcribed and interpreted through a content analysis technique. 2.2. Setting As shown in Fig. 1 , this study was undertaken in Fogera, Ebenat and Estie woredas 1 of South Gondar Zone, Amhara National Regional State (ANRS). The ANRS is located in the northwestern Ethiopia between 9°20' and 14°20' North latitude and 36° 20' and 40° 20' East longitude (Aynalem, 2021 ). South Gondar Zone covers an area of 14,607km2 in 11° 39' 59.99" N latitude and 38° 00' 0.00" E longitude (Akalu et.al., 2009 ). Fogera is one of the major woredas in the South Gondar zone situated between the latitudes 11°57 and 11°59 and the longitudes 37°42 and 37°43 and altitudes ranging between 1793 to 1800 meters above sea level (Mare et.al, 2009). Woreta is the capital of the district, a town located 625 km from Addis Ababa and 55 km from the regional capital city, Bahir Dar (Gebrekidan, 2014 ). Ebenat is bordered on the South by Farta, on the Southwest by Fogera, on the West by Libo Kemekem, on the North by the Semien Gondar Zone, on the Northeast by the Wag Hemra Zone, on the East by North Wollo Zone, and on the Southeast by Lay Gayint (SERA, 2000). Estie woreda is located at 11°34’N, latitude, and 36°41’E, longitude and covers 132,374 km2 area. The woreda is situated about 676 km Northwest of Addis Ababa and about 100 km North of Bahr Dar, and it is bordered on the North by the Farta Woreda, on the Southwest Gojam, on the East by Simada Woreda and on the West by Andabet and Dera woredas (Metadel et.al. 2021). Fogera has a total of 34 Kebeles 2 , amongst 29 are rural. The rural population is estimated to be around 270243 and the number of agricultural households is approximately 44000 (Hagos, 2015 ). The woreda is dominantly known for rice production besides maize, finger millet, tef, onion, cattle rearing and others (Tsega, 2017). Ebenat woreda is structured by 37 kebele administrations, and 35 of them are rural. The total population of the woreda is 235,091 with 93% of rural population. Among the total population, women account for 48.74% or 114, 582. (Emewedew and Menberu, 2017) About 2.2% of the wereda population are migrants. Most of the migrants live in urban areas of the woreda, and about three/fourth of them originate from rural areas. Estie has 42 rural and 3 urban kebeles with total population of 424,041, out of which 216,329 and 207,712 are male and female respectively (CSA, 2008). The rural population size is nearly 94%. Most of the population follows the religion of Orthodox Christianity, while 2.91% are Muslims. 2.3. Study Population and Sampling Techniques This study employed both probability and nonprobability sampling techniques. Nonprobability purposive sampling technique was used to identify the target Zone, three woredas and nine specific kebeles using prior and existing experience with DRM as main selection criteria. Based on this technique, the research focused on South Gondar as this zone has contextual and environmental setting to better address the research questions that are aimed at assessing knowledge, attitude, and practice of DRM. Using purposive sampling strategy, this study identified three woredas names Fogera, Ebenat and Estie in South Gondar Zone. These areas have a total of 929,375 population under 116 kebeles of which 106 are rural and 10 are urban. Employing the same purposive sampling technique, a total of 9 kebeles were included through applying disaster prevalence and residential characteristics as major selection criterions. Three major criterions used were known as rural highly disaster affected, semiurban less disaster affected and urban with infrequent and normal context. As shown in Table 1 below, nine kebeles were identified with the total population of 62034 individuals and 10103 households. Table 1 Study population by kebele Woreda Kebele Criteria Total Population Households Fogera Shena Affected, and rural 2136 348 Woreta Zuria Mixed, both rural and urban 3599 587 Woreta town Less affected, semi/urban 21222 3456 Sub-total 3 26957 4391 Este Ziguara Affected, and rural 1242 202 Liwaye Mixed, both rural and urban 608 99 Mekane Eyesus Less affected, semi/urban 15413 2510 Sub-total 3 17263 2811 Ebenat Burkoch Affected, and rural 4350 708 Amesteya Mixed, both rural and urban 1462 238 Ebinat town Less affected, semi/urban 12002 1955 Sub-total 3 17814 2901 Total 9 62034 10103 Based on probability strategies, multistage cluster sampling technique was employed to determine the number of households on which observation was made. Using household as a sampling frame, standard population survey formula was used to determine number of households that were included in the study. The sample size was calculated using a formula (Cochran, 1977 ) considering the total population that is more than 10,000 and significant level of variation on “P”. Using probability simple random sampling, 412 household research participants have been identified across the nine kebeles. Trained data collectors secured household list by village from the kebele administration offices, and initially marked the households in seven intervals starting from the first household on the list. The identified households have been contacted for data collection. In an event where the identified household was not available, and in a few cases where a household was not willing to provide information, the immediate next and next household have been replaced and data was collected accordingly. In addition, purposive sampling was used to identify the research participants for qualitative methods at the region, zone, woreda and kebele levels. In this regard, this study included 36 representatives of key organizations from different sectors including government and non-governmental organizations, and 28 additional research participants from academia Among the government, regional, zonal, district and kebele level staffs of the regional Disaster Prevention and Food Security Program, Agriculture Burau, Health Bureau, and Education Bureau were included. 2.4. Data Collection This study employed both quantitative and qualitative data collection tools. The major quantitative research technique was structured disaster practice survey that was employed at different levels. Based on this, quantitative primary data was collected among 412 households at the nine kebeles, 28 academia and 36 representatives of local stakeholders. In addition, 177 research participants have involved through qualitative methods and primary information was collected using 69 KIIs, 45 IDI and nine FGDs involving 63 participants. 2.5. Data Analysis Using a quantitative design, this study collected data through 41 structured questions that are customized into the context through three sub-topics including preparedness (17 questions), prevention (12 questions) and mitigation (12 questions). These questions are analyzed using descriptive techniques and they are used to support the major findings as presented using percentages and tabulate summaries. In addition, five close-ended and actual participation-focused (yes/no) questions were used to measure the practice levels of households. Then parametric tests were conducted to identify and test the effects of key factors on households’ practice for DRM. Shapiro-Wilk test was conducted to determine the normality of the factors along the household practice levels with the null hypothesis that the variable is normally distributed, and this is rejected if the p-value is less than 0.05. The analysis indicated that the practice levels of research participants is not normally distributed with p value of 0.00001. Based on the findings of data normality test, this study has employed Wilcoxon-Mann-Whitney analysis to assess the influence of factors that are binary independent variables on the dependent variable of practice for DRM. For the categorical independent variables that have two and more levels, Kruskal Wallis test was conducted separately to test the influence with the dependent variable of households’ DRM practice levels, which are ordinal and non-normally distributed variables with 95% of confidence level and Ho that there is significant level of difference between the groups of independent variables towards households’ DRM practice levels. Using qualitative method, data was collected through KII, IDI and FGDs. Data collection was managed through briefly migrating into day-log book in the way that all information was properly documented on time and without any change from the original meaning provided by respondents. Once the data was properly collected, cross-sectional and categorical indexing was used to organize qualitative information for the use of content analysis through grounded theory approach. Data transcribing, coding and thematic development tools were used to properly prepare and analyze qualitative data. 2.6. Ethical Considerations This study fully complied with all the ethical standards throughout the whole process including data collection, analysis, presentation, and post-research periods. Prior to the starting the research, the proposal was examined by university professors, and the study was approved by the University after a detailed evaluation followed by a successful face-to-face defense. The university provided written formal letters to undertake the research. All forms of the data collection tools, and the questionnaires have been intensively reviewed by university professors and approved. At the time of collecting data, respondents and informants were provided with all the necessary briefing and informed consent was obtained from each research participant. Respondents’ right not to participate and/or to reject one or more questions were respected consistently. Personal information and indicators of research participants have been kept confidential. In addition, all data collected for the study is only used for the purpose of the research, that no data was provided for third party throughout all times, and all collected data will be disposed properly once this study is concluded. 3. Results 3.1. Demographic characteristics of practice survey respondent households Total number of respondents, gender, and locations A total of 412 households responded to the quantitative data collection process using disaster practice survey. Amongst, 34% were females. These households were from nine Kebeles and 31 villages with average number of 45 and 13 respondents respectively. Age of research participants The mean age of the household heads was 40, with the youngest age of 20 and 76 the oldest. The mean age for male households was 41, while the mean age of female households was 39. The overall age of research participants was stratified in four age categories for the purposes of data analysis. Accordingly, 13.47% and 2.24% were youths and elderly respectively, while the majority 58.35% and 25.94% were adults between the ages of 30–45, and 46–65 respectively. Education level of the households Among the total households, 54.5% reported illiterate and basic literacy from informal education. Amongst, 41% are in Fogera followed by 33.5% in Estie and 25.5% in Ebenat. Kebele wise, nearly 60% of the illiterate households are concentrated in three Kebeles mainly Amestaya in Ebenat (21%), Shena in Fogera (20%) and Liway in Estie (19%). The number of research participants having university diploma, first degree and second degree increases from the rural kebeles into the semirural and the urban Kebeles. Religions of the households According to the responses, 92% of the households are reportedly Christian Orthodox followed by 7.5% Muslims and 0.5% of Christian Protestants. While the Orthodox households are dispersed across the nine Kebeles, Muslim households are concentrated in urban kebeles of Fogera Woreda (32% in Woreta town 01 kebele and 16% in Woreta Zuria kebele), and 23% others in Ebenat woreda Burkoch kebele. Economic statuses of households Using subjective self-assessment of economic status, this study found that 46% of households are middle economy that was defined as comparatively similar to others, 28% rich, 23% poor defied as below most of the community members and 3% very poor that was indicated as extremely lower economic status from the majority households in their kebeles. The study used a follow-up question to triangulate economic status through the average daily expenditure of a household could afford in Ethiopian Birr (ETB). According to their responses and based on the World Bank Group poverty and equity category brief (2020), 73% of households are below the international poverty line or below USD1.90 income per day, 16% are lower middle with less than USD3.20, 5% are upper middle economic status with more than USD3.20 per day, while the remaining 6% are in the upper midlevel economic status affording more than USD5.50 per day. Vulnerability to hazards According to the responses from households, 41% are aware of the different hazards, and they perceive household vulnerabilities. Amongst the households who are not aware of vulnerabilities, nearly half (48%) are in Ebenat woreda with majority of them in Amestaya kebele followed by Shena kebele in Fogera woreda. 3.2. Demographic characteristics of stakeholders Academia A total of 28 individuals in academic institutions have participated from Bahir Dar University, Debre Tabor university Woreta campus and Debre Tabor University main campus. Among the total 28, eight were females, and 82% of the research participants have second degree education level. Other stakeholders A total of 36 individuals from different sectors have participated, and two were females. The majority were in Ebenat (30%), followed by Estie (28%), Bahir Dar (22%) and Fogera (19%). From these, 22 are governmental, 10 in non-governmental organizations, and the remaining four from religious institutions representing Christian Orthodox church and Muslim. Among these participants, 72% have technical working experience directly related with disaster risk management while the remaining 18% are engaged in managerial roles. 3.3. Demographic Characteristics of Qualitative Data Participants KIIs were conducted involving 69 (female, 32) participants in the regional government bodies (4 males), regional non-governmental humanitarian organizations (4, 2 females), South Gondar Zone administration (3, males), Debre Tabor University (1, male), the three woreda administrations (12, 4 females) and households at the nine kebeles (45, 26 females). In-depth interviews were organized among 45 (27, female) other participants from households across the nine kebeles (33, 22 females), three woreda governmental bodies (3, 1 female) and nine kebele administration offices (9, 4 females). FGDs were facilitated across nine kebeles involving a total of 63 participants (44, female). The participants of FGDs included the households, kebele administration offices, faith-based organizations, and youth. The average number of participants per FGD was seven. 3.4. Practice levels of households in disaster and risk management activities Based on a descriptive analysis of practice survey, 16% of the households have not been involved in any of disaster risk management activities at the community level followed by 28% who reported a very-low level of practice. As presented in Table 2 , households in Fogera constitute 50% of the total households who have below the mid-level of practices. The mean of the total practice levels for three woredas is 1.97, while Estie has the highest mean (2.42) followed by Ebenat (1.79) and then Fogera (1.72). Preparedness Based on the responses, 80.5% of households did not participate in any disaster preparedness and risk early warning activities. In addition, 71% of research participants indicated that they do not have community disaster management plan. However, 48% of the respondents indicated the existence of informal and indigenous risk management practice at their communities. Prevention response Although 80% of the households reported their willingness to participate in disaster prevention, 61% have not been involved in any activities aimed at preventing a risk. In support of this, 82% of the respondents revealed the inexistence of disaster or risk and hazard prevention structure at their community. The other respondents who reported the availability of disaster structure were asked their membership, and 96% indicated that they are neither members nor actively involved. Mitigation Alike the disaster prevention, around 84% of the households indicated their willingness to participate in disaster mitigation activities within their community but it is 36% of them who have reported actual participation in relevant roles. In addition, 31% of the households supported the existence of defined roles and responsibilities to mitigate disasters in their communities. 