Poultry intensification through hatchery vaccination: Implications for women’s empowerment in Nigeria and Tanzania

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Campbell, Humphrey Jumba, Adolf Jeremiah, Ekundayo Arogundade, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8918389/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 13 You are reading this latest preprint version Abstract Background Vaccination is a strategy for protecting productivity gains in Africa’s poultry sector and supporting intensification of small scale producers. Transitions from semi-intensive to intensive systems are rare because they require infrastructure, inputs, and market access — resources women often struggle to obtain compared with men. This mixed-methods study assessed the impact of introducing hatchery vaccination of day-old chicks in medium-sized hatcheries, of welfare benefits for chicken keepers, and implications for gender equality as production intensifies. Results Over five years, the market-based intervention introduced 137 million vaccinated chicks through six hatcheries in Tanzania and 16 million through seven hatcheries in Nigeria. One larger hatchery in Tanzania, with a chick distribution model based on the Poultry Multiplication Initiative, contributed disproportionately more chicks. There was no measurable impact in Nigeria, partly because of lower sales volumes, economic volatility, and a weaker intervention pathway. In Tanzania, the program increased flock size and cash income from poultry, but not total household income. Surprisingly, producers with <200 birds also benefited, likely through access to vaccinated older chicks brooded by mother units or semi-intensive producers. Field Technicians provided extension and linked chicken keepers to hatcheries, but they were few and focused on large, existing customers. There was no impact on the empowerment scores of men or women in either country. Work balance contributed to women’s disempowerment. Qualitative findings showed that as women intensified production and sometimes out-earned husbands, men could feel disrespected and restrict business growth; alternatively, some men invested in women-founded enterprises, but at the cost of women’s control. In Tanzania, where flock sizes increased, the proportion of women achieving adequacy in autonomy over income use declined (66% to 55%), whereas respect among household members increased (43% to 63%). Although not statistically significant, these trends suggest trade-offs for women during intensification. Conclusion Hatchery vaccination can increase flock size and income under high-uptake conditions, including for smaller scale producers, particularly by engaging larger hatcheries with established distribution models. The intervention did not improve women’s empowerment or cause harm. Respect within households and women’s work balance and autonomy over income are indicators to monitor during intensification. Women’s empowerment poultry chickens commercialization hatchery vaccination gender smallholder Africa vaccines Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Background While “the chicken is women’s livestock” in traditional systems where women often manage and own poultry, in some contexts, intensification has been associated with increased male involvement in management, decision-making, and financial control, particularly where enterprises become more profitable or require greater capital investment [1]. Transitions from semi-intensive to intensive farming are neither gradual nor frequent because of the required investments in infrastructure and access to reliable inputs and markets, meaning smallholders intensifying are often the better-off farmers [2]. The resources required to make the difficult transition toward commercialization – investment capital, land, inputs, and market access – are those that women in agriculture systematically struggle to access compared to their male counterparts [3]. Non-commercial livestock activities are often in the domain of women, whereas men tend to dominate commercial activities [4]. While there are few gender-disaggregated studies showing women’s involvement in commercial poultry keeping in Sub-Saharan Africa, small studies such as one with 257 randomly selected poultry farmers in Kano, Nigeria suggest that women are fewer as intensification increases. Among those with 500 or more chickens, only 27% of the sampled producers were women [5]. This raises the question of how the intensification of small-scale producers in low and middle income countries can be supported while allowing women to continue enjoying the benefits. Interventions supporting livestock intensification can lead to both positive impacts for women including increased income, resiliency to shocks, opportunities to expand their livestock portfolio into a business, greater ability to make decisions about their time and workload, and increased freedom of movement [6,7]. While livestock intensification provides pathways for gains in aspects of women’s empowerment, it requires gender equitable dynamics and norms. The following four factors can be considered as part of a conducive environment for livestock interventions to be empowering for women: recognition as farmers, access to resources, access to opportunities, and effective decision-making power. When these conditions are not met, there is a greater risk of unintended negative consequences, such as more work without corresponding compensation [8,9]. In a scoping review of 102 studies that measured the effect of livestock interventions on women’s empowerment, women’s labor or workload was the most negatively affected indicator, underscoring how livestock interventions generally rely on women’s labor in their design or do not address inequitable gender dynamics and division of labor in the household [6]. A study of women milk marketers in Kenya described the trade-offs they faced when navigating dairy system intensification in their communities, such as whether to sell milk frequently on the informal market for small payments or sell infrequently to a dairy co-operative for a large payment which she is less likely to control [10]. Research on intensification in the poultry sector has focused on development-style interventions in animal husbandry and access to veterinary inputs, especially farm-level vaccines, with the goal of alleviating poverty or improving food security. Many of these initiatives, especially vaccination for Newcastle disease, have led to modest increases in flock size in traditional and improved backyard systems [11–13]. The downstream benefits of poultry intervention packages ranged from no change in mother and child micronutrient adequacy in Burkina Faso to causal improvement in boys’ and girls’ growth scores in Kenya [14]. These studies have focused on Sector 4 producers, those with traditional and improved backyard production systems with up to 200 birds [15] (Figure 1). The Poultry Multiplication Initiative (PMI) is an example of an intervention that takes a broader approach to include more intensified producers. The PMI is a poultry value chain model that scales private sector delivery of improved chicks to small-scale producers (SSPs) [16]. The term SSP includes Sector 4 and Sector 3 producers (semi-intensive and emergent commercial producers). We interchangeably refer to this group of people as SSPs, chicken keepers, and poultry producers to balance the connotations and assumptions associated with each term. PMI engages hatcheries and brooder units, Sector 3 poultry producers who raise chicks to approximately 28 days of age (teen chicks) and sell them in their area. PMI was implemented in eight countries, delivering over 100 million day-old chicks (DOCs) to rural farmers through private sector partners in Nigeria, Tanzania, and Zimbabwe. This study describes a market-driven intervention that aimed to benefit chicken keepers by introducing hatchery vaccination of DOCs in mid-sized African hatcheries through the PREVENT project (PRomoting and Enabling Vaccination Efficiently, Now and Tomorrow). Through the collaboration between GALVmed, a UK-based NGO specializing in developing animal health products that serves small-scale livestock producers and Ceva Santé Animale, a French animal health company, 31 hatcheries in 11 countries were equipped to vaccinate DOCs [17]. The target diseases for vaccination were Infectious Bronchitis (IB), Newcastle disease (ND), Gumboro or Infectious Bursal Disease (IBD), Marek’s Disease, Mycoplasma, and Fowl Pox. Working with medium-sized hatcheries was an intentional strategy to reach smaller scale farmers because they are often non-integrated, meaning as independent businesses, they sell chicks directly to commercial farmers. In contrast, integrated hatcheries are a single company that owns the breeding flock, hatchery, and processing plant, and chicks are often sold in large batches through contracts. The project relied on Field Technicians, extension officers employed at the hatchery or engaged by the project as independent consultants, to sell vaccinated DOCs produced by the hatcheries to farmers (Figure 2). There were two research questions. 1) To what extent will the provision and adoption of vaccinated Day Old Chicks (VDOCs) enable the measurable progression of SSPs? 2) What are the consequences for gender equality as small-scale poultry production intensifies? Methods Study design The mixed methods study was designed to inform, evaluate, and understand the impact of the project intervention. Of the 11 participating countries, Tanzania and Nigeria were selected purposively to host gender research. We used four data sources to address the research questions, with their respective methods described below: hatchery data, gender qualitative study, impact evaluation, and the FT monitoring and evaluation (M&E) survey. Hatchery data VDOC production data and vaccination coverage (estimates of the proportion of hatchery chicks vaccinated) were self-reported by each hatchery and shared with Ceva as part of their private partnership. These data provided a context for the intensity and nature of the intervention in each country based on the performance of the participating hatcheries. Gender study The goal of the qualitative gender study was to understand the gender dynamics within the poultry sector that might change during intensification, inform quantitative indicators for impact evaluation and M&E, flag potential unintended negative consequences, and understand the context underlying some of the impact evaluation quantitative findings. The baseline consisted of focus group discussions with livestock keepers disaggregated by gender and production system [18], focusing on empowerment indicators including decision-making, control of income, and project specific topics such as perceptions of women who are successfully intensifying in the poultry industry. Respondents were purposively chosen by community mobilizers with the goal of representing chicken keepers of various backgrounds within the study area. After enumerators explained the study, those who chose to continue gave written consent or a thumbprint. Key informants included animal health professionals, hatchery workers, and brooders. The study sites were purposively selected to be near hatcheries enrolled in the project (Table 1). The findings informed quantitative indicators in the impact evaluation and the FT monitoring and evaluation. The qualitative endline used a different tool from baseline (Additional files 1 and 2). The endline guides focused on empowerment indicators of interest from the baseline impact evaluation such as respect by household members and work balance, and discussants were invited to separate groups based on whether they had achieved high or low empowerment scores (using the threshold of a 75% score indicating adequacy in empowerment for that indicator). We added in-depth interviews for Field Technicians given their important role in the intervention and youth poultry producers, especially unmarried youth, because they were under-represented in the impact evaluation. All research activities were recorded, then interviews were transcribed and translated into English by the enumerators who conducted the fieldwork and uploaded into NVivo for thematic analysis by co-authors. Table 1. Summary of the research activities, timelines, locations, and sample sizes in the PREVENT project. Tanzania-specific information in regular font, Nigeria in italics. Activity Date Method Target Location Sample size Gender baseline Nov 2021 FGDs, KIIs Poultry keepers (men and women, Sector 3 and 4), veterinarians and other value chain actors Iringa & Pwani, Tanzania Oyo State, Nigeria 6 KIIs, 66 FGD participants 5 KIIs, 29 FGD participants Impact evaluation baseline Apr – Aug, 2023 Household survey, quasi-experimental counterfactual design. Subsample WELI. Poultry keepers (men and women, Sector 3 and 4) Arusha, Dar es Salaam, Iringa, Kilimanjaro, Morogoro, Pwani Regions Delta, Ekiti, Kaduna, Kogi, Kwara, Lagos, Ogun, Ondo, Osun, and Oyo State 1,812 SSPs, 344 WELI subsample 1,844 SSPs, 436 WELI subsample FT M&E survey Jul 2023-Dec 2024 Longitudinal M&E survey at extension visits Poultry keepers visited by Field Technicians Same as impact evaluation 1,009 households with male and female respondents Gender endline Nov 2024 May-June, 2024 FGDs, KIIs, and IDIs (youth focus) with FGDs disaggregated by WELI scores Poultry keepers (men and women, Sector 3 and 4), veterinarians, brooders, Field Technicians Iringa Region Oyo State 10 KIIs, 8 IDIs, 30 FGD participants 8 KIIs, 4 IDIs, 27 FGD participants Impact evaluation endline Jun – Jul, 2025 Aug – Sep, 2025 Household survey, subsample WELI. Poultry keepers Same as baseline 1,567 SSPs (86% of baseline), 275 WELI (80% of baseline) 1,427 SSPs (77%), 329 WELI (75%) Impact evaluation The third data source was the quantitative impact evaluation led by Oxford Policy Management (OPM) that used a quasi-experimental counterfactual design to identify the causal impact of the intervention. The evaluation enrolled approximately 1,800 poultry-producing households each in Tanzania and Nigeria and followed up with the same households for an endline two years later. Treatment households were located within the catchment areas of participating hatcheries. Coursened Exact Matching (CEM) was used to identify an appropriate control group of poultry producers who were not geographically exposed to participating hatcheries. CEM was applied at three states: prior to the baseline using secondary data to select research locations, in the baseline survey sample, and based on the panel of households surveyed at both the baseline and endline to ensure balance was maintained despite survey attrition. Participants were given information about the study and those who chose to participate gave verbal consent. Outcome indicators fell into four categories: poultry production and market engagement (e.g. flock size and proportion of households purchasing VDOCs), income and expenditure (e.g. poultry net income and overall net income, husbandry practices (e.g. adoption of active feeding and use of non-vaccine medicines), and gender and empowerment. Other contextual data were collected such as the percentage of households that experienced shocks of different types. The evaluation matrix is provided in Additional file 3 and the survey tool in Additional file 4. A subset of men and women from the survey households were administered the Women’s Empowerment in Livestock Index (WELI). The WELI is a systematic way to measure empowerment to show program impact, build political commitment for gender equality, and allow for worldwide comparisons [19]. WELI measures empowerment across three domains: intrinsic agency (power within), instrumental agency (power to), and collective agency (power with), hence abbreviated as 3DE (three domains of empowerment). The 3DE index values were determined by aggregating 13 indicators: autonomy in income, self-efficacy, attitudes about intimate partner violence against women, respect among household members, input in productive decisions—general, input in productive decisions—livestock, ownership of land and other assets, access to and decisions regarding financial services, control over use of income, work balance, ability to visit important locations, group membership, membership in influential groups. All WELI domains, indicators, explanations, and definitions of adequacy are available in Additional file 5. A respondent’s empowerment score is the weighted average of her/his adequacy scores in the 13 indicators (all weighted 1/13). If her/his score is 75% or higher, s/he is classified as empowered [20]. We refer to these as high and low empowerment scores in the eligibility criteria for respondents in the qualitive endline. Field Technician M&E study FTs were financially incentived by the project to administer a short M&E questionnaire for the first ten households per month they visited for extension. Indicators included flock size, whether VDOCs were purchased within the last three months, and changes in workload. A man and a woman were registered for each household and the survey tool alternated who should be selected as the primary respondent for each visit. The goal was to identify any trends or negative consequences that could be addressed before the end of the project. The output was longitudinal data from 1,004 unique households visited during extension visits in Tanzania and Nigeria over a period of 18 months (questionnaire in Additional file 6). Study sites Nigeria and Tanzania were purposively selected for gender studies because they had participating hatcheries early in the project lifecycle, which gave more time for impact, and because they represent different regions within Sub-Saharan Africa. Nigeria’s poultry sector is one of the largest in Africa, with the largest annual egg production and second largest chicken population, second only to Egypt. Approximately 100 million of the country’s 180M estimated chickens are raised in semi- intensive or intensive systems. Despite rapid expansion, national production is estimated to meet only 30% of domestic demand for meat and eggs [21]. In contrast, Tanzania’s poultry sector is smaller, estimated at 83M chickens [22], less intensified, and the supply of indigenous chickens is estimated to meet more than 70% of the meat and egg demand in rural areas and up to 20% in urban areas [23]. The largest proportion of the national flock is kept under low-input and low-output traditional systems. The study sites were in multiple locations within each country to match the catchment areas of the participating hatcheries, except the control sites selected for the impact evaluation. Locations are described using high-level administrative divisions (regions for Tanzania and states for Nigeria) to protect the identity of the hatcheries, except Silverlands Tanzania hatchery in Iringa, Tanzania where we were given permission to refer to it by name. Qualitative gender research was conducted in a subset of purposively chosen locations hypothesized to have large program effects with the goal of understanding gender dynamics during intensification. These sites include Oyo State in Nigeria, a hub for poultry farming with the large urban population in Ibadan with an open air weekly market for poultry and Iringa Region in Tanzania, a region known for crop and livestock production in the southern highlands which hosts Silverlands Tanzania, one of the largest national hatcheries. Results Progression of SSPs The first research question asked about the extent to which the provision and adoption of improved inputs (VDOCs) and better flock management enable the measurable progression of SSPs. Following the Theory of Change (Figure 1), we outline the production of VDOCs at hatcheries, the uptake by different types of chicken keepers, and the potential impacts at household and individual levels. (Datasets in Additional files 7-8.) Of the 11 project countries where hatcheries partnered with CEVA, Tanzania stood out as the dominant contributor, producing approximately 27 million VDOCs per year across six hatcheries over the five years of the project (Table 2). This is a huge contribution given the national population estimate of 83 million chickens. Nigeria, with seven hatcheries joining later in 2022, had an estimated increase of only 3 million VDOCs, relative to an estimated national chicken population of 180 million [24]. While VDOC production and national chicken populations are not directly comparable, national census data can quickly become outdated and are susceptible to underreporting by livestock keepers [25], and chick mortality can be as high as 20% at farm level [26], the comparison highlights the scale of the project in Tanzania compared to Nigeria. Descriptions of the vaccines used are available in Additional file 9. Table 2. Numbers of VDOCs produced by hatcheries in Nigeria and Tanzania enrolled in the PREVENT project, 2021-2025. Country 2021 2022 2023 2024 2025 (+ projection)* Total Tanzania 2,110,805 15,635,583 29,672,981 39,936,967 20,767,575 (+29,363,009) 108,123,911 (137,486,920) Nigeria - 878,755 3,172,090 5,560,446 2,684,034 (+3,794,921) 12,295,325 (16,090,246) *The projections for the second half of 2025 were calculated by applying a factor of 1.385 to the actual data from the first half, based on an analysis of monthly seasonal patterns and