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Fighting Lassa fever through community-based disease surveillance in Nigeria (2)


Participants at the meeting of stakeholders on the analysis of data from the Research Study on Anti Retro Viral (ARV) Drug Resistance Strains, on Monday February 8, 2016. The meeting was organized by the Nigerian Institute of Medical Research (NIMR) Yaba, Lagos.

Participants at the meeting of stakeholders on the analysis of data from the Research Study on Anti Retro Viral (ARV) Drug Resistance Strains, on Monday February 8, 2016. The meeting was organized by the Nigerian Institute of Medical Research (NIMR) Yaba, Lagos.

Unfortunately, in developing countries like Nigeria, most of these data sources are either not available, or not usually in electronic forms. They are commonly kept manually in notebooks with attendant laxity and inconsistencies due to human error. Besides, such manual information can neither be transmitted automatically nor aggregated in real-time for outbreak detection. This is a handicap for most developing countries, which may want to join the trend in using automated data sources for syndromic surveillance.

This system is used to report potential outbreaks of diseases like Cholera, Ebola, Lassa fever, etc., as well as help health workers contain the spread of diseases. With this eIDSR, the users can collect timely information from the field via the web and mobile phones and electronically transmit them to all health facilities at the same time. This has reportedly helped to improve timeliness, accuracy and completeness of reporting, and helped officials detect outbreaks rapidly, investigate them and mount a quick response within the country.

Also, some African countries have used select members of the community for delivering basic health services. For instance, in Rwanda, community health workers (CHWs) are simply select members of the community assigned to designated geographic area for basic health services delivery. There is also the “Nyateros of Gambia” (Friends of the eye) who because of the prevalence of eye disease, Trachoma (or Ocular Chlamydia trachomatis infection), are employed to deliver basic eye care services in their community.

In the Call-in system of syndromic surveillance, select members of the community are trained for surveillance purposes and early detection of infectious diseases. Implementation of this in Nigeria could lead to early detection, prompt reporting, as well as early investigation, and rapid response to outbreaks like Lassa fever.

During the 2014 Ebola outbreak in West Africa (mostly in Liberia, Sierra Leone, Guinea and Nigeria), a text message was sent on 17th August 2014, by the Federal Ministry of Health, Nigeria, through MTN to all subscribers, asking them to help prevent the spread of Ebola by reporting any suspected case. The message gave the phone number and the government email address to which these messages would be sent. Though such reporting is clearly unscientific, one must agree that when many of such reports flow in from a particular area or village, the Ministry is bound to investigate further to determine whether an outbreak is actually occurring.

The Call-in system of syndromic surveillance presents a more structured arrangement in the sense that each select member of the public is assigned specific geographic area in their community to cover and will be instructed to collect and send outbreak information to a designated health centre or hospital. They would be taught what to look for and a standardized way of reporting it. The advantages of engaging the community in this way is that they would help to quickly point out where outbreak is likely occurring for prompt investigation and urgent laboratory confirmations. It is therefore a good supplement to traditional surveillance for early detection of outbreaks; faster control and containment of infectious diseases.

Like all syndromic surveillance, the Call-in system is intended to alert public health officials of possible outbreaks leading to further investigation. Generally, if incoming reports show an increase/unseasonal spike in a particular syndromic group; a manifestation of an unknown syndrome/disease; or an event that is either hazardous to health or could create a potential for disease; then a response is triggered. This response, depending on the kind of disease or event could vary from mere preliminary investigation, to emergency control measures if the disease is highly infectious.

Under the Call-in system, preliminary investigation starts with call-backs to participants, health centers/hospitals from where the reports were originally submitted. This is a way to also cross-validate the information and ensure that it is not a fluke. Depending on the outcome of this preliminary investigation (example, if the suspicion of outbreak is sustained), detailed reporting including location of the victims/source population, age, gender, occupation, date and time of the onset of symptom, and its severity etc., may be required so that the sick could easily be tracked for control and treatment protocols.

Some of the challenges to this system include: Poor understanding of how to operate the apps; difficulties in actual disease detection through a syndromic approach and understanding case definitions; also training the participants may not always produce the assurance that they will know how to use the disease surveillance applications or correctly recognize reportable disease syndromes; there may be problems of how to appropriately fashion incentives to participants in order to improve the willingness to participate and sustain enthusiasm in reporting; analysis of the data may pose a problem at the implementation level due to a dearth of equipment for instant analysis, qualified manpower and enabling environment like steady power supply and other ancillary and supporting technology.

The challenges anticipated to arise in the operation of the Call-in system much like any other smart phone-based system of data collection and analysis could be cured with intensive training and retraining of the participants. This systematic training will improve the quality and accuracy of the system with respect to outbreak detection and reporting. To improve the willingness to participate and sustain enthusiasm in reporting, some incentives in form of bonus airtime minutes, free medical screening and some monetary stipends should be given to the participants. However, full-time CHWs have to be paid. In Rwanda, performance- based financing (PBF) is used for this purpose, and may be adopted by Nigeria with necessary modifications. Availability of funding both for equipment purchase and maintenance, training of the workforce and payment of remuneration, etc., is a big issue. This may be improved by intense advocacy in support of the system so that the government would increase funds allocation for healthcare and disease surveillance. Appeal for funds should also be made to international organizations, and corporations.

In conclusion, syndromic surveillance for infectious diseases outbreak alert and response must be taken serious if we must remain a step ahead of any pandemic. Nigeria should invest in the training of CHWs and health professionals to act as health vigilant eyes and ears for reportable diseases/syndromes and health events in their communities. Also, Nigeria needs sustained capacity building in health personnel and services in order to make healthcare accessible to the vast majority of the people, and supply the workforce for surveillance activities.

The Call-in system’s community-sourcing paradigm will help to energize community participation, improve public vigilance and situational awareness leading to early detection of outbreaks like Lassa fever in the community. It will also be an effective way for Nigeria and other low-resourced African countries to meet the IHR’s deadline for the development and maintenance of core surveillance systems. The adoption of this system or at least a variant of it is therefore, recommended for Nigeria.


* Millicent Ele, An Environmental and Public Health Law Consultant, Lecturer, Faculty of Law, University of Nigeria, Enugu Campus.,

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