3.5. Factors affecting households’ DRM practices and activities The households and the other research participants representing academia and stakeholders were asked to identify the different factors influencing disaster practices among the communities in Ethiopia. Based on the preliminary research hypothesis and the responses from research participants, a total of eight factors were identified as the underlying factors affecting households’ disaster and risk management practices. The factors, also referred to independent variables, are age, location, gender, education status, religion, economic status, indigenous disaster management experience, and awareness of vulnerabilities. Among these, five independent variables have been stratified and analyzed in different groups for triangulation purposes and to minimize bias from self-reported data. In this regard, Age has been used as a continuous variable (as responded by each household) as well as categorical variable after stratified in four age groups separately. Education status has been stratified in binary variable (literate and illiterate), as well as categorical variable along the five levels of education that were used to collect primary data (none-basic literacy, 12 complete, diploma, university degree and second degree). Likewise, economic status has been analyzed as categorical variable using the self-assessment data from households (very poor, poor, midclass/regular, and rich) and the average daily expenditure that a household can afford (1-50ETB, 51-150ETB, 151-300ETB, 301-500ETB, and 500 + ETB). In addition, household risk awareness or perception of vulnerability has been stratified as a binary variable (yes/no) and categorical (yes, no and I don’t know any risk/vulnerability). Location has been analyzed at two levels, by Woreda (the three) and Kebele (nine Kebeles). Sex/Gender The Mann - Whitney test on gender indicated no statistically significant difference between the male and female headed households for disaster practice levels (z = 0.222, P = 0.8240). To determine the actual difference, the rank with sums was compared with the expected, which indicated that the sum of males’ rank was slightly higher than females (m = 207, and f = 204). Risk awareness and indigenous disaster management activities The same test was conducted to see if the households’ awareness of vulnerability is different for their practice levels in disaster management activities. The result indicated no statistically significant difference between risk awareness and DRM practice of households (z = 1.764, P = 0.0778). The rank sum comparison showed that households who have no risk information have higher level of practices than those who are aware of certain hazards. The analysis between households who have indigenous disaster and risk management practices, and the others who reported no such experiences showed no statistically significant difference (z = 1.424, p = 0.1545). However, the average rank sum of households is higher for those who have indigenous practices (n = 195, actual total rs = 41429.5) compared to others who do not have any indigenous risk management experiences (n = 212, actual rs = 41598.5). Education status and disaster practices A Mann - Whitney test conducted using stratified education levels of households indicated no statistically significant difference between the literate and illiterate for disaster practice levels (z = -0.109, p = 0.9135). The comparison of the average actual and expected rank sum is almost the same between the illiterate (204) and literate (205) households. Age of the households According to the Kruskal Wallis test using the stratified age groups and DRM practice, there is no statistically significant difference between the different age groups at a p value of 0.6675 with ties and 0.6841 without ties. Meanwhile, the rank sum with the corresponding number of observations indicated that households between 66–76 ages have higher level of DRM practice with average rank sum of 211.5, followed by a 206 average rank sum of the households in the 30–45 age group. The minimum average rank sum is 190 among the households aged 46–65 compared to 196 within the youngest. Religions of the households The difference within the religion types and DRM practices of households was analyzed using Kruskal Wallis. This test indicated no statistically significant difference among the Orthodox Christians, Muslims and Protestant Christians for the DRM practice at a p value of 0.0809 without ties and 0.0720 with ties. However, rank sum suggested that disaster practice is higher among Protestant Christians compared to the Orthodox Christians and the least within Muslims. Education levels of the households Likewise, the same test indicated no statistically significant difference within the various levels of education and the DRM practice at a p value of 0.5331 with ties and 0.5563 without ties. The average actual rank sum of a household who has masters’ degree is the highest (404.5), followed by households who have diploma (208), and then those households who do not have formal education level (204). The average actual rank sum of households who have first degree is the lowest (201.6) followed by those 12th grade complete (202). Economic status of the households According to the results of a Kruskal Wallis test, there is a statistically significant level of difference within households’ economic status and the DRM practices at p = 0.0406 with ties and 0.0482 without ties. The average rank sum of households who reported economically very poor has been the highest (n = 14, rank sum = 3649) followed by those who reported economically rich (n = 111, rs = 23507), and those who reported regular (n = 184, rs = 36951.5) with the lowest being among economically poor households (n = 92, rs = 16493.5). As shown in Table 3 , the analysis on households’ average daily expenditure has also indicated statistically significant difference within the groups and the practice levels of DRM at p = 0.0087 with ties and 0.0113 without ties. The result indicated a difference with the findings of households’ self-economic assessment where households with highest daily expenditure have lowest rank sum (n = 23, rank sum = 3540) followed by the low expenditure group ETB51-150 (n = 145, rs = 28063.5) and then the very low expenditure group ETB1-50 (n = 155, rs = 31229.5). The highest rank sum was among households with average daily expenditure of ETB301–500 (n = 19, rs = 4830) followed by the mid-expenditure households ETB151-300 (n = 64, rs = 14958). Locations of the households Kruskal - Wallis test using woredas indicated statistically significant difference within the three woredas and the households’ practice levels for DRM at a p value of 0.0001 with both ties and without ties. The test also suggested that households in Fogera have lowest average rank sum compared to households in Ebenat and the highest in Estie. As presented in the Table 4 below, the test using kebeles similarly revealed a statistically significant difference within the nine kebeles and the households’ practice levels of DRM practices at p value 0.0001 for both with ties and without ties. Among the three highest rank sums, two are urban kebeles (Ebenat town 01 kebele and Mekane Eyesus kebele. The least rank sum was also within the rural kebeles mainly in Burkoch kebele, followed by Woreta Zuria and Shena kebeles both in Fogera woreda. 3.6. Strength, limitations, and opportunities of disaster management practices Based on responses from 412 households across three woredas and nine kebeles, key strengths of current DRM practices include positive community attitudes (41%) and the support of faith-based organizations, particularly the Orthodox Church and mosques (38%), which contribute to awareness and recovery efforts. Additionally, 32% of households recognized the importance of natural resources, such as land and water, in enhancing DRM effectiveness. Other strengths identified include local government support (31%), community-based planning (29%), and strong NGO involvement (24%). Academics highlighted NGO and humanitarian agency engagement (75%) and the role of faith-based organizations (36%) as major strengths. However, 100% of academic respondents disagreed that policy, gender equality, and community attitudes were strengths. Local stakeholders similarly pointed to positive community attitudes (50%), effective policy and regulation (42%), and NGO support (36%) as top strengths. The main limitations identified by households were financial constraints (66%), lack of timely government support (64%), and ineffective DRM activities (50%). Other issues included insufficient coordination, policy gaps, and low community awareness. The least impactful challenges were the influence of faith-based organizations and harmful traditional practices. Academics ranked low government support (82%) and weak planning and implementation (82%) as the most significant limitations, while local stakeholders similarly pointed to resource shortages (72%) and hastily implemented DRM activities (61%) as top issues. Qualitative findings from key informants also identified poor structural capacity at local levels, insufficient resources, and weak DRM quality, characterized by unqualified personnel, untimely actions, and corruption. Households identified the availability of natural resources (58%), human labor (53%), and community commitment to DRM (46%) as the main opportunities. NGOs and humanitarian organizations were seen as moderately supportive (32%). However, financial resources and government support were viewed as less significant opportunities. Academics and local stakeholders echoed the importance of NGO and humanitarian support, labor availability, and natural resources, while also pointing to the potential for increased community engagement and awareness as key opportunities for improving DRM. 3.7. The roles and responsibilities of households in DRM practices Roles and responsibilities of households during disaster preparedness Qualitative insights from KII, IDI and FGDs highlighted several common roles and responsibilities for households. These include active participation in planning processes and meetings, direct involvement in hazard, vulnerability, and risk assessments, engagement in disaster preparedness planning, resource mobilization both in-kind and in cash, running community-owned early warning activities, and participation in regular follow-up and review sessions. While all groups agreed on these roles, their implementation varied. Academics generally noted that these responsibilities are often not practical across kebeles. Local stakeholders suggested that these responsibilities are shared with households, yet many households disagreed, feeling they do not play significant roles in these areas. Using quantitative descriptive analysis on the responses from 36 representatives of local stakeholders and 28 academia, the major roles and responsibilities of households include hazard and vulnerability assessment (82%), active participation in disaster preparedness planning (82%), local resource mobilization (64%), and joint risk assessment (61%). In the other side of the 412 households, 87% reported the absence of disaster preparedness plan. Of those with a reported DRM plan, 92% did not participate in its development. When asked about disaster response structures, 90% indicated there was no established committee for planning and responding to disasters. Among those who noted the presence of such structures, 97.6% reported having no role in the committees. Additionally, only 14% of households confirmed regular kebele and woreda meetings to discuss disaster preparedness and review DRM progress, with nearly 95% stating they did not attend these meetings. Regarding early warning systems, 31% of households acknowledged existence of different mechanisms to communicate risks among their localities. However, 61% were unaware of who manages these activities, and only 2.43% had roles in the early warning systems. To gauge households' readiness for disaster response, participants were asked if they knew their responsibilities during a disaster; 50% indicated they did not. Roles and responsibilities of households during disaster prevention Quantitative data from local stakeholders and academics indicated several key responsibilities for households during disaster prevention. Self-preparedness was highlighted as essential by 100% of respondents, while 64% indicated participation in actual prevention activities. Additionally, 61% noted the importance of hazard identification and planning for prevention activities, and 57% emphasized the need for monitoring prevention efforts. Joint risk assessment was acknowledged by 43% of respondents. The data also highlighted the roles households play in supporting affected individuals, primarily through resource mobilization and rehabilitation services, with 39% identifying these contributions. Despite this, most households, approximately 69%, did not perceive themselves as having defined roles. Qualitative responses varied, with participants in areas like Shena and Woreta Zuria noting their contributions through labor and in-kind assistance. Roles and responsibilities of households during disaster mitigation Based on the responses from academics and local stakeholders’ disaster mitigation roles of households included preparing for mitigation, with 75% of respondents acknowledging its importance, and participating in mitigation planning sessions, which 57% confirmed. Implementing mitigation activities was noted by 61% of participants, while 57% emphasized resource mobilization for mitigation responses and supporting reintegration and rehabilitation interventions. Community follow-up was similarly highlighted by 57% of respondents. Despite this, a significant number of households, approximately 65%, felt they lacked clearly defined roles in community disaster mitigation efforts. However, 14% of households indicated that their contributions, including labor, in-kind materials, and financial support, constituted their main roles in this area, with 8% emphasizing the importance of awareness creation in mitigation responses. 4. Discussion 4.1. The practice levels of households in disaster and risk management activities The practice for disaster risk management comprises the efforts and activities carried out in the context of disaster prevention, mitigation, preparedness, emergency response and recovery, which are performed before, during and after a disaster (Kyooman, 2020). Households play important role over the key phases of disaster management mainly preparedness, mitigation, and preventive response (Kar 2016). Several empirical studies have assessed the DRM practices of different key stakeholders including households, emergency responders, health workers and students. For instance, Shanableh et.al ( 2023 ) found that the overall disaster practice levels of health professionals through descriptive analysis of median and concluded that health workers have high level of readiness for disaster practice. Najafi et.al ( 2015 ) similarly measured the DRM practice levels of Nepalese immigrants in Japan and reported that more than 70% were unable to perform some preventive practices against natural hazards. Despite the common understanding on the significance of preparedness, prevention and mitigation, the participation of key stakeholders within this key practice involves various situations. According to this study, not more than 20% of the households across the three woredas and nine kebeles have disaster preparedness practice. In addition, only 39% of the households mentioned their involvement in disaster prevention activities while less than 35% reported participation in disaster mitigation practices. Among the total research participants, including 13% who reported the availability of preparedness plan, 92% were not involved in any of the preparedness planning processes. In addition, nearly 70% of the research participants reported that they are not engaged in disaster early warning practices. In the assessment of personal early warning readiness, most households (55%) do not have important equipment to be prepared including radio, mobile phones, and emergency tools. In other areas like Nepal, people seek information about hazards from mass media, and some from community outreach programs. According to Nepal Earthquake Preparedness for Safer Communities (NEPSC) (2013), more than 50% of community members use mobile as communication tool. In addition, only a small portion of the households had prepared plans and organized pre-arranged meeting points. NEPSC (2013) reported that 87.6% of households practice special committee for disaster preparedness. According to the REACH survey report (2015), it was only 6% of people in India rural areas reported the existence of a disaster management plan (DMP). In addition, the presence of community-level disaster management systems is extremely sparse and only 13% of people reported that their community has a disaster management committee, and 5% have taken part in a disaster preparedness activity. According to Suryadi et al. ( 2021 ), 88% of research participants understand that disaster preparedness was an activity carried out to anticipate disasters through appropriate and efficient steps. In terms of prevention and mitigation, the REACH survey (2015) reported that communities are involved in mitigation activities, and they believe on roles to reduce the effects of disasters. Accordingly, 32% of households reported awareness-raising, followed by the 32% planting and rehabilitating forests, and others indicating flood mitigation and related undertakings. However, prevention and mitigation practices are different compared to the findings of this study, which 64% of households reported that their community does not have defined roles and responsibilities for both prevention and mitigation practices. 