Sentinel surveillance system for early outbreak detection in Madagascar

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Abstract

Background

Following the outbreak of chikungunya in the Indian Ocean, the Ministry of Health directed the necessary development of an early outbreak detection system. A disease surveillance team including the Institut Pasteur in Madagascar (IPM) was organized to establish a sentinel syndromic-based surveillance system. The system, which was set up in March 2007, transmits patient data on a daily basis from the various voluntary general practitioners throughout the six provinces of the country to the IPM. We describe the challenges and steps involved in developing a sentinel surveillance system and the well-timed information it provides for improving public health decision-making.

Methods

Surveillance was based on data collected from sentinel general practitioners (SGP). The SGPs report the sex, age, visit date and time, and symptoms of each new patient weekly, using forms addressed to the management team. However, the system is original in that SGPs also report data at least once a day, from Monday to Friday (number of fever cases, rapid test confirmed malaria, influenza, arboviral syndromes or diarrhoeal disease), by cellular telephone (encrypted message SMS). Information can also be validated by the management team, by mobile phone. This data transmission costs 120 ariary per day, less than US$1 per month.

Results

In 2008, the sentinel surveillance system included 13 health centers, and identified 5 outbreaks. Of the 218,849 visits to SGPs, 12.2% were related to fever syndromes. Of these 26,669 fever cases, 12.3% were related to Dengue-like fever, 11.1% to Influenza-like illness and 9.7% to malaria cases confirmed by a specific rapid diagnostic test.

Conclusion

The sentinel surveillance system represents the first nationwide real-time-like surveillance system ever established in Madagascar. Our findings should encourage other African countries to develop their own syndromic surveillance systems.

Prompt detection of an outbreak of infectious disease may lead to control measures that limit its impact and help prevent future outbreaks.

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Most cited references 9

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Can the ubiquitous power of mobile phones be used to improve health outcomes in developing countries?

Warren A. Kaplan (2006)

Background The ongoing policy debate about the value of communications technology in promoting development objectives is diverse. Some view computer/web/phone communications technology as insufficient to solve development problems while others view communications technology as assisting all sections of the population. This paper looks at evidence to support or refute the idea that fixed and mobile telephones is, or could be, an effective healthcare intervention in developing countries. Methods A Web-based and library database search was undertaken including the following databases: MEDLINE, CINAHL, (nursing & allied health), Evidence Based Medicine (EBM), POPLINE, BIOSIS, and Web of Science, AIDSearch (MEDLINE AIDS/HIV Subset, AIDSTRIALS & AIDSDRUGS) databases. Results Evidence can be found to both support and refute the proposition that fixed and mobile telephones is, or could be, an effective healthcare intervention in developing countries. It is difficult to generalize because of the different outcome measurements and the small number of controlled studies. There is almost no literature on using mobile telephones as a healthcare intervention for HIV, TB, malaria, and chronic conditions in developing countries. Clinical outcomes are rarely measured. Convincing evidence regarding the overall cost-effectiveness of mobile phone " telemedicine" is still limited and good-quality studies are rare. Evidence of the cost effectiveness of such interventions to improve adherence to medicines is also quite weak. Conclusion The developed world model of personal ownership of a phone may not be appropriate to the developing world in which shared mobile telephone use is important. Sharing may be a serious drawback to use of mobile telephones as a healthcare intervention in terms of stigma and privacy, but its magnitude is unknown. One advantage, however, of telephones with respect to adherence to medicine in chronic care models is its ability to create a multi-way interaction between patient and provider(s) and thus facilitate the dynamic nature of this relationship. Regulatory reforms required for proper operation of basic and value-added telecommunications services are a priority if mobile telecommunications are to be used for healthcare initiatives.

