Article Text

Community-based surveillance of infectious diseases: a systematic review of drivers of success
  1. Catherine R. McGowan1,
  2. Emi Takahashi2,
  3. Laura Romig3,
  4. Kathryn Bertram4,
  5. Ayesha Kadir2,
  6. Rachael Cummings1,5,
  7. Laura J. Cardinal3
  1. 1Department of Public Health, Environments & Society, London School of Hygiene & Tropical Medicine, London, UK
  2. 2Humanitarian Public Health Technical Unit, Save the Children Fund, London, UK
  3. 3Department of Humanitarian Response, Save the Children Federation, Washington, District of Columbia, USA
  4. 4Department of Health, Behavior, and Society, Johns Hopkins University, Baltimore, Maryland, USA
  5. 5Humanitarian Department, Save the Children International, London, UK
  1. Correspondence to Dr Catherine R. McGowan; catherine.mcgowan{at}


Introduction Community-based surveillance may improve early detection and response to disease outbreaks by leveraging the capacity of community members to carry out surveillance activities within their communities. In 2021, the WHO published a report detailing the evidence gaps and research priorities around community-centred approaches to health emergencies. In response, we carried out a systematic review and narrative synthesis of the evidence describing the drivers of success of community-based surveillance systems.

Methods We included grey literature and peer-reviewed sources presenting empirical findings of the drivers of success of community-based surveillance systems for the detection and reporting of infectious disease-related events. We searched for peer-reviewed literature via MEDLINE, EMBASE, Global Health, SCOPUS and ReliefWeb. We carried out grey literature searches using Google Search and DuckDuckGo. We used an evaluation quality checklist to assess quality.

Results Nineteen sources (17 peer-reviewed and 2 grey literature) met our inclusion criteria. Included sources reported on community-based surveillance for the detection and reporting of a variety of diseases in 15 countries (including three conflict settings). The drivers of success were grouped based on factors relating to: (1) surveillance workers, (2) the community, (3) case detection and reporting, (4) and integration.

Discussion The drivers of success were found to map closely to principles of participatory community engagement with success factors reflecting high levels of acceptability, collaboration, communication, local ownership, and trust. Other factors included: strong supervision and training, a strong sense of responsibility for community health, effective engagement of community informants, close proximity of surveillance workers to communities, the use of simple and adaptable case definitions, quality assurance, effective use of technology, and the use of data for real-time decision-making. Our findings highlight strategies for improving the design and implementation of community-based surveillance. We suggest that investment in participatory community engagement more broadly may be a key surveillance preparedness activity.

PROSPERO registration number CRD42022303971.

  • Systematic review
  • Public Health

Data availability statement

Data sharing not applicable as no datasets generated and/or analysed for this study.

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:

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  • Community-based surveillance can provide an essential complement to facility-based surveillance systems, which may have limited effectiveness in some settings due to poor facility attendance.

  • Previous reviews of community-based surveillance (in crisis-affected settings) and event-based surveillance (in low and middle-income settings) have concluded that challenges to community-based surveillance often involve the failure to address operational requirements.


  • Our findings highlight the alignment between many of the identified success factors and principles of participatory community engagement including high levels of community acceptability, meaningful and ongoing collaboration, effective communication, local ownership, and trust.


  • Given the close alignment between success factors and the principles of participatory community engagement, we suggest that the emphasis of community-based surveillance preparedness should be on investing in community participation approaches more broadly such that these may be leveraged in an emergency.

  • Developing and deploying a community-based surveillance system based on known drivers of success may improve their efficiency and effectiveness; however, it is important to balance the burdens of community-based surveillance (particularly in resource-limited settings) against the potential benefits.