historical ratios of the second semester to the first semester from the last three years. The Tanzania coverage rate (the percentage of DOCs produced by the participating hatcheries that were vaccinated) was 92%, which was likely due to the poor performance of one hatchery. Tanzania’s performance was heavily influenced by a large hatchery, Silverlands Tanzania, which was established in Iringa in 2014 [27]. They vaccinated 100% of their production of dual purpose chickens and layers with the full vaccine range (Mareks, ND, IBD and where necessary fowl pox and Mycoplasma gallisepticum ), delivering a “fully vaccinated chick.” They also benefited from a strong network of extension officers who provided biosecurity guidance and the mother‑unit model outlined by the PMI. In contrast, Nigeria’s landscape was very different. Small and medium hatcheries, typically producing approximately 1M DOC/year, vaccinated just 10–50% of their production, usually only against ND and IBDV. Vaccination coverage in Nigeria averaged only 55% across seven hatcheries, with the largest hatchery (11.8 million chicks) stagnating at 52%. A 30-year old man working as a Field Technician in Nigeria described that for the hatchery to vaccinate, a client needed to have a minimum order. Only 10% of my clients have taken vaccinated chicks. Some who don’t take the vaccination option say “doctor, don’t worry, we will combine our orders so that you can help us get the vaccinated chicks.” Small-scale farmers can’t really get them, unless they are buying up to 2,000 or 4,000 chicks at once. The quantitative evaluation found no meaningful program impact in Nigeria as measured by key indicators in the project’s sphere of influence including purchase of VDOCs and flock size. Consequently, there was no change in welfare indicators such as income from poultry and empowerment. In the qualitative endline from November 2024, all five focus group discussions included mentions of reducing flock size in response to poor economic conditions and the high cost of feeds and other inputs. External factors also played a role. The abrupt shift to digital payments in early 2023 just before the elections [28], cash shortages [29], the removal of fuel subsidies in May 2023 [30] , and the resulting financial pressures reduced hatcheries’ ability to invest in hatchery vaccination and farmers’ willingness to pay a premium for fully vaccinated chicks. The inflation rate in Nigeria was over 30% from February to December 2024 [31]. Domestic producers receive some protection through the ban on imported chicken meat first introduced in 2003, but smuggled poultry meat continues to enter the country [32]. Taken together, the macroeconomic volatility and the lower vaccination coverage and sales volumes of the participating hatcheries meant the causal pathway of increased access and adoption of VDOCs did not activate in Nigeria, which helps explain the absence of detectable production or welfare effects. A 38-year old veterinarian and brooder from Oyo State spoke of the changes she had observed in the sector because of difficult economic conditions. There has been a marked difference in the way things are now. Every day, there is a rise in the cost of inputs. In the last two years, we used to exhaust over two tons of maize alone as a feed ingredient, but it is not so now. Most farmers have reduced the number of birds that they have and the number of farmers has reduced. Some have left layer bird production and migrated to broiler production, which is only seasonal (during the festive season). The rate at which we sell veterinary drugs has also reduced. In contrast, PREVENT had an impact in Tanzania, beginning with an increase in flock size. Sector 3 households kept 230 more chickens than expected without the program (Figure 3). For Tanzanian Sector 4 households, the increases were smaller in absolute terms but statistically clearer. Treatment households kept about eight more chickens on the survey day and about 18 more birds three months earlier than expected without PREVENT. Given that Sector 4 flocks are usually a few dozen chickens, this represents a meaningful expansion. What was the role of VDOCs in flock size increases? Unlike in Nigeria, where one fifth of Sector 4 farmers reported VDOC purchases at endline, Tanzanian Sector 4 farmers rarely purchased VDOCs at baseline or endline. Approximately 40 percent of Tanzanian Sector 3 treatment households reported buying VDOCs in the three months before both the baseline and endline surveys. Among Tanzanian Sector 3 treatment households, intake (defined as hatching, buying, or receiving chickens in other ways) increased from 573 chickens at baseline to 775 at the endline. Among Sector 4 households, intake rose from about 12 to about 27 chickens. The increase in chicken purchases in Sector 3 appears to have been led by increased VDOC purchase. For Sector 4, we observe a clear increase for non-VDOC chicken purchases, while the estimate for VDOC purchases is positive but not statistically significant. This suggests that Sector 4 households bought more chickens overall, not only VDOCs (Figure 4). Reduced mortality was another benefit to households that could have driven the flock size increase, but the effects were only significant for Secor 4 households (5% reduction in Tanzania and 3% in Nigeria). For Sector 3 households in both countries, the estimated effects are small and not statistically significant. Impact estimates showed that Sector 3 Tanzanian households earned an average of USD 1,632 more cash income from chickens and eggs over the last 12 months than they would have in the absence of PREVENT, while Sector 4 households earned approximately USD 188 more. However, we did not detect a program effect on net income from chickens and eggs or on total household net income for either sector. The treatment households reported buying more chickens, more feed, and spending more on medicines, so higher sales were accompanied by higher recurrent costs. The qualitative findings suggest hatchery vaccination may not reduce vaccine related expenses for many chicken keepers. Tanzanian men in Iringa were most confident about the vaccination status of chicks while some women were unsure if chicks were vaccinated, especially when they received them from agents who then explained the schedule for the continuation of farm vaccines. A woman with high WELI score keeping 500 layers explained “We don’t know if DOCs are vaccinated or not because we are told by the hatchery agents to vaccinate them on their 21st day.” In Oyo State, Nigeria, the presence of multiple hatcheries, an open air market for poultry including DOCs, and extremely competitive pricing for chicks contributed to a lack of confidence from respondents in chick vaccination status unless they had personal experience with a trusted hatchery. A 39-year old man with 1,000 birds and a low empowerment score remembered buying inexpensive chicks from a new supplier, doubting their vaccination status, and vaccinating again. “It was discovered that the birds have been vaccinated against Marek’s initially, so the resulting mortality was my fault because of the double dose.” While vaccine expenses may not have been reduced due to misinformation, PREVENT appears to have helped Tanzanian households generate more revenue, but not yet to keep more of it as profit due to reinvestment in recurrent production costs. The pathway to impact is clear for Sector 3 SSPs in Tanzania who were buying VDOCs, but less clear for Sector 4 households. Chicken keepers in Sector 4 bought more chickens but not VDOCs, yet somehow experienced less mortality, larger flock sizes, and a modest financial benefit to reinvest in recurrent costs in their chicken businesses. The PREVENT Theory of Change anticipated that Sector 3 producers would be the main customers of VDOCs, with Sector 4 using vaccinated teen chicks raised by brooders or mother units instead. While mother units were more common in the Nigeria impact evaluation survey, the endline survey in Tanzania identified only 17, most (15) of which served less than 20 SSPs. In the qualitative findings, no respondents in Iringa Region described buying teen chicks from a brooder; instead, they purchased directly from the hatchery or allowed their hens to hatch eggs. A woman brooder, who began keeping chickens in 2014, described the support she received from the hatchery. After the training, they gave me a loan of 500 chicks and feed. The hatchery officer used to pass by my home where I keep the chicks to see my progress. Many chicken farmers liked my way of keeping and were motivated by the large number of chicks I keep. One theory is that Sector 4 chicken keepers buy from fellow Sector 3 chicken keepers who fall upon hard times and sell early, serving as “accidental brooders.” In the baseline qualitative study, Sector 4 men in Pwani Region had lower access to hatchery chicks compared to their peers in Iringa who could access chicks through hatchery agents. This led to Sector 4 chicken keepers buying from “wherever chickens were available.” Meanwhile, while those in Sector 3 were less likely to describe their motivation for chicken-keeping as “to sell in case of a problem” than their Sector 4 counterparts, they sometimes sold before chickens reached maturity. At endline, of the 25% of Sector 3 households that experienced shocks, 36% reported selling chickens or eggs in response. Transitioning between sectors Lastly, we consider a specific type of progression of interest to development practitioners – the aspirational ascent from Sector 4 to Sector 3 (and vice versa), using the threshold of 200 chickens as our operational sector definition. While on average, the Tanzanian households were increasing their flock sizes, when we classified households at endline using the same flock-size rule that we used at baseline (based on the larger of “now” and “3 months ago”) 18% of Tanzanian households that started in Sector 3 then fell below the 200-chicken threshold, while only 8% of Sector 4 households moved up. One possible explanation is that Tanzanian Sector 3 was not a single, uniformly commercial group: some households were operating close to the Sector 3/Sector 4 cut-off and, depending on where they were in the production cycle at the endline, they could look like Sector 4 again. There was a sharper reclassification in Nigeria where a third (34%) of households that were Sector 3 at baseline would be classified as Sector 4 at endline, while 13% of Sector 4 households would now qualify as Sector 3. This two-way movement appears consistent with a more volatile operating environment, in which a sizeable proportion scaled back from a higher-input position, while a smaller group still managed to expand. Unfortunately, the impact evaluation required respondents from the baseline to remain in poultry production to be eligible for the endline, making it impossible to estimate how many may have left the business entirely. About half the qualitative endline research activities in Nigeria included mentions of the respondents or other reducing flock size of leaving the business entirely. One young man working as a FT wryly referred to this as “hanging up your feeders.” FT M&E data from Nigeria and Tanzania confirmed that most households stayed in the production system where they started, with more downward movement to less intensive production systems than upward movement to more intensive ones. Qualitative findings support that intensifying chicken production past a certain threshold, with the 200 bird cutoff being a reasonable estimate, is associated with a new set of requirements including capital for purchasing chicks, feed, and veterinary inputs to last until the chickens are sold or start laying, improved housing and land, and labor and time of dedicated household members or employees. While not quantified in this study due to the design, this is a threshold at which women start to drop out of poultry production. As a 27 year old male veterinarian in Nigeria explained: For the women, you can do 200 birds in your backyard, but when you are going into large-scale production, you actually relocate to the bush because birds make noise. In the qualitative baseline, respondents in Tanzania, Nigeria, and Zimbabwe responded to a hypothetical story about a woman named Amina who successfully grew her chicken business until one day, her husband called her to discuss it. Respondents acknowledged that Amina’s husband could respond positively or negatively, and that some of the activities or attitudes of a successful female agripreneur could be viewed as problematic. These included a woman out-earning her husband, interacting with male customers or animal health workers especially late at night, or neglecting to give sufficient time and energy to her husband, children, and other relatives. A Sector 3 woman in Oyo State, Nigeria reflects on Amina’s husband. Maybe the man is jealous she is doing better than him, that he is not getting her attention, and other men are eyeing her. She is getting more money. He might think one day she will not be submissive to him. He is afraid. Amina was also commended for being hard-working, committed, and an asset to her family. A Sector 3 man in Tanzania considered “perhaps Amina’s husband wanted to know if the business is suitable to be a family business.” While such an arrangement can be beneficial for the business, a husband’s investment can also be associated with reduced decision-making and control for the woman who started it. Gender norms, such as it being inappropriate for a woman to outearn her husband or boyfriend, can limit the ability of a woman to intensify. Empowerment The PREVENT program did not have a measurable impact on the empowerment of men and women poultry producers as measured by WELI 3DE scores, even in Tanzania where intensification occurred because of the program as evidenced by flock size increases. Despite this, we combine the quantitative and qualitative empowerment findings to understand the differences between Sector 3 and Sector 4 producers, identify trends in specific indicators of empowerment for Tanzania Sector 3 and 4 producers where hatchery vaccination increased flock sizes for many households, and explore why some Tanzanian men could feel disrespected by other household members or be unable to use income in line with their own values when keeping chickens. Given the eligibility criteria for enrolling people involved in chicken production, some empowerment indicators, such as input into livestock decisions and input into productive decisions, had high percentages of adequacy for respondents in both Nigeria and Tanzania at baseline and endline. In Nigeria, over 95% of female respondents in both sectors had adequacy in the self-efficacy indicator, defined as an individual’s internal belief in their own capabilities and rights to act and achieve their goals. A subset of empowerment indicators had lower percentages of adequacy and therefore more room for variability: autonomy in income, respect among household members, work balance, and mobility to important locations (<75% of Sector 4 female respondents in Tanzania and Nigeria had adequacy at baseline). For women in Sector 3 in both Tanzania and Nigeria, work life balance was a shared area of concern where only 57 and 38% of respondents achieved adequacy respectively. Sector 3 chicken keepers in treatment households in Tanzania experienced a significant increase in flock size, which could have changed the patterns of resource control and decision-making within the household. While the changes are not significant, we see a decrease in the proportion of women achieving adequacy in autonomy in income use (66% to 55%), an increase in self-efficacy (66% to 79%), an increase in respect among household members (43% to 63%), and a decrease in mobility to important locations (Figure 5). Work balance remains an indicator associated with high disempowerment. The bar graph for Sector 4 chicken keepers is in Additional file 10. A woman with a high WELI score who kept over 350 layers with her husband explained how income use and respect interact within her marriage. It affects us (women) since we have no power in decision-making. If you do something that your husband doesn’t agree with, he feels as if you disrespected him. This kind of situation happened to me once. I was given a pig from a group where I was a member. When I brought the pig home, he said if this pig will be kept here, it is not just yours, it is ours. I accepted, but after a while, he brought a buyer home and sold the pig without involving me. In this situation, it is hard for a woman to intensify poultry farming. Most women agreed that work balance was a challenge, with some citing support from their husbands or children and time management as strategies used to manage their responsibilities. A woman with a high WELI score in Sector 3 who recently managed to shift from local to improved chickens with her husband’s financial support explained. Honestly, the issue is real. Women are obviously overwhelmed by different responsibilities. From my understanding, this happens because of the patriarchal system. Since years back, the community believes that some activities cannot be done by men, and that’s why men don’t support their partners even when they are overwhelmed by responsibilities. In Tanzania, both men and women reported an increase in time spent on chicken management, with women indicating a slightly higher increase than their male counterparts (Figure 6). This suggests that while intensification may bring productivity gains, it also places additional demands on women's time. In contrast, in Nigeria, most men and women reported no significant changes in their work time. However, about 39% of the respondents, both male and female, experienced an increase, indicating that while the impact is less widespread than in Tanzania, it is still notable for a significant portion of the population. The reduction in mobility for Sector 3 women in Tanzania was not discussed in the endline qualitative tool, however at baseline, farmers described how time-intensive managing DOCs was, which could contribute to reduced mobility temporarily especially if less labor-intensive teen chicks were not available. Three additional barriers to intensifying into Sector 3 from the qualitative findings that were not well captured in WELI were access to land (required for Sector 3 due to the noise and waste management of more birds, especially near residential areas), access to capital and credit with appropriate terms, and for Sector 3 chicken keepers in Nigeria, security concerns caused by bandits and thieves while traveling between home and farm, especially during early or late hours. These barriers were mentioned by both men and women but experienced more acutely by women because of patriarchal laws and inheritance practices that favor men, multiple formal and informal factors that can make it easier for men to access credit or capital to invest in business, and the risk of sexual assault or rape by bandits in addition to theft and violence if the person moving through their area was a woman. In the WELI, a high proportion of respondents had adequate empowerment scores for access to credit, but the amount and terms were not specified, which the qualitative findings clarified often meant access to loans with lending periods too short for a cycle of poultry production, for amounts too small to be meaningfully invested, or prohibitively high interest rates. The ownership of assets indicator included questions about owning assets including livestock, land, and household goods. Men and women in Sector 3 or nearing the threshold acknowledged that renting property or keeping chickens near residences was problematic past a certain flock size. While in Tanzania and Nigeria, some women owned land, it was more difficult for women to purchase, and married women usually required their husband’s support to use shared land. Young, unmarried men and women were sometimes given family land to use temporarily for poultry business, although girls were less likely to be given land permanently because it was understood they would leave the family upon marriage. A woman with a high empowerment score who experimented with raising improved chickens commercially with her husband before returning to keeping local chickens explained. It’s true, a woman can’t have a larger piece of land than a man because men are more likely to be given land by their parents than women. So even if a married woman buys one acre, a husband is still a few steps ahead of her because the land will be owned by both of them. But if you understand one another, you can be free to use the land for anything. While the WELI sample size for men was small with over-representation from Sector 4, adequacy in two indicators was notably low: autonomy in income (29% adequacy at endline, N=41 ) and respect among household members (34% adequacy). There were fewer Sector 3 producers in the communities and it was difficult to find men at home. These were also the two indicators with the lowest percentages of adequacy for men in Nigeria (67% adequacy in autonomy in income use and 54% in respect among household members, N=72). The endline included only households interviewed at baseline. A man in Tanzania with a low empowerment score who kept 20 chickens in a village about 60 km from the nearest town explained