Air travel and vector-borne disease movement

Controlling arbovirus infection: high-throughput transcriptome and proteome insights

Arboviruses pose a significant threat to public health globally, demanding innovative approaches for their control. For this, a better understanding of the complex web of interactions established in arbovirus-infected mosquitoes is fundamental. High-throughput analyses allow a genome-wide view of arbovirus-induced alterations at different gene expression levels. This review provides a comprehensive perspective into the current literature in transcriptome and proteome landscapes in mosquitoes infected with arboviruses. It also proposes a coordinated research effort to define the critical nodes that determine arbovirus infection and transmission.

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.

Arthropod vectors of disease agents: their role in public and veterinary health in Turkiye and their control measures

Mosquitoes, sandflies, and ticks are hematophagous arthropods that pose a huge threat to public and veterinary health. They are capable of serving as vectors of disease agents that can and have caused explosive epidemics affecting millions of people and animals. Several factors like climate change, urbanization, and international travel contribute substantially to the persistence and dispersal of these vectors from their established areas to newly invaded areas. Once established in their new home, they can serve as vectors for disease transmission or increase the risk of disease emergence. Turkiye is vulnerable to climate change and has experienced upward trends in annual temperatures and rising sea levels, and greater fluctuations in precipitation rates. It is a potential hotspot for important vector species because the climate in various regions is conducive for several insect and acari species and serves as a conduit for refugees and immigrants fleeing areas troubled with armed conflicts and natural disasters, which have increased substantially in recent years. These people may serve as carriers of the vectors or be infected by disease agents that require arthropod vectors for transmission. Although it cannot be supposed that every arthropod species is a competent vector, this review aims to (1)illustrate the factors that contribute to the persistence and dispersal of arthropod vectors, (2)determine the status of the established arthropod vector species in Turkiye and their capability of serving as vectors of disease agents, and (3)assess the role of newly-introduced arthropod vectors into Turkiye and how they were introduced into the country. We also provide information on important disease incidence (if there's any) and control measures applied by public health officials from different provinces.

Impact of urban structure on infectious disease spreading

The ongoing SARS-CoV-2 pandemic has been holding the world hostage for several years now. Mobility is key to viral spreading and its restriction is the main non-pharmaceutical interventions to fight the virus expansion. Previous works have shown a connection between the structural organization of cities and the movement patterns of their residents. This puts urban centers in the focus of epidemic surveillance and interventions. Here we show that the organization of urban flows has a tremendous impact on disease spreading and on the amenability of different mitigation strategies. By studying anonymous and aggregated intra-urban flows in a variety of cities in the United States and other countries, and a combination of empirical analysis and analytical methods, we demonstrate that the response of cities to epidemic spreading can be roughly classified in two major types according to the overall organization of those flows. Hierarchical cities, where flows are concentrated primarily between mobility hotspots, are particularly vulnerable to the rapid spread of epidemics. Nevertheless, mobility restrictions in such types of cities are very effective in mitigating the spread of a virus. Conversely, in sprawled cities which present many centers of activity, the spread of an epidemic is much slower, but the response to mobility restrictions is much weaker and less effective. Investing resources on early monitoring and prompt ad-hoc interventions in more vulnerable cities may prove helpful in containing and reducing the impact of future pandemics.

Infectious disease in an era of global change

The twenty-first century has witnessed a wave of severe infectious disease outbreaks, not least the COVID-19 pandemic, which has had a devastating impact on lives and livelihoods around the globe. The 2003 severe acute respiratory syndrome coronavirus outbreak, the 2009 swine flu pandemic, the 2012 Middle East respiratory syndrome coronavirus outbreak, the 2013-2016 Ebola virus disease epidemic in West Africa and the 2015 Zika virus disease epidemic all resulted in substantial morbidity and mortality while spreading across borders to infect people in multiple countries. At the same time, the past few decades have ushered in an unprecedented era of technological, demographic and climatic change: airline flights have doubled since 2000, since 2007 more people live in urban areas than rural areas, population numbers continue to climb and climate change presents an escalating threat to society. In this Review, we consider the extent to which these recent global changes have increased the risk of infectious disease outbreaks, even as improved sanitation and access to health care have resulted in considerable progress worldwide.

Challenges in evaluating risks and policy options around endemic establishment or elimination of novel pathogens

When a novel pathogen emerges there may be opportunities to eliminate transmission - locally or globally - whilst case numbers are low. However, the effort required to push a disease to elimination may come at a vast cost at a time when uncertainty is high. Models currently inform policy discussions on this question, but there are a number of open challenges, particularly given unknown aspects of the pathogen biology, the effectiveness and feasibility of interventions, and the intersecting political, economic, sociological and behavioural complexities for a novel pathogen. In this overview, we detail how models might identify directions for better leveraging or expanding the scope of data available on the pathogen trajectory, for bounding the theoretical context of emergence relative to prospects for elimination, and for framing the larger economic, behavioural and social context that will influence policy decisions and the pathogen’s outcome.

A multiplex PCR assay for six Aedini species, including Aedes albopictus

Background

Mosquitoes, as vectors of various human pathogens, are significant drivers of serious human illness. In particular, those species in the Aedini tribe, which typically transmit dengue virus, Chikungunya fever virus, and Zika virus, are increasing their range because of climate change and international commerce. In order to evaluate the risk of disease transmission, accurate mosquito species identification and monitoring are needed. The goal of this work was to develop a rapid and simple molecular diagnostic method for six morphologically similar Aedini species (Aedes flavopictus, Aedes albopictus, Ochlerotatus koreicus, Ochlerotatus japonicus, Ochlerotatus togoi and Ochlerotatus hatorii) in Korea.

Methods

A total of 109 samples were assayed in this study. The internal transcribed spacer 2 (ITS2) regions from all six species were amplified, sequenced and analyzed using Mega 6. Following the identification of regions that were consistently different in terms of sequence between all six species, multiplex primers were designed to amplify these regions to generate species-specific fragments distinguishable by their size.

