The risk of dengue for non-immune foreign visitors to the 2016 summer olympic games in Rio de Janeiro, Brazil

Complexity in the dengue spreading: A network analysis approach

In an increasingly interconnected society, preventing epidemics has become a major challenge. Numerous infectious diseases spread between individuals by a vector, creating bipartite networks of infection with the characteristics of complex networks. In the case of dengue, a mosquito-borne disease, these infection networks include a vector-the Aedes aegypti mosquito-which has expanded its endemic area due to climate change. In this scenario, innovative approaches are essential to help public agents in the fight against the disease. Using an agent-based model, we investigated the network morphology of a dengue endemic region considering four different serotypes and a small population. The degree, betweenness, and closeness distributions are evaluated for the bipartite networks, considering the interactions up to the second order for each serotype. We observed scale-free features and heavy tails in the degree distribution and betweenness and quantified the decay of the degree distribution with a q-Gaussian fit function. The simulation results indicate that the spread of dengue is primarily driven by human-to-human and human-to-mosquito interaction, reinforcing the importance of controlling the vector to prevent episodes of epidemic outbreaks.

Spatio-Temporal Cluster Detection of Dengue, Chikungunya, and Zika Viruses' Infection in Rio de Janeiro State from 2010 to 2019

Dengue (DENV), chikungunya (CHIKV), and Zika (ZIKV) virus infections are widespread throughout the Rio de Janeiro state. The co-circulation of these emergent arboviruses constitutes a serious public health problem, resulting in outbreaks that can spatially and temporally overlap. Environmental conditions favor the presence, maintenance, and expansion of Aedes aegypti, the primary vector of these urban arboviruses. This study assessed the detection of clusters of urban arboviruses in the Rio de Janeiro state from 2010 to 2019. Notified cases of dengue, chikungunya, and Zika were grouped by year according to the onset of symptoms and their municipality of residence. The study period recorded the highest number of dengue epidemics in the state along with the simultaneous circulation of chikungunya and Zika viruses. The analyzes showed that the central municipalities of the metropolitan regions were associated with higher risk areas. Central municipalities in metropolitan regions were the first most likely clusters for dengue and Zika, and the second most likely cluster for chikungunya. Furthermore, the northwest and north regions were comprised clusters with the highest relative risk for the three arboviruses, underscoring the impact of these arboviruses in less densely populated regions of Brazil. The identification of high-risk areas over time highlights the need for effective control measures, targeted prevention and control interventions for these urban arboviral diseases.

Data-driven methods for dengue prediction and surveillance using real-world and Big Data: A systematic review

Background

Traditionally, dengue surveillance is based on case reporting to a central health agency. However, the delay between a case and its notification can limit the system responsiveness. Machine learning methods have been developed to reduce the reporting delays and to predict outbreaks, based on non-traditional and non-clinical data sources. The aim of this systematic review was to identify studies that used real-world data, Big Data and/or machine learning methods to monitor and predict dengue-related outcomes.

Methodology/Principal findings

We performed a search in PubMed, Scopus, Web of Science and grey literature between January 1, 2000 and August 31, 2020. The review (ID: CRD42020172472) focused on data-driven studies. Reviews, randomized control trials and descriptive studies were not included. Among the 119 studies included, 67% were published between 2016 and 2020, and 39% used at least one novel data stream. The aim of the included studies was to predict a dengue-related outcome (55%), assess the validity of data sources for dengue surveillance (23%), or both (22%). Most studies (60%) used a machine learning approach. Studies on dengue prediction compared different prediction models, or identified significant predictors among several covariates in a model. The most significant predictors were rainfall (43%), temperature (41%), and humidity (25%). The two models with the highest performances were Neural Networks and Decision Trees (52%), followed by Support Vector Machine (17%). We cannot rule out a selection bias in our study because of our two main limitations: we did not include preprints and could not obtain the opinion of other international experts.

Conclusions/Significance

Combining real-world data and Big Data with machine learning methods is a promising approach to improve dengue prediction and monitoring. Future studies should focus on how to better integrate all available data sources and methods to improve the response and dengue management by stakeholders.

