Maize-based intercropping systems and determinants of practices: implications for the adoption of a push-pull technology for insect pest management in the Republic of Benin

Introduction: Maize (Zea mays L.) is the most commonly grown cereal crop in Benin and is a staple for millions of people. However, its production is hampered by insect pests such as the fall armyworm (Spodoptera frugiperda J. E. Smith), which causes substantial yield losses. Chemical pest control has demonstrated several limitations, leading to the promotion of ecological approaches such as pushpull technology, which deters insect pests through strategic intercropping. Promoting this technology in Benin requires an understanding of the maize-based intercropping systems developed by Beninese farmers across different agroecological zones and ethnic groups, as well as their perception of crop associations. It is also crucial to identify the factors that have an impact on the adoption of a maize-based intercropping system.

Methods: To access this technology in Benin, 438 farmers from 60 villages located in seven agroecological zones, belonging to eight sociolinguistic groups, were interviewed using participatory methods.

Results and Discussion: According to the findings, crop association was practiced by 70.56% of surveyed the farmers in their maize fields, and four distinct crop association types and systems were documented. Farmers listed six constraints that hinder the use of maize-based intercropping systems, with field maintenance difficulty (60.54% of responses) being the most important. Cultural prohibitions or taboos (21.67% of responses) regarding intercropping systems such as maize and common beans were recorded in the study area. The practices and types of crop associations vary according to ethnic groups and agroecological zones. The push-pull method should be implemented in Benin by targeting Yoa-Lokpa and Fon ethnic groups and agroecological zones 4 and 8. For mass adoption of the push-pull technology by Beninese farmers, it is necessary to implement participatory methods such as farmer field schools or field days and target farmers with extensive agricultural experience.

1 Introduction

Maize (Zea mays L.) is the most commonly consumed food in the Republic of Benin, accounting for 72.99% of the national cereal production and contributing significantly to food security and poverty reduction (Ibikoule et al., 2024). In 2023, maize production was estimated at 2,059,254 tons and continues to grow steadily (FAO, 2023), making it the only cereal that the country exports in surplus to neighboring nations (Adeguelou et al., 2018). However, this increase in maize production is closely linked to the increase in cultivated land with a yield well below (991.9 kg/ha) the global average of 5962.3 kg/ha (FAO, 2023). Indeed, maize production in the Republic of Benin is subject to many biotic constraints, of which the insects are the most damaging pests (Emeraghi et al., 2024).

Fall armyworm (Spodoptera frugiperda J. E. Smith) attacks have caused significant agricultural losses across all agro-ecological zones in the Republic of Benin in recent years (Houngbo et al., 2020; Winsou et al., 2022). Annual maize yield losses caused by this pest were estimated to range between 295.8 to 735.8 thousand tonnes, resulting in financial losses of approximately 86.6 and 215.6 million dollars (Day et al., 2017). The control of maize pests primarily relies on synthetic pesticides, which contribute to biodiversity loss and the emergence of resistant insect populations (Houngbo et al., 2020; Tossou et al., 2025). Therefore, it is crucial to develop sustainable and eco-friendly methods for pest management in maize fields.

Minimizing the infestation of maize fields by this pest can be achieved through intercropping, which is an important component of an integrated pest management strategy (Soujanya et al., 2024). Push-Pull technology based on an intercropping system using repelling plants as intercropping (push) and attractive plants in the plot contour (pull) is of great interest as an eco-friendly method for controlling maize pests, especially the fall armyworm (Abate et al., 2024). This agro-ecological control method, adopted by thousands of smallholder farmers in East and Southern Africa, has proven effective in managing insect pests and parasitic weeds (Striga), while significantly increasing soil fertility and maize yields (Luttermoser et al., 2023; Jalloh et al., 2024b). The most commonly used push-pull system developed by the International Centre of Insect Physiology (icipe) and its partners involves intercropping silverleaf Desmodium species and planting Brachiaria or Napier grass along the borders (Mumo et al., 2024). This system has been proven to enhance maize’s resistance to herbivore attacks (Lang et al., 2024). However, the adoption of this technology remains relatively low due to the susceptibility of companion crops to climate change (Murage et al., 2015). This highlights the need to adapt push-pull technology to meet farmers’ needs and realities (Adesina et al., 2024; Sime et al., 2024; Waiswa et al., 2024). Therefore, to implement this cost-effective technology for smallholder farmers in the Republic of Benin, it is important to understand the maize-based intercropping systems they have developed, the challenges they face, and the factors affecting their adoption decisions. Given that farmers’ perceptions of innovations like push-pull technology significantly affect both adoption and dissemination (Amudavi et al., 2009a), this study aims to document maize-based intercropping systems in the study area, identify the challenges associated with these practices, and explore the factors influencing their adoption.

