Risk of symptomatic dengue for foreign visitors to the 2014 FIFA World Cup in Brazil

Massad, Eduardo; Wilder-Smith, Annelies; Ximenes, Raphael; Amaku, Marcos; López, Luis Fernández; Coutinho, Francisco Antônio Bezerra; Coelho, Giovanini Evelim; Silva, Jarbas Barbosa da; Struchiner, Cláudio J.; Burattini, Marcelo Nascimento

doi:10.1590/0074-0276140133

Cited by 27 publications

(25 citation statements)

References 20 publications

(22 reference statements)

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“…For instance, this approach correctly identified 3 additional non-epidemics in 2017 compared to weather patterns alone, supporting the discourse on the unusually low dengue activity seen in Brazil in 2017 34 . Still, our models missed half (6/12) of non-epidemics in 2014, which was predicted by experts to be a low transmission year due to immunity provided by a large 2013 outbreak with no changes in circulating DENV serotypes 35,36 . Thus, incorporating information on specific circulating serotypes could be used to better detect changes in population immunity and enhance our approach.…”

Section: Discussionmentioning

confidence: 81%

Combining weather patterns and cycles of population susceptibility to forecast dengue fever epidemic years in Brazil: a dynamic, ensemble learning approach

et al. 2019

Preprint

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Transmission of dengue fever depends on a complex interplay of human, climate, and mosquito dynamics, which often change in time and space. It is well known that disease dynamics are highly influenced by a population's susceptibility to infection and microclimates, small-area climatic conditions which create environments favorable for the breeding and survival of the mosquito vector. Here, we present a novel machine learning dengue forecasting approach, which, dynamically in time and adaptively in space, identifies local patterns in weather and population susceptibility to make epidemic predictions at the city-level in Brazil, months ahead of the occurrence of disease outbreaks. Weather-based predictions are improved when information on population susceptibility is incorporated, indicating that immunity is an important predictor neglected by most dengue forecast models. Given the generalizability of our methodology, it may prove valuable for public-health decision making aimed at mitigating the effects of seasonal dengue outbreaks in locations globally.

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Section: Discussionmentioning

confidence: 81%

Combining weather patterns and cycles of population susceptibility to forecast dengue fever epidemic years in Brazil: a dynamic, ensemble learning approach

et al. 2019

Preprint

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“…A concrete legacy of hosting mass events for the country is already confirmed: the spread of epidemics and the impact of health problems such as the Chikungunya Virus and the Zika Virus epidemics are directly associated with those events [22] [23]. In 2013 Zika virus probably arrived in Brazil, during the Soccer Confederations Cup, although other international events held in Rio are also associated with it, especially the Va'a World Sprint Championship canoe race [24].…”

Section: Mega Events In Brazil: Epidemics As a Legacy?mentioning

confidence: 99%

Zika Virus Controversies: Epidemics as a Legacy of Mega Events?

Arbex¹,

Bizarro²,

Paletti³

et al. 2016

Health

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The current knowledge of the Zika Virus epidemic clearly lacks a comprehensive understanding of its determinants and clinical outcomes. Until recently regarded as a "simple" dengue-like infection, it nowadays turned into a real challenge to Public Health around the world. The Zika Epidemic shows a quick spread, affects unprepared health systems, and presents with severe neurological complications of newborns-a concrete threat to pregnancies. This re-emerging infectious disease is a source of deep doubts and harsh debates regarding Public Health and even bioethical issues. Several doubts still remain on how to deal with the various possible transmission ways of the disease, the surge of a generation of thousands of microcephalic newborns (and questions on how to handle them within limited health systems), and severe malformations concentrated so far in Northeastern Brazil. Finally, a debate is raised about how the "Endemic State" of Brazil, deeply merged in a health care crisis for almost 40 years now, currently confronts 3 current epidemics of the arboviruses Dengue, Chikungunya and now Zika, all associated with a lack of basic sanitation. Brazil must deal with these biological threats in the context of the Rio 2016 Olympic Games, since Chikungunya has probably been brought to Brazil during the FIFA Soccer World Cup (2014) and Zika Virus spread is associated with the Soccer Confederations Cup (2013).

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“…United States Department of Transport 14 [15,20,54,[62][63][64][65]84,97,100,112,115,133,148] Australian Department of Transport 2 [18,19] Australian International Airport Traffic 4 [15,[18][19][20] Brazilian Ministry of Tourism 1 [126] Department 18-20,48,87,90,94,97,114,119,127,143] among other criteria. An additional complication is that customers of the same data provider may receive different data depending on the timing, exact parameters of their database query and their subscription levels.…”

Section: Government-published Information (N = 33; 15%)mentioning

confidence: 99%

The use and reporting of airline passenger data for infectious disease modelling: a systematic review

et al. 2019

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Background A variety of airline passenger data sources are used for modelling the international spread of infectious diseases. Questions exist regarding the suitability and validity of these sources. Aim We conducted a systematic review to identify the sources of airline passenger data used for these purposes and to assess validation of the data and reproducibility of the methodology. Methods Articles matching our search criteria and describing a model of the international spread of human infectious disease, parameterised with airline passenger data, were identified. Information regarding type and source of airline passenger data used was collated and the studies’ reproducibility assessed. Results We identified 136 articles. The majority (n = 96) sourced data primarily used by the airline industry. Governmental data sources were used in 30 studies and data published by individual airports in four studies. Validation of passenger data was conducted in only seven studies. No study was found to be fully reproducible, although eight were partially reproducible. Limitations By limiting the articles to international spread, articles focussed on within-country transmission even if they used relevant data sources were excluded. Authors were not contacted to clarify their methods. Searches were limited to articles in PubMed, Web of Science and Scopus. Conclusion We recommend greater efforts to assess validity and biases of airline passenger data used for modelling studies, particularly when model outputs are to inform national and international public health policies. We also recommend improving reporting standards and more detailed studies on biases in commercial and open-access data to assess their reproducibility.

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Risk of symptomatic dengue for foreign visitors to the 2014 FIFA World Cup in Brazil

Cited by 27 publications

References 20 publications

Combining weather patterns and cycles of population susceptibility to forecast dengue fever epidemic years in Brazil: a dynamic, ensemble learning approach

Combining weather patterns and cycles of population susceptibility to forecast dengue fever epidemic years in Brazil: a dynamic, ensemble learning approach

Zika Virus Controversies: Epidemics as a Legacy of Mega Events?

The use and reporting of airline passenger data for infectious disease modelling: a systematic review

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