| Literature DB >> 30978224 |
José Guerra1, Pratikshya Acharya1, Céline Barnadas1.
Abstract
BACKGROUND: Involving community members in identifying and reporting health events for public health surveillance purposes, an approach commonly described as community-based surveillance (CBS), is increasingly gaining interest. We conducted a scoping review to list terms and definitions used to characterize CBS, to identify and summarize available guidance and recommendations, and to map information on past and existing in-country CBS systems.Entities:
Mesh:
Year: 2019 PMID: 30978224 PMCID: PMC6461245 DOI: 10.1371/journal.pone.0215278
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Fig 1Variables collected from each included document.
Fig 2Documents selection.
Definitions of the term used to denote the approach of engaging community members in identifying and reporting health events occurring in their community for public health surveillance purposes.
| Reference | Definition |
|---|---|
| [Community-based surveillance is] “a network of lay people involved in the systematic detection and reporting of health-related events from their community” | |
| “CBSS [Community-based surveillance system] is a surveillance system which detects and report diseases from within the community by village health volunteers” | |
| “In this system [Community-based surveillance system], trained surveillance informants identify and report events in the community that have public health significance. Community informants report to the health facility or, in the case of a serious event, directly to the district authorities.” | |
| “CBS [Community-based surveillance] is a set of activities that increase public awareness of the symptoms of a disease or condition and encourage self-initiated case-reporting by the community to the official MOH [Ministry of Health] and/or WHO surveillance authorities. This system includes a mechanism for active case search in the community by non-clinical volunteers or employees and a system for tracking the cases detected. Two elements of this definition are important to note as central to distinguishing CBS from other forms of active surveillance or outreach: (1) case detection activities occur outside a health facility, and (2) those performing case detection activities are community members.” | |
| “Community-based Surveillance (CBS) is an active process of community participation in detecting, reporting, responding to and monitoring health events in the community. The scope of CBS is limited to systematic on-going collection of data on events and diseases using simplified case definitions and forms and reporting to health facilities for verification, investigation, collation, analysis and response as necessary. CBS should be a routine function for: (a) the pre-epidemic period (to provide early warning or alerts); (b) the period during epidemic (to actively detect and respond to cases and deaths); (c) the post-epidemic period (to monitor progress with disease control activities). CBS should also include a process to report rumours and misinformation of unusual public health events occurring in the community.” | |
| “It [Community-based surveillance] is an ongoing activity conducted at community level by community volunteers and includes active case searches during house-to-house visits, religious and traditional healing sites (holy water, prayers, church, mosque) visits, with kalicha (Muslim traditional healers) and reporting to the nearby health facilities” | |
| “Community event-based surveillance is the organized and rapid capture of information from the community about events that are a potential risk to public health.” | |
| “Community-based surveillance is a surveillance system that monitors a broad range of information directly from community members. It is a simple, adaptable and low-cost public health initiative managed by communities to protect communities. CBS empowers trained RC [Red Cross/Red Crescent] volunteers to report unusual events in the community where they live through the use of a mobile phone or other form of communication”. |
Major guidance documents on CBS.
| Title of the document [ref] | Organization (Year) | Main objective of document | Target audience | Topics addressed |
|---|---|---|---|---|
| Academy for Educational Development (2001) | To support polio surveillance for its elimination and surveillance of other diseases, namely: measles, neonatal tetanus, cholera, meningitis, and, yellow fever. | Community surveillance coordinators involved in supervision of surveillance volunteers | ||
| World Health Organization Regional Office for Western Pacific (2008) | To support the “design of event-based surveillance systems”. | Not specified | ||
| World Health Organization Regional Office for Africa (2014) | “To build and strengthen the capacity of communities to conduct effective surveillance and response activities in line with the IDSR [Integrated disease surveillance and response] strategy.“ | Health Facility managers, | ||
| World Health Organization (2014) | “To provide health-care workers in risk areas with a working tool to combat Ebola Virus Disease (EVD) or Marburg Virus Disease (MVD) effectively” | District-level health workers, | ||
| World Health Organization Regional Office for Africa (2015) | To guide training on the aspects of CBS presented in the guide for establishing CBS | Community health workers and anyone who have a role in CBS implementation | ||
| International Rescue Committee (2015) | To describe “the structure and implementation of an effective community event-based surveillance system (CEBS) for Ebola in Sierra Leone” | Community Surveillance Supervisors (CSS), | ||
| International Federation of Red Cross and Red Crescent Societies (2017) | “To provide an understanding of CBS and how it can be used in the countries where Red Cross / Red Crescent (RC) volunteers are involved in strengthening existing national surveillance, as well as RC activities” | National RC societies, |
Fig 3Distribution of CBS systems identified across different countries.
Fig 4Distribution of CBS systems by scopes of interest (n = 79 systems).
a includes influenza like illness and avian influenza; b includes cholera, acute gastrointestinal illnesses; c includes Buruli ulcer (n = 1), cutaneous leishmaniasis (n = 1), yaws (n = 1), smallpox (n = 1); d includes Ebola virus disease and dengue; e includes pregnancy complications (n = 2), low birth weight (n = 1), suicidal and self-injurious behaviour (n = 1); f includes maternal, neonatal, infant, under-five deaths.