Results

Uniquely sized fragments were generated in Ae. flavopictus (495 bp), Ae. albopictus (438 bp), Oc. koreicus (361 bp), Oc. togoi (283 bp), Oc. hatorii (220 bp) and Oc. japonicus (160 bp). Pairwise distance analysis showed that the difference was 35.0 ± 1.5% between Aedes spp. and Ochlerotatus spp., 17.4 ± 0.2% between Ae. albopictus and Ae. flavopictus and 11.1 ± 0.3% between Oc. koreicus and Oc. japonicus.

Conclusions

In this study, a multiplex PCR assay for six species of the Aedini tribe was developed. This assay is more accurate than morphological identification and will be useful for monitoring and controlling these vector mosquitoes.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s13071-021-04871-7.

Small-molecule endoplasmic reticulum proteostasis regulator acts as a broad-spectrum inhibitor of dengue and Zika virus infections

Flaviviruses, including dengue and Zika, are widespread human pathogens; however, no broadly active therapeutics exist to fight infection. Recently, remodeling of endoplasmic reticulum (ER) proteostasis by pharmacologic regulators, such as compound 147, was shown to correct pathologic ER imbalances associated with protein misfolding diseases. Here, we establish an additional activity of compound 147 as an effective host-centered antiviral agent against flaviviruses. Compound 147 reduces infection by attenuating the infectivity of secreted virions without causing toxicity in host cells. Compound 147 is a preferential activator of the ATF6 pathway of the ER unfolded protein response, which requires targeting of cysteine residues primarily on protein disulfide isomerases (PDIs). We find that the antiviral activity of 147 is independent of ATF6 induction but does require modification of reactive thiols on protein targets. Targeting PDIs and additional non-PDI targets using RNAi and other small-molecule inhibitors was unable to recapitulate the antiviral effects, suggesting a unique polypharmacology may mediate the activity. Importantly, 147 can impair infection of multiple strains of dengue and Zika virus, indicating that it is suitable as a broad-spectrum antiviral agent.

Modelling airport catchment areas to anticipate the spread of infectious diseases across land and air travel

Air travel is an increasingly important conduit for the worldwide spread of infectious diseases. However, methods to identify which airports an individual may use to initiate travel, or where an individual may travel to upon arrival at an airport is not well studied. This knowledge gap can be addressed by estimating airport catchment areas: the geographic extent from which the airport derives most of its patronage. While airport catchment areas can provide a simple decision-support tool to help delineate the spatial extent of infectious disease spread at a local scale, observed data for airport catchment areas are rarely made publicly available. Therefore, we evaluated a probabilistic choice behavior model, the Huff model, as a potential methodology to estimate airport catchment areas in the United States in data-limited scenarios. We explored the impact of varying input parameters to the Huff model on estimated airport catchment areas: distance decay exponent, distance cut-off, and measures of airport attractiveness. We compared Huff model catchment area patterns for Miami International Airport (MIA) and Harrisburg International Airport (MDT). We specifically compared our model output to observed data sampled for MDT to align model parameters with an established, observed catchment area. Airport catchment areas derived using the Huff model were highly sensitive to changes in model parameters. We observed that a distance decay exponent of 2 and a distance cut-off of 500 km represented the most realistic spatial extent and heterogeneity of the MIA catchment area. When these parameters were applied to MDT, the Huff model produced similar spatial patterns to the observed MDT catchment area. Finally, our evaluation of airport attractiveness showed that travel volume to the specific international destinations of interest for infectious disease importation risks (i.e., Brazil) had little impact on the predicted choice of airport when compared to all international travel. Our work is a proof of concept for use of the Huff model to estimate airport catchment areas as a generalizable decision-support tool in data-limited scenarios. While our work represents an initial examination of the Huff model as a method to approximate airport catchment areas, an essential next step is to conduct a quantitative calibration and validation of the model based on multiple airports, possibly leveraging local human mobility data such as call detail records or online social network data collected from mobile devices. Ultimately, we demonstrate how the Huff model could be potentially helpful to improve the precision of early warning systems that anticipate infectious disease spread, or to incorporate when local public health decision makers need to identify where to mobilize screening infrastructure or containment strategies at a local level.

Dengue, chikungunya and Zika in GeoSentinel surveillance of international travellers: a literature review from 1995 to 2020

INTRODUCTION

GeoSentinel is a global surveillance network of travel medicine providers seeing ill-returned travellers. Much of our knowledge on health problems and infectious encountered by international travellers has evolved as a result of GeoSentinel surveillance, providing geographic and temporal trends in morbidity among travellers while contributing to improved pre-travel advice. We set out to synthesize epidemiological information, clinical manifestations and time trends for dengue, chikungunya and Zika in travellers as captured by GeoSentinel.

METHODS

We conducted a systematic literature search in PubMed on international travellers who presented with dengue, chikungunya or Zika virus infections to GeoSentinel sites around the world from 1995 until 2020.

RESULTS

Of 107 GeoSentinel publications, 42 articles were related to dengue, chikungunya and/or Zika. The final analyses and synthesis of and results presented here are based on the findings from 27 original articles covering the three arboviral diseases.

CONCLUSIONS

Dengue is the most frequent arboviral disease encountered in travellers presenting to GeoSentinel sites, with increasing trends over the past two decades. In Southeast Asia, annual proportionate morbidity increased from 50 dengue cases per 1000 ill returned travellers in non-epidemic years to an average of 159 cases per 1000 travellers during epidemic years. The highest number of travellers with chikungunya virus infections was reported during the chikungunya outbreak in the Americas and the Caribbean in the years 2013-16. Zika was first reported by GeoSentinel already in 2012, but notifications peaked in the years 2016-17 reflecting the public health emergency in the Americas at the time.