Dengue is one of the most important arbovirus infections in the world and its public health, societal and economic burden is increasing. Although the majority of dengue cases are asymptomatic or mild, severe disease forms can lead to death. For this reason, early diagnosis and monitoring of dengue are crucial to decrease mortality. However, most endemic regions still rely on traditional monitoring methods, despite the growing availability of novel data sources and data-driven methods based on real-world data, Big Data, and machine learning algorithms. In this systematic review, we identified and analyzed studies that used these novel approaches for dengue monitoring and/or prediction. We found that novel data streams, such as Internet search engines and social media platforms, and machine learning methods can be successfully used to improve dengue management, but are still vastly ignored in real life. These approaches should be combined with traditional methods to help stakeholders better prepare for each outbreak and improve early responsiveness.

Disentangling associations between vegetation greenness and dengue in a Latin American city: Findings and challenges

Being a Re-Emerging Infectious Disease, dengue causes 390 million cases globally and is prevalent in many urban areas in South America. Understanding the fine-scale relationships between dengue incidence and environmental and socioeconomic factors can guide improved disease prevention strategies. This ecological study examines the association between dengue incidence and satellite-based vegetation greenness in 3826 census tracts nested in 474 neighborhoods in Belo Horizonte, Brazil, during the 2010 dengue epidemic. To reduce potential bias in the estimated dengue-greenness association, we adjusted for socioeconomic vulnerability, population density, building height and density, land cover composition, elevation, weather patterns, and neighborhood random effects. We found that vegetation greenness was negatively associated with dengue incidence in a univariate model, and this association attenuated after controlling for additional covariates. The dengue-greenness association was modified by socioeconomic vulnerability: while a positive association was observed in the least vulnerable census tracts, the association was negative in the most vulnerable areas. Using greenness as a proxy for vegetation quality, our results show the potential of vegetation management in reducing dengue incidence, particularly in socioeconomically vulnerable areas. We also discuss the role of water infrastructure, sanitation services, and tree cover in lowering dengue risk.

Effects of a Health Promotion Intervention on Physical Activity in African American Men Living with HIV: Randomized Controlled Trial

HIV and its treatment with antiretroviral therapy increase the risk of noncommunicable diseases (NCDs) tied to physical inactivity. Older African American men are also at high risk for NCDs. We tested the efficacy of a theory-based intervention to increase adherence to federal aerobic and muscle-strengthening physical activity (PA) guidelines among African American men aged 40 years and older living with HIV. We randomized African American men aged 40 years and older living with HIV to a three-session social cognitive theory-informed health promotion intervention targeting PA or a one-session health awareness control condition. The primary outcome was PA guideline adherence assessed (self-reported) preintervention, immediate postintervention, and 3, 6, and 12 months postintervention. Secondary outcomes were the number of days on which participants reported moderate-intensity aerobic PA, vigorous-intensity aerobic PA, and muscle-strengthening PA in the past 7 days. Of 302 participants, 255 completed the 12-month postintervention measures. Generalized estimated equation logistic regression indicated that the health promotion intervention participants had higher odds of meeting PA guidelines than health awareness control participants, adjusting for baseline adherence (p = 0.011). Health promotion intervention participants also reported more muscle-strengthening PA (p = 0.001), vigorous-intensity aerobic PA (p = 0.049), and moderate-intensity aerobic PA (p = 0.010) than control participants. The rise in self-reported adherence to PA guidelines and improvements in muscle-strengthening and aerobic PA considered separately suggest that a relatively brief behavioral intervention can increase PA among African American men aged 40 years and older living with HIV and potentially curb their risk of NCDs that PA can prevent.

Public health emergencies of international concern: a historic overview

RATIONALE

The International Health Regulations (IHR) have been the governing framework for global health security since 2007. Declaring public health emergencies of international concern (PHEIC) is a cornerstone of the IHR. Here we review how PHEIC are formally declared, the diseases for which such declarations have been made from 2007 to 2020 and justifications for such declarations.