why he wasn’t often able to spend income from chickens according to his own values and wishes. Others in the group agreed that their business and investment goals were easily superseded by unplanned family obligations. It is very difficult for men to stick to their goals when they have family to take care of. At least those who are not married may spend their income according to their goals and wishes. Sometimes, we men prioritize the family needs. A man in the second group with a low empowerment score keeping 69 local chickens described how household expenses, especially for education, were different from those in the past. In previous years, even education for children was not priority in many households, so the responsibilities requiring money were minor. Nowadays, education is compulsory and a priority. It requires collaboration so everything done in the household can be more profitable. Women are now focusing on the future, so if a man doesn’t involve his wife in production, there is a chance of being divorced. Young, unmarried chicken keepers were not represented in the WELI sample which required couples, so we intentionally interviewed youth in the endline. Two unmarried men in the Tanzania sample who were keeping chickens while living with their parents described being protected from contributing poultry income to family expenses so that they could grow their businesses. Men’s respect by household members came up in the Amina vignette at baseline for Tanzania and Nigeria, and was specifically addressed in a second vignette in Tanzania at endline to understand men’s low empowerment scores. In the second vignette, a happily married man, Mr. Sanga, kept chickens with his wife. They were described as sharing decision-making, income, and even routine tasks such as cleaning the chicken coop and collecting eggs. In the discussions with men who had low empowerment scores, respondents immediately identified the potential for Mr. Sanga to feel disrespected by friends and neighbors because of doing activities such as feeding and cleaning traditionally done by women. A woman will be happy because she feels that her husband is cooperative. But Sanga's neighbors and friends will perceive that he is being controlled . ( Man with low empowerment score) Women were also quick to mention that Mr. Sanga may feel disrespected, with many pointing to the wife’s behavior as a factor, such as discussing personal matters with people outside the home. The feeling of a man being disrespected is obviously caused by the wife. If I tell my fellow women that my husband is performing certain chicken keeping chores, it may give a picture that my husband is always under my control. When a husband hears the rumors, it will bring the feeling of not being respected. Sometimes men feel disrespected when they lack power to control income, especially from chicken keeping. (Woman with high empowerment score, Sector 4) The vignette was not used in Nigeria, with men with both high and low empowerment scores describing feeling proud of and respected for their involvement in the chicken business. Women also felt the work was respectable, as a 28-year old Sector 4 farmer with a low empowerment score explained. Poultry brings honor since you are not stealing. I have never been disrespected before. It is not a job where if a visitor comes, you will run away. A few women described being looked down upon when wearing dirty farm clothes, and one described people trying to shame her for choosing agricultural work after finishing higher education. A Sector 4 woman in her fifties with a high empowerment score reflected. The society we are in makes it look like as a woman, there are some areas you cannot be recognized. In Yoruba land, we believe that the man is the head of the woman. If they have not seen a man involved in what a woman is doing, it is perceived that the woman is not worth collaborating in business with. One potential unintended consequence the project monitored through the Field Technician M&E data was that with intensification, women might lose decision-making control they had previously had with a smaller flock. In Tanzania the opposite occurred: 53% of women and 44% of men who purchased VDOCs said they made more management decisions (Figure 7). While women maintaining or increasing their management decision-making relative to men is good news, as it suggests they are not being pushed out following intensification caused by the hatchery interventions, the qualitative findings outlined some pathways by which increased women’s decision-making and engagement in chicken-keeping can lead to increased workload and in some cases, husbands feeling disrespected which may lead them to limit or take over aspects of the business. Field Technicians In the final results section, we consider the role of Field Technicians. Field Technicians, a mixture of hatchery employees and independent consultants hired by the PREVENT project, were intended to be at the heart of the intervention, connecting SSPs with vaccinated chicks from the hatcheries. Many of the Theory of Change assumptions therefore focused on FTs; that there would be sufficient paravets to create a cadre of FTs, that farmers would trust them, that they could create a profitable business selling DOCs, and that FTs would not only deliver chicks but also provide extension – with a focus on women! Field Technicians had a busy schedule. About half (46 FTs) were hatchery employees, with day-to-day responsibilities in management, biosecurity protocols, diagnostic services, managing hatchery incubation, plus farmer visits. The remaining 39 FTs (46%) were independent consultants who had more flexibility to focus on farm visits. At endline, some FTs had been promoted within the hatchery or moved to other opportunities, suggesting it was perceived to be an entry-level position in some workplaces. A Nigerian FT in his thirties described his work on the sales team at a hatchery. I am an office person except for two days a week when we sell all the chicks that come from the hatchery. I am always in the middle of business. An FT in Tanzania employed by a hatchery described her farm visit routine. The region that she served is approximately 35,000 square kilometers. One of the questions I ask is the availability of men and women in the household so I can provide knowledge on chicken keeping for both and tell them the importance of working together in performing different responsibilities. I always go with the private animal health officer who responds to different challenges (especially diseases). It is done for free, the costs are paid by hatchery. My coverage area is the whole region, but I have not yet reached some areas. Over the duration of the project, 19 FTs in Tanzania and 16 FTs in Nigeria each completed an average of 536 and 380 farm visits, respectively. Despite this effort, there were relatively few FTs given the scope and geographic reach of the program. In Tanzania, only 13% of Sector 3 households and 2% of Sector 4 households at the endline reported being visited by an employee from a chick supply company to discuss VDOCs in the three months prior to the endline survey. These percentages are roughly the same at the baseline, where 14% of Sector 3 and 1% of Sector 4 households reported receiving such visits. In Nigeria, 14% of Sector 3 and 6% of Sector 4 treatment households at endline reported receiving these household visits within the three months prior to the survey. Again, these percentages are roughly the same as those observed at baseline. Consequently, there was no increase in the proportion of households reporting VDOC purchases in the three months before the survey in either country or sector, indicating that a small cadre of FTs was insufficient to reach new customers with VDOCs. Producers pausing on restocking or decreasing their flock sizes due to volatile input markets also limits the ability of FTs to sell DOCs. The two unique profiles of some FTs employed through hatcheries and some as independent consultants provided some insights into how the two models impact extension. Hatchery employees were more technically focused, running more standardized, prevention‑oriented visits, where advisory activities dominated (management, biosecurity, performance, and brooding). They were more likely to perform troubleshooting, necropsy, and sampling, consistent with stronger diagnostic training, access to laboratories, and a mandate for health surveillance to protect company reputation. Their fixed salary structure reduced commercial pressure and their geographically restricted zones allow for deeper follow-up. In contrast, the FTs who were employed as independent consultants were more productive, with 52 average visits/ quarter compared to 33 for hatchery employees, but they were weaker in diagnostics (<6% and <2% of visits included troubleshooting or necropsy, for example). Independent consultants leaned toward commercial activities because of their economic model, which combines service fees with sales commissions. They diversified their income streams through product sales and enjoyed the freedom to offer multiple brands. High visit volumes imposed time constraints, favoring shorter and less complex visits. On-demand treatments and vaccinations were similar for both profiles (Additional file 11). Incentive structures and workplace expectations for both types of FTs encouraged the prioritization of existing and large scale customers. Sector 4 chicken keepers, who represented 57% of the beneficiaries tracked by the Field Technicians, received only 30% of the services, while the largest-scale chicken keepers (representing 15% of the beneficiaries) received three times as many visits and five times as many vaccines. Unfortunately, partly due to the disproportionate number of women in Sector 4 compared to Sector 3, these extension models can reinforce existing gender inequalities. The project Theory of Change included “farmers provided management support (focus on women),” but lack of support for gender-responsive extension was flagged midway through implementation as an area without supporting activities. Gender-responsive extension involves taking gender differences into account and paying attention to the unique needs of women, men, girls, and boys. Acknowledging that other individual characteristics are also important to the way people engage with veterinary extension services, the ILRI Gender Team developed a training called “Social Extension.” The Social Extension training was delivered in a single session in Nigeria. At the qualitative endline, none of the four interviewed Field Technicians remembered anything about it, and no one could articulate a way to modify their extension to be more inclusive. In contrast, in Tanzania we piloted a five month Social Extension mentorship program for all 12 active Field Technicians [33]. After the program, all FTs could identify gender stereotypes in the poultry sector and most described changes in their extension to be more inclusive, primarily directing extension material to multiple household members without making assumptions about their role based on gender, age, or other social markers. The mentorship program was qualitatively evaluated and seemed most impactful for young men who had recently graduated compared to older participants. A male FT in Morogoro described the changes that he made. I educate men and women about chicken-keeping without bias. I also educate men to collaborate with their wives when they are planning their chicken- keeping budget. Since the mentorship program, there are already some families co-operating together in chicken-keeping. Adjustments to the training, workplace incentives, and size of the Field Technician team could be made to prioritize the specific goals of future projects, such as gender-responsive extension, reaching new clients with VDOCs, or providing producers with access to diagnostic services. Discussion PREVENT was a market-based program to support hatchery vaccination. The contrast between Tanzania and Nigeria illustrates how variation in market penetration, commercial uptake, and macro-economic conditions affect the detectability of impact. In Tanzania, the evaluation detected measurable improvements in flock size, mortality, and poultry cash income. Similar benefits are attributed to farm-level vaccination of poultry [11–13]. Hatchery vaccination delivers much of its value through avoided losses, which can be difficult to observe when disease outbreaks are sporadic and severe. When no outbreak occurs, vaccination appears as a cost, whereas when an outbreak occurs, the benefit is large but concentrated in a smaller share of households or production cycles. Poultry producers do not always know which hatchery vaccines were given and may duplicate efforts through on farm vaccination, which dilutes potential cost-saving benefits. This is consistent with a study of broiler farmers in Kenya where 82% of farmers reported being aware that the DOCs they acquired had been vaccinated, with 44% of those unaware of the specific vaccines administered [34]. In Tanzania, the increased cash income was reinvested into recurring poultry expenses, perhaps reflecting the commercialization dynamic explored in the Background that intensification increases both revenue and cost structures [2]. Another consideration is that PREVENT looks at incremental improvements in systems where many poultry producers, especially in Sector 3, were already vaccinating to some degree. That makes the counterfactual more conservative: gains are real, but smaller and harder to isolate. While effects appear modest at the household level, when delivered across large sales volumes, they accumulate into substantial system-level benefits. From a hatchery perspective, it can be hard to justify the cost of vaccination for a hatchery in a tight market context. Without trust in a reputable hatchery and knowledge about the likely return on investment of a hatchery chick, price-sensitive consumers may be attracted to less expensive chicks which are under-vaccinated or unvaccinated, failing to see the benefits if they mix with different vaccination statuses within or across production cycles. Similarly, farmers in Western Kenya didn’t invest in fertilizer that could increase profits, although they responded to nudges in the form of discounts [35]. Despite lower uptake of best practices for hatchery vaccination, Ceva reported the strongest commercial success in Nigeria because participating hatcheries moved from a situation of no demand to some demand for hatchery vaccination by non-integrated hatcheries. For Sector 3 chicken keepers, the purchase of VDOCs was a clear impact pathway, but for Sector 4 chicken keepers who bought more chicks but not necessarily VDOCs, the impact was surprising. Further, Silverlands Tanzania hatchery in Iringa uses the PMI model to support mother units, but few households in the impact evaluation study were identified as mother units. In reality, mother units that initially received loans from the hatchery to operate under a credit model now operate on a cash basis and often raise hybrid flocks with some of the birds sold at 28 days with remaining birds remaining for live market sale and egg production. This suggests the Sector 4 households purchase from Sector 3 neighbors who may not formally identify as mother units but sell part of their VDOC batch as teen chicks due to economic problems or as part of their business strategy, thereby derisking the chicks for the Sector 4 producers by rearing them past the sensitive brooding period and giving downstream positive effects. The unexpected movement of chicks into Sector 4 through Sector 3 SSPs and the success attributed to including a larger hatchery supports the potential of working with large-scale, integrated hatcheries that mostly sell to Sector 3 for impact on SSPs. By incorporating gender research throughout the project lifecycle from qualitative baselines and endlines, quantitative WELI, and indicators on decision-making and work balance in the monitoring and evaluation, we also asked “under what conditions can poultry continue to benefit women during intensification/ commercialization?” In Tanzania, there was no program impact on empowerment for men or women as measured by WELI 3DE scores. In some sense, this represents good news that the intensification caused by the program did not have unintended consequences in two main areas of concern identified in other livestock intervention studies: decision-making and work balance. While there were no measurable negative effects of the intervention, the vignettes in the qualitative research outlined theoretical pathways for husbands to disapprove of their wives out-earning them or growing a business at the expense of other domestic obligations. Men in Tanzania could feel a lack of respect from household members in certain scenarios such as when the wife appeared to be leading a successful business while the man contributed minimally or in menial tasks considered within the domain of women. Both these scenarios could lead to men either restricting the business growth or taking over. There was no evidence of this happening because of the PREVENT project intervention, although there were a small number of men in the WELI sample in Tanzania who reported extremely low adequacy in the respect from household members and autonomy of income indicators, which could set the stage for the dynamics described in the qualitative findings. The challenge of finding men at home for the WELI sample also suggests the men who were available may not have been a representative sample, perhaps more likely to be injured, unwell, or unemployed. In contrast to these findings, in a study of small-scale farmers in Machakos Kenya with WELI data for men and women, the proportion of men achieving adequacy in respect among household members was significantly higher than for women, although respect among household members was one of the indicators contributing to men’s disempowerment [36]. For women, we saw differences in a few WELI indicators that were not significant, but consistent with trade-offs during intensification identified in the qualitative data. We measured a decrease in the proportion of women achieving adequacy in autonomy in income use (66% to 55%), an increase in self-efficacy (66% to 79%), an increase in respect among household members (43% to 63%), and a decrease in mobility to important locations. Decreased autonomy in income use is consistent with a male takeover or capture of resources while an increase in respect is consistent with the qualitative findings from the Amina vignette where male and female respondents described the positive ways in which a successful female agripreneur could be viewed. These are specific indicators of women’s empowerment that should be further monitored to understand the trade-offs and shifts that occur during intensification, especially for household businesses in which multiple family members contribute in different ways. This may be less relevant in Nigeria, where many of the Sector 3 chicken businesses were run by a single household member with hired employees providing more labor as opposed to in Tanzania where labor was often provided by household members [18]. Finally, the study provided insight into the best models for linking hatcheries to chicken keepers for the delivery of DOCs. The FTs identified in the Theory of Change to provide this linkage were too few to reach new clients and were incentivized to spend most of their time on larger, existing clients. In a study mapping the movement of DOCs in Machakos, Kenya, only 36% of broiler farmers obtained chicks from hatchery sales agents; most sourced from veterinary drug stores [34]. Silverlands Tanzania’s strategy of incorporating the PMI mother unit model and working with private agents to buy and resell DOCs is part of their corporate strategy. If gender-responsive extension is a goal, FTs are likely to perpetuate gender inequities in their extension without further training and mentorship, as evidenced by the inability of the Nigeria FTs to describe ways of improving their extension to be more inclusive even after a one-time training session. Training opportunities that occur over a longer period of time with more interactions, such as the five-month Social Mentorship pilot with FTs in Tanzania, can be more effective at changing behavior [37]. This is consistent with a study of trainings for medical professionals which found the opportunity to practice skills was associated with more effective trainings [38]. Another strategy for supporting women through intensification is the Women in Business Model, which like PMI, was developed from learnings from the African Chicken Genetic Gains project [16]. The Women in Business model aimed to develop, promote and test women-led chicken businesses in Tanzania with the goal of promoting the economic empowerment of women and young graduate women and improving food and nutrition security of their households [39]. After public and private adoption by Tanzania’s Ministry of Livestock and Fisheries and AKM Glitters (a private hatchery) [40], it is currently being scaled to other regions within Tanzania and to neighboring countries [41]. The model supports young women who have recently graduated to self-employ in the poultry value chain as vendors and brooders in order to strengthen linkages