Event-based surveillance in north-western Ethiopia: experience and lessons learnt in the field

Evaluation of National Event-Based Surveillance, Nigeria, 2016-2018

Nigeria Centres for Disease Control and Prevention established an event-based surveillance (EBS) system in 2016 to supplement traditional surveillance structures. The EBS system is comprised of an internet-based data mining tool and a call center. To evaluate the EBS system for usefulness, simplicity, acceptability, timeliness, and data quality, we performed a descriptive analysis of signals received during September 2017–June 2018. We used questionnaires, semistructured interviews, and direct observation to collect information from EBS staff. Amongst 43,631 raw signals detected, 138 (0.3%) were escalated; 63 (46%) of those were verified as events, including 25 Lassa fever outbreaks and 13 cholera outbreaks. Interviewees provided multiple examples of earlier outbreak detections but suggested notifications and logging could be improved to ensure action. EBS proved effective in detecting outbreaks, but we noted clear opportunities for efficiency gains. We recommend improving signal logging, standardizing processes, and revising outputs to ensure appropriate public health action.

Rumor surveillance methods in outbreaks: A systematic literature review

Background: The spreading of health-related rumors can profoundly put society at risk, and the investigation of strategies and methods can efficiently prevent the dissemination of hazardous rumor is necessary, especially during a public health emergency including disease outbreaks. In this article we review the studies that implicated the surveillance system in identifying rumors and discuss the different aspects of current methods in this field. Methods: We searched PubMed, EMBASE, Scopus, and Web of Science databases for relevant publications in English from 2000 to 2020. The PICOS approach was used to select articles, and two reviewers extracted the data. Findings were categorized as a source of rumors, type of systems, data collection, and data transmission methods. The quality of the articles was assessed using the Mixed Method Appraisal Tool (MMAT) checklist. Results: Five studies that presented the methods used for rumor detection in different outbreaks were included in the critical appraisal process. Findings were grouped into four categories: source of rumors, type of systems, data collection, and data transmission methods. The source of rumors in most studies was media, including new social and traditional media. The most used data collection methods were human-computer interaction technique, and automatic and manual methods each were discussed in one study. Also, the data transmission method was asynchronous in the majority of studies. Conclusion: Based on our findings, the most common rumor detection systems used in the outbreaks were manual and/or human-computer methods which are considered to be time-consuming processes. Due to the ever-increasing amount of modern social media platforms and the fast-spreading of misinformation in the times of outbreaks, developing the automatically and real-time tools for rumor detection is a vital need.

Community Health Workers and Disease Surveillance in Tanzania: Promoting the Use of Mobile Technologies in Detecting and Reporting Health Events

This cross-sectional study was conducted in the Kilosa, Morogoro Urban, Ngorongoro, and Ulanga districts of Tanzania to investigate the practices of community health workers (CHWs) related to disease surveillance functions and to establish their needs and technology capacities. We also established the strength of mobile phone networks and internet connections in the study areas to inform the feasibility of using mobile-based applications in community-based disease surveillance. A total of 135 CHWs from 85 villages participated in the study. Health events captured at the community level were entirely paper-based. CHWs submitted reports to higher-level health authorities mainly on foot (100%), but they also used public transport (65%) and telephone calls (56%). The median number of days between the onset of a suspected disease outbreak at the community level and reporting to a primary healthcare facility was 10 days (interquartile range [IQR] 2-30). The median number of days between submitting a report and receiving a response was 7 days (IQR 2-30). Of the 53 CHWs who reported the most recent health events to a higher-level health authority, 39 (74%) never received feedback. All 85 villages had a reliable mobile phone network and 74 (87%) had a mobile phone internet connection that was strong enough to support data transmission using digital technology. Almost all (n = 132, 98%) of the CHWs owned mobile phones. The practices related to detection and reporting of health events could be improved to enhance early warning disease surveillance. Reliable mobile networks and internet connections and the ownership of mobile phones among CHWs in the study areas present opportunities to strengthen community event-based surveillance using mobile-based solutions.