KEY FINDINGS

Six events were declared PHEIC between 2007 and 2020: the 2009 H1N1 influenza pandemic, Ebola (West African outbreak 2013-2015, outbreak in Democratic Republic of Congo 2018-2020), poliomyelitis (2014 to present), Zika (2016) and COVID-19 (2020 to present). Poliomyelitis is the longest PHEIC. Zika was the first PHEIC for an arboviral disease. For several other emerging diseases a PHEIC was not declared despite the fact that the public health impact of the event was considered serious and associated with potential for international spread.

RECOMMENDATIONS

The binary nature of a PHEIC declaration is often not helpful for events where a tiered or graded approach is needed. The strength of PHEIC declarations is the ability to rapidly mobilize international coordination, streamline funding and accelerate the advancement of the development of vaccines, therapeutics and diagnostics under emergency use authorization. The ultimate purpose of such declaration is to catalyse timely evidence-based action, to limit the public health and societal impacts of emerging and re-emerging disease risks while preventing unwarranted travel and trade restrictions.

A Prospective Study on the Impact and Out-of-Pocket Costs of Dengue Illness in International Travelers

Although the costs of dengue illness to patients and households have been extensively studied in endemic populations, international travelers have not been the focus of costing studies. As globalization and human travel activities intensify, travelers are increasingly at risk for emerging and reemerging infectious diseases, such as dengue. This exploratory study aims to investigate the impact and out-of-pocket costs of dengue illness among travelers. We conducted a prospective study in adult travelers with laboratory-confirmed dengue and recruited patients at travel medicine clinics in eight different countries from December 2013 to December 2015. Using a structured questionnaire, we collected information on patients and their health-care utilization and out-of-pocket expenditures, as well as income and other financial losses they incurred because of dengue illness. A total of 90 patients participated in the study, most of whom traveled for tourism (74%) and visited countries in Asia (82%). Although 22% reported hospitalization and 32% receiving ambulatory care while traveling, these percentages were higher at 39% and 71%, respectively, after returning home. The out-of-pocket direct and indirect costs of dengue illness were US$421 (SD 744) and US$571 (SD 1,913) per episode, respectively, averaging to a total out-of-pocket cost of US$992 (SD 2,052) per episode. The study findings suggest that international travelers incur important direct and indirect costs because of dengue-related illness. This study is the first to date to investigate the impact and out-of-pocket costs of travel-related dengue illness from the patient's perspective and paves the way for future economic burden studies in this population.

Risk Assessment of Dengue Autochthonous Infections in Tokyo during Summer, Especially in the Period of the 2020 Olympic Games

An outbreak of autochthonous dengue fever occurred in the summer of 2014 in Tokyo, Japan. Numerous participants and spectators from abroad are expected to visit Tokyo in the summer of 2020. This study aims to analyze the risk of autochthonous dengue infections in Tokyo in summer and also assess the additional risk in the Olympiad using a mathematical model. A stochastic transmission model was developed with the cooperation of seasonal factors that greatly influence the transmission cycle of dengue virus, and stochastic simulations were conducted for each scenario provided adequately. This study found that (i) the incidence of dengue autochthonous infections is predicted to occur in a small number of cases; (ii) the local climate greatly influences the scale of dengue autochthonous infections; (iii) the incidence reaches its peak in August and early September; and (iv) the possibility of progressing to dengue outbreak is rare. In the Olympiad to be held in the summer of 2020, an additional risk of dengue autochthonous infections will amount to double compared with that in other years.

Mass gatherings medicine: public health issues arising from mass gathering religious and sporting events

Mass gathering events are associated with major public health challenges. The 2014 Lancet Series on the new discipline of mass gatherings medicine was launched at the World Health Assembly of Ministers of Health in Geneva in May, 2014. The Series covered the planning and surveillance systems used to monitor public health risks, public health threats, and experiences of health-care providers from mass gathering events in 2012 and 2013. This follow-up Review focuses on the main public health issues arising from planned mass gathering events held between 2013 and 2018. We highlight public health and research data on transmission of infectious diseases and antibiotic-resistant bacteria, mass casualty incidents, and non-communicable diseases, including thermal disorders. In the events discussed in this Review, the combination of a large influx of people, many from countries with outbreak-prone infectious diseases, with a high degree of crowd interactions imposed substantial burdens on host countries' health systems. The detection and transmission of antibiotic-resistant bacteria in pilgrims attending the Kumbh Mela and the Hajj raise concern of possible globalisation from mass-gathering religious events. Priorities for further investments and opportunities for research into prevention, surveillance, and management of these public health issues are discussed.

