Prevalence and Risk factors for Cryptosporidiosis among Livestock and Livestock keepers in northern Tanzania

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This study aimed to determine the prevalence and risk factors for cryptosporidiosis among livestock and livestock keepers in northern Tanzania. This was a cross-sectional survey that was conducted in northern Tanzania from September 2024 to February 2025 to screen livestock keepers and their livestock for cryptosporidiosis using modified Ziehl-Neelsen staining. Data on risk factors were collected through structured questionnaires and animal checklists. The prevalence of cryptosporidiosis in livestock and livestock keepers was estimated using descriptive statistics, while the association between variables was analyzed using logistic regression. Multivariate logistic analysis was employed to assess risk factors for disease. The overall prevalence of cryptosporidiosis among livestock keepers was 56.5% (212/425). A higher proportion of males tested positive, at 58% (91), compared with females, at 55.5% (121). The highest prevalence occurred in the 60–64 age group, with a prevalence of 9/10 (90%). Cryptosporidiosis was statistically associated with education (p = 0.024), occupation (p = 0.033), HIV status(p = 0.0001), diarrhea(p = 0.0001), and hand hygiene (0.0001). Among livestock, 64% (272/425) were positive for cryptosporidiosis, with greater prevalence in females (66.3%). Cryptosporidiosis was significantly influenced by gender(p = 0.037), management practice(p = 0.048), species (p = 0.05), disposal of wastes (p = 0.0001), cleanliness of hind legs (p = 0.0001), and age (p = 0.0001). These findings indicate that cryptosporidiosis is prevalent among livestock and livestock keepers, highlighting the need for targeted community education to reduce exposure and control the infection. Cryptosporidiosis Livestock keepers Prevalence Risk factors Zoonosis Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Cryptosporidiosis is a zoonotic disease caused by the oocyst-forming parasite Cryptosporidium , which is environmentally resistant (Guy et al. 2022 ). Infection occurs when contaminated food or water is taken in, allowing oocysts to colonize the gastrointestinal tracts of a wide range of vertebrate hosts(Odeniran and Ademola 2019 ). Recent studies indicated that more than 40 species have been described in the genus Cryptosporidium (Widmer et al. 2020 ), with at least 13 Cryptosporidium species identified in livestock globally(Ryan et al. 2021 ). In livestock, the most frequently detected species include Cryptosporidium parvum, C.andersoni, C.bovis , and C.ryanae (Guy et al. 2022 ). Among these, C.parvum, C.andersoni , and C.bovis are also capable of infecting humans, with C.parvum being predominantly responsible for zoonotic cryptosporidiosis (Ryan et al. 2021 ). Infected hosts may excrete large numbers of Cryptosporidium oocysts in their feces, which can contaminate water and food supplies, thereby facilitating further transmission. Cryptosporidiosis in humans presents with self-limiting diarrhea in immunocompetent individuals. However, it can become chronic and life-threatening in children and immunocompromised patients, such as those with human immunodeficiency virus infection, young children, the elderly, and individuals undergoing cancer treatment and organ transplants. The clinical signs include diarrhea, stomach pain, anorexia, weight loss, and stunted growth(Tombang et al. 2019 ). On the other hand, cryptosporidiosis in animals, particularly cattle, may be asymptomatic or symptomatic, with young calves often shedding the highest intensity of Cryptosporidium oocysts(Abdullah et al. 2019 ). These calves excrete Cryptosporidium parvum , a species with a wide host range, and are considered to be a potentially zoonotic agent(Kifleyohannes et al. 2022 ). Calves and lambs are considered as the main reservoirs of human cryptosporidiosis. Although adult animals are frequently subclinically infected, the disease can still adversely affect milk and meat production,(Khan et al. 2019 ) as well as growth rate and mortality(Shaw et al. 2021 ). Globally, diarrhea diseases associated with unsafe water, poor sanitation, and hygiene are responsible for over 829,000 deaths annually, with cryptosporidiosis contributing to this burden (WHO 2022 ). Additionally, foodborne illness affects nearly 600 million people and causes 420,000 deaths, leading to a loss of roughly 33 million disability adjusted life years (DALYs), with 125,000 under-five children dying from foodborne illness each year(WHO 2024 ). In South Asia and sub-Saharan Africa, cryptosporidiosis remains a leading cause of diarrhea, with an estimated 2.9 to 4.7 million cases of diarrhea each year among children under the age of two(Sow et al. 2016 ). This substantial burden highlights the public medical importance of this parasite, particularly in vulnerable populations. Major risk factors reported among humans are age, gender, education level(Tombang et al. 2019 ), food handling practices, and hygienic habits such as washing hands before meals and after using the toilet, as well as age, disposal of animal waste, type of toilet facilities, and contact with domestic or farmed animals(Hussin et al. 2016 , Dankwa et al. 2021 , Tamomh et al. 2021 , Kankya et al. 2023 ). Regarding livestock, several studies from Africa have reported prevalence rates ranging from 13.8% to 40% in animals(Ngowi et al. 2017 , Krumkamp et al. 2021 , Tamomh et al. 2021 , Kankya et al. 2023 , Mensah et al. 2023 ), with age, sex, breed, housing, water source, and hygiene status were identified as important risk factors(Ebiyo and Haile 2022 ). Several diagnostic approaches are available for detecting Cryptosporidium , including microscopic, immunological, and molecular techniques(Khan et al. 2019 , Javidmehr et al. 2020 , Berhanu et al. 2022 , Ebiyo and Haile 2022 , Majeed et al. 2022 ). Microscopy is commonly performed using modified Ziehl-Neelsen staining techniques where oocysts appear as bright red granules against a pale blue background(Khan et al. 2019 , Javidmehr et al. 2020 , Krumkamp et al. 2021 ). Effective control and prevention plans depend on a clear understanding of drivers that facilitate the introduction, transmission, and spread of the infection among livestock keepers and their animals. To date, several studies have been conducted in northern Tanzania, reporting positivity rates ranging from 6 to 15%(Krumkamp et al. 2021 , Hugho et al. 2023 ); however, these investigations were primarily focused on children under the age of five, while little information is available on other age groups and animals, particularly within livestock communities. Moreover, the potential risk factors for cryptosporidiosis among livestock and livestock keepers are poorly understood. Therefore, this study aimed to determine the prevalence and identify the risk factors contributing to the transmission of cryptosporidiosis among livestock and livestock keepers in Northern Tanzania. Material and methods Study area, design, and recruitment The study was carried out in Northern Tanzania. The northern zone is located at latitude 3 0 51 ’ 41.40 south and longitude 36 59 44.16 East. It exhibits a relatively cool and moderate climate, with temperatures ranging from 15 0 C to 25 0 C year-round. Northern Tanzania experiences a dry season (June-October) followed by two rainy seasons (March-May and November-December). The Northern zone has four administrative regions, but the study was carried out in three regions, namely Kilimanjaro, Manyara, and Tanga, specifically in Hai, Moshi, Simanjiro, Mbulu, and Korogwe districts. These three regions are characterized by a majority of the population that engages in pastoral and agro-pastoral activities as a source of daily and household income (Fig. 1). This was a prospective cross-sectional study conducted between September 2024 and February 2025 across fifty livestock farms and seven health facilities in the five selected administrative districts of northern Tanzania to determine the prevalence and risk factors among livestock and livestock keepers by examining fecal samples. The required fecal samples were calculated using the Cochran formula as described by T.S Nanjundeswaraswamy and S Divakar (Nanjundeswaraswamy and Divakar 2021). The sample size was estimated using an assumed prevalence of 50% at a 95% confidence interval and 5% margin of error. A total of 422 livestock keepers and 384 livestock were obtained from the estimation; however, a total of 425 livestock and 375 individuals were involved in the study. The purposive and random sampling were used to recruit study participants who met the inclusion criteria and provided informed consent. Questionnaire/checklist administration, fecal sample collection, and laboratory analysis A structured questionnaire was used to collect individuals' demographic information, including age, gender, clinical symptoms such as diarrhea and its duration, source of drinking water, type of toilet facility, and hygiene practices. Diarrhea was defined as the passage of loose or watery stools three or more per day for at least 72 hours. Cases lasting fewer than 14 days were classified as acute, while those persisting beyond 14 days were considered chronic. Checklists were used to gather information on the location of the animal farm (region and district), age, gender, diarrhea, management practices, source of drinking water, hygiene practices, breed, purpose of keeping, animal species, and disposal of animal waste (Refer to the supplementary materials). The sterilized fecal containers were used to collect fecal samples from the livestock and livestock keepers. The codes assigned to the containers were checked for visibility and confirmed to match those on the questionnaires and checklists. Fecal samples were preserved in 10% formalin and subsequently transported to the Nelson Mandela African Institution of Science and Technology, where they were kept refrigerated at 20°C until processed using microscopy. Fecal samples were removed from the refrigerator and allowed to thaw at room temperature. Moderately thick fecal smears were then prepared on standard glass microscope slides using a wooden applicator stick for both thick and thin smears. The slides were air-dried on drying racks and then tested for cryptosporidiosis using modified Ziehl-Neelsen staining techniques, as described by Alireza Javidmehr(Javidmehr et al. 2020). The slides were placed in a multi-slide carrier for fixation in methanol for 3 minutes, followed by staining with strong carbol fuchsin for approximately 15 minutes. The slide was then thoroughly rinsed in tap water. Minimal decolorization was achieved by agitation in 1% hydrochloric acid-alcohol (70%) for 15 seconds, followed by rinsing in tap water. Counterstain for 30 seconds in 1% methylene blue, rinse well, and air-dry. The stained slides were examined using 20X and 100X oil immersion magnification. The slides were prepared for each sample and were examined by two separate individuals based on the Cryptosporidium -positive slides obtained from the Tanzania National Laboratory (TNL). Additionally, to reduce the likelihood of false-positive results and enhance diagnostic accuracy, all slides were processed with standardized staining procedures and examined by three trained personnel based on morphological criteria. Statistical analysis Data were analyzed using IBM SPSS version 20. Prevalence was estimated with descriptive statistics, including frequencies, percentages, and means, to summarize characteristics. Logistic regression was used to determine the association between risk factors and cryptosporidiosis prevalence, while multivariate logistic regression was employed to identify risk factors and evaluate the combined effects of predictor variables. Ethical approval and informed consent This study received approval from the Kibong’oto-Nelson Mandela-Cedha Health Research Ethical Committee (approval# KNCHREC00029/01/2024) and was conducted in accordance with the ethical standards outlined in the 1964 Declaration of Helsinki and its subsequent amendments, or equivalent ethical