Estimates of the sensitivity and positive predictive value of CBS systems.
| Country [ref] | Methodology | Sensitivity calculation | Positive predictive value calculation | Period of interest | Scope | Sensitivity estimate | Positive predictive value estimate |
|---|---|---|---|---|---|---|---|
| Benin [ | Cross-sectional household survey: in 2011 surveyors visited all households covered by the CBS system to collect the same information as collected by the CBS system in 2010. | Not specified | / | 2010 | Maternal death | 95% | / |
| Infant death | 47% | ||||||
| Under 5 death | 48% | ||||||
| Cambodia [ | Cross-sectional household survey: surveyors visited households (in 3 out of 7 areas implementing CBS) to collect cases of diseases (preceding month) and vital events (preceding year), using the same case definitions as used by the CBS system. The survey was conducted once. | (No. of cases/events identified both by the CBS system and the household survey) / (No. of cases or events identified by the household survey) | (No. of cases or events identified both by the CBS system and household survey) / (No. of cases identified by the CBS system) | One year (2000–2001) | Measles | 93% (n = 86/92) | 90% (n = 86/96) |
| Birth | 82% (n = 28/34) | 100% (n = 28/28) | |||||
| One month (2001) | Severe diarrhoea | 82% (n = 10/12) | 82% (n = 10/12) | ||||
| Chronic cough | 75% (n = 55/73) | 89% (n = 55/62) | |||||
| Malaria | 65% (n = 57/88) | 88% (n = 57/65) | |||||
| Ethiopia [ | Cross-sectional survey: in randomly selected villages implementing the CBS system, the blood of suspect malaria cases identified by CBS actors were tested to confirm malaria. | / | (No. of malaria cases confirmed with blood test) / (No. of suspected malaria cases identified by the CBS system) | 1995–1996 | Malaria | / | 93% (n = 1453/1562) |
| Nigeria [ | Confirmatory follow-up visits by an investigator in the villages reported having new cases as well as villages reported having zero cases. | (No. of villages reported confirmed as having cases through the follow-up visit) / (Total No. of villages with verified cases of guinea worm) | (No. of villages reported confirmed as having cases through the follow-up visit) / (Total No. of villages with cases reported by the CBS system). | 6 months (1990–1991) | Guinea-worm disease | 79% (n = 50/63) | 93% (n = 50/54) |
| Sierra Leone [ | Suspected cases were confirmed by laboratory diagnostic test | (No. of confirmed cases detected by the CBS system) / (Total No. of confirmed cases identified in the area). | (No. of confirmed cases detected by the CBS system) / (Total No. of cased detected by CBS system (suspected, probable and confirmed)). | 7 months (2015) | Ebola virus disease | 30% (n = 16/53) | 6% (n = 16/287) |
| Sweden [ | One week recall survey: a sample of participants in the CBS system was sent a questionnaire to collect the occurrence of influenza like illness in the previous week. Each year each participant went through two-three validation surveys. | / | (No. of participants who reported having influenza like illness in both the CBS system and one-week recall survey) / (No. of participants who reported having influenza like illness in the CBS system) | Two 8-week period (in 2008 and 2009) | Influenza like illness | / | 2008: 79% (n = 73/92); |
| Tanzania [ | Cross-sectional survey: investigators visited and searched for mosquito larvae habitat in randomly selected housing clusters (consisting of 20–100 houses) covered by CBS system. | (No. of mosquito larvae habitat identified by the CBS system in the areas covered by cross-sectional survey) / (No. of mosquito larvae habitat reported by investigator during the cross-sectional survey) | / | 8 months (2007–2008) | Mosquito larvae habitat | 66.2% (n = 1963/2965) | / |
Completeness of data reporting for CBS systems.
| Country [ref] | Scope | Reporting rate calculation | Period of interest | Reporting frequency | Completeness of data reporting |
|---|---|---|---|---|---|
| Birth, Death | (No. of catchment areas submitting reports per month) / (Total No. of catchment areas (n = 183)) | 2012–2013 | Monthly | 95% on average | |
| Malaria | (No. of surveillance actors submitting reports per month/week) / (Total No. of surveillance actors (about 2500)) | 1994–1998 | Monthly | 90% on average | |
| Weekly | 60% on average | ||||
| Acute flaccid paralysis, Meningitis, Measles, Neonatal tetanus, Guinea-worm disease, Buruli Ulcer, Birth, Death, Maternal death, Infant death, Unusual events | (Total No. of submitted reports) / (Total No. of expected reports (n = NA)) | 1999 | Monthly | 74% overall (range: 53%’94% for different districts) | |
| Diarrhoea, Malaria, Measles, Dengue, Meningitis, Acute respiratory illness, Tuberculosis, Acute flaccid paralysis, Unusual symptoms, Birth, Death | (Total No. of surveillance actors submitting reports) / (Total number of expected reports (n = 48)) | Six weeks (2005) | Weekly | 91.6% overall by women self-help groups; | |
| Malaria, Birth, Death | Village health volunteers interview (n = 137) | Three previous months (2014) | Monthly | 12.4% stated they reported every month during the 3 previous months (n = 17/137); | |
| Birth, Death | (No. of catchment areas submitting reports per month) / (Total No. of catchment areas (n = 78)) | 2012–2013 | Monthly | 100% on average | |
| Birth, Death | (No. of catchment areas submitting reports per month) / (Total No. of catchment areas (n = 160)) | 2010–2013 | Monthly | 95% on average | |
| Guinea-worm disease | (No. of reports received per week) / (Expected number of reports per week (n = 164)) | 16 weeks (1990) | Weekly | 84% on average | |
| Ebola virus disease | (No. of surveillance actors submitting reports per month) / (Total No. of surveillance actors (n = 7142)) | Six months (2015) | Weekly | 82% on average (range: 38%’92% for different months) | |
| Acute Flaccid Paralysis | Not specified | 2005 | Daily, Weekly | 40.5%: average reporting rate in 2005 for each State. |