A global airport-based risk model for the spread of dengue infection via the air transport network

Potential applicability of the importation risk index for predicting the risk of rarely imported infectious diseases

BACKGROUND

There have been many prediction studies for imported infectious diseases, employing air-travel volume or the importation risk (IR) index, which is the product of travel-volume and disease burden in the source countries, as major predictors. However, there is a lack of studies validating the predictability of the variables especially for infectious diseases that have rarely been reported. In this study, we analyzed the prediction performance of the IR index and air-travel volume to predict disease importation.

METHODS

Rabies and African trypanosomiasis were used as target diseases. The list of rabies and African trypanosomiasis importation events, annual air-travel volume between two specific countries, and incidence of rabies and African trypanosomiasis in the source countries were obtained from various databases.

RESULTS

Logistic regression analysis showed that IR index was significantly associated with rabies importation risk (p value < 0.001), but the association with African trypanosomiasis was not significant (p value = 0.923). The univariable logistic regression models showed reasonable prediction performance for rabies (area under curve for Receiver operating characteristic [AUC] = 0.734) but poor performance for African trypanosomiasis (AUC = 0.641).

CONCLUSIONS

Our study found that the IR index cannot be generally applicable for predicting rare importation events. However, it showed the potential utility of the IR index by suggesting acceptable performance in rabies models. Further studies are recommended to explore the generalizability of the IR index's applicability and to propose disease-specific prediction models.

Trends in mosquito species distribution modeling: insights for vector surveillance and disease control

Species distribution modeling (SDM) has become an increasingly common approach to explore questions about ecology, geography, outbreak risk, and global change as they relate to infectious disease vectors. Here, we conducted a systematic review of the scientific literature, screening 563 abstracts and identifying 204 studies that used SDMs to produce distribution estimates for mosquito species. While the number of studies employing SDM methods has increased markedly over the past decade, the overwhelming majority used a single method (maximum entropy modeling; MaxEnt) and focused on human infectious disease vectors or their close relatives. The majority of regional models were developed for areas in Africa and Asia, while more localized modeling efforts were most common for North America and Europe. Findings from this study highlight gaps in taxonomic, geographic, and methodological foci of current SDM literature for mosquitoes that can guide future efforts to study the geography of mosquito-borne disease risk.

Mapping carbon emissions of China's domestic air passenger transport: From individual cities to intercity networks

As a significant carbon emission source with high growth potential, the air transport sector plays a crucial role in China's decarbonisation efforts. However, the spatial pattern and evolutionary dynamics of aviation carbon emissions in China have not been thoroughly studied. This study proposed a framework to reveal the spatial characteristics and influencing factors of aviation carbon emissions at the city level. Using data from 2019 to construct the aviation carbon emissions network of China (ACENC), the novelty of the study lies in the subdivision of carbon emissions of air passenger transport into cities and intercity lines in China, which helps to reveal the spatial characteristics of individual cities in the intercity network. Beijing, Shanghai, Shenzhen, Chengdu, and Guangzhou were the cities with the highest carbon emissions, and the routes between these cities caused a significant amount of carbon emissions. >80 % of the total carbon emissions can be attributed to two communities in the network, owing to their large size and strong connections. Correlation analysis indicates that a city's carbon emissions are significantly related to its demographic and economic attributes as well as its connection with other cities, while a city's carbon emission intensity may be influenced by its centrality in the whole network and the structure of the community to which it belongs. Overall, the presented results provide directions for stakeholders and policymakers to regulate carbon emissions from air transportation.

Airport Malaria in Non-Endemic Areas: New Insights into Mosquito Vectors, Case Management and Major Challenges

Despite the implementation of preventive measures in airports and aircrafts, the risk of importing Plasmodium spp. infected mosquitoes is still present in malaria-free countries. Evidence suggests that mosquitoes have found a new alliance with the globalization of trade and climate change, leading to an upsurge of malaria parasite transmission around airports. The resulting locally acquired form of malaria is called Airport malaria. However, piecemeal information is available, regarding its epidemiological and entomological patterns, as well as the challenges in the diagnosis, treatment, and prevention. Understanding these issues is a critical step towards a better implementation of control strategies. To cross reference this information, we conducted a systematic review on 135 research articles published between 1969 (when the first cases of malaria in airports were reported) and 2020 (i.e., 51 years later). It appears that the risk of malaria transmission by local mosquito vectors in so called malaria-free countries is not zero; this risk is more likely to be fostered by infected vectors coming from endemic countries by air or by sea. Furthermore, there is ample evidence that airport malaria is increasing in these countries. From 2010 to 2020, the number of cases in Europe was 7.4 times higher than that recorded during the 2000-2009 decade. This increase may be associated with climate change, increased international trade, the decline of aircraft disinsection, as well as delays in case diagnosis and treatment. More critically, current interventions are weakened by biological and operational challenges, such as drug resistance in malaria parasites and vector resistance to insecticides, and logistic constraints. Therefore, there is a need to strengthen malaria prevention and treatment for people at risk of airport malaria, and implement a rigorous routine entomological and epidemiological surveillance in and around airports.