4.2. Factors influencing households’ practices in DRM activities Location by woreda This study found that households in Fogera have lowest level of DRM practices followed by Ebenat, and the highest in Estie. This implies that the households that are in disaster prone areas like Ebenat and Fogera have lower levels of practices compared to the areas that are less prevalent to disasters. In this view, Mostafizur et.al., (2023) found that research participants living outside the urban areas of Dhaka have higher levels of practices to prevent COVID-19 than others living in semi-urban and urban cities. Location by kebele This study revealed that all the urban kebeles have high levels of disaster management practice except Woreta town 01 kebele. Disaster affected and rural kebeles have the lowest levels of practices with an exception to Zigura kebele in Estie. The communities in rural and disaster-affected areas are known to participate in different types of disaster management activities. During the KII and FGDs, the households in Sehna and Woreta Zuria discussed about the flood mitigation, forestation, and improved farming activities that they undertake to prevent the effects of disasters. However, the finding of practice survey is different from showing what the households discuss in FGDs and KII. In addition, the households in urban kebeles have more access to information and psychological readiness, which might contribute to overall aptitude than actual practice. Economic status According to results of this study, economically very poor households have very high level of participation in DRM activities. Economically mid-class households have the next higher and mid-level of engagement within risk management. Households with highest amount of daily expenditure have lowest levels of practices in DRM. The households who are affording the midlevel expenditure amounts have also lower level of practice but much higher than those who are affording highest expenditure. In comparison, the high level of DRM activities is practiced among households who can afford the middle expenditure levels. Therefore, the DRM practice and participation is higher among the households who have middle level economic status followed by the poor. The disaster management practice is very low for the households who have uppermost income or those who have the highest economic status. In studies like Mostafizur et.al., (2023), individuals who have the highest level of economic status showed highest level of DRM practices during disasters like the outbreak of COVID-19 pandemic. However, the continuous level of engagement in DRM activities is low among this groups, which midclass and poor are often involved in many countries. During the FGDs with academia and representatives of local stakeholders, this point was echoed where participants indicated that households who have highest income levels participate in DRM activities when there is active disaster (during disaster) than preparedness. They are also characterized as detached from the wider community during preparedness and preventions, which they intend to focus and invest more on ensuring their own protection than working with the communities for collective disaster management results. Sex/Gender This study found no difference between males and females for their practices in disaster and risk management activities. Since most research participants are in rural and semi-urban areas where female households share farming, agricultural, livestock and environmental responsibilities with the male households, the situation is likely. In support of this, Shanableh et.al ( 2023 ) reported that the overall DRM practice levels of women was 39 compared to the men 41. This study conducted Mann – Whitney test and reported that there was no statistically significant difference between men and women (p = 0.064) for their readiness and practice against disasters. Religion The difference between religion groups for the DRM practice levels of households indicated no statically significant difference among the Orthodox Christians, Muslims, and Protestant Christians. However, Table 5 shows the descriptive analysis of means and it revealed that the disaster management practice levels is higher among the Orthodox Christians than the Protestant Christians and the least of Muslim households. Table 5 Mean of DRM practice by religion .tabulate of Religion, summarize (Practice Level of Respondent) Religion Summary of the respondent practice level in 0–5 scale Mean Std. Dev. Freq. Orthodox 2.0212766 1.4045923 376 Muslim 1.4516129 1.3376275 31 Protestant 2 0 2 Total 1.9779951 1.4027301 409 In terms of preparedness, 13% of Christian Orthodox households, and 12.9% of Muslims have actively participated, while none of the Christian Protestants engaged in this activity. As shown in Table 6 , 37.5% of Christian Orthodox and 58% of Muslims have been involved in disaster prevention activities. Regarding mitigation, 34% of Christian Orthodox households and 61% of Muslims reported their participation in their community, except Christian Protestant households. Table 6 DRM prevention participation by religion .tabulate Religion DisasterPreventionParticipation Religion Have you ever participated in preventing a forecasted disaster? Yes No I don’t k Freq. Orthodox 142 122 113 377 Muslim 18 8 5 31 Protestant 0 0 2 2 Total 160 130 120 410 In the practice survey, the Christian Protestant households have responded much better than both the Orthodox and Muslim households. The likelihood reason behind the increased result of DRM practices among these households could relate to access for information that contributed to respond for the KAP survey questions. Therefore, this is one of the potential areas for further studies and scientific research in the future. Education status The practice levels of disaster management activities have statistically no significant difference within the education levels of households. However, this study also found that households with the highest educational level of masters’ degree and then the diploma or TVET graduates have higher level of DRM practices. Most of the households who are illiterate, basic literacy and numeracy have comparatively high practices than the households with first degree and others who are 12th grade complete who have the lowest levels of practices in DRM activities. According to Fatmah (2023), a higher education facilitates better information absorption, which impacts the level of knowledge. This knowledge and awareness will influence how the people deal with disaster situations before, during and after a disaster. Therefore, involving individuals particularly older adults in regular training positively influence the DRM practice and preparedness. In a study that assessed the climate adaptation practice of households in South Gondar zone, Beletech et.al, ( 2019 ) reported that of lack of information and knowledge negatively affected households who failed to take adaptation measures against climate change. Awareness of vulnerability and risk information According to the practice survey, there is no statistically significant difference for disaster practice among households who have vulnerability awareness and other households who do not have this information. Meanwhile, the results indicated that the overall DRM practice levels of households who have vulnerability awareness is lower than households who do not have risk and vulnerability information. This is mainly due to the situation that most of the DRM practices in the target areas lack to integrate vulnerability and risk information with households’ participation within DRM activities. Even though some areas like Shena and Worera Zuria in Fogera, and Amestaya in Ebenat have information on hazards including flood, and drought respectively, the households are not supported to internalize the risk information in a way that they actively participate during DRM practices. Another reason is lack of accurate information on vulnerabilities and risk information. In this regard, the households in the nine kebeles have wide range of perception on their vulnerabilities. For instance, more than 60% of the households reported that they have faced at least 3 hazards and the related consequences of disasters in the areas. In the identification of the hazards, most of the households commonly agree a few hazards are not the case such as 74% of the total households reporting that COVID-19 is not a risk across the areas. In other cases, there are hazards that have majority support such as communal conflict that a total of 71% households report as a significant risk across most of the kebeles including urban areas like Woreta town. Likewise, more than 84% of the households across the nine kebeles and three woredas perceive flood as a threatening hazard, which 45% of the households identified it as highly prevalent risk. The kebeles who have identified this hazard as a major risk and vulnerability include urban areas such as Ebenat and Woreta town kebeles. So long the hazard and risk information are not supported to reflect the context, and are not integrated in community actions, awareness of vulnerability by itself hardly makes difference within the DRM practice levels of households. Indigenous DRM practices Even though experience with different types of indigenous DRM activities has no statistically significant difference, this study found that households who are engaged in the indigenous practice have higher level of practice than other households who have no indigenous practices. In a descriptive analysis, the participation of households who have indigenous DRM practices is consistently higher than others in early warning, disaster preparedness, prevention, and mitigation activities. As presented in Table 7 , among the total households involved in DRM planning, 59% are households that have indigenous practices in their communities. Table 7 DRM plan by ingenuous practices .tabulate IndigenousDRM Practices DRM Plan Do you have Indigenous DRM Practice Do you know DRM Plan? Yes No Total Yes 71 125 196 No 32 115 147 I don’t know 18 47 65 Total 121 287 408 From the total households who reported having early warning responsibilities, 63% are the households involved in indigenous practices. Likewise, 67%, and 68% of the total households involved in disaster prevention and mitigation are the households that have experiences in the indigenous DRM undertakings. Therefore, the active participation of households in DRM practice is evident than other households who have no experience of indigenous DRM activities. In support of this as shown in Table 8 , the overall DRM practice mean is highest among households who have indigenous practices (2.08) than others who do not have such experience (1.81) and the remaining uncertain households (1.92). Table 8 DRM mitigation participation by indigenous practices .tabulate IndigenousDRM Practices MitigationParticipation Do you have Indigenous DRM Practice Have you ever participated in mitigating disaster and its consequences Yes No I don’t k Total Yes 96 59 41 196 No 39 62 42 143 I don’t know 7 16 42 65 Total 142 137 125 404 Age Households aged 66–76 have higher level of disaster management practice, followed by the 30–45 age groups. While the young group within 18–29 has lower level of practice, the older adult aged 46–65 have the lowest level of participation in DRM activities. In support of this, Shanableh et.al ( 2023 ) revealed that the total score for practice was higher among health professionals over the age of 50 years (44, 38–44) than the young group (42, 34–44) and the adults between 26–50 (39, 33–44). However, the overall result indicated no statistically significant difference between the age group and total practice score (p = 0.14). Nevertheless, Fatmah (2023) reported that efforts are required to improve older adults’ preparedness for disasters through involving them or their family members in regular training and seminars and by updating knowledge and information accessible for them. In addition, the REACH ( 2015 ) survey suggested that women over 60 are less likely to view DRM as a priority, and less likely to feel involved in household or community-level disaster preparations. Even though other empirical studies indicated this age group as highly vulnerable that seeks the support from others, this study consistently revealed that the elders have higher level of knowledge, attitudes, and practices. 4.3. The strengths and limitations of DRM practices The research participants identified several key strengths in disaster risk management (DRM). These include a positive attitude towards DRM and constructive traditional practices that enhance the effectiveness of various activities. Faith-based organizations, particularly the Orthodox Christian Church and Mosques, provide vital support in awareness creation and recovery assistance. Additionally, a conducive environment with accessible natural resources, local government support, community-based planning and implementation, and strong backing from non-governmental organizations (NGOs) contribute positively to DRM efforts. Weak support from government bodies, particularly at the kebele level, and insufficient financial resources pose significant challenges. Other issues include limited technical knowledge and skills, inconsistent engagement, negative perceptions among some households, and a lack of strong agencies for coordinated household engagement. In areas like Shena and Woreta Zuria, participants acknowledged government involvement in DRM but also highlighted issues such as untimely responses, corruption, and inadequate government actions related to disaster management. According to Petros and Neng (2021), community participation in formal disaster risk planning is underdeveloped, and there is a pressing need for a shift from emergency responses to risk reduction initiatives. Engaging the private sector is also a critical area that requires improvement. While there have been policy-level achievements, creating resilient communities during disasters demands greater effort. Policies must ensure that lives and livelihoods are safeguarded, aligning with sustainable development goals. Studies by Aaron (2013) and Mulugeta (2010) highlighted common limitations, such as low levels of information on vulnerabilities and coping mechanisms, reactive disaster management approaches, inadequate inter-sector coordination, and challenges in decentralized planning and budgeting. Sheganew et al. (2022) noted that DRM policy provisions lack enforcement and accountability, leading to an unresponsive system. Furthermore, traditional reliance on emergency assistance and food aid, coupled with insufficient investment in building resilient households, presents ongoing challenges. 4.4. The roles and responsibilities of households in disaster risk management The study identified several key roles and responsibilities for households in DRM. These include preparing for mitigation activities, participating in disaster mitigation planning sessions, implementing mitigation strategies, mobilizing resources for responses, supporting reintegration and rehabilitation efforts, and engaging in community follow-up. Households reported that their responsibilities include providing labor, in-kind material support, financial contributions, and raising awareness. However, over 65% of participants indicated they lack clearly defined roles in DRM, particularly in preparedness, prevention, and mitigation phases. Quantitative data and feedback from key informant interviews (KII) and focus group discussions (FGD) confirm this lack of clarity. This finding aligns with the REACH KAP report (2015), which noted that 42% of participants were unaware of their responsibilities during disasters. This confusion undermines the efficiency of responses and accountability among actors. Numerous studies emphasize the foundational role of households and communities in DRM, advocating for community-based practices. Few et al. ( 2015 ) assert that communities should lead disaster preparedness efforts, including establishing preparedness plans, enhancing communication, and raising public awareness about mitigation strategies. Communities must analyze their hazards, vulnerabilities, and capacities. Ebinezer ( 2010 ) outlined five levels of community responsibility in DRM, including informing members about available services, consulting on issues, being accountable for decisions, facilitating collective decision-making, and managing service delivery. Kiranjot ( 2024 ) emphasized that communities can collaboratively analyze threats, capabilities, vulnerabilities, and risks by integrating local and scientific knowledge. Essential elements of this process include creating disaster management plans, forming disaster management committees and teams, raising awareness, training, and establishing contingency funds. 