Dengue disease outbreak definitions are implicitly variable

Brady, Oliver J.; Smith, David L.; Scott, Thomas W.; Hay, Simon I.

doi:10.1016/j.epidem.2015.03.002

Cited by 85 publications

(75 citation statements)

References 42 publications

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“…Outbreaks varied widely across time and space in the MENA: reported cases varied from <10 to >100,000 over a span of months to years, reported from the village level to the level of the province and region. This presents a challenge to epidemiologic monitoring and policy planning for DENV, as use of different outbreak definitions results in differences in early detection and response [30]. There is currently no consensus on how to define DENV outbreaks, and adopting a common definition for the MENA is challenging given the region’s heterogeneous infection pressures, multiple DENV serotypes, and variable surveillance and detection capacity.…”

Section: Discussionmentioning

confidence: 99%

“…Guidelines and tools for calculating vector infection rates are available [141, 152]. Finally, attaining a meaningful definition of DENV outbreaks in the MENA countries will require a thorough assessment of baseline surveillance, control, and treatment capacities in endemic regions [30]. …”

Section: Discussionmentioning

confidence: 99%

“…albopictus occurrence in the MENA were also sought from the articles retrieved through the search databases as well as through ProMED-MENA and Google Scholar. Given that the characteristics and definitions of dengue outbreaks in the literature are implicitly variable and that there is currently no consensus on how to define such events [30], we broadly included any outbreak report if the author of the report defined the event as an outbreak. Multiple reports of the same outbreak were recorded only once.…”

Section: Methodsmentioning

confidence: 99%

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Dengue in the Middle East and North Africa: A Systematic Review

et al. 2016

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BackgroundDengue virus (DENV) infection is widespread and its disease burden has increased in past decades. However, little is known about the epidemiology of dengue in the Middle East and North Africa (MENA).Methodology / Principal FindingsFollowing Cochrane Collaboration guidelines and reporting our findings following PRISMA guidelines, we systematically reviewed available records across MENA describing dengue occurrence in humans (prevalence studies, incidence studies, and outbreak reports), occurrence of suitable vectors (Aedes aegypti and Aedes albopictus), and DENV vector infection rates. We identified 105 human prevalence measures in 13 of 24 MENA countries; 81 outbreaks reported from 9 countries from 1941–2015; and reports of Ae. aegypti and/or Ae. albopictus occurrence in 15 countries. The majority of seroprevalence studies were reported from the Red Sea region and Pakistan, with multiple studies indicating >20% DENV seroprevalence in general populations (median 25%, range 0–62%) in these subregions. Fifty percent of these studies were conducted prior to 1990. Multiple studies utilized assays susceptible to serologic cross-reactions and 5% of seroprevalence studies utilized viral neutralization testing. There was considerable heterogeneity in study design and outbreak reporting, as well as variability in subregional study coverage, study populations, and laboratory methods used for diagnosis.Conclusions / SignificanceDENV seroprevalence in the MENA is high among some populations in the Red Sea region and Pakistan, while recent outbreaks in these subregions suggest increasing incidence of DENV which may be driven by a variety of ecologic and social factors. However, there is insufficient study coverage to draw conclusions about Aedes or DENV presence in multiple MENA countries. These findings illustrate the epidemiology of DENV in the MENA while revealing priorities for DENV surveillance and Aedes control.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Dengue in the Middle East and North Africa: A Systematic Review

et al. 2016

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“…Existing outbreak definitions are composed of two components: (i) an endemic channel that aims to replicate historical trends of expected cases; and (ii) a set of criteria that determines what level of variation above this endemic frequency should be classified as an outbreak26. The methods used to define outbreak risk are closely linked to the targets of various disease surveillance methods and to the transmission characteristics of the specified diseases.…”

Section: Methodsmentioning

confidence: 99%

A new method for assessing the risk of infectious disease outbreak

Liao

Wang

et al. 2017

Sci Rep

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Over the past few years, emergent threats posed by infectious diseases and bioterrorism have become public health concerns that have increased the need for prompt disease outbreak warnings. In most of the existing disease surveillance systems, disease outbreak risk is assessed by the detection of disease outbreaks. However, this is a retrospective approach that impacts the timeliness of the warning. Some disease surveillance systems can predict the probabilities of infectious disease outbreaks in advance by determining the relationship between a disease outbreak and the risk factors. However, this process depends on the availability of risk factor data. In this article, we propose a Bayesian belief network (BBN) method to assess disease outbreak risks at different spatial scales based on cases or virus detection rates. Our experimental results show that this method is more accurate than traditional methods and can make uncertainty estimates, even when some data are unavailable.

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“…Brazil’s comprehensive dengue surveillance system covers over 200 million individuals12 , 13, thereby enabling a detailed assessment of this data resource.…”

Section: Introductionmentioning

confidence: 99%

Social Media as a Sentinel for Disease Surveillance: What Does Sociodemographic Status Have to Do with It?

et al. 2016

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Introduction: Data from social media have been shown to have utility in augmenting traditional approaches to public health surveillance. Quantifying the representativeness of these data is needed for making accurate public health inferences.Methods: We applied machine-learning methods to explore spatial and temporal dengue event reporting trends on Twitter relative to confirmed cases, and quantified associations with sociodemographic factors across three Brazilian states (São Paulo, Rio de Janeiro, and Minas Gerais) at the municipality level.Results: Education and income were positive predictors of dengue reporting on Twitter. In contrast, municipalities with a higher percentage of older adults, and males were less likely to report suspected dengue disease on Twitter. Overall, municipalities with dengue disease tweets had higher mean per capita income and lower proportion of individuals with no primary school education.Conclusions: These observations highlight the need to understand population representation across locations, age, and racial/ethnic backgrounds in studies using social media data for public health research. Additional data is needed to assess and compare data representativeness across regions in Brazil.

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Dengue disease outbreak definitions are implicitly variable

Cited by 85 publications

References 42 publications

Dengue in the Middle East and North Africa: A Systematic Review

Dengue in the Middle East and North Africa: A Systematic Review

A new method for assessing the risk of infectious disease outbreak

Social Media as a Sentinel for Disease Surveillance: What Does Sociodemographic Status Have to Do with It?

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