Community-based surveillance (CBS) is defined by the WHO as: ‘…the systematic detection and reporting of events of public health significance within a community by community members’.1 Though CBS is often designed for the routine detection and reporting of infectious diseases, it is a potentially versatile and scalable intervention and has been used for the detection and reporting of non-communicable diseases2–4, for monitoring births and deaths5 6, for carrying out verbal autopsies7 8, and more recently, for containing outbreaks of COVID-19.9–12 A CBS system can: provide early case detection and reporting during disease outbreaks; monitor events of public health importance in humanitarian emergencies; and supplement non-existent or limited surveillance coverage in other complex settings.13 In addition, CBS is one of the few suitable options for supporting OneHealth surveillance activities given its proximity to the interface between humans and animals.14 15 Given its potential to enhance the early warning and containment function of national surveillance systems, CBS is increasingly framed as a promising surveillance modality in the discourse around global health security.16

Case identification and reporting are often carried out at health facilities. Health facilities are able to perform these functions for various reasons: (1) they are typically staffed by healthcare workers who are able to carry out case identification based on standardised case definitions, (2) they are part of a network capable of centralised communication and reporting using an established data collection system, (3) they may provide allied health services (eg, laboratory services) that enable case detection and confirmation, and (4) they attract people who are seeking care for diseases or conditions under surveillance. The effectiveness of facility-based surveillance systems is largely dependent on context-specific healthcare-seeking behaviours. Health facilities may be difficult to access and may require people to weigh the challenges of accessing a facility against more proximal and practical concerns. Limited access to health facilities may encourage and inculcate community preference for informal care, particularly in remote areas with limited transportation options, and in countries that require out-of-pocket payments for health services. Community distrust of healthcare actors and/or a lack of confidence in the quality of health services also erode willingness to engage with services. Even in settings with strong facility-based surveillance systems, late presentation of patients with an infectious disease is common and often results in over-representation of late-stage infections that may be difficult and costly to manage. Delayed health seeking may increase community transmission, complicate case investigation and contact-tracing, and limit the impact of public health measures including health education and behaviour change initiatives, vaccination, and antimicrobial prophylaxis. CBS—which involves engaging community members to carry out specific surveillance functions within their own communities—is intended to complement facility-based systems by addressing these challenges, particularly in rural areas within low-resource settings.

In July 2021, the WHO published the findings of an ad hoc consultation on community-centred approaches to health emergencies with the aim of identifying evidence gaps and research priorities.17 The consultation proposed that a review of the evidence was required to determine, ‘what methodologies and approaches are being used for community surveillance, and what are the fundamental drivers of success?’17 (p. 32). A 2019 scoping review by Guerra et al18 presents a thorough description of CBS methods and approaches; thus, the aim of this review is to synthesise the empirical evidence of the key success factors of CBS systems. Our review expands beyond the scope of Ratnayake et al19 (which was limited to the use of CBS in humanitarian crises) and Kuehne et al20 (which focused exclusively on event-based surveillance), and incorporates learning from recent studies evaluating the use of CBS for the detection and reporting of COVID-19.

This review is reported against the updated Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines including the extension for abstract reporting.21 22 The review was published in the PROSPERO prospective review database (CRD42022303971).23


Eligibility criteria

We defined eligibility as any empirical source that included a significant evaluative component and that described CBS in a manner consistent with the definition proposed by the technical contributors to the 2018 WHO global technical meeting.1 We included peer-reviewed or grey literature sources reporting on the use of CBS for event-based or indicator-based surveillance. We limited sources to those that described CBS in the context of infectious diseases (including parasitic infection) in humans. We included sources that identified drivers of success (regardless of how the authors defined success), provided there was a clear empirical basis for such assertions. We included sources in any language, employing any method (ie, qualitative or quantitative), or reporting on the use of CBS in any setting.

Sources that focused exclusively on the use of CBS for vector control or non-human animal surveillance were excluded, as were sources focusing exclusively on the evaluation of a technological solution. In addition, we excluded sources that did not aim to evaluate CBS, that were not substantially focused on CBS, or that focused exclusively on one specific aspect of CBS (eg, training). We excluded reviews and conference abstracts.