between hatcheries and female SSPs. A limitation of the study was the insufficient time for impact between the rollout of VDOCs by the participating hatcheries and the endline assessment, especially considering that a cohort of layers could be kept for almost two years and the seasonality of some poultry diseases. Future projects would benefit from a longer timeline, especially when establishing contracts with private companies happens within the project timeline. The impact evaluation survey had sufficient power to detect program impact on indicators like flock size, but further analyses that narrowed in on subsets of the data, such as Sector 3 women in Tanzania, were underpowered. This was also true for analyses of subsets of the WELI sample or comparisons of specific WELI indicators, forcing us to report trends while triangulating findings with the qualitative results. The impact evaluation did not include those who dropped from poultry production due to the requirement for baseline respondents to still be in poultry production. The sampling strategies used by the project activities focused on representing both men and women chicken keepers, even alternating between male and female respondents in the M&E survey conducted by Field Technicians, which meant like many studies, the data could not be used to estimate the proportions of women and men in Sector 3 versus Sector 4. The requirement for FTs to submit data for their first ten extension visits each month may have contributed to bias towards existing or more accessible clients. Narrowing in on one site per country for the qualitative endline allowed for focus on mechanisms to impact, but selection of Iringa meant the findings were not generalizable to other communities within Tanzania because of the unique profile of Silverlands Tanzania as one of the largest hatcheries in the PREVENT project. Lastly, the social extension mentorship program piloted with the Tanzanian Field Technicians was promising but the qualitative impact assessment was limited and raised questions about how such programs change extension delivery, farmer results, and the extent to which such a program could be scaled. Conclusions When correctly implemented and fully adopted, hatchery vaccination protects against catastrophic disease loss, and can increase flock size and cash income for SSPs, including Sector 4 producers. While large, integrated hatcheries were not the project’s target partners, the successful engagement with Silverlands Tanzania, a large hatchery with established distribution models based on the PMI, supports inclusion of large hatcheries in future projects. Economic volatility and partial adoption of DOC vaccination in Nigeria eroded any detectable impact of the intervention. In Tanzania, input prices were described as high, and possibly one of the reasons why the increased cash income did not translate into increases in net poultry income or household income; the funds were generally re-invested in poultry production. While intensification neither improved empowerment scores or caused harm, the qualitative findings identified pathways for women to face consequences from their husbands if they out-earned them or neglected domestic responsibilities while intensifying poultry production and for men in Tanzania to feel a lack of respect among household members if they participated in menial activities considered for women and others perceived them to be sub-ordinate to their wives in the business. Future studies on intensification in the livestock or poultry sector could focus on the impact of gender training for extension workers such as the Social Extension Mentorship pilot and the benefit of incorporating variations of the PMI for chick dissemination that support women agripreneurs, such as the Women in Business model. Key indicators of empowerment to monitor during commercialization or intensification include respect among household members for men and women, and women’s work balance and autonomy of income. These indicators may shift before aggregate WELI 3DE scores reflect changes, so mixed methods studies are recommended to capture early changes. Abbreviations 3DE – Three domains of empowerment DOC – Day Old Chick FT – Field Technician IB – Avian Infectious Bronchitis IBD – Infectious Bursal Disease, or Gumboro ILRI – International Livestock Research Institute M&E – Monitoring and evaluation ND – Newcastle disease OPM – Oxford Policy Management PMI – Poultry Multiplication Initiative (previously known as African Poultry Multiplication Initiative) PREVENT - PRomoting and Enabling Vaccination Efficiently, Now and Tomorrow Sector 3 – Poultry production classification which includes semi-intensive and emergent commercial systems Sector 4 - Includes traditional and backyard systems SSP – Small-scale Producer VDOC – Vaccinated Day Old Chick WELI – Women’s Empowerment in Livestock Index Declarations Ethics approval and consent to participate All participants were over 18 years old and gave informed consent after the research team shared information about the activity including risks and the reminder that participation was voluntary. Participants gave written or thumbprint consent for the qualitative studies and verbal consent for the impact evaluation and Field Technician survey, in line with the ethical approvals below. The qualitative baseline and endline studies were approved by the International Livestock Research Institute (ILRI) Institutional Research Ethics Committee (IREC), reference numbers ILRI-IREC2021-39 and ILRI-IREC2021-39/1 (approval period 28 Sept 2021 – 27 Sept 2022) and ILRI-IREC2021-39/2 (approval period 16 Jan 2024 – 14 Jan 2025), respectively. The impact evaluation and Field Technician survey studies were approved by the National Health Research Ethics Committee in Nigeria, reference numbers NHREC/01/01/2007-16/03/2023 and NHREC/01/01/2007-23/07/2025 and the Tanzania Commission for Science and Technology in Tanzania, reference numbers 2023-45-NA-2022-385 and CST00001174-2025-2025-00425. Consent for publication Not applicable. Availability of data and materials The quantitative datasets generated during the current study are available as additional files. All study tools are provided, with the exception of the WELI tool, which is available from the corresponding author on request. Qualitative transcripts are not available due to challenges anonymizing them and limited value of secondary analyses without the proper context. Competing interests The authors declare that they have no competing interests. Funding This work was supported in whole by the Gates Foundation [Investment ID INV-005820]. The findings and conclusions contained within are those of the authors and do not necessarily reflect positions or policies of the Gates Foundation. This work was conducted as part of the CGIAR Sustainable Animal and Aquatic Foods (SAAF) Program. SAAF is part of CGIAR’s 2025-2030 Research Portfolio. SAAF works across Africa, Asia, and Latin America to improve access to nutritious foods while reducing emissions and supporting inclusive livelihoods. By combining livestock and aquatic systems, it develops integrated, climate- and environment-friendly solutions tailored to local contexts. CGIAR research is supported by contributions to the CGIAR Trust Fund (https://www.cgiar.org/funders/). CGIAR is a global research partnership for a food-secure future dedicated to transforming food, land, and water systems in a climate crisis. The PREVENT project is a partnership between Ceva Santé Animale and GALVmed. Authors' contributions Conceptualization by ZAC, HJ, LA, KT, and MD; Formal analysis by ZAC, HJ, AT, TK, SO; Funding acquisition by LA, KT, MD; Investigation by ZAC, HJ, AJ, EA; Methodology by ZA, HJ, KT, SO; Project administration by EA, LA, KT; Supervision by AJ, EA, SO; Visualization by AT, TK, SO; Writing – original draft by ZAC; Writing – reviewing and editing by all co-authors. All authors read and approved the final manuscript. Acknowledgements We thank Dr. Sunday Ofueg (Ceva Field Officer in Nigeria) and Dr. Lazaro Kapella (formerly at Ceva in Dar es Salaam) for their logistical support during fieldwork. Thank you to Pierre-Marie Borne at Ceva for data analysis and other program support. Thank you to Paul Bessel, Julie Koehler, and Stewart Bradnick for their insights that improved the final draft. We appreciate the Field Technicians, data collectors, and enumerators in Tanzania and Nigeria for making the project happen. Lastly, thank you to the chicken keepers for opening your doors to us throughout the project and sharing your perspectives and insights. References Abay, K., Tiruneh, H. A., Terfa, Z., Karugia, J., & Breisinger, C. (2025). How good are livestock statistics in Africa? Evidence from Ethiopia . IFPRI Blog. https://www.ifpri.org/blog/how-good-are-livestock-statistics-in-africa-evidence-from-ethiopia/ Assocle, S. (2026, January 22). 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Food Security , 8 (3), 507–520. https://doi.org/10.1007/s12571-016-0579-5 FAO. (2023). The status of women in agrifood systems. In The status of women in agrifood systems . https://doi.org/10.4060/cc5343en Galiè, A., Teufel, N., Korir, L., Baltenweck, I., Webb Girard, A., Dominguez-Salas, P., & Yount, K. M. (2018). The Women’s Empowerment in Livestock Index. Social Indicators Research , 142 (2), 799–825. https://doi.org/10.1007/s11205-018-1934-z Gelli, A., Becquey, E., Ganaba, R., Headey, D., Hidrobo, M., Huybregts, L., Verhoef, H., Kenfack, R., Zongouri, S., & Guedenet, Helli, A. (2017). Improving diets and nutrition through an integrated poultry value chain and nutrition intervention (SELEVER) in Burkina Faso: study protocol for a randomized trial. Trials , 18 , 412. https://trialsjournal.biomedcentral.com/articles/10.1186/s13063-017-2156-4 Goromela, E., Urassa, N., Omore, A., Gali, A., & Jeremiah, A. (2022). The effectiveness of ‘ business models ’ promoted by the Women in Business project and opportunities for improvement : a report (Number December). https://hdl.handle.net/10568/128523 Ibayi, E. L., Nyambura, J. N., Guyo, B. A., Moodley, A., & Muloi, D. M. (2025). Mapping the flow of commercial broiler day-old chicks in Kenya. Frontiers in Veterinary Science , 12 (December), 1–9. https://doi.org/10.3389/fvets.2025.1607825 Innovation for Poverty Action. (2025). Poverty Probability Index . https://www.povertyindex.org/about-us Jalal-Eddeen, S. (2025). Digital financialization through demonetization: disruption, fintech adoption and everyday endurance in Nigeria. Review of International Political Economy , 0 (0), 1–27. https://doi.org/10.1080/09692290.2025.2588287 Kaluwa, C., Oduma, J., Abdirahman, F. A., Kitoga, B. K., Opondoh, A. A., Muchibi, J., Bagnol, B., Rosenbaum, M., Onchaga, S., Stanley, M., & Amuguni, J. H. (2022). Using the Women Empowerment in Livestock Index (WELI) to Examine Linkages between Women Smallholder Livestock Farmers’ Empowerment and Access to Livestock Vaccines in Machakos County of Kenya: Insights and Critiques. Vaccines , 10 (11). https://doi.org/10.3390/vaccines10111868 Komolafe, B., Ayanfeoluwa, P., & Agbakwuru, S. O. J. (2023, February 14). Banks reject old naira notes as queues persist at ATMs. Vanguard . https://www.vanguardngr.com/2023/02/banks-reject-old-naira-notes-as-queues-persist-at-atms/#google_vignette Kryger, K., Thomsen, K., Whyte, M., & Dissing, M. (2010). Smallholder poultry production – livelihoods, food security and sociocultural significance. In Smallholder Poultry Production . http://www.fao.org/docrep/013/al674e/al674e00.pdf Mbaegbu, R., & Nwanze, C. (2025, March 19). AD958: Nigerians say country is headed in wrong direction, oppose fuel-subsidy removal. AFR Barometer . https://www.afrobarometer.org/publication/ad958-nigerians-say-country-is-headed-in-wrong-direction-oppose-fuel-subsidy-removal/ Mramba, R. P., & Mwantambo, P. A. (2024). The impact of management practices on the disease and mortality rates of broilers and layers kept by small-scale farmers in Dodoma urban district, Tanzania. Heliyon , 10 (8). https://doi.org/10.1016/j.heliyon.2024.e29624 Musime, A. (2025). Understanding Mortality in Chicks: Causes, Prevention, and Best Practices . https://aaronvetfarms.com/understanding-mortality-in-chicks-causes-prevention-and-best-practices/ Nyaga, P. N. (2007). Poultry Sector Country Review: Kenya. FAO Poultry Sector Country Review , 3–9. Odunze, E., Boussini, H., Mikecz, O., & Pica-Ciamarra, U. (2018). Livestock and livelihoods spotlight Nigeria: Cattle and poultry sectors. Food and Agriculture Organization, Africa Sustainable Livestock 2050 , 11–12. Otiang, E., Campbell, Z., Thumbi, S. M., & Palmer, G. (2020). Mortality as the primary constraint to enhancing nutritional and financial gains from poultry: A multi-year longitudinal study of smallholder farmers in western Kenya. PloS One , 15 (5), e0233691. https://doi.org/https://doi.org/10.1371/journal.pone.0233691 Rashid, H., & Ndibalema, G. (2024). Empowering Tanzania’s women in business: Evaluating the readiness for scaling for two ILRI-designed gender empowerment tools . ILRI News. https://www.ilri.org/news/empowering-tanzanias-women-business-evaluating-readiness-scaling-two-ilri-designed-gender Silverlands Tanzania. (2025). About Us . https://www.silverlandstanzania.net/about-us Suleiman, M. S., Tafida, I., Nazifi, B., & Inuwa, S. I. (2023). Socio-economic analysis of gender participation in poultry production in Kano Metropolis, Nigeria. Federal University Dutsin-Ma Journal of Agriculture and Agricultural Technology , 9 (3). https://doi.org/https://doi.org/10.33003/jaat.2023.0903.11 Tavenner, K., Crane, T. A., & Saxena, T. (2021). “Breaking Even” under Intensification? Gendered Trade-Offs for Women Milk Marketers in Kenya*. Rural Sociology , 86 (1), 110–138. https://doi.org/10.1111/ruso.12345 Trading Economics. (2025). Nigeria Inflation Rate . https://tradingeconomics.com/nigeria/inflation-cpi World Poultry Foundation. (2022). Dual Purpose Poultry and Impact on African Households . https://worldpoultryfoundation.org/wp-content/uploads/2022/04/WPF-Poster.pdf Additional Declarations No competing interests reported. Supplementary Files Additionalfile5WELIindicators.pdf AdditionalFile11.png Additionalfile3.pdf AdditionalFile9Vaccinationvalencedistribution.pdf Additionalfile6FTquestionnaire.pdf AdditionalFile10.png Additionalfile1.pdf Additionalfile8aDatasetdescription.docx Additionalfile2.pdf Additionalfile4studytoolimpactevaluation.pdf Additionalfile7bNigeriaWELI.xls Additionalfile8dPREVENTFTbatchlog.xls Additionalfile7dTanzaniaWELI.xls Additionalfile8cPREVENTFTHHmembers.xls Additionalfile7aNigeriaimpactevaluation.xls Additionalfile7cTanzaniaimpactevaluation.xls Additionalfile8bPREVENTFTmaindata.xls Additionalfiles.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 07 Apr, 2026 Reviews received at journal 02 Apr, 2026 Reviews received at journal 30 Mar, 2026 Reviewers agreed at journal 23 Mar, 2026 Reviewers agreed at journal 20 Mar, 2026 Reviewers agreed at journal 09 Mar, 2026 Reviewers agreed at journal 02 Mar, 2026 Reviewers agreed at journal 24 Feb, 2026 Reviewers invited by journal 24 Feb, 2026 Editor assigned by journal 24 Feb, 2026 Editor invited by journal 24 Feb, 2026 Submission checks completed at journal 24 Feb, 2026 First submitted to journal 24 Feb, 2026 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. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8918389","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":598871951,"identity":"076db9b8-57ef-49e0-ad5b-b7b47fc86e09","order_by":0,"name":"Zoë A. 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17:22:38","extension":"docx","order_by":18,"title":"","display":"","copyAsset":false,"role":"supplement","size":16200,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfiles.docx","url":"https://assets-eu.researchsquare.com/files/rs-8918389/v1/88819b119985021dbf5f13df.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Poultry intensification through hatchery vaccination: Implications for women’s empowerment in Nigeria and Tanzania","fulltext":[{"header":"Background","content":"\u003cp\u003eWhile \u0026ldquo;the chicken is women\u0026rsquo;s livestock\u0026rdquo; in traditional systems where women often manage and own poultry, in some contexts, intensification has been associated with increased male involvement in management, decision-making, and financial control, particularly where enterprises become more profitable or require greater capital investment [1]. Transitions from semi-intensive to intensive farming are neither gradual nor frequent because of the required investments in infrastructure and access to reliable inputs and markets, meaning smallholders intensifying are often the better-off farmers [2]. The resources required to make the difficult transition toward commercialization \u0026ndash; investment capital, land, inputs, and market access \u0026ndash; are those that women in agriculture systematically struggle to access compared to their male counterparts [3]. Non-commercial livestock activities are often in the domain of women, whereas men tend to dominate commercial activities [4]. While there are few gender-disaggregated studies showing women\u0026rsquo;s involvement in commercial poultry keeping in Sub-Saharan Africa, small studies such as one with 257 randomly selected poultry farmers in Kano, Nigeria suggest that women are fewer as intensification increases. Among those with 500 or more chickens, only 27% of the sampled producers were women [5]. This raises the question of how the intensification of small-scale producers in low and middle income countries can be supported while allowing women to continue enjoying the benefits.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eInterventions supporting livestock intensification can lead to both positive impacts for women including increased income, resiliency to shocks, opportunities to expand their livestock portfolio into a business, greater ability to make decisions about their time and workload, and increased freedom of movement [6,7]. While livestock intensification provides pathways for gains in aspects of women\u0026rsquo;s empowerment, it requires gender equitable dynamics and norms. The following four factors can be considered as part of a conducive environment for livestock interventions to be empowering for women: recognition as farmers, access to resources, access to opportunities, and effective decision-making power. When these conditions are not met, there is a greater risk of unintended negative consequences, such as more work without corresponding compensation [8,9]. In a scoping review of 102 studies that measured the effect of livestock interventions on women\u0026rsquo;s empowerment, women\u0026rsquo;s labor or workload was the most negatively affected indicator, underscoring how livestock interventions generally rely on women\u0026rsquo;s labor in their design or do not address inequitable gender dynamics and division of labor in the household [6]. A study of women milk marketers in Kenya described the trade-offs they faced when navigating dairy system intensification in their communities, such as whether to sell milk frequently on the informal market for small payments or sell infrequently to a dairy co-operative for a large payment which she is less likely to control [10].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eResearch on intensification in the poultry sector has focused on development-style interventions in animal husbandry and access to veterinary inputs, especially farm-level vaccines, with the goal of alleviating poverty or improving food security. Many of these initiatives, especially vaccination for Newcastle disease, have led to modest increases in flock size in traditional and improved backyard systems [11\u0026ndash;13]. The downstream benefits of poultry intervention packages ranged from no change in mother and child micronutrient adequacy in Burkina Faso to causal improvement in boys\u0026rsquo; and girls\u0026rsquo; growth scores in Kenya [14]. These studies have focused on Sector 4 producers, those with traditional and improved backyard production systems with up to 200 birds [15] (Figure 1).\u0026nbsp;The Poultry Multiplication Initiative (PMI) is an example of an intervention that takes a broader approach to include more intensified producers. The PMI is a poultry value chain model that scales private sector delivery of improved chicks to small-scale producers (SSPs) [16]. The term SSP includes Sector 4 and Sector 3 producers (semi-intensive and emergent commercial producers). We interchangeably refer to this group of people as SSPs, chicken keepers, and poultry producers to balance the connotations and assumptions associated with each term. PMI engages hatcheries and brooder units, Sector 3 poultry producers who raise chicks to approximately 28 days of age (teen chicks) and sell them in their area. PMI was implemented in eight countries, delivering over 100 million day-old chicks (DOCs) to rural farmers through private sector partners in Nigeria, Tanzania, and Zimbabwe.