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Syndromic Surveillance and Bioterrorism-related Epidemics

James W. Buehler, Ruth L. Berkelman, David M. Hartley … (2003)

To facilitate rapid detection of a future bioterrorist attack, an increasing number of public health departments are investing in new surveillance systems that target the early manifestations of bioterrorism-related disease. Whether this approach is likely to detect an epidemic sooner than reporting by alert clinicians remains unknown. The detection of a bioterrorism-related epidemic will depend on population characteristics, availability and use of health services, the nature of an attack, epidemiologic features of individual diseases, surveillance methods, and the capacity of health departments to respond to alerts. Predicting how these factors will combine in a bioterrorism attack may be impossible. Nevertheless, understanding their likely effect on epidemic detection should help define the usefulness of syndromic surveillance and identify approaches to increasing the likelihood that clinicians recognize and report an epidemic.

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Time series modeling for syndromic surveillance

Ben Reis, Kenneth Mandl (2003)

Background Emergency department (ED) based syndromic surveillance systems identify abnormally high visit rates that may be an early signal of a bioterrorist attack. For example, an anthrax outbreak might first be detectable as an unusual increase in the number of patients reporting to the ED with respiratory symptoms. Reliably identifying these abnormal visit patterns requires a good understanding of the normal patterns of healthcare usage. Unfortunately, systematic methods for determining the expected number of (ED) visits on a particular day have not yet been well established. We present here a generalized methodology for developing models of expected ED visit rates. Methods Using time-series methods, we developed robust models of ED utilization for the purpose of defining expected visit rates. The models were based on nearly a decade of historical data at a major metropolitan academic, tertiary care pediatric emergency department. The historical data were fit using trimmed-mean seasonal models, and additional models were fit with autoregressive integrated moving average (ARIMA) residuals to account for recent trends in the data. The detection capabilities of the model were tested with simulated outbreaks. Results Models were built both for overall visits and for respiratory-related visits, classified according to the chief complaint recorded at the beginning of each visit. The mean absolute percentage error of the ARIMA models was 9.37% for overall visits and 27.54% for respiratory visits. A simple detection system based on the ARIMA model of overall visits was able to detect 7-day-long simulated outbreaks of 30 visits per day with 100% sensitivity and 97% specificity. Sensitivity decreased with outbreak size, dropping to 94% for outbreaks of 20 visits per day, and 57% for 10 visits per day, all while maintaining a 97% benchmark specificity. Conclusions Time series methods applied to historical ED utilization data are an important tool for syndromic surveillance. Accurate forecasting of emergency department total utilization as well as the rates of particular syndromes is possible. The multiple models in the system account for both long-term and recent trends, and an integrated alarms strategy combining these two perspectives may provide a more complete picture to public health authorities. The systematic methodology described here can be generalized to other healthcare settings to develop automated surveillance systems capable of detecting anomalies in disease patterns and healthcare utilization.

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Author and article information

Journal

Journal ID (nlm-ta): BMC Public Health

Title: BMC Public Health

Publisher: BioMed Central

ISSN (Electronic): 1471-2458

Publication date Collection: 2010

Publication date (Electronic): 21 January 2010

Volume: 10

Page: 31

Affiliations

[1 ]Unité d'Epidémiologie, Institut Pasteur de Madagascar, Antananarivo, République de Madagascar

[2 ]Service de la Lutte contre les Maladies Emergentes et Réémergentes, Direction des Urgences et de la Lutte contre les Maladies Transmissibles, Ministère de la Santé, du Planning Familial et de la Protection Sociale, Antananarivo, République de Madagascar

[3 ]Service de la Surveillance Epidémiologique, Direction des Urgences et de la Lutte contre les Maladies Transmissibles, Ministère de la Santé, du Planning Familial et de la Protection Sociale, Antananarivo, République de Madagascar

[4 ]Unité de Virologie, Institut Pasteur de Madagascar, Antananarivo, République de Madagascar

Article

Publisher ID: 1471-2458-10-31

DOI: 10.1186/1471-2458-10-31

PMC ID: 2823701

PubMed ID: 20092624

SO-VID: 39011e6f-3aae-4c9e-828f-deb486031335

License:

This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Sentinel surveillance system for early outbreak detection in Madagascar

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Coronaviruses, COVID-19 and SARS-CoV-2

Most cited references 9

Can the ubiquitous power of mobile phones be used to improve health outcomes in developing countries?

Syndromic Surveillance and Bioterrorism-related Epidemics

Time series modeling for syndromic surveillance

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