Information sources and search strategy

We searched for peer-reviewed literature via MEDLINE, EMBASE and Global Health databases (via Ovid). We also searched SCOPUS and ReliefWeb. All searches were carried out using proximity and controlled vocabulary searches. We limited our search strategy to the last 10 years (beginning 1 January 2012) assuming: (a) that there would be very little published evidence before this time period (the evidence gap was identified in 202117), and (b) that CBS approaches have been refined over time and that it would therefore be sensible to focus on current iterations of CBS approaches in the context of diseases of current importance to public health. All database searches were carried out on 7 February 2022. The complete search strategy is included in online supplemental appendix 1.

Supplemental material

Two members of the review team carried out grey literature searches using both the Google and DuckDuckGo search engines, and by searching relevant websites (eg, Médecins Sans Frontières’s (MSF) Science Portal, WHO’s Publications website) using ‘community-based surveillance’ as the primary search term. The grey literature searches were carried out during the first week of February 2022.

Data extraction and synthesis

Two authors independently reviewed all peer-reviewed sources; disagreements were resolved by a third author. One author reviewed grey literature sources. One author manually extracted all data by coding sources in NVivo V.1.0 (Melbourne, Australia: QSR International). Data were extracted based on the following domains: (1) the CBS system (ie, description of the CBS system, the problem CBS was intended to address, the disease(s)/condition(s) under surveillance, the data that were collected, and the setting in which the CBS system was implemented, performance indicators and evaluation methods), and (2) the reported challenges and drivers of success. We undertook a narrative synthesis of the literature with an emphasis on the evidence of drivers of success.

Quality assessment

We used the evaluation quality checklist created by Warsame et al to simplify the quality assessment (online supplemental appendix 2).24 This method allowed us to focus on the quality of the evaluative aspects of the included sources and to allocate weighted scores based, in part, on the degree to which the challenges and drivers of success were substantiated by the empirical evidence. One author completed the scorecard for all sources; scores were compared with those of a second author for two sources before the remainder of the scorecards were completed. We did not assess risk of bias.

Supplemental material

Patient and public involvement

Humanitarian health professionals have been involved in every stage of this review including in its design, conduct, and write-up. Our team includes humanitarians with direct experience designing, implementing, and/or otherwise supporting community-based and facility-based surveillance systems. The entire review team has experience working in conflict settings and/or in infectious disease outbreak response.


Study selection

Our initial database search resulted in 1274 records published between 2012 and 2022. Removal of duplicate records was carried out using EndNote V.20 (Philadelphia, Pennsylvania, USA: Clarivate) and resulted in 881 unique records. Sixty-eight records remained following the initial screening on title and abstract; the full-text was retrieved for all included sources. Two authors reviewed the 68 full-text sources. Full-text review resulted in the exclusion of 51 sources owing to: (1) an unsubstantial focus on CBS, (2) a disproportionate focus on a specific aspect of CBS (eg, training), (3) no evaluative component and/or lack of empirical evidence, (4) a lack of focus on the use of CBS for infectious disease detection and reporting, (5) exclusive focus on vector control or animal surveillance (eg, diseases in pigs/dogs only), (6) exclusive focus on evaluating the effectiveness of a technological solution and (7) no mention of success factors. Other systematic reviews and conference abstracts were also excluded. The grey literature search identified 20 sources; the full text for all 20 sources was retrieved. Of these, only two met the inclusion criteria; the remaining 18 sources did not include any evaluation. Nineteen sources were included in the final synthesis. The PRISMA flow chart is included in figure 1.

Figure 1

PRISMA flow diagram. CBS, community-based surveillance; PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses.

