A framework for evaluating health system surveillance sensitivity to support public health decision-making for malaria elimination: a case study from Indonesia.

Riris Andono Ahmad; Luca Nelli ORCID logo; Henry Surendra; Risalia Reni Arisanti; Dyah Ayu Shinta Lesmanawati; Isabel Byrne ORCID logo; Elin Dumont; Chris Drakeley ORCID logo; Gillian Stresman ORCID logo; Lindsey Wu; (2022) A framework for evaluating health system surveillance sensitivity to support public health decision-making for malaria elimination: a case study from Indonesia. BMC infectious diseases, 22 (1). 619-. ISSN 1471-2334 DOI: 10.1186/s12879-022-07581-2
Copy

BACKGROUND: The effectiveness of a surveillance system to detect infections in the population is paramount when confirming elimination. Estimating the sensitivity of a surveillance system requires identifying key steps in the care-seeking cascade, from initial infection to confirmed diagnosis, and quantifying the probability of appropriate action at each stage. Using malaria as an example, a framework was developed to estimate the sensitivity of key components of the malaria surveillance cascade. METHODS: Parameters to quantify the sensitivity of the surveillance system were derived from monthly malaria case data over a period of 36 months and semi-quantitative surveys in 46 health facilities on Java Island, Indonesia. Parameters were informed by the collected empirical data and estimated by modelling the flow of an infected individual through the system using a Bayesian framework. A model-driven health system survey was designed to collect empirical data to inform parameter estimates in the surveillance cascade. RESULTS: Heterogeneity across health facilities was observed in the estimated probability of care-seeking (range = 0.01-0.21, mean ± sd = 0.09 ± 0.05) and testing for malaria (range = 0.00-1.00, mean ± sd = 0.16 ± 0.29). Care-seeking was higher at facilities regularly providing antimalarial drugs (Odds Ratio [OR] = 2.98, 95% Credible Intervals [CI]: 1.54-3.16). Predictably, the availability of functioning microscopy equipment was associated with increased odds of being tested for malaria (OR = 7.33, 95% CI = 20.61). CONCLUSIONS: The methods for estimating facility-level malaria surveillance sensitivity presented here can help provide a benchmark for what constitutes a strong system. The proposed approach also enables programs to identify components of the health system that can be improved to strengthen surveillance and support public-health decision-making.


picture_as_pdf
s12879-022-07581-2.pdf
subject
Published Version
Available under Creative Commons: 4.0

View Download

Atom BibTeX OpenURL ContextObject in Span Multiline CSV OpenURL ContextObject Dublin Core Dublin Core MPEG-21 DIDL EndNote HTML Citation JSON MARC (ASCII) MARC (ISO 2709) METS MODS RDF+N3 RDF+N-Triples RDF+XML RIOXX2 XML Reference Manager Refer Simple Metadata ASCII Citation EP3 XML
Export

Downloads