Revisiting the Effects of High-Speed Railway Transfers in the Early COVID-19 Cross-Province Transmission in Mainland China

Coronavirus disease 2019 (COVID-19) is an ongoing pandemic that was reported at the end of 2019 in Wuhan, China, and was rapidly disseminated to all provinces in around one month. The study aims to assess the changes in intercity railway passenger transport on the early spatial transmission of COVID-19 in mainland China. Examining the role of railway transport properties in disease transmission could help quantify the spatial spillover effects of large-scale travel restriction interventions. This study used daily high-speed railway schedule data to compare the differences in city-level network properties (destination arrival and transfer service) before and after the Wuhan city lockdown in the early stages of the spatial transmission of COVID-19 in mainland China. Bayesian multivariate regression was used to examine the association between structural changes in the railway origin-destination network and the incidence of COVID-19 cases. Our results show that the provinces with rising transfer activities after the Wuhan city lockdown had more confirmed COVID-19 cases, but changes in destination arrival did not have significant effects. The regions with increasing transfer activities were located in provinces neighboring Hubei in the widthwise and longitudinal directions. These results indicate that transfer activities enhance interpersonal transmission probability and could be a crucial risk factor for increasing epidemic severity after the Wuhan city lockdown. The destinations of railway passengers might not be affected by the Wuhan city lockdown, but their itinerary routes could be changed due to the replacement of an important transfer hub (Wuhan city) in the Chinese railway transportation network. As a result, transfer services in the high-speed rail network could explain why the provinces surrounded by Hubei had a higher number of confirmed COVID-19 cases than other provinces.

Forecasting the probability of local dengue outbreaks in Queensland, Australia

The global incidence of dengue is increasing, and many previously unaffected areas have reported local cases of the vector-borne disease in recent years. For the effective containment of local outbreaks health authorities rely on the prompt notification of new cases. However, due to severe under-reporting and misdiagnosis, non-endemic countries face difficulties in containing local outbreaks, and the possibility of dengue becoming endemic. Outbreak control measures in non-endemic countries are largely reactive and health authorities would benefit from a universal early warning system that forecasts the probability of dengue outbreaks for given times and locations. We develop a model that establishes a link between pre- and post-border risk of dengue outbreaks. Specifically, we predict the probability of travellers importing dengue from other countries as well as the probability of those travellers causing local outbreaks. Our model can act as an early warning system, forecasting likely times and places of dengue outbreaks. We run our model for the Australian state of Queensland over a period of twelve years. Our results reveal the airports where dengue infected travellers are most likely to arrive and geographic locations associated with high outbreak probabilities. Our results can be used by health authorities to better utilise prevention and control resources and lead to the development of new prevention measures.

Dominant bee species and floral abundance drive parasite temporal dynamics in plant-pollinator communities

Pollinator reductions can leave communities less diverse and potentially at increased risk of infectious diseases. Species-rich plant and bee communities have high species turnover, making the study of disease dynamics challenging. To address how temporal dynamics shape parasite prevalence in plant and bee communities, we screened >5,000 bees and flowers over an entire growing season for five common bee microparasites (Nosema ceranae, Nosema bombi, Crithidia bombi, Crithidia expoeki and neogregarines). Over 110 bee species and 89 flower species were screened, revealing that 42% of bee species (12.2% individual bees) and 70% of flower species (8.7% individual flowers) had at least one parasite in or on them, respectively. Some common flowers (for example, Lychnis flos-cuculi) harboured multiple parasite species whilst others (for example, Lythrum salicaria) had few. Significant temporal variation of parasite prevalence in bees was linked to bee diversity, bee and flower abundance and community composition. Specifically, we found that bee communities had the highest prevalence late in the season, when social bees (Bombus spp. and Apis mellifera) were dominant and bee diversity was lowest. Conversely, prevalence on flowers was lowest late in the season when floral abundance was highest. Thus turnover in the bee community impacted community-wide prevalence, and turnover in the plant community impacted when parasite transmission was likely to occur at flowers. These results imply that efforts to improve bee health will benefit from the promotion of high floral numbers to reduce transmission risk, maintaining bee diversity to dilute parasites and monitoring the abundance of dominant competent hosts.

Modeling the relative role of human mobility, land-use and climate factors on dengue outbreak emergence in Sri Lanka

Background

More than 80,000 dengue cases including 215 deaths were reported nationally in less than 7 months between 2016 and 2017, a fourfold increase in the number of reported cases compared to the average number over 2010–2016. The region of Negombo, located in the Western province, experienced the greatest number of dengue cases in the country and is the focus area of our study, where we aim to capture the spatial-temporal dynamics of dengue transmission.

Methods

We present a statistical modeling framework to evaluate the spatial-temporal dynamics of the 2016–2017 dengue outbreak in the Negombo region of Sri Lanka as a function of human mobility, land-use, and climate patterns. The analysis was conducted at a 1 km × 1 km spatial resolution and a weekly temporal resolution.

Results

Our results indicate human mobility to be a stronger indicator for local outbreak clusters than land-use or climate variables. The minimum daily temperature was identified as the most influential climate variable on dengue cases in the region; while among the set of land-use patterns considered, urban areas were found to be most prone to dengue outbreak, followed by areas with stagnant water and then coastal areas. The results are shown to be robust across spatial resolutions.

Conclusions

Our study highlights the potential value of using travel data to target vector control within a region. In addition to illustrating the relative relationship between various potential risk factors for dengue outbreaks, the results of our study can be used to inform where and when new cases of dengue are likely to occur within a region, and thus help more effectively and innovatively, plan for disease surveillance and vector control.

