An algorithm applied to national surveillance data for the early detection of major dengue outbreaks in Cambodia

Abstract

Dengue is a national priority disease in Cambodia. The Cambodian National Dengue Surveillance System is based on passive surveillance of dengue-like inpatients reported by public hospitals and on a sentinel, pediatric hospital-based active surveillance system. This system works well to assess trends but the sensitivity of the early warning and time-lag to usefully inform hospitals can be improved. During The ECOnomic development, ECOsystem MOdifications, and emerging infectious diseases Risk Evaluation (ECOMORE) project’s knowledge translation platforms, Cambodian hospital staff requested an early warning tool to prepare for major outbreaks. Our objective was therefore to find adapted tools to improve the early warning system and preparedness. Dengue data was provided by the National Dengue Control Program (NDCP) and are routinely obtained through passive surveillance. The data were analyzed at the provincial level for eight Cambodian provinces during 2008–2015. The R surveillance package was used for the analysis. We evaluated the effectiveness of Bayesian algorithms to detect outbreaks using count data series, comparing the current count to an expected distribution obtained from observations of past years. The analyses bore on 78,759 patients with dengue-like syndromes. The algorithm maximizing sensitivity and specificity for the detection of major dengue outbreaks was selected in each province. The overall sensitivity and specificity were 73% and 97%, respectively, for the detection of significant outbreaks during 2008–2015. Depending on the province, sensitivity and specificity ranged from 50% to 100% and 75% to 100%, respectively. The final algorithm meets clinicians’ and decisionmakers’ needs, is cost-free and is easy to implement at the provincial level.

Early warning systems (EWSs) for chikungunya, dengue, malaria, yellow fever, and Zika outbreaks: What is the evidence? A scoping review

“…Of the 28 studies addressing EWS for dengue outbreaks, only 4 studies presented the user perspective on implementing EWS within national programs [ 12 , 21 , 26 , 27 ], and 24 studies showed EWS under development (i.e., model exercise); see Table 1 . Only 2 dengue studies used a prospective study design [ 28 , 29 ], and one applied both prospective and retrospective approaches [ 30 ]; the other 23 were retrospective analyses of surveillance data (1 of those specified as cohort study [ 21 ], 1 with a cross-sectional design [ 31 ], and 1 as a time series analysis [ 30 ]), and 2 studies were exclusively relying on mathematical simulation models [ 32 , 33 ]. The 2 Zika studies reported on exercises of testing EWS [ 24 , 25 ].…”

“…All 28 dengue studies relied on IBS, of which 24 studies were alarm informed, i.e., of outbreak predictive nature—using at least 1 meteorological, entomological or epidemiological indicator—and 4 studies [ 28 , 31 , 32 , 35 ] were case-informed EWS, i.e., of early outbreak detection—relying solely on previous trends of cases for outbreaks. Almost all studies demanded routine access to data as well as advanced statistical and analytical skills, but 5 studies [ 12 , 21 , 26 , 28 , 31 ] reported prediction tools that are adapted for less skilled users. The outbreak indicators used were hospitalized cases (2 studies) [ 12 , 21 ], laboratory-confirmed cases (23 studies), or suspected cases (3 studies) [ 12 , 28 , 31 ].…”

“…Almost all studies demanded routine access to data as well as advanced statistical and analytical skills, but 5 studies [ 12 , 21 , 26 , 28 , 31 ] reported prediction tools that are adapted for less skilled users. The outbreak indicators used were hospitalized cases (2 studies) [ 12 , 21 ], laboratory-confirmed cases (23 studies), or suspected cases (3 studies) [ 12 , 28 , 31 ]. One study [ 30 ] used mathematically simulated cases.…”

“…Three studies [ 22 , 41 , 42 ] referred to the lack of climate information and biased, inaccessible, or poor resolution data. Other limitations addressed the methodological approach with 3 studies [ 26 , 31 , 35 ] declaring method-related issues such as that methods (like LASSO) are not amenable to direct interpretation, requiring advanced statistical skills, or have a limited prediction robustness.…”

Evaluating the Potential of Pyriproxyfen Dissemination using Mosquito Home System against Aedes albopictus at a Dengue Hotspot Area

“…It is estimated that more than 3.9 billion people from 129 countries are at risk of contracting dengue fever, with one million deaths reported each year (Bhatt et al 2011;WHO 2020). The World Health Organization (WHO 2020) reported that the Asian region represents 70% of the global burden of dengue with several countries having become endemic including Cambodia (Ladien et al 2019), Indonesia (Maula et al 2018), Thailand (Srichan et al 2018), Singapore (Ong et al 2018), and Malaysia (Suppiah et al 2018).…”