\u003c/p\u003e\n\u003cp\u003eThis study describes a market-driven intervention that aimed to benefit chicken keepers by introducing hatchery vaccination of DOCs in mid-sized African hatcheries through the PREVENT project (PRomoting and Enabling Vaccination Efficiently, Now and Tomorrow). Through the collaboration between GALVmed, a UK-based NGO specializing in developing animal health products that serves small-scale livestock producers and Ceva Sant\u0026eacute; Animale, a French animal health company, 31 hatcheries in 11 countries were equipped to vaccinate DOCs [17]. The target diseases for vaccination were Infectious Bronchitis (IB), Newcastle disease (ND), Gumboro or Infectious Bursal Disease (IBD), Marek\u0026rsquo;s Disease, Mycoplasma, and Fowl Pox. Working with medium-sized hatcheries was an intentional strategy to reach smaller scale farmers because they are often non-integrated, meaning as independent businesses, they sell chicks directly to commercial farmers. In contrast, integrated hatcheries are a single company that owns the breeding flock, hatchery, and processing plant, and chicks are often sold in large batches through contracts. The project relied on Field Technicians, extension officers employed at the hatchery or engaged by the project as independent consultants, to sell vaccinated DOCs produced by the hatcheries to farmers (Figure 2).\u003c/p\u003e\n\u003cp\u003eThere were two research questions. 1) To what extent will the provision and adoption of vaccinated Day Old Chicks (VDOCs) enable the measurable progression of SSPs? 2) What are the consequences for gender equality as small-scale poultry production intensifies?\u0026nbsp;\u003c/p\u003e"},{"header":"Methods","content":"\u003ch2\u003eStudy design\u003c/h2\u003e\n\u003cp\u003eThe mixed methods study was designed to inform, evaluate, and understand the impact of the project intervention. Of the 11 participating countries, Tanzania and Nigeria were selected purposively to host gender research. We used four data sources to address the research questions, with their respective methods described below: hatchery data, gender qualitative study, impact evaluation, and the FT monitoring and evaluation (M\u0026amp;E) survey.\u003c/p\u003e\n\u003ch3\u003eHatchery data\u003c/h3\u003e\n\u003cp\u003eVDOC production data and vaccination coverage (estimates of the proportion of hatchery chicks vaccinated) were self-reported by each hatchery and shared with Ceva as part of their private partnership. These data provided a context for the intensity and nature of the intervention in each country based on the performance of the participating hatcheries.\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003eGender study\u003c/h3\u003e\n\u003cp\u003eThe goal of the qualitative gender study was to understand the gender dynamics within the poultry sector that might change during intensification, inform quantitative indicators for impact evaluation and M\u0026amp;E, flag potential unintended negative consequences, and understand the context underlying some of the impact evaluation quantitative findings. The baseline consisted of focus group discussions with livestock keepers disaggregated by gender and production system [18], focusing on empowerment indicators including decision-making, control of income, and project specific topics such as perceptions of women who are successfully intensifying in the poultry industry. Respondents were purposively chosen by community mobilizers with the goal of representing chicken keepers of various backgrounds within the study area. After enumerators explained the study, those who chose to continue gave written consent or a thumbprint. Key informants included animal health professionals, hatchery workers, and brooders. The study sites were purposively selected to be near hatcheries enrolled in the project (Table 1). The findings\u0026nbsp;informed quantitative indicators in the impact evaluation and the FT monitoring and evaluation. The qualitative endline used a different tool from baseline (Additional files 1 and 2). The endline guides focused on empowerment indicators of interest from the baseline impact evaluation such as respect by household members and work balance, and discussants were invited to separate groups based on whether they had achieved high or low empowerment scores (using the threshold of a 75% score indicating adequacy in empowerment for that indicator). We added in-depth interviews for Field Technicians given their important role in the intervention and youth poultry producers, especially unmarried youth, because they were under-represented in the impact evaluation. All research activities were recorded, then interviews were transcribed and translated into English by the enumerators who conducted the fieldwork and uploaded into NVivo for thematic analysis by co-authors.\u003c/p\u003e\n\u003cp\u003eTable 1. Summary of the research activities, timelines, locations, and sample sizes in the PREVENT project. Tanzania-specific information in regular font, \u003cem\u003eNigeria in italics.\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eActivity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMethod\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTarget\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLocation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSample size\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eGender baseline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eNov 2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003eFGDs, KIIs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003ePoultry keepers (men and women, Sector 3 and 4), veterinarians and other value chain actors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eIringa \u0026amp; Pwani, Tanzania\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eOyo State, Nigeria\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e6 KIIs, 66 FGD participants\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e5 KIIs, 29 FGD participants\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eImpact evaluation baseline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eApr \u0026ndash; Aug, 2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003eHousehold survey, quasi-experimental counterfactual design. Subsample WELI.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003ePoultry keepers (men and women, Sector 3 and 4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eArusha, Dar es Salaam, Iringa, Kilimanjaro, Morogoro, Pwani Regions\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eDelta, Ekiti, Kaduna, Kogi, Kwara, Lagos, Ogun, Ondo, Osun, and Oyo State\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e1,812 SSPs, 344 WELI subsample\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e1,844 SSPs, 436 WELI subsample\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eFT M\u0026amp;E survey\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eJul 2023-Dec 2024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003eLongitudinal M\u0026amp;E survey at extension visits\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003ePoultry keepers visited by Field Technicians\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eSame as impact evaluation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e1,009 households with male and female respondents\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eGender endline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eNov 2024\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eMay-June, 2024\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003eFGDs, KIIs, and IDIs (youth focus) with FGDs disaggregated by WELI scores\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003ePoultry keepers (men and women, Sector 3 and 4), veterinarians, brooders, Field Technicians\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eIringa Region\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eOyo State\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e10 KIIs, 8 IDIs, 30 FGD participants\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e8 KIIs, 4 IDIs, 27 FGD participants\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eImpact evaluation endline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eJun \u0026ndash; Jul, 2025\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eAug \u0026ndash; Sep, 2025\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003eHousehold survey, subsample WELI.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003ePoultry keepers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eSame as baseline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e1,567 SSPs (86% of baseline), 275 WELI (80% of baseline)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e1,427 SSPs (77%), 329 WELI (75%)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003eImpact evaluation\u003c/h3\u003e\n\u003cp\u003eThe third data source was the quantitative impact evaluation led by Oxford Policy Management (OPM) that used a quasi-experimental counterfactual design to identify the causal impact of the intervention. The evaluation enrolled approximately 1,800 poultry-producing households each in Tanzania and Nigeria and followed up with the same households for an endline two years later. Treatment households were located within the catchment areas of participating hatcheries. Coursened Exact Matching (CEM) was used to identify an appropriate control group of poultry producers who were not geographically exposed to participating hatcheries. CEM was applied at three states: prior to the baseline using secondary data to select research locations, in the baseline survey sample, and based on the panel of households surveyed at both the baseline and endline to ensure balance was maintained despite survey attrition.\u0026nbsp;Participants were given information about the study and those who chose to participate gave verbal consent.\u003c/p\u003e\n\u003cp\u003eOutcome indicators fell into four categories: poultry production and market engagement (e.g. flock size and proportion of households purchasing VDOCs), income and expenditure (e.g. poultry net income and overall net income, husbandry practices (e.g. adoption of active feeding and use of non-vaccine medicines), and gender and empowerment. Other contextual data were collected such as the percentage of households that experienced shocks of different types. The evaluation matrix is provided in Additional file 3 and the survey tool in Additional file 4.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA subset of men and women from the survey households were administered the Women\u0026rsquo;s Empowerment in Livestock Index (WELI).\u0026nbsp;The WELI is a systematic way to measure empowerment to show program impact, build political commitment for gender equality, and allow for worldwide comparisons [19]. WELI measures empowerment across three domains: intrinsic agency (power within), instrumental agency (power to), and collective agency (power with), hence abbreviated as 3DE (three domains of empowerment). The 3DE index values were determined by aggregating 13 indicators: autonomy in income, self-efficacy, attitudes about intimate partner violence against women, respect among household members, input in productive decisions\u0026mdash;general, input in productive decisions\u0026mdash;livestock, ownership of land and other assets, access to and decisions regarding financial services, control over use of income, work balance, ability to visit important locations, group membership, membership in influential groups. All WELI domains, indicators, explanations, and definitions of adequacy are available in Additional file 5. A respondent\u0026rsquo;s empowerment score is the weighted average of her/his adequacy scores in the 13 indicators (all weighted 1/13). If her/his score is 75% or higher, s/he is classified as empowered [20]. We refer to these as high and low empowerment scores in the eligibility criteria for respondents in the qualitive endline.\u003c/p\u003e\n\u003ch3\u003eField Technician M\u0026amp;E study\u003c/h3\u003e\n\u003cp\u003eFTs were financially incentived by the project to administer a short M\u0026amp;E questionnaire for the first ten households per month they visited for extension. Indicators included flock size, whether VDOCs were purchased within the last three months, and changes in workload. A man and a woman were registered for each household and the survey tool alternated who should be selected as the primary respondent for each visit. The goal was to identify any trends or negative consequences that could be addressed before the end of the project. The output was\u0026nbsp;longitudinal data from 1,004 unique households visited during extension visits in Tanzania and Nigeria over a period of 18 months (questionnaire in Additional file 6).\u003c/p\u003e\n\u003ch2\u003eStudy sites\u003c/h2\u003e\n\u003cp\u003eNigeria and Tanzania were purposively selected for gender studies because they had participating hatcheries early in the project lifecycle, which gave more time for impact, and because they represent different regions within Sub-Saharan Africa. Nigeria\u0026rsquo;s poultry sector is one of the largest in Africa, with the largest annual egg production and second largest chicken population, second only to Egypt. Approximately 100 million of the country\u0026rsquo;s 180M estimated chickens are raised in semi- intensive or intensive systems. Despite rapid expansion, national production is estimated to meet only 30% of domestic demand for meat and eggs [21]. In contrast, Tanzania\u0026rsquo;s poultry sector is smaller, estimated at 83M chickens [22], less intensified, and the supply of indigenous chickens is estimated to meet more than 70% of the meat and egg demand in rural areas and up to 20% in urban areas [23]. The largest proportion of the national flock is kept under low-input and low-output traditional systems. The study sites were in multiple locations within each country to match the catchment areas of the participating hatcheries, except the control sites selected for the impact evaluation. Locations are described using high-level administrative divisions (regions for Tanzania and states for Nigeria) to protect the identity of the hatcheries, except Silverlands Tanzania hatchery in Iringa, Tanzania where we were given permission to refer to it by name. Qualitative gender research was conducted in a subset of purposively chosen locations hypothesized to have large program effects with the goal of understanding gender dynamics during intensification. These sites include Oyo State in Nigeria, a hub for poultry farming with the large urban population in Ibadan with an open air weekly market for poultry and Iringa Region in Tanzania, a region known for crop and livestock production in the southern highlands which hosts Silverlands Tanzania, one of the largest national hatcheries.\u003c/p\u003e"},{"header":"Results","content":"\u003ch2\u003eProgression of SSPs\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThe first research question asked about the extent to which the provision and adoption of improved inputs (VDOCs) and better flock management enable the measurable progression of SSPs. Following the Theory of Change (Figure 1), we outline the production of VDOCs at hatcheries, the uptake by different types of chicken keepers, and the potential impacts at household and individual levels. (Datasets in Additional files 7-8.)\u003c/p\u003e\n\u003cp\u003eOf the 11 project countries where hatcheries partnered with CEVA, Tanzania stood out as the dominant contributor, producing approximately 27 million VDOCs per year across six hatcheries over the five years of the project (Table 2). This is a huge contribution given the national population estimate of 83 million chickens. Nigeria, with seven hatcheries joining later in 2022, had an estimated increase of only 3 million VDOCs, relative to an estimated national chicken population of 180 million [24]. While VDOC production and national chicken populations are not directly comparable, national census data can quickly become outdated and are susceptible to underreporting by livestock keepers [25], and\u0026nbsp;chick mortality can be as high as 20% at farm level [26], the comparison highlights the scale of the project in Tanzania compared to Nigeria. Descriptions of the vaccines used are available in Additional file 9.\u003c/p\u003e\n\u003cp\u003eTable 2. Numbers of VDOCs produced by hatcheries in Nigeria and Tanzania enrolled in the PREVENT project, 2021-2025.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCountry\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2021\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2022\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2023\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2024\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2025 (+ projection)*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003eTanzania\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e2,110,805\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e15,635,583\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e29,672,981\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e39,936,967\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e20,767,575 (+29,363,009)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e108,123,911\u003c/p\u003e\n \u003cp\u003e(137,486,920)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e878,755\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e3,172,090\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e5,560,446\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e2,684,034 (+3,794,921)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e12,295,325\u003c/p\u003e\n \u003cp\u003e(16,090,246)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*The projections for the second half of 2025 were calculated by applying a factor of 1.385 to the actual data from the first half, based on an analysis of monthly seasonal patterns and historical ratios of the second semester to the first semester from the last three years.\u003c/p\u003e\n\u003cp\u003eThe Tanzania coverage rate (the percentage of DOCs produced by the participating hatcheries that were vaccinated) was 92%, which was likely due to the poor performance of one hatchery. Tanzania\u0026rsquo;s performance was heavily influenced by a large hatchery, Silverlands Tanzania, which was established in Iringa in 2014 [27]. They vaccinated 100% of their production of dual purpose chickens and layers with the full vaccine range (Mareks, ND, IBD and where necessary fowl pox and \u003cem\u003eMycoplasma gallisepticum\u003c/em\u003e), delivering a \u0026ldquo;fully vaccinated chick.\u0026rdquo;\u0026nbsp;They also benefited from a\u0026nbsp;strong network of extension officers who provided biosecurity guidance and the mother‑unit model outlined by the PMI. In contrast, Nigeria\u0026rsquo;s landscape was very different. Small and medium hatcheries, typically producing approximately 1M DOC/year, vaccinated just 10\u0026ndash;50% of their production, usually only against ND and IBDV.\u0026nbsp;Vaccination coverage in Nigeria averaged only 55% across seven hatcheries, with the largest hatchery (11.8 million chicks) stagnating at 52%. A 30-year old man working as a Field Technician in Nigeria described that for the hatchery to vaccinate, a client needed to have a minimum order.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eOnly 10% of my clients have taken vaccinated chicks. Some who don\u0026rsquo;t take the vaccination option say \u0026ldquo;doctor, don\u0026rsquo;t worry, we will combine our orders so that you can help us get the vaccinated chicks.\u0026rdquo; Small-scale farmers can\u0026rsquo;t really get them, unless they are buying up to 2,000 or 4,000 chicks at once.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe quantitative evaluation found no meaningful program impact in Nigeria as measured by key indicators in the project\u0026rsquo;s sphere of influence including purchase of VDOCs and flock size. Consequently, there was no change in welfare indicators such as income from poultry and empowerment. In the qualitative endline from November 2024, all five focus group discussions included mentions of reducing flock size in response to poor economic conditions and the high cost of feeds and other inputs. External factors also played a role. The abrupt shift to digital payments in early 2023 just before the elections [28], cash shortages [29], the removal of fuel subsidies in May 2023 \u003cspan lang=\"EN-US\"\u003e[30]\u003c/span\u003e, and the resulting financial pressures reduced hatcheries\u0026rsquo; ability to invest in hatchery vaccination and farmers\u0026rsquo; willingness to pay a premium for fully vaccinated chicks. The inflation rate in Nigeria was over 30% from February to December 2024 [31]. Domestic producers receive some protection through the ban on imported chicken meat first introduced in 2003, but smuggled poultry meat continues to enter the country [32]. Taken together, the macroeconomic volatility and the lower vaccination coverage and sales volumes of the participating hatcheries meant the causal pathway of increased access and adoption of VDOCs did not activate in Nigeria, which helps explain the absence of detectable production or welfare effects.\u003c/p\u003e\n\u003cp\u003eA 38-year old veterinarian and brooder from Oyo State spoke of the changes she had observed in the sector because of difficult economic conditions.