Role of bridge nodes in epidemic spreading: Different regimes and crossovers

Power-law behaviors are common in many disciplines, especially in network science. Real-world networks, like disease spreading among people, are more likely to be interconnected communities, and show richer power-law behaviors than isolated networks. In this paper, we look at the system of two communities which are connected by bridge links between a fraction r of bridge nodes, and study the effect of bridge nodes to the final state of the Susceptible-Infected-Recovered model by mapping it to link percolation. By keeping a fixed average connectivity, but allowing different transmissibilities along internal and bridge links, we theoretically derive different power-law asymptotic behaviors of the total fraction of the recovered R in the final state as r goes to zero, for different combinations of internal and bridge link transmissibilities. We also find crossover points where R follows different power-law behaviors with r on both sides when the internal transmissibility is below but close to its critical value for different bridge link transmissibilities. All of these power-law behaviors can be explained through different mechanisms of how finite clusters in each community are connected into the giant component of the whole system, and enable us to pick effective epidemic strategies and to better predict their impacts.

Dengue importation into Europe: A network connectivity-based approach

The spread of dengue through global human mobility is a major public health concern. A key challenge is understanding the transmission pathways and mediating factors that characterized the patterns of dengue importation into non-endemic areas. Utilizing a network connectivity-based approach, we analyze the importation patterns of dengue fever into European countries. Seven connectivity indices were developed to characterize the role of the air passenger traffic, seasonality, incidence rate, geographical proximity, epidemic vulnerability, and wealth of a source country, in facilitating the transport and importation of dengue fever. We used generalized linear mixed models (GLMMs) to examine the relationship between dengue importation and the connectivity indices while accounting for the air transport network structure. We also incorporated network autocorrelation within a GLMM framework to investigate the propensity of a European country to receive an imported case, by virtue of its position within the air transport network. The connectivity indices and dynamical processes of the air transport network were strong predictors of dengue importation in Europe. With more than 70% of the variation in dengue importation patterns explained. We found that transportation potential was higher for source countries with seasonal dengue activity, high passenger traffic, high incidence rates, high epidemic vulnerability, and in geographical proximity to a destination country in Europe. We also found that position of a European country within the air transport network was a strong predictor of the country's propensity to receive an imported case. Our findings provide evidence that the importation patterns of dengue into Europe can be largely explained by appropriately characterizing the heterogeneities of the source, and topology of the air transport network. This contributes to the foundational framework for building integrated predictive models for bio-surveillance of dengue importation.

A scoping review of importation and predictive models related to vector-borne diseases, pathogens, reservoirs, or vectors (1999-2016)

BACKGROUND

As globalization and climate change progress, the expansion and introduction of vector-borne diseases (VBD) from endemic regions to non-endemic regions is expected to occur. Mathematical and statistical models can be useful in predicting when and where these changes in distribution may happen. Our objective was to conduct a scoping review to identify and characterize predictive and importation models related to vector-borne diseases that exist in the global literature.

METHODS

A literature search was conducted to identify publications published between 1999 and 2016 from five scientific databases using relevant keywords. All publications had to be in English or French, and include a predictive or importation model on VBDs, pathogens, reservoirs and/or vectors. Relevance screening and data characterization were performed by two reviewers using pretested forms. The data were analyzed using descriptive statistics.

RESULTS

The search initially identified 19 710 unique articles, reports, and conference abstracts. This was reduced to 428 relevant documents after relevance screening and data charting. About half of the models used mathematical techniques, and the remainder were statistical. Most of the models were predictive (87%), rather than importation (5%). The most commonly investigated diseases were malaria and dengue fever. Around 12% of the publications did not report all the parameters used in their model. Only 29% of the models incorporated the impacts of climate change.

CONCLUSIONS

A wide variety of mathematical and statistical models on vector-borne diseases exist. Researchers creating their own mathematical and/or statistical models may be able to use this scoping review to be informed about the diseases and/or regions, parameters, model types, and methodologies used in published models.

An economic investigation of the dengue incidence as a result of a tailings dam accident in Brazil

On November 2015, the Fundão Tailings Dam, located at Mariana municipality in Brazil, failed. Besides the deaths and injuries, economic losses, pollution and health problems associated to heavy metals in the water, Brazilian municipalities near the accident experienced an increase in the incidence of dengue. Since dengue fever is an insect-borne disease and the mosquito develops where there is stored water, there must be a relationship between the dam accident and the incidence of the disease. The purpose of this study is to test whether there is a causal relationship between the dam accident in Mariana and the number of dengue cases, number of hospitalizations due to dengue, and dengue outbreak in the municipalities affected by the accident. We find evidence that the accident had a positive and statistically significant impact on dengue indicators (for example, the probability of a dengue outbreak increased in 19%), what makes us call attention to another negative externality of tailings dam accidents.

Clinical and epidemiological characteristics of imported dengue fever among inbound passengers: Infrared thermometer-based active surveillance at an international airport

BACKGROUND

Dengue fever is endemic in tropical and subtropical areas, especially Southeast Asia. International air travel facilitates the spread of dengue across and within borders. To date, no predictive factors have been established for assessing risk of dengue among febrile travelers.

METHODS

Since 2006, Taiwan has operated a program of infrared thermometer-based non-contact active surveillance at Taoyuan International Airport (TPE). All inbound passengers from dengue-endemic countries who are febrile (tympanic temperature ≥38°C) undergo routine laboratory testing for dengue. We analyzed clinical and epidemiological characteristics of all tested passengers entering Taiwan via TPE in 2011 to identify the predictive factors of dengue infection.