2 Materials and methods

2.1 Study area

The Republic of Benin, located in West Africa between latitudes 6°10’ N and 12°25’ N and longitudes 0°45’ E and 3°55’ E, has an area of 112,622 km². The south of Benin is characterized by an equatorial climate with two rainy seasons, while the center and north of Benin have a tropical climate with one rainy season. The rainfall in the south is between 1200 and 1500 mm per year, while in the center, it is between 1000 and 1200 mm per year, and in the north, it is between 800 and 1100 mm. The soil is predominantly hydromorphic in the south, ferralitic in the center, and predominantly ferruginous in the north. The vegetation in the south is lush, with tropical forests, palm groves, and mangroves along the coast. Wooded savannahs and open forests dominate the vegetation in the center, while shrubby and herbaceous savannahs dominate the north. Benin is an agriculture-based country, with the sector accounting for 30% of gross domestic product and employing 70% of the labor force (Kinkpe et al., 2024).

2.2 Sampling methods

The surveys were carried out in 60 villages (23 in the south, 14 in the center, and 23 in the north) located across the main maize-growing areas in Benin (Figure 1). These villages were selected based on maize production statistics and taking into account ethnic diversity, agroecological zones, and accessibility. In each village, a group of producers was identified and brought together with the help of the village chief and the representative of maize producers in the area. The transect method described by Dansi et al. (2010) was used for sampling household for individual interviews. The investigation covered all agroecological zones in Benin (zone 2: north cotton zone; zone 3: south Borgou crop zone; zone 4: west Atacora zone; zone 5: central Benin cotton zone; zone 6: clayey earth zone; zone 7: depression zone, and zone 8: fishing zone), with the exception of agroecological zone 1 (extreme north zone), located in the W National Park.

Figure 1

Figure 1. Map of Benin showing the geographical position of the villages surveyed.

The sample size was obtained using the formula proposed by Dagnelie (1998):

$$N=\frac{U_{1-\propto /2}^2\times p(1-p)}{d^2}$$

U1-α/2 is the value of the normal random variable corresponding to the probability value 1-α/2, where α is the risk of error. For α = 5%, the value of 1-α/2 is 0.975, so U1-α/2 = 1.96. Pxis the proportion of people engaged in maize production in the study environment, and d is the margin of estimation error, which was set at 8% in this study (Assogbadjo et al., 2011). The proportion of maize producers (p = 0.79) was determined by considering the total number of agricultural households in Benin (1,371,062) and those involved in maize production (1,089,233) (Direction de la Statistique Agricole (DSA), 2024). The minimum number of households to be surveyed was estimated at 102.03. The analysis of the diversity of intercropping systems based on maize was carried out at two levels: at the regional level using a representative sample of villages (village survey) and at the level of each village using a sample of its farms (Yabi et al., 2016; Gidey et al., 2024), which led us to survey 438 households.

2.3 Data collection

The surveys were carried out using participatory research approaches (household surveys and field visits) supported by data collection tools such as questionnaires. Maize producers from each village were selected for individual interviews with the assistance of village chiefs and leaders of producer associations. In total, 438 maize producers were surveyed across the country. Due to ethnic diversity, local interpreters were hired to facilitate discussions and exchanges with producers. The data collected focused on the socio-demographic characteristics of the maize producers (education, gender, household size, age, agricultural experience, main activity, marital status, religion, area sown, livestock farming practices, agricultural training, farmers’ association membership, land ownership, and visits from extension agents), as well as farmers’ perceptions of intercropping systems and the factors affecting their adoption.

2.4 Data analysis

Descriptive statistics (frequencies, percentages, means, etc.) were used to analyze the data and generate tables and figures at different levels using STATISTICA version 17. Chi-square (χ²) or Fisher’s exact tests were performed to assess adopters’ and non-adopters’ perceptions of the benefits of intercropping systems. Logit regression analysis was performed to identify the factors that affect the selection of crop association type and the crop association system. The data collected on cropping systems and types of crop associations across agro-ecological zones were converted into numerical codes. A discriminant analysis was conducted to retain only the most relevant explanatory variables. The selected variables were then standardized. Bartlett’s test, followed by the determination of the KMO index, was carried out. A principal component analysis (PCA) was performed to determine the significance of cropping systems and types of crop associations across agro-ecological zones.

