From the grassroots up: Redefining Public Health Surveillance in Nigeria through Community Action Networks

Abstract

Background:

Gaps in community-level surveillance continue to limit early detection of communicable diseases in Nigeria, particularly for zoonotic and emerging infections. Strengthening participatory, One-Health (OH)–oriented surveillance systems is critical for improving outbreak preparedness and response. The objective of this study is to evaluate the operational performance of Community Action Networks (CANs) in strengthening participatory, OH–oriented disease surveillance in Nigeria.

Methodology:

This was a retrospective program evaluation of the implementation of CAN under the West Africa One Health (WAOH) project. The project was conducted in eight Local Government Areas (LGAs) in five states. Community members (12– 15 per site) were trained in disease recognition, reporting, and risk communication using standardised tools. Surveillance data collected between January 2023 and March 2025 were analysed using descriptive and comparative approaches.

Results:

Eighty-six CAN members were trained. Between January 2023 and March 2025, 800 health events were reported across eight LGAs. Human health events accounted for 674 (84.2%), environmental events 62 (7.8%), and animal health events were infrequently reported. Reporting increased over time, with higher contributions from rural areas and substantial participation by female members (39, 45.4%). Most reports were channelled through District Surveillance and Notification Officers 559 (69.9%), indicating integration with existing surveillance structures. However, investigation and confirmation rates were higher for human health events compared to animal and environmental events.

Conclusion:

The CAN model demonstrates operational feasibility and potential to strengthen community-based surveillance and integration into national systems. Addressing gaps in animal and environmental health coordination will be essential for fully realising OH surveillance in Nigeria.

Introduction

Public health surveillance is a globally recognised strategy for controlling and preventing communicable diseases and other public health events [1,2]. It provides essential evidence for understanding disease spread in humans and animals, including novel hosts or locations [3–5]. enabling early detection and timely intervention to reduce morbidity and mortality [6,7]. Effective surveillance forms the foundation for data-driven decision-making [4].

An estimated 60% of all known infectious diseases and 75% of emerging or re-emerging infections are of animal origin [8]. Consequently, surveillance must adopt a multidisciplinary One Health (OH) approach that integrates human, animal, and environmental health with policy, agriculture, and trade considerations [9]. One Health is defined as “a collaborative, multisectoral, and transdisciplinary approach recognising the interconnection between people, animals, plants, and their shared environment” [10]. This approach enhances outbreak detection before pathogens spread widely among humans [9,11] and relies on collaboration and information exchange among sectors and with national and international organisations [5,10].

In Nigeria, disease reporting historically lacked standardisation, with states free to submit data in varying formats and intervals. The 1986/87 yellow fever outbreak, which affected over 19 states, led to the creation of a national disease surveillance and notification system [12]. A decade later, the Integrated Disease Surveillance and Response (IDSR) strategy—adopted by the WHO-AFRO in 1998—was introduced to unify multiple surveillance systems for cost-effectiveness and early detection [6,13]. Full implementation began in 2001 with the establishment of the IDSR steering committee [14,15]. Operating from the community to the national level, the local government area (LGA) serves as the principal application point for collecting data via standard case definitions, generating alerts, and triggering actions such as laboratory testing and outbreak investigations [9,15].

Many low- and middle-income countries, including Nigeria, have poorly structured clinical settings with high infectious disease burdens and limited point-of-care diagnostic capacity [16,17]. Emerging and re-emerging infections are especially difficult to detect [15]. Most IDSR-detected cases originate from facility-based surveillance [14,15,18], which is dependent on healthcare professionals recognising and reporting notifiable diseases [19]. Although IDSR is designed to begin at the community level, implementation at that level has been suboptimal [20,21], delaying detection and prompting costly National Rapid Response Team deployments. WHO guidance emphasises community engagement in surveillance [9,22], and evidence shows that community-based surveillance strengthens early detection and response [6,9]. Outbreaks often begin and end in communities; coordinated local action supported by higher levels of government forms the foundation for resilient, disease-free populations [23,24].

