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Enhancing disease surveillance with novel data streams: challenges and opportunities.

ABSTRACT: Novel data streams (NDS), such as web search data or social media updates, hold promise for enhancing the capabilities of public health surveillance. In this paper, we outline a conceptual framework for integrating NDS into current public health surveillance. Our approach focuses on two key questions: What are the opportunities for using NDS and what are the minimal tests of validity and utility that must be applied when using NDS? Identifying these opportunities will necessitate the involvement of public health authorities and an appreciation of the diversity of objectives and scales across agencies at different levels (local, state, national, international). We present the case that clearly articulating surveillance objectives and systematically evaluating NDS and comparing the performance of NDS to existing surveillance data and alternative NDS data is critical and has not sufficiently been addressed in many applications of NDS currently in the literature.

SUBMITTER: Althouse BM

PROVIDER: S-EPMC5156315 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Enhancing disease surveillance with novel data streams: challenges and opportunities.

Althouse Benjamin M BM Scarpino Samuel V SV Meyers Lauren Ancel LA Ayers John W JW Bargsten Marisa M Baumbach Joan J Brownstein John S JS Castro Lauren L Clapham Hannah H Cummings Derek At DA Del Valle Sara S Eubank Stephen S Fairchild Geoffrey G Finelli Lyn L Generous Nicholas N George Dylan D Harper David R DR Hébert-Dufresne Laurent L Johansson Michael A MA Konty Kevin K Lipsitch Marc M Milinovich Gabriel G Miller Joseph D JD Nsoesie Elaine O EO Olson Donald R DR Paul Michael M Polgreen Philip M PM Priedhorsky Reid R Read Jonathan M JM Rodríguez-Barraquer Isabel I Smith Derek J DJ Stefansen Christian C Swerdlow David L DL Thompson Deborah D Vespignani Alessandro A Wesolowski Amy A

EPJ data science 20151016

Novel data streams (NDS), such as web search data or social media updates, hold promise for enhancing the capabilities of public health surveillance. In this paper, we outline a conceptual framework for integrating NDS into current public health surveillance. Our approach focuses on two key questions: What are the opportunities for using NDS and what are the minimal tests of validity and utility that must be applied when using NDS? Identifying these opportunities will necessitate the involvement ...[more]

PMID: 27990325

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Project description:BackgroundDiabetic kidney disease (DKD) is the most common cause of the end-stage renal disease (ESRD). Regardless of intensive treatments with hyperglycemic control, blood pressure control, and the use of renin-angiotensin system blockades, the prevalence of DKD remains high. Recent studies suggest that the spectrum of DKD has been changed and many progresses have been made to develop new treatments for DKD. Therefore, it is time to perform a systemic review on the new developments in the field of DKD.SummaryAlthough the classic clinical presentation of DKD is characterized by a slow progression from microalbuminuria to macroalbuminuria and by a hyperfiltration at the early stage and progressive decline of renal function at the late stage, recent epidemiological studies suggest that DKD patients have a variety of clinical presentations and progression rates to ESRD. Some DKD patients have a decline in renal function without albuminuria but display prominent vascular and interstitial fibrosis on renal histology. DKD patients are more susceptible to acute kidney injury, which might contribute to the interstitial fibrosis. A large portion of type 2 diabetic patients with albuminuria could have overlapping nondiabetic glomerular disease, and therefore, kidney biopsy is required for differential diagnosis for these patients. Only a small portion of DKD patients eventually progress to end-stage renal failure. However, we do not have sensitive and specific biomarkers to identify these high-risk patients. Genetic factors that have a strong association with DKD progression have not been identified yet. A combination of circulating tumor necrosis factor receptor (TNFR)1, TNFR2, and kidney injury molecular 1 provides predictive value for DKD progression. Artificial intelligence could enhance the predictive values for DKD progression by combining the clinical parameters and biological markers. Sodium-glucose co-transporter-2 inhibitors should be added to the new standard care of DKD patients. Several promising new drugs are in clinical trials.Key messagesOver last years, our understanding of DKD has been much improved and new treatments to halt the progression of DKD are coming. However, better diagnostic tools, predictive markers, and treatment options are still urgently needed to help us to better manage these patients with this detrimental disease.

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Enhancing disease surveillance with novel data streams: challenges and opportunities.

Publications

Enhancing disease surveillance with novel data streams: challenges and opportunities.

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