Forecasting imported COVID-19 cases in South Korea using mobile roaming data

As the number of global coronavirus disease (COVID-19) cases increases, the number of imported cases is gradually rising. Furthermore, there is no reduction in domestic outbreaks. To assess the risks from imported COVID-19 cases in South Korea, we suggest using the daily risk score. Confirmed COVID-19 cases reported by John Hopkins University Center, roaming data collected from Korea Telecom, and the Oxford COVID-19 Government Response Tracker index were included in calculating the risk score. The risk score was highly correlated with imported COVID-19 cases after 12 days. To forecast daily imported COVID-19 cases after 12 days in South Korea, we developed prediction models using simple linear regression and autoregressive integrated moving average, including exogenous variables (ARIMAX). In the validation set, the root mean squared error of the linear regression model using the risk score was 6.2, which was lower than that of the autoregressive integrated moving average (ARIMA; 22.3) without the risk score as a reference. Correlation coefficient of ARIMAX using the risk score (0.925) was higher than that of ARIMA (0.899). A possible reason for this time lag of 12 days between imported cases and the risk score could be the delay that occurs before the effect of government policies such as closure of airports or lockdown of cities. Roaming data could help warn roaming users regarding their COVID-19 risk status and inform the national health agency of possible high-risk areas for domestic outbreaks.

Social Distancing Metrics and Estimates of SARS-CoV-2 Transmission Rates: Associations Between Mobile Telephone Data Tracking and R

BACKGROUND

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease 2019 (COVID-19). In the absence of robust preventive or curative strategies, the implementation of social distancing has been a key component of limiting the spread of the virus.

METHODS

Daily estimates of R(t) were calculated and compared with measures of social distancing made publicly available by Unacast. Daily generated variables representing an overall grade for distancing, changes in distances traveled, encounters between individuals, and daily visitation, were modeled as predictors of average R value for the following week, using linear regression techniques for 8 counties surrounding the city of Syracuse, New York. Supplementary analysis examined differences between counties.

RESULTS

A total of 225 observations were available across the 8 counties, with 166 meeting the mean R(t) < 3 outlier criterion for the regression models. Measurements for distance (β = 1.002, P = .012), visitation (β = .887, P = .017), and encounters (β = 1.070, P = .001) were each predictors of R(t) for the following week. Mean R(t) drops when overall distancing grades move from D+ to C-. These trends were significant (P < .001 for each).

CONCLUSIONS

Social distancing, when assessed by free and publicly available measures such as those shared by Unacast, has an impact on viral transmission rates. The scorecard may also be useful for public messaging about social distance, in hospital planning, and in the interpretation of epidemiological models.

Breeding Habitat Preferences of Major Culicoides Species (Diptera: Ceratopogonidae) in Germany

Biting midges of the genus Culicoides (Diptera, Ceratopognidae) are demonstrably or putatively involved in the transmission of both bluetongue (BTV) and Schmallenberg viruses (SBV) in Central Europe. Although these insects are ubiquitous in Europe, relatively little is known about their requirements in terms of breeding habitats and substrates. Culicoides species composition and relative abundance in potential breeding habitats were therefore studied at various locations in Northeastern Germany and one location in Western Germany by emergence trap collections. Forty-three potential breeding sites were analyzed in ten landscape structures, with 28,091 adult biting midges emerging from them. Among these, 2116 specimens belonged to the genus Culicoides. Species of the culicoid subgenus Avaritia were most abundant (70.6% of all specimens) and widespread (91.6% of all sites), while the subgenus Culicoides accounted for 15.6% of the specimens registered but emerged from 70.8% of all sites sampled. Culicoides species of other subgenera were collected in 75.0% of all studied sites, with a relative abundance of 8.7%. The results indicate that various types of dung, but probably also some landscape habitats, offer suitable substrates for the development of potential Culicoides vector species. Adaptations in dung management on farms and landscape design and use might therefore be appropriate approaches to reduce the risk of BTV or SBV transmission.

The Relationship between the Migrant Population's Migration Network and the Risk of COVID-19 Transmission in China-Empirical Analysis and Prediction in Prefecture-Level Cities

The outbreak of COVID-19 in China has attracted wide attention from all over the world. The impact of COVID-19 has been significant, raising concerns regarding public health risks in China and worldwide. Migration may be the primary reason for the long-distance transmission of the disease. In this study, the following analyses were performed. (1) Using the data from the China migrant population survey in 2017 (Sample size = 432,907), a matrix of the residence-birthplace (R-B matrix) of migrant populations is constructed. The matrix was used to analyze the confirmed cases of COVID-19 at Prefecture-level Cities from February 1-15, 2020 after the outbreak in Wuhan, by calculating the probability of influx or outflow migration. We obtain a satisfactory regression analysis result (R2 = 0.826-0.887, N = 330). (2) We use this R-B matrix to simulate an outbreak scenario in 22 immigrant cities in China, and propose risk prevention measures after the outbreak. If similar scenarios occur in the cities of Wenzhou, Guangzhou, Dongguan, or Shenzhen, the disease transmission will be wider. (3) We also use a matrix to determine that cities in Henan province, Anhui province, and Municipalities (such as Beijing, Shanghai, Guangzhou, Shenzhen, Chongqing) in China will have a high risk level of disease carriers after a similar emerging epidemic outbreak scenario due to a high influx or outflow of migrant populations.

Assessing spread risk of Wuhan novel coronavirus within and beyond China, January-April 2020: a travel network-based modelling study

Background

A novel coronavirus (2019-nCoV) emerged in Wuhan City, China, at the end of 2019 and has caused an outbreak of human-to-human transmission with a Public Health Emergency of International Concern declared by the World Health Organization on January 30, 2020.

Aim

We aimed to estimate the potential risk and geographic range of Wuhan novel coronavirus (2019-nCoV) spread within and beyond China from January through to April, 2020.

Methods

A series of domestic and international travel network-based connectivity and risk analyses were performed, by using de-identified and aggregated mobile phone data, air passenger itinerary data, and case reports.