3 Results

3.1 Sociodemographic characteristics of the surveyed households

In the study area, the surveyed producers belonged to eight sociocultural groups, the majority of whom practiced crop association (70%) and were male (86%). Many household heads were Muslim (46%) and illiterate (47.26%) (Table 1). The majority of producers were married (93.19%), with an average household size of 7.67 ± 4.25 people. The average age of the surveyed producers was 43.71 ± 13.38 years, and they had an average of 23.18 ± 13.05 years of experience in agriculture. The average area of land sown with maize in the study area was 5.67 ± 0.50 hectares. Most producers practiced livestock breeding (57.03%) and owned the land they cultivated (90%). Almost all households (99%) depended on agriculture as their main source of income. Only 13.09% of surveyed producers were members of a farmers’ association, particularly those who did not practice crop rotation. Very few households (13%) received visits from extension agents or agricultural training (14%).

Table 1

Table 1. Definition of variables used in logistic regression and descriptive statistics.

3.2 Farmers’ perceptions of the importance of maize-based intercropping system

The majority of surveyed farmers (70.56%) practiced crop association in their maize fields. According to the farmers, they adopted a maize-based cropping system by either consulting other producers or relatives (75.96%), participating in farmer field schools in their area (21.79%), or attending training sessions (2.24%). The Chi-square analysis revealed that the perception of the positive impact of maize intercropping systems on soil fertility and yield was comparable among farmers who adopted these systems and those who did not (Table 2). However, farmers’ perceptions of maize intercropping systems regarding decreased tillage costs, pest attacks, maintenance difficulty, and the difficulty in treating fields with pesticides differ significantly between adopters and non-adopters. A significantly higher percentage of adopters agreed that maize intercropping increases the availability of multiple crops in a single season.

Table 2

Table 2. Results of the chi-square test used to determine if there are different views on the advantages of the maize-based intercropping system between adopters and non-adopters.

3.3 Farmers’ perception of constraints related to the maize-based intercropping system

Despite the importance of maize-based intercropping systems, farmers identified six factors that hinder the implementation of cultural association practices. According to farmers, field maintenance difficulty (60.54% of responses) and low productivity (22.67% of responses) were the main constraints related to the maize-based intercropping system. Farmers have mentioned other challenges such as the difficulty of applying phytosanitary treatments (9.07% of responses), low profitability (3.41%), and competition between crops (3.17%). Some farmers also mentioned that maize-based intercropping systems made harvesting (0.46% of responses) and sowing more difficult (0.22%) and attracted more insect pests (0.46%).

3.4 Maize intercropping systems developed by farmers in the study area

A wide variety of maize-based intercropping systems was recorded in the Republic of Benin (Figure 2). The true cultural association or mixed intercropping, which involves simultaneous planting of both plants, was the most popular system (33.66% of responses). Some farmers (26.54% of responses) in all agro-ecological zones practice crop relay intercropping, where maize is sown in the field 2–4 weeks before companion plants are sown. Other farmers (21.03% of responses) practiced intercropping at the edge of the field, where the maize fields are fenced with different crops. Only a few farmers in agro-ecological zones 4, 5, and 6 practiced maize row intercropping, where the second crop is sown in the furrow corridors (Table 3). In all agro-ecological zones, farmers (17.48% of respondents) tended to combine at least two maize-based intercropping systems.

Figure 2

Figure 2. Examples of types of maize-based intercropping practiced in the Republic of Benin ((a) Maize/groundnut real intercropping system; (b) Maize/rice/yam relay intercropping system; (c) Maize/yam intercropping system; (d) Maize/pineapple field border intercropping; (e) Maize/sorghum/okra intercropping system; (f) Maize/cowpea intercropping system; Maize/chilli/cassava intercropping system].

Table 3

Table 3. Types of maize associations and intercropping systems by agro-ecological zone.