The West Africa One Health (WAOH) project aimed to accelerate and expand actions to prevent and mitigate infectious disease outbreaks at the community and national levels in four West African countries (Sierra Leone, Guinea, Liberia, and Nigeria) while also providing a better understanding of socioecological drivers, impacts, and solutions at the human–animal–environment interface. The project aimed to support disease surveillance in Nigeria by building strong community-based participatory surveillance organisations called the Community Action Network (CAN).

The CAN concept is rooted in well-tested and trusted methods such as Community-Based Participatory Research (CBPR), a proven method for tackling public health challenges from infectious diseases to obesity [25,26]. CBPR “combines methods of inquiry with community-oriented capacity-building strategies to bridge the gap between knowledge and what is practised in communities” [27]. It creates solutions with those affected by health issues, engaging community leaders, health workers, women’s groups, civil organisations, and policymakers. Participatory research in diverse settings, including rural areas, fosters capacity, ownership, and sustainability [28,29]; increases trust in health systems [23]; and strengthens the ability of communities and decision-makers to mobilise resources, improve policies, and deliver better services

This study aimed to evaluate the operational performance and feasibility of CANs in strengthening participatory, OH–oriented disease surveillance in Nigeria.

Our specific objectives were to:

• 1.Describe the demographic, educational, and professional composition of CAN members involved in community-based surveillance.
• 2.Assess the contributions of CAN to the detection and reporting of human, animal, and environmental health events.
• 3.Examine key surveillance performance indicators, including reporting volume, geographic coverage, sectoral distribution, and reporting pathways within the existing surveillance system.
• 4.Identify strengths, operational challenges, and gaps in the implementation of community-led One Health surveillance.
• 5.Provide evidence-informed recommendations for strengthening, scaling, and sustaining CAN as a model for participatory surveillance within Nigeria’s health system.

Methods

Study Design and Site Selection

This study was a retrospective program evaluation of the Community Action Network (CAN) model implemented under the West Africa One Health (WAOH) project in Nigeria. The evaluation utilised routinely collected surveillance data to assess the operational performance of community-based participatory surveillance across selected sites.

The WAOH project was piloted across six Nigerian states—Ebonyi, Edo, Ogun, Lagos, Ondo, and Oyo— covering eleven Local Government Areas (LGAs). Site selection was guided by epidemiological risk profiling, including proximity to international borders, Lassa fever endemicity, and strategic relevance for emerging and re-emerging infectious diseases such as Lassa fever, mpox, COVID-19, and Ebola.

Within each state, LGAs with the highest vulnerability to these priority diseases were identified. In states with multiple high-risk LGAs, two LGAs were selected (except Oyo State, where one LGA was selected). The selected LGAs were: Ebonyi (Izzi, Ezza), Lagos (Somolu, Badagry), Ondo (Akure South, Owo), Oyo (Iwajowa), Edo (Etsako West, Esan West), and Ogun (Ipokia, Abeokuta South).

Following site selection, implementation of CAN activities, including training, was conducted in nine LGAs. Lagos State LGAs (Somolu and Badagry) were excluded at this stage due to the delayed commencement of CAN activities.

For the final analysis, eight LGAs were included: Izzi, Ezza, Owo, Iwajowa, Etsako West, Esan West, Ipokia, and Abeokuta South. Akure South LGA was excluded due to incomplete reporting data during the study period (Figure 1).

Figure 1:

Flow Diagram of Study Site Selection, Implementation, and Final Analytical Inclusion for the Community Action Network (CAN) model.

Stakeholder Mapping and Coordination

Sustained community engagement relies on multisectoral collaboration and clear role definitions [30]. Stakeholder mapping creates a network of all the actors influencing project success (Figure 2) [31]. Engagement began nationally, targeting senior officers in the Federal Ministries of Health, Agriculture, and Environment; the Chief Veterinary Officer; the Nigeria Centre for Disease Control leadership; and long-standing partners such as the WHO and Damien Foundation.