RESULTS

In 2011, of the 3,719 febrile passengers from dengue-endemic countries, 74 (2.0%) had laboratory-confirmed dengue infection. Multivariable logistic regression analysis revealed that those who were aged ≥60 years (adjusted odds ratio [aOR], 8.7; 95% confidence interval [CI], 2.6-29.6) and had self-reported fever (aOR, 2.5; 95% CI, 1.5-4.1), skin rashes (aOR, 11.0; 95% CI, 3.4-35.1), or a tympanic temperature ≥39°C (aOR, 2.9; 95% CI, 1.7-4.9) were significantly more likely to have dengue (all p values < 0.05). Compared with travelers who stayed in dengue-endemic countries for ≤7 days, those who traveled 8-14, 15-21, 22-28, and ≥29 days were also more likely to be infected (aORs of 10.2, 14.9, 39.0 and 12.0, respectively).

CONCLUSION

These clinical and epidemiological features can facilitate timely recognition and diagnosis of imported dengue in febrile inbound passengers and therefore help prevent domestic transmission of dengue virus.

A global model for predicting the arrival of imported dengue infections

With approximately half of the world's population at risk of contracting dengue, this mosquito-borne disease is of global concern. International travellers significantly contribute to dengue's rapid and large-scale spread by importing the disease from endemic into non-endemic countries. To prevent future outbreaks and dengue from establishing in non-endemic countries, knowledge about the arrival time and location of infected travellers is crucial. We propose a network model that predicts the monthly number of dengue-infected air passengers arriving at any given airport. We consider international air travel volumes to construct weighted networks, representing passenger flows between airports. We further calculate the probability of passengers, who travel through the international air transport network, being infected with dengue. The probability of being infected depends on the destination, duration and timing of travel. Our findings shed light onto dengue importation routes and reveal country-specific reporting rates that have been until now largely unknown. This paper provides important new knowledge about the spreading dynamics of dengue that is highly beneficial for public health authorities to strategically allocate the often limited resources to more efficiently prevent the spread of dengue.

A dynamic neural network model for predicting risk of Zika in real time

BACKGROUND

In 2015, the Zika virus spread from Brazil throughout the Americas, posing an unprecedented challenge to the public health community. During the epidemic, international public health officials lacked reliable predictions of the outbreak's expected geographic scale and prevalence of cases, and were therefore unable to plan and allocate surveillance resources in a timely and effective manner.

METHODS

In this work, we present a dynamic neural network model to predict the geographic spread of outbreaks in real time. The modeling framework is flexible in three main dimensions (i) selection of the chosen risk indicator, i.e., case counts or incidence rate; (ii) risk classification scheme, which defines the high-risk group based on a relative or absolute threshold; and (iii) prediction forecast window (1 up to 12 weeks). The proposed model can be applied dynamically throughout the course of an outbreak to identify the regions expected to be at greatest risk in the future.

RESULTS

The model is applied to the recent Zika epidemic in the Americas at a weekly temporal resolution and country spatial resolution, using epidemiological data, passenger air travel volumes, and vector habitat suitability, socioeconomic, and population data for all affected countries and territories in the Americas. The model performance is quantitatively evaluated based on the predictive accuracy of the model. We show that the model can accurately predict the geographic expansion of Zika in the Americas with the overall average accuracy remaining above 85% even for prediction windows of up to 12 weeks.

CONCLUSIONS

Sensitivity analysis illustrated the model performance to be robust across a range of features. Critically, the model performed consistently well at various stages throughout the course of the outbreak, indicating its potential value at any time during an epidemic. The predictive capability was superior for shorter forecast windows and geographically isolated locations that are predominantly connected via air travel. The highly flexible nature of the proposed modeling framework enables policy makers to develop and plan vector control programs and case surveillance strategies which can be tailored to a range of objectives and resource constraints.

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

BackgroundA 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.AimWe 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.MethodsArticles 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.ResultsWe 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.LimitationsBy 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.ConclusionWe 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.

Potential for the Invasive Species Aedes Albopictus and Arboviral Transmission through the Chabahar Port in Iran

BACKGROUND

Dengue, chikungunya, and Zika viruses are emerging infectious disease threats wherever suitable vectors, hosts, and habitat are present. The aim of the present study was to use the bioagent transport and environmental modeling system (BioTEMS) to identify the potential for arbovirus-infected Aedes species to invade the Chabahar area in southeastern Iran.

METHODS

ArcGIS geospatial analysis software, Statistica software, and BioTEMS were used to analyze geographic information and conduct data analysis. BioTEMS utilizes up to several hundred abiotic and biotic factors to produce risk and vulnerability assessments for biological agents and infectious diseases. The output of BioTEMS was validated using published predictive models, and most importantly published collection data of Aedes species in Iran.

RESULTS

There appears to have been two separate invasion events by Ae. albopictus into the southern region of Iran, first preceding 2009 and then again in 2013. BioTEMS identified two probable areas of introduction during the 2009 time frame, either through one or both the Chabahar ports or the Iranshahr airport with subsequent spread through vehicular transport. BioTEMS identified the port as an introduction zone for ZIKAV with high-risk zones and identifies gap zones during the 2013 time frame. Recommended surveillance sites are provided.

CONCLUSION

The air and maritime ports of Iran serve international customers, and are therefore vulnerable to import and invasion of mosquito vectors and arboviruses. Based on comparisons with other published low-resolution models, BioTEMS provides information for medical and public health professionals conducting integrated mosquito management, preventive medicine, and epidemiological surveillance.