Four types of cultural associations based on various crops were recorded in the study area (Table 3). Maize was most frequently associated with legumes such as peanuts, and beans, which were the most favorable (66.5% of responses) across the study area, particularly in zones 5 and 6. Some farmers (21.68% of respondents) grow maize alongside other cereals. A further 15.86% of respondents associated maize with roots and tubers such as yam, cassava, and cocoyam. Only a small proportion of farmers (5.83%) in agroecological zones 4, 6, 7, and 8 cultivated several types of crops alongside maize. Twenty-one crop plants were used as companion plants in maize-based cropping systems in the study area (Figure 3). The most common plants used in maize intercropping systems were peanut (25.22% of responses), cassava (19.31%), and sorghum (10.78%).

Figure 3

Figure 3. Common crop plants used by farmers in maize-based intercropping systems in the study area.

3.5 Agroecological zones and maize-based intercropping systems

The principal component analysis indicated that the factorization plan using axes 1 and 2 accounted for 23.01% of the observed differences. The analysis revealed that farmers in agro-ecological zones 3 and 7 mainly practiced intercropping in relay of the cereal/legume type, unlike those in zone 5 who practiced a border intercropping association (Figure 4). Farmers in zone 6 mainly practiced border intercropping of cereals and root and tuber crops. Those in zones 4 and 8 practiced a combination of several systems and associations, primarily the ‘intercropping in corridor’ system and maize/vegetable crop associations. Farmers in zone 2 mainly practiced real intercropping of cereal crops.

Figure 4

Figure 4. (A) Projection of agroecological zones in the first factorial plane formed by axes 1 and 2 defined by association systems and types of association. (B) Group formed by the different agroecological zones across association systems and types of association. G1: characterized by a mixed intercrop of maize-cereal type (zone 2); G2: characterized by a relay intercrop of maize-legume type. It includes 2 zones (3 and 7); G3: characterized by several systems and types of association. It includes 2 zones (4 and 8); G4: characterized by an edge intercrop of maize-legume type. It includes 3 zones (5, 6 and 8).

3.6 Ethnicities and maize-based intercropping systems

The Principal Component Analysis revealed that the factorization plan based on axes 1 and 2 accounted for 21.17% of the observed variation. The analysis revealed that the Peulh, Adja, and Ottamari farmers primarily used a real maize/cereal type crop association (Figure 5). Relay intercropping of the cereal/legume type was the main practice of Bariba and Dendi. As for the Yoruba farmers, they mainly practiced border-intercropping association with cereal/legume types. The main practice of Yoa-Lokpa and Fon farmers was to combine various systems and types of crop associations (Figure 5).

Figure 5

Figure 5. (A) Projection of the ethnic groups on the first factorial plane formed by axes 1 and 2 defined by the association systems and types of association. (B) Group formed by the different ethnicities through the association systems and types of association. G1: characterized by a mixed relay cropping system of the maize-cereal type. It is the group of 2 ethnicities (Adja and Peulh); G2: characterized by a relay intercultural cropping system of the maize-legume type. It is the group of 2 ethnicities (Bariba and Dendi); G3: characterized by several systems and types of association. It is the group of 3 ethnicities (Yoa-Lokpa, Ottamari and Yoruba); G4: characterized by edge intercultural cropping of the maize-legume type. It is the group of 1 ethnicity (Fon).

3.7 Taboos related to maize-based intercropping systems

Cultural prohibitions or taboos (21.67% of responses) regarding maize-based intercropping systems were recorded in the study area. In the Plateau department (agroecological zone 7), some farmers (43) revealed that the association of maize with common beans is prohibited because it is a totem of the village fetish which, if transgressed, provokes the anger of the fetish and leads to a scarcity of rain. Some farmers have revealed that the association of maize with sweet potato (7), cotton (4), or sorghum (2) was prohibited because it leads to soil depletion and low yields.

3.8 Determinant of the adoption of maize-based intercropping systems

The choice of the maize-based intercropping systems by farmers was significantly influenced by seven factors, which are age, experience in agriculture, area sown, training in agriculture, main activity, level of education, visit by extension agents and agro-ecological zone (Table 4). Farmers, who have a primary focus on agriculture and a significant amount of experience, have had a substantial influence on the utilization of maize/cereal or maize/root and tuber intercropping systems. While farmers in agroecological zone 2 and those with some level of education positively influenced the use of the maize/legume intercropping system. Household size, sown area, extension service visits, and the agroecological zone 5 positively influenced the use of the maize/vegetable intercropping system. The fact that farmers are landowners and their educational level had a positive impact on interleaving companion crops at the edge of the field. The agricultural experience of the farmers was a significant factor in the combination of several maize-cropping systems (Table 4). Ethnicities or agroecological zones were found to be significantly correlated with the type of association system and association type (Figures 6, 7).