5. Conclusion Household engagement in disaster management activities remains critically low, with only 34% of research participants involved in risk management practices. The most concerning is preparedness, where just 20% of households are participating in activities aimed at mitigating risks and vulnerabilities. This indicates a significant gap in disaster preparedness, compounded by a lack of involvement in community-based structures and low participation in available committees. Despite the overall low engagement, households show slightly higher participation in prevention efforts compared to preparedness and mitigation. When comparing participation by woreda, households in Estie are most engaged in DRM practices, followed by Ebenat, while those in Fogera are the least involved. At the kebele level, higher levels of engagement are observed in Ziguara, Ebenat Town 01, and Mekane Eyesus 01 kebeles, compared to Burkoch, Woreta Zuriya, and Ametasya kebeles. This suggests that DRM practices are more prevalent in urban kebeles, particularly those less affected by recurrent disasters. Demographic factors influence participation where males engage more than females, Orthodox Christians are more active than Muslims and Protestants, and literate households participate more than illiterate ones. Households informed about their vulnerabilities show more involvement, as do those engaged in indigenous DRM activities. Additionally, older adults and elders participate more than youth, while economically disadvantaged households display higher levels of DRM practice. The strengths of disaster management practices include a positive attitude toward DRM, constructive traditional practices, support from faith-based organizations (notably the Orthodox Christian Church and Mosques), a conducive environment, access to natural resources, community awareness, and engagement from NGOs and humanitarian agencies. However, challenges persist, including weak government support at the kebele level, limited financial resources, inadequate technical knowledge and skills, inconsistent engagement, negative perceptions among some households, and a lack of a strong agency to coordinate household involvement. Most households take on roles related to preparing their families for mitigation activities, participating in disaster mitigation planning, implementing mitigation strategies, mobilizing resources, and supporting rehabilitation efforts. Common responsibilities include providing labor, in-kind material support, financial contributions, and raising awareness. Although many households express a willingness to participate in DRM practices, they often lack clearly defined roles and responsibilities in preparedness, prevention, and mitigation efforts. 6. Implications Disaster risk management practices and household involvement in related activities are notably low across the three woredas, particularly in rural areas frequently affected by hazards. Preparedness emerges as a significant concern among research participants. Therefore, efforts should focus on strengthening existing preparedness practices and establishing new ones throughout the three woredas, prioritizing rural kebeles in Fogera, Ebenat, and Estie in that order. Preparedness activities should center on mobilizing households for hazard, vulnerability, and risk assessments. This includes actively engaging households in disaster preparedness planning processes, establishing and enhancing kebele level early warning systems, and creating community owned disaster preparedness structures and committees. Over 88% of households express a willingness to participate in DRM practices, including prevention and mitigation activities. However, it is crucial to intentionally target, mobilize, and engage households with low income, as well as those with higher economic status, in DRM efforts. The strengths of current DRM practices should be further enhanced through a selective approach at the household, community, and system levels. At the system level, reinforcing policies and maintaining DRM structures at the regional, zonal, and woreda levels are strategic actions for advancing DRM more effectively. Policy reviews should be evidence-based, with actions aimed at maximizing policy efficacy. One key area for improvement is to shift the focus from the traditional emergency response model to preparedness and knowledge-building. The policy should reinforce the integration of basic DRM engagement within community members. Another critical area for policy review is establishing accountability for DRM among households and local key actors, including the private sector and academia. Participation in DRM should not be optional for households, government bodies, private sectors, academia, and community-based organizations. The Ethiopian community-based health insurance scheme can serve as a valuable example of promoting local ownership and accountability in DRM. At the household and community levels, the involvement of NGOs and humanitarian organizations has been a strength. Traditional and religious DRM response activities such as the emergency bell ringing by the Orthodox Church and the initiatives of Muslim communities should be adapted into more effective community-owned practices during disaster prevention and mitigation phases. Promoting community-owned DRM is essential, which households must be engaged continuously before, during, and after disasters. The roles and responsibilities of households should be clearly defined and mutually agreed upon within communities. The current emergency focused and resource-centered disaster practice approach should gradually transition to a holistic and sustainable disaster risk management process, supported by local resources and accountability at the grassroots level. 7. Limitations This study involves limitations associated with the use of self-reported data, analysis techniques and data normality. In terms of the increased use of self-reported data, the study has employed different strategies to mitigate potential bias. This was through triangulation using secondary data and collecting more information about the same independent variable. For instance, age was analyzed in a range of four groups as well as individually along respondents. The self-reported economic status was triangulated using average daily expenditure the household can afford, and education status has been analyzed in similar two strategies. The use of multivariate analysis may enhance the results showing the relationships between independent and outcome variables more clearly. This study did not employ multivariate analysis due to data nonnormality. Additional studies are recommended to address this potential gap in the future. 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International Journal of Research Studies in Agricultural Sciences (IJRSAS); 2019. The World Bank. Disaster Risk Profile Ethiopia. Africa Disaster Risk Financing Initiative. Office of the, The World Bank; 2019. Tsega Adego. Characterizing and tailoring climate change adaptation practices into a diversified agroecosystem. Research Square; 2017. Yogesh K, Singhal RB, Bhanwar L, Bharti P. (2016). Knowledge, attitudes, and practices of medical internship students regarding disaster preparedness at a tertiary-care hospital of Udaipur, Rajasthan, India. International Journal of Medical Science and Public Health Online 2016. Footnotes The administrative unit under zone and region that oversees the smallest units called as Kebeles in Ethiopia. This is similar to County form of administration. The smallest administrative unit in Ethiopia Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6233979","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":429250874,"identity":"d933ae74-4bb7-4625-9ebc-06a18075a491","order_by":0,"name":"Temesgen Alemu Tilahun","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0klEQVRIiWNgGAWjYNCCAoYEBvYGBmaiFPOASQOgFp4DJGuRSCBSiz17d+KDHwZ2eQY33xh+LqiwYeBv707AbwvP2c2GPQbJxQa3c4ylZ5xJY5A4c3YDfi0SudskeAyYEzfczjGQ5m07zGAgkUtAi/zb7T//GNQnbrh5xvg3cVokeLcx8xgcTtxwg8eMSFvO5G6WljE4Xix5Jq3MmudMGg9Bv7C3n9348U1FdR7f8cObb/NU2Mjxt/fi14IEOAzA1hKrHGzhA1JUj4JRMApGwQgCALEPRVDEDg1qAAAAAElFTkSuQmCC","orcid":"","institution":"Bahir Dar University","correspondingAuthor":true,"prefix":"","firstName":"Temesgen","middleName":"Alemu","lastName":"Tilahun","suffix":""},{"id":429250875,"identity":"ffc07d66-2618-4148-b40b-50fba6e000da","order_by":1,"name":"Abraham Mebrat Asemare","email":"","orcid":"","institution":"Bahir Dar University","correspondingAuthor":false,"prefix":"","firstName":"Abraham","middleName":"Mebrat","lastName":"Asemare","suffix":""},{"id":429250876,"identity":"04e3197e-3ac2-481a-8d5d-d61b4ba51c9c","order_by":2,"name":"Tesfahun Asmamaw Kassie","email":"","orcid":"","institution":"Bahir Dar University","correspondingAuthor":false,"prefix":"","firstName":"Tesfahun","middleName":"Asmamaw","lastName":"Kassie","suffix":""}],"badges":[],"createdAt":"2025-03-15 16:38:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6233979/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6233979/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":79651667,"identity":"62bfb6ad-cb6e-4542-8d72-3b9f444b2cd0","added_by":"auto","created_at":"2025-04-01 08:01:03","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":250467,"visible":true,"origin":"","legend":"\u003cp\u003eStudy locations, by country, region and zone\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6233979/v1/aa46c062931a32f9bca712f8.png"},{"id":81019974,"identity":"d0ae14ad-0170-4146-af5c-c3440578ac41","added_by":"auto","created_at":"2025-04-21 09:32:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1656398,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6233979/v1/5a31ff33-a859-442b-bf2d-22c327296127.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Disaster Risk Management Practices among Households in Selected Kebeles of South Gondar Administrative Zone","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eDisasters have significantly impacted Africa, including Ethiopia, for a long time. In Ethiopia, the 2021/22 drought affected over 2\u0026nbsp;million people, while inter-communal conflicts displaced 2\u0026nbsp;million and impacted over 5\u0026nbsp;million (Sheganew et al., 2022). The Amhara region, particularly South Gondar Zone and districts like Fogera, Ebenat, and Estie, is highly vulnerable to food insecurity and disasters, including floods and droughts. In 2021, more than 12,000 people were affected by these hazards (UNOCHA, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite progress in disaster risk management (DRM), there remains a gap in understanding how formal (government led) and informal (community driven) disaster responses translate into practice. While there has been a shift towards community-owned DRM, particularly in Ethiopia, the implementation of these practices has not been adequately studied, especially at the household level in regions like Amhara.\u003c/p\u003e \u003cp\u003eStudies show that even when people are aware of natural hazards, they often lack the resources to prepare and respond effectively (REACH, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The challenge of integrating scientific knowledge into actionable policies and practices also persists, both globally and locally (Kristoffer et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In Africa, countries like Rwanda have shown that many DRM workers lack preparedness, with 58.6% of Red Cross staff reporting no experience in disaster readiness (Kayiranga, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn Ethiopia, research on disaster management practices, particularly at the household level, has been limited. Existing studies often focus on specific sectors such as hospitals, schools, and emergency workers, neglecting the broader context of households and their roles in disaster preparedness and response. Furthermore, most studies rely on quantitative methods, which fail to capture the deeper, qualitative insights needed to fully understand these practices.\u003c/p\u003e \u003cp\u003eThis study aims to address these gaps by providing comprehensive quantitative data on household disaster management practices, alongside in-depth qualitative insights into the roles, strengths, and challenges of households in managing disaster risks.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study Design\u003c/h2\u003e \u003cp\u003eThis study employed qualitative and quantitative mixed research method. Through quantitative methodology, this study used cross-sectional design to collect, organize, analyze, and present results from a disaster practice survey with a focus on assessing the levels of households\u0026rsquo; practice, and to identify and present the influence of relevant factor influencing household practice. Qualitative data was collected using key informant interview (KII), in-depth interviews (IDI) and focus group discussions (FGDs). Qualitative data was transcribed and interpreted through a content analysis technique.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Setting\u003c/h2\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, this study was undertaken in Fogera, Ebenat and Estie woredas\u003ca class=\"FNLink\" href=\"#Fn1\" id=\"#FNLinkFn1\"\u003e\u003csup\u003e1\u003c/sup\u003e\u003c/a\u003e of South Gondar Zone, Amhara National Regional State (ANRS). The ANRS is located in the northwestern Ethiopia between 9\u0026deg;20' and 14\u0026deg;20' North latitude and 36\u0026deg; 20' and 40\u0026deg; 20' East longitude (Aynalem, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSouth Gondar Zone covers an area of 14,607km2 in 11\u0026deg; 39' 59.99\" N latitude and 38\u0026deg; 00' 0.00\" E longitude (Akalu et.al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Fogera is one of the major woredas in the South Gondar zone situated between the latitudes 11\u0026deg;57 and 11\u0026deg;59 and the longitudes 37\u0026deg;42 and 37\u0026deg;43 and altitudes ranging between 1793 to 1800 meters above sea level (Mare et.al, 2009).\u003c/p\u003e \u003cp\u003eWoreta is the capital of the district, a town located 625 km from Addis Ababa and 55 km from the regional capital city, Bahir Dar (Gebrekidan, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Ebenat is bordered on the South by Farta, on the Southwest by Fogera, on the West by Libo Kemekem, on the North by the Semien Gondar Zone, on the Northeast by the Wag Hemra Zone, on the East by North Wollo Zone, and on the Southeast by Lay Gayint (SERA, 2000). Estie woreda is located at 11\u0026deg;34\u0026rsquo;N, latitude, and 36\u0026deg;41\u0026rsquo;E, longitude and covers 132,374 km2 area. The woreda is situated about 676 km Northwest of Addis Ababa and about 100 km North of Bahr Dar, and it is bordered on the North by the Farta Woreda, on the Southwest Gojam, on the East by Simada Woreda and on the West by Andabet and Dera woredas (Metadel et.al. 2021).\u003c/p\u003e \u003cp\u003eFogera has a total of 34 Kebeles\u003ca class=\"FNLink\" href=\"#Fn2\" id=\"#FNLinkFn2\"\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/a\u003e, amongst 29 are rural. The rural population is estimated to be around 270243 and the number of agricultural households is approximately 44000 (Hagos, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The woreda is dominantly known for rice production besides maize, finger millet, tef, onion, cattle rearing and others (Tsega, 2017). Ebenat woreda is structured by 37 kebele administrations, and 35 of them are rural. The total population of the woreda is 235,091 with 93% of rural population. Among the total population, women account for 48.74% or 114, 582. (Emewedew and Menberu, 2017) About 2.2% of the wereda population are migrants. Most of the migrants live in urban areas of the woreda, and about three/fourth of them originate from rural areas. Estie has 42 rural and 3 urban kebeles with total population of 424,041, out of which 216,329 and 207,712 are male and female respectively (CSA, 2008). The rural population size is nearly 94%. Most of the population follows the religion of Orthodox Christianity, while 2.91% are Muslims.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Study Population and Sampling Techniques\u003c/h2\u003e \u003cp\u003eThis study employed both probability and nonprobability sampling techniques. Nonprobability purposive sampling technique was used to identify the target Zone, three woredas and nine specific kebeles using prior and existing experience with DRM as main selection criteria. Based on this technique, the research focused on South Gondar as this zone has contextual and environmental setting to better address the research questions that are aimed at assessing knowledge, attitude, and practice of DRM. Using purposive sampling strategy, this study identified three woredas names Fogera, Ebenat and Estie in South Gondar Zone. These areas have a total of 929,375 population under 116 kebeles of which 106 are rural and 10 are urban. Employing the same purposive sampling technique, a total of 9 kebeles were included through applying disaster prevalence and residential characteristics as major selection criterions. Three major criterions used were known as rural highly disaster affected, semiurban less disaster affected and urban with infrequent and normal context. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e below, nine kebeles were identified with the total population of 62034 individuals and 10103 households.