Spatiotemporal responses of dengue fever transmission to the road network in an urban area

Urbanization is one of the important factors leading to the spread of dengue fever. Recently, some studies found that the road network as an urbanization factor affects the distribution and spread of dengue epidemic, but the study of relationship between the distribution of dengue epidemic and road network is limited, especially in highly urbanized areas. This study explores the temporal and spatial spread characteristics of dengue fever in the distribution of road network by observing a dengue epidemic in the southern Chinese cities. Geographic information technology is used to extract the spatial location of cases and explore the temporal and spatial changes of dengue epidemic and its spatial relationship with road network. The results showed that there was a significant "severe" period in the temporal change of dengue epidemic situation, and the cases were mainly concentrated in the vicinity of narrow roads, the spread of the epidemic mainly along the high-density road network area. These results show that high-density road network is an important factor to the direction and scale of dengue epidemic. This information may be helpful to the development of related epidemic prevention and control strategies.

Inferring the risk factors behind the geographical spread and transmission of Zika in the Americas

BACKGROUND

An unprecedented Zika virus epidemic occurred in the Americas during 2015-2016. The size of the epidemic in conjunction with newly recognized health risks associated with the virus attracted significant attention across the research community. Our study complements several recent studies which have mapped epidemiological elements of Zika, by introducing a newly proposed methodology to simultaneously estimate the contribution of various risk factors for geographic spread resulting in local transmission and to compute the risk of spread (or re-introductions) between each pair of regions. The focus of our analysis is on the Americas, where the set of regions includes all countries, overseas territories, and the states of the US.

METHODOLOGY/PRINCIPAL FINDINGS

We present a novel application of the Generalized Inverse Infection Model (GIIM). The GIIM model uses real observations from the outbreak and seeks to estimate the risk factors driving transmission. The observations are derived from the dates of reported local transmission of Zika virus in each region, the network structure is defined by the passenger air travel movements between all pairs of regions, and the risk factors considered include regional socioeconomic factors, vector habitat suitability, travel volumes, and epidemiological data. The GIIM relies on a multi-agent based optimization method to estimate the parameters, and utilizes a data driven stochastic-dynamic epidemic model for evaluation. As expected, we found that mosquito abundance, incidence rate at the origin region, and human population density are risk factors for Zika virus transmission and spread. Surprisingly, air passenger volume was less impactful, and the most significant factor was (a negative relationship with) the regional gross domestic product (GDP) per capita.

CONCLUSIONS/SIGNIFICANCE

Our model generates country level exportation and importation risk profiles over the course of the epidemic and provides quantitative estimates for the likelihood of introduced Zika virus resulting in local transmission, between all origin-destination travel pairs in the Americas. Our findings indicate that local vector control, rather than travel restrictions, will be more effective at reducing the risks of Zika virus transmission and establishment. Moreover, the inverse relationship between Zika virus transmission and GDP suggests that Zika cases are more likely to occur in regions where people cannot afford to protect themselves from mosquitoes. The modeling framework is not specific for Zika virus, and could easily be employed for other vector-borne pathogens with sufficient epidemiological and entomological data.

Control of Mosquito-Borne Diseases in Northwestern Italy: Preparedness from One Season to the Next

INTRODUCTION

Mosquito-borne diseases (MBDs) are spreading worldwide due to globalization and climate change, representing a threat for both humans and animals. Of great concern are the infections caused by viruses belonging to the Flavivirus genus as West Nile virus (WNV) and Usutu virus (USUV) transmitted by Culex sp. or Dengue virus and Zika virus (ZIKV), transmitted by Aedes sp. This work describes the surveillance protocol enforced in Piedmont (Northwestern Italy) to control MBDs spread, focusing on the activities performed on mosquitoes during the 2015 vector season.

MATERIALS AND METHODS

From July to October, mosquitoes were fortnightly sampled in 50 selected sites according to risk factors with CDC dry ice-baited traps and BG-Sentinel traps baited with BG-Lure and dry ice. Adults were counted, identified to species level, pooled, and screened for flaviviruses using different reverse transcription-PCR protocols and sequencing. Finally, phylogenetic analysis was performed on a dataset including 2014 and 2015 WNV sequences and reference sequences retrieved from GenBank.

RESULTS AND DISCUSSION

A total of 17,000 mosquitoes, grouped in 730 pools, were tested. Five pools of Culex pipiens were positive for WNV Lineage 2 in Novara, Alessandria, Vercelli, and Torino Provinces. One pool of C. pipiens and one pool of Anopheles maculipennis s.l. were positive for USUV in Vercelli and Alessandria Provinces. In Vercelli Province one pool of C. pipiens resulted positive both for WNV and USUV. Control measures were quickly implemented. Phylogenetic analyses showed that the WNV Lin 2 sequences from Piedmont region cluster with those circulating in Northeastern Italy in the previous years. Given the positive trend in WNV activity compared to 2014 and the emergence caused by other flavivirus as ZIKV, the level of attention for the 2016 vector season may be increased and this surveillance protocol could represent an important tool for public health authorities.

Vector status of Aedes species determines geographical risk of autochthonous Zika virus establishment

Background

The 2015-16 Zika virus pandemic originating in Latin America led to predictions of a catastrophic global spread of the disease. Since the current outbreak began in Brazil in May 2015 local transmission of Zika has been reported in over 60 countries and territories, with over 750 thousand confirmed and suspected cases. As a result of its range expansion attention has focused on possible modes of transmission, of which the arthropod vector-based disease spread cycle involving Aedes species is believed to be the most important. Additional causes of concern are the emerging new links between Zika disease and Guillain-Barre Syndrome (GBS), and a once rare congenital disease, microcephaly.