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThere has been a marked difference in the way things are now. Every day, there is a rise in the cost of inputs. In the last two years, we used to exhaust over two tons of maize alone as a feed ingredient, but it is not so now. Most farmers have reduced the number of birds that they have and the number of farmers has reduced. Some have left layer bird production and migrated to broiler production, which is only seasonal (during the festive season). The rate at which we sell veterinary drugs has also reduced.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIn contrast, PREVENT had an impact in Tanzania, beginning with an increase in flock size. Sector 3 households kept 230 more chickens than expected without the program (Figure 3). For Tanzanian Sector 4 households, the increases were smaller in absolute terms but statistically clearer. Treatment households kept about eight more chickens on the survey day and about 18 more birds three months earlier than expected without PREVENT. Given that Sector 4 flocks are usually a few dozen chickens, this represents a meaningful expansion.\u003c/p\u003e\n\u003cp\u003eWhat was the role of VDOCs in flock size increases? Unlike in Nigeria, where one fifth of Sector 4 farmers reported VDOC purchases at endline, Tanzanian Sector 4 farmers rarely purchased VDOCs at baseline or endline. Approximately 40 percent of Tanzanian Sector 3 treatment households reported buying VDOCs in the three months before both the baseline and endline surveys.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAmong Tanzanian Sector 3 treatment households, intake (defined as hatching, buying, or receiving chickens in other ways) increased from 573 chickens at baseline to 775 at the endline. Among Sector 4 households, intake rose from about 12 to about 27 chickens. The increase in chicken purchases in Sector 3 appears to have been led by increased VDOC purchase. For Sector 4, we observe a clear increase for non-VDOC chicken purchases, while the estimate for VDOC purchases is positive but not statistically significant. This suggests that Sector 4 households bought more chickens overall, not only VDOCs (Figure 4). Reduced mortality was another benefit to households that could have driven the flock size increase, but the effects were only significant for Secor 4 households (5% reduction in Tanzania and 3% in Nigeria). For Sector 3 households in both countries, the estimated effects are small and not statistically significant.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eImpact estimates showed that Sector 3 Tanzanian households earned an average of USD 1,632 more cash income from chickens and eggs over the last 12 months than they would have in the absence of PREVENT, while Sector 4 households earned approximately USD 188 more. However, we did not detect a program effect on net income from chickens and eggs or on total household net income for either sector. The treatment households reported buying more chickens, more feed, and spending more on medicines, so higher sales were accompanied by higher recurrent costs. The qualitative findings suggest hatchery vaccination may not reduce vaccine related expenses for many chicken keepers. Tanzanian men in Iringa were most confident about the vaccination status of chicks while some women were unsure if chicks were vaccinated, especially when they received them from agents who then explained the schedule for the continuation of farm vaccines. A woman with high WELI score keeping 500 layers explained \u0026ldquo;We don\u0026rsquo;t know if DOCs are vaccinated or not because we are told by the hatchery agents to vaccinate them on their 21st day.\u0026rdquo; In Oyo State, Nigeria, the presence of multiple hatcheries, an open air market for poultry including DOCs, and extremely competitive pricing for chicks contributed to a lack of confidence from respondents in chick vaccination status unless they had personal experience with a trusted hatchery. A 39-year old man with 1,000 birds and a low empowerment score remembered buying inexpensive chicks from a new supplier, doubting their vaccination status, and vaccinating again. \u0026ldquo;It was discovered that the birds have been vaccinated against Marek\u0026rsquo;s initially, so the resulting mortality was my fault because of the double dose.\u0026rdquo; While vaccine expenses may not have been reduced due to misinformation, PREVENT appears to have helped Tanzanian households generate more revenue, but not yet to keep more of it as profit due to reinvestment in recurrent production costs.\u003c/p\u003e\n\u003cp\u003eThe pathway to impact is clear for Sector 3 SSPs in Tanzania who were buying VDOCs, but less clear for Sector 4 households. Chicken keepers in Sector 4 bought more chickens but not VDOCs, yet somehow experienced less mortality, larger flock sizes, and a modest financial benefit to reinvest in recurrent costs in their chicken businesses. The PREVENT Theory of Change anticipated that Sector 3 producers would be the main customers of VDOCs, with Sector 4 using vaccinated teen chicks raised by brooders or mother units instead. While mother units were more common in the Nigeria impact evaluation survey, the endline survey in Tanzania identified only 17, most (15) of which served less than 20 SSPs. In the qualitative findings, no respondents in Iringa Region described buying teen chicks from a brooder; instead, they purchased directly from the hatchery or allowed their hens to hatch eggs. A woman brooder, who began keeping chickens in 2014, described the support she received from the hatchery.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAfter the training, they gave me a loan of 500 chicks and feed. The hatchery officer used to pass by my home where I keep the chicks to see my progress. Many chicken farmers liked my way of keeping and were motivated by the large number of chicks I keep.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eOne theory is that Sector 4 chicken keepers buy from fellow Sector 3 chicken keepers who fall upon hard times and sell early, serving as \u0026ldquo;accidental brooders.\u0026rdquo; In the baseline qualitative study, Sector 4 men in Pwani Region had lower access to hatchery chicks compared to their peers in Iringa who could access chicks through hatchery agents. This led to Sector 4 chicken keepers buying from \u0026ldquo;wherever chickens were available.\u0026rdquo; Meanwhile, while those in Sector 3 were less likely to describe their motivation for chicken-keeping as \u0026ldquo;to sell in case of a problem\u0026rdquo; than their Sector 4 counterparts, they sometimes sold before chickens reached maturity. At endline, of the 25% of Sector 3 households that experienced shocks, 36% reported selling chickens or eggs in response.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eTransitioning between sectors\u003c/h2\u003e\n\u003cp\u003eLastly, we consider a specific type of progression of interest to development practitioners \u0026ndash; the aspirational ascent from Sector 4 to Sector 3 (and vice versa), using the threshold of 200 chickens as our operational sector definition. While on average, the Tanzanian households were increasing their flock sizes, when we classified households at endline using the same flock-size rule that we used at baseline (based on the larger of \u0026ldquo;now\u0026rdquo; and \u0026ldquo;3 months ago\u0026rdquo;) 18% of Tanzanian households that started in Sector 3 then fell below the 200-chicken threshold, while only 8% of Sector 4 households moved up. One possible explanation is that Tanzanian Sector 3 was not a single, uniformly commercial group: some households were operating close to the Sector 3/Sector 4 cut-off and, depending on where they were in the production cycle at the endline, they could look like Sector 4 again. There was a sharper reclassification in Nigeria where a third (34%) of households that were Sector 3 at baseline would be classified as Sector 4 at endline, while 13% of Sector 4 households would now qualify as Sector 3. This two-way movement appears consistent with a more volatile operating environment, in which a sizeable proportion scaled back from a higher-input position, while a smaller group still managed to expand. Unfortunately, the impact evaluation required respondents from the baseline to remain in poultry production to be eligible for the endline, making it impossible to estimate how many may have left the business entirely. About half the qualitative endline research activities in Nigeria included mentions of the respondents or other reducing flock size of leaving the business entirely. One young man working as a FT wryly referred to this as \u0026ldquo;hanging up your feeders.\u0026rdquo; FT M\u0026amp;E data from Nigeria and Tanzania confirmed that most households stayed in the production system where they started, with more downward movement to less intensive production systems than upward movement to more intensive ones.\u003c/p\u003e\n\u003cp\u003eQualitative findings support that intensifying chicken production past a certain threshold, with the 200 bird cutoff being a reasonable estimate, is associated with a new set of requirements including capital for purchasing chicks, feed, and veterinary inputs to last until the chickens are sold or start laying, improved housing and land, and labor and time of dedicated household members or employees. While not quantified in this study due to the design, this is a threshold at which women start to drop out of poultry production. As a 27 year old male veterinarian in Nigeria explained:\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFor the women, you can do 200 birds in your backyard, but when you are going into large-scale production, you actually relocate to the bush because birds make noise.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIn the qualitative baseline, respondents in Tanzania, Nigeria, and Zimbabwe responded to a hypothetical story about a woman named Amina who successfully grew her chicken business until one day, her husband called her to discuss it. Respondents acknowledged that Amina\u0026rsquo;s husband could respond positively or negatively, and that some of the activities or attitudes of a successful female agripreneur could be viewed as problematic. These included a woman out-earning her husband, interacting with male customers or animal health workers especially late at night, or neglecting to give sufficient time and energy to her husband, children, and other relatives. A Sector 3 woman in Oyo State, Nigeria reflects on Amina\u0026rsquo;s husband.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMaybe the man is jealous she is doing better than him, that he is not getting her attention, and other men are eyeing her. She is getting more money. He might think one day she will not be submissive to him. He is afraid.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAmina was also commended for being hard-working, committed, and an asset to her family. A Sector 3 man in Tanzania considered \u0026ldquo;perhaps Amina\u0026rsquo;s husband wanted to know if the business is suitable to be a family business.\u0026rdquo; While such an arrangement can be beneficial for the business, a husband\u0026rsquo;s investment can also be associated with reduced decision-making and control for the woman who started it. Gender norms, such as it being inappropriate for a woman to outearn her husband or boyfriend, can limit the ability of a woman to intensify.\u003c/p\u003e\n\u003ch2\u003eEmpowerment\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThe PREVENT program did not have a measurable impact on the empowerment of men and women poultry producers as measured by WELI 3DE scores, even in Tanzania where intensification occurred because of the program as evidenced by flock size increases. Despite this, we combine the quantitative and qualitative empowerment findings to understand the differences between Sector 3 and Sector 4 producers, identify trends in specific indicators of empowerment for Tanzania Sector 3 and 4 producers where hatchery vaccination increased flock sizes for many households, and explore why some Tanzanian men could feel disrespected by other household members or be unable to use income in line with their own values when keeping chickens.\u003c/p\u003e\n\u003cp\u003eGiven the eligibility criteria for enrolling people involved in chicken production, some empowerment indicators, such as input into livestock decisions and input into productive decisions, had high percentages of adequacy for respondents in both Nigeria and Tanzania at baseline and endline. In Nigeria, over 95% of female respondents in both sectors had adequacy in the self-efficacy indicator, defined as an individual\u0026rsquo;s internal belief in their own capabilities and rights to act and achieve their goals. A subset of empowerment indicators had lower percentages of adequacy and therefore more room for variability: autonomy in income, respect among household members, work balance, and mobility to important locations (\u0026lt;75% of Sector 4 female respondents in Tanzania and Nigeria had adequacy at baseline). For women in Sector 3 in both Tanzania and Nigeria, work life balance was a shared area of concern where only 57 and 38% of respondents achieved adequacy respectively.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSector 3 chicken keepers in treatment households in Tanzania experienced a significant increase in flock size, which could have changed the patterns of resource control and decision-making within the household. While the changes are not significant, we see a decrease in the proportion of women achieving adequacy in autonomy in income use (66% to 55%), an increase in self-efficacy (66% to 79%), an increase in respect among household members (43% to 63%), and a decrease in mobility to important locations (Figure 5). Work balance remains an indicator associated with high disempowerment. The bar graph for Sector 4 chicken keepers is in Additional file 10.\u003c/p\u003e\n\u003cp\u003eA woman with a high WELI score who kept over 350 layers with her husband explained how income use and respect interact within her marriage.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eIt affects us (women) since we have no power in decision-making. If you do something that your husband doesn\u0026rsquo;t agree with, he feels as if you disrespected him. This kind of situation happened to me once. I was given a pig from a group where I was a member. When I brought the pig home, he said if this pig will be kept here, it is not just yours, it is ours. I accepted, but after a while, he brought a buyer home and sold the pig without involving me. In this situation, it is hard for a woman to intensify poultry farming.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eMost women agreed that work balance was a challenge, with some citing support from their husbands or children and time management as strategies used to manage their responsibilities. A woman with a high WELI score in Sector 3 who recently managed to shift from local to improved chickens with her husband\u0026rsquo;s financial support explained.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eHonestly, the issue is real. Women are obviously overwhelmed by different responsibilities. From my understanding, this happens because of the\u0026nbsp;patriarchal system. Since years back, the\u0026nbsp;community believes that some activities cannot be done by men, and\u0026nbsp;that\u0026rsquo;s why men don\u0026rsquo;t support their partners even when they are overwhelmed by responsibilities.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIn Tanzania, both men and women reported an increase in time spent on chicken management, with women indicating a slightly higher increase than their male counterparts (Figure 6). This suggests that while intensification may bring productivity gains, it also places additional demands on women\u0026apos;s time. In contrast, in Nigeria, most men and women reported no significant changes in their work time. However, about 39% of the respondents, both male and female, experienced an increase, indicating that while the impact is less widespread than in Tanzania, it is still notable for a significant portion of the population.\u003c/p\u003e\n\u003cp\u003eThe reduction in mobility for Sector 3 women in Tanzania was not discussed in the endline qualitative tool, however at baseline, farmers described how time-intensive managing DOCs was, which could contribute to reduced mobility temporarily especially if less labor-intensive teen chicks were not available.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThree additional barriers to intensifying into Sector 3 from the qualitative findings that were not well captured in WELI were access to land (required for Sector 3 due to the noise and waste management of more birds, especially near residential areas), access to capital and credit with appropriate terms, and for Sector 3 chicken keepers in Nigeria, security concerns caused by bandits and thieves while traveling between home and farm, especially during early or late hours. These barriers were mentioned by both men and women but experienced more acutely by women because of patriarchal laws and inheritance practices that favor men, multiple formal and informal factors that can make it easier for men to access credit or capital to invest in business, and the risk of sexual assault or rape by bandits in addition to theft and violence if the person moving through their area was a woman. In the WELI, a high proportion of respondents had adequate empowerment scores for access to credit, but the amount and terms were not specified, which the qualitative findings clarified often meant access to loans with lending periods too short for a cycle of poultry production, for amounts too small to be meaningfully invested, or prohibitively high interest rates. The ownership of assets indicator included questions about owning assets including livestock, land, and household goods. Men and women in Sector 3 or nearing the threshold acknowledged that renting property or keeping chickens near residences was problematic past a certain flock size. While in Tanzania and Nigeria, some women owned land, it was more difficult for women to purchase, and married women usually required their husband\u0026rsquo;s support to use shared land. Young, unmarried men and women were sometimes given family land to use temporarily for poultry business, although girls were less likely to be given land permanently because it was understood they would leave the family upon marriage. A woman with a high empowerment score who experimented with raising improved chickens commercially with her husband before returning to keeping local chickens explained.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eIt\u0026rsquo;s true, a woman can\u0026rsquo;t have a larger piece of land than a\u0026nbsp;man because men are more\u0026nbsp;likely to be given land by their parents than women. So even if\u0026nbsp;a married woman buys one acre, a husband is still a few steps ahead of her because the land will be owned by both of them. But if you understand one another, you can be free to use the land for anything.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWhile the WELI sample size for men was small with over-representation from Sector 4, adequacy in two indicators was notably low: autonomy in income (29% adequacy at endline, N=41 ) and respect among household members (34% adequacy). There were fewer Sector 3 producers in the communities and it was difficult to find men at home. These were also the two indicators with the lowest percentages of adequacy for men in Nigeria (67% adequacy in autonomy in income use and 54% in respect among household members, N=72). The endline included only households interviewed at baseline. A man in Tanzania with a low empowerment score who kept 20 chickens in a village about 60 km from the nearest town explained why he wasn\u0026rsquo;t often able to spend income from chickens according to his own values and wishes. Others in the group agreed that their business and investment goals were easily superseded by unplanned family obligations.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eIt is very difficult for men to stick to their goals when they have family to take care of. At least those who are not married may spend their income according to their goals and wishes. Sometimes, we men prioritize the family needs.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eA man in the second group with a low empowerment score keeping 69 local chickens described how household expenses, especially for education, were different from those in the past.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eIn previous years, even education for children was not priority in many households, so the responsibilities requiring money were minor. Nowadays, education is compulsory and a priority. It requires collaboration so everything done in the household can be more profitable. Women are now focusing on the future, so if a man doesn\u0026rsquo;t involve his wife in production, there is a chance of being divorced.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eYoung, unmarried chicken keepers were not represented in the WELI sample which required couples, so we intentionally interviewed youth in the endline. Two unmarried men in the Tanzania sample who were keeping chickens while living with their parents described being protected from contributing poultry income to family expenses so that they could grow their businesses.