Community-Based Surveillance in Côte d'Ivoire

Community-based surveillance can be an important component of early warning systems. In 2016, the Côte d'Ivoire Ministry of Health launched a community-based surveillance project in 3 districts along the Guinea border. Community health workers were trained in detection and immediate reporting of diseases and events using a text-messaging platform. In December 2017, surveillance data from before and after implementation of community-based surveillance were analyzed in intervention and control districts. A total of 3,734 signals of priority diseases and 4,918 unusual health events were reported, of which 420 were investigated as suspect diseases and none were investigated as unusual health events. Of the 420 suspected cases reported, 23 (6%) were laboratory confirmed for a specific pathogen. Following implementation of community-based surveillance, 5-fold and 8-fold increases in reporting of suspected measles and yellow fever clusters, respectively, were documented. Reporting incidence rates in intervention districts for suspected measles, yellow fever, and acute flaccid paralysis were significantly higher after implementation, with a difference of 29.2, 19.0, and 2.5 cases per 100,000 person-years, respectively. All rate differences were significantly higher in intervention districts (p < 0.05); no significant increase in reporting was noted in control districts. These findings suggest that community-based surveillance strengthened detection and reporting capacity for several suspect priority diseases and events. However, the surveillance program was very sensitive, resulting in numerous false-positives. Learning from the community-based surveillance implementation experience, the ministry of health is revising signal definitions to reduce sensitivity and increase specificity, reviewing training materials, considering scaling up sustainable reporting platforms, and standardizing community health worker roles.

Developing monitoring and evaluation tools for event-based surveillance: experience from Vietnam

BACKGROUND

In 2016-2017, Vietnam's Ministry of Health (MoH) implemented an event-based surveillance (EBS) pilot project in six provinces as part of Global Health Security Agenda (GHSA) efforts. This manuscript describes development and design of tools for monitoring and evaluation (M&E) of EBS in Vietnam.

METHODS

A strategic EBS framework was developed based on the EBS implementation pilot project's goals and objectives. The main process and outcome components were identified and included input, activities, outputs, and outcome indicators. M&E tools were developed to collect quantitative and qualitative data. The tools included a supervisory checklist, a desk review tool, a key informant interview guide, a focus group discussion guide, a timeliness form, and an online acceptability survey. An evaluation team conducted field visits for assessment of EBS 5-9 months after implementation.

RESULTS

The quantitative data collected provided evidence on the number and type of events that were being reported, the timeliness of the system, and the event-to-signal ratio. The qualitative and subjective data collected helped to increase understanding of the system's field utility and acceptance by field staff, reasons for non-compliance with established guidelines, and other factors influencing implementation.

CONCLUSIONS

The use of M&E tools for the EBS pilot project in Vietnam provided data on signals and events reported, timeliness of reporting and response, perceptions and opinions of implementers, and fidelity of EBS implementation. These data were valuable for Vietnam's MoH to understand the function of the EBS program, and the success and challenges of implementing this project in Vietnam.

Strengthening timely detection and reporting of unusual respiratory events from health facilities in Yaoundé, Cameroon

BACKGROUND

The International Health Regulations state that early detection and immediate reporting of unusual health events is important for early warning and response systems.

OBJECTIVE

To describe a pilot surveillance program established in health facilities in Yaoundé, Cameroon in 2017 which aimed to enable detection and reporting of public health events.

METHODS

Cameroon's Ministry of Health, in partnership with the US Centers for Disease Control and Prevention, Cameroon Pasteur Center, and National Public Health Laboratory, implemented event-based surveillance (EBS) in nine Yaoundé health facilities. Four signals were defined that could indicate possible public health events, and a reporting, triage, and verification system was established among partner organizations. A pre-defined laboratory algorithm was defined, and a series of workshops trained health facilities, laboratory, and public health staff for surveillance implementation.