Methodology/principal findings

Like dengue and chikungunya, the geographic establishment of Zika is thought to be limited by the occurrence of its principal vector mosquito species, Ae. aegypti and, possibly, Ae. albopictus. While Ae. albopictus populations are more widely established than those of Ae. aegypti, the relative competence of these species as a Zika vector is unknown. The analysis reported here presents a global risk model that considers the role of each vector species independently, and quantifies the potential spreading risk of Zika into new regions. Six scenarios are evaluated which vary in the weight assigned to Ae. albopictus as a possible spreading vector. The scenarios are bounded by the extreme assumptions that spread is driven by air travel and Ae. aegypti presence alone and spread driven equally by both species. For each scenario destination cities at highest risk of Zika outbreaks are prioritized, as are source cities in affected regions. Finally, intercontinental air travel routes that pose the highest risk for Zika spread are also ranked. The results are compared between scenarios.

Conclusions/significance

Results from the analysis reveal that if Ae. aegypti is the only competent Zika vector, then risk is geographically limited; in North America mainly to Florida and Texas. However, if Ae. albopictus proves to be a competent vector of Zika, which does not yet appear to be the case, then there is risk of local establishment in all American regions including Canada and Chile, much of Western Europe, Australia, New Zealand, as well as South and East Asia, with a substantial increase in risk to Asia due to the more recent local establishment of Zika in Singapore.

Between 1952, when the Zika virus was first found in humans, and 2007 Zika disease outbreaks were limited to small isolated epidemics in equatorial Africa and tropical Asia. However, the recent outbreak, which began in Brazil in May 2015, resulted over 750 thousand estimated cases and confirmed local transmission in more than 60 countries by October, 2016. Like dengue and chikungunya, Zika is spread by Aedes aegypti mosquitoes and possibly, other species including Aedes albopictus. Geographic spread of the virus occurs when infected travelers travel from affected regions to ones without an established local Zika disease cycle, but in which the known and potential vector species have established populations. We estimate the risk of Zika importation and establishment into new regions using air travel data and ecological vector habitat suitability models for Ae. aegypti and Ae. albopictus. Given the uncertainties surrounding the vectorial competence of Aedes mosquitoes, we compare the geographic risk profiles when spread is driven by air travel and Ae. aegypti presence alone, with spread driven by air travel and both species. We conclude that there is a much higher global risk of Zika spread under the latter scenario, although it is the least likely.

Assessing likely invasion sites of Zika virus-infected mosquitoes in civilian and naval maritime ports in Florida

Several mosquito species are capable of invading new geographic regions and exploiting niches that are similar to their natural home ranges where they may introduce, or reintroduce, pathogens. In addition to initial invasion, introduction of new genotypes into established populations may also occur. Zika virus is spreading throughout the world, posing significant health risks to human populations, particularly pregnant women and their infants. The first locally acquired case of Zika virus in the US occurred in July 2016 in Miami, Florida on the Atlantic coast; the first locally acquired case in another US county occurred in the Tampa, Florida area. Three port cities in Florida were chosen to assess the risk of import and spread of Zika virus: Mayport Naval Station, Miami, and Tampa. The bioagent transport and enviromental modeling system TIGER model and ArcGIS were used to analyze abiotic and biotic factors influencing potentially Zika-infected Aedes species, should they enter through these ports. The model was tested by overlaying documented and suspected concurrent Zika cases and comparing published high-risk areas for Zika virus. In addition to Zika hot zones being identified, output indicates surveillance and integrated mosquito management should expect larger zones. Surveillance sites at ports should be identified and prioritized for pathogen and vector control to reduce the import of mosquitoes infected with Zika virus. Low resolution maps often provide valuable suitability of the geographic expansion of organisms. Providing a higher resolution predictive map, identifying probable routes of invasion, and providing areas at high risk for initial invasion and control zones, will aid in controlling and perhaps eliminating the spread of arboviruses through mosquito vectors.

A spatial model of socioeconomic and environmental determinants of dengue fever in Cali, Colombia

Dengue fever has gradually re-emerged across the global South, particularly affecting urban areas of the tropics and sub-tropics. The dynamics of dengue fever transmission are sensitive to changes in environmental conditions, as well as local demographic and socioeconomic factors. In 2010, the municipality of Cali, Colombia, experienced one of its worst outbreaks, however the outbreak was not spatially homogeneous across the city. In this paper, we evaluate the role of socioeconomic and environmental factors associated with this outbreak at the neighborhood level, using a Geographically Weighted Regression model. Key socioeconomic factors include population density and socioeconomic stratum, whereas environmental factors are proximity to both tire shops and plant nurseries and the presence of a sewage system (R²=0.64). The strength of the association between these factors and the incidence of dengue fever is spatially heterogeneous at the neighborhood level. The findings provide evidence to support public health strategies in allocating resources locally, which will enable a better detection of high risk areas, a reduction of the risk of infection and to strengthen the resilience of the population.

Risk of MERS importation and onward transmission: a systematic review and analysis of cases reported to WHO

BACKGROUND

The continuing circulation of MERS in the Middle East makes the international dissemination of the disease a permanent threat. To inform risk assessment, we investigated the spatiotemporal pattern of MERS global dissemination and looked for factors explaining the heterogeneity observed in transmission events following importation.