standards. The authors confirmed that all participants were thoroughly informed about the study's purpose and voluntarily provided written informed consent for their data to be used. Participants under 18 years old provided their consent through their parents or guardians. They were also made aware of their right to decline participation or to withdraw from the study at any time without penalty. Additionally, we used code numbers to protect the confidentiality of all patient-identifiable information. Results Demographic Characteristics A total of 375 individuals took part in the study, including 157 males and 218 females, accounting for 41.9% and 58.1% of the participants, respectively. The participants’ ages ranged from 1 to 80 years, with a mean age of 38.5 ± 17.3 years. Concerning educational levels, 22.7% had no formal education, 46.7% had primary education, 25.3% completed secondary education, and 5.3% had post-secondary education. Regarding marital status, 91.2% were married, 8.3% were single, and 0.5% were divorced. Most participants, 90.9%, were involved in livestock-keeping activities, while the remaining 9.1% worked in other occupations, such as small businesses. While a total of 425 livestock animals were included in the study, which comprised 66.1% cattle, 17.6% goats, 9.6% sheep, pigs 5.6% and 0.9% dogs. The animals’ age ranged from 0 to 10 years, with a mean age of 2.6 ± 1.99 years. Regarding sex distribution, 31.8% were males and 68.2% females. On the other hand, the livestock were raised under different management systems, with 219(51.5%) under extensive and 206 (48.5%) semi-intensive. Regarding breed 209(49.2%) were indigenous/local breeds, while 216(50.8%) were improved breeds. The animals were sourced from various farms across five districts of northern Tanzania, as shown in Table 1 Table 1 Demographic characteristics of Livestock keepers and Livestock Characteristic Category Frequency (n) Percentage (%) Livestock keepers Gender Male 157 41.9 Female 218 58.1 Age(years) 0–5 3 0.8 6–17 35 9.3 18–59 304 81.1 60–64 10 2.7 65+ 23 6.1 Martial Single 31 8.3 Married 342 91.2 Divorced 2 0.5 Education No education 85 22.7 Primary Education 175 46.7 Secondary Education 95 25.3 Postsecondary Education 20 5.3 Occupation Livestock keeping 341 90.9 Non-livestock keeping 34 9.1 Livestock Gender Male 134 31.5 Female 291 68.5 Age(months) 0–6 172 40.5 7–24 110 25.9 > 24 143 33.6 Management system Extensive 219 51.5 Semi-intensive 206 48.5 Breed Local 209 49.2 Improved 216 50.8 Species Cattle 281 66.1 Goat 75 17.6 Sheep 41 9.6 Pigs 24 5.6 Dogs 4 0.9 Table 1 summarizes the sociodemographic characteristics of livestock keepers and livestock included in the study. For livestock keepers, variables assessed were age, gender, education, occupation, and marital status, whereas in livestock, characteristics were age, gender, breed, species, and management practices. Categorical variables were presented as frequencies and percentages. Prevalence of cryptosporidiosis The microscopic examination through modified Ziehl-Neelsen staining showed the presence of Cryptosporidium spp oocysts. The oocysts of Cryptosporidium appeared as sphere-shaped morphology and blurry inner structure, as shown in Fig. 2 below. A total of 56.5% (212/ 375) of fecal samples collected from livestock keepers tested positive for cryptosporidiosis. The prevalence of the parasite was higher among individuals from Hai (72.2%), followed by Mbulu (66.7%) and Korogwe (59.2%), compared to those from Moshi (49.4%) and Simanjiro (32.3%), as shown in Fig. 3 . Among livestock, 64% (272/ 425) of fecal samples were positive for cryptosporidiosis. Cryptosporidiosis was higher among livestock in Hai (82%), followed by Korogwe (72%) and Mbulu (60.5%), compared to those from Moshi (56.2%) and Simanjiro (44.6%) districts, as shown in Fig. 4 . Risk factors Risk factors assessed during the study were categorized into factors related to livestock keepers and those linked to livestock. Among the factors related to livestock keepers, diarrheic status (AOR = 3.078, 95%CI, 1.658–5.715, p = 0.0001), HIV status (AOR = 0.122, 95% CI 0.062–0.24, p = 0.0001), materials used in hand hygiene (AOR = 1.497,95%CI 1.218–1.841, p = 0.0001), education(AOR = 1.362, 95% CI 1.04–1.784;p = 0.025), and occupation status (AOR = 0.852,95% CI 0.736–0.987, p = 0.032) showed a significant association with the cryptosporidiosis prevalence; however, there was no statistically significant associations between cryptosporidiosis prevalence and animal contact, water source, type of toilet facility, age, gender, overcrowding, location, type of animals reared in household, and marital, even though higher proportions of infection were observed among individuals with daily animal contact 209/367(56.9%),those using surface water 196/344 (57%), flush toilets 107/172 (62.2%), participants aged 60–64 years 9/10 (90%), males 91/157 (58%), households with six or more members 58(60.4%), residents of Hai (72.2%), Mbulu (66.7%) Korogwe (59.2%), and those keeping non-ruminant animals 37/63 (58.7%), as shown in Table 2 . Whereas, among the latter category, gender (AOR = 0.558, 95% CI 0.323–0.965, p = 0.037), age (AOR = 0.561, 95% CI 0.413–0.778, p = 0.0001), disposal of animal waste(AOR = 0.06,95% CI 0.76–6.9, p = 0.0001), management practice(AOR = 0.374, 95%CI 0.141–0.992, p = 0.048), animal species (AOR = 0.743, 95% CI 0.549–1.006, p = 0.05), cleanliness of the animal house (AOR = 0.039, 95%CI, 0.005–0.282, p = 0.001) and hind legs (AOR 25.796, 95%CI 7.876–84.485, p = 0.0001) were statistically significant associated with infection rate of cryptosporidiosis, however, diarrhea, breed, location, overcrowding, and water source were not significantly associated with prevalence of cryptosporidiosis nonetheless higher prevalence was recorded among livestock presented with diarrhea 19/26 (73.1%), belonged to local breed 143/209(68.4%), originated from Hai (82%), Korogwe (72%), and Mbulu (60.5%), were kept under grouped housing 270/412 (65.4%), and consumed surface water, 127/179 (70.9%), as shown in Table 3 Table 2 Prevalence and risk factors for cryptosporidiosis among livestock keepers Variable No sample No (100%) positive of cryptosporidium based on categories Prevalence AOR 95% CI p-value Age(years) 0–5 3 0 0(0%) 1.035 0.672–1.594 0.875 6–17 35 14 14(40%) 18–59 304 178 178(58.6%) 60–64 10 9 9(90%) 65+ 23 11 11(47.8%) Gender Male 157 91 91(58%) 1.28 0.782–2.096 0.325 Female 218 121 121(55.5%) Education status No education 85 45 45(52.9%) 1.362 1.04–1.784 0.025* Primary Education 174 89 89(50.9%) Secondary Education 95 60 60(63.2%) Post Secondary Education 20 18 18(90%) Occupation status Livestock keeping 341 201 201(58.9%) 0.852 0.736–0.987 0.032* Non-Livestock keeping 34 11 11(32.4%) Marital status Single 31 11 11(35.5%) 0.623 0.267–1.45 0.272 Married 342 201 201(58.8%) Divorced 2 0 0(0%) HIV status Yes 106 83 83 0.122 0.062–0.241 0.0001* No 269 129 129 Diarrhea Yes 154 104 104(67.5%) 3.078 1.658–5.715 0.0001* No 221 108 108(48.9%) Type of toilet facility Pit Latrine 155 90 90(58.1%) 1.208 0.769–1.896 0.412 Flush latrine 172 107 107(62.2%) No facility 48 15 15(31.2%) Material used in Hand hygiene Soap and water 281 148 148(52.7%) 1.497 1.218–1.841 0.0001* Soil 3 1 1(33.3%) Water 91 63 63(69.2%) Contact with animals Daily 367 209 209(56.9%) 1.298 0.389–4.33 0.672 Rarely 8 3 3(37.5%) Source of drinking water Surface water 344 196 196(57%) 0.19 0.017–2.157 0.18 Ground water 31 16 16(51.6%) Number of individuals living in a household 2 people 56 30 30(53.6%) 0.93 0.625–1.385 0.722 3–5 223 124 124(55.6%) 6–10 96 58 58(60.4%) Type of animals in the household Ruminants 70 38 38(54.3%) 0.955 0.844–1.08 0.464 Non-ruminant 63 37 37(58.7%) Mixed 242 137 137(56.6%) Geographic location (District-wise) Simanjiro 62 20 20(32.3%) 0.94 0.739–1.195 0.614 Hai 72 52 52(72.2%) Korogwe 82 48 48(59.3%) Mbulu 75 50 50(66.7%) Moshi 85 42 42(49.4%) Table 2 indicates the risk factors associated with cryptosporidiosis among livestock keepers, including sociodemographic characteristics, diarrhea, HIV status, water source, hygiene practice, geographical location, number of people, and the type of animals in the household. The associations between variables and cryptosporidiosis are presented as an adjusted odds ratio (AOR) with a 95% confidence interval (CI) and corresponding p-values, whereby (*) represents statistically significant at p<0.05. Table 3 Prevalence and risk factors for cryptosporidiosis among Livestock Variable No sample No (100%) positive of cryptosporidium based on categories Prevalence AOR 95% CI p-value Age (months) 0–6 172 123 123(71.5%) 0.561 0.413–0.778 0.0001* 7–24 110 67 67(60.9%) > 24 143 82 82(57.3%) Gender Male 134 79 79(59%) 0.558 0.323–0.965 0.037* Female 291 193 193(66.3%) Management system Extensive 219 131 131(59.8%) 0.374 0.141–0.992 0.048* Semi-intensive 206 141 141(68.4%) Breed Local 209 143 143(68.4%) 1.435 0.484–4.256 0.515 Improved 216 129 129(59.7%) Source of drinking water Surface 179 127 127(70.9%) 0.316 0.46–2.16 0.24 Ground 246 145 145(58.9%) Disposal of animal waste Unhygienic 234 167 167(71.4%) 0.061 0.023–0.161 0.0001* Hygienic 191 105 105(55%) Diarrhea Yes 26 19 19(73.1%) 1.85 0.624–5.487 0.267 No 399 253 253(63.4%) Cleanliness of the animal house Yes 28 22 22(78.6%) 0.039 0.005–0.282 0.001* No 397 250 250(63%) Type of animal house Individual 12 2 2(16.7%) 5.663 0.823–38.963 0.078 Groups 413 270 270(65.4%) Cleanliness of the hind legs Yes 74 32 32(43.2%) 25.796 7.876–84.485 0.0001* No 351 240 240(68.4%) Animal species Cattle 281 193 193(68.7%) 0.743 0.549–1.006 0.05* Goat 75 40 40(53.3%) Sheep 41 26 26(63.4%) Pigs 24 10 10(41.7%) Dogs 4 3 3(75%) Geographical location Hai 99 82 82(82.8%) 0.729 0.463–1.15 0.175 Moshi 80 45 45(56.2%) Simanjiro 83 37 37(44.6%) Mbulu 81 49 49(60.5%) Korogwe 82 59 59(72%) Table 3 shows the risk factors associated with cryptosporidiosis among livestock, including sociodemographic characteristics, diarrhea, water source, hygiene practice, geographical location, and type of animal house. The associations between variables and cryptosporidiosis are presented as an adjusted odds ratio (AOR) with a 95% confidence interval (CI) and corresponding p-values, whereby (*) represents statistically significant at p<0.05. Discussion Cryptosporidiosis is an enteric disease that infects the gastrointestinal tracts of both humans and animals. Although it has zoonotic potential, most research in Tanzania has focused on human cases (Hugho et al. 2023 ). The present study investigated the prevalence of cryptosporidiosis in both livestock and livestock keepers. Employing modified Ziehl-Neelsen techniques, it also identified the risk factors for the disease. The overall human prevalence reported in this study was 56.5%. which was lower than reported in Bangladesh (77%) and higher than that reported in Ethiopia (48%)(Korpe et al. 2016 , Hailu et al. 2021 ). Additionally, the overall livestock prevalence was 64%. This result is aligned with the prevalence reported in Northern China (63.6%), but this prevalence differs from the findings reported in Cameroon (44.5%) (Wang et al. 2024 , Siama et al. 2025 ). The observed variation of prevalence may be attributed to differences in study design, including sample size, geographical location, and age structure of the population, as well as the diagnostic techniques used. Several factors, such as age, occupation, water source, animals contact, gender, diarrhea, geographical location, education, HIV, and marital status, play a major role in the current prevalence among livestock keepers, whereas the management system, breed, age, gender, water source, hygiene practice, type of house, disposal animal waste and animals species contribute to higher prevalence among livestock. Cryptosporidiosis has been reported in people from 0 to 80 years; however, the current findings show that individuals aged 60–64 and 18–59 years were more exposed and infected 90% and 59.6%, respectively. This finding is similar to the study from Iran and Turkey, which reported a higher prevalence among individuals aged 30–59 and the elders (Sinyangwe 2016 , Nouraftab et al. 2022 , Orak et al. 2023 ). However, the