Advances in using Internet searches to track dengue

Abstract

Dengue is a mosquito-borne disease that threatens over half of the world’s population. Despite being endemic to more than 100 countries, government-led efforts and tools for timely identification and tracking of new infections are still lacking in many affected areas. Multiple methodologies that leverage the use of Internet-based data sources have been proposed as a way to complement dengue surveillance efforts. Among these, dengue-related Google search trends have been shown to correlate with dengue activity. We extend a methodological framework, initially proposed and validated for flu surveillance, to produce near real-time estimates of dengue cases in five countries/states: Mexico, Brazil, Thailand, Singapore and Taiwan. Our result shows that our modeling framework can be used to improve the tracking of dengue activity in multiple locations around the world.

Improved real-time influenza surveillance using Internet search data in eight Latin American countries

“…ARGO displays improvement in 6 countries in terms of the efficiency metric, reaching significant error reductions in Brazil (155 to 104 or 33%), Mexico (243 to 184 or 24%), Peru (48 to 40 or 16%) and Chile (131 to 119 or 9%). ARGO consistently outperforms GFT on Pearson correlation during the time period when GFT was active in every country and improves upon AR in all countries except Bolivia and Uruguay over the whole study period, reaching significant [20,21], we chose the number of suspected influenza cases (as captured by the FluNet's NPS) as our gold standard for our prediction tasks. Our choice was based on the intuitive fact that flurelated Google search activity is higher when more people "suspect" they may be affected by flu like symptoms, regardless of the outcome of any lab test.…”

“…We extended ARGO, a methodology originally conceived and tested to track flu activity in the U.S. in multiple spatial scales, as a way to produce retrospective and strictly out-of-sample flu estimates individually for each country [20,22]. This methodology is based on a multivariable regularized linear model that is dynamically recalibrated every week as new flu activity information becomes available.…”

“…The discontinuation of GFT in 2015 led many to believe that Internet search trends were too noisy to track disease activity, a problem exacerbated in developing countries with limited Internet access. However, recent research has shown that robust and dynamically selfcorrecting machine learning methodologies can extract meaningful signals from real-time search activity to track Zika and Dengue activity in low to middle income countries around the world [11,20,21]. We apply lessons learned from these studies and successfully extend a state-of-the-art modeling approach for flu surveillance to eight Latin American countries.…”

Analytical sociology and computational social science

“…The real-time collection of online data is important because it allows for analyses of issues of high public relevance such as the early detection of outbreaks of contagious diseases based on web search queries and symptom posting on social media [61][62][63]. In an exemplary study on effective vaccination strategies, Mones et al [64] equipped Danish students with mobile phones to collect multidimensional network data from proximate and online interactions.…”

Improved state-level influenza activity nowcasting in the United States leveraging Internet-based data sources and network approaches via ARGONet

“…These systems 19 provide weekly reports of influenza statistics, aggregated over the national, regional (10 groups as defined by 20 the Health and Human Services), and starting in fall 2017, state level. Of particular interest, U.S. Outpatient 21 Influenza-like Illness Surveillance Network (ILINet) records the percentage of patients reporting to outpatient 22 clinics with symptoms of influenza-like illness (ILI), which is defined by fever over 100°F in addition to sore 23 throat or cough, over the total number of patient visits [4]. While these measurements are an established 24 indicator of historical ILI activity, they require around a week to collect from individual health-care providers 25 across the country, analyze, and report and are frequently revised.…”