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStudy population by kebele\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWoreda\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKebele\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCriteria\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal Population\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHouseholds\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eFogera\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eShena\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAffected, and rural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e348\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWoreta Zuria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMixed, both rural and urban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3599\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e587\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWoreta town\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLess affected, semi/urban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3456\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSub-total\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26957\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4391\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eEste\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eZiguara\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAffected, and rural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e202\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLiwaye\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMixed, both rural and urban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e608\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMekane Eyesus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLess affected, semi/urban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15413\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2510\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSub-total\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e17263\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2811\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eEbenat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBurkoch\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAffected, and rural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4350\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e708\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAmesteya\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMixed, both rural and urban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1462\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e238\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEbinat town\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLess affected, semi/urban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1955\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSub-total\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e17814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2901\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e62034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10103\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eBased on probability strategies, multistage cluster sampling technique was employed to determine the number of households on which observation was made. Using household as a sampling frame, standard population survey formula was used to determine number of households that were included in the study. The sample size was calculated using a formula (Cochran, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1977\u003c/span\u003e) considering the total population that is more than 10,000 and significant level of variation on \u0026ldquo;P\u0026rdquo;.\u003c/p\u003e \u003cp\u003eUsing probability simple random sampling, 412 household research participants have been identified across the nine kebeles. Trained data collectors secured household list by village from the kebele administration offices, and initially marked the households in seven intervals starting from the first household on the list. The identified households have been contacted for data collection. In an event where the identified household was not available, and in a few cases where a household was not willing to provide information, the immediate next and next household have been replaced and data was collected accordingly.\u003c/p\u003e \u003cp\u003eIn addition, purposive sampling was used to identify the research participants for qualitative methods at the region, zone, woreda and kebele levels. In this regard, this study included 36 representatives of key organizations from different sectors including government and non-governmental organizations, and 28 additional research participants from academia Among the government, regional, zonal, district and kebele level staffs of the regional Disaster Prevention and Food Security Program, Agriculture Burau, Health Bureau, and Education Bureau were included.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Data Collection\u003c/h2\u003e \u003cp\u003eThis study employed both quantitative and qualitative data collection tools. The major quantitative research technique was structured disaster practice survey that was employed at different levels. Based on this, quantitative primary data was collected among 412 households at the nine kebeles, 28 academia and 36 representatives of local stakeholders. In addition, 177 research participants have involved through qualitative methods and primary information was collected using 69 KIIs, 45 IDI and nine FGDs involving 63 participants.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Data Analysis\u003c/h2\u003e \u003cp\u003eUsing a quantitative design, this study collected data through 41 structured questions that are customized into the context through three sub-topics including preparedness (17 questions), prevention (12 questions) and mitigation (12 questions). These questions are analyzed using descriptive techniques and they are used to support the major findings as presented using percentages and tabulate summaries. In addition, five close-ended and actual participation-focused (yes/no) questions were used to measure the practice levels of households. Then parametric tests were conducted to identify and test the effects of key factors on households\u0026rsquo; practice for DRM.\u003c/p\u003e \u003cp\u003eShapiro-Wilk test was conducted to determine the normality of the factors along the household practice levels with the null hypothesis that the variable is normally distributed, and this is rejected if the p-value is less than 0.05. The analysis indicated that the practice levels of research participants is not normally distributed with p value of 0.00001. Based on the findings of data normality test, this study has employed Wilcoxon-Mann-Whitney analysis to assess the influence of factors that are binary independent variables on the dependent variable of practice for DRM.\u003c/p\u003e \u003cp\u003eFor the categorical independent variables that have two and more levels, Kruskal Wallis test was conducted separately to test the influence with the dependent variable of households\u0026rsquo; DRM practice levels, which are ordinal and non-normally distributed variables with 95% of confidence level and Ho that there is significant level of difference between the groups of independent variables towards households\u0026rsquo; DRM practice levels.\u003c/p\u003e \u003cp\u003eUsing qualitative method, data was collected through KII, IDI and FGDs. Data collection was managed through briefly migrating into day-log book in the way that all information was properly documented on time and without any change from the original meaning provided by respondents. Once the data was properly collected, cross-sectional and categorical indexing was used to organize qualitative information for the use of content analysis through grounded theory approach. Data transcribing, coding and thematic development tools were used to properly prepare and analyze qualitative data.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Ethical Considerations\u003c/h2\u003e \u003cp\u003e This study fully complied with all the ethical standards throughout the whole process including data collection, analysis, presentation, and post-research periods. Prior to the starting the research, the proposal was examined by university professors, and the study was approved by the University after a detailed evaluation followed by a successful face-to-face defense. The university provided written formal letters to undertake the research. All forms of the data collection tools, and the questionnaires have been intensively reviewed by university professors and approved.\u003c/p\u003e \u003cp\u003eAt the time of collecting data, respondents and informants were provided with all the necessary briefing and informed consent was obtained from each research participant. Respondents\u0026rsquo; right not to participate and/or to reject one or more questions were respected consistently. Personal information and indicators of research participants have been kept confidential. In addition, all data collected for the study is only used for the purpose of the research, that no data was provided for third party throughout all times, and all collected data will be disposed properly once this study is concluded.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Demographic characteristics of practice survey respondent households\u003c/h2\u003e \u003cp\u003eTotal number of respondents, gender, and locations\u003c/p\u003e \u003cp\u003eA total of 412 households responded to the quantitative data collection process using disaster practice survey. Amongst, 34% were females. These households were from nine Kebeles and 31 villages with average number of 45 and 13 respondents respectively.\u003c/p\u003e \u003cp\u003eAge of research participants\u003c/p\u003e \u003cp\u003eThe mean age of the household heads was 40, with the youngest age of 20 and 76 the oldest. The mean age for male households was 41, while the mean age of female households was 39. The overall age of research participants was stratified in four age categories for the purposes of data analysis. Accordingly, 13.47% and 2.24% were youths and elderly respectively, while the majority 58.35% and 25.94% were adults between the ages of 30\u0026ndash;45, and 46\u0026ndash;65 respectively.\u003c/p\u003e \u003cp\u003eEducation level of the households\u003c/p\u003e \u003cp\u003eAmong the total households, 54.5% reported illiterate and basic literacy from informal education. Amongst, 41% are in Fogera followed by 33.5% in Estie and 25.5% in Ebenat. Kebele wise, nearly 60% of the illiterate households are concentrated in three Kebeles mainly Amestaya in Ebenat (21%), Shena in Fogera (20%) and Liway in Estie (19%). The number of research participants having university diploma, first degree and second degree increases from the rural kebeles into the semirural and the urban Kebeles.\u003c/p\u003e \u003cp\u003eReligions of the households\u003c/p\u003e \u003cp\u003eAccording to the responses, 92% of the households are reportedly Christian Orthodox followed by 7.5% Muslims and 0.5% of Christian Protestants. While the Orthodox households are dispersed across the nine Kebeles, Muslim households are concentrated in urban kebeles of Fogera Woreda (32% in Woreta town 01 kebele and 16% in Woreta Zuria kebele), and 23% others in Ebenat woreda Burkoch kebele.\u003c/p\u003e \u003cp\u003eEconomic statuses of households\u003c/p\u003e \u003cp\u003eUsing subjective self-assessment of economic status, this study found that 46% of households are middle economy that was defined as comparatively similar to others, 28% rich, 23% poor defied as below most of the community members and 3% very poor that was indicated as extremely lower economic status from the majority households in their kebeles. The study used a follow-up question to triangulate economic status through the average daily expenditure of a household could afford in Ethiopian Birr (ETB). According to their responses and based on the World Bank Group poverty and equity category brief (2020), 73% of households are below the international poverty line or below USD1.90 income per day, 16% are lower middle with less than USD3.20, 5% are upper middle economic status with more than USD3.20 per day, while the remaining 6% are in the upper midlevel economic status affording more than USD5.50 per day.\u003c/p\u003e \u003cp\u003eVulnerability to hazards\u003c/p\u003e \u003cp\u003eAccording to the responses from households, 41% are aware of the different hazards, and they perceive household vulnerabilities. Amongst the households who are not aware of vulnerabilities, nearly half (48%) are in Ebenat woreda with majority of them in Amestaya kebele followed by Shena kebele in Fogera woreda.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Demographic characteristics of stakeholders\u003c/h2\u003e \u003cp\u003eAcademia\u003c/p\u003e \u003cp\u003e A total of 28 individuals in academic institutions have participated from Bahir Dar University, Debre Tabor university Woreta campus and Debre Tabor University main campus. Among the total 28, eight were females, and 82% of the research participants have second degree education level.\u003c/p\u003e \u003cp\u003eOther stakeholders\u003c/p\u003e \u003cp\u003eA total of 36 individuals from different sectors have participated, and two were females. The majority were in Ebenat (30%), followed by Estie (28%), Bahir Dar (22%) and Fogera (19%). From these, 22 are governmental, 10 in non-governmental organizations, and the remaining four from religious institutions representing Christian Orthodox church and Muslim. Among these participants, 72% have technical working experience directly related with disaster risk management while the remaining 18% are engaged in managerial roles.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Demographic Characteristics of Qualitative Data Participants\u003c/h2\u003e \u003cp\u003eKIIs were conducted involving 69 (female, 32) participants in the regional government bodies (4 males), regional non-governmental humanitarian organizations (4, 2 females), South Gondar Zone administration (3, males), Debre Tabor University (1, male), the three woreda administrations (12, 4 females) and households at the nine kebeles (45, 26 females). In-depth interviews were organized among 45 (27, female) other participants from households across the nine kebeles (33, 22 females), three woreda governmental bodies (3, 1 female) and nine kebele administration offices (9, 4 females). FGDs were facilitated across nine kebeles involving a total of 63 participants (44, female). The participants of FGDs included the households, kebele administration offices, faith-based organizations, and youth. The average number of participants per FGD was seven.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Practice levels of households in disaster and risk management activities\u003c/h2\u003e \u003cp\u003eBased on a descriptive analysis of practice survey, 16% of the households have not been involved in any of disaster risk management activities at the community level followed by 28% who reported a very-low level of practice. As presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, households in Fogera constitute 50% of the total households who have below the mid-level of practices. The mean of the total practice levels for three woredas is 1.97, while Estie has the highest mean (2.42) followed by Ebenat (1.79) and then Fogera (1.72).\u003c/p\u003e \n\u003cp\u003e\u003cimg 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\" width=\"584\" height=\"188\"\u003e\u003c/p\u003e\n\u003cp\u003ePreparedness\u003c/p\u003e \u003cp\u003eBased on the responses, 80.5% of households did not participate in any disaster preparedness and risk early warning activities. In addition, 71% of research participants indicated that they do not have community disaster management plan. However, 48% of the respondents indicated the existence of informal and indigenous risk management practice at their communities.\u003c/p\u003e \u003cp\u003ePrevention response\u003c/p\u003e \u003cp\u003eAlthough 80% of the households reported their willingness to participate in disaster prevention, 61% have not been involved in any activities aimed at preventing a risk. In support of this, 82% of the respondents revealed the inexistence of disaster or risk and hazard prevention structure at their community. The other respondents who reported the availability of disaster structure were asked their membership, and 96% indicated that they are neither members nor actively involved.\u003c/p\u003e \u003cp\u003eMitigation\u003c/p\u003e \u003cp\u003eAlike the disaster prevention, around 84% of the households indicated their willingness to participate in disaster mitigation activities within their community but it is 36% of them who have reported actual participation in relevant roles. In addition, 31% of the households supported the existence of defined roles and responsibilities to mitigate disasters in their communities.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.5. Factors affecting households\u0026rsquo; DRM practices and activities\u003c/h2\u003e \u003cp\u003eThe households and the other research participants representing academia and stakeholders were asked to identify the different factors influencing disaster practices among the communities in Ethiopia. Based on the preliminary research hypothesis and the responses from research participants, a total of eight factors were identified as the underlying factors affecting households\u0026rsquo; disaster and risk management practices. The factors, also referred to independent variables, are age, location, gender, education status, religion, economic status, indigenous disaster management experience, and awareness of vulnerabilities. Among these, five independent variables have been stratified and analyzed in different groups for triangulation purposes and to minimize bias from self-reported data. In this regard, Age has been used as a continuous variable (as responded by each household) as well as categorical variable after stratified in four age groups separately. Education status has been stratified in binary variable (literate and illiterate), as well as categorical variable along the five levels of education that were used to collect primary data (none-basic literacy, 12 complete, diploma, university degree and second degree).