Results

The cordon sanitaire of Wuhan is likely to have occurred during the latter stages of peak population numbers leaving the city before Lunar New Year (LNY), with travellers departing into neighbouring cities and other megacities in China. We estimated that 59,912 air passengers, of which 834 (95% UI: 478 - 1349) had 2019-nCoV infection, travelled from Wuhan to 382 cities outside of mainland China during the two weeks prior to Wuhan's lockdown. The majority of these cities were in Asia, but major hubs in Europe, the US and Australia were also prominent, with strong correlation seen between predicted importation risks and reported cases. Because significant spread has already occurred, a large number of airline travellers (3.3 million under the scenario of 75% travel reduction from normal volumes) may be required to be screened at origin high-risk cities in China and destinations across the globe for the following three months of February to April, 2020 to effectively limit spread beyond its current extent.

Conclusion

Further spread of 2019-nCoV within China and international exportation is likely to occur. All countries, especially vulnerable regions, should be prepared for efforts to contain the 2019-nCoV infection.

Rift Valley Fever - epidemiological update and risk of introduction into Europe

Rift Valley fever (RVF) is a vector-borne disease transmitted by a broad spectrum of mosquito species, especially Aedes and Culex genus, to animals (domestic and wild ruminants and camels) and humans. Rift Valley fever is endemic in sub-Saharan Africa and in the Arabian Peninsula, with periodic epidemics characterised by 5-15 years of inter-epizootic periods. In the last two decades, RVF was notified in new African regions (e.g. Sahel), RVF epidemics occurred more frequently and low-level enzootic virus circulation has been demonstrated in livestock in various areas. Recent outbreaks in a French overseas department and some seropositive cases detected in Turkey, Tunisia and Libya raised the attention of the EU for a possible incursion into neighbouring countries. The movement of live animals is the most important pathway for RVF spread from the African endemic areas to North Africa and the Middle East. The movement of infected animals and infected vectors when shipped by flights, containers or road transport is considered as other plausible pathways of introduction into Europe. The overall risk of introduction of RVF into EU through the movement of infected animals is very low in all the EU regions and in all MSs (less than one epidemic every 500 years), given the strict EU animal import policy. The same level of risk of introduction in all the EU regions was estimated also considering the movement of infected vectors, with the highest level for Belgium, Greece, Malta, the Netherlands (one epidemic every 228-700 years), mainly linked to the number of connections by air and sea transports with African RVF infected countries. Although the EU territory does not seem to be directly exposed to an imminent risk of RVFV introduction, the risk of further spread into countries neighbouring the EU and the risks of possible introduction of infected vectors, suggest that EU authorities need to strengthen their surveillance and response capacities, as well as the collaboration with North African and Middle Eastern countries.

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.

Phylogeography and invasion history of Aedes aegypti, the Dengue and Zika mosquito vector in Cape Verde islands (West Africa)

Aedes-borne arboviruses have spread globally with outbreaks of vast impact on human populations and health systems. The West African archipelago of Cape Verde had its first outbreak of Dengue in 2009, at the time the largest recorded in Africa, and was one of the few African countries affected by the Zika virus epidemic. Aedes aegypti was the mosquito vector involved in both outbreaks. We performed a phylogeographic and population genetics study of A. aegypti in Cape Verde in order to infer the geographic origin and evolutionary history of this mosquito. These results are discussed with respect to the implications for vector control and prevention of future outbreaks. Mosquitoes captured before and after the Dengue outbreak on the islands of Santiago, Brava, and Fogo were analyzed with two mitochondrial genes COI and ND4, 14 microsatellite loci and five kdr mutations. Genetic variability was comparable to other African populations. Our results suggest that A. aegypti invaded Cape Verde at the beginning of the Holocene from West Africa. Given the historic importance of Cape Verde in the transatlantic trade of the 16th-17th centuries, a possible contribution to the genetic pool of the founding populations in the New World cannot be fully discarded. However, contemporary gene flow with the Americas is likely to be infrequent. No kdr mutations associated with pyrethroid resistance were detected. The implications for vector control and prevention of future outbreaks are discussed.

Predicting Risk of Imported Disease with Demographics: Geospatial Analysis of Imported Malaria in Minnesota, 2010-2014

Although immigrants who visit friends and relatives (VFRs) account for most of the travel-acquired malaria cases in the United States, there is limited evidence on community-level risk factors and best practices for prevention appropriate for various VFR groups. Using 2010–2014 malaria case reports, sociodemographic census data, and health services data, we explored and mapped community-level characteristics to understand who is at risk and where imported malaria infections occur in Minnesota. We examined associations with malaria incidence using Poisson and negative binomial regression. Overall, mean incidence was 0.4 cases per 1,000 sub-Saharan African (SSA)–born in communities reporting malaria, with cases concentrated in two areas of Minneapolis–St. Paul. We found moderate and positive associations between imported malaria and counts of SSA- and Asian-born populations, respectively. Our findings may inform future studies to understand the knowledge, attitudes, and practices of VFR travelers and facilitate and focus intervention strategies to reduce imported malaria in the United States.

Temperature impacts on dengue emergence in the United States: Investigating the role of seasonality and climate change

Tropical mosquito-borne viruses have been expanding into more temperate regions in recent decades. This is partly due to the coupled effects of temperature on mosquito life history traits and viral infection dynamics and warming surface temperatures, resulting in more suitable conditions for vectors and virus transmission. In this study, we use a deterministic ordinary differential equations model to investigate how seasonal and diurnal temperature fluctuations affect the potential for dengue transmission in six U.S. cities. We specifically consider temperature-dependent mosquito larval development, adult mosquito mortality, and the extrinsic incubation period of the virus. We show that the ability of introductions to lead to outbreaks depends upon the relationship between a city's temperature profile and the time of year at which the initial case is introduced. We also investigate how the potential for outbreaks changes with predicted future increases in mean temperatures due to climate change. We find that climate change will likely lead to increases in suitability for dengue transmission and will increase the periods of the year in which introductions may lead to outbreaks, particularly in cities that typically have mild winters and warm summers, such as New Orleans, Louisiana, and El Paso, Texas. We discuss our results in the context of temperature heterogeneity within and across cities and how these differences may impact the potential for dengue emergence given present day and predicted future temperatures.

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.