Figure 2:

WAOH Stakeholder Mapping

At the state level, coordination was structured in three tiers:

• •Administrative: Formal introduction letters were sent to Commissioners, Permanent Secretaries, and Directors in each line ministry. The ministry composition varied slightly by state but consistently covered health, agriculture (veterinary services), and the environment (environmental health).
• •Intermediate: Three State Coordinators per state, one from each ministry, were appointed based on expertise, availability, and leadership skills. One was designated State Lead, serving as liaison between field teams and state-level management. State leaders received dedicated training workshops.
• •Field level: Included LGA coordinators, health facility focal points, CAN members, and community representatives

Composition of the Community Action Network

The CAN is a multidisciplinary group of 12–15 carefully selected, trusted community members, representing both males and females, who actively reside in the target LGA. The members included community leaders, religious figures, women’s group leaders, NGO representatives, community health workers, animal health workers, environmental health officers, traditional birth attendants and healers, patent medicine vendors (PMVs), hunters, pastoralists, and farmers.

CAN members function as disease surveillance agents, collecting and relaying information on health events affecting humans, animals, and the environment to their coordinators or DSNOs. They also acted as mobilisers, OH champions, immunisation advocates, and community health educators.

Training of CAN Members

CAN capacity-building focused on outbreak recognition, reporting, and basic OH principles. Standardised one-day, in-person training was conducted at each site. Although the training dates varied, all the sites followed the same manual and schedule. Only those who attended and completed the training were eventually enlisted to participate in the project. The training modules included:

• •Overview of WAOH
• •Community case definitions of IDSR priority diseases, with emphasis on WAOH targets
• •Basics of infection prevention and control
• •Disease reporting channels and standard operating procedures (SOPs) for CAN operations
• •Introduction to the OH approach and its relevance to surveillance

The participants completed pre- and post-tests via a pretested, interviewer-administered electronic questionnaire on the Open Data Kit (ODK) platform. Trained enumerators conducted interviews in local languages. A total of 86 members from 8 CANs in five states were included in the training.

Innovations in CAN Implementation

The CAN structure integrated personnel from key OH ministries—DSNOs, Area Veterinary Officers, and LGA Environmental Health Officers—forming the surveillance backbone. SOPs outlined roles and responsibilities at the state and LGA levels.

To enhance timeliness and reach, CAN adopted mobile-based participatory surveillance, building on precedents such as the Global Rinderpest Eradication Program [32]. Mobile technology has expanded real-time reporting capacity even in remote, underserved areas [33,34]. CAN members used SMS, WhatsApp, and phone calls to communicate with LGA coordinators, who escalated reports to DSNOs and WAOH management. This digital workflow allowed rapid two-way communication, file sharing, and virtual coordination across dispersed teams.

Surveillance and Reporting Process

CAN members monitored and reported a broad range of events, including the following:

• •Human and animal disease cases
• •Deaths (human and unusual animal deaths)
• •Environmental hazards (pest infestations, illegal dumping, pollution, chemical spills, severe flooding)
• •Community-level rejection of public health interventions (e.g., immunisation)
• •Any event beyond community capacity that requires external support

Reports were submitted via:

• 1.SMS to the CAN or State Coordinator
• 2.Phone calls to CAN or State Coordinator
• 3.Messages to a designated or personal WhatsApp account of CAN/State Coordinator
• 4.In-person visits to the DSNO/CAN coordinator

The LGA, DSNO, or reporting officer then completed an electronic case form documenting the CAN member’s details, event description, and epidemiological data (person, place, time).

Data Collection and Analysis

Surveillance performance was assessed using routinely collected program monitoring data from January 2023 to March 2025.

“Key Performance Indicators” included reporting volume (number of detected events), geographic coverage, sectoral distribution (human, animal, and environmental health), and reporting pathways within the surveillance system.