\u003c/p\u003e \u003cp\u003eLikewise, economic status has been analyzed as categorical variable using the self-assessment data from households (very poor, poor, midclass/regular, and rich) and the average daily expenditure that a household can afford (1-50ETB, 51-150ETB, 151-300ETB, 301-500ETB, and 500\u0026thinsp;+\u0026thinsp;ETB). In addition, household risk awareness or perception of vulnerability has been stratified as a binary variable (yes/no) and categorical (yes, no and I don\u0026rsquo;t know any risk/vulnerability). Location has been analyzed at two levels, by Woreda (the three) and Kebele (nine Kebeles).\u003c/p\u003e \u003cp\u003e \u003cb\u003eSex/Gender\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe Mann - Whitney test on gender indicated no statistically significant difference between the male and female headed households for disaster practice levels (z\u0026thinsp;=\u0026thinsp;0.222, P\u0026thinsp;=\u0026thinsp;0.8240). To determine the actual difference, the rank with sums was compared with the expected, which indicated that the sum of males\u0026rsquo; rank was slightly higher than females (m\u0026thinsp;=\u0026thinsp;207, and f\u0026thinsp;=\u0026thinsp;204).\u003c/p\u003e \u003cp\u003e \u003cb\u003eRisk awareness and indigenous disaster management activities\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe same test was conducted to see if the households\u0026rsquo; awareness of vulnerability is different for their practice levels in disaster management activities. The result indicated no statistically significant difference between risk awareness and DRM practice of households (z\u0026thinsp;=\u0026thinsp;1.764, P\u0026thinsp;=\u0026thinsp;0.0778). The rank sum comparison showed that households who have no risk information have higher level of practices than those who are aware of certain hazards.\u003c/p\u003e \u003cp\u003eThe analysis between households who have indigenous disaster and risk management practices, and the others who reported no such experiences showed no statistically significant difference (z\u0026thinsp;=\u0026thinsp;1.424, p\u0026thinsp;=\u0026thinsp;0.1545). However, the average rank sum of households is higher for those who have indigenous practices (n\u0026thinsp;=\u0026thinsp;195, actual total rs\u0026thinsp;=\u0026thinsp;41429.5) compared to others who do not have any indigenous risk management experiences (n\u0026thinsp;=\u0026thinsp;212, actual rs\u0026thinsp;=\u0026thinsp;41598.5).\u003c/p\u003e \u003cp\u003e \u003cb\u003eEducation status and disaster practices\u003c/b\u003e \u003c/p\u003e \u003cp\u003eA Mann - Whitney test conducted using stratified education levels of households indicated no statistically significant difference between the literate and illiterate for disaster practice levels (z = -0.109, p\u0026thinsp;=\u0026thinsp;0.9135). The comparison of the average actual and expected rank sum is almost the same between the illiterate (204) and literate (205) households.\u003c/p\u003e \u003cp\u003e \u003cb\u003eAge of the households\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAccording to the Kruskal Wallis test using the stratified age groups and DRM practice, there is no statistically significant difference between the different age groups at a p value of 0.6675 with ties and 0.6841 without ties. Meanwhile, the rank sum with the corresponding number of observations indicated that households between 66\u0026ndash;76 ages have higher level of DRM practice with average rank sum of 211.5, followed by a 206 average rank sum of the households in the 30\u0026ndash;45 age group. The minimum average rank sum is 190 among the households aged 46\u0026ndash;65 compared to 196 within the youngest.\u003c/p\u003e \u003cp\u003e \u003cb\u003eReligions of the households\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe difference within the religion types and DRM practices of households was analyzed using Kruskal Wallis. This test indicated no statistically significant difference among the Orthodox Christians, Muslims and Protestant Christians for the DRM practice at a p value of 0.0809 without ties and 0.0720 with ties. However, rank sum suggested that disaster practice is higher among Protestant Christians compared to the Orthodox Christians and the least within Muslims.\u003c/p\u003e \u003cp\u003e \u003cb\u003eEducation levels of the households\u003c/b\u003e \u003c/p\u003e \u003cp\u003eLikewise, the same test indicated no statistically significant difference within the various levels of education and the DRM practice at a p value of 0.5331 with ties and 0.5563 without ties. The average actual rank sum of a household who has masters\u0026rsquo; degree is the highest (404.5), followed by households who have diploma (208), and then those households who do not have formal education level (204). The average actual rank sum of households who have first degree is the lowest (201.6) followed by those 12th grade complete (202).\u003c/p\u003e \u003cp\u003e \u003cb\u003eEconomic status of the households\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAccording to the results of a Kruskal Wallis test, there is a statistically significant level of difference within households\u0026rsquo; economic status and the DRM practices at p\u0026thinsp;=\u0026thinsp;0.0406 with ties and 0.0482 without ties. The average rank sum of households who reported economically very poor has been the highest (n\u0026thinsp;=\u0026thinsp;14, rank sum\u0026thinsp;=\u0026thinsp;3649) followed by those who reported economically rich (n\u0026thinsp;=\u0026thinsp;111, rs\u0026thinsp;=\u0026thinsp;23507), and those who reported regular (n\u0026thinsp;=\u0026thinsp;184, rs\u0026thinsp;=\u0026thinsp;36951.5) with the lowest being among economically poor households (n\u0026thinsp;=\u0026thinsp;92, rs\u0026thinsp;=\u0026thinsp;16493.5).\u003c/p\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, the analysis on households\u0026rsquo; average daily expenditure has also indicated statistically significant difference within the groups and the practice levels of DRM at p\u0026thinsp;=\u0026thinsp;0.0087 with ties and 0.0113 without ties.\u003c/p\u003e \u003cp\u003e\u003cimg 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\" height=\"355\" width=\"584\"\u003e\u003c/p\u003e\u003cp\u003eThe result indicated a difference with the findings of households\u0026rsquo; self-economic assessment where households with highest daily expenditure have lowest rank sum (n\u0026thinsp;=\u0026thinsp;23, rank sum\u0026thinsp;=\u0026thinsp;3540) followed by the low expenditure group ETB51-150 (n\u0026thinsp;=\u0026thinsp;145, rs\u0026thinsp;=\u0026thinsp;28063.5) and then the very low expenditure group ETB1-50 (n\u0026thinsp;=\u0026thinsp;155, rs\u0026thinsp;=\u0026thinsp;31229.5). The highest rank sum was among households with average daily expenditure of ETB301\u0026ndash;500 (n\u0026thinsp;=\u0026thinsp;19, rs\u0026thinsp;=\u0026thinsp;4830) followed by the mid-expenditure households ETB151-300 (n\u0026thinsp;=\u0026thinsp;64, rs\u0026thinsp;=\u0026thinsp;14958).\u003c/p\u003e \u003cp\u003e \u003cb\u003eLocations of the households\u003c/b\u003e \u003c/p\u003e \u003cp\u003eKruskal - Wallis test using woredas indicated statistically significant difference within the three woredas and the households\u0026rsquo; practice levels for DRM at a p value of 0.0001 with both ties and without ties. The test also suggested that households in Fogera have lowest average rank sum compared to households in Ebenat and the highest in Estie.\u003c/p\u003e \u003cp\u003eAs presented in the Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e below, the test using kebeles similarly revealed a statistically significant difference within the nine kebeles and the households\u0026rsquo; practice levels of DRM practices at p value 0.0001 for both with ties and without ties.\u003c/p\u003e \u003cp\u003e\u003cimg 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\" height=\"447\" width=\"584\"\u003e\u003c/p\u003e\u003cp\u003eAmong the three highest rank sums, two are urban kebeles (Ebenat town 01 kebele and Mekane Eyesus kebele. The least rank sum was also within the rural kebeles mainly in Burkoch kebele, followed by Woreta Zuria and Shena kebeles both in Fogera woreda.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.6. Strength, limitations, and opportunities of disaster management practices\u003c/h2\u003e \u003cp\u003eBased on responses from 412 households across three woredas and nine kebeles, key strengths of current DRM practices include positive community attitudes (41%) and the support of faith-based organizations, particularly the Orthodox Church and mosques (38%), which contribute to awareness and recovery efforts. Additionally, 32% of households recognized the importance of natural resources, such as land and water, in enhancing DRM effectiveness. Other strengths identified include local government support (31%), community-based planning (29%), and strong NGO involvement (24%).\u003c/p\u003e \u003cp\u003eAcademics highlighted NGO and humanitarian agency engagement (75%) and the role of faith-based organizations (36%) as major strengths. However, 100% of academic respondents disagreed that policy, gender equality, and community attitudes were strengths. Local stakeholders similarly pointed to positive community attitudes (50%), effective policy and regulation (42%), and NGO support (36%) as top strengths.\u003c/p\u003e \u003cp\u003eThe main limitations identified by households were financial constraints (66%), lack of timely government support (64%), and ineffective DRM activities (50%). Other issues included insufficient coordination, policy gaps, and low community awareness. The least impactful challenges were the influence of faith-based organizations and harmful traditional practices. Academics ranked low government support (82%) and weak planning and implementation (82%) as the most significant limitations, while local stakeholders similarly pointed to resource shortages (72%) and hastily implemented DRM activities (61%) as top issues. Qualitative findings from key informants also identified poor structural capacity at local levels, insufficient resources, and weak DRM quality, characterized by unqualified personnel, untimely actions, and corruption.\u003c/p\u003e \u003cp\u003eHouseholds identified the availability of natural resources (58%), human labor (53%), and community commitment to DRM (46%) as the main opportunities. NGOs and humanitarian organizations were seen as moderately supportive (32%). However, financial resources and government support were viewed as less significant opportunities. Academics and local stakeholders echoed the importance of NGO and humanitarian support, labor availability, and natural resources, while also pointing to the potential for increased community engagement and awareness as key opportunities for improving DRM.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.7. The roles and responsibilities of households in DRM practices\u003c/h2\u003e \u003cp\u003eRoles and responsibilities of households during disaster preparedness\u003c/p\u003e \u003cp\u003eQualitative insights from KII, IDI and FGDs highlighted several common roles and responsibilities for households. These include active participation in planning processes and meetings, direct involvement in hazard, vulnerability, and risk assessments, engagement in disaster preparedness planning, resource mobilization both in-kind and in cash, running community-owned early warning activities, and participation in regular follow-up and review sessions. While all groups agreed on these roles, their implementation varied. Academics generally noted that these responsibilities are often not practical across kebeles. Local stakeholders suggested that these responsibilities are shared with households, yet many households disagreed, feeling they do not play significant roles in these areas.\u003c/p\u003e \u003cp\u003eUsing quantitative descriptive analysis on the responses from 36 representatives of local stakeholders and 28 academia, the major roles and responsibilities of households include hazard and vulnerability assessment (82%), active participation in disaster preparedness planning (82%), local resource mobilization (64%), and joint risk assessment (61%).\u003c/p\u003e \u003cp\u003eIn the other side of the 412 households, 87% reported the absence of disaster preparedness plan. Of those with a reported DRM plan, 92% did not participate in its development. When asked about disaster response structures, 90% indicated there was no established committee for planning and responding to disasters. Among those who noted the presence of such structures, 97.6% reported having no role in the committees. Additionally, only 14% of households confirmed regular kebele and woreda meetings to discuss disaster preparedness and review DRM progress, with nearly 95% stating they did not attend these meetings.\u003c/p\u003e \u003cp\u003eRegarding early warning systems, 31% of households acknowledged existence of different mechanisms to communicate risks among their localities. However, 61% were unaware of who manages these activities, and only 2.43% had roles in the early warning systems. To gauge households' readiness for disaster response, participants were asked if they knew their responsibilities during a disaster; 50% indicated they did not.\u003c/p\u003e \u003cp\u003eRoles and responsibilities of households during disaster prevention\u003c/p\u003e \u003cp\u003eQuantitative data from local stakeholders and academics indicated several key responsibilities for households during disaster prevention. Self-preparedness was highlighted as essential by 100% of respondents, while 64% indicated participation in actual prevention activities. Additionally, 61% noted the importance of hazard identification and planning for prevention activities, and 57% emphasized the need for monitoring prevention efforts. Joint risk assessment was acknowledged by 43% of respondents. The data also highlighted the roles households play in supporting affected individuals, primarily through resource mobilization and rehabilitation services, with 39% identifying these contributions. Despite this, most households, approximately 69%, did not perceive themselves as having defined roles. Qualitative responses varied, with participants in areas like Shena and Woreta Zuria noting their contributions through labor and in-kind assistance.\u003c/p\u003e \u003cp\u003eRoles and responsibilities of households during disaster mitigation\u003c/p\u003e \u003cp\u003eBased on the responses from academics and local stakeholders\u0026rsquo; disaster mitigation roles of households included preparing for mitigation, with 75% of respondents acknowledging its importance, and participating in mitigation planning sessions, which 57% confirmed. Implementing mitigation activities was noted by 61% of participants, while 57% emphasized resource mobilization for mitigation responses and supporting reintegration and rehabilitation interventions. Community follow-up was similarly highlighted by 57% of respondents.\u003c/p\u003e \u003cp\u003eDespite this, a significant number of households, approximately 65%, felt they lacked clearly defined roles in community disaster mitigation efforts. However, 14% of households indicated that their contributions, including labor, in-kind materials, and financial support, constituted their main roles in this area, with 8% emphasizing the importance of awareness creation in mitigation responses.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.1. The practice levels of households in disaster and risk management activities\u003c/h2\u003e \u003cp\u003eThe practice for disaster risk management comprises the efforts and activities carried out in the context of disaster prevention, mitigation, preparedness, emergency response and recovery, which are performed before, during and after a disaster (Kyooman, 2020). Households play important role over the key phases of disaster management mainly preparedness, mitigation, and preventive response (Kar 2016). Several empirical studies have assessed the DRM practices of different key stakeholders including households, emergency responders, health workers and students. For instance, Shanableh et.al (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) found that the overall disaster practice levels of health professionals through descriptive analysis of median and concluded that health workers have high level of readiness for disaster practice. Najafi et.al (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) similarly measured the DRM practice levels of Nepalese immigrants in Japan and reported that more than 70% were unable to perform some preventive practices against natural hazards.\u003c/p\u003e \u003cp\u003eDespite the common understanding on the significance of preparedness, prevention and mitigation, the participation of key stakeholders within this key practice involves various situations. According to this study, not more than 20% of the households across the three woredas and nine kebeles have disaster preparedness practice. In addition, only 39% of the households mentioned their involvement in disaster prevention activities while less than 35% reported participation in disaster mitigation practices. Among the total research participants, including 13% who reported the availability of preparedness plan, 92% were not involved in any of the preparedness planning processes. In addition, nearly 70% of the research participants reported that they are not engaged in disaster early warning practices. In the assessment of personal early warning readiness, most households (55%) do not have important equipment to be prepared including radio, mobile phones, and emergency tools. In other areas like Nepal, people seek information about hazards from mass media, and some from community outreach programs. According to Nepal Earthquake Preparedness for Safer Communities (NEPSC) (2013), more than 50% of community members use mobile as communication tool. In addition, only a small portion of the households had prepared plans and organized pre-arranged meeting points.