present study contrasts with a study from Pakistan that reported higher infection rates among children under five years of age (Khan et al. 2019 ). The higher burden may be explained by variation in environmental factors, including source of drinking water and contact with pets, poor hygiene practices, such as hand washing before meals and after using the toilet, as well as fruit and vegetable washing before eating. Also, this may be attributed to the number of population structures seeking medical care at health facilities during the data collection. Moreover, the present study indicates that male individuals from Mbulu, Hai, and Korogwe reported a higher prevalence of cryptosporidiosis compared to females. This finding aligns with a study from Zambia reporting that male individuals were 1.3 times more at higher risk compared to their female counterparts (Sinyangwe 2016 ). This may be justified by the fact that males, particularly those from Mbulu and Korogwe, are more involved in livestock keeping than females, and hence they are more exposed to the infection agents through frequent contact with animals compared to females. However, the high prevalence among male individuals from Hai district by poor hygiene practices, such as hand washing before meals and after daily activities that involve contact with animals, including grazing, animal care, and slaughtering(Terfa and Getushe 2023 ). Furthermore, the finding also suggests that individuals who use surface water(p = 0.18) for hand hygiene(p = 0.0001), and flush toilets (p = 0.412) were likely more at risk of having cryptosporidiosis. This result aligns with findings from Pakistan and Zambia (Sinyangwe et al. 2020 , Abbas et al. 2022 ), which identified surface water as a major reservoir for Cryptosporidium spp. oocysts and a key route of exposure. A study's results showed that individuals with higher education were at a higher risk of having cryptosporidiosis compared to those with lower education. This finding differs from a study conducted in Qatar (Boughattas et al. 2019 ) which reported that individuals who had an elementary school education were more infected with cryptosporidiosis(p = 0.025) than those with higher education. The likelihood of participants with higher education to have cryptosporidiosis may be caused by poor hygiene practices, such as ingesting contaminated water and food, using contaminated water to wash hands before meals and after using the toilet, particularly during medical research, and travel. A comparative analysis of our study revealed that individuals who presented with diarrhea (104), 67.5%, were significantly more likely to be infected with cryptosporidiosis. (AOR = 3.078, 95%CI, 1.658–5.715, p = 0.0001) than those without diarrhea. These findings align with a study done in Pakistan, which likewise found an increased risk of Cryptosporidium infection among individuals with diarrhea(Khan et al. 2019 ). Cryptosporidiosis has been reported among immunocompromised individuals. This is justifiable with our result that revealed that the HIV status was statistically significantly associated with the prevalence of cryptosporidiosis (AOR = 0.122, 95% CI 0.062–0.241). Also, this finding aligns with a study from Zambia and North West Ethiopia reporting that the immunocompromised status was statistically significant with Cryptosporidium infection(Sinyangwe 2016 , Tamrat et al. 2024 ), suggesting that these individuals are at higher risk of infection because of immunosuppression. Our study results showed that cryptosporidiosis is prevalent in animals under the age of six months. This finding aligns with the studies from Spain, Ethiopia, Egypt, Kuwait, Cameroon, and Kenya (Ogendo 2020 , Díaz et al. 2021 , Berhanu et al. 2022 , Gattan et al. 2023 , Tamrat et al. 2024 , Siama et al. 2025 ) which found that the prevalence of cryptosporidiosis decreased as livestock age increased. The likelihood of young animals being susceptible to cryptosporidiosis could be due to their immature immunity, which fails to fight against infection. Nevertheless, it is important to recognize that both young and adult infected animals play a significant role in disease transmission because they both eliminate oocysts in their feces (Thomson et al. 2017 ) Furthermore, the study revealed that female animals are more likely to have cryptosporidiosis than their male counterpart. Similar observations have been reported from China among Equus(Li et al. 2022 ). This higher likelihood of female animals having cryptosporidiosis is attributed to a weaker body immunity at certain periods in their physiologic cycle (Eze et al. 2019 ), but it could also be due to a higher level of animal-human contact, particularly during milking, making them more susceptible than male animals. Additionally, the study reported that unhygienic disposal of animal waste, especially near a water source, increases the risk of contamination, resulting in waterborne transmission. This finding aligns with the studies from Kuwait, Brazil, and Egypt that reported that a lack of hygienic conditions helps spread infections [20, 35, 39]. The environmental context also supports this link, as domestic animals (e.g., cattle, goats, sheep) and wildlife often access surface water sources like rivers and ponds, potentially introducing Cryptosporidium oocysts through fecal contamination [40]. These findings emphasize the importance of improving water, sanitation, and hygiene (WASH) practices by limiting animal access to water sources and strengthening WASH services to reduce the environmental spread and human exposure to Cryptosporidium oocysts. Moreover, studies reported that excretion of oocysts was frequently related to the presence of diarrhea; however, our data indicate that asymptomatic animals also eliminate oocysts, therefore, they may play an important role in contaminating the environment, hence, facilitating the transmission(Thomson et al. 2017 ). Additionally, the study revealed that cryptosporidiosis is associated with management practices, with higher cases recorded in semi-intensive systems. This finding aligns with findings from Brazil and Cameroon that reported semi-intensive rearing (OR = 0.2, p = 0.024) as a risk factor (Conceição et al. 2021 , Siama et al. 2025 ). This may be attributed to ingesting contaminated food and water, and contact with infected animals or their feces, particularly in mixing herds and crowded housing. Furthermore, our results showed that the prevalence of cryptosporidiosis was significantly associated with animal species, with dogs, cattle, and sheep being at greater risk than goats and pigs. This result aligns with a study from Uganda that reported that the dogs were 50 times at risk of having Cryptosporidium infection than goats and pigs(Kankya et al. 2023 ). This may be attributed to the management practice used for keeping dogs, which allows them to roam freely, resulting in exposing them to infectious agents through ingesting contaminated water and food. Conclusion Our findings indicated that cryptosporidiosis is highly prevalent among livestock and livestock keepers in Northern Tanzania, suggesting that livestock can harbor and shed the Cryptosporidium oocysts that contaminate the environment, thereby infecting humans. Also, the concentration of this burden among male individuals suggests a need for a targeted community education program aiming to reach the population at risk and reduce exposure and control infection in the livestock too. Moreover, based on our study findings, there is also a need for further studies on larger samples to understand other factors that may be associated with cryptosporidiosis, including identifying circulating species and genotypes among both animal and human populations in the study areas and beyond. Declarations Funding This study was funded by the University of Dar es Salaam Higher Education for Economics for Transformation (UDSM-HEET) project. Competing interests The authors have no relevant financial or non-financial interests to disclose. Author contribution All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by HK, BL, BN, and ES. The first draft of the manuscript was written by HK, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.” Consent to participate Informed consent was obtained from all individual participants included in the study. Additionally, written informed consent was obtained from the parents. Consent to publish The authors affirm that human research participants provided informed consent for publication of this data. Acknowledgement The authors extend sincere appreciation to the Local authorities for granting permission to carry out this study and to all participants for their willingness to take part. Additionally, special thanks are due to the research assistants who worked diligently to support data and sample collection during the conduct of this study. We also thank the University of Dar es Salaam Higher Education for Economics for Transformation (UDSM-HEET) project for financing this survey. Data availability The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.” References Abbas, Z., M. K. Khan, R. Z. Abbas, Z. u. D. Sindhu, M. S. Sajid, A. Munir, A. Wahid, A. Zafar, M. A. S. Mughal and M. Imran (2022). "Molecular epidemiology of Cryptosporidium parvum and Giardia lamblia in different water bodies, soil, and vegetables in Pakistan." Health security 20 (4): 308-320https://doi.org/10.1089/hs.2021.0118. 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Supplementary Files HusnaKangusiAnimalChecklist.docx HusnaKangusiQuestionnaires.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 04 Nov, 2025 Reviewers invited by journal 04 Nov, 2025 Editor invited by journal 22 Oct, 2025 Editor assigned by journal 21 Oct, 2025 First submitted to journal 19 Oct, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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07:13:10","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":585344,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eCryptosporidium \u003c/em\u003espp oocysts stained with modified Ziehl-Neelsen staining techniques.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCryptosporidium s\u003c/em\u003epp oocysts appeared as bright rose-pink on a pale blue background. The presence or absence of oocysts was documented. To reduce the risk of false-positive results, trained personnel verified the findings based on morphological criteria\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7705991/v1/fd052939171e606808dd6404.png"},{"id":95905321,"identity":"730bd1b0-784b-4226-90e4-09a4c960eab3","added_by":"auto","created_at":"2025-11-14 09:21:50","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":56761,"visible":true,"origin":"","legend":"\u003cp\u003ePrevalence of cryptosporidiosis in Livestock based on districts\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7705991/v1/5c8c5391ed382d16080711ed.png"},{"id":95905322,"identity":"9b87e4aa-fd4d-4555-afe7-6eedb19f2c9c","added_by":"auto","created_at":"2025-11-14 09:21:50","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":36892,"visible":true,"origin":"","legend":"\u003cp\u003ePrevalence of cryptosporidiosis in Livestock based on districts\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7705991/v1/07a6fb882c22bc0e9c0c8710.png"},{"id":96602995,"identity":"794fd805-8bf8-4899-a3ce-453339613cce","added_by":"auto","created_at":"2025-11-24 09:05:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2621855,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7705991/v1/5d4231cc-5974-4c25-9b90-5f082b08e7d8.pdf"},{"id":95905328,"identity":"9764d72e-f9cd-4833-af36-c92841327db1","added_by":"auto","created_at":"2025-11-14 09:21:50","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":28415,"visible":true,"origin":"","legend":"","description":"","filename":"HusnaKangusiAnimalChecklist.docx","url":"https://assets-eu.researchsquare.com/files/rs-7705991/v1/fa158617a27dd6a513ed01d1.docx"},{"id":95905329,"identity":"2ce20998-6fb1-46f6-b87e-77ec1c53c37c","added_by":"auto","created_at":"2025-11-14 