Health events reported by CAN members included suspected or confirmed diseases in humans and animals, unexplained deaths, and environmental hazards such as pollution, flooding, and waste-related issues. Each reported event was recorded as a discrete observation and included relevant details such as event type, location, and basic descriptive information.

LGAs were classified as urban, rural, or semi-urban based on predominant settlement patterns and infrastructure characteristics. Accordingly, Izzi, Ezza, Iwajowa, and Ipokia were classified as rural LGAs; Abeokuta South as urban; and Etsako West, Esan West, and Owo as semi-urban.

Data were cleaned, validated, and analysed using IBM SPSS Statistics (version 26). Descriptive statistics were used to summarise event distribution across locations and sectors. Comparative analyses were conducted to assess variations in reporting patterns by geographic classification (rural, urban, semi-urban) and to show trends over time (quarterly for each year included)

Ethical approval was obtained from the University of Ibadan/University College Hospital Ethical Review Committee (UI/EC/22/0305; approved on 18 August 2022). Written informed consent was obtained from all participants, and all data were handled in accordance with confidentiality protocols, with personal identifiers removed before analysis.

Results

Demographic Characteristics of CAN

Eighty-six CAN members belonging to eight CANs in five States were trained, and the mean age of the participants was 40.3 years (SD = 9.6), with most being aged 31-40 years 35(40.7%). Among those trained, 49 (46.2%) participants were female. Fifty-two CAN members 52 (60.5%) lived in rural areas, and the majority 72 (83.7%) had spent more than five years in their respective communities. Up to 68 (79.1%) members were currently married and living with their partners. Most of the CAN members were Christians 68 (79.1%), whereas 15 (17.4%) were Muslims. Although many of the CAN members lived or worked in rural areas, 62 (72.1%) participants had undergone tertiary education (Table 1).

Table 1:

Sociodemographic Characteristics of the Trained CAN Members (N=86)

Variable	Frequency (n)	Percentage (%)
State
Ebonyi	14	16.3
Edo	17	19.8
Ogun	20	23.3
Ondo	22	25.6
Oyo	13	15.1
Age category (in years) Mean age = 40.3 ± 9.6SD
≤30	11	12.8
31-40	35	40.7
≥41	40	46.5
Sex
Female	39	45.4
Male	47	54.7
Level of Education
Less than secondary	5	5.8
Secondary	19	22.1
Tertiary	62	72.1
Marital status
Currently married and living with spouse/husband	68	79.1
Not currently married	18	20.9
Religion
Christianity	68	79.1
Islam	15	17.4
Others	3	3.5
Location
Rural	52	60.5
Urban	34	39.5
Length of residency in current community
≤5yrs	14	16.3
>5yrs	72	83.7

The CAN had diverse members, including community leaders, PMVs, farmers, medical workers, animal and environmental health officers, and many other key stakeholders who could play critical roles in disease prevention, detection, reporting, mitigation and control (Figure 3). Thirty-nine members (45.4%) were female, ensuring gender balance.

Figure 3:

Composition of trained CAN members by occupation in pilot states

CAN Surveillance Network Activities

From 20 January 2023, when the first case was reported, to 31 March 2025, a total of 800 health events involving eight LGAs were reported by CANs from currently active states. The majority 674 (84.2%) of reported health events were from the human health sector, whereas the fewest 62 (7.8%) were from the environmental health sector. Edo State reported 490 (61.3%) events, followed by Ebonyi 173 (21.7%) and Ogun 114 (14.3%). The events selected from the communities involved a diverse range of individuals connected to CAN, including community health workers 24 (22.4%), traditional leaders 21 (2.6%) and pastoralists 30 (3.8%). Most of the health events were submitted to the reporting platforms by the DSNOs 559 (69.9%) and LGA CAN Coordinator 175 (21.9%) (Table 2).