Study characteristics

The study characteristics are included in table 1. The included sources reported on CBS in: Bangladesh25, Cambodia26, Cameroon27, Côte d’Ivoire28, the Dominican Republic29, the Democratic Republic of the Congo (DRC)30, Ethiopia31 32, Ghana33 34, Niger11, Nigeria35, Senegal36, Sierra Leone37 38, South Sudan39 40, Vietnam41, and Yemen.12 Two CBS systems were described in the context of refugee/internally displaced person camps (Bangladesh and Yemen) and three were deployed into an active conflict setting (Cameroon, South Sudan, and Yemen). No studies of the use of CBS in high-income settings were identified.

Table 1

List of sources and CBS characteristics

Sources evaluated CBS for detection and reporting of: buruli ulcer33, COVID-1911 12, Ebola virus disease30 37, guinea worm40, malaria26 29, polio31 39, and multiple infectious diseases.25 27 28 32 34–36 38 41 The CBS systems were designed specifically to address the following problems:

  1. Limitations to the effectiveness of facility-based surveillance systems

    These limitations included: delayed care seeking resulting in advanced clinical presentation and/or complicated and costly treatment33; delayed care seeking resulting in poor prognosis including comorbidities, permanent disability or death12 33; cases not presenting to health facility, low health service uptake, and/or poor access to health facilities11 12 27 30 31 35 38; and healthcare facilities lacked event-based reporting, had poor indicator reporting (eg, no established alert threshold), or are not required to report.11 27 34 41

  2. Heightened risk/vulnerability within communities

    These included: an outbreak or spike in cases detected and/or high community transmission26 29 30 38 39, low levels of vaccination39, high population movement39, insecurity27 39, and endemic and/or high numbers of cases40 and/or the need for urgent containment.12 26 37

  3. Health system factors

    These included: existing surveillance system slow to identify cases36; community health workers underused, not engaged in case detection and/or reporting41; insufficient health system capacity to contain outbreak11 12 30; poor integration of OneHealth34; disease or condition is low incidence (requiring expanded case detection) and high priority for early detection31 39; and CBS established in response to a formal review/assessment/technical consultation of surveillance capacity.34–36 39 41

Three CBS systems were implemented out of a desire/opportunity to scale up an existing community-based function to include CBS, or to scale up an existing CBS system to include surveillance of infectious diseases.28 32 37 Additionally, one was developed as part of a global elimination effort (ie, guinea worm)40; another was developed as part of a system of standard epidemiological tools/functions to monitor the health of the refugee population in Cox’s Bazar, Bangladesh.25

Included sources described CBS systems that involved the recruitment of community members (eg, community health workers, community health volunteers) to carry out active surveillance, the scale up of an existing surveillance system (to include new infectious diseases), or the scale up of an existing community health worker programme (to involve disease surveillance). The CBS systems included both event-based surveillance, indicator-based surveillance, and a mixture of both.


The quality of the included sources ranged from 0.35 (out of 1) to 0.925 (table 2). We considered five sources very high quality (between 0.9 and 1.0)12 33 35 39 41, six high quality (between 0.8 and 0.89),25–28 34 37three moderate quality (between 0.7 and 0.79),29 30 38and five of lower quality (below 0.69).11 31 32 36 40 Most sources contained a clear rationale, a clear objective, and a thorough description of the operational context. Few sources used or reported using a formal evaluation framework or assessment tool despite the fact that such resources are available.42–44

Table 2

Quality assessment

Results of synthesis

We report below a narrative synthesis of our findings. Our emphasis, in line with the WHO call for evidence, is on identifying drivers of success.17 Some of the challenges we identified whilst carrying out this review have been reported elsewhere19 20; we have included a brief summary of the challenges we identified in online supplemental appendix 3.

Supplemental material

Drivers of success

Success factors fell broadly into four categories: (1) CBS workers (often community health workers), (2) community, (3) case detection and reporting, and (4) integration.

CBS workers

The CBS workers were described as those responsible for active case detection. Additionally, CBS workers were often responsible for a number of additional tasks including: reporting, referral, follow-up, case management, health promotion, physical examinations (eg, for buruli ulcer33), and testing (eg, taking blood slides for malaria parasites26).