09:21:50","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":32426,"visible":true,"origin":"","legend":"","description":"","filename":"HusnaKangusiQuestionnaires.docx","url":"https://assets-eu.researchsquare.com/files/rs-7705991/v1/661390e826f12d3d02d8357d.docx"}],"financialInterests":"","formattedTitle":"Prevalence and Risk factors for Cryptosporidiosis among Livestock and Livestock keepers in northern Tanzania","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCryptosporidiosis is a zoonotic disease caused by the oocyst-forming parasite \u003cem\u003eCryptosporidium\u003c/em\u003e, which is environmentally resistant (Guy et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Infection occurs when contaminated food or water is taken in, allowing oocysts to colonize the gastrointestinal tracts of a wide range of vertebrate hosts(Odeniran and Ademola \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Recent studies indicated that more than 40 species have been described in the genus \u003cem\u003eCryptosporidium\u003c/em\u003e (Widmer et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), with at least 13 \u003cem\u003eCryptosporidium\u003c/em\u003e species identified in livestock globally(Ryan et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In livestock, the most frequently detected species include \u003cem\u003eCryptosporidium parvum, C.andersoni, C.bovis\u003c/em\u003e, and \u003cem\u003eC.ryanae\u003c/em\u003e (Guy et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Among these, \u003cem\u003eC.parvum, C.andersoni\u003c/em\u003e, and \u003cem\u003eC.bovis\u003c/em\u003e are also capable of infecting humans, with \u003cem\u003eC.parvum\u003c/em\u003e being predominantly responsible for zoonotic cryptosporidiosis (Ryan et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Infected hosts may excrete large numbers of \u003cem\u003eCryptosporidium\u003c/em\u003e oocysts in their feces, which can contaminate water and food supplies, thereby facilitating further transmission.\u003c/p\u003e\u003cp\u003eCryptosporidiosis in humans presents with self-limiting diarrhea in immunocompetent individuals. However, it can become chronic and life-threatening in children and immunocompromised patients, such as those with human immunodeficiency virus infection, young children, the elderly, and individuals undergoing cancer treatment and organ transplants. The clinical signs include diarrhea, stomach pain, anorexia, weight loss, and stunted growth(Tombang et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). On the other hand, cryptosporidiosis in animals, particularly cattle, may be asymptomatic or symptomatic, with young calves often shedding the highest intensity of \u003cem\u003eCryptosporidium\u003c/em\u003e oocysts(Abdullah et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). These calves excrete \u003cem\u003eCryptosporidium parvum\u003c/em\u003e, a species with a wide host range, and are considered to be a potentially zoonotic agent(Kifleyohannes et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Calves and lambs are considered as the main reservoirs of human cryptosporidiosis. Although adult animals are frequently subclinically infected, the disease can still adversely affect milk and meat production,(Khan et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) as well as growth rate and mortality(Shaw et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eGlobally, diarrhea diseases associated with unsafe water, poor sanitation, and hygiene are responsible for over 829,000 deaths annually, with cryptosporidiosis contributing to this burden (WHO \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Additionally, foodborne illness affects nearly 600\u0026nbsp;million people and causes 420,000 deaths, leading to a loss of roughly 33\u0026nbsp;million disability adjusted life years (DALYs), with 125,000 under-five children dying from foodborne illness each year(WHO \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In South Asia and sub-Saharan Africa, cryptosporidiosis remains a leading cause of diarrhea, with an estimated 2.9 to 4.7\u0026nbsp;million cases of diarrhea each year among children under the age of two(Sow et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). This substantial burden highlights the public medical importance of this parasite, particularly in vulnerable populations. Major risk factors reported among humans are age, gender, education level(Tombang et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), food handling practices, and hygienic habits such as washing hands before meals and after using the toilet, as well as age, disposal of animal waste, type of toilet facilities, and contact with domestic or farmed animals(Hussin et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2016\u003c/span\u003e, Dankwa et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Tamomh et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Kankya et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Regarding livestock, several studies from Africa have reported prevalence rates ranging from 13.8% to 40% in animals(Ngowi et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2017\u003c/span\u003e, Krumkamp et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Tamomh et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Kankya et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, Mensah et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), with age, sex, breed, housing, water source, and hygiene status were identified as important risk factors(Ebiyo and Haile \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Several diagnostic approaches are available for detecting \u003cem\u003eCryptosporidium\u003c/em\u003e, including microscopic, immunological, and molecular techniques(Khan et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, Javidmehr et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, Berhanu et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, Ebiyo and Haile \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, Majeed et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Microscopy is commonly performed using modified Ziehl-Neelsen staining techniques where oocysts appear as bright red granules against a pale blue background(Khan et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, Javidmehr et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, Krumkamp et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Effective control and prevention plans depend on a clear understanding of drivers that facilitate the introduction, transmission, and spread of the infection among livestock keepers and their animals. To date, several studies have been conducted in northern Tanzania, reporting positivity rates ranging from 6 to 15%(Krumkamp et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Hugho et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2023\u003c/span\u003e); however, these investigations were primarily focused on children under the age of five, while little information is available on other age groups and animals, particularly within livestock communities. Moreover, the potential risk factors for cryptosporidiosis among livestock and livestock keepers are poorly understood. Therefore, this study aimed to determine the prevalence and identify the risk factors contributing to the transmission of cryptosporidiosis among livestock and livestock keepers in Northern Tanzania.\u003c/p\u003e"},{"header":"Material and methods","content":"\u003ch2\u003e\u003cstrong\u003eStudy area, design, and recruitment\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe study was carried out in Northern Tanzania. The northern zone is located at latitude 3\u003csup\u003e0\u003c/sup\u003e51\u003csup\u003e\u0026rsquo;\u003c/sup\u003e41.40 south and longitude 36 59 44.16 East. It exhibits a relatively cool and moderate climate, with temperatures ranging from 15\u003csup\u003e0\u003c/sup\u003eC to 25\u003csup\u003e0\u003c/sup\u003eC year-round. Northern Tanzania experiences a dry season (June-October) followed by two rainy seasons (March-May and November-December). The Northern zone has four administrative regions, but the study was carried out in three regions, namely Kilimanjaro, Manyara, and Tanga, specifically in Hai, Moshi, Simanjiro, Mbulu, and Korogwe districts. These three regions are characterized by a majority of the population that engages in pastoral and agro-pastoral activities as a source of daily and household income (Fig. 1). \u003c/p\u003e\n\u003cp\u003eThis was a prospective cross-sectional study conducted between September 2024 and February 2025 across fifty livestock farms and seven health facilities in the five selected administrative districts of northern Tanzania to determine the prevalence and risk factors among livestock and livestock keepers by examining fecal samples. The required fecal samples were calculated using the Cochran formula as described by T.S Nanjundeswaraswamy and S Divakar (Nanjundeswaraswamy and Divakar 2021). The sample size was estimated using an assumed prevalence of 50% at a 95% confidence interval and 5% margin of error. A total of 422 livestock keepers and 384 livestock were obtained from the estimation; however, a total of 425 livestock and 375 individuals were involved in the study. The purposive and random sampling were used to recruit study participants who met the inclusion criteria and provided informed consent.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eQuestionnaire/checklist administration, fecal sample collection, and laboratory analysis\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eA structured questionnaire was used to collect individuals\u0026apos; demographic information, including age, gender, clinical symptoms such as diarrhea and its duration, source of drinking water, type of toilet facility, and hygiene practices. Diarrhea was defined as the passage of loose or watery stools three or more per day for at least 72 hours. Cases lasting fewer than 14 days were classified as acute, while those persisting beyond 14 days were considered chronic. Checklists were used to gather information on the location of the animal farm (region and district), age, gender, diarrhea, management practices, source of drinking water, hygiene practices, breed, purpose of keeping, animal species, and disposal of animal waste \u003cstrong\u003e(Refer to the supplementary materials).\u003c/strong\u003e The sterilized fecal containers were used to collect fecal samples from the livestock and livestock keepers. The codes assigned to the containers were checked for visibility and confirmed to match those on the questionnaires and checklists. Fecal samples were preserved in 10% formalin and subsequently transported to the Nelson Mandela African Institution of Science and Technology, where they were kept refrigerated at 20\u0026deg;C until processed using microscopy.\u003c/p\u003e\n\u003cp\u003eFecal samples were removed from the refrigerator and allowed to thaw at room temperature. Moderately thick fecal smears were then prepared on standard glass microscope slides using a wooden applicator stick for both thick and thin smears. The slides were air-dried on drying racks and then tested for cryptosporidiosis using modified Ziehl-Neelsen staining techniques, as described by Alireza Javidmehr(Javidmehr et al. 2020). The slides were placed in a multi-slide carrier for fixation in methanol for 3 minutes, followed by staining with strong carbol fuchsin for approximately 15 minutes. The slide was then thoroughly rinsed in tap water. Minimal decolorization was achieved by agitation in 1% hydrochloric acid-alcohol (70%) for 15 seconds, followed by rinsing in tap water. Counterstain for 30 seconds in 1% methylene blue, rinse well, and air-dry. The stained slides were examined using 20X and 100X oil immersion magnification. The slides were prepared for each sample and were examined by two separate individuals based on the \u003cem\u003eCryptosporidium\u003c/em\u003e-positive slides obtained from the Tanzania National Laboratory (TNL). Additionally, to reduce the likelihood of false-positive results and enhance diagnostic accuracy, all slides were processed with standardized staining procedures and examined by three trained personnel based on morphological criteria.