Table 2:

Characteristics of the CAN Surveillance Reporting (N=800 reported events)

Variable	Frequency (n)	Percent (%)
Health event
Environmental Health	62	7.8
Animal Health	64	8.0
Human health	674	84.2
State (LGA)
Ogun
i. Abeokuta South	98	12.3
ii. Ipokia	16	2.0
Edo
i. Esan West	78	9.8
ii. Etsako West	412	51.5
Oyo
i. Iwajowa	10	1.3
Ebonyi
i. Izzi	135	16.9
ii. Ezza	38	4.8
Ondo
i. Owo	13	1.6
Sex of CAN members who reported the health event
Female	221	27.6
Male	579	72.4
Designation of CAN members who reported cases
Women Leader	2	0.3
Hunter	9	1.1
Patent Medicine Vendors	19	2.4
Community/Traditional leaders	21	2.6
Farmers	22	2.8
Pastoralist	30	3.8
Community Health Worker	179	22.4
*Others	518	64.8
Sex of Officers who submitted Reports
Female	289	36.1
Male	511	63.9
Designation of Officers who submitted Reports
Area Veterinary Officer	38	4.8
DSNO	559	69.9
LGA CAN Coordinator	175	21.9
State Coordinator	28	3.5

*includes teachers, animal health professionals, artisans, food vendors, religious leaders, and business owners

Nature of Reported Events

CAN activities were linked to state-level One Health coordination structures. Reported events were communicated through DSNOs and, where relevant, referred to veterinary or environmental authorities for investigation, i.e.

Community → CAN Member → DSNO → Human health / Veterinary / Environmental CAN member → Response (investigation)s

For example:

• •Flooding → When flooding occurred in Abeokuta, an environmental authority was notified, and an investigation was carried out. Also, when a CAN member reported a rat infestation in Etsako LGA, Edo State, the ministry stakeholder was contacted, an investigation was done, and the environmental authority was contacted to do De-ratisation in the area, which was successfully done.
• •Livestock death → A veterinary investigation in Ebonyi that affected thousands of goats in a farm was conducted after a CAN member reported it.
• •Rabies→ After a dog bite from a rabid dog, a CAN member, who is also a veterinarian, contacted the victim at the hospital and collected the blood sample for laboratory testing. The testing proved that it was indeed rabies, though the bite victim eventually died. The project contributed to the lab testing and confirmation of the cause of death

Human Health Events

Approximately 674 (84.2%) human health events were reported during the period under review. Nearly two-thirds of the disease events reported were Lassa fever cases 431 (63.9%). Other suspected diseases reported were measles 48 (7.1%) and Mpox 33 (4.9%). CAN sites in Edo State reported the most cases, 451 (66.9%), Ebonyi State reported 111 (16.5%) disease events, and Ogun State reported 79 (11.7%) cases. Most events identified by CAN members were reported through the recommended IDSR channels, and 632 (79.0%) were investigated. Samples were collected from 590 (73.8%) of the suspected cases, with 155 (26.3%) confirmed. About 126 (72.4%) of the disease events were resolved (Table 3).

Table 3:

Distribution of Reported Human Cases and Other Related Factors (N=674)

Variable	Frequency (n)	Percent (%)
Specific disease suspected
Acute flaccid paralysis	24	3.6
Chickenpox	16	2.4
Lassa fever	431	63.9
Cholera	11	1.6
Diphtheria	4	0.6
Elephantiasis	4	0.6
Leprosy	5	0.7
Malaria	30	4.5
Measles	48	7.1
Monkeypox	33	4.9
Rabies	2	0.3
Yellow Fever	9	1.3
Other/Unidentified Incidence	57	8.5
LGA (State)
Abeokuta South (Ogun)	79	11.7
Esan West (Edo)	64	9.5
Etsako West (Edo)	387	57.4
Ipokia (Ogun)	14	2.1
Iwajowa (Oyo)	8	1.2
Izzi (Ebonyi)	82	12.2
Ezza North (Ebonyi)	29	4.3
Owo (Ondo)	11	1.6
Event investigated
Yes	632	79.0
No	168	21.0
Sample collected for event
Yes	590	73.8
No	210	26.2
Result
Negative	89	15.1
Pending	346	58.6
Positive	155	26.3
Has event been resolved
Yes	579	72.4
No	126	15.8
Don’t know	95	11.9