Acceptance of CBS workers

Successful CBS was believed to be associated with community acceptance of the CBS workers that was, in turn, associated with their recruitment (ie, having the community nominate the CBS workers31 33 or recruiting CBS workers from within the community25 27 38), or with having nested CBS within an existing emergency response system that itself had good acceptability (which, in turn, was attributed to active participation and collaboration with communities).27 Trust between CBS workers and the community was also described as a key success factor.25 29 31 38

Motivation of CBS workers

Success was also attributed to high motivation of CBS workers who described their motivation in terms of: ‘contributing to bringing good health to the people’33 (p. 10), feeling a sense of service to the community26 29 38 41, and a desire to increase ties and trust with other community members.29 41 Training opportunities and the opportunity to increase knowledge were also described as motivating factors, even when the programme lacked material incentives.26 Success in achieving high performance and acceptance of CBS workers in Ghana was, in part, ascribed to efforts made to ‘follow all community protocols and encourage the people to see the project as their own’33 (p. 9). A sense of camaraderie amongst CBS workers and a shared sense of responsibility for bringing an outbreak of malaria under control were also felt to be associated with the success of a CBS programme in the Dominican Republic.29 Volunteer CBS workers in Ghana were provided with material incentives (in the form of a token to cover travel costs, plus a bicycle), which were described as motivating factors in addition to a sense of service and ownership of the CBS programme.33 Finally, CBS workers in Sierra Leone derived satisfaction from knowing that they had saved lives of people with Ebola; ‘volunteers gave examples of cases they had reported which had received response and treatment […] many of the volunteers were confident that the death rate had decreased due to [CBS workers] influencing people to seek medical attention earlier”38 (p. 4).

CBS worker proximity to communities

The close proximity of CBS workers to their communities was felt to have contributed to increased detection of disease clusters in Vietnam41 and better overall case detection in the Dominican Republic.29 The CBS programme amongst conflict-affected populations in Cameroon succeeded in collecting data from populations despite ‘pendular displacements’; this was attributed to the fact that CBS workers were travelling with their communities and were thus able to continue surveillance.27 Similarly, CBS workers in Ethiopia were able to spend time at locations where pastoralist communities congregate (eg. wells or water collection areas, mosques, marketplaces), allowing CBS workers to carry out polio surveillance among a nomadic population.31

Supervision and training

Strong supervision was believed to have influenced the success of CBS programmes for malaria in Cambodia26, acute flaccid paralysis (AFP)—a proxy for polio—in South Sudan39, Ebola in Sierra Leone37, and eight high-priority diseases in Senegal.32 Training was also frequently mentioned as a key factor in the success of CBS, either due to its effect on motivation of CBS workers or improving the quality of their work (in terms of quantity of reports and the specificity of case detection).26 28 34 39 41 Training was felt to be particularly important in low transmission settings where CBS workers have few opportunities to practise their skills.26 Availability of refresher training was also felt to be important and resulted in an increase in the quality of blood sample slides in a CBS system for malaria in western Cambodia.26


Several success factors related to the interaction between the CBS system and the community: effective communication and engagement strategies, and the recruitment of community informants were both described as influencing the success of CBS programmes.

Communication and engagement

Communication and engagement were the most frequently cited success factors of CBS. For example, increased community involvement and ‘innovative communication strategies’ (ie, a text-based reporting system to enable real-time reporting of signals) were felt to improve signal detection in Côte d’Ivoire28 (p. S-32). Providing feedback to communities was associated with completeness of reporting in Nigeria35, and increased community reporting in Cameroon.27 In Ethiopia, CBS workers organised village coffee ceremonies at which they were able to ask for reports of AFP and discuss signs, symptoms and reporting.31 Engagement with community leaders was positively associated with programme uptake in Vietnam.41 Finally, strong community engagement was believed to have been key to the success of an AFP programme in South Sudan39, a malaria surveillance and control programme in the Dominican Republic29, and an Ebola surveillance system in Sierra Leone.37