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eData were analyzed using IBM SPSS version 20. Prevalence was estimated with descriptive statistics, including frequencies, percentages, and means, to summarize characteristics. Logistic regression was used to determine the association between risk factors and cryptosporidiosis prevalence, while multivariate logistic regression was employed to identify risk factors and evaluate the combined effects of predictor variables.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eEthical approval and informed consent\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThis study received approval from the Kibong\u0026rsquo;oto-Nelson Mandela-Cedha Health Research Ethical Committee (approval# KNCHREC00029/01/2024) and was conducted in accordance with the ethical standards outlined in the 1964 Declaration of Helsinki and its subsequent amendments, or equivalent ethical standards. The authors confirmed that all participants were thoroughly informed about the study\u0026apos;s purpose and voluntarily provided written informed consent for their data to be used. Participants under 18 years old provided their consent through their parents or guardians. They were also made aware of their right to decline participation or to withdraw from the study at any time without penalty. Additionally, we used code numbers to protect the confidentiality of all patient-identifiable information.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003eDemographic Characteristics\u003c/h2\u003e\n \u003cp\u003eA total of 375 individuals took part in the study, including 157 males and 218 females, accounting for 41.9% and 58.1% of the participants, respectively. The participants\u0026rsquo; ages ranged from 1 to 80 years, with a mean age of 38.5\u0026thinsp;\u0026plusmn;\u0026thinsp;17.3 years. Concerning educational levels, 22.7% had no formal education, 46.7% had primary education, 25.3% completed secondary education, and 5.3% had post-secondary education. Regarding marital status, 91.2% were married, 8.3% were single, and 0.5% were divorced. Most participants, 90.9%, were involved in livestock-keeping activities, while the remaining 9.1% worked in other occupations, such as small businesses. While a total of 425 livestock animals were included in the study, which comprised 66.1% cattle, 17.6% goats, 9.6% sheep, pigs 5.6% and 0.9% dogs. The animals\u0026rsquo; age ranged from 0 to 10 years, with a mean age of 2.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.99 years. Regarding sex distribution, 31.8% were males and 68.2% females. On the other hand, the livestock were raised under different management systems, with 219(51.5%) under extensive and 206 (48.5%) semi-intensive. Regarding breed 209(49.2%) were indigenous/local breeds, while 216(50.8%) were improved breeds. The animals were sourced from various farms across five districts of northern Tanzania, as shown in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDemographic characteristics of Livestock keepers and Livestock\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCategory\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFrequency (n)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePercentage (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003eLivestock keepers\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e218\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge(years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u0026ndash;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u0026ndash;17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u0026ndash;59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e304\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e81.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60\u0026ndash;64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMartial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e342\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e91.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDivorced\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEducation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrimary Education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e175\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSecondary Education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePostsecondary Education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOccupation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLivestock keeping\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e341\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e90.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon-livestock keeping\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eLivestock\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e291\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e68.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge(months)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u0026ndash;6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e172\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u0026ndash;24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e143\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eManagement system\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eExtensive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e219\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSemi-intensive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e206\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBreed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLocal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e209\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eImproved\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSpecies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCattle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e281\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGoat\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSheep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePigs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDogs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003eTable 1 summarizes the sociodemographic characteristics of livestock keepers and livestock included in the study. For livestock keepers, variables assessed were age, gender, education, occupation, and marital status, whereas in livestock, characteristics were age, gender, breed, species, and management practices. Categorical variables were presented as frequencies and percentages.\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003ePrevalence of cryptosporidiosis\u003c/h2\u003e\n \u003cp\u003eThe microscopic examination through modified Ziehl-Neelsen staining showed the presence of \u003cem\u003eCryptosporidium\u003c/em\u003e spp oocysts. The oocysts of \u003cem\u003eCryptosporidium\u003c/em\u003e appeared as sphere-shaped morphology and blurry inner structure, as shown in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e below. A total of 56.5% (212/ 375) of fecal samples collected from livestock keepers tested positive for cryptosporidiosis. The prevalence of the parasite was higher among individuals from Hai (72.2%), followed by Mbulu (66.7%) and Korogwe (59.2%), compared to those from Moshi (49.4%) and Simanjiro (32.3%), as shown in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e. Among livestock, 64% (272/ 425) of fecal samples were positive for cryptosporidiosis. Cryptosporidiosis was higher among livestock in Hai (82%), followed by Korogwe (72%) and Mbulu (60.5%), compared to those from Moshi (56.2%) and Simanjiro (44.6%) districts, as shown in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eRisk factors\u003c/h3\u003e\n\u003cp\u003eRisk factors assessed during the study were categorized into factors related to livestock keepers and those linked to livestock. Among the factors related to livestock keepers, diarrheic status (AOR\u0026thinsp;=\u0026thinsp;3.078, 95%CI, 1.658\u0026ndash;5.715, p\u0026thinsp;=\u0026thinsp;0.0001), HIV status (AOR\u0026thinsp;=\u0026thinsp;0.122, 95% CI 0.062\u0026ndash;0.24, p\u0026thinsp;=\u0026thinsp;0.0001), materials used in hand hygiene (AOR\u0026thinsp;=\u0026thinsp;1.497,95%CI 1.218\u0026ndash;1.841, p\u0026thinsp;=\u0026thinsp;0.0001), education(AOR\u0026thinsp;=\u0026thinsp;1.362, 95% CI 1.04\u0026ndash;1.784;p\u0026thinsp;=\u0026thinsp;0.025), and occupation status (AOR\u0026thinsp;=\u0026thinsp;0.852,95% CI 0.736\u0026ndash;0.987, p\u0026thinsp;=\u0026thinsp;0.032) showed a significant association with the cryptosporidiosis prevalence; however, there was no statistically significant associations between cryptosporidiosis prevalence and animal contact, water source, type of toilet facility, age, gender, overcrowding, location, type of animals reared in household, and marital, even though higher proportions of infection were observed among individuals with daily animal contact 209/367(56.9%),those using surface water 196/344 (57%), flush toilets 107/172 (62.2%), participants aged 60\u0026ndash;64 years 9/10 (90%), males 91/157 (58%), households with six or more members 58(60.4%), residents of Hai (72.2%), Mbulu (66.7%) Korogwe (59.2%), and those keeping non-ruminant animals 37/63 (58.7%), as shown in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. Whereas, among the latter category, gender (AOR\u0026thinsp;=\u0026thinsp;0.558, 95% CI 0.323\u0026ndash;0.965, p\u0026thinsp;=\u0026thinsp;0.037), age (AOR\u0026thinsp;=\u0026thinsp;0.561, 95% CI 0.413\u0026ndash;0.778, p\u0026thinsp;=\u0026thinsp;0.0001), disposal of animal waste(AOR\u0026thinsp;=\u0026thinsp;0.06,95% CI 0.76\u0026ndash;6.9, p\u0026thinsp;=\u0026thinsp;0.0001), management practice(AOR\u0026thinsp;=\u0026thinsp;0.374, 95%CI 0.141\u0026ndash;0.992, p\u0026thinsp;=\u0026thinsp;0.048), animal species (AOR\u0026thinsp;=\u0026thinsp;0.743, 95% CI 0.549\u0026ndash;1.006, p\u0026thinsp;=\u0026thinsp;0.05), cleanliness of the animal house (AOR\u0026thinsp;=\u0026thinsp;0.039, 95%CI, 0.005\u0026ndash;0.282, p\u0026thinsp;=\u0026thinsp;0.001) and hind legs (AOR 25.796, 95%CI 7.876\u0026ndash;84.485, p\u0026thinsp;=\u0026thinsp;0.0001) were statistically significant associated with infection rate of cryptosporidiosis, however, diarrhea, breed, location, overcrowding, and water source were not significantly associated with prevalence of cryptosporidiosis nonetheless higher prevalence was recorded among livestock presented with diarrhea 19/26 (73.1%), belonged to local breed 143/209(68.4%), originated from Hai (82%), Korogwe (72%), and Mbulu (60.5%), were kept under grouped housing 270/412 (65.4%), and consumed surface water, 127/179 (70.9%), as shown in Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePrevalence and risk factors for cryptosporidiosis among livestock keepers\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNo sample\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNo (100%) positive of cryptosporidium based on categories\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePrevalence\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAOR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"9\"\u003e\n \u003cp\u003eAge(years)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e0\u0026ndash;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003e1.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003e0.672\u0026ndash;1.594\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003e0.875\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e6\u0026ndash;17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14(40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e18\u0026ndash;59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e304\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e178\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e178(58.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e60\u0026ndash;64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9(90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e65+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11(47.