Animal Health Events

Sixty-four animal health events were reported, with over half from Izzi, Ebonyi State, 38 (59.4%), followed by Ogun State, 9 (14.1%). Some of the events that occurred in sheep and goats were reported through the National Animal Health Information System (NADIS) platform and were investigated. Still, no definitive diagnosis has been entered into the CAN surveillance system.

However, most events 49 (76.6%) were not investigated, and samples were collected in only 9 (14.1%) of the cases. In 55 (85.9%) of the cases, no result was available, whereas only one case (1.6%) yielded a positive result. With respect to event resolution, only 14 (21.9%) were confirmed to be resolved, 11 (17.2%) remained unresolved, and 39 (60.9%) of CAN members were unsure (Table 4).

Table 4:

Distribution of Reported Animal Cases and Other Related Factors (N=64)

Variable	Frequency (n)	Percent (%)
LGA (State)
Abeokuta South (Ogun)	9	14.1
Esan West (Edo)	3	4.7
Etsako West (Edo)	8	12.5
Ezza North (Ebonyi)	5	7.8
Izzi (Ebonyi)	38	59.4
Owo (Ondo)	1	1.6
Event investigated
Yes	15	23.4
No	49	76.6
Sample collected for event
Yes	9	14.1
No	55	85.9
Result
None	55	85.9
Pending	8	12.5
Positive	1	1.6
Has event been resolved
Yes	14	21.9
No	11	17.2
Don’t know	39	60.9

Environmental Health Events

Some of the reported issues were "illegal dumping of refuse" (16 cases), flooding (9 cases) and air pollution (8 cases). Etsako West (17 incidents) and Izzi (15 incidents) had the highest total number of reported events, whereas Owo had the lowest (1 incident) (Figure 4). Some issues, such as "rat infestation" and "water pollution," were less commonly reported and occurred in only a few LGAs.

Figure 4:

Frequency of occurrence of environmental health events by reporting LGA

Geographic Coverage

The CAN members covered some areas within and around the selected LG areas in Ogun, Oyo, Edo, Ebonyi and Ondo State, Nigeria (see additional files).

Comparison by Geographic Classification

A total of 800 health events were reported across urban, rural, and semi-urban LGAs. Human health events constituted the majority across all settings, accounting for 674 (84.3%) of total reports. The proportion of human events was highest in semi-urban areas (91.8%), followed by urban (80.6%) and rural LGAs (66.8%).

Environmental events represented a smaller proportion overall (62; 7.8%), with comparable contributions from rural (11.6%) and urban areas (10.2%), but lower representation in semi-urban LGAs (5.8%).

Animal health events accounted for 64 (8.0%) of total reports and were disproportionately higher in rural LGAs (21.6%) compared to urban (9.2%) and semi-urban areas (2.4%).

The observed difference in the distribution of event types across the three settings was statistically significant (p < 0.001) (Table 5).

Table 5:

A Comparative Table Showing Differences across Geographic Settings (N=800 events)

Indicator	Urban n (%)	Rural n (%)	Semi-urban n (%)	Total N (%)	P-value
Human events	79 (80.6)	133 (66.8)	462(91.8)	674 (84.3)	<0.001*
Environmental events	10 (10.2)	23 (11.6)	29 (5.8)	62 (7.8)
Animal events	9 (9.2)	43 (21.6)	12 (2.4)	64 (8.0)

*significant P-value

Quarterly Trends in Reported Events by Geographic Area (2023-2025):

Quarterly analysis revealed dynamic shifts in reporting patterns across geographic settings from 2023 to early 2025. In the early implementation phase (2023 Q1–Q2), semi-urban LGAs dominated reporting, contributing 35(66.0%) and 18 (66.7%) of total events, respectively, while urban contributions were minimal, including no reported events in 2023 Q2.