The risk of urban yellow fever resurgence in Aedes-infested American cities

Aedes aegypti, historically known as yellow fever (YF) mosquito, transmits a great number of other viruses such as Dengue, West Nile, Chikungunya, Zika, Mayaro and perhaps Oropouche, among others. Well established in Africa and Asia, Aedes mosquitoes are now increasingly invading large parts of the American continent, and hence the risk of urban YF resurgence in the American cities should because of great concern to public health authorities. Although no new urban cycle of YF was reported in the Americas since the end of an Aedes eradication programme in the late 1950s, the high number of non-vaccinated individuals that visit endemic areas, that is, South American jungles where the sylvatic cycle of YF is transmitted by canopy mosquitoes, and return to Aedes-infested urban areas, increases the risk of resurgence of the urban cycle of YF. We present a method to estimate the risk of urban YF resurgence in dengue-endemic cities. This method consists in (1) to estimate the number of Aedes mosquitoes that explains a given dengue outbreak in a given region; (2) calculate the force of infection caused by the introduction of one infective individual per unit area in the endemic area under study; (3) using the above estimates, calculate the probability of at least one autochthonous YF case per unit area produced by one single viraemic traveller per unit area arriving from a YF endemic or epidemic sylvatic region at the city studied. We demonstrate that, provided the relative vector competence, here defined as the capacity to being infected and disseminate the virus, of Ae. aegypti is greater than 0.7 (with respect to dengue), one infected traveller can introduce urban YF in a dengue endemic area.

Dynamics of Zika virus outbreaks: an overview of mathematical modeling approaches

BACKGROUND

The Zika virus was first discovered in 1947. It was neglected until a major outbreak occurred on Yap Island, Micronesia, in 2007. Teratogenic effects resulting in microcephaly in newborn infants is the greatest public health threat. In 2016, the Zika virus epidemic was declared as a Public Health Emergency of International Concern (PHEIC). Consequently, mathematical models were constructed to explicitly elucidate related transmission dynamics.

SURVEY METHODOLOGY

In this review article, two steps of journal article searching were performed. First, we attempted to identify mathematical models previously applied to the study of vector-borne diseases using the search terms "dynamics," "mathematical model," "modeling," and "vector-borne" together with the names of vector-borne diseases including chikungunya, dengue, malaria, West Nile, and Zika. Then the identified types of model were further investigated. Second, we narrowed down our survey to focus on only Zika virus research. The terms we searched for were "compartmental," "spatial," "metapopulation," "network," "individual-based," "agent-based" AND "Zika." All relevant studies were included regardless of the year of publication. We have collected research articles that were published before August 2017 based on our search criteria. In this publication survey, we explored the Google Scholar and PubMed databases.

RESULTS

We found five basic model architectures previously applied to vector-borne virus studies, particularly in Zika virus simulations. These include compartmental, spatial, metapopulation, network, and individual-based models. We found that Zika models carried out for early epidemics were mostly fit into compartmental structures and were less complicated compared to the more recent ones. Simple models are still commonly used for the timely assessment of epidemics. Nevertheless, due to the availability of large-scale real-world data and computational power, recently there has been growing interest in more complex modeling frameworks.

DISCUSSION

Mathematical models are employed to explore and predict how an infectious disease spreads in the real world, evaluate the disease importation risk, and assess the effectiveness of intervention strategies. As the trends in modeling of infectious diseases have been shifting towards data-driven approaches, simple and complex models should be exploited differently. Simple models can be produced in a timely fashion to provide an estimation of the possible impacts. In contrast, complex models integrating real-world data require more time to develop but are far more realistic. The preparation of complicated modeling frameworks prior to the outbreaks is recommended, including the case of future Zika epidemic preparation.