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"9\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e91(58%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.782\u0026ndash;2.096\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.325\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e218\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e121\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e121(55.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"9\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eNo education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45(52.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e1.362\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e1.04\u0026ndash;1.784\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e0.025*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003ePrimary Education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e174\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e89(50.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eSecondary Education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60(63.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003ePost Secondary Education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18(90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"9\"\u003e\n \u003cp\u003e\u003cstrong\u003eOccupation status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eLivestock keeping\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e341\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e201\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e201(58.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.852\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.736\u0026ndash;0.987\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.032*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eNon-Livestock keeping\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11(32.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"9\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11(35.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.623\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.267\u0026ndash;1.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.272\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e342\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e201\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e201(58.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eDivorced\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"9\"\u003e\n \u003cp\u003e\u003cstrong\u003eHIV status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.122\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.062\u0026ndash;0.241\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.0001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e269\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e129\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"9\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiarrhea\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e104(67.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e3.078\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e1.658\u0026ndash;5.715\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.0001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e221\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e108(48.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"9\"\u003e\n \u003cp\u003e\u003cstrong\u003eType of toilet facility\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003ePit Latrine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e155\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e90(58.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e1.208\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e0.769\u0026ndash;1.896\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e0.412\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eFlush latrine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e172\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e107\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e107(62.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eNo facility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15(31.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"9\"\u003e\n \u003cp\u003e\u003cstrong\u003eMaterial used in Hand hygiene\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSoap and water\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e281\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e148(52.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e1.497\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e1.218\u0026ndash;1.841\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e0.0001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSoil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1(33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWater\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63(69.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"9\"\u003e\n \u003cp\u003e\u003cstrong\u003eContact with animals\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDaily\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e367\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e209\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e209(56.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e1.298\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.389\u0026ndash;4.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.672\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRarely\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3(37.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"9\"\u003e\n \u003cp\u003e\u003cstrong\u003eSource of drinking water\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eSurface water\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e344\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e196\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e196(57%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.017\u0026ndash;2.157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eGround water\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16(51.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"9\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of individuals living in a household\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e2 people\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30(53.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.625\u0026ndash;1.385\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.722\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e3\u0026ndash;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e223\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e124\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e124(55.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e6\u0026ndash;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58(60.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"9\"\u003e\n \u003cp\u003e\u003cstrong\u003eType of animals in the household\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eRuminants\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38(54.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e0.955\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e0.844\u0026ndash;1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e0.464\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eNon-ruminant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37(58.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eMixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e242\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e137\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e137(56.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"9\"\u003e\n \u003cp\u003e\u003cstrong\u003eGeographic location (District-wise)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eSimanjiro\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20(32.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003e0.739\u0026ndash;1.195\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003e0.614\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eHai\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52(72.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eKorogwe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48(59.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eMbulu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50(66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eMoshi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42(49.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003eTable 2 indicates the risk factors associated with cryptosporidiosis among livestock keepers, including sociodemographic characteristics, diarrhea, HIV status, water source, hygiene practice, geographical location, number of people, and the type of animals in the household. The associations between variables and cryptosporidiosis are presented as an adjusted odds ratio (AOR) with a 95% confidence interval (CI) and corresponding p-values, whereby (*) represents statistically significant at p\u0026lt;0.05.\u003c/p\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePrevalence and risk factors for cryptosporidiosis among Livestock\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNo sample\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNo (100%) positive of cryptosporidium based on categories\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePrevalence\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAOR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003eAge (months)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u0026ndash;6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e172\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e123\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e123(71.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e0.561\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e0.413\u0026ndash;0.778\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e0.0001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u0026ndash;24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67(60.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e143\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e82(57.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e79(59%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.558\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.323\u0026ndash;0.965\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.037*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e291\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e193\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e193(66.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003e\u003cstrong\u003eManagement system\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eExtensive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e219\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e131(59.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.374\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.141\u0026ndash;0.992\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.048*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSemi-intensive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e206\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e141\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e141(68.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003e\u003cstrong\u003eBreed\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLocal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e209\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e143\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e143(68.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.435\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.484\u0026ndash;4.256\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.515\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eImproved\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e129(59.