Recruitment of community informants

Several CBS systems relied on the recruitment of community informants who would report suspect cases to CBS workers. The recruitment of a diverse team (including money lenders, insurance agents, veterinary health staff, landlords, factory managers, community leaders and others) of informants with strong community ties in Vietnam, ‘…broadened the sources of reporting and resulted in the reporting of numerous signals that otherwise would have been missed, such as school absenteeism reported by teachers and the resulting multiple detections of vaccine-preventable disease (eg, mumps and chickenpox)’41 (p. 1656). In Nigeria, there was a significant positive association between informant satisfaction and completeness of disease notification35, and field interviews in South Sudan indicated that having a network of community informants in every village contributed to the effective functioning of the CBS system.39

Case detection and reporting

Successes relating to data collection included: dynamic (ie, adapted and improved) use of case definitions34; the implementation of quality assurance procedures (ie, data were regularly reviewed for accuracy and completeness)30; and engaging in rapid, real-time data-driven decision-making.25 30 41 Efforts to improve the office environment (eg, by implementing a filing system) in the health posts supporting a CBS pilot in Ethiopia were found to improve record keeping and reporting.32

The use of technology for data collection and reporting was generally reported as a challenge, though two sources referenced successful use of technological solutions which ‘removed reporting obstacles and may account for the increase in the number of notifications’ (in the case of a text-based reporting system in Côte d’Ivoire)28 (p. S-31) and was cited by WHO as ‘a critical factor for improved early detection of suspected cases’ (in the case of a voice and SMS-based alert system in DRC)30 (p. S-89). It should be noted that the text and voice messaging solutions in Côte d’Ivoire and DRC were described as ‘simple’ and yet both systems received considerable technological support from the International Rescue Committee (in Côte d’Ivoire), and RT International, MSF and the WHO (in DRC).28 30

Ultimately, the most often observed driver of success was simplicity with respect to the design of data collection and reporting tools (eg, ‘tools should aim to collect a minimum set of data that can provide usable information, should be clear and simple, and minimise burden to implementers’34 (p. 10)). Simplifying data collection by limiting the number of reportable diseases28, and by simplifying signals28 and case definitions12 40, was associated with ease of reporting, case identification and reducing the proportion of false alerts.

Integration with the wider surveillance system

Effective vertical integration of CBS with different actors along the reporting pathway (eg, from communities, to the health facility, to the regional/national surveillance system), and lateral integration between the CBS system and other components of the surveillance system at, or close to, the same operational level (eg, laboratory services, operational partners) were identified as success factors.

Vertical integration

Clear reporting pathways from communities through the various levels within the wider surveillance system were felt to have: improved timeliness of reporting and response in Cameroon27; enabled regular reporting and rapid case confirmation in Ethiopia32, Vietnam41, Senegal36, and Niger11; and increased community engagement in polio eradication in South Sudan.39 Widespread mobile phone coverage, coupled with the close proximity of health posts to communities (most were within a 30-minute walk), ensured regular reporting of suspect cases of communicable diseases from CBS volunteers and health extension workers (who were responsible for case confirmation and reporting to the cluster health centre) in southern Ethiopia.32

In Niger, an extensive polio surveillance system was scaled to include active case finding and reporting of COVID-19.11 The polio surveillance system used established reporting pathways (from community health workers up to the Central Supervisory Directorate of Public Health); thus, the COVID-19 CBS capitalised on pre-existing vertical integration and avoided the, ‘structural challenges [of] establishing a de novo CBS to respond to an emerging public health crisis’11 (p. 5).