\u003c/p\u003e\n\u003cp\u003eMen\u0026rsquo;s respect by household members came up in the Amina vignette at baseline for Tanzania and Nigeria, and was specifically addressed in a second vignette in Tanzania at endline to understand men\u0026rsquo;s low empowerment scores. In the second vignette, a happily married man, Mr. Sanga, kept chickens with his wife. They were described as sharing decision-making, income, and even routine tasks such as cleaning the chicken coop and collecting eggs. In the discussions with men who had low empowerment scores, respondents immediately identified the potential for Mr. Sanga to feel disrespected by friends and neighbors because of doing activities such as feeding and cleaning traditionally done by women.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eA woman will be happy because she feels that her husband is cooperative. But Sanga\u0026apos;s neighbors and friends will perceive that he is being controlled\u003c/em\u003e. \u003cem\u003e(\u003c/em\u003eMan with low empowerment score)\u003c/p\u003e\n\u003cp\u003eWomen were also quick to mention that Mr. Sanga may feel disrespected, with many pointing to the wife\u0026rsquo;s behavior as a factor, such as discussing personal matters with people outside the home.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe feeling of a man being disrespected is obviously caused by the wife. If I tell my fellow women that my husband is performing certain chicken keeping chores, it may give a picture that my husband is always under my control. When a husband hears the rumors, it will bring the feeling of not being respected. Sometimes men feel disrespected when they lack power to control income, especially from chicken keeping.\u0026nbsp;\u003c/em\u003e(Woman with high empowerment score, Sector 4)\u003c/p\u003e\n\u003cp\u003eThe vignette was not used in Nigeria, with men with both high and low empowerment scores describing feeling proud of and respected for their involvement in the chicken business. Women also felt the work was respectable, as a 28-year old Sector 4 farmer with a low empowerment score explained.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePoultry brings honor since you are not stealing. I have never been disrespected before. It is not a job where if a visitor comes, you will run away.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eA few women described being looked down upon when wearing dirty farm clothes, and one described people trying to shame her for choosing agricultural work after finishing higher education. A Sector 4 woman in her fifties with a high empowerment score reflected.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe society we are in makes it look like as a woman, there are some areas you cannot be recognized. In Yoruba land, we believe that the man is the head of the woman. If they have not seen a man involved in what a woman is doing, it is perceived that the woman is not worth collaborating in business with.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eOne potential unintended consequence the project monitored through the Field Technician M\u0026amp;E data was that with intensification, women might lose decision-making control they had previously had with a smaller flock. In Tanzania the opposite occurred: 53% of women and 44% of men who purchased VDOCs said they made more management decisions (Figure 7). While women maintaining or increasing their management decision-making relative to men is good news, as it suggests they are not being pushed out following intensification caused by the hatchery interventions, the qualitative findings outlined some pathways by which increased women\u0026rsquo;s decision-making and engagement in chicken-keeping can lead to increased workload and in some cases, husbands feeling disrespected which may lead them to limit or take over aspects of the business.\u003c/p\u003e\n\u003ch2\u003eField Technicians\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eIn the final results section, we consider the role of Field Technicians. Field Technicians, a mixture of hatchery employees and independent consultants hired by the PREVENT project, were intended to be at the heart of the intervention, connecting SSPs with vaccinated chicks from the hatcheries. Many of the Theory of Change assumptions therefore focused on FTs; that there would be sufficient paravets to create a cadre of FTs, that farmers would trust them, that they could create a profitable business selling DOCs, and that FTs would not only deliver chicks but also provide extension \u0026ndash; with a focus on women!\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eField Technicians had a busy schedule. About half (46 FTs) were hatchery employees, with day-to-day responsibilities in management, biosecurity protocols, diagnostic services, managing hatchery incubation, plus farmer visits. The remaining 39 FTs (46%) were independent consultants who had more flexibility to focus on farm visits. At endline, some FTs had been promoted within the hatchery or moved to other opportunities, suggesting it was perceived to be an entry-level position in some workplaces. A Nigerian FT in his thirties described his work on the sales team at a hatchery.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eI am an office person except for two days a week when we sell all the chicks that come from the hatchery. I am always in the middle of business.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAn FT in Tanzania employed by a hatchery described her farm visit routine. The region that she served is approximately 35,000 square kilometers.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eOne of the questions I ask is the availability of men and women in the household so I can provide knowledge on chicken keeping for both and tell them the importance of working together in performing different responsibilities. I always go with the private animal health officer who responds to different challenges (especially diseases). It is done for free, the costs are paid by hatchery.\u003c/em\u003e \u003cem\u003eMy coverage area is the whole region, but I have not yet reached some areas.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eOver the duration of the project, 19 FTs in Tanzania and 16 FTs in Nigeria each completed an average of 536 and 380 farm visits, respectively. Despite this effort, there were relatively few FTs given the scope and geographic reach of the program. In Tanzania, only 13% of Sector 3 households and 2% of Sector 4 households at the endline reported being visited by an employee from a chick supply company to discuss VDOCs in the three months prior to the endline survey. These percentages are roughly the same at the baseline, where 14% of Sector 3 and 1% of Sector 4 households reported receiving such visits. In Nigeria, 14% of Sector 3 and 6% of Sector 4 treatment households at endline reported receiving these household visits within the three months prior to the survey. Again, these percentages are roughly the same as those observed at baseline. Consequently, there was no increase in the proportion of households reporting VDOC purchases in the three months before the survey in either country or sector, indicating that a small cadre of FTs was insufficient to reach new customers with VDOCs. Producers pausing on restocking or decreasing their flock sizes due to volatile input markets also limits the ability of FTs to sell DOCs.\u003c/p\u003e\n\u003cp\u003eThe two unique profiles of some FTs employed through hatcheries and some as independent consultants provided some insights into how the two models impact extension. Hatchery employees were more technically focused, running more standardized, prevention‑oriented visits, where advisory activities dominated (management, biosecurity, performance, and brooding). They were more likely to perform troubleshooting, necropsy, and sampling, consistent with stronger diagnostic training, access to laboratories, and a mandate for health surveillance to protect company reputation. Their fixed salary structure reduced commercial pressure and their geographically restricted zones allow for deeper follow-up. In contrast, the FTs who were employed as independent consultants were more productive, with 52 average visits/ quarter compared to 33 for hatchery employees, but they were weaker in diagnostics (\u0026lt;6% and \u0026lt;2% of visits included troubleshooting or necropsy, for example). Independent consultants leaned toward commercial activities because of their economic model, which combines service fees with sales commissions. They diversified their income streams through product sales and enjoyed the freedom to offer multiple brands. High visit volumes imposed time constraints, favoring shorter and less complex visits. On-demand treatments and vaccinations were similar for both profiles (Additional file 11).\u003c/p\u003e\n\u003cp\u003eIncentive structures and workplace expectations for both types of FTs encouraged the prioritization of existing and large scale customers. Sector 4 chicken keepers, who represented 57% of the beneficiaries tracked by the Field Technicians, received only 30% of the services, while the largest-scale chicken keepers (representing 15% of the beneficiaries) received three times as many visits and five times as many vaccines. Unfortunately, partly due to the disproportionate number of women in Sector 4 compared to Sector 3, these extension models can reinforce existing gender inequalities. The project Theory of Change included \u0026ldquo;farmers provided management support (focus on women),\u0026rdquo; but lack of support for gender-responsive extension was flagged midway through implementation as an area without supporting activities. Gender-responsive extension involves taking gender differences into account and paying attention to the unique needs of women, men, girls, and boys. Acknowledging that other individual characteristics are also important to the way people engage with veterinary extension services, the ILRI Gender Team developed a training called \u0026ldquo;Social Extension.\u0026rdquo; The Social Extension training was delivered in a single session in Nigeria. At the qualitative endline, none of the four interviewed Field Technicians remembered anything about it, and no one could articulate a way to modify their extension to be more inclusive. In contrast, in Tanzania we piloted a five month Social Extension mentorship program for all 12 active Field Technicians [33]. After the program, all FTs could identify gender stereotypes in the poultry sector and most described changes in their extension to be more inclusive, primarily directing extension material to multiple household members without making assumptions about their role based on gender, age, or other social markers. The mentorship program was qualitatively evaluated and seemed most impactful for young men who had recently graduated compared to older participants. A male FT in Morogoro described the changes that he made.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eI educate men and women about chicken-keeping without bias. I also educate men to collaborate with their wives when they are planning their chicken- keeping budget. Since the mentorship program, there are already some families co-operating together in chicken-keeping.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAdjustments to the training, workplace incentives, and size of the Field Technician team could be made to prioritize the specific goals of future projects, such as gender-responsive extension, reaching new clients with VDOCs, or providing producers with access to diagnostic services.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003ePREVENT was a market-based program to support hatchery vaccination. The contrast between Tanzania and Nigeria illustrates how variation in market penetration, commercial uptake, and macro-economic conditions affect the detectability of impact. In Tanzania, the evaluation detected measurable improvements in flock size, mortality, and poultry cash income. Similar benefits are attributed to farm-level vaccination of poultry [11\u0026ndash;13]. Hatchery vaccination delivers much of its value through avoided losses, which can be difficult to observe when disease outbreaks are sporadic and severe. When no outbreak occurs, vaccination appears as a cost, whereas when an outbreak occurs, the benefit is large but concentrated in a smaller share of households or production cycles. Poultry producers do not always know which hatchery vaccines were given and may duplicate efforts through on farm vaccination, which dilutes potential cost-saving benefits. This is consistent with a study of broiler farmers in Kenya where 82% of farmers reported being aware that the DOCs they acquired had been vaccinated, with 44% of those unaware of the specific vaccines administered [34]. In Tanzania, the increased cash income was reinvested into recurring poultry expenses, perhaps reflecting the commercialization dynamic explored in the Background that intensification increases both revenue and cost structures [2]. Another consideration is that PREVENT looks at incremental improvements in systems where many poultry producers, especially in Sector 3, were already vaccinating to some degree. That makes the counterfactual more conservative: gains are real, but smaller and harder to isolate. While effects appear modest at the household level, when delivered across large sales volumes, they accumulate into substantial system-level benefits.\u003c/p\u003e \u003cp\u003eFrom a hatchery perspective, it can be hard to justify the cost of vaccination for a hatchery in a tight market context. Without trust in a reputable hatchery and knowledge about the likely return on investment of a hatchery chick, price-sensitive consumers may be attracted to less expensive chicks which are under-vaccinated or unvaccinated, failing to see the benefits if they mix with different vaccination statuses within or across production cycles. Similarly, farmers in Western Kenya didn\u0026rsquo;t invest in fertilizer that could increase profits, although they responded to nudges in the form of discounts [35]. Despite lower uptake of best practices for hatchery vaccination, Ceva reported the strongest commercial success in Nigeria because participating hatcheries moved from a situation of \u003cem\u003eno\u003c/em\u003e demand to \u003cem\u003esome\u003c/em\u003e demand for hatchery vaccination by non-integrated hatcheries.\u003c/p\u003e \u003cp\u003eFor Sector 3 chicken keepers, the purchase of VDOCs was a clear impact pathway, but for Sector 4 chicken keepers who bought more chicks but not necessarily VDOCs, the impact was surprising. Further, Silverlands Tanzania hatchery in Iringa uses the PMI model to support mother units, but few households in the impact evaluation study were identified as mother units. In reality, mother units that initially received loans from the hatchery to operate under a credit model now operate on a cash basis and often raise hybrid flocks with some of the birds sold at 28 days with remaining birds remaining for live market sale and egg production. This suggests the Sector 4 households purchase from Sector 3 neighbors who may not formally identify as mother units but sell part of their VDOC batch as teen chicks due to economic problems or as part of their business strategy, thereby derisking the chicks for the Sector 4 producers by rearing them past the sensitive brooding period and giving downstream positive effects. The unexpected movement of chicks into Sector 4 through Sector 3 SSPs and the success attributed to including a larger hatchery supports the potential of working with large-scale, integrated hatcheries that mostly sell to Sector 3 for impact on SSPs.\u003c/p\u003e \u003cp\u003eBy incorporating gender research throughout the project lifecycle from qualitative baselines and endlines, quantitative WELI, and indicators on decision-making and work balance in the monitoring and evaluation, we also asked \u0026ldquo;under what conditions can poultry continue to benefit women during intensification/ commercialization?\u0026rdquo; In Tanzania, there was no program impact on empowerment for men or women as measured by WELI 3DE scores. In some sense, this represents good news that the intensification caused by the program did not have unintended consequences in two main areas of concern identified in other livestock intervention studies: decision-making and work balance. While there were no measurable negative effects of the intervention, the vignettes in the qualitative research outlined theoretical pathways for husbands to disapprove of their wives out-earning them or growing a business at the expense of other domestic obligations. Men in Tanzania could feel a lack of respect from household members in certain scenarios such as when the wife appeared to be leading a successful business while the man contributed minimally or in menial tasks considered within the domain of women. Both these scenarios could lead to men either restricting the business growth or taking over. There was no evidence of this happening because of the PREVENT project intervention, although there were a small number of men in the WELI sample in Tanzania who reported extremely low adequacy in the respect from household members and autonomy of income indicators, which could set the stage for the dynamics described in the qualitative findings. The challenge of finding men at home for the WELI sample also suggests the men who were available may not have been a representative sample, perhaps more likely to be injured, unwell, or unemployed. In contrast to these findings, in a study of small-scale farmers in Machakos Kenya with WELI data for men and women, the proportion of men achieving adequacy in respect among household members was significantly higher than for women, although respect among household members was one of the indicators contributing to men\u0026rsquo;s disempowerment [36].\u003c/p\u003e \u003cp\u003eFor women, we saw differences in a few WELI indicators that were not significant, but consistent with trade-offs during intensification identified in the qualitative data. We measured a decrease in the proportion of women achieving adequacy in autonomy in income use (66% to 55%), an increase in self-efficacy (66% to 79%), an increase in respect among household members (43% to 63%), and a decrease in mobility to important locations. Decreased autonomy in income use is consistent with a male takeover or capture of resources while an increase in respect is consistent with the qualitative findings from the Amina vignette where male and female respondents described the positive ways in which a successful female agripreneur could be viewed. These are specific indicators of women\u0026rsquo;s empowerment that should be further monitored to understand the trade-offs and shifts that occur during intensification, especially for household businesses in which multiple family members contribute in different ways. This may be less relevant in Nigeria, where many of the Sector 3 chicken businesses were run by a single household member with hired employees providing more labor as opposed to in Tanzania where labor was often provided by household members [18].\u003c/p\u003e \u003cp\u003e Finally, the study provided insight into the best models for linking hatcheries to chicken keepers for the delivery of DOCs. The FTs identified in the Theory of Change to provide this linkage were too few to reach new clients and were incentivized to spend most of their time on larger, existing clients. In a study mapping the movement of DOCs in Machakos, Kenya, only 36% of broiler farmers obtained chicks from hatchery sales agents; most sourced from veterinary drug stores [34]. Silverlands Tanzania\u0026rsquo;s strategy of incorporating the PMI mother unit model and working with private agents to buy and resell DOCs is part of their corporate strategy. If gender-responsive extension is a goal, FTs are likely to perpetuate gender inequities in their extension without further training and mentorship, as evidenced by the inability of the Nigeria FTs to describe ways of improving their extension to be more inclusive even after a one-time training session. Training opportunities that occur over a longer period of time with more interactions, such as the five-month Social Mentorship pilot with FTs in Tanzania, can be more effective at changing behavior [37]. This is consistent with a study of trainings for medical professionals which found the opportunity to practice skills was associated with more effective trainings [38].\u003c/p\u003e \u003cp\u003eAnother strategy for supporting women through intensification is the Women in Business Model, which like PMI, was developed from learnings from the African Chicken Genetic Gains project [16]. The Women in Business model aimed to develop, promote and test women-led chicken businesses in Tanzania with the goal of promoting the economic empowerment of women and young graduate women and improving food and nutrition security of their households [39]. After public and private adoption by Tanzania\u0026rsquo;s Ministry of Livestock and Fisheries and AKM Glitters (a private hatchery) [40], it is currently being scaled to other regions within Tanzania and to neighboring countries [41]. The model supports young women who have recently graduated to self-employ in the poultry value chain as vendors and brooders in order to strengthen linkages between hatcheries and female SSPs.