Table 4

Table 4. Factors influencing the choice of cropping association and maize-based cropping system in the study area.

Figure 6

Figure 6. Correlation matrix for all variables (agroecological zones, association systems and types of association). CSS, Combination_several_systems; IEF, Intercrop _edge_field; ICR, Intercrop_in_crop_relay; ISC, Intercrop_spacer_corridor; TCA, True_crops_association; CA, Combination_association; MC, Maize_cereal; ML, Maize_legume; MRT, Maize_Root_and_tuber and MV, Maize_vegetable.

Figure 7

Figure 7. Correlation matrix for all variables (ethnicities, association systems and types of association). CSS, Combination_several_systems; IEF, Intercrop _edge_field; ICR, Intercrop_in_crop_relay; ISC, Intercrop_spacer_corridor; TCA, True_crops_association; CA, Combination_association; MC, Maize_cereal; ML, Maize_legume; MRT, Maize_Root_and_tuber and MV, Maize_vegetable.

4 Discussion

The great majority of surveyed farmers in the study area cultivate maize in association with other crops. This cultural practice is common in Africa as it improves both maize yield and soil fertility (Gidey et al., 2024). Furthermore, intercropping systems based on maize are known to have a positive effect on the management of insect pests such as S. frugiperda, as they maintain diversity among natural enemies in fields (Soujanya et al., 2024). Most farmers reported that they started practicing intercropping after receiving recommendations from other farmers or relatives, participating in farmer field schools in their area, or receiving training. This highlights the importance of considering farmers’ socio-economic and cultural conditions when developing strategies for the adoption of new cultural practices in rural areas (Yabi et al., 2016). Therefore, farmer-to-farmer learning methods, such as farmer field schools or field days, are necessary for implementing push-pull technology in the Republic of Benin, as was the case in Kenya (Amudavi et al., 2009b).

Farmers reported facing challenges when implementing maize-based intercropping systems, primarily relating to field maintenance and low productivity. This is not surprising, as these are the same issues that have led to the limited uptake of leguminous intercropping systems among Zimbabwean farmers (Madembo et al., 2020). Although the difficulty of maintaining maize-based intercropping systems is a reality due to the impracticality of using agricultural machinery for weeding, it nevertheless remains contrasted. Indeed, maize-based intercropping systems have been proven to suppress weeds due to competition for light (Soujanya et al., 2024). In Malawi, for example, farmers prefer to cultivate maize in intercropping systems because of their suppressive effect on Striga populations (Silberg et al., 2020). Some studies showed that maize intercropping systems with legume like soybean can give high yield, while with pigeon pea can give low yield over sole maize cropping (Ngwira et al., 2012; Raza et al., 2022). It is crucial to raise awareness among Beninese producers of the advantages of maize-based intercropping systems and to instruct them in efficient intercropping practices (Huss et al., 2022). Push-pull technology, an intercropping system proven to increase maize yields, improve soil fertility, and reduce pests, must be promoted (Waiswa et al., 2024).

In the study area, four maize-based intercropping systems were identified, and the most popular among surveyed farmers was the association of maize with legumes based on the true crop association system. The performance of this intercropping system is mainly due to its ability to improve soil water use by the complementarity of the root distributions of the associated species (Wu et al., 2016). Moreover, intercropping grain legumes with cereals allows for enhanced land-use efficiency, farm income, and resistance to biotic and abiotic stresses (Gidey et al., 2024). Furthermore, intercropping systems that combine maize with edible legumes can improve the quality and yield of maize (Begam et al., 2024) by reorganizing rhizospheric soil and maize root microbial communities (Jalloh et al., 2024a). Various studies have shown that combining maize and legumes can decrease the damage caused by fall armyworm (Hailu et al., 2018; Udayakumar et al., 2021). Given the significant benefits that farmers can derive from the practice of combining maize and legumes, it is important that the Territorial Agricultural Development Agency (ATDA) popularize this cultivation practice throughout Benin to boost maize production.