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003e\u003cstrong\u003eSource of drinking water\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSurface\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e179\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e127(70.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.316\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.46\u0026ndash;2.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGround\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e246\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e145\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e145(58.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003e\u003cstrong\u003eDisposal of animal waste\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnhygienic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e234\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e167(71.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.023\u0026ndash;0.161\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.0001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHygienic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e191\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e105\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e105(55%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiarrhea\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19(73.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e1.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.624\u0026ndash;5.487\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.267\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e399\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e253\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e253(63.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003e\u003cstrong\u003eCleanliness of the animal house\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22(78.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.005\u0026ndash;0.282\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e397\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e250(63%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003e\u003cstrong\u003eType of animal house\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIndividual\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2(16.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e5.663\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.823\u0026ndash;38.963\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.078\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGroups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e413\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e270\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e270(65.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003e\u003cstrong\u003eCleanliness of the hind legs\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32(43.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e25.796\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e7.876\u0026ndash;84.485\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.0001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e351\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e240\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e240(68.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnimal species\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCattle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e281\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e193\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e193(68.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.743\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.549\u0026ndash;1.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.05*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGoat\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40(53.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSheep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26(63.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePigs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10(41.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDogs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3(75%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003e\u003cstrong\u003eGeographical location\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHai\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e82(82.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.729\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.463\u0026ndash;1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.175\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMoshi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45(56.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSimanjiro\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37(44.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMbulu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49(60.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKorogwe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59(72%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003eTable 3 shows the risk factors associated with cryptosporidiosis among livestock, including sociodemographic characteristics, diarrhea, water source, hygiene practice, geographical location, and type of animal house. The associations between variables and cryptosporidiosis are presented as an adjusted odds ratio (AOR) with a 95% confidence interval (CI) and corresponding p-values, whereby (*) represents statistically significant at p\u0026lt;0.05.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eCryptosporidiosis is an enteric disease that infects the gastrointestinal tracts of both humans and animals. Although it has zoonotic potential, most research in Tanzania has focused on human cases (Hugho et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The present study investigated the prevalence of cryptosporidiosis in both livestock and livestock keepers. Employing modified Ziehl-Neelsen techniques, it also identified the risk factors for the disease. The overall human prevalence reported in this study was 56.5%. which was lower than reported in Bangladesh (77%) and higher than that reported in Ethiopia (48%)(Korpe et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2016\u003c/span\u003e, Hailu et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Additionally, the overall livestock prevalence was 64%. This result is aligned with the prevalence reported in Northern China (63.6%), but this prevalence differs from the findings reported in Cameroon (44.5%) (Wang et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2024\u003c/span\u003e, Siama et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The observed variation of prevalence may be attributed to differences in study design, including sample size, geographical location, and age structure of the population, as well as the diagnostic techniques used.\u003c/p\u003e\u003cp\u003eSeveral factors, such as age, occupation, water source, animals contact, gender, diarrhea, geographical location, education, HIV, and marital status, play a major role in the current prevalence among livestock keepers, whereas the management system, breed, age, gender, water source, hygiene practice, type of house, disposal animal waste and animals species contribute to higher prevalence among livestock.\u003c/p\u003e\u003cp\u003eCryptosporidiosis has been reported in people from 0 to 80 years; however, the current findings show that individuals aged 60\u0026ndash;64 and 18\u0026ndash;59 years were more exposed and infected 90% and 59.6%, respectively. This finding is similar to the study from Iran and Turkey, which reported a higher prevalence among individuals aged 30\u0026ndash;59 and the elders (Sinyangwe \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2016\u003c/span\u003e, Nouraftab et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, Orak et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, the present study contrasts with a study from Pakistan that reported higher infection rates among children under five years of age (Khan et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The higher burden may be explained by variation in environmental factors, including source of drinking water and contact with pets, poor hygiene practices, such as hand washing before meals and after using the toilet, as well as fruit and vegetable washing before eating. Also, this may be attributed to the number of population structures seeking medical care at health facilities during the data collection.\u003c/p\u003e\u003cp\u003eMoreover, the present study indicates that male individuals from Mbulu, Hai, and Korogwe reported a higher prevalence of cryptosporidiosis compared to females. This finding aligns with a study from Zambia reporting that male individuals were 1.3 times more at higher risk compared to their female counterparts (Sinyangwe \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). This may be justified by the fact that males, particularly those from Mbulu and Korogwe, are more involved in livestock keeping than females, and hence they are more exposed to the infection agents through frequent contact with animals compared to females. However, the high prevalence among male individuals from Hai district by poor hygiene practices, such as hand washing before meals and after daily activities that involve contact with animals, including grazing, animal care, and slaughtering(Terfa and Getushe \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFurthermore, the finding also suggests that individuals who use surface water(p\u0026thinsp;=\u0026thinsp;0.18) for hand hygiene(p\u0026thinsp;=\u0026thinsp;0.0001), and flush toilets (p\u0026thinsp;=\u0026thinsp;0.412) were likely more at risk of having cryptosporidiosis. This result aligns with findings from Pakistan and Zambia (Sinyangwe et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, Abbas et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), which identified surface water as a major reservoir for \u003cem\u003eCryptosporidium\u003c/em\u003e spp. oocysts and a key route of exposure.\u003c/p\u003e\u003cp\u003eA study's results showed that individuals with higher education were at a higher risk of having cryptosporidiosis compared to those with lower education. This finding differs from a study conducted in Qatar (Boughattas et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) which reported that individuals who had an elementary school education were more infected with cryptosporidiosis(p\u0026thinsp;=\u0026thinsp;0.025) than those with higher education. The likelihood of participants with higher education to have cryptosporidiosis may be caused by poor hygiene practices, such as ingesting contaminated water and food, using contaminated water to wash hands before meals and after using the toilet, particularly during medical research, and travel.\u003c/p\u003e\u003cp\u003eA comparative analysis of our study revealed that individuals who presented with diarrhea (104), 67.5%, were significantly more likely to be infected with cryptosporidiosis. (AOR\u0026thinsp;=\u0026thinsp;3.078, 95%CI, 1.658\u0026ndash;5.715, p\u0026thinsp;=\u0026thinsp;0.0001) than those without diarrhea. These findings align with a study done in Pakistan, which likewise found an increased risk of \u003cem\u003eCryptosporidium\u003c/em\u003e infection among individuals with diarrhea(Khan et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eCryptosporidiosis has been reported among immunocompromised individuals. This is justifiable with our result that revealed that the HIV status was statistically significantly associated with the prevalence of cryptosporidiosis (AOR\u0026thinsp;=\u0026thinsp;0.122, 95% CI 0.062\u0026ndash;0.241). Also, this finding aligns with a study from Zambia and North West Ethiopia reporting that the immunocompromised status was statistically significant with \u003cem\u003eCryptosporidium\u003c/em\u003e infection(Sinyangwe \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2016\u003c/span\u003e, Tamrat et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), suggesting that these individuals are at higher risk of infection because of immunosuppression.