A Note on the Risk of Infections Invading Unaffected Regions

We present two probabilistic models to estimate the risk of introducing infectious diseases into previously unaffected countries/regions by infective travellers. We analyse two distinct situations, one dealing with a directly transmitted infection (measles in Italy in 2017) and one dealing with a vector-borne infection (Zika virus in Rio de Janeiro, which may happen in the future). To calculate the risk in the first scenario, we used a simple, nonhomogeneous birth process. The second model proposed in this paper provides a way to calculate the probability that local mosquitoes become infected by the arrival of a single infective traveller during his/her infectiousness period. The result of the risk of measles invasion of Italy was of 93% and the result of the risk of Zika virus invasion of Rio de Janeiro was of 22%.

The extensive networks of frequent population mobility in the Samoan Islands and their implications for infectious disease transmission

Population mobility has been demonstrated to contribute to the persistent transmission and global diffusion of epidemics. In the Pacific Islands, population mobility is particularly important for emerging infectious diseases, disease elimination programs, and diseases spread by close contact. The extent of population mobility between American Samoa villages, Samoa districts and other countries was investigated based on travel data collected during community surveys in American Samoa in 2010 and 2014. Within American Samoa, workers commuted daily across the whole of the main island of Tutuila, with work hubs drawing from villages across the island. Of the 670 adult workers surveyed, 37% had traveled overseas in the past year, with 68% of trips to Samoa. Of children aged 8–13 years (n = 337), 57% had traveled overseas, with 55% of trips to Samoa. An extensive network of connections between American Samoa villages and Samoa districts was demonstrated, with most trips lasting one week to one month. Our study showed that populations in the Samoan islands are highly mobile, and quantified the extent and destinations of their travels. Our findings offer insight into the impact of population mobility on the transmission of infectious diseases and data to refine existing models of disease transmission in the Pacific islands.

The spread of mosquito-borne viruses in modern times: A spatio-temporal analysis of dengue and chikungunya

Since the 1970s, mosquito-borne pathogens have spread to previously disease-free areas, as well as causing increased illness in endemic areas. In particular, dengue and chikungunya viruses, transmitted primarily by Aedes aegypti and secondarily by Aedes albopictus mosquitoes, represent a threat for up to a third of the world population, and are a growing public health concern. In this study, we assess the spatial and temporal factors related to the occurrences of historic dengue and chikungunya outbreaks in 76 nations focused geographically on the Indian Ocean, with outbreak data from 1959 to 2009. First, we describe the historical spatial and temporal patterns of outbreaks of dengue and chikungunya in the focal nations. Second, we use a boosted regression tree approach to assess the statistical relationships of nations' concurrent outbreak occurrences and annual occurrences with their spatial proximity to prior infections and climatic and socio-economic characteristics. We demonstrate that higher population density and shorter distances among nations with outbreaks are the dominant factors that characterize both dengue and chikungunya outbreaks. In conclusion, our analysis provides crucial insights, which can be applied to improve nations' surveillance and preparedness for future vector-borne disease epidemics.

Mapping road network communities for guiding disease surveillance and control strategies

Human mobility is increasing in its volume, speed and reach, leading to the movement and introduction of pathogens through infected travelers. An understanding of how areas are connected, the strength of these connections and how this translates into disease spread is valuable for planning surveillance and designing control and elimination strategies. While analyses have been undertaken to identify and map connectivity in global air, shipping and migration networks, such analyses have yet to be undertaken on the road networks that carry the vast majority of travellers in low and middle income settings. Here we present methods for identifying road connectivity communities, as well as mapping bridge areas between communities and key linkage routes. We apply these to Africa, and show how many highly-connected communities straddle national borders and when integrating malaria prevalence and population data as an example, the communities change, highlighting regions most strongly connected to areas of high burden. The approaches and results presented provide a flexible tool for supporting the design of disease surveillance and control strategies through mapping areas of high connectivity that form coherent units of intervention and key link routes between communities for targeting surveillance.

Mosquitoes on a plane: Disinsection will not stop the spread of vector-borne pathogens, a simulation study

Mosquito-borne diseases are increasingly being recognized as global threats, with increased air travel accelerating their occurrence in travelers and their spread to new locations. Since the early days of aviation, concern over the possible transportation of infected mosquitoes has led to recommendations to disinsect aircraft. Despite rare reports of mosquitoes, most likely transported on aircraft, infecting people far from endemics areas, it is unclear how important the role of incidentally transported mosquitoes is compared to the role of traveling humans. We used data for Plasmodium falciparum and dengue viruses to estimate the probability of introduction of these pathogens by mosquitoes and by humans via aircraft under ideal conditions. The probability of introduction of either pathogen by mosquitoes is low due to few mosquitoes being found on aircraft, low infection prevalence among mosquitoes, and high mortality. Even without disinsection, introduction via infected human travelers was far more likely than introduction by infected mosquitoes; more than 1000 times more likely for P. falciparum and more than 200 times more likely for dengue viruses. Even in the absence of disinsection and under the most favorable conditions, introduction of mosquito-borne pathogens via air travel is far more likely to occur as a result of an infected human travelling rather than the incidental transportation of infected mosquitoes. Thus, while disinsection may serve a role in preventing the spread of vector species and other invasive insects, it is unlikely to impact the spread of mosquito-borne pathogens.

Importation of yellow fever into China: assessing travel patterns

Rapid increase in trade and a growing air passenger market encourages high travel volume between the regions associated with increasing risks of such importations including China. Eleven Chinese workers infected during the 2016 yellow fever (YF) outbreak in Angola imported YF into China highlighting the potential for spread into Asia. Using outbound and inbound travel data, we assessed travel patterns from and to YF endemic countries in relation to China. Among YF endemic countries, Angola has the second highest number of travellers into China and also receives the second highest number of Chinese visitors. We estimated that China needs around half a million YF vaccine doses to cover their population travelling to YF endemic countries. The recent importation cases into China also unmasked the low YF vaccination coverage among Chinese travellers and workers to Angola, indicating the need to ensure better adherence to the International Health Regulations.