Lateral integration

A CBS system for OneHealth surveillance was deemed to have been successful due to the close collaboration between the Ghana Health Service and the Veterinary Services Directorate.34 Additionally, members of the wider surveillance system (at the regional and district levels) received targeted training on multiagency coordination.34

The simplicity of the CBS system in Cox’s Bazar, Bangladesh was felt to have enabled easy integration with other aspects of the surveillance system (eg, WHO’s Early Warning, Alert and Response System).25 System integration was also managed by a focal point who was appointed to submit reports and coordinate between the WHO and MSF.25


Success factors largely fell into four categories: 1) CBS workers, 2) community, 3) case detection and reporting, and 4) integration. In addition to individual-level factors (such as motivating and training CBS workers) and system factors (including simplifying data collection systems and coordinating with formal surveillance systems and partner organisations), successes were largely attributed to effective leveraging of community knowledge and capacity. This acknowledgement of the importance of ‘bottom-up’ solutions speaks to a common sense recognition of the importance of participatory approaches that are now endorsed as essential to the effectiveness of a myriad of health interventions (eg, maternal and newborn care,45 water and sanitation46). Ultimately, the evidence largely points towards drivers of success that map closely to principles of participatory community engagement.47 48

There is an expanding body of literature evidencing the importance of community participation and meaningful co-production in the management of infectious disease outbreaks.49–51 Guidelines on the design and implementation of CBS attempt, in varying degrees, to operationalise principles of community participation in order to enhance the effectiveness of surveillance efforts.10 13 52–57 Building genuine community participation into the design and implementation of a specific public health function, like infectious disease surveillance, is both time-consuming and resource intensive. However, our review has highlighted that many of the key drivers of success of CBS map to the principles and best practices of community participation, including: enabling and emphasising community ownership29 33; committing to meaningful engagement27 28 37 39 41 and bilateral information exchange11 26–28 31 35; involving a diverse group of community informants35 39 41; recognising and enabling the desire, and competency, of community members to help themselves26 29 33 38 41; and ensuring that systems are designed to build on the trust and goodwill within communities.25 29 31 38 These drivers of success were manifested not only in observed community acceptance (evidenced, for example, in 94% of community members agreeing to a physical examination for buruli ulcer)25–27 33, but were attributed to the overall success of the CBS programme.12 27 34 37

A CBS system cannot operate independently of a facility-based system and must be complemented by a reliable and effective system for responding to alerts.58 It is notable that strategies which were identified as having improved system integration within the wider surveillance system were both intuitive (eg, capitalising on existing reporting pathways, close proximity of health posts to communities, and widespread mobile phone coverage) and straightforward (ie, assigning a focal point, clarifying reporting pathways). However, some of these successes may have relied on serendipitous features of a particular response that may be difficult to reproduce in a more logistically complex setting. This highlights that do-no-harm approaches to CBS require careful consideration of the operational context, and acknowledgment that in some settings CBS may not be feasible or appropriate. Ultimately, the benefits of CBS should be balanced against potential resource requirements (including the opportunity cost of moving limited resources into surveillance activities and the cost to sustain CBS system over time) as well as the burden CBS places on communities.44 In some settings, a more effective and efficient approach to surveillance preparedness may involve bolstering the capacity of facility-based systems whilst increasing their accessibility and working to develop community confidence and trust. It is also important to consider that the consequences of poor implementation can be considerable and can further erode trust between communities and healthcare providers.

Beyond the benefits to case detection and reporting, a well-designed and skilfully implemented CBS system enables the forming of resilient community networks, increases community awareness of infectious diseases, and provides an effective platform with the potential to absorb additional public health functions. Even though effective CBS may be both time and resource intensive, we find that the evidence largely supports the inclusion of CBS as a component of outbreak preparedness and response.


There are several important limitations to our review.

Limitations of the evidence

Few sources provided a thorough description of the design and deployment of the CBS system, making it difficult to create a descriptive typology of systems as originally planned23: it is notable that a lack of sufficient descriptive information has been identified elsewhere.18–20 Though we accept that the lack of granular description is almost certainly the result of the often restrictive length limits of academic journals, few sources included additional descriptive information in annexes. This lack of granular description has limited the degree to which we are able to associate drivers of success (and challenges) with aspects of system design. There was also an absence of sufficient detail to describe some drivers of success, which complicates their interpretation and potential for improving future CBS systems.