In 2023 Q3, rural LGAs recorded the highest proportion of reports, 19 (46.3%), marking an early indication of increased rural engagement. This was followed by a return to semi-urban dominance in 2023 Q4 78 (74.3%).

In 2024, semi-urban LGAs again accounted for the majority of reports in Q1 169 (92.9%) and Q2 68 (77.3%). However, a notable shift occurred in Q3 and Q4, where rural LGAs contributed the largest proportions, 62 (46.6%) and 36 (44.4%), respectively, reflecting a substantial increase in rural reporting activity.

By 2025 Q1, reporting was more evenly distributed across all settings, with semi-urban LGAs contributing 40(44.4%), rural LGAs 31 (34.4%), and urban LGAs 19 (21.1%).

The observed difference in the reporting trends across the three settings was statistically significant (p < 0.001 (Figure 5).

Figure 5:

Quarterly Trends in Reported Events by Geographic Area (2023-2025) 1076

Discussion

The composition and characteristics of the initial Community Action Network (CAN) cohort reflect a strategic investment in grassroots capacity for disease surveillance in Nigeria. By mobilising a demographically diverse and socially embedded group of `non-traditional community actors, the CAN model aligns with best practices that emphasise local ownership, culturally appropriate interventions, and inclusive engagement.

A notable strength of the network is the relatively high level of education and digital literacy among members. Many participants, including those in rural areas, demonstrated the ability to use mobile tools for communication and reporting, challenging common assumptions about limited digital capacity in such settings [35–37]. Evidence suggests that higher educational attainment is associated with greater readiness to adopt health innovations [38], which likely supports CAN members’ ability to understand surveillance concepts and serve as effective intermediaries between communities and formal health systems.

The multidisciplinary composition of CAN, comprising traditional leaders, religious figures, patent medicine vendors, community health workers, and animal and environmental health personnel—facilitates engagement across the OH spectrum. Leveraging trusted community actors is consistent with established health communication frameworks that emphasise culturally relevant messaging and local influence [39]. This is further strengthened by the social embeddedness of members, whose longstanding residency and community roles enhance trust, support early reporting, and improve responsiveness. For instance, patent medicine vendors often serve as first points of care in underserved areas and can play an important role in guiding care-seeking behaviour [40].

Gender representation within the network also contributes to its operational relevance. The inclusion of women in both leadership and participation roles supports engagement with populations that are often underserved and enables more context-sensitive communication strategies, consistent with global recommendations on participatory leadership in health [41].

From an operational perspective, the network demonstrated its ability to extend the reach of the Integrated Disease Surveillance and Response (IDSR) system, particularly in underserved LGAs [42]. The predominance of human health events, including Lassa fever, reflects both community sensitisation and functional reporting pathways between CAN members and Disease Surveillance and Notification Officers. Variations in reporting across locations, such as higher contributions from certain states, highlight the influence of local epidemiology, infrastructure, and stakeholder engagement on system performance.

Over time, reporting patterns showed notable shifts across geographic settings. Semi-urban LGAs initially accounted for the majority of reported events, likely reflecting better infrastructure and earlier uptake of CAN activities. However, increasing contributions from rural LGAs—particularly from late 2023 through 2024—suggest gradual strengthening of community-based surveillance in these settings. By early 2025, reporting was more evenly distributed across rural, urban, and semi-urban areas, indicating broader system engagement. These trends suggest that participatory surveillance models may require a period of adaptation before reaching optimal functionality, particularly in resource-constrained contexts.

Differences in the distribution of event types further highlight contextual dynamics. Human health events predominated across all settings, especially in semi-urban areas, possibly reflecting closer integration with formal healthcare systems. In contrast, rural LGAs reported a higher proportion of animal-related events, consistent with greater human–animal interaction in these environments. Environmental events were reported across all settings but in relatively smaller proportions, which may reflect variations in awareness, reporting priorities, or institutional response mechanisms.