Modelling the effects of global climate change on Chikungunya transmission in the 21st century

The arrival and rapid spread of the mosquito-borne viral disease Chikungunya across the Americas is one of the most significant public health developments of recent years, preceding and mirroring the subsequent spread of Zika. Globalization in trade and travel can lead to the importation of these viruses, but climatic conditions strongly affect the efficiency of transmission in local settings. In order to direct preparedness for future outbreaks, it is necessary to anticipate global regions that could become suitable for Chikungunya transmission. Here, we present global correlative niche models for autochthonous Chikungunya transmission. These models were used as the basis for projections under the representative concentration pathway (RCP) 4.5 and 8.5 climate change scenarios. In a further step, hazard maps, which account for population densities, were produced. The baseline models successfully delineate current areas of active Chikungunya transmission. Projections under the RCP 4.5 and 8.5 scenarios suggest the likelihood of expansion of transmission-suitable areas in many parts of the world, including China, sub-Saharan Africa, South America, the United States and continental Europe. The models presented here can be used to inform public health preparedness planning in a highly interconnected world.

Essential oils and their components as an alternative in the control of mosquito vectors of disease

More than half of the human population is exposed to mosquito-borne infections. Climate change and the emergence of strains resistant to traditionally used insecticides have motivated the search of new agents for mosquito population control. Essential oils have been effective repellents and larvicidal agents.The aim of this work was to review research studies conducted in recent years on the larvicidal activity of essential oils and their components against Aedes, Anopheles and Culex mosquitoes, as well as the latest reports about their possible mechanism of action.

Quantifying the potential pathways and locations of Rift Valley fever virus entry into the United States

The global invasion of West Nile virus, chikungunya virus and Zika virus in the past two decades suggests an increasing rate of mosquito-borne virus (arbovirus) dispersal. Rift Valley fever virus (RVFV) is an arbovirus identified as a high-consequence threat to the United States (USA) because of the severe economic and health consequences associated with disease. Numerous studies demonstrate that the USA is receptive to RVFV transmission based on the widespread presence of competent mosquito species and vertebrate species. In this study, the potential pathways and locations of RVFV entry into the USA were quantitatively estimated to support a priori surveillance and RVFV prevention strategies. International movement data, ecological data and epidemiological data were combined to estimate the number of RVFV-infected mosquitoes entering the USA. Results suggest infected humans travelling by plane pose the highest risk of importing RVFV into the USA, followed by the unintentional transport of infected adult mosquitoes by ship and airplane. Furthermore, New York, New York, Washington DC, Atlanta, Georgia, and Houston, Texas, are implicated as the most likely regions of RVFV entry. Results are interpreted and discussed to support the prediction and mitigation of RVFV spread to the USA.

Virus evolution and transmission in an ever more connected world

The frequency and global impact of infectious disease outbreaks, particularly those caused by emerging viruses, demonstrate the need for a better understanding of how spatial ecology and pathogen evolution jointly shape epidemic dynamics. Advances in computational techniques and the increasing availability of genetic and geospatial data are helping to address this problem, particularly when both information sources are combined. Here, we review research at the intersection of evolutionary biology, human geography and epidemiology that is working towards an integrated view of spatial incidence, host mobility and viral genetic diversity. We first discuss how empirical studies have combined viral spatial and genetic data, focusing particularly on the contribution of evolutionary analyses to epidemiology and disease control. Second, we explore the interplay between virus evolution and global dispersal in more depth for two pathogens: human influenza A virus and chikungunya virus. We discuss the opportunities for future research arising from new analyses of human transportation and trade networks, as well as the associated challenges in accessing and sharing relevant spatial and genetic data.

The geography of imported malaria to non-endemic countries: a meta-analysis of nationally reported statistics

BACKGROUND

Malaria remains a problem for many countries classified as malaria free through cases imported from endemic regions. Imported cases to non-endemic countries often result in delays in diagnosis, are expensive to treat, and can sometimes cause secondary local transmission. The movement of malaria in endemic countries has also contributed to the spread of drug resistance and threatens long-term eradication goals. Here we focused on quantifying the international movements of malaria to improve our understanding of these phenomena and facilitate the design of mitigation strategies.

METHODS

In this meta-analysis, we studied the database of publicly available nationally reported statistics on imported malaria in the past 10 years, covering more than 50 000 individual cases. We obtained data from 40 non-endemic countries and recorded the geographical variations.

FINDINGS

Infection movements were strongly skewed towards a small number of high-traffic routes between 2005 and 2015, with the west Africa region accounting for 56% (13 947/24 941) of all imported cases to non-endemic countries with a reported travel destination, and France and the UK receiving the highest number of cases, with more than 4000 reported cases per year on average. Countries strongly linked by movements of imported cases are grouped by historical, language, and travel ties. There is strong spatial clustering of plasmodium species types.

INTERPRETATION

The architecture of the air network, historical ties, demographics of travellers, and malaria endemicity contribute to highly heterogeneous patterns of numbers, routes, and species compositions of parasites transported. With global malaria eradication on the international agenda, malaria control altering local transmission, and the threat of drug resistance, understanding these patterns and their drivers is increasing in importance.

FUNDING

Bill & Melinda Gates Foundation, National Institutes of Health, UK Medical Research Council, UK Department for International Development, Wellcome Trust.

Plasmodium falciparum malaria importation from Africa to China and its mortality: an analysis of driving factors

Plasmodium falciparum malaria importation from Africa to China is rising with increasing Chinese overseas investment and international travel. Identifying networks and drivers of this phenomenon as well as the contributors to high case-fatality rate is a growing public health concern to enable efficient response. From 2011-2015, 8653 P. falciparum cases leading to 98 deaths (11.3 per 1000 cases) were imported from 41 sub-Saharan countries into China, with most cases (91.3%) occurring in labour-related Chinese travellers. Four strongly connected groupings of origin African countries with destination Chinese provinces were identified, and the number of imported cases was significantly associated with the volume of air passengers to China (P = 0.006), parasite prevalence in Africa (P < 0.001), and the amount of official development assistance from China (P < 0.001) with investment in resource extraction having the strongest relationship with parasite importation. Risk factors for deaths from imported cases were related to the capacity of malaria diagnosis and diverse socioeconomic factors. The spatial heterogeneity uncovered, principal drivers explored, and risk factors for mortality found in the rising rates of P. falciparum malaria importation to China can serve to refine malaria elimination strategies and the management of cases, and high risk groups and regions should be targeted.