RESULTS

From May 2017 to January 2018, 30 signals were detected, corresponding to 15 unusual respiratory events. All health facilities reported a signal at least once, and more than three-quarters of health facilities reported ≥2 times. Among specimens tested, the pathogens detected included Klebsiella pneumoniae, Moraxella catarrhalis, Streptococcus pneumoniae, Haemophilus influenza, Staphylococcus aureus, Pneumocystis jiroveci, influenza A (H1N1) virus, rhinovirus, and adenovirus.

CONCLUSIONS

The events detected in this pilot were caused by routine respiratory bacteria and viruses, and no novel influenza viruses or other emerging respiratory threats were identified. The surveillance system, however, strengthened relationships and communication linkages between health facilities and public health authorities. Astute clinicians can play a critical role in early detection and EBS is one approach that may enable reporting of emerging outbreaks and public health events.

Event-based surveillance at health facility and community level in low-income and middle-income countries: a systematic review

Background

The International Health Regulations require member states to establish “capacity to detect, assess, notify and report events”. Event-based surveillance (EBS) can contribute to rapid detection of acute public health events. This is particularly relevant in low-income and middle-income countries (LMICs) which may have poor public health infrastructure. To identify best practices, we reviewed the literature on the implementation of EBS in LMICs to describe EBS structures and to evaluate EBS systems.

Methods

We conducted a systematic literature search of six databases to identify articles that evaluated EBS in LMICs and additionally searched for grey literature. We used a framework approach to facilitate qualitative data synthesis and exploration of patterns across and within articles.

Results

We identified 778 records, of which we included 15 studies concerning 13 different EBS systems. The 13 EBS systems were set up as community-based surveillance, health facility-based surveillance or open surveillance (ie, notification by non-defined individuals and institutions). Four systems were set up in outbreak settings and nine outside outbreaks. All EBS systems were integrated into existing routine surveillance systems and pre-existing response structures to some extent. EBS was described as useful in detecting a large scope of events, reaching remote areas and guiding outbreak response.

Conclusion

Health facility and community-based EBS provide valuable information that can strengthen the early warning function of national surveillance systems. Integration into existing early warning and response systems was described as key to generate data for action and to facilitate rapid verification and response. Priority in its implementation should be given to settings that would particularly benefit from EBS strengths. This includes areas most prone to outbreaks and where traditional ‘routine’ surveillance is suboptimal.

Factors Influencing Community Event-based Surveillance: Lessons Learned from Pilot Implementation in Vietnam

Community event-based surveillance aims to enhance the early detection of emerging public health threats and thus build health security. The Ministry of Health of Vietnam launched a community event-based surveillance pilot program in 6 provinces to improve the early warning functions of the existing surveillance system. An evaluation of the pilot program took place in 2017 and 2018. Data from this evaluation were analyzed to determine which factors were associated with increased detection and reporting. Results show that a number of small, local events were detected and reported through community event-based surveillance, supporting the notion that it would also facilitate the rapid detection and reporting of potentially larger events or outbreaks. The study showed the value of supportive supervision and monitoring to sustain community health worker reporting and the importance of conducting evaluations for community event-based surveillance programs to identify barriers to effective implementation.

Assessment of Community Event-Based Surveillance for Ebola Virus Disease, Sierra Leone, 2015

Case detection improved, but many false alerts were generated, suggesting a need for additional staff training.

In 2015, community event–based surveillance (CEBS) was implemented in Sierra Leone to assist with the detection of Ebola virus disease (EVD) cases. We assessed the sensitivity of CEBS for finding EVD cases during a 7-month period, and in a 6-week subanalysis, we assessed the timeliness of reporting cases with no known epidemiologic links at time of detection. Of the 12,126 CEBS reports, 287 (2%) met the suspected case definition, and 16 were confirmed positive. CEBS detected 30% (16/53) of the EVD cases identified during the study period. During the subanalysis, CEBS staff identified 4 of 6 cases with no epidemiologic links. These CEBS-detected cases were identified more rapidly than those detected by the national surveillance system; however, too few cases were detected to determine system timeliness. Although CEBS detected EVD cases, it largely generated false alerts. Future versions of community-based surveillance could improve case detection through increased staff training and community engagement.