\u003c/p\u003e \u003cp\u003eNEPSC (2013) reported that 87.6% of households practice special committee for disaster preparedness. According to the REACH survey report (2015), it was only 6% of people in India rural areas reported the existence of a disaster management plan (DMP). In addition, the presence of community-level disaster management systems is extremely sparse and only 13% of people reported that their community has a disaster management committee, and 5% have taken part in a disaster preparedness activity. According to Suryadi et al. (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), 88% of research participants understand that disaster preparedness was an activity carried out to anticipate disasters through appropriate and efficient steps.\u003c/p\u003e \u003cp\u003eIn terms of prevention and mitigation, the REACH survey (2015) reported that communities are involved in mitigation activities, and they believe on roles to reduce the effects of disasters. Accordingly, 32% of households reported awareness-raising, followed by the 32% planting and rehabilitating forests, and others indicating flood mitigation and related undertakings. However, prevention and mitigation practices are different compared to the findings of this study, which 64% of households reported that their community does not have defined roles and responsibilities for both prevention and mitigation practices.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e4.2. Factors influencing households\u0026rsquo; practices in DRM activities\u003c/h2\u003e \u003cp\u003e \u003cb\u003eLocation by woreda\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThis study found that households in Fogera have lowest level of DRM practices followed by Ebenat, and the highest in Estie. This implies that the households that are in disaster prone areas like Ebenat and Fogera have lower levels of practices compared to the areas that are less prevalent to disasters. In this view, Mostafizur et.al., (2023) found that research participants living outside the urban areas of Dhaka have higher levels of practices to prevent COVID-19 than others living in semi-urban and urban cities.\u003c/p\u003e \u003cp\u003e \u003cb\u003eLocation by kebele\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThis study revealed that all the urban kebeles have high levels of disaster management practice except Woreta town 01 kebele. Disaster affected and rural kebeles have the lowest levels of practices with an exception to Zigura kebele in Estie. The communities in rural and disaster-affected areas are known to participate in different types of disaster management activities. During the KII and FGDs, the households in Sehna and Woreta Zuria discussed about the flood mitigation, forestation, and improved farming activities that they undertake to prevent the effects of disasters. However, the finding of practice survey is different from showing what the households discuss in FGDs and KII. In addition, the households in urban kebeles have more access to information and psychological readiness, which might contribute to overall aptitude than actual practice.\u003c/p\u003e \u003cp\u003e \u003cb\u003eEconomic status\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAccording to results of this study, economically very poor households have very high level of participation in DRM activities. Economically mid-class households have the next higher and mid-level of engagement within risk management.\u003c/p\u003e \u003cp\u003eHouseholds with highest amount of daily expenditure have lowest levels of practices in DRM. The households who are affording the midlevel expenditure amounts have also lower level of practice but much higher than those who are affording highest expenditure. In comparison, the high level of DRM activities is practiced among households who can afford the middle expenditure levels. Therefore, the DRM practice and participation is higher among the households who have middle level economic status followed by the poor. The disaster management practice is very low for the households who have uppermost income or those who have the highest economic status.\u003c/p\u003e \u003cp\u003eIn studies like Mostafizur et.al., (2023), individuals who have the highest level of economic status showed highest level of DRM practices during disasters like the outbreak of COVID-19 pandemic. However, the continuous level of engagement in DRM activities is low among this groups, which midclass and poor are often involved in many countries. During the FGDs with academia and representatives of local stakeholders, this point was echoed where participants indicated that households who have highest income levels participate in DRM activities when there is active disaster (during disaster) than preparedness. They are also characterized as detached from the wider community during preparedness and preventions, which they intend to focus and invest more on ensuring their own protection than working with the communities for collective disaster management results.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSex/Gender\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThis study found no difference between males and females for their practices in disaster and risk management activities. Since most research participants are in rural and semi-urban areas where female households share farming, agricultural, livestock and environmental responsibilities with the male households, the situation is likely. In support of this, Shanableh et.al (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) reported that the overall DRM practice levels of women was 39 compared to the men 41. This study conducted Mann \u0026ndash; Whitney test and reported that there was no statistically significant difference between men and women (p\u0026thinsp;=\u0026thinsp;0.064) for their readiness and practice against disasters.\u003c/p\u003e \u003cp\u003e \u003cb\u003eReligion\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe difference between religion groups for the DRM practice levels of households indicated no statically significant difference among the Orthodox Christians, Muslims, and Protestant Christians. However, Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows the descriptive analysis of means and it revealed that the disaster management practice levels is higher among the Orthodox Christians than the Protestant Christians and the least of Muslim households.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMean of DRM practice by religion\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e.tabulate of Religion, summarize (Practice Level of Respondent)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eReligion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eSummary of the respondent practice\u003c/p\u003e \u003cp\u003elevel in 0\u0026ndash;5 scale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStd. Dev.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFreq.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOrthodox\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.0212766\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.4045923\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e376\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMuslim\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.4516129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.3376275\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProtestant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.9779951\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.4027301\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e409\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn terms of preparedness, 13% of Christian Orthodox households, and 12.9% of Muslims have actively participated, while none of the Christian Protestants engaged in this activity. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, 37.5% of Christian Orthodox and 58% of Muslims have been involved in disaster prevention activities. Regarding mitigation, 34% of Christian Orthodox households and 61% of Muslims reported their participation in their community, except Christian Protestant households.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDRM prevention participation by religion\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e.tabulate Religion DisasterPreventionParticipation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eReligion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c7\" namest=\"c3\"\u003e \u003cp\u003eHave you ever participated in preventing a forecasted disaster?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eI don\u0026rsquo;t k\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eFreq.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOrthodox\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e377\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMuslim\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProtestant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e130 120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e410\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn the practice survey, the Christian Protestant households have responded much better than both the Orthodox and Muslim households. The likelihood reason behind the increased result of DRM practices among these households could relate to access for information that contributed to respond for the KAP survey questions. Therefore, this is one of the potential areas for further studies and scientific research in the future.\u003c/p\u003e \u003cp\u003e \u003cb\u003eEducation status\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe practice levels of disaster management activities have statistically no significant difference within the education levels of households. However, this study also found that households with the highest educational level of masters\u0026rsquo; degree and then the diploma or TVET graduates have higher level of DRM practices. Most of the households who are illiterate, basic literacy and numeracy have comparatively high practices than the households with first degree and others who are 12th grade complete who have the lowest levels of practices in DRM activities.\u003c/p\u003e \u003cp\u003eAccording to Fatmah (2023), a higher education facilitates better information absorption, which impacts the level of knowledge. This knowledge and awareness will influence how the people deal with disaster situations before, during and after a disaster. Therefore, involving individuals particularly older adults in regular training positively influence the DRM practice and preparedness. In a study that assessed the climate adaptation practice of households in South Gondar zone, Beletech et.al, (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) reported that of lack of information and knowledge negatively affected households who failed to take adaptation measures against climate change.\u003c/p\u003e \u003cp\u003e \u003cb\u003eAwareness of vulnerability and risk information\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAccording to the practice survey, there is no statistically significant difference for disaster practice among households who have vulnerability awareness and other households who do not have this information. Meanwhile, the results indicated that the overall DRM practice levels of households who have vulnerability awareness is lower than households who do not have risk and vulnerability information. This is mainly due to the situation that most of the DRM practices in the target areas lack to integrate vulnerability and risk information with households\u0026rsquo; participation within DRM activities. Even though some areas like Shena and Worera Zuria in Fogera, and Amestaya in Ebenat have information on hazards including flood, and drought respectively, the households are not supported to internalize the risk information in a way that they actively participate during DRM practices.\u003c/p\u003e \u003cp\u003eAnother reason is lack of accurate information on vulnerabilities and risk information. In this regard, the households in the nine kebeles have wide range of perception on their vulnerabilities. For instance, more than 60% of the households reported that they have faced at least 3 hazards and the related consequences of disasters in the areas. In the identification of the hazards, most of the households commonly agree a few hazards are not the case such as 74% of the total households reporting that COVID-19 is not a risk across the areas. In other cases, there are hazards that have majority support such as communal conflict that a total of 71% households report as a significant risk across most of the kebeles including urban areas like Woreta town.\u003c/p\u003e \u003cp\u003eLikewise, more than 84% of the households across the nine kebeles and three woredas perceive flood as a threatening hazard, which 45% of the households identified it as highly prevalent risk. The kebeles who have identified this hazard as a major risk and vulnerability include urban areas such as Ebenat and Woreta town kebeles. So long the hazard and risk information are not supported to reflect the context, and are not integrated in community actions, awareness of vulnerability by itself hardly makes difference within the DRM practice levels of households.\u003c/p\u003e \u003cp\u003e \u003cb\u003eIndigenous DRM practices\u003c/b\u003e \u003c/p\u003e \u003cp\u003eEven though experience with different types of indigenous DRM activities has no statistically significant difference, this study found that households who are engaged in the indigenous practice have higher level of practice than other households who have no indigenous practices. In a descriptive analysis, the participation of households who have indigenous DRM practices is consistently higher than others in early warning, disaster preparedness, prevention, and mitigation activities. As presented in Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e, among the total households involved in DRM planning, 59% are households that have indigenous practices in their communities.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDRM plan by ingenuous practices\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e.tabulate IndigenousDRM Practices DRM Plan\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eDo you have Indigenous DRM Practice\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eDo you know DRM Plan?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e196\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI don\u0026rsquo;t know\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e287\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e408\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFrom the total households who reported having early warning responsibilities, 63% are the households involved in indigenous practices. Likewise, 67%, and 68% of the total households involved in disaster prevention and mitigation are the households that have experiences in the indigenous DRM undertakings. Therefore, the active participation of households in DRM practice is evident than other households who have no experience of indigenous DRM activities. In support of this as shown in Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e, the overall DRM practice mean is highest among households who have indigenous practices (2.08) than others who do not have such experience (1.81) and the remaining uncertain households (1.92).