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Fighting Lassa fever through community-based disease surveillance in Nigeria (1)

By Millicent Ele
11 February 2016   |   3:39 am
  DISEASE surveillance is primary and indispensable towards effective prevention and control of infectious diseases. It provides needed information for prompt detection of outbreaks and the initiation of response actions. An effective disease surveillance system must be able to produce valid, representative data in a timely manner; and these would be promptly analyzed for early…

 

Lassa fever

Lassa fever

DISEASE surveillance is primary and indispensable towards effective prevention and control of infectious diseases. It provides needed information for prompt detection of outbreaks and the initiation of response actions. An effective disease surveillance system must be able to produce valid, representative data in a timely manner; and these would be promptly analyzed for early detection of outbreaks.

The International Health Regulations (IHR 2005 or the Regulations) came into force on 15th June, 2007 and mandates all Member States to develop, strengthen, and maintain core capacity for disease surveillance and response at most by June 2016. With no specific provision for funding, it is a challenge for low-resourced African countries (including Nigeria) to meet this deadline. It is equally a global concern because infectious diseases know no boundaries and can spread to other nations and continents in a matter of hours and days. Therefore, developing an effective surveillance system for African countries is an imperative.

Traditional surveillance that relies on exact diagnosis and laboratory confirmation is usually very slow. This is because data collection and reporting take a long winding route from the time the patient gets to the hospital and the doctor orders the laboratory test to the time the test result comes back and is reported if reportable. This journey could take days or even weeks especially in Africa where the bulk of the population lives in rural areas with few hospitals and inefficient transportation systems. Time is usually of the essence in infectious disease detection and control and a day or two could mean a life time in controlling the spread of such diseases. Additionally, even where a laboratory test was ordered and the results come back indicating a reportable disease, the doctor may fail to log in the report either because he is not aware of any obligation to do so or because the infrastructure to enable such reporting is not in existence.

Syndromic surveillance is a surveillance technique that monitors and analyses routinely collected automated disease-indicator data for early signs of outbreak of diseases. These data sources may include for instance, pharmacy records of sales of medications, ambulance dispatch records, outpatient records, records of hospital emergency departments, requests for laboratory tests in public and private hospitals and health centers, etc., captured electronically, and capable of real-time analysis for early signs of disease outbreaks in a community.

Syndromic surveillance could also be done through the use of appropriate internet applications to mine the web, gather, and sort through disease indictor data and outbreak information in real-time, in order to detect possible outbreaks of disease before the actual identification of the pathogenic organism. Under this category are the use of initiatives like the Global Public Health Intelligence Network (GPHIN), HealthMap, and EpiSPIDER, etc. However, due to the diverse nature, sources, and huge volumes of information collected through these techniques, it is difficult to classify and analyze the data without the possibility of losing vital materials. Therefore, improved algorithm for data classification and analysis is needed.

Alternatively, a more targeted and well-structured form of data collection needs to be adopted so as to simplify, quicken and possibly standardize the analytical process. This could be achieved by the use of modern technologies like mobile phones and mobile devices equipped with appropriate applications (apps), and standard forms for gathering and reporting health events and outbreaks in a community. A good demonstration of such mobile phone app was the Open Data Kit (ODK) Collect application used for data collection and reporting for contact tracing in Nigeria during the Ebola outbreak response in 2014. So, rather than wait for laboratory confirmation of diseases before reporting them or collect desperate information via the web, members of the community will gather and supply outbreak information in a pre-determined format with their mobile phones and devices.

A new community-based syndromic surveillance system called the “Call-in system of syndromic surveillance” is built on the above idea. Under this system, data collection is outsourced to a distributed group in the community and the data collected are reported to a center, which could be a hospital, health center or a designated section of the ministry of health. These data are tallied and analyzed for early detection of outbreaks like Lassa fever Cholera, Zika virus etc. This system is event-based and as such is supported by the World Health Organization (WHO), and the International Health Regulations (2005).

The Regulations embraced a comprehensive syndrome oriented approach that would take care of both known and unknown infectious diseases. It defined ‘surveillance’ as the systematic ongoing collection, collation and analysis of data for public health purposes and the timely dissemination of public health information for assessment and public health response. This operational definition can be actualized where there is a system set up for continuous
collection and collation of data, and analysis of the same in real time; where the result of such data analysis is promptly disseminated to relevant agencies and institutions for rapid response and control actions.

However, today, there is extensive use of mobile phones and applications even in developing countries. There is equally a broad agreement in literature and practice that these mobile devices could be used to report incidents of disease outbreaks, collect health related data for surveillance purposes, and reach patients in remote locations in order to offer medical advice and diagnosis. This practice is becoming increasingly popular in Africa especially because of its advantage of taking healthcare services to the hard-to-reach areas and getting health related information from there, for surveillance and planning purposes. For instance, the government of Kenya has introduced and piloted a number of mobile devices for health services and disease surveillance.

Also, in Rwanda, in 2013, an electronic integrated disease surveillance and response (eIDSR) system was built and launched in all district hospitals and for well over a decade now and mostly in developed countries, logs and records of automated disease-indicators like records of hospital emergency departments, nurse advice lines, data from poison control centers, school/personnel absenteeism, ambulance dispatch records, pharmacy records of sales of medications, etc., have been used for syndromic surveillance.

For instance, an unusual or unseasonal spike in sale of certain medications at the pharmacy will be an indication of an outbreak of the disease the medication is meant to cure or control.

In 2003 following the severe acute respiratory syndrome (SARS) epidemic, it was discovered that two months before the outbreak, there was a spike in the sale of an anti-viral herbal medication used in treating flu-like symptoms in the Guangdong province of China from where SARS originated. If this pharmacy sale had been tracked for purposes of syndromic surveillance, perhaps, SARS would have been detected earlier and the epidemic prevented. In the same vein, spikes in school/personnel absenteeism, records of hospital emergency room on certain diseases, or an unusually large influx of calls on nurse advise lines on the same or similar symptom/syndrome have been used as outbreak indicators.

To be continued.

* Millicent Ele, An Environmental and Public Health Law Consultant, Lecturer, Faculty of Law, University of Nigeria, Enugu Campus. millicent.ele@unn.edu.ng, millicentele@gmail.com

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