Human to human transmission of arthropod-borne pathogens

Human-to-human (H2H) transmitted arthropod-borne pathogens are a growing burden worldwide, with malaria and dengue being the most common mosquito-borne H2H transmitted diseases. The ability of vectors to get infected by humans during a blood meal to further propel an epidemic depends on complex interactions between pathogens, vectors and humans, in which human interventions and demographic and environmental conditions play a significant role. Herein, we discuss the distal and proximal drivers affecting H2H vector-borne pathogen transmission and identify knowledge gaps and future perspectives.

Analysis of Seasonal Risk for Importation of the Mediterranean Fruit Fly, Ceratitis capitata (Diptera: Tephritidae), via Air Passenger Traffic Arriving in Florida and California

The Mediterranean fruit fly, Ceratitis capitata (Wiedemann), is one of the most economically damaging pests in the world and has repeatedly invaded two major agricultural states in the United States, Florida and California, each time requiring costly eradication. The Mediterranean fruit fly gains entry primarily in infested fruit carried by airline passengers and, since Florida and California each receive about 13 million international passengers annually, the risk of Mediterranean fruit fly entering the United States is potentially very high. The risk of passengers bringing the pest into Florida or California from Mediterranean fruit fly-infested countries was determined with two novel models, one estimated seasonal variation in airline passenger number and the other defined the seasonal and spatial variability in Mediterranean fruit fly abundance. These models elucidated relationships among the risk factors for Mediterranean fruit fly introduction, such as amount of passenger traffic, routes traveled, season of travel, abundance of Mediterranean fruit fly in countries where flights departed, and risk of the pest arriving at destination airports. The risk of Mediterranean fruit fly being introduced into Florida was greatest from Colombia, Brazil, Panama, Venezuela, Argentina, and Ecuador during January-August, whereas primarily the risk to California was from Brazil, Panama, Colombia, and Italy in May-August. About three times more Mediterranean fruit flies were intercepted in passenger baggage at airports in Florida than California, although the data were compromised by a lack of systematic sampling and other limitations. Nevertheless, this study achieved the goal of analyzing available data on seasonal passenger flow and Mediterranean fruit fly population levels to determine when surveillance should be intensified at key airports in Florida and California.

Modeling Mosquito-Borne Disease Spread in U.S. Urbanized Areas: The Case of Dengue in Miami

Expansion of mosquito-borne pathogens into more temperate regions of the world necessitates tools such as mathematical models for understanding the factors that contribute to the introduction and emergence of a disease in populations naïve to the disease. Often, these models are not developed and analyzed until after a pathogen is detected in a population. In this study, we develop a spatially explicit stochastic model parameterized with publicly available U.S. Census data for studying the potential for disease spread in Urbanized Areas of the United States. To illustrate the utility of the model, we specifically study the potential for introductions of dengue to lead to autochthonous transmission and outbreaks in a population representative of the Miami Urbanized Area, where introductions of dengue have occurred frequently in recent years. We describe seasonal fluctuations in mosquito populations by fitting a population model to trap data provided by the Miami-Dade Mosquito Control Division. We show that the timing and location of introduced cases could play an important role in determining both the probability that local transmission occurs as well as the total number of cases throughout the entire region following introduction. We show that at low rates of clinical presentation, small outbreaks of dengue could go completely undetected during a season, which may confound mitigation efforts that rely upon detection. We discuss the sensitivity of the model to several critical parameter values that are currently poorly characterized and motivate the collection of additional data to strengthen the predictive power of this and similar models. Finally, we emphasize the utility of the general structure of this model in studying mosquito-borne diseases such as chikungunya and Zika virus in other regions.

Estimated global exportations of Zika virus infections via travellers from Brazil from 2014 to 2015

The ongoing Zika pandemic in Latin America illustrates a potential source for further globalized spread. Here, we assessed global travel-related Zika virus exportations from Brazil during the initial year of the epidemic. Similar to subsequent national notifications, we estimated 584-1786 exported Zika cases from Brazil occurred September 2014-August 2015.

Estimated Zika virus importations to Europe by travellers from Brazil

BACKGROUND

Given the interconnectivity of Brazil with the rest of the world, Zika virus (ZIKV) infections have the potential to spread rapidly around the world via viremic travellers. The extent of spread depends on the travel volume and the endemicity in the exporting country. In the absence of reliable surveillance data, we did mathematical modelling to estimate the number of importations of ZIKV from Brazil into Europe.

DESIGN

We applied a previously developed mathematical model on importations of dengue to estimate the number of ZIKV importations into Europe, based on the travel volume, the probability of being infected at the time of travel, the population size of Brazil, and the estimated incidence of ZIKV infections.

RESULTS

Our model estimated between 508 and 1,778 imported infections into Europe in 2016, of which we would expect between 116 and 355 symptomatic Zika infections; with the highest number of importations being into France, Portugal and Italy.

CONCLUSIONS

Our model identified high-risk countries in Europe. Such data can assist policymakers and public health professionals in estimating the extent of importations in order to prepare for the scale up of laboratory diagnostic assays and estimate the occurrence of Guillain-Barré Syndrome, potential sexual transmission, and infants with congenital ZIKV syndrome.