Although multisectoral reporting was observed, the relatively lower contribution of animal and environmental events in some settings suggests opportunities to strengthen engagement across these sectors. Enhancing collaboration with veterinary and environmental health services, improving feedback mechanisms, and strengthening coordination structures will be important for advancing a more integrated OH surveillance approach [43-44].

Animal health surveillance, in particular, appears less developed within the current system. Reports were fewer and less frequently followed up, which may reflect broader structural challenges such as limited diagnostic capacity, resource constraints, and weaker integration with existing platforms such as the National Animal Disease Information System (NADIS) [45]. Addressing these issues will be important to ensure balanced participation across all One Health domains and to sustain community engagement.

Despite these challenges, the ability of CAN to generate community-level intelligence across human, animal, and environmental domains provides an important proof of concept. The findings suggest that, with appropriate training, support, and system responsiveness, community actors can contribute meaningfully to early detection and reporting of diverse health risks.

Limitations

This study utilised routinely collected program data and employed primarily descriptive analyses, consistent with its program evaluation design. As such, causal inferences cannot be established. In addition, variations in reporting across locations and sectors may reflect differences in system maturity, implementation timelines, and resource availability. While these factors may influence interpretation, the findings provide useful insights into the operational dynamics of community-based surveillance and highlight areas for strengthening multisectoral coordination.

Conclusion

This study demonstrates the value of One Health strategies and community engagement in strengthening disease surveillance in Nigeria. CAN’s integration of grassroots mobilisation, mobile technology, and multisectoral collaboration has expanded participatory surveillance and improved linkages between communities and the formal health system. By engaging trusted local actors, Nigeria has taken a significant step toward earlier detection and response to infectious diseases.

Future expansion of CAN should prioritise the following:

• 1.Geographic scale-up to additional states, tailored to local epidemiology and stakeholder landscapes.
• 2.Strengthening cross-sector linkages, especially with environmental and animal health systems.
• 3.Embedding structured multisectoral training in risk recognition and reporting.
• 4.Improving feedback and resolution mechanisms to maintain trust and engagement.
• 5.Institutionalising CAN through national policy integration, sustained investment, and adaptive learning frameworks.

By addressing these priorities, Nigeria can evolve CAN into a fully integrated, sustainable one-health surveillance platform capable of responding to complex public health threats.

Declarations

• 1.Ethics approval and consent to participate

• Ethical approval for this study was obtained from the University of Ibadan/University College Hospital (UI/UCH) Ethics Committee (Reference number: UI/EC/22/0305). Written informed consent was obtained from all participants before their involvement in the study.

• 2.Consent for publication

• Not applicable. All participants provided informed consent for participation, and no individually identifiable data were reported.

• 3.Availability of data and materials

• The datasets generated and/or analysed during the current study are available from the corresponding author upon reasonable request.

• 4.Competing interests

• The authors declare that they have no competing interests.

• 5.Funding

• This work was supported by the International Development Research Centre (IDRC), Canada (Partial Funding for Research). The views expressed in this publication are those of the authors and do not necessarily reflect the views of the IDRC or its Board of Governors.

• 6.Authors' contributions

• SC and RA conceptualised the study and secured funding. MB and FO curated the data and conducted the formal analysis. EC and SC led the investigation and project administration. SC and RA developed the methodology. FO and MB provided study resources, while MB conducted data visualisation. Statistical analysis was performed via SPSS. SO, AF, AJ, AO, and TO provided supervision. SC led the validation activities. FO, MB, and EC drafted the original manuscript. All the authors contributed to manuscript review and editing and approved the final version.

Acknowledgements

The authors sincerely acknowledge the dedication and support of the CAN members towards the effective implementation, high-quality reporting, and successful delivery of project activities across participating states.