METHODS

We reviewed imported MERS cases worldwide up to July 2015. We modelled importations in time based on air travel combined with incidence in Middle East. We used the detailed history of MERS case management after importation (time to hospitalization and isolation, number of hospitals visited,…) in logistic regression to identify risk factors for secondary transmission. We assessed changes in time to hospitalization and isolation in relation to collective and public health attention to the epidemic, measured by three indicators (Google Trends, ProMED-mail, Disease Outbreak News).

RESULTS

Modelled importation events were found to reproduce both the temporal and geographical structure of those observed - the Pearson correlation coefficient between predicted and observed monthly time series was large (r = 0.78, p < 10(-4)). The risk of secondary transmission following importation increased with the time to case isolation or death (OR = 1.7 p = 0.04) and more precisely with the duration of hospitalization (OR = 1.7, p = 0.02). The average daily number of secondary cases was 0.02 [0.0,0.12] in the community and 0.20 [0.03,9.0] in the hospital. Time from hospitalisation to isolation decreased in periods of high public health attention (2.33 ± 0.34 vs. 6.44 ± 0.97 days during baseline attention).

CONCLUSIONS

Countries at risk of importation should focus their resources on strict infection control measures for the management of potential cases in healthcare settings and on prompt MERS cases identification. Individual and collective awareness are key to substantially improve such preparedness.

Infectious Risks of Air Travel

Infectious diseases are still among the leading causes of death worldwide due to their persistence, emergence, and reemergence. As the recent Ebola virus disease and MERS-CoV outbreaks demonstrate, the modern epidemics and large-scale infectious outbreaks emerge and spread quickly. Air transportation is a major vehicle for the rapid spread and dissemination of communicable diseases, and there have been a number of reported outbreaks of serious airborne diseases aboard commercial flights including tuberculosis, severe acute respiratory syndrome, influenza, smallpox, and measles, to name a few. In 2014 alone, over 3.3 billion passengers (a number equivalent to 42% of the world population) and 50 million metric tons of cargo traveled by air from 41,000 airports and 50,000 routes worldwide, and significant growth is anticipated, with passenger numbers expected to reach 5.9 billion by 2030. Given the increasing numbers of travelers, the risk of infectious disease transmission during air travel is a significant concern, and this chapter focuses on the current knowledge about transmission of infectious diseases in the context of both transmissions within the aircraft passenger cabin and commercial aircraft serving as vehicles of worldwide infection spread.

Prospects for dengue vaccines for travelers

Travel-acquired dengue cases have been increasing as the overall global dengue burden has expanded. In Korea, imported dengue cases have been reported since 2000 when it first became a notifiable disease. During the first four months of 2016, three times more dengue cases were reported in Korea than during the same period the previous year. A safe and efficacious vaccine for travelers would be beneficial to prevent dengue disease in individual travelers and potentially decrease the risk of virus spread to non-endemic areas. Here, we summarize the characteristics of dengue vaccines for travelers and review dengue vaccines currently licensed or in clinical development.

Surveillance of Mosquitoes and Selected Arthropod-Borne Viruses in the Context of Milan EXPO 2015

From 1 May 2015 to 31 October 2015 over 20 million visitors from all over the world visited the Universal Exhibition (EXPO) hosted by Milan (Lombardy region, Italy), raising concerns about the possible introduction of mosquito-borne diseases from endemic countries. The entomological surveillance protocol performed in Lombardy over the last three years was implemented in the EXPO area and in the two major regional airports using both Center for Disease Control CO₂ and Biogents Sentinel traps. This surveillance aimed to estimate the presence and densities of putative vectors, and also to support investigations, including the vector species involved and area of diffusion, on the local spread of Chikungunya, Dengue and West Nile viruses (WNV) by competent vectors. From 3544 mosquitoes belonging to five different species, 28 pools of Culex spp. and 45 pools of Aedes spp. were screened for the presence of WNV, and for both Chikungunya and flaviviruses, respectively. The entomological surveillance highlighted a low density of potential vectors in the surveyed areas and did not reveal the presence of Chikungunya or Dengue viruses in the local competent vectors inside the EXPO area or in the two airports. In addition, the surveillance reported a low density of Culex spp. mosquitoes, which all tested negative for WNV.

Risk of global spread of Middle East respiratory syndrome coronavirus (MERS-CoV) via the air transport network

BACKGROUND

Middle East respiratory syndrome coronavirus (MERS-CoV) emerged from the Kingdom of Saudi Arabia (KSA) in 2012 and has since spread to 26 countries. All cases reported so far have either been in the Middle East or linked to the region through passenger air travel, with the largest outbreak outside KSA occurring in South Korea. Further international spread is likely due to the high travel volumes of global travel, as well as the occurrence of large annual mass gathering such as the Haj and Umrah pilgrimages that take place in the region.

METHODS

In this study, a transport network modelling framework was used to quantify the risk of MERS-CoV spreading internationally via air travellers. All regions connected to MERS-CoV affected countries via air travel are considered, and the countries at highest risk of travel-related importations of MERS-CoV were identified, ranked and compared with actual spread of MERS cases.

RESULTS

The model identifies all countries that have previously reported a travel acquired case to be in the top 50 at-risk countries. India, Pakistan and Bangladesh are the highest risk countries which have yet to report a case, and should be prepared for the possibility of (pilgrims and general) travellers returning infected with MERS-CoV. In addition, the UK, Egypt, Turkey and the USA are at risk of more cases.

CONCLUSIONS

We have demonstrated a risk-analysis approach, using travel patterns, to prioritize countries at highest risk for MERS-CoV importations. In order to prevent global outbreaks such as the one seen in South Korea, it is critical for high-risk countries to be prepared and have appropriate screening and triage protocols in place to identify travel-related cases of MERS-CoV. The results from the model can be used by countries to prioritize their airport and hospital screening and triage protocols.