The Multifactorial Background of Emerging Viral Infections with Neurological Manifestation

The events of the past year have highlighted the continuing importance of emerging virus infections on the diagnosis and treatment of neurological disease. This review focusses on clarifying the effects of the multiple overlapping factors that impact emergence, including viral richness, transmission opportunity, and establishment. Case studies of the West Nile, chikungunya, and Zika viruses are utilised to illustrate the dramatic effects of expansion in the range and geographical distribution of emerging infectious disease, the acquisition of new virus vectors, and of increasing human anthropogenic factors such as global transport, climate change, and mosquito abatement programmes on the regional spread and clinical consequences of emerging infectious disease.

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.

International Air Travel to Ohio, USA, and the Impact on Malaria, Influenza, and Hepatitis A

The State of Ohio led the United States in measles in 2014, ostensibly related to international air travel (IAT), and ranked lower than 43 other states in infectious disease outbreak preparedness. We conducted a retrospective cohort study using surveillance data of the total Ohio population of 11 million from 2010 through 2014 with a nested case control of air travelers to determine the risk of malaria, seasonal influenza hospitalizations (IH), and hepatitis A (HA) disease related to international travel and to estimate the association with domestic enplanement. IAT appeared protective for HA and IH with a risk of 0.031 (.02-.04) but for malaria was 2.7 (2.07-3.62). Enplanement increased the risk for nonendemic M 3.5 (2.5-4.9) and for HA and IH 1.39 (1.34-1.44). IAT's ratio of relative risk (RRR) of malaria to HA and IH was 87.1 (55.8-136) greater than 219 times versus domestic enplanement which was protective for malaria at 0.397 (0.282-0.559). Malaria is correlated with IAT with cases increasing by 6.9 for every 10,000 passports issued.

Preparedness for threat of chikungunya in the pacific

Chikungunya virus (CHIKV) caused significant outbreaks of illness during 2005–2007 in the Indian Ocean region. Chikungunya outbreaks have also occurred in the Pacific region, including in Papua New Guinea in 2012; New Caledonia in April 2013; and Yap State, Federated States of Micronesia, in August 2013. CHIKV is a threat in the Pacific, and the risk for further spread is high, given several similarities between the Pacific and Indian Ocean chikungunya outbreaks. Island health care systems have difficulties coping with high caseloads, which highlights the need for early multidisciplinary preparedness. The Pacific Public Health Surveillance Network has developed several strategies focusing on surveillance, case management, vector control, laboratory confirmation, and communication. The management of this CHIKV threat will likely have broad implications for global public health.

Modeling Importations and Exportations of Infectious Diseases via Travelers

This paper is an attempt to estimate the risk of infection importation and exportation by travelers. Two countries are considered: one disease-free country and one visited or source country with a running endemic or epidemic infectious disease. Two models are considered. In the first model (disease importation), susceptible individuals travel from their disease-free home country to the endemic country and come back after some weeks. The risk of infection spreading in their home country is then estimated supposing the visitors are submitted to the same force of infection as the local population but do not contribute to it. In the second model (disease exportation), it is calculated the probability that an individual from the endemic (or epidemic) country travels to a disease-free country in the condition of latent infected and eventually introduces the infection there. The input of both models is the force of infection at the visited/source country, assumed known. The models are deterministic, but a preliminary stochastic formulation is presented as an appendix. The models are exemplified with two distinct real situations: the risk of dengue importation from Thailand to Europe and the risk of Ebola exportation from Liberia to the USA.

Viral Epidemiology

The science of epidemiology has been developed over the last 200 years, using traditional methods to describe the distribution of diseases by person, place, and time. However, in the last several decades, a new set of technologies has become available, based on the methods of computer sciences, systems biology, and the extraordinary powers of the Internet. Technological and analytical advances can enhance traditional epidemiological methods to study the emergence, epidemiology, and transmission dynamics of viruses and associated diseases. Social media are increasingly used to detect the emergence and geographic spread of viral disease outbreaks. Large-scale population movement can be estimated using satellite imagery and mobile phone use, and fine-scale population movement can be tracked using global positioning system loggers, allowing estimation of transmission pathways and contact patterns at different spatial scales. Advances in genomic sequencing and bioinformatics permit more accurate determination of viral evolution and the construction of transmission networks, also at different spatial and temporal scales. Phylodynamics links evolutionary and epidemiological processes to better understand viral transmission patterns. More complex and realistic mathematical models of virus transmission within human and animal populations, including detailed agent-based models, are increasingly used to predict transmission patterns and the impact of control interventions such as vaccination and quarantine. In this chapter, we will briefly review traditional epidemiological methods and then describe the new technologies with some examples of their application.

Modeling monthly flows of global air travel passengers: An open-access data resource

The global flow of air travel passengers varies over time and space, but analyses of these dynamics and their integration into applications in the fields of economics, epidemiology and migration, for example, have been constrained by a lack of data, given that air passenger flow data are often difficult and expensive to obtain. Here, these dynamics are modeled at a monthly scale to provide an open-access spatio-temporally resolved data source for research purposes (www.vbd-air.com/data). By refining an annual-scale model of Huang et al. (2013), we developed a set of Poisson regression models to predict monthly passenger volumes between directly connected airports during 2010. The models not only performed well in the United States with an overall accuracy of 93%, but also showed a reasonable confidence in estimating air passenger volumes in other regions of the world. Using the model outcomes, this research studied the spatio-temporal dynamics in the world airline network (WAN) that previous analyses were unable to capture. Findings on the monthly variation of WAN offer new knowledge for dynamic planning and strategy design to address global issues, such as disease pandemics and climate change.

Geo-Located Tweets. Enhancing Mobility Maps and Capturing Cross-Border Movement

Capturing human movement patterns across political borders is difficult and this difficulty highlights the need to investigate alternative data streams. With the advent of smart phones and the ability to attach accurate coordinates to Twitter messages, users leave a geographic digital footprint of their movement when posting tweets. In this study we analyzed 10 months of geo-located tweets for Kenya and were able to capture movement of people at different temporal (daily to periodic) and spatial (local, national to international) scales. We were also able to capture both long and short distances travelled, highlighting regional connections and cross-border movement between Kenya and the surrounding countries. The findings from this study has broad implications for studying movement patterns and mapping inter/intra-region movement dynamics.