Estimating the probability of dengue virus introduction and secondary autochthonous cases in Europe

Given the speed of air travel, diseases even with a short viremia such as dengue can be easily exported to dengue naïve areas within 24 hours. We set out to estimate the risk of dengue virus introductions via travelers into Europe and number of secondary autochthonous cases as a result of the introduction. We applied mathematical modeling to estimate the number of dengue-viremic air passengers from 16 dengue-endemic countries to 27 European countries, taking into account the incidence of dengue in the exporting countries, travel volume and the probability of being viremic at the time of travel. Our models estimate a range from zero to 167 air passengers who are dengue-viremic at the time of travel from dengue endemic countries to each of the 27 receiving countries in one year. Germany receives the highest number of imported dengue-viremic air passengers followed by France and the United Kingdom. Our findings estimate 10 autochthonous secondary asymptomatic and symptomatic dengue infections, caused by the expected 124 infected travelers who arrived in Italy in 2012. The risk of onward transmission in Europe is reassuringly low, except where Aedes aegypti is present.

Estimating the prevalence of infectious diseases from under-reported age-dependent compulsorily notification databases

Background

National or local laws, norms or regulations (sometimes and in some countries) require medical providers to report notifiable diseases to public health authorities. Reporting, however, is almost always incomplete. This is due to a variety of reasons, ranging from not recognizing the diseased to failures in the technical or administrative steps leading to the final official register in the disease notification system. The reported fraction varies from 9 to 99% and is strongly associated with the disease being reported.

Methods

In this paper we propose a method to approximately estimate the full prevalence (and any other variable or parameter related to transmission intensity) of infectious diseases. The model assumes incomplete notification of incidence and allows the estimation of the non-notified number of infections and it is illustrated by the case of hepatitis C in Brazil. The method has the advantage that it can be corrected iteratively by comparing its findings with empirical results.

Results

The application of the model for the case of hepatitis C in Brazil resulted in a prevalence of notified cases that varied between 163,902 and 169,382 cases; a prevalence of non-notified cases that varied between 1,433,638 and 1,446,771; and a total prevalence of infections that varied between 1,597,540 and 1,616,153 cases.

Conclusions

We conclude that the model proposed can be useful for estimation of the actual magnitude of endemic states of infectious diseases, particularly for those where the number of notified cases is only the tip of the iceberg. In addition, the method can be applied to other situations, such as the well-known underreported incidence of criminality (for example rape), among others.

Estimating the size of Aedes aegypti populations from dengue incidence data: Implications for the risk of yellow fever outbreaks

In this paper we present a model to estimate the density of aedes mosquitoes in a community affected by dengue. The method consists in fitting a continuous function to the incidence of dengue infections, from which the density of infected mosquitoes is derived straightforwardly. Further derivations allow the calculation of the latent and susceptible mosquitoes' densities, the sum of the three equals the total mosquitoes' density. The method is illustrated with the case of the risk of urban yellow fever resurgence in dengue infested areas but the same procedures apply for other aedes-transmitted infections like Zika and chikungunya viruses.

On the origin and timing of Zika virus introduction in Brazil

The timing and origin of Zika virus (ZIKV) introduction in Brazil has been the subject of controversy. Initially, it was assumed that the virus was introduced during the FIFA World Cup in June-July 2014. Then, it was speculated that ZIKV may have been introduced by athletes from French Polynesia (FP) who competed in a canoe race in Rio de Janeiro in August 2014. We attempted to apply mathematical models to determine the most likely time window of ZIKV introduction in Brazil. Given that the timing and origin of ZIKV introduction in Brazil may be a politically sensitive issue, its determination (or the provision of a plausible hypothesis) may help to prevent undeserved blame. We used a simple mathematical model to estimate the force of infection and the corresponding individual probability of being infected with ZIKV in FP. Taking into account the air travel volume from FP to Brazil between October 2013 and March 2014, we estimated the expected number of infected travellers arriving at Brazilian airports during that period. During the period between December 2013 and February 2014, 51 individuals travelled from FP airports to 11 Brazilian cities. Basing on the calculated force of ZIKV infection (the per capita rate of new infections per time unit) and risk of infection (probability of at least one new infection), we estimated that 18 (95% CI 12-22) individuals who arrived in seven of the evaluated cities were infected. When basic ZIKV reproduction numbers greater than one were assumed in the seven evaluated cities, ZIKV could have been introduced in any one of the cities. Based on the force of infection in FP, basic reproduction ZIKV number in selected Brazilian cities, and estimated travel volume, we concluded that ZIKV was most likely introduced and established in Brazil by infected travellers arriving from FP in the period between October 2013 and March 2014, which was prior to the two aforementioned sporting events.