None of the published sources presented the results of a comprehensive evaluation with many reporting on only a few specific outcomes and/or performance indicators. Despite this, all included sources made some attempt to evaluate an operationalised CBS system and to present empirically informed learning. Finally, the authors of the included sources were often involved in the design and implementation of the study suggesting a potential bias towards presenting more favourable results.

Limitations of the review process

We restricted our search to a 10-year period starting 1 January 2012. Though we found evidence of evaluations published prior to 2012, the bulk of the relevant evidence has been published since 2016 (which coincides with the publication delay of research on the West African Ebola outbreak 2013–2016). Despite carrying out our searches in early 2022, we were only able to identify two sources reporting on the use of CBS in the context of COVID-19.11 12 This suggests that much of the evidence on the current use of CBS for the detection and reporting of COVID-19 may be forthcoming, and that this review should be updated to provide a more substantial response to the WHO’s call for evidence.

In addition, database search terms for CBS lack precision and generate many irrelevant sources relating to CBS studies (ie, epidemiological research studies carried out within communities). The high number of irrelevant sources retrieved using the search term ‘community-based surveillance’ has been noted in other reviews.18 Finally, we suspect that we may have missed sources that describe CBS, but which do not reference it as such.


Though the evidence details numerous challenges to CBS, it also highlights key successes. Ultimately, our findings—insofar as they emphasise the benefits of meaningful community participation—suggest that developing CBS preparedness is more likely to be both successful and sustainable within communities that are actively engaged in designing and implementing a range of co-produced public health solutions. As such, we believe that the emphasis of CBS preparedness should be on investing in community participation approaches in health more broadly—to enable the leveraging of this approach in an emergency—rather than on investing exclusively in siloed public health functions such as CBS.

Our database search identified several sources reporting exclusively on the use of CBS for identifying the presence of animal vectors, and for identifying zoonotic diseases in pigs and dogs. Though outside the scope of this review, we would welcome a systematic review focused exclusively on the use of CBS as part of a OneHealth approach. In addition, few of the sources identified in this review reported on community perceptions of CBS, lending force to the suggestion included in the WHO ad hoc consultation report, that collecting community accounts about their experiences with CBS is an important research priority.17

Finally, we endorse the recommendation that all CBS programmes be subject to rigorous evaluation19 20 and reassert the suggestion, published elsewhere, that evaluations be published, that they follow an established evaluation framework or assessment tool that contains multiple domains including those that are often overlooked (eg, connectedness, coherence and impact), and that they include performance indicators co-produced with communities themselves.59

Data availability statement

Data sharing not applicable as no datasets generated and/or analysed for this study.

Ethics statements

Patient consent for publication

Ethics approval

Not applicable.


Supplementary materials


  • Handling editor Seye Abimbola

  • Contributors CM—conceptualisation, methodology, formal analysis, resources, investigation, data curation, writing (original draft), writing (review and editing), supervision, guarantor. ET—formal analysis, investigation, writing (original draft), writing (review and editing). LR—quality assessment, formal analysis, investigation, writing (original draft), writing (review and editing). KB—writing (original draft), writing (review and editing). AK—writing (review and editing). RC—conceptualisation, funding acquisition, writing (review and editing). LC—conceptualisation, funding acquisition, writing (original draft), writing (review and editing), supervision.

  • Funding This review was made possible by the generous support of the American people through the US Agency for International Development (USAID).

  • Disclaimer The contents are the responsibility of READY Initiative and do not necessarily reflect the views of USAID or the US Government.

  • Competing interests None declared.

  • Patient and public involvement Patients and/or the public were involved in the design, or conduct, or reporting, or dissemination plans of this research. Refer to the Methods section for further details.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.