\u003c/p\u003e \u003cp\u003eA limitation of the study was the insufficient time for impact between the rollout of VDOCs by the participating hatcheries and the endline assessment, especially considering that a cohort of layers could be kept for almost two years and the seasonality of some poultry diseases. Future projects would benefit from a longer timeline, especially when establishing contracts with private companies happens within the project timeline. The impact evaluation survey had sufficient power to detect program impact on indicators like flock size, but further analyses that narrowed in on subsets of the data, such as Sector 3 women in Tanzania, were underpowered. This was also true for analyses of subsets of the WELI sample or comparisons of specific WELI indicators, forcing us to report trends while triangulating findings with the qualitative results. The impact evaluation did not include those who dropped from poultry production due to the requirement for baseline respondents to still be in poultry production. The sampling strategies used by the project activities focused on representing both men and women chicken keepers, even alternating between male and female respondents in the M\u0026amp;E survey conducted by Field Technicians, which meant like many studies, the data could not be used to estimate the proportions of women and men in Sector 3 versus Sector 4. The requirement for FTs to submit data for their first ten extension visits each month may have contributed to bias towards existing or more accessible clients. Narrowing in on one site per country for the qualitative endline allowed for focus on mechanisms to impact, but selection of Iringa meant the findings were not generalizable to other communities within Tanzania because of the unique profile of Silverlands Tanzania as one of the largest hatcheries in the PREVENT project. Lastly, the social extension mentorship program piloted with the Tanzanian Field Technicians was promising but the qualitative impact assessment was limited and raised questions about how such programs change extension delivery, farmer results, and the extent to which such a program could be scaled.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eWhen correctly implemented and fully adopted, hatchery vaccination protects against catastrophic disease loss, and can increase flock size and cash income for SSPs, including Sector 4 producers. While large, integrated hatcheries were not the project\u0026rsquo;s target partners, the successful engagement with Silverlands Tanzania, a large hatchery with established distribution models based on the PMI, supports inclusion of large hatcheries in future projects. Economic volatility and partial adoption of DOC vaccination in Nigeria eroded any detectable impact of the intervention. In Tanzania, input prices were described as high, and possibly one of the reasons why the increased cash income did not translate into increases in net poultry income or household income; the funds were generally re-invested in poultry production. While intensification neither improved empowerment scores or caused harm, the qualitative findings identified pathways for women to face consequences from their husbands if they out-earned them or neglected domestic responsibilities while intensifying poultry production and for men in Tanzania to feel a lack of respect among household members if they participated in menial activities considered for women and others perceived them to be sub-ordinate to their wives in the business. Future studies on intensification in the livestock or poultry sector could focus on the impact of gender training for extension workers such as the Social Extension Mentorship pilot and the benefit of incorporating variations of the PMI for chick dissemination that support women agripreneurs, such as the Women in Business model. Key indicators of empowerment to monitor during commercialization or intensification include respect among household members for men and women, and women\u0026rsquo;s work balance and autonomy of income. These indicators may shift before aggregate WELI 3DE scores reflect changes, so mixed methods studies are recommended to capture early changes.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e3DE \u0026ndash; Three domains of empowerment\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDOC \u0026ndash; Day Old Chick\u003c/p\u003e\n\u003cp\u003eFT \u0026ndash; Field Technician\u003c/p\u003e\n\u003cp\u003eIB \u0026ndash; Avian Infectious Bronchitis\u003c/p\u003e\n\u003cp\u003eIBD \u0026ndash; Infectious Bursal Disease, or Gumboro\u003c/p\u003e\n\u003cp\u003eILRI \u0026ndash; International Livestock Research Institute\u003c/p\u003e\n\u003cp\u003eM\u0026amp;E \u0026ndash; Monitoring and evaluation\u003c/p\u003e\n\u003cp\u003eND \u0026ndash; Newcastle disease\u003c/p\u003e\n\u003cp\u003eOPM \u0026ndash; Oxford Policy Management\u003c/p\u003e\n\u003cp\u003ePMI \u0026ndash; Poultry Multiplication Initiative (previously known as African Poultry Multiplication Initiative)\u003c/p\u003e\n\u003cp\u003ePREVENT - PRomoting and Enabling Vaccination Efficiently, Now and Tomorrow\u003c/p\u003e\n\u003cp\u003eSector 3 \u0026ndash; Poultry production classification which includes semi-intensive and emergent commercial systems\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSector 4 - Includes traditional and backyard systems\u003c/p\u003e\n\u003cp\u003eSSP \u0026ndash; Small-scale Producer\u003c/p\u003e\n\u003cp\u003eVDOC \u0026ndash; Vaccinated Day Old Chick\u003c/p\u003e\n\u003cp\u003eWELI \u0026ndash; Women\u0026rsquo;s Empowerment in Livestock Index\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\n\u003cp\u003eAll participants were over 18 years old and gave informed consent after the research team shared information about the activity including risks and the reminder that participation was voluntary. Participants gave written or thumbprint consent for the qualitative studies and verbal consent for the impact evaluation and Field Technician survey, in line with the ethical approvals below.\u003c/p\u003e\n\u003cp\u003eThe qualitative baseline and endline studies were approved by the International Livestock Research Institute (ILRI) Institutional Research Ethics Committee (IREC), reference numbers ILRI-IREC2021-39 and ILRI-IREC2021-39/1 (approval period 28 Sept 2021 \u0026ndash; 27 Sept 2022) and ILRI-IREC2021-39/2 (approval period 16 Jan 2024 \u0026ndash; 14 Jan 2025), respectively.\u003c/p\u003e\n\u003cp\u003eThe impact evaluation and Field Technician survey studies were approved by the National Health Research Ethics Committee in Nigeria, reference numbers NHREC/01/01/2007-16/03/2023 and NHREC/01/01/2007-23/07/2025 and the Tanzania Commission for Science and Technology in Tanzania, reference numbers 2023-45-NA-2022-385 and CST00001174-2025-2025-00425.\u003c/p\u003e\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e\n\u003cp\u003eThe quantitative datasets generated during the current study are available as additional files. All study tools are provided, with the exception of the WELI tool, which is available from the corresponding author on request. Qualitative transcripts are not available due to challenges anonymizing them and limited value of secondary analyses without the proper context.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis work was supported in whole by the\u0026nbsp;Gates Foundation [Investment ID INV-005820]. The findings and conclusions contained within are those of the authors and do not necessarily reflect positions or policies of the Gates Foundation.\u003c/p\u003e\n\u003cp\u003eThis work was conducted as part of the CGIAR Sustainable Animal and Aquatic Foods (SAAF) Program. SAAF is part of CGIAR\u0026rsquo;s 2025-2030 Research Portfolio. SAAF works across Africa, Asia, and Latin America to improve access to nutritious foods while reducing emissions and supporting inclusive livelihoods. By combining livestock and aquatic systems, it develops integrated, climate- and environment-friendly solutions tailored to local contexts. CGIAR research is supported by contributions to the CGIAR Trust Fund (https://www.cgiar.org/funders/). CGIAR is a global research partnership for a food-secure future dedicated to transforming food, land, and water systems in a climate crisis.\u003c/p\u003e\n\u003cp\u003eThe PREVENT project is a partnership between Ceva Sant\u0026eacute; Animale and GALVmed.\u003c/p\u003e\n\u003ch2\u003eAuthors\u0026apos; contributions\u003c/h2\u003e\n\u003cp\u003eConceptualization by ZAC, HJ, LA, KT, and MD; Formal analysis by ZAC, HJ, AT, TK, SO; Funding acquisition by LA, KT, MD; Investigation by ZAC, HJ, AJ, EA; Methodology by ZA, HJ, KT, SO; Project administration by EA, LA, KT; Supervision by AJ, EA, SO; Visualization by AT, TK, SO; Writing \u0026ndash; original draft by ZAC; Writing \u0026ndash; reviewing and editing by all co-authors. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eWe thank Dr. Sunday Ofueg (Ceva Field Officer in Nigeria) and Dr. Lazaro Kapella (formerly at Ceva in Dar es Salaam) for their logistical support during fieldwork. Thank you to\u0026nbsp;Pierre-Marie Borne\u003csup\u003e\u0026nbsp;\u003c/sup\u003eat Ceva for data analysis and other program support. Thank you to Paul Bessel, Julie Koehler, and Stewart Bradnick for their insights that improved the final draft.\u003c/p\u003e\n\u003cp\u003eWe appreciate the Field Technicians, data collectors, and enumerators in Tanzania and Nigeria for making the project happen.\u003c/p\u003e\n\u003cp\u003eLastly, thank you to the chicken keepers for opening your doors to us throughout the project and sharing your perspectives and insights.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAbay, K., Tiruneh, H. A., Terfa, Z., Karugia, J., \u0026amp; Breisinger, C. (2025). \u003cem\u003eHow good are livestock statistics in Africa? Evidence from Ethiopia\u003c/em\u003e. IFPRI Blog. https://www.ifpri.org/blog/how-good-are-livestock-statistics-in-africa-evidence-from-ethiopia/\u003c/li\u003e\n \u003cli\u003eAssocle, S. (2026, January 22). Nigeria\u0026rsquo;s Poultry Push: New Projects, New Plan, Old Challenges. \u003cem\u003eEcofin Agency\u003c/em\u003e. https://www.ecofinagency.com/news/2201-52181-nigeria-s-poultry-push-new-projects-new-plan-old-challenges\u003c/li\u003e\n \u003cli\u003eBaltenweck, I., Achandi, E., Bullock, R., Campbell, Z., Crane, T., Eldermire, E., Gichuki, L., de Haan, N., Njuguna-Mungai, E., Poole, J., \u0026amp; Gali\u0026egrave;, A. (2024). 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Mapping the flow of commercial broiler day-old chicks in Kenya. \u003cem\u003eFrontiers in Veterinary Science\u003c/em\u003e, \u003cem\u003e12\u003c/em\u003e(December), 1\u0026ndash;9. https://doi.org/10.3389/fvets.2025.1607825\u003c/li\u003e\n \u003cli\u003eInnovation for Poverty Action. (2025). \u003cem\u003ePoverty Probability Index\u003c/em\u003e. https://www.povertyindex.org/about-us\u003c/li\u003e\n \u003cli\u003eJalal-Eddeen, S. (2025). Digital financialization through demonetization: disruption, fintech adoption and everyday endurance in Nigeria. \u003cem\u003eReview of International Political Economy\u003c/em\u003e, \u003cem\u003e0\u003c/em\u003e(0), 1\u0026ndash;27. https://doi.org/10.1080/09692290.2025.2588287\u003c/li\u003e\n \u003cli\u003eKaluwa, C., Oduma, J., Abdirahman, F. A., Kitoga, B. K., Opondoh, A. A., Muchibi, J., Bagnol, B., Rosenbaum, M., Onchaga, S., Stanley, M., \u0026amp; Amuguni, J. H. (2022). Using the Women Empowerment in Livestock Index (WELI) to Examine Linkages between Women Smallholder Livestock Farmers\u0026rsquo; Empowerment and Access to Livestock Vaccines in Machakos County of Kenya: Insights and Critiques. \u003cem\u003eVaccines\u003c/em\u003e, \u003cem\u003e10\u003c/em\u003e(11). https://doi.org/10.3390/vaccines10111868\u003c/li\u003e\n \u003cli\u003eKomolafe, B., Ayanfeoluwa, P., \u0026amp; Agbakwuru, S. O. J. (2023, February 14). Banks reject old naira notes as queues persist at ATMs. \u003cem\u003eVanguard\u003c/em\u003e. https://www.vanguardngr.com/2023/02/banks-reject-old-naira-notes-as-queues-persist-at-atms/#google_vignette\u003c/li\u003e\n \u003cli\u003eKryger, K., Thomsen, K., Whyte, M., \u0026amp; Dissing, M. (2010). Smallholder poultry production \u0026ndash; livelihoods, food security and sociocultural significance. In \u003cem\u003eSmallholder Poultry Production\u003c/em\u003e. http://www.fao.org/docrep/013/al674e/al674e00.pdf\u003c/li\u003e\n \u003cli\u003eMbaegbu, R., \u0026amp; Nwanze, C. (2025, March 19). AD958: Nigerians say country is headed in wrong direction, oppose fuel-subsidy removal. \u003cem\u003eAFR Barometer\u003c/em\u003e. https://www.afrobarometer.org/publication/ad958-nigerians-say-country-is-headed-in-wrong-direction-oppose-fuel-subsidy-removal/\u003c/li\u003e\n \u003cli\u003eMramba, R. P., \u0026amp; Mwantambo, P. A. (2024). The impact of management practices on the disease and mortality rates of broilers and layers kept by small-scale farmers in Dodoma urban district, Tanzania. \u003cem\u003eHeliyon\u003c/em\u003e, \u003cem\u003e10\u003c/em\u003e(8). https://doi.org/10.1016/j.heliyon.2024.e29624\u003c/li\u003e\n \u003cli\u003eMusime, A. (2025). \u003cem\u003eUnderstanding Mortality in Chicks: Causes, Prevention, and Best Practices\u003c/em\u003e. https://aaronvetfarms.com/understanding-mortality-in-chicks-causes-prevention-and-best-practices/\u003c/li\u003e\n \u003cli\u003eNyaga, P. N. (2007). Poultry Sector Country Review: Kenya. \u003cem\u003eFAO Poultry Sector Country Review\u003c/em\u003e, 3\u0026ndash;9.\u003c/li\u003e\n \u003cli\u003eOdunze, E., Boussini, H., Mikecz, O., \u0026amp; Pica-Ciamarra, U. (2018). Livestock and livelihoods spotlight Nigeria: Cattle and poultry sectors. \u003cem\u003eFood and Agriculture Organization, Africa Sustainable Livestock 2050\u003c/em\u003e, 11\u0026ndash;12.\u003c/li\u003e\n \u003cli\u003eOtiang, E., Campbell, Z., Thumbi, S. M., \u0026amp; Palmer, G. (2020). Mortality as the primary constraint to enhancing nutritional and financial gains from poultry: A multi-year longitudinal study of smallholder farmers in western Kenya. \u003cem\u003ePloS One\u003c/em\u003e, \u003cem\u003e15\u003c/em\u003e(5), e0233691. https://doi.org/https://doi.org/10.1371/journal.pone.0233691\u003c/li\u003e\n \u003cli\u003eRashid, H., \u0026amp; Ndibalema, G. (2024). \u003cem\u003eEmpowering Tanzania\u0026rsquo;s women in business: Evaluating the readiness for scaling for two ILRI-designed gender empowerment tools\u003c/em\u003e. ILRI News. https://www.ilri.org/news/empowering-tanzanias-women-business-evaluating-readiness-scaling-two-ilri-designed-gender\u003c/li\u003e\n \u003cli\u003eSilverlands Tanzania. (2025). \u003cem\u003eAbout Us\u003c/em\u003e. https://www.silverlandstanzania.net/about-us\u003c/li\u003e\n \u003cli\u003eSuleiman, M. S., Tafida, I., Nazifi, B., \u0026amp; Inuwa, S. I. (2023). Socio-economic analysis of gender participation in poultry production in Kano Metropolis, Nigeria. \u003cem\u003eFederal University Dutsin-Ma Journal of Agriculture and Agricultural Technology\u003c/em\u003e, \u003cem\u003e9\u003c/em\u003e(3). https://doi.org/https://doi.org/10.33003/jaat.2023.0903.11\u003c/li\u003e\n \u003cli\u003eTavenner, K., Crane, T. A., \u0026amp; Saxena, T. (2021). \u0026ldquo;Breaking Even\u0026rdquo; under Intensification? Gendered Trade-Offs for Women Milk Marketers in Kenya*. \u003cem\u003eRural Sociology\u003c/em\u003e, \u003cem\u003e86\u003c/em\u003e(1), 110\u0026ndash;138. https://doi.org/10.1111/ruso.12345\u003c/li\u003e\n \u003cli\u003eTrading Economics. (2025). \u003cem\u003eNigeria Inflation Rate\u003c/em\u003e. https://tradingeconomics.com/nigeria/inflation-cpi\u003c/li\u003e\n \u003cli\u003eWorld Poultry Foundation. (2022). \u003cem\u003eDual Purpose Poultry and Impact on African Households\u003c/em\u003e. https://worldpoultryfoundation.org/wp-content/uploads/2022/04/WPF-Poster.pdf\u0026nbsp;\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-agriculture","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [BMC Agriculture](https://bmcagriculture.biomedcentral.com/)","snPcode":"44399","submissionUrl":"https://submission.nature.com/new-submission/44399/3","title":"BMC Agriculture","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Women’s empowerment, poultry, chickens, commercialization, hatchery, vaccination, gender, smallholder, Africa, vaccines","lastPublishedDoi":"10.21203/rs.3.rs-8918389/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8918389/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eVaccination is a strategy for protecting productivity gains in Africa’s poultry sector and supporting intensification of small scale producers. Transitions from semi-intensive to intensive systems are rare because they require infrastructure, inputs, and market access — resources women often struggle to obtain compared with men. This mixed-methods study assessed the impact of introducing hatchery vaccination of day-old chicks in medium-sized hatcheries, of welfare benefits for chicken keepers, and implications for gender equality as production intensifies.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eOver five years, the market-based intervention introduced 137 million vaccinated chicks through six hatcheries in Tanzania and 16 million through seven hatcheries in Nigeria. One larger hatchery in Tanzania, with a chick distribution model based on the Poultry Multiplication Initiative, contributed disproportionately more chicks. There was no measurable impact in Nigeria, partly because of lower sales volumes, economic volatility, and a weaker intervention pathway. In Tanzania, the program increased flock size and cash income from poultry, but not total household income. Surprisingly, producers with \u0026lt;200 birds also benefited, likely through access to vaccinated older chicks brooded by mother units or semi-intensive producers. Field Technicians provided extension and linked chicken keepers to hatcheries, but they were few and focused on large, existing customers.\u003c/p\u003e\n\u003cp\u003eThere was no impact on the empowerment scores of men or women in either country. Work balance contributed to women’s disempowerment. Qualitative findings showed that as women intensified production and sometimes out-earned husbands, men could feel disrespected and restrict business growth; alternatively, some men invested in women-founded enterprises, but at the cost of women’s control. In Tanzania, where flock sizes increased, the proportion of women achieving adequacy in autonomy over income use declined (66% to 55%), whereas respect among household members increased (43% to 63%). Although not statistically significant, these trends suggest trade-offs for women during intensification.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eHatchery vaccination can increase flock size and income under high-uptake conditions, including for smaller scale producers, particularly by engaging larger hatcheries with established distribution models. The intervention did not improve women’s empowerment or cause harm. Respect within households and women’s work balance and autonomy over income are indicators to monitor during intensification.\u003c/p\u003e","manuscriptTitle":"Poultry intensification through hatchery vaccination: Implications for women’s empowerment in Nigeria and Tanzania","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-02 17:22:26","doi":"10.21203/rs.3.rs-8918389/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-07T09:18:01+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-02T19:49:13+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-30T10:53:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"128158971144201945554189020488248053819","date":"2026-03-23T13:57:42+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"87651376514068094526370338874058784177","date":"2026-03-20T20:17:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"135810880326454707401058697192708472683","date":"2026-03-09T05:14:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"286214812413476206265432882564621019001","date":"2026-03-02T12:49:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"258275208259241915599343612244153759067","date":"2026-02-24T20:32:29+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-24T17:59:28+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-24T17:54:22+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-02-24T15:14:58+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-24T11:47:09+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Agriculture","date":"2026-02-24T11:41:19+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-agriculture","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [BMC Agriculture](https://bmcagriculture.biomedcentral.com/)","snPcode":"44399","submissionUrl":"https://submission.nature.com/new-submission/44399/3","title":"BMC Agriculture","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f2c52a73-329f-4905-b1d7-5ce14b4c111e","owner":[],"postedDate":"March 2nd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-14T09:38:33+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-02 17:22:26","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8918389","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8918389","identity":"rs-8918389","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}