Dengue and chikungunya: modelling the expansion of mosquito-borne viruses into naïve populations

With the recent global spread of a number of mosquito-borne viruses, there is an urgent need to understand the factors that contribute to the ability of viruses to expand into naïve populations. Using dengue and chikungunya viruses as case studies, we detail the necessary components of the expansion process: presence of the mosquito vector; introduction of the virus; and suitable conditions for local transmission. For each component we review the existing modelling approaches that have been used to understand recent emergence events or to assess the risk of future expansions. We identify gaps in our knowledge that are related to each of the distinct aspects of the human-mosquito transmission cycle: mosquito ecology; human-mosquito contact; mosquito-virus interactions; and human-virus interactions. Bridging these gaps poses challenges to both modellers and empiricists, but only through further integration of models and data will we improve our ability to better understand, and ultimately control, several infectious diseases that exert a significant burden on human health.

Estimating air travel-associated importations of dengue virus into Italy

BACKGROUND

Southern Europe is increasingly at risk for dengue emergence, given the seasonal presence of relevant mosquito vectors and suitable climatic conditions. For example, Aedes mosquitoes, the main vector for both dengue and chikungunya, are abundant in Italy, and Italy experienced the first ever outbreak of chikungunya in Europe in 2007. We set out to estimate the extent of dengue virus importations into Italy via air travelers.

METHODS

We attempted to quantify the number of dengue virus importations based on modeling of published estimates on dengue incidence in the countries of disembarkation and analysis of data on comprehensive air travel from these countries into Italy's largest international airport in Rome.

RESULTS

From 2005 to 2012, more than 7.3 million air passengers departing from 100 dengue-endemic countries arrived in Rome. Our Importation Model, which included air traveler volume, estimated the incidence of dengue infections in the countries of disembarkation, and the probability of infection coinciding with travel accounted for an average of 2,320 (1,621-3,255) imported dengue virus infections per year, of which 572 (381-858) were "apparent" dengue infections and 1,747 (1,240-2,397) "inapparent."

CONCLUSIONS

Between 2005 and 2012, we found an increasing trend of dengue virus infections imported into Rome via air travel, which may pose a potential threat for future emergence of dengue in Italy, given that the reoccurring pattern of peak importations corresponds seasonally with periods of relevant mosquito vector activity. The observed increasing annual trends of dengue importation and the consistent peaks in late summer underpin the urgency in determining the threshold levels for the vector and infected human populations that could facilitate novel autochthonous transmission of dengue in Europe.

International dispersal of dengue through air travel: importation risk for Europe

Background

The worldwide distribution of dengue is expanding, in part due to globalized traffic and trade. Aedes albopictus is a competent vector for dengue viruses (DENV) and is now established in numerous regions of Europe. Viremic travellers arriving in Europe from dengue-affected areas of the world can become catalysts of local outbreaks in Europe. Local dengue transmission in Europe is extremely rare, and the last outbreak occurred in 1927–28 in Greece. However, autochthonous transmission was reported from France in September 2010, and from Croatia between August and October 2010.

Methodology

We compiled data on areas affected by dengue in 2010 from web resources and surveillance reports, and collected national dengue importation data. We developed a hierarchical regression model to quantify the relationship between the number of reported dengue cases imported into Europe and the volume of airline travellers arriving from dengue-affected areas internationally.

Principal Findings

In 2010, over 5.8 million airline travellers entered Europe from dengue-affected areas worldwide, of which 703,396 arrived at 36 airports situated in areas where Ae. albopictus has been recorded. The adjusted incidence rate ratio for imported dengue into European countries was 1.09 (95% CI: 1.01–1.17) for every increase of 10,000 travellers; in August, September, and October the rate ratios were 1.70 (95%CI: 1.23–2.35), 1.46 (95%CI: 1.02–2.10), and 1.35 (95%CI: 1.01–1.81), respectively. Two Italian cities where the vector is present received over 50% of all travellers from dengue-affected areas, yet with the continuing vector expansion more cities will be implicated in the future. In fact, 38% more travellers arrived in 2013 into those parts of Europe where Ae. albopictus has recently been introduced, compared to 2010.

Conclusions

The highest risk of dengue importation in 2010 was restricted to three months and can be ranked according to arriving traveller volume from dengue-affected areas into cities where the vector is present. The presence of the vector is a necessary, but not sufficient, prerequisite for DENV onward transmission, which depends on a number of additional factors. However, our empirical model can provide spatio-temporal elements to public health interventions.

The global disease burden of dengue is staggering. Continuous expansion and vaccine failures illustrate the limitations of current dengue control efforts. Novel approaches and additional tools are required to combat and contain the disease. In Europe, dengue infections are rare and the last outbreak of dengue occurred in the late 1920s, in Greece. In 2010, however, local transmission occurred in France and Croatia. Based on 2010 data, we present a novel quantitative model of the risk of dengue importation for Europe. The 2010 model predicts the risk of dengue importation to be greatest for Milan, Rome and Barcelona in August, September and October, precisely when vector activity is the highest. With the current expansion of the vector in Europe, more cities are projected to be at risk in the future. Thus, the model based on 2010 data quantifies the likelihood and timing of importation. This approach employs global travel data to assess dengue importation risk in the EU and illustrates how quantitative models could tailor infectious disease control to certain regions and time periods.