Risk of Globalization of the Disease in Europe

Risk of dissemination of ZIKV disease is based on multiple factors, including environmental (climate, socioeconomically, deforestation or industrialization) and travel/traveller factors. Both the disease (viremic travellers) and vector movement to mosquito-free area contributes to the introduction and establishment of autochthonous ZIKV transmission. Mass gathering events can contribute to magnify transmission due to close crowd life in a confined area. Also, multitudinary events can promote the introduction of an infectious disease to a previously naïve area when returning home. Although mathematical models estimate a low risk for introduction of ZIKV in Europe, specific European regions (mainly Portuguese Island of Madeira) account with suitable and efficient vector and opportune climate conditions to harbour the disease. Clinicians should be aware to enable early detection of autochthonous ZIKV cases. International and local guidelines can help clinicians on how to handle suspicious cases, how to confirm the infection and how to report suspected and confirmed cases. In case of autochthonous ZIKV detection, public authorities should perform surveillance and provide adequate resources to sustain enhanced mosquito control.

Zika virus infection during the Olympic Games in Rio: A fear or an actual risk?

The recent outbreak of Zika virus infection in Brazil has aroused considerable media interest due to its association with neurological malformations in children born from mothers infected by the virus and to its association with Guillain-Barre syndrome in adults. This relationship has led to the World Health Organisation declaring the current epidemic as a "Public Health Emergency of International Concern". Controversy also emerged on the advisability of delaying or changing the location of the Olympic and Paralympic Games, which were held in August at various locations in Brazil. In this article, we review the available evidence on the risk of Zika and dengue virus infection in individuals who travel to endemic countries, especially for multitudinous events.

A comparative analysis of three different methods for the estimation of the basic reproduction number of dengue

The basic reproduction number, R₀, is defined as the expected number of secondary cases of a disease produced by a single infection in a completely susceptible population, and can be estimated in several ways. For example, from the stability analysis of a compartmental model; through the use of the matrix of next generation, or from the final size of an epidemic, etc. In this paper we applied the method for estimating R₀ of dengue fever from the initial growth phase of an outbreak, without assuming exponential growth of cases, a common assumption in many studies. We used three different methods of calculating R₀ to compare the techniques' details and to evaluate how these techniques estimate the value of R₀ of dengue using data from the city of Ribeirão Preto (SE of Brazil) in two outbreaks. The results of the three methods are numerically different but, when we compare them using a system of differential equations developed for modeling only the first generation time, we can observe that the methods differ little in the initial growth phase. We conclude that the methods predict that dengue will spread in the city studied and the analysis of the data shows that the estimated values of R₀ have an equal pattern overtime.

Zika is not a reason for missing the Olympic Games in Rio de Janeiro: response to the open letter of Dr Attaran and colleagues to Dr Margaret Chan, Director - General, WHO, on the Zika threat to the Olympic and Paralympic Games

Attaran and colleagues in an open letter to WHO expressed their concern about the upcoming Olympic and Paralympic Games in Rio de Janeiro and the threat posed by the Zika epidemic (Attaran 2016). We agree that Zika virus is of great public health concern and much remains to be known about this disease. Care should be taken to reduce the risk of infection, especially to pregnant women. However, we argue that this is not sufficient reason for changing the original plans for the Games, in particular because of the time of the year when they will take place. The present article outlines several scientific results related to Zika and mosquito-borne infectious diseases dynamics that we believe ratify the current position of WHO in not endorsing the postponing or relocation of the 2016 Olympic and Paralympic Games (WHO 2016).