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDRM mitigation participation by indigenous practices\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"13\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"13\" nameend=\"c13\" namest=\"c1\"\u003e \u003cp\u003e.tabulate IndigenousDRM Practices MitigationParticipation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eDo you have Indigenous DRM Practice\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c9\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c13\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c9\" namest=\"c3\"\u003e \u003cp\u003eHave you ever participated in mitigating disaster and its consequences\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c13\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eI don\u0026rsquo;t k\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c13\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c12\" namest=\"c9\"\u003e \u003cp\u003e196\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c12\" namest=\"c9\"\u003e \u003cp\u003e143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI don\u0026rsquo;t know\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c12\" namest=\"c9\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e137 125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c11\" namest=\"c9\"\u003e \u003cp\u003e404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \n\u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e\n\u003cp\u003eHouseholds aged 66\u0026ndash;76 have higher level of disaster management practice, followed by the 30\u0026ndash;45 age groups. While the young group within 18\u0026ndash;29 has lower level of practice, the older adult aged 46\u0026ndash;65 have the lowest level of participation in DRM activities. In support of this, Shanableh et.al (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) revealed that the total score for practice was higher among health professionals over the age of 50 years (44, 38\u0026ndash;44) than the young group (42, 34\u0026ndash;44) and the adults between 26\u0026ndash;50 (39, 33\u0026ndash;44). However, the overall result indicated no statistically significant difference between the age group and total practice score (p\u0026thinsp;=\u0026thinsp;0.14). Nevertheless, Fatmah (2023) reported that efforts are required to improve older adults\u0026rsquo; preparedness for disasters through involving them or their family members in regular training and seminars and by updating knowledge and information accessible for them. In addition, the REACH (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) survey suggested that women over 60 are less likely to view DRM as a priority, and less likely to feel involved in household or community-level disaster preparations. Even though other empirical studies indicated this age group as highly vulnerable that seeks the support from others, this study consistently revealed that the elders have higher level of knowledge, attitudes, and practices.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e4.3. The strengths and limitations of DRM practices\u003c/h2\u003e \u003cp\u003eThe research participants identified several key strengths in disaster risk management (DRM). These include a positive attitude towards DRM and constructive traditional practices that enhance the effectiveness of various activities. Faith-based organizations, particularly the Orthodox Christian Church and Mosques, provide vital support in awareness creation and recovery assistance. Additionally, a conducive environment with accessible natural resources, local government support, community-based planning and implementation, and strong backing from non-governmental organizations (NGOs) contribute positively to DRM efforts.\u003c/p\u003e \u003cp\u003eWeak support from government bodies, particularly at the kebele level, and insufficient financial resources pose significant challenges. Other issues include limited technical knowledge and skills, inconsistent engagement, negative perceptions among some households, and a lack of strong agencies for coordinated household engagement. In areas like Shena and Woreta Zuria, participants acknowledged government involvement in DRM but also highlighted issues such as untimely responses, corruption, and inadequate government actions related to disaster management.\u003c/p\u003e \u003cp\u003eAccording to Petros and Neng (2021), community participation in formal disaster risk planning is underdeveloped, and there is a pressing need for a shift from emergency responses to risk reduction initiatives. Engaging the private sector is also a critical area that requires improvement. While there have been policy-level achievements, creating resilient communities during disasters demands greater effort. Policies must ensure that lives and livelihoods are safeguarded, aligning with sustainable development goals.\u003c/p\u003e \u003cp\u003eStudies by Aaron (2013) and Mulugeta (2010) highlighted common limitations, such as low levels of information on vulnerabilities and coping mechanisms, reactive disaster management approaches, inadequate inter-sector coordination, and challenges in decentralized planning and budgeting. Sheganew et al. (2022) noted that DRM policy provisions lack enforcement and accountability, leading to an unresponsive system. Furthermore, traditional reliance on emergency assistance and food aid, coupled with insufficient investment in building resilient households, presents ongoing challenges.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e4.4. The roles and responsibilities of households in disaster risk management\u003c/h2\u003e \u003cp\u003eThe study identified several key roles and responsibilities for households in DRM. These include preparing for mitigation activities, participating in disaster mitigation planning sessions, implementing mitigation strategies, mobilizing resources for responses, supporting reintegration and rehabilitation efforts, and engaging in community follow-up. Households reported that their responsibilities include providing labor, in-kind material support, financial contributions, and raising awareness.\u003c/p\u003e \u003cp\u003eHowever, over 65% of participants indicated they lack clearly defined roles in DRM, particularly in preparedness, prevention, and mitigation phases. Quantitative data and feedback from key informant interviews (KII) and focus group discussions (FGD) confirm this lack of clarity. This finding aligns with the REACH KAP report (2015), which noted that 42% of participants were unaware of their responsibilities during disasters. This confusion undermines the efficiency of responses and accountability among actors.\u003c/p\u003e \u003cp\u003eNumerous studies emphasize the foundational role of households and communities in DRM, advocating for community-based practices. Few et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) assert that communities should lead disaster preparedness efforts, including establishing preparedness plans, enhancing communication, and raising public awareness about mitigation strategies. Communities must analyze their hazards, vulnerabilities, and capacities.\u003c/p\u003e \u003cp\u003eEbinezer (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) outlined five levels of community responsibility in DRM, including informing members about available services, consulting on issues, being accountable for decisions, facilitating collective decision-making, and managing service delivery. Kiranjot (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) emphasized that communities can collaboratively analyze threats, capabilities, vulnerabilities, and risks by integrating local and scientific knowledge. Essential elements of this process include creating disaster management plans, forming disaster management committees and teams, raising awareness, training, and establishing contingency funds.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eHousehold engagement in disaster management activities remains critically low, with only 34% of research participants involved in risk management practices. The most concerning is preparedness, where just 20% of households are participating in activities aimed at mitigating risks and vulnerabilities. This indicates a significant gap in disaster preparedness, compounded by a lack of involvement in community-based structures and low participation in available committees.\u003c/p\u003e \u003cp\u003eDespite the overall low engagement, households show slightly higher participation in prevention efforts compared to preparedness and mitigation. When comparing participation by woreda, households in Estie are most engaged in DRM practices, followed by Ebenat, while those in Fogera are the least involved. At the kebele level, higher levels of engagement are observed in Ziguara, Ebenat Town 01, and Mekane Eyesus 01 kebeles, compared to Burkoch, Woreta Zuriya, and Ametasya kebeles. This suggests that DRM practices are more prevalent in urban kebeles, particularly those less affected by recurrent disasters.\u003c/p\u003e \u003cp\u003eDemographic factors influence participation where males engage more than females, Orthodox Christians are more active than Muslims and Protestants, and literate households participate more than illiterate ones. Households informed about their vulnerabilities show more involvement, as do those engaged in indigenous DRM activities. Additionally, older adults and elders participate more than youth, while economically disadvantaged households display higher levels of DRM practice.\u003c/p\u003e \u003cp\u003eThe strengths of disaster management practices include a positive attitude toward DRM, constructive traditional practices, support from faith-based organizations (notably the Orthodox Christian Church and Mosques), a conducive environment, access to natural resources, community awareness, and engagement from NGOs and humanitarian agencies. However, challenges persist, including weak government support at the kebele level, limited financial resources, inadequate technical knowledge and skills, inconsistent engagement, negative perceptions among some households, and a lack of a strong agency to coordinate household involvement.\u003c/p\u003e \u003cp\u003eMost households take on roles related to preparing their families for mitigation activities, participating in disaster mitigation planning, implementing mitigation strategies, mobilizing resources, and supporting rehabilitation efforts. Common responsibilities include providing labor, in-kind material support, financial contributions, and raising awareness. Although many households express a willingness to participate in DRM practices, they often lack clearly defined roles and responsibilities in preparedness, prevention, and mitigation efforts.\u003c/p\u003e"},{"header":"6. Implications","content":"\u003cp\u003eDisaster risk management practices and household involvement in related activities are notably low across the three woredas, particularly in rural areas frequently affected by hazards. Preparedness emerges as a significant concern among research participants. Therefore, efforts should focus on strengthening existing preparedness practices and establishing new ones throughout the three woredas, prioritizing rural kebeles in Fogera, Ebenat, and Estie in that order.\u003c/p\u003e \u003cp\u003ePreparedness activities should center on mobilizing households for hazard, vulnerability, and risk assessments. This includes actively engaging households in disaster preparedness planning processes, establishing and enhancing kebele level early warning systems, and creating community owned disaster preparedness structures and committees. Over 88% of households express a willingness to participate in DRM practices, including prevention and mitigation activities. However, it is crucial to intentionally target, mobilize, and engage households with low income, as well as those with higher economic status, in DRM efforts.\u003c/p\u003e \u003cp\u003eThe strengths of current DRM practices should be further enhanced through a selective approach at the household, community, and system levels. At the system level, reinforcing policies and maintaining DRM structures at the regional, zonal, and woreda levels are strategic actions for advancing DRM more effectively. Policy reviews should be evidence-based, with actions aimed at maximizing policy efficacy. One key area for improvement is to shift the focus from the traditional emergency response model to preparedness and knowledge-building. The policy should reinforce the integration of basic DRM engagement within community members.\u003c/p\u003e \u003cp\u003eAnother critical area for policy review is establishing accountability for DRM among households and local key actors, including the private sector and academia. Participation in DRM should not be optional for households, government bodies, private sectors, academia, and community-based organizations. The Ethiopian community-based health insurance scheme can serve as a valuable example of promoting local ownership and accountability in DRM.\u003c/p\u003e \u003cp\u003eAt the household and community levels, the involvement of NGOs and humanitarian organizations has been a strength. Traditional and religious DRM response activities such as the emergency bell ringing by the Orthodox Church and the initiatives of Muslim communities should be adapted into more effective community-owned practices during disaster prevention and mitigation phases. Promoting community-owned DRM is essential, which households must be engaged continuously before, during, and after disasters. The roles and responsibilities of households should be clearly defined and mutually agreed upon within communities.\u003c/p\u003e \u003cp\u003eThe current emergency focused and resource-centered disaster practice approach should gradually transition to a holistic and sustainable disaster risk management process, supported by local resources and accountability at the grassroots level.\u003c/p\u003e"},{"header":"7. Limitations","content":"\u003cp\u003eThis study involves limitations associated with the use of self-reported data, analysis techniques and data normality. In terms of the increased use of self-reported data, the study has employed different strategies to mitigate potential bias. This was through triangulation using secondary data and collecting more information about the same independent variable. For instance, age was analyzed in a range of four groups as well as individually along respondents. The self-reported economic status was triangulated using average daily expenditure the household can afford, and education status has been analyzed in similar two strategies. The use of multivariate analysis may enhance the results showing the relationships between independent and outcome variables more clearly. This study did not employ multivariate analysis due to data nonnormality. Additional studies are recommended to address this potential gap in the future.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eTemesgen Alemu Tilahun: Writing \u0026ndash; original draft, Validation, Software, Resources, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization. Abraham Mebrat Asmare: Writing \u0026ndash; review \u0026amp; editing, Validation, Supervision, Methodology. Tesfahun Asmamaw Kassie: Writing \u0026ndash; review \u0026amp; editing, Supervision, Software, Methodology.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbhinav S, Pal DK, Kasar PK, Tiwari R, Sharma A. (2008). Knowledge, attitude and practice of disaster preparedness and mitigation among medical students. Disaster Prevention and Management. Vol. 17 No. 4, 2008 pp. 503\u0026ndash;507. Emerald Group Publishing Limited.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAkalu T, Melaku W, Fentahun M, Birru Y. Agricultural potentials, constraints and opportunities in the Megech and Ribb rivers irrigation project areas in the Lake Tana Basin of Ethiopia. Amhara Region Agricultural Research Institute; 2009.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAllotey K, Arku G, Amponsah P. 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International Journal of Medical Science and Public Health Online 2016.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Footnotes","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e The administrative unit under zone and region that oversees the smallest units called as Kebeles in Ethiopia. This is similar to County form of administration.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e The smallest administrative unit in Ethiopia\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Disaster Risk Management, Disaster Preparedness, Disaster Prevention, Risk Mitigation","lastPublishedDoi":"10.21203/rs.3.rs-6233979/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6233979/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAlthough disaster risk management has evolved as an interdisciplinary field and a community driven practice, disasters in Ethiopia have continued to grow in both scale and impact. One of the major challenges in addressing this issue is the lack of scientific knowledge about local disaster management practices and a limited understanding of the underlying factors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis mixed study assesses the disaster management practices of 635 households in locations affected by different hazards in South Gondar zone. The results showed that 66% of households exhibit very low levels of disaster management preparedness. Alarmingly, only 20% of households are engaged in disaster preparedness, while 35% are involved in prevention activities, and 39% in mitigation efforts. Statistical analysis revealed significant differences in disaster management practices based on location (kebeles, p = 0.001; woreda, p = 0.001) and economic status (p = 0.04). Younger, more educated, and higher-income households were found to be less involved in risk management activities.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo improve disaster management practices, there needs to be a stronger emphasis on community ownership and active participation throughout all key phases. In particular, more efforts are required to promote disaster preparedness among households.\u003c/p\u003e","manuscriptTitle":"Disaster Risk Management Practices among Households in Selected Kebeles of South Gondar Administrative Zone","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-01 08:00:59","doi":"10.21203/rs.3.rs-6233979/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"83493023-9ce5-4e11-bd9d-930df67f67ee","owner":[],"postedDate":"April 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-04-21T09:23:47+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-01 08:00:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6233979","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6233979","identity":"rs-6233979","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}