\u003c/p\u003e\u003cp\u003eOur study results showed that cryptosporidiosis is prevalent in animals under the age of six months. This finding aligns with the studies from Spain, Ethiopia, Egypt, Kuwait, Cameroon, and Kenya (Ogendo \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, D\u0026iacute;az et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Berhanu et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, Gattan et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, Tamrat et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2024\u003c/span\u003e, Siama et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) which found that the prevalence of cryptosporidiosis decreased as livestock age increased. The likelihood of young animals being susceptible to cryptosporidiosis could be due to their immature immunity, which fails to fight against infection. Nevertheless, it is important to recognize that both young and adult infected animals play a significant role in disease transmission because they both eliminate oocysts in their feces (Thomson et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2017\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eFurthermore, the study revealed that female animals are more likely to have cryptosporidiosis than their male counterpart. Similar observations have been reported from China among Equus(Li et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This higher likelihood of female animals having cryptosporidiosis is attributed to a weaker body immunity at certain periods in their physiologic cycle (Eze et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), but it could also be due to a higher level of animal-human contact, particularly during milking, making them more susceptible than male animals.\u003c/p\u003e\u003cp\u003eAdditionally, the study reported that unhygienic disposal of animal waste, especially near a water source, increases the risk of contamination, resulting in waterborne transmission. This finding aligns with the studies from Kuwait, Brazil, and Egypt that reported that a lack of hygienic conditions helps spread infections [20, 35, 39]. The environmental context also supports this link, as domestic animals (e.g., cattle, goats, sheep) and wildlife often access surface water sources like rivers and ponds, potentially introducing \u003cem\u003eCryptosporidium\u003c/em\u003e oocysts through fecal contamination [40]. These findings emphasize the importance of improving water, sanitation, and hygiene (WASH) practices by limiting animal access to water sources and strengthening WASH services to reduce the environmental spread and human exposure to \u003cem\u003eCryptosporidium\u003c/em\u003e oocysts.\u003c/p\u003e\u003cp\u003eMoreover, studies reported that excretion of oocysts was frequently related to the presence of diarrhea; however, our data indicate that asymptomatic animals also eliminate oocysts, therefore, they may play an important role in contaminating the environment, hence, facilitating the transmission(Thomson et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Additionally, the study revealed that cryptosporidiosis is associated with management practices, with higher cases recorded in semi-intensive systems. This finding aligns with findings from Brazil and Cameroon that reported semi-intensive rearing (OR\u0026thinsp;=\u0026thinsp;0.2, p\u0026thinsp;=\u0026thinsp;0.024) as a risk factor (Concei\u0026ccedil;\u0026atilde;o et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Siama et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). This may be attributed to ingesting contaminated food and water, and contact with infected animals or their feces, particularly in mixing herds and crowded housing.\u003c/p\u003e\u003cp\u003eFurthermore, our results showed that the prevalence of cryptosporidiosis was significantly associated with animal species, with dogs, cattle, and sheep being at greater risk than goats and pigs. This result aligns with a study from Uganda that reported that the dogs were 50 times at risk of having \u003cem\u003eCryptosporidium\u003c/em\u003e infection than goats and pigs(Kankya et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This may be attributed to the management practice used for keeping dogs, which allows them to roam freely, resulting in exposing them to infectious agents through ingesting contaminated water and food.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur findings indicated that cryptosporidiosis is highly prevalent among livestock and livestock keepers in Northern Tanzania, suggesting that livestock can harbor and shed the \u003cem\u003eCryptosporidium\u003c/em\u003e oocysts that contaminate the environment, thereby infecting humans. Also, the concentration of this burden among male individuals suggests a need for a targeted community education program aiming to reach the population at risk and reduce exposure and control infection in the livestock too. Moreover, based on our study findings, there is also a need for further studies on larger samples to understand other factors that may be associated with cryptosporidiosis, including identifying circulating species and genotypes among both animal and human populations in the study areas and beyond.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThis study was funded by the\u0026nbsp;University of Dar es Salaam Higher Education for Economics for Transformation (UDSM-HEET) project.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eAuthor contribution\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by HK, BL, BN, and ES. The first draft of the manuscript was written by HK, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u0026rdquo;\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eInformed consent was obtained from all individual participants included in the study. Additionally, written informed consent was obtained from the parents.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eConsent to publish\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe authors affirm that human research participants provided informed consent for publication of this data.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe authors extend sincere appreciation to the Local authorities for granting permission to carry out this study and to all participants for their willingness to take part. Additionally, special thanks are due to the research assistants who worked diligently to support data and sample collection during the conduct of this study. We also thank the University of Dar es Salaam Higher Education for Economics for Transformation (UDSM-HEET) project for financing this survey.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.\u0026rdquo;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbbas, Z., M. K. Khan, R. Z. Abbas, Z. u. D. Sindhu, M. S. Sajid, A. Munir, A. Wahid, A. Zafar, M. A. S. Mughal and M. Imran (2022). \u0026quot;Molecular epidemiology of Cryptosporidium parvum and Giardia lamblia in different water bodies, soil, and vegetables in Pakistan.\u0026quot; \u003cu\u003eHealth security\u003c/u\u003e \u003cstrong\u003e20\u003c/strong\u003e(4): 308-320https://doi.org/10.1089/hs.2021.0118.\u003c/li\u003e\n\u003cli\u003eAbdullah, D., S. Ola-Fadunsin, K. Ruviniyia, F. Gimba, P. 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(2024). \u0026quot;Foodborne Disease Estimates.\u0026quot; from https://www.who.int/data/gho/data/themes/who-estimates-of-the-global-burden-of-foodborne-diseases.\u003c/li\u003e\n\u003cli\u003eWidmer, G., P. C. K\u0026ouml;ster and D. Carmena (2020). \u0026quot;Cryptosporidium hominis infections in non-human animal species: revisiting the concept of host specificity.\u0026quot; \u003cu\u003eInternational journal for parasitology\u003c/u\u003e \u003cstrong\u003e50\u003c/strong\u003e(4): 253-262https://doi.org/10.1089/hs.2021.0118.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-parasitic-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jopd","sideBox":"Learn more about [Journal of Parasitic Diseases](https://www.springer.com/journal/12639)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/jopd/default.aspx","title":"Journal of Parasitic Diseases","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Cryptosporidiosis, Livestock keepers, Prevalence, Risk factors, Zoonosis","lastPublishedDoi":"10.21203/rs.3.rs-7705991/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7705991/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCryptosporidiosis is a zoonotic disease caused by the \u003cem\u003eCryptosporidium species\u003c/em\u003e, affecting both animals and humans, with a significant impact on young animals, children, and immunocompromised individuals. This study aimed to determine the prevalence and risk factors for cryptosporidiosis among livestock and livestock keepers in northern Tanzania. This was a cross-sectional survey that was conducted in northern Tanzania from September 2024 to February 2025 to screen livestock keepers and their livestock for cryptosporidiosis using modified Ziehl-Neelsen staining. Data on risk factors were collected through structured questionnaires and animal checklists. The prevalence of cryptosporidiosis in livestock and livestock keepers was estimated using descriptive statistics, while the association between variables was analyzed using logistic regression. Multivariate logistic analysis was employed to assess risk factors for disease. The overall prevalence of cryptosporidiosis among livestock keepers was 56.5% (212/425). A higher proportion of males tested positive, at 58% (91), compared with females, at 55.5% (121). The highest prevalence occurred in the 60\u0026ndash;64 age group, with a prevalence of 9/10 (90%). Cryptosporidiosis was statistically associated with education (p\u0026thinsp;=\u0026thinsp;0.024), occupation (p\u0026thinsp;=\u0026thinsp;0.033), HIV status(p\u0026thinsp;=\u0026thinsp;0.0001), diarrhea(p\u0026thinsp;=\u0026thinsp;0.0001), and hand hygiene (0.0001). Among livestock, 64% (272/425) were positive for cryptosporidiosis, with greater prevalence in females (66.3%). Cryptosporidiosis was significantly influenced by gender(p\u0026thinsp;=\u0026thinsp;0.037), management practice(p\u0026thinsp;=\u0026thinsp;0.048), species (p\u0026thinsp;=\u0026thinsp;0.05), disposal of wastes (p\u0026thinsp;=\u0026thinsp;0.0001), cleanliness of hind legs (p\u0026thinsp;=\u0026thinsp;0.0001), and age (p\u0026thinsp;=\u0026thinsp;0.0001). These findings indicate that cryptosporidiosis is prevalent among livestock and livestock keepers, highlighting the need for targeted community education to reduce exposure and control the infection.\u003c/p\u003e","manuscriptTitle":"Prevalence and Risk factors for Cryptosporidiosis among Livestock and Livestock keepers in northern Tanzania","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-14 09:21:45","doi":"10.21203/rs.3.rs-7705991/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2025-11-04T15:19:11+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-04T08:30:30+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Journal of Parasitic Diseases","date":"2025-10-22T16:22:56+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-21T10:13:32+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Parasitic Diseases","date":"2025-10-19T09:43:32+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-parasitic-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jopd","sideBox":"Learn more about [Journal of Parasitic Diseases](https://www.springer.com/journal/12639)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/jopd/default.aspx","title":"Journal of Parasitic Diseases","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"48782d31-4129-4b30-aa95-c589e11cb83d","owner":[],"postedDate":"November 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-11-14T09:21:45+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-14 09:21:45","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7705991","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7705991","identity":"rs-7705991","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}