Evaluating an incentive based syndromic case reporting model using local health volunteers for predicting and preventing chikungunya epidemics in North Kerala, India
DOI:
https://doi.org/10.18203/2394-6040.ijcmph20161373Keywords:
Syndromic case reporting, Evaluation, Local health volunteers, Chikungunya epidemicAbstract
Background: We attempted to explore the utility of incentive based syndromic surveillance for chikungunya, by identifying, training and utilizing female health volunteers and testing its adaptability in a low resource setting.
Methods:A prospective evaluation of the syndromic reporting model was done in five selected urban and two rural units of Kozhikode district in North Kerala. Since large gaps were identified in the district health system reports of CKG for 2009 epidemic, an incentive based reporting and intervention model was developed which functioned independently from the official reporting systems by training health volunteers. For comparison baseline fever levels were generated using 5 year district health system data, calculating Z-scores. Statistical forecasting using time series analysis was done in both rural areas for the year 2011. Official IDSP and health volunteer fever reports were compared to predicted fever counts for 2011.Timeliness and completeness of reporting units and completeness of case reporting was monitored by WHO inventory method.
Results: The current reporting model detected higher fever counts compared to the official data. For every 100 fever counts by the LHVs only 15 fever counts were reported by the official health system. Timeliness and completeness of reporting units exceeded 70% and completeness of case reporting 75%.
Conclusions:The present study reiterated the ability of syndromic surveillance in detecting and monitoring out breaks. Timeliness and completeness of reports goes to prove the effectiveness of incentive based reporting system at the regional level. Incentive based disease surveillance and reporting at grass root levels, is effective in detecting early outbreaks triggering a reactive community participation leading to prompt disease containment measures and is applicable in resource poor settings.
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References
Shah KV, Gibbs CJ Jr, Banerjee G. Virological investigation of the epidemic of haemorrhagic fever in Calcutta:isolation of three strains of chikungunya virus. Indian J Med Res. 1964;52:676-83.
Jadhav M, Namboodripad M, Carman RH, Carey DE, Myers RM. chikungunya disease in infants and children in Vellore: a report of clinical and haematological features of virologically proved cases. Indian J Med Res. 1965;53:764-76.
Dandawate CN, Thiruvengadam KV, Kalyanasundaram V, Rajagopal J, Rao TR. serological survey in Madras city with special reference to chikungunya. Indian J Med Res. 1965;53:707-14.
Thiruvengadam KV, Kalyanasundaram V, Rajgopal J. Clinical and pathological studies on chikungunya fever in Madras city. Indian J Med Res. 1965;53:729-44.
IDSP Data-Kozhikode district -2006-2009,Integrated surveillance disease programme.
WHO/SEAROCasedefinition. Available at www.searo.WHO.int / entity/ emerging_diseases / topics / Def_Chikungunya_Fever.pdf. Accessed on 26th October 2010.
Keusch GT, Pappaioanou M, Gonzalez MC, Scott KA, Tsai P. Sustaining Global Surveillance and Response to Emerging Zoonotic Diseases. Washington, DC: The National Academies Press; 2009.
World Health Organization 2004; Field guide for malaria epidemic assessment and reporting.
World Health Organization 2006; Communicable disease surveillance and response systems. Guide to monitoring and evaluating.
World Health Organization 2012; Assessing tuberculosis under-reporting through inventory studies.
Timothy J, Doyle M. Glynn K, Samuel L. Groseclose; completeness of notifiable infectious disease reporting in the United States: An analytical literature review. Am J Epidemiol. 2002;155(9):866-74.
Cooper DL, Verlander NQ, Smith GE, Charlett A, Gerard E, Willocks L, O'Brien S. Can syndromic surveillance data detect local outbreaks of communicable disease? A model using a historical cryptosporidiosis outbreak. Epimediol Infect. 2006;134(1):13-20.
Heffernan R, Moshtashari F, Das D, Karpati A, Kurldoff M, Weiss D. Syndromic surveillance in public health practice, New york city. Emerg Infect disease. 2004;10(5):858-64.
Bellika JG, Hasvold T, HartvigsenG. Propogation of programme control: a tool for distributed disease surveillance. Int J Med inform. 2007;76(4):313-29.
Josseran L, Fouillet A, Caillere N, Brun-Ney D, Ilef D, Brucker G, Medeiros H, Astagneau P. Assessment of a syndromic surveillance system based on morbidity data: results from the Oscour network during a heat wave. PLoS One. 2010;5(8):e 11984.
Caudle JM, Dijk VA, Rolland E, Moore KM. Tele health Ontario detection of gastrointestinal illness outbreaks. Can J Public Health. 2009;100(4):253-7.
Dan YY1, Tambyah PA, Sim J, Lim J, Hsu LY, Chow WL, Fisher DA, Wong YS, Ho KY. Cost effectiveness and analysis of hospital infection control response to an epidemic respiratory virus threat. Emerg Infect Dis. 2009;15(12):1909-16.
Browsers L, Cakici B, Carnitz M, Tegnell A, Boman M. Economic consequences to society of Pandemic H1N1 influenza 2009-preliminary results for sweden. Eurosurveill.2009;14(37):19333.
Srivastava DK, Venketesh S, Pandey S. Completeness and timeliness of reporting under IDSP in rural surveillance unit of Nainital district. Indian J.Prev.Soc.Med. 2009;40:138-42.
M’Ikanatha N, Southwell B, Lautenbach E. Automated Laboratory Reporting of Infectious Diseases in a Climate of Bioterrorism. Emerg Infect Dis. 2003;9(9):1053-7.
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