Across agroecological zones and ethnicities, crop association types and systems did not have the same importance. The push-pull system, which involves intercropping and trap crops, is based on mixed maize-based intercropping systems commonly practiced by farmers from Yoa-Lokpa and Fon ethnic groups and agroecological zones 4 and 8. A push-pull technology implementation program developed by the International Centre of Insect Physiology (ICIPE) in the Republic of Benin should primarily target these ethnic groups and agro-ecological zones to maximize its adoption by smallholder farmers. However, the fact that Desmodium and Brachiaria are not edible makes it important to choose other crops to integrate nutritional security into push-pull technology (Chidawanyika et al., 2023). It is crucial to conduct surveys and experiments in Benin to find suitable repellent and attractive local plants that are compatible with maize and can be integrated into an efficient push-pull technology.

We found that there was a prohibition on the maize-beans intercropping in some maize-growing areas. This is not surprising because in the Republic of Benin beans are widely used in indigenous religions, and the cultivation of certain varieties, such as Séssé, is prohibited when the field is near a voodoo temple (Loko et al., 2018). Unfortunately, taboos are not unique to Beninese producers. Indeed, Malawian producers cultivate Bambara groundnut in secret and conceal it through intercropping to protect themselves from bad luck, witchcraft, or death (Forsythe et al., 2015). Maize-bean intercropping is a practice used by many producers worldwide (Vazeux-Blumental et al., 2025). For example, Colombian producers use maize-bean intercropping to improve productivity under the combined stress conditions of acidic soils and high temperatures (Suárez et al., 2025). It is therefore important to raise awareness among Beninese producers about the benefits of combining maize with beans, mainly targeting farmers in agroecological zone 2 and those with some level of education. Taking into account the prohibitions and taboos identified in the study area is crucial in the process of popularizing push-pull technology.

The findings showed that farmers’ socioeconomic characteristics have an impact on their selection of intercropping type and system. Indeed, several studies have found that age, gender, education, frequent interactions with extension services or peers, and many other socioeconomic factors were associated with the adoption of intercropping systems by maize producers (Chichongue et al., 2019). In our study area, the combination of practices was greatly influenced by the agricultural experience of farmers. Indeed, farmers who have extensive agricultural experience have sufficient expertise and are more likely to adopt new agricultural methods (Murage et al., 2011). To promote push-pull technology, it would be interesting to target this farmer’s category. However, it is crucial to consider the social and psychological factors of producers, as they have been shown to be significant in the adoption of this technology by smallholder farmers in East Africa (Waiswa et al., 2024). The development of strategies for scaling up push-pull technology requires considering other potential barriers such as availability of relevant inputs, land tenure, gender inequality, and extension capacity (Isgren et al., 2023). To promote the adoption of push-pull technology by farmers, it is essential to create policy interventions that would support it by promoting local innovation platforms that bring together farmers, researchers, and extensionists.

5 Conclusion

The findings of this study revealed that Beninese farmers practice maize-based crop associations and there are four types of crop associations and crop association systems respectively. The main obstacles to the adoption of crop association in maize fields were the difficulty in maintenance and low productivity. The practices and types of crop associations vary according to ethnic groups and agroecological zones. The push-pull method should be implemented in Benin by targeting Yoa-Lokpa and Fon ethnic groups and agroecological zones 4 and 8. To mass adopt the push-pull method by Beninese producers, it is necessary to implement participatory methods such as farmer field schools or field days and target farmers with extensive agricultural experience. However, the implementation of push-pull technology in Benin requires local adaptation through the identification of local plants that produce the same impact as those used by ICIPE. Further research is necessary to evaluate the effectiveness of push-pull systems in the main maize-growing regions of Benin, examine the reasons for adoption and barriers, and evaluate the economic impact of this technology to better guide its implementation.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.

Author contributions

DG: Investigation, Writing – original draft. YL: Conceptualization, Data curation, Formal Analysis, Funding acquisition, Methodology, Project administration, Supervision, Validation, Writing – review & editing. JT: Conceptualization, Writing – review & editing. AD: Writing – review & editing. ID: Writing – review & editing. ET: Writing – review & editing. AY: Writing – review & editing.

Funding

The author(s) declared that financial support was received for this work and/or its publication. This work was supported by the project BIOPAD (N°3116_2023) funded by the Université Nationale des Sciences, Technologies, Ingénierie et Mathématiques (UNSTIM).

Acknowledgments

The authors express their gratitude to the surveyed households for sharing their knowledge and data.